Advances in Psychology Research: Volume 96 9781624172519, 1624172512

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ADVANCES IN PSYCHOLOGY RESEARCH

ADVANCES IN PSYCHOLOGY RESEARCH VOLUME 96

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ADVANCES IN PSYCHOLOGY RESEARCH

ADVANCES IN PSYCHOLOGY RESEARCH VOLUME 96

ALEXANDRA M. COLUMBUS EDITOR

New York

Copyright © 2013 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book.

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ISSN: 1532-723X

Published by Nova Science Publishers, Inc. † New York

CONTENTS Preface Chapter 1

Chapter 2

vii Investigating the Hindsight Bias at Canadian University Football Games Stuart J. McKelvie

1

N-Methyl-D-Aspartate Enhancing Agents: A New Class of Novel Antipsychotic Drugs Huey-Jen Chang, Hsien-Yuan Lane, and Guochuan E. Tsai

97

Chapter 3

Humanistic Psychology and the Mental Health Worker Elliot Benjamin

Chapter 4

Inefficient Neural Control of Attention in Adolescent Chronic Cannabis Abuse Yalchin Abdullaev

Chapter 5

Behavioral Choice Paradigms and their Mathematical Representation Sigal Kaplan

Chapter 6

Perversion, from the Act to the Structure, a New Therapeutic Challenge A. Hachet and J. L. Pedinielli

145

169 199

225

Chapter 7

OCD Critical Variables in CBT OCD Adam Reid

245

Chapter 8

Youth Cyber-Bullying: Risks, Intervention and Prevention Tali Heiman and Dorit Olenik Shemesh

269

Chapter 9

Stigma and Substance Use Disorders: Research, Implications, and Potential Solutions Lindsay A. Phillips

Chapter 10 Index

Transworld Egoism, Empathy and the Golden Rule H. E. Baber

287 297 303

PREFACE This continuing series presents original research results on the leading edge of psychology. Each article has been carefully selected in an attempt to present substantial results across a broad spectrum. This book reviews research on cognitive illusions and its impact on reasoning, judgment and decision-making; glutamatergic neurotransmission through N-methyl-D-Aspartate (NMDA) receptor and its role in the pathophsyiology of schizophrenia; humanistic psychology and the mental health worker; inefficient neural control of attention in adolescent chronic cannabis abuse; behavioral choice paradigms and their mathematical representation; epistemological and clinical conceptions of perversion; critical variables in cognitive-behavioral therapy for pediatric and adult obsessive-compulsive disorders; cyber-bullying risk and protective factors; stigma and substance use disorders; and a transworld eogism and empathy study. Chapter 1 – A total of 776 participants in eight studies made judgments about the outcome of Canadian university football games. During the two days before the games, participants estimated the number of points for each team. During the two days after the games, participants were informed of the score for each team, then either estimated what they would have predicted if that had been asked before the games (Studies 1 to 6) or recalled what they had predicted (Studies 7 and 8). In the vast majority of cases, there was no evidence of a hindsight effect: most post-game estimates were not significantly closer to the actual score than pre-game estimates. However, when changes in the estimates over time were converted to standardized effect sizes (d), the mean effect size was significant, showing a very small hindsight effect (d = 0.14, 0.17). When the game outcomes were classified as surprising or not and then into different degrees of surprise, and when the postgame judgments were classified as showing hindsight or not, no significant relationship was found between surprise and hindsight. However, in terms of effect size, the hindsight effect was greater for surprising outcomes than for nonsurprising outcomes, as predicted by Pezzo’s (2003) sense-making model of surprise. The hindsight effect did not differ between women and men and was not more likely to occur for people who were higher than lower in selfinvolvement (interest). On the other hand, there was a small amount of evidence that it was more likely with people who were less knowledgeable about Canadian university football. Strengths and weaknesses of the present research are discussed and suggestions are offered for future research. Chapter 2 – Glutamatergic neurotransmission, particularly through the N-methyl-Daspartate (NMDA) receptor, has drawn attention for its emerging role in the pathophysiology

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of schizophrenia. This chapter reviews the symptom domains of schizophrenia and their importance in predicting the long-term outcomes of this illness, the evolution of the concept in the pathophysiology of schizophrenia from the dopaminergic, serotonergic to glutamatergic hypothesis through decades, the physiology of each type of glutamate receptors, the evidence of NMDA receptor dysfunction in schizophrenia based on various clinical models and genetic studies. The clinical efficacy and safety of currently available NMDA-enhancing agents, either as adjuncts to typical/atypical antipsychotics or as monotherapy, in schizophrenic patients, particularly those with refractory negative and cognitive symptoms are under studies and revealing encouraging results. Novel antipsychotics acting to correct this dysfunction are on the way for development. Chapter 3 – This article discusses the precarious relationship of humanistic psychology to the mental health worker in our current managed care, empirically based, behaviorally focused, excessively medication-oriented mental health system. Some of the challenges, frustrations, and potential successes of bringing real and nurturing human relationships in the context of humanistic psychology into the day-to-day involvements with clients for the mental health worker are described. Some of the particular ethical dilemmas of the mental health worker attempting to work in this context of humanistic psychology are discussed, inclusive of the enormous difficulties of bringing humanistic psychology into the all pervasive medical model that controls mental health practice in our society. Through a series of case descriptions, the author provides a narrative account of his own experiences in attempting to bring the authentic nurturing relationship context of humanistic psychology into his various mental health worker jobs. The author reaches the conclusion that this relationship context of humanistic psychology is in actuality being practiced by many mental health workers without knowing it by name. He further concludes that in spite of the challenges and frustrations of engaging in real and nurturing relationships with clients as part of the mental health worker’s job in our current society, the core ingredients of empathy, authenticity, and realness of bond between client and mental health worker, which are the hallmarks of humanistic psychology, are apparently being practiced with partial success through the cleverness, flexibility, and humaneness of mental health workers in spite of the enormous obstacles against this kind of humanistic practice. Chapter 4 – Control of attention is a key mechanism underlying behavior regulation. This chapter details the aspects of attention, language, and movement functions in terms of their underlying brain activity that covary with the chronic use of cannabis throughout adolescence. The authors compare task performance and brain activation differences in tasks involving attention, language, and movement between young adults with a history of chronic cannabis use during adolescence and matched non-user control subjects. Two tasks were used to activate attention networks: the Attention Network Task (ANT) and the use generation task. In the ANT, subjects responded to a left- or right-pointing central arrow which was surrounded by 4 arrows pointing in the same (congruent condition: →→→→→) or opposite (incongruent condition: →→←→→) direction by pressing one of the two buttons under their left or right thumb. Other conditions of ANT mapped alerting and orienting components of attention by using central or peripheral cues preceding the target. Chronic users differ from control subjects in showing poorer performance (longer reaction time and more errors) on tasks requiring processing of incongruent stimuli reflecting the executive attention network,

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but not in networks related to alerting or orienting components of attention in the ANT. Functional MRI of brain activity shows stronger activation within the right prefrontal cortex in chronic users compared to the control group specifically on ANT trials requiring executive attention. The use generation task also reveals significantly stronger activation of the same right prefrontal area in users compared to controls. These results suggest that chronic cannabis users develop less efficient executive attention in conflict resolution tasks, demanding more activation in the right prefrontal areas to resolve conflict. Aspects of brain activity related to motor output (button press in the ANT) demonstrates that chronic users seem to activate ipsilateral primary motor cortex as well in addition to the expected strong contralateral primary motor cortex. Significantly stronger ipsilateral primary motor cortex activation in cannabis users may indicate the presence of pathological mirror movements, when the unintended hand passively mirrors the movement of the intended hand. This developmentally normal phenomenon usually disappears in childhood, and is considered developmental pathology if persists beyond the age of 10. Chapter 5 – This chapter provides a comprehensive review of the cognitive mechanisms that are considered as the fundamentals of rational choice, spanning from the concept of utility driven choices, through the theory of bounded rationality and preference heuristics, and to the newest approach of ecological rationality. The review encompasses compensatory, non-compensatory and semi-compensatory decision strategies. The compensatory strategies include utility maximization and regret minimization. The non-compensatory decision rules consist of elimination by aspects, lexicographic order and the conjunctive heuristic. The semi-compensatory decision strategy combines a sequence of non-compensatory rules for choice set formation, followed by a compensatory evaluation for choosing among the retained choice set. Last, the new theorem of ecological rationality is discussed, in particular with respect to the notion of adaptive toolbox, from which decision strategies are retrieved in order to cope with the choice environment while balancing decision quality and speed. The mathematical representation of each strategy is reviewed alongside the behavioral framework. The chapter presents for each family of models an overview of its development over time, mathematical framework, examples for application, advantages and limitations. The chapter concludes with thoughts regarding possible gaps in the inter-weave between behavioral paradigms and their mathematical representation and discusses future directions for further research. Chapter 6 – The definition of perversion has always been a matter of controversy opposing psychoanalysis to psychiatry. While perversion, for the psychoanalyst, defines a structure that cannot be simply reduced to behavior or symptoms, it remains, for the psychiatrist, closely related to its clinical manifestations (symptoms, acts). Though, a perverse structure does not systematically result in what the authors commonly call “paraphilia”, or a sexually deviated compulsive behavior. More than an “abnormal” or “law breaking” behavior, both on the sexual and interpersonal level perversion has to be mainly considered as a structure, which is, according to Freud, the exact opposite of both neurotic and psychotic structures. Clavreul (1967), reports that the majority of psychoanalytical work tend to show that the perverse act is achieved by subjects whose libidinal investments and relation both to desire and to the law are deeply different from those of neurotics. This is why the author rather prefer to talk about perverse structure than to talk about perversion (either in singular or plural terms).

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Actually, the issue is paramount and very challenging since only an exact identification of the perverse structure helps to successfully deal with it at a psychotherapeutic level. Such challenge to perversion treatment will be illustrated through clinical brief accounts of psychotherapy of male patients who either had recourse to sadomasochistic acts without having a perverse structure (the masochist case) or had a perverse character and acted their incestuous fantasies as well. Chapter 7 – Cognitive-Behavioral Therapy (CBT) has been empirically validated as an effective first-line treatment for both pediatric and adult Obsessive-Compulsive Disorder (OCD). However, OCD is a highly heterogeneous disorder, causing many treatment refractory cases that leave clinicians baffled. This chapter reviews the past ten years of research on several of the most challenging OCD presentations, including OCD with poor insight, high family accommodation, comorbid oppositional defiant disorder, scrupulosity, and postpartum onset. Each of these presentations are discussed in terms of identifying characteristics, treatment augmentation, and case examples. Research supporting innovative assessment for these OCD presentations is outlined as well. CBT is a highly adaptable treatment approach. This chapter aims to summarize past findings and facilitate future research that will guide clinicians in adapting CBT for treatment refractory OCD, thus improving overall treatment outcome. Chapter 8 – Now days, there is no doubt that among adolescents and youth, the Internet communication is the most important use and the most popular for conversations, entrainment, personal refection, etc. The paper will examine the cyber-bullying (CB) phenomenon and its various effects in adolescent populations. It will illustrate the unique characteristics of CB in comparison with face-to-face (f-2-f) bullying, as well as describe the different roles in CB: victims, perpetrators, and witnesses (bystanders). The authors shall focus on revealing the risk factors associated with CB among adolescents and youth, point on the main intervention and prevention plans aimed at effectively coping with this phenomenon, mainly among adolescents, and future examination regarding college students technological misbehavior. Chapter 9 – This chapter reviews recent research on perception of individuals with substance use disorders. Such research indicates ongoing stigma toward individuals with substance use disorders, which is often even greater than stigma toward individuals with other difficulties, and which might continue even when people have stopped using substances. This chapter provides definitions of stigma, and reviews the common themes found in research. The negative implications of stigma will also be addressed. Finally, this chapter addresses resources and methods that may help treatment providers to decrease stigma, help individuals with substance use disorders prepare for potential stigma, and help the public at large to decrease stigma. Chapter 10 – According to the broad preferentist account of well-being merely possible states of affairs can harm or benefit us. On this account, possible as well as actual preference satisfaction contributes to well-being: the satisfaction of our nearby-possible as well as actual preferences may make us better off and the frustration of our preferences at other possible worlds undermines our well-being. Intuitively mere possibilities can affect our well-being. Most of us value effective freedom for its own sake: we believe that an abundance of real options, even if we never exercise them, is in and of itself a good thing. Intuitions however are not decisive and are, in this case, negotiable.

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We may prefer to have more options rather than fewer because we are prudent, banking possibilities against the prospect of changes in our circumstances or preferences. In this case, narrow preferentism, which does not recognize the value of merely possible states of affairs, will do as well as broad preferentism when it comes to explaining our interest in mere possibilities. There is however reason to prefer broad preferentism to narrow preferentism. In addition to providing an account of well-being, broad preferentism suggests a plausible answer to the fundamental question of ethics: “Why should I be moral?” On this account we should engage in altruistic behavior because even if it does not in any obvious way promote our own interests it benefits our counterparts at other possible worlds and, to that extent, makes us better off. The basis for morality, on this account, is transworld egoism.

In: Advances in Psychology Research. Volume 96 Editor: Alexandra M. Columbus

ISBN: 978-1-62417-250-2 © 2013 Nova Science Publishers, Inc.

Chapter 1

INVESTIGATING THE HINDSIGHT BIAS AT CANADIAN UNIVERSITY FOOTBALL GAMES Stuart J. McKelvie Department of Psychology, Bishop’s University, Sherbrooke, Quebec, Canada

ABSTRACT A total of 776 participants in eight studies made judgments about the outcome of Canadian university football games. During the two days before the games, participants estimated the number of points for each team. During the two days after the games, participants were informed of the score for each team, then either estimated what they would have predicted if that had been asked before the games (Studies 1 to 6) or recalled what they had predicted (Studies 7 and 8). In the vast majority of cases, there was no evidence of a hindsight effect: most post-game estimates were not significantly closer to the actual score than pre-game estimates. However, when changes in the estimates over time were converted to standardized effect sizes (d), the mean effect size was significant, showing a very small hindsight effect (d = 0.14, 0.17). When the game outcomes were classified as surprising or not and then into different degrees of surprise, and when the postgame judgments were classified as showing hindsight or not, no significant relationship was found between surprise and hindsight. However, in terms of effect size, the hindsight effect was greater for surprising outcomes than for nonsurprising outcomes, as predicted by Pezzo’s (2003) sense-making model of surprise. The hindsight effect did not differ between women and men and was not more likely to occur for people who were higher than lower in self-involvement (interest). On the other hand, there was a small amount of evidence that it was more likely with people who were less knowledgeable about Canadian university football. Strengths and weaknesses of the present research are discussed and suggestions are offered for future research.

INTRODUCTION Perceptual, cognitive and motor processes usually operate efficiently, allowing people to perform well in everyday life and sometimes perform extremely well when the occasion

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demands. At the same time, these processes can also function less than optimally, leading to errors. People can experience perceptual illusions where what they see (Coren and Girgus, 1978), hear (Warren and Warren, 1970), or touch (Hayward, 2008) may not correspond to reality. They can also experience memory illusions (Roediger, 1996), where the person’s recall does not correspond with what actually happened. And they can experience cognitive illusions (Kahneman, 2011; Kahneman and Tversky, 1996), where their reasoning, judgment and decision-making may be biased. It is within the framework of cognitive illusions that the present research on the hindsight bias is situated.

Cognitive Illusions Modern research on cognitive illusions is usually traced back to the work of Tversky and Kahneman (1974), who argued that judgment and decision-making are often based on shortcut reasoning strategies or heuristics that sometimes lead to errors. They pointed to three major strategies: the availability heuristic, the representative heuristic, and the anchoring and adjustment heuristic. In the first case, the probability of an event is judged on the basis of how easily it comes to mind. In the second case, the probability of an event is judged on how typical it seems. And in the third case, the probability is estimated from an initial value and then adjusted from there. In all three cases, these strategies can lead to biased judgments. According to Fischhoff (2007), after these three heuristics were described, researchers began asking whether judgments might also be distorted by other kinds of cognitive bias. A number have been identified. For example, people prefer information that is consistent with their own beliefs (the confirmation bias; Hart, Albaracin, Eagly, Brechin, Lindberg, and Merrill, 2009), people exaggerate how confident they are relative to their accuracy (the overconfidence effect; Kahneman and Tversky, 1996; Koriat, Lichtenstein, and Fischhoff, 1980; Dunning, Griffin, Milojkovic, and Ross, 1990), people exaggerate how noticeable they are (the spotlight effect; Gilovich, Medvec, and Savistsky, 2000), and people think that if something exists, then it is good (the existence bias; Eidelman, Crandall, and Pattershall, 2009; Eidelman, Paterhall, and Crandall (2010; McKelvie, 2012).

The Hindsight Bias In his own quest, Fischhoff (1975) reports that he was struck by Meehl’s (1973; cited in Fischhoff, 2007) observation that clinicians sometimes seemed to have a false sense of knowing all along that cases would turn out the way that they did. To find out if he could capture this phenomenon, Fischoff conducted two seminal experiments (Fischhoff, 1975; Fischoff and Beyth, 1975) that inaugurated a vigorous programme of research that has continued over the years (e.g., Fischhoff, Gonzales, Lerner, and Small, 2005). He also includes the hindsight bias in his argument that we may misunderstand history because we are seduced by determinism, which is the impression we have that events unfold inevitably (Fischhoff, 1980). In the initial study, Fischhoff and Beyth (1975) asked people to estimate the probability for various outcomes of President Nixon’s upcoming visit to China and the Soviet Union. From two to six weeks after the visit, they asked the same people to state what they thought

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had actually occurred and to recall their estimates for the possible outcomes. For events they thought had occurred, their recalled probabilities were higher than before, and for events that they thought had not occurred, their recall probabilities were lower than before. It seemed that knowing that an event had occurred (or in this case, knowing what you thought had occurred) made the event seem more likely after the fact. In the second original study (Fischhoff, 1975), in which he introduced the term “hindsight” to describe the bias that he had identified, Fischhoff conducted three experiments in which he examined the effect with a number of scenarios. For example, in one of them, five groups of participants read an account of fighting between the Gurkas and the British in India in 1814. For one group, the actual outcome was not listed, but participants were asked to judge the probability of four possible outcomes. For the other four groups, participants were given an outcome and then asked to judge the probability of that outcome and also the other three outcomes. Fischhoff found that, for each outcome that was identified as the actual outcome, its estimated probability of occurrence was higher for the group that was told that it was the outcome than for the group that judged it without knowing the outcome. In addition, for three of the four groups who were told the outcome, the estimated probability of occurrence was higher for their given outcome than for the other three outcomes. These results were replicated with three other scenarios, providing reliable evidence that knowing an outcome makes it seem more likely. Fischhoff speculated that participants made biased judgments after the outcome was given because they were trying to make sense of everything they knew about the event. As noted above, Fischhoff has continued to examine the hindsight bias over the years. Most recently, he studied it by investigating risk judgments associated with the events of September 11, 2001 (Fischhoff, et al., 2005; see also Fischhoff, Gonzalez, Lerner, and Small, 2012a, 2012b). In November, 2001, participants judged the likelihood of four terror-related events over the next 12 months. One year later, they recalled their predictions then, given what they knew about events during the past year, they estimated what they now thought the prior likelihoods were. In both cases, the probabilities were lower for the second judgments than for the first ones. Because the world seemed safer in 2002 than was implied by the judgments in 2001, this shift represents a hindsight effect. Researchers have investigated the hindsight effect in a variety of ways. A methodological factor has been the design of the study. In the within-subjects design (“memory” design; Hoffrage and Pohl, 2003; Pohl, 2007; Pohl, Bender, and Lachmann, 2002), the same people are tested before and after the event, and are usually asked to recall their earlier judgments (e.g., Fischhoff and Beyth, 1975; Fischhoff et al., 2005) or, as was observed above, to update them (Fischhoff et al., 2005). In the between-subjects design (“hypothetical” design; Hoffrage and Pohl, 2003; Pohl, 2007; Pohl et al., 2002), one group of people make judgments about the event before it happens (predictions) and another group makes judgments after it has happened (postdictions). People in the second group, who know the outcome, make retrospective judgments about what they would have predicted if they had made judgments before the event (e.g., Fischoff, 1975; Leary, 1982). A content factor has been the nature of the event that is judged, which has ranged from actual episodes to assertions about facts or questions about quantity (Pohl, 2007). In some studies, the event is real and is drawn from everyday life (e.g., the O. J. Simpson trial, Bryant and Brockway, 1997; the 1980 U.S. Presidential election, Leary, 1982). In others, which are more numerous (Guilbault, Bryant, Brockway, and Posavac, 2004; Pezzo and Beckstead, 2008), the event consists of factual

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material, such as almanac-type statements (e.g., Musch, 2003) or experimental material such as faces (Harley, Carleson, and Loftus, 2004) or auditorially-presented words and sentences (Bernstein, Wilson, Pernat, and Meilleur, 2012). In some studies, the participants are “experts” (e.g. , Rachlinski, Guthrie, and Wistrich, 2011), who are familiar with the task or have direct experience with it (Christensen-Szalanski and Willham, 1991; Hertwig, Fanselow, and Hoffrage, 2003), and in some they are not (e.g., Fischhoff, 1975). The role of individual differences, as predictors of the hindsight effect has also been examined (Musch and Wagner, 2007). Among these subject variables are the judge’s personality (Musch, 2003) and the judge’s self-involvement with the task (e.g., Leary, 1982; Pezzo and Beckstead, 2008). Moreover, the hindsight effect has been studied in different cultures from around the world (Pohl, et al., 2002) and in different age groups (Bayen, Pohl, Erdfelder, and Auer, 2007), which have ranged from 5 to 95 (Bernstein, Erdfelder , Meltzoff, Peria, and Loftus, 2011). There have been three major reviews of this literature. Some quantitative results will be presented here, particularly if they are relevant to factors that are considered in the present research. Firstly, Hawkins and Hastie (1990) summarize empirical findings from both laboratory and nonlaboratory studies, and consider theoretical accounts of the results. People have differentiated motivational accounts (based on receiving incentives for accuracy) from cognitive accounts (based on how old and new beliefs are remembered), but Hawkins and Hastie think that they overlap and that elements of both are needed. Secondly, ChristensenSzaalanski and Willham (1991) conducted a meta-analysis of the research findings. Overall, they concluded that the effect size was “small” (r = .17), but was larger for events that did occur than for events that did not occur, and for tasks that were unfamiliar (i.e., if the participant had not directly experienced it or was not an expert in it) than for tasks that were familiar (rs = .19, .11 respectively). They also suggested that the hindsight effect was more likely to be cognitively based than motivationally based. Thirdly, Guilbault et al. (2004) conducted another meta-analysis of the literature, but report their results in terms of the standardized effect size (d). Overall, they concluded that the effect size was “small to medium” (d = 0.39), and that it was commensurate with Christensen-Szaalanski and Willham’s (1991) results, because a correlation coefficient of .17 is equivalent to d = 0.35. Notably, the two groups of researchers label their similar effect slightly differently (“small”, “small to medium”). However, most people accept Cohen’s (1977) guidelines of d = 0.2 for small, 0.5 for medium, and 0.8 for large, according to which both estimates would be small to medium, which is how Guilbault et al. characterize the effect. In addition, they concluded that the effect was larger for objective estimates than for subjective estimates, for almanac-type questions where people judged statements as being true or false than for real-world events or case histories (ds = 0.57, 0.33, 0.36 respectively), and for neutral outcomes than for positive or negative outcomes, which did not differ (ds = 0.47, 0.28, 0.34 respectively). However, unlike Christensen-Szaalanski and Willham’s (1991), Guilbault et al. did not find that expertise was a factor in the hindsight effect. Clearly, the hindsight effect has attracted considerable research interest. According to Blank, Musch, and Pohl (2007), the bias is important because it occurs in a wide variety of circumstances, even when warnings are given to avoid it, and because it may have negative consequences in everyday life. For example, because we think that “we knew it all along”, we may resist changing our way of thinking when it would be beneficial to do so.

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Explaining the Hindsight Effect As noted above, Fischhoff (1975) suggested that the hindsight bias occurs because participants were trying to make sense of everything they knew about the event. This is consistent with the view that the hindsight biased is cognitively rather than motivationally based (Christensen-Szaalanski and Willham, 1991), which would justify classifying the phenomenon as a cognitive illusion (Blank and Peters, 2010). Others have also emphasized the role of sense-making in the effect (e.g., Blank and Nestler, 2007; Nestler, Blank, and Collani, 2008), and it has been suggested that this reasoning process is accompanied by important metacognitive experiences such as emotion or how difficult the sense-making is felt to be (Sanna and Schwarz, 2006). Indeed, one of the conditions that may be associated with or may even spark the process of sense-making is experience that the outcome is surprising. Many researchers have investigated the role of surprise as a factor in the hindsight bias, but with various expectations: some predict that surprise would enhance the effect, some predict that surprise would diminish it, and some predict that surprise would not influence it at all (Ash, 2009). In one study devoted to the investigation of surprise, Ofir and Mazursky (1997) found that the hindsight bias occurred when surprise was low or moderate, but was actually reversed when surprise was high. A somewhat similar result was obtained by Calvillo and Gomes (2011). Unlike Ofir and Mazursky, they found that the hindsight bias did not occur when surprise was low. However, like Ofir and Mazursky, they found that it did occur when surprise was medium and was reversed when surprise was high. To illustrate what is meant by reversed hindsight, their experiment will be summarized. Participants viewed animations of automobile accidents. In the foresight condition, participants were told that an accident might occur and they predicted when they thought it would happen by stopping the video. Their prediction was quantified by the number of frames from this point to the accident. In the hindsight condition, participants were told that an accident would occur. They watched the complete video and then watched it again, stopping the video where they thought a person who had not seen the animation would stop it. When the accident had been rated as low in surprise, they found that the frame before contact at which the video was stopped was similar in the foresight and hindsight conditions. When the accident was medium in surprise, the video was stopped further before contact (earlier) in the hindsight than in the foresight condition. That is, the accident was predicted earlier in the video in the hindsight condition, which constitutes hindsight bias. When the outcome was high in surprise, the video was stopped later before contact (closer to contact) in the hindsight than in the foresight condition. This is a reversed hindsight effect. These findings are broadly consistent with a sense-making model of surprise proposed by Pezzo (2003). He distinguishes between “initial surprise” and “resultant surprise”. When an outcome occurs as expected, there is no surprise and no hindsight bias. This is because no sense-making activity takes place (Calvillo and Gomes, 2011). However, when an outcome is unexpected (“incongruent with prior expectation”), people experience initial surprise, and try to make sense of the outcome. If they are successful, there is no resultant surprise, but the hindsight bias is likely to occur. That is, because they were able to make sense of the outcome, people feel that they “knew it all along”. If they are not successful in making sense of the outcome, they experience resultant surprise, and the hindsight bias is reduced or even reversed. Overall, this implies that if an outcome is not surprising, then there will be no

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hindsight. However, if an outcome is surprising, then there may be hindsight (if sense-making is successful). Perhaps Pezzo’s (2003) model of surprise can be connected to the findings of Ofir and Mazursky (1997) and Calvillo and Gomes (2011) as follows. When the outcome is not surprising, it is not necessary to engage in sense-making activity, and the hindsight effect will not occur. When the outcome is slightly surprising (small surprise), there may be a small amount sense-making activity, and it will probably be successful. It would then produce a hindsight effect as Pezzo’s model stipulates. Alternatively, if the surprise is small, it may be insufficient to provoke sense-making activity, leading to no hindsight. When the outcome is moderately surprising, Pezzo’s model applies, and hindsight will occur if the sense-making is successful and but will not occur if the sense-making is unsuccessful. Finally, when the outcome is very surprising (large surprise), sense-making activity will take place but is less likely to be successful. Under these circumstances, there will be no hindsight effect and possibly a reversed effect. In addition, there may be a special situation if the outcome is very surprising and very disappointing. People may not wish to think about it and would therefore avoid any sense-making, leading to no hindsight effect. Of course, if the outcome is self-relevant, a surprise may be welcome rather than disappointing. If this factor plays a role in the hindsight effect, a full explanation may have to involve motivation as well as cognition (Blank and Peters, 2010). In a study of real-world outcomes (Pezzo and Beckstead, 2008), students rated the likelihood that certain positive events would happen and that certain negative events would happen over the course of the semester. About two months later, they indicated whether each event happened or not and the recalled their original judgment. For events that happened, recalled likelihoods were greater than the original estimates and this hindsight effect occurred for both positive events and negative events, but it was greater for the positive events than for the negative events. They also found that the hindsight effect was greater for events that were rated as more controllable, but even for the less controllable ones, there was a hindsight effect. In addition, the effect of valence was independent of the effect of controllability. That is, the hindsight effect was greater for positive than for negative events whether the events were more controllable or less controllable. Notably, the effect of valence is inconsistent with Guilbault et al.’s (2004) meta-analytic finding that the hindsight effect was greater for neutral outcomes than for positive or negative ones (which did not differ). In addition, surprise can mean that an event occurs when it was not expected or that an event does not occur when it was expected. In both cases, Pezzo and Beckstead found that the hindsight effect was greater than where there was no surprise, either from an unexpected event that did not occur or from an expected event did occur. Another issue of interest is whether any effect of valence is a function of surprise. For example, if the hindsight effect is greater for positive events than for negative events, does this hold both for events that are surprising and for events that are not surprising? In Pezzo and Beckstead’s research, the events that the students rated were likely to be self-relevant, and they found different levels of hindsight for positive and negative outcomes. However, Blank and Peters (2010) cite research showing that even self-relevant negative event outcomes are associated with different levels of hindsight: sometimes the bias is reduced and sometimes it is increased. To account for this, they argue that hindsight bias may have two components: foreseeability and inevitability. In the first case, an event is judged as one that could have been predicted, which refers to a person’s subjective state of knowledge.

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In the second case, an event is judged as one that was inevitable, or had to turn out that way, which refers to an objective state of the world. Blank and Peters suggest that when hindsight was reduced in the studies with self-relevant negative outcomes, it had been measured by foreseeability. However, when hindsight was increased, it was measured by inevitability. To test this notion, Blank and Peters manipulated these components, and found experimental support for their model. In another study of the two hindsight components, Nestler and Egloff (2009) also found a hindsight effect when inevitability was measured. However, when foreseeability was measured, the effect was reversed.

The Hindsight Bias in Everyday Life: The Case of Sport In his original discussion of the hindsight effect, Fischhoff (1975) pointed out that it has implications for our judgments in everyday life, and for our general understanding of past events. In particular, as noted above, it may even help to throw light on what we learn from history (Fischhoff, 1980). However, according to Pezzo and Beckstead (2008) not many studies (approximately 25% of the ones listen in Guilbault et al., 2004 meta-analysis) have been conducted with real-life materials and real-world outcomes that are both relevant to the participants. Somewhat ironically, Guilbault et al. (2004)’s analysis found that hindsight effects seem to be smaller with the more realistic materials. If this is the case, even if the hindsight bias has implications for judgments in everyday life (Fischoff, 1975), the effect may not be very strong. However, one area of everyday life in which hindsight may occur more frequently is sport. Anecdotally, after an event, or even after plays during the event, players, commentators, journalists and fans often seem to talk as if they thought that they knew all along what was going to happen. Indeed, the hindsight effect is often referred to as “Monday morning quarterbacking”. Therefore, the purpose of the present research is to examine the hindsight effect with a real-world sports event. This topic has been investigated in a number of studies that are reviewed below. Before describing them, two controlled laboratory investigations will be noted. The first experiment is interesting because it examined the hindsight effect with experts and non-experts in baseball. In a virtual baseball batting task, Gray, Beilock, and Carr (2007) asked participants to judge where the ball would land. People with collegiate batting experience, who have procedural knowledge of baseball, were more accurate than novices. After receiving feedback about where the ball did land, participants repeated their judgments. Errors were lower after the feedback than before, providing evidence of a hindsight bias, but the effect was smaller for the experts than for the novices. This finding is consistent with the results of Christensen-Szaalanski and Willham’s (1991) meta-analysis, in which the hindsight bias was greater for people who were unfamiliar with the task than for people who were more familiar. However, a slightly more complex result from a simulation experiment was reported by Hertwig, Fanselow, and Hoffrage (2003). They confirmed that the hindsight effect was greater when knowledge was less, but when they distinguished accurate from inaccurate knowledge, they found that the hindsight effect was greater when the knowledge was more accurate.

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The second experiment is interesting for the present research because Ash (2009) simulated the kind of study (see below) in which people judged the outcome of games. Ash manipulated expectations and outcomes in a scenario that described a tennis match. Because the scenario and procedure are similar to a real-world sports event, this study will be described in some detail. In Ash’s scenarios, there were three conditions: congruent, in which the outcome of the match was consistent with expectation (not surprising), ambivalent, in which outcomes were not clearly consistent or inconsistent with expectation (perhaps surprising), and incongruent, in which outcomes were inconsistent with expectation (surprising). After reading one of the scenarios, introductory psychology students (73% women) rated the likelihood of one or the other player winning (the prediction condition). They were then told which player had won. Participants returned one week later and tried to recall their initial judgment (memory condition). These retrospective ratings for the likelihood that a player would win were generally closer to the outcome than the original ratings that predicted the outcome, demonstrating a hindsight bias. Ash also reported that this effect occurred in the ambivalent condition and in the incongruent condition, but not in the congruent condition. That is, there was hindsight bias when the outcome was perhaps surprising or clearly surprising but there was no hindsight bias when the outcome was expected (not surprising). This is consistent with Pezzo’s (2003) model of hindsight.

Previous Studies of the Hindsight Bias in Judgments of Outcomes in Team Sport Because the present studies examined whether the hindsight bias occurred when people made judgments about the outcome of actual football games, the previous studies of real-life sports outcomes are described in detail. In particular, because the issue of replication was an important issue in the present studies, information was provided about the design, participants, procedure, statistical analysis, results, and whether these results were consistent with Pezzo’s (2003) model of surprise. The first investigation of the hindsight bias at an actual sports event was conducted by Leary (1981). Using the between subjects (“hypothetical”) design, 83 people (42 women, 51 men) were approached as they entered the football stadium before a home American university football game or as they left the stadium after the game. Most of the participants were students, and the others were nonstudent adults, mostly alumni. Those who were tested before wrote down their prediction for the score and those tested after wrote down what they would have predicted if that had been asked before. Half of the participants made public estimates in which the interviewer could see what they wrote and half made private estimates that were placed in sealed envelopes. To measure ego involvement, participants also rated themselves on how important to them was their knowledge and understanding of football. Based on a median split, they were then classified as higher or lower in ego involvement. The estimates were transformed into a difference score in which a positive number represented a home win and a negative number represented an away win. The actual score was 10-20, giving a difference of -10. The mean difference in the estimates made before the game (7.6) was significantly greater than this value, indicating that there was the possibility of a hindsight effect. That is, if the prediction had been accurate, there would not have been

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room for it to move closer to the actual score. In fact, Leary found that the predicted difference was also greater than the mean difference after the game (2.2). Although Leary does not state whether he checked whether participants leaving the stadium knew the score in the game, it is probably reasonable to assume that they did. Consequently, because the estimates moved from pregame to postgame in the direction of the actual difference, this change demonstrates a hindsight bias. Although Leary did not report whether the hindsight effect was related to sex of participant, he found that it was unrelated to whether the judgments were made publically or privately or to whether ego involvement was higher or lower. He concluded that his results showed that the hindsight bias occurred in a natural setting and that, because it was unrelated to self presentation or ego involvement, it was more likely to be based on cognitive reconstruction than on a motivational factor. Finally, because the predicted difference was a home win of between 7 and 14 points and the outcome was an away win (home loss) of 10 points, I would judge that the outcome of this game was a surprise. Therefore, the occurrence of the hindsight bias is consistent with Pezzo’s (2003) model of surprise. Notably, in view of Pezzo and Beckstead’s (2008) report that the hindsight effect was stronger for positive than for negative events, the bias occurred with a loss for the home team, which is a negative event. In the second study of the hindsight bias in sport, Roese and Maniar (1997) also employed the hypothetical design. In this case, a total of 241 students (79 women, 162 men) who were attending one of three home American university football games provided predictions (one group) or postdictions (three groups). People were tested before the game as they embarked on a bus taking them from the campus to the game and people tested after the game were tested as they disembarked from the bus. They rated the likelihood of a home loss or win (from 1 to 10) and of the size of the win or loss (percentage likelihood for four outcomes: losing by more than 10 or less than 10 and winning by less than 10 and more than 10). Participants who were tested after the game were asked to recall their hunch about the game before it was played. One of the three postdictive groups (control) thought about the game and recorded their thoughts before making their estimates. The second postdictive group (counterfactual) imagined and then recorded ways that the game might have gone differently before making their estimates. The third postdictive group (causal) thought about and recorded key determining moments before making their estimates. Finally, participants reported their team affiliation and, to measure expertise, how many sporting events they attended in an average month. The home team won all three games, with scores of 35-0, 21-10, and 31-20. For the three games combined, win-loss certainty increased significantly from 4.8 out of 10 before the games to 6.5 after the games for the control group, and showed an additional increase to 7.7 for the counterfactual and causal groups, which did not differ from each other. For the likelihood that the home team would win by more than 10 points, percentage estimates increased significantly from 13.8% before the games to 30.2% after the games for the control group, and showed two additional increases to 49.3 and then to 55.4 for the causal and counterfactual groups respectively. Because the home team won all the games, these changes demonstrate a hindsight bias. As in Leary’s study, Roese and Manier do not report whether they checked whether the postgame participants knew the outcome of the game, but it is probably reasonable to assume that they did. Roese and Manier did not break down the results according to sex of participant, but they did report that the results were not related to expertise. In addition, although the general

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pattern of results was similar for the first two games, it was slightly different for the third one. That is, in the first two games, the hindsight effect was significant for the control group where participants simply thought about the game, and it was even stronger for the two groups who thought about alternative game events or about key events that might have explained the outcomes. In the third game, scores were not greater for the control group than for the pregame group, which indicates that there was no hindsight bias when participants simply thought about the game. However, scores did increase significantly for both the counterfactual and causal groups, indicating a hindsight bias. Notably, the pregame estimates for the likelihood of a win were less than 5 out of 10 for the first two games (4,2, 3.1 respectively) and more than five out of 10 (7.3) for the third game. This indicates that there was more room for movement in the ratings in the first two games than in the third game. Given that all three games were home team wins, it is likely that that the first two results were more surprising than the last one. However, even if the last outcome was not a surprise, it would still have been pleasing. The results obtained from the first two games agree with Pezzo’s (2003) model of hindsight because the outcomes were surprising and the hindsight effect occurred. For the third game, the results for the control group were also consistent with the model because the outcome was not surprising and the hindsight effect did not occur. However, there was evidence of hindsight in the causal and counterfactual groups, which does not agree with the model. Finally, in view of the fact that all games were wins, the hindsight effect is consistent with Pezzo and Beckstead’s (2008) report that the bias is greater for positive than for negative events. Like Leary, the authors emphasize that their results demonstrate the hindsight bias in a real-world setting. They also observe that it occurred with participants who were strong supporters of the home team and who were knowledgeable about football and interested in it. Finally, Roese and Maniar argue that counterfactual thinking may induce people to consider the causes of the outcomes, and that the more an event can be explained, the more inevitable it may appear to be. If this was the case, it might be thought that the results with the third game in the counterfactual group may be partially consistent with Pezzo’s model because it has been argued that if a result is explained as being inevitable, the hindsight bias is more likely (Blank and Peters, 2010). However, this suggestion applies when the outcome is negative for the participants, which is not the case here. Bonds-Raacke, Fryer, Nicks and Durr (2001) employed the memory design in their study of 42 students (13 men, 29 women) in psychology classes. Before the weekend of Super Bowl XXXIII in 1999, participants predicted which team they thought would win. They also rated how much they watched football on a 3-step scale from “all of the time” to “some of the time” to “never”. On the Monday following the game, the same people stated which team they had predicted to win and whether they were surprised by the outcome. The game was played between Atlanta and Denver, with Denver winning. The authors state that 15 people predicted Denver to win and 27 predicted Atlanta to win. Although they do not present their reasoning in precise detail, it appears that they assume that the people who predicted a win for Atlanta would have been surprised (unpleasantly) by the outcome. However, they found that 56% of these participants were not surprised, which they interpret as evidence of the hindsight effect. It is unfortunate that they do not report the number of people who recalled predicting each team as the winner. Clear evidence of hindsight would be indicated if a significant number of the 27 people who had predicted a win for Atlanta recalled in error that they had actually predicted a win for Denver. In addition,

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they did not break down their results by sex of participant or by amount of football watching. Given the manner in which they analyzed the results, with the emphasis on those who predicted a win for Atlanta, it could be said that the outcome was surprising. Accepting the authors’ conclusion that there was evidence of hindsight, the results are consistent with Pezzo’s (2003) surprise model. Finally, it is notable that the participants in this study were students in an introductory psychology class, who presumably varied in their interest in and knowledge about football. In particular, and unlike the participants in the first two studies, they did not attend the event. Some may have watched it on television but, by the same token, some may not. Bonds-Raacke et al. do not state whether they informed the participants of the outcome. Another study of American university football was conducted by Sanna and Schwarz (2003) with introductory psychology students. Because they were interested in how the hindsight bias might be affected by counterfactual thoughts about why the game might have turned out differently, they manipulated this variable among participants who were tested on the Monday after the Saturday game in question. The game was played during Homecoming Weekend, with the home team winning 13-10. This yielded a difference score of +3 in their favour. It is not clear from their report whether Sanna and Schwarz informed their participants of this result. However, they allocated 53 introductory psychology (sex unspecified) students randomly to four conditions. Participants generated either 4 or 12 reasons about how the game might have turned out differently, and in each case half of the participants were given attributions and some were not. In the two attribution conditions, half of the participants in the 12-reasons group were informed that this task required extensive knowledge of football, and half the participants in the 4-reasons group were informed that this task was. All participants rated their knowledge of football on a 7-point rating scale before judging what they would have predicted the score in the game to be if they had been asked before the game. As in Leary’s (1981) study, participants were required to estimate the number of points that each team would have obtained. The authors report the estimated scores for each team but, like Leary, they converted the two estimates into a difference score for the dependent variable, with a positive value indicating a win for the home team. They also observe that this score is more appropriate than one in which the estimates for the two teams are considered separately because participants make these estimates in the light of their knowledge of both teams, which implies that they are not independent. In the no attribution condition in which participants were not told anything about task difficulty, the mean difference score was significantly lower in the 12-thought condition (4.8 derived from 15.7 and 10.9 for each team) than in the 4-thought condition (10.5 derived from 27.5 and 16.9 for each team). Because the difference score in the 12-thought condition is closer to 3, it shows more hindsight than in the 4-thought condition. However, when participants were given a reason why the generation of reasons might be difficult or easy, the two corresponding difference scores for the 12- and 4-thought conditions of 10.3 (from team scores of 23.6 and 15.1) and 7.1 (from team scores of 19.1, 12) were not significantly different. Given that they were both further away from 3, they indicate less or even no hindsight bias. The authors conclude that the hindsight bias was higher when more thoughts were generated, but only if doubts were not raised about the informational value of the difficulty experienced when generating the thoughts. The authors also state that there was insufficient variation in self-rated football knowledge to meaningfully analyze its relationship

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with the hindsight bias effect. Unfortunately, scores were not broken down by sex of participant. It was not possible to judge directly whether or not outcome of the game was a surprise to the participants because predictions were not gathered before the game. However, the authors state that two teams had similar records and odds makers predicted the game to be close, estimating a 6-point win for the home team. From this, it can be argued that the outcome was pleasing but probably not surprising. The presence of the hindsight bias therefore seems generally inconsistent with Pezzo’s (2003) model. At the same time, the fact that the hindsight bias was greater with 12 reasons compared to four reasons may be seen as partially consistent with the model because there is likely to be more sense-making when there are more reasons. In the studies described above, estimates were made about the outcomes of football games. Two other studies of team sport outcomes have been conducted, one with professional soccer in Israel and one with American university basketball. In the first case, Tykocinski, Pick and Kedmi (2002) employed the memory design with 43 university students (sex unspecified) who identified themselves as fans of one team (Team H, n = 12) or the other team (Team B, n = 31) and who watched a game between them on television. Two or three days before the game, participants rated the chance that each team would win, using an 11point scale. Shortly after the game, they were asked the final score (2-1 for Team H). Everyone reported it correctly. Notably, in these studies of the hindsight effect with real-life events, this is the only one that explicitly reported checking that postgame participants knew the outcome. Using the same scale as before, participants then rated what they now thought in retrospect were the chances that, first, Team H would win the game and, second, that Team B would win the game. Finally, participants rated how disappointed or happy they were with the outcome. Fans of the winning team (Team H) predicted that their team was more likely to win (7.8/10) than Team B (2.7/10) and these ratings did not change significantly over time. That is, there was no evidence of the hindsight bias for fans of Team H. Fans of the losing team (Team B) did not differ significantly in the predictions for the two teams (5.8 for Team H and 4.8 for their own Team B). However, their ratings for the likelihood that Team H would win increased significantly over time (to 7.0) and their ratings for the likelihood that their own Team B would win decreased significantly over time (to 4.0). Because Team H won and Team B lost, both of these changes provide evidence of the hindsight bias. Notably, for the fans of Team H, the initial ratings for Teams H and B were fairly high (7.8/10) and low (2.7/10) respectively. These ceiling and floor levels did not leave much room for movement in the ratings. However, for the fans of Team B, the initial ratings were near the middle of the scale, leaving room to move in either direction. Finally, fans of Team H clearly expected them to win (mean rating of 7.8 out of 10), which means that the win was not surprising to them. The fact that the hindsight bias did not occur for these fans is consistent with Pezzo’s (2003) model of surprise. However, even fans of Team B rated the likelihood that Team H would win above the midpoint of the scale (5.8 compared to 5), which means that the win was not much of a surprise for them either. According to Pezzo’s model, this implies that there should not be a hindsight effect for the fans of Team B. The presence of the effect is inconsistent with the model. Notably, the hindsight effect was found for the fans the losing team but not for fans of the winning team. This is inconsistent with the finding that the

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hindsight effect is greater for positive outcomes than for negative outcomes (Pezzo and Beckstead, 2008). In the final previous study of team sport outcomes, Pezzo (2003) himself employed the hypothetical design with a total of 281 people (sex unspecified) attending one of three American university basketball games. Participants were approached immediately before or after the games and asked which team they supported. Then, on a percentage scale, they rated how likely it is that the home team will win the game (for those tested before) or how likely it was that the home would win the game (for those tested afterwards). Although Pezzo does not state if he checked whether participants tested after the games knew the outcomes, it is reasonable to assume that they did. Moreover, they were only required to judge the likelihood of a win. Even if they did not remember the precise number of points scored by each team, they would almost certainly remember which team won. The home team won all three games. Fans of the home team rated the likelihood of a home team win fairly highly before the games (mean = 82%), and this did not change significantly for fans of the home team tested after the games (80%). That is, there was no evidence of the hindsight bias for fans of the home team. Fans of the visiting team rated the likelihood of a home team win fairly low before the games (44%). However, for visiting fans tested after the games, the mean rating for a home team win was 47%, an increase that was marginally significant (p = .07). Because the home team did win, Pezzo argues this provides some evidence (albeit marginally significant) for the hindsight bias. Notably the initially high ratings from the home team fans are fairly close to the ceiling, which means that there was not much room for them to move up. At the same time, there was room for a change of 3%, which was the amount of change shown by the visiting fans. Finally, home fans clearly expected the home team to win (mean rating of 82%), which means that the win was not surprising to them. The fact that there was no hindsight effect for home fans is consistent with Pezzo’s model. In contrast, visiting fans were much less likely to predict a home win before the game (mean rating of 44%), which means that the win would have been somewhat surprising. Assuming that the visiting fans’ small increase in likelihood of a home win is evidence of hindsight, the effect is consistent with Pezzo’s model of surprise. Indeed, Pezzo himself interprets the results as supporting his model, according to which hindsight bias is associated with relatively unexpected outcomes in which sense-making activities are successful but not with expected ones in which sense-making activities do not occur. Note, however, that the presence of a hindsight effect for fans of the losing team but not for the fans of the winning team is inconsistent with Pezzo and Beckstead’s (2008) report of a greater hindsight effect for positive than for negative outcomes. In these five studies of real-life sports events, there were 19 tests of the hindsight bias. Two studies included one test (Leary, 1981; Bonds-Raake et al., 2001), two included two tests (Tykocinski et al., 2002 et al. with fans of the winning team and fans of the losing team, Pezzo , 2003, with home fans and visiting fans), one study included four tests (Sanna and Schwarz, 2003, with two reasons conditions each with two attribution conditions), and one study included nine tests (Roese and Maniar, 1997) with three games each with control, counterfactual and causal conditions). In all nine cases where the outcomes were judged to be surprising (whether pleasant or not), there was a significant hindsight bias. For the nine cases where the outcomes were judged to be not surprising and pleasant, there was hindsight bias in three cases and no hindsight bias in six, and for the single case that was surprising and unpleasant, there was a

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significant hindsight bias. Combining the pleasant and unpleasant outcomes for the nine cases that were not surprising, there was hindsight bias in four cases and no hindsight bias in six cases. A 2 X 2 (Surprise X Hindsight) chi square test on the four frequencies was significant, χ2(N = 19) = 5.36, p = .021 indicating that if an outcome is surprising, then hindsight is likely to occur, but if it is not surprising, then it is less likely to occur. The results for surprise are consistent with Pezzo’s sense-making model, because the hindsight bias can occur when the outcome is surprising, but the results for no surprise are only partially consistent, because the model predicts that there will be no hindsight if there is no surprise. However, it is notable that the six cases in which there was no significant hindsight bias all occurred when the outcome was not surprising (but pleasant). Excluding the eight conditions with special instructions (counterfactual reasons, causal reasons, explanations of difficulty or ease in generating reasons) leaves 11 conditions. In all five cases where the outcomes were judged to be surprising (whether pleasant or not), there was a hindsight bias. For the five cases where the outcomes were judged to be not surprising and pleasant, there was hindsight bias in one case and no hindsight bias in four, and for the single case that was surprising and unpleasant, there was hindsight bias. Notably, the four cases in which there was no significant hindsight bias all occurred when the outcome was not surprising (but pleasant). Again, these results suggest that if an outcome is surprising, then hindsight is likely to occur, but if it is not surprising, then it is less likely to occur. Finally, with regard to the effect of valence on the hindsight effect, the results here were mixed. The effect occurred for fans of the winning team in one study (Roese and Maniar, 1997), but it also occurred for fans of the losing team in another study (Leary, 1981). In contradiction to the previous finding that the effect was stronger for positive than for negative events (Pezzo and Beckstead, 2008), within the same studies, the hindsight effect occurred for fans of the losing team but not for the fans of the winning team (Pezzo, 2003; Tykocinski et al., 2002). These results suggest surprise is a more important factor than valence in the occurrence of the hindsight effect.

THE PRESENT STUDIES Overview As shown above, the original study with university football was conducted by Leary in 1981, and has been followed sporadically by studies with football and other sports. The purpose of the present studies was to conduct a further investigation of the hindsight bias with a real-world event, in this case Canadian university football. The major goal was to ascertain if the hindsight effect occurs. In particular, given that the effect has been reported with a number of sporting events, the goal was to investigate if it can be replicated in this setting. In addition, given its theoretical implications for explaining the hindsight effect, the role of surprise as a moderator of the hindsight effect was reexamined. In particular, as was done in the present descriptions of the previous studies of the hindsight effect in sports, the results were compared with predictions from Pezzo’s (2003) model of surprise. Finally, in line with previous investigations that have included individual differences as a factor in the hindsight effect (Musch and Wagner, 2007), the subject variables of interest, knowledge and sex of

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participants were included in some of the analyses. Knowledge is related to expertise, which has been found to be a factor in some cases (Christensen-Szaalanski and Willham (1991). Interest is related to self-involvement, which has theoretical implications for the proposal that motivation must be considered in explanations of the hindsight effect (Hawkins and Hastie, 1990).

The Importance of Replication Replication, which is fundamental in order to establish the reliability of scientific findings, can be either direct or systematic (McBurney and White, 2010, p. 209). With direct replication, the previous procedures are followed as closely as possible. With systematic replication, a similar study is conducted, but with changes (e.g., to materials or the kind of participants). Direct replication is rare, perhaps because it brings little glory or professional reward (Burman, Reed, and Alm, 2010; McBurney and White, 2010, p. 209). However, although replication should lie at the heart of science (Amir and Sharon, 1991; Burman, Reed, and Alm, 2010; Lamal, 1991), it does not occur as often as it should, particularly in psychology (Neuliep and Crandall, 1991). Recently, the issue of replication has received attention, sparked by a demonstration that some apparently strong significant effects seem to have become considerably weaker over time (Ioannidis, 2005a; Schooler, 2011). This trend, which has been labelled the “decline effect” (Lehrer 2010; Schooler, 2011), has been related to the problem of publication bias, where studies with a particular outcome, usually a significant one, are more likely to be published (Ferguson and Brannick, 2012; Francis, 2012; Ioannidis and Trikalinos, 2007; Schooler, 2011). Worse still is the suggestion that some effects might be false positives (Coyne, 2009; Ioanidis, 2005b; Simmons, Nelson, and Simonsohn, 2011). This has led to the recommendation that there should be more publication of replications from different teams (Ioannidis, 2005; Simmons et al., 2011; Yong, 2012), and that it should not matter whether or not the effects are significant (Coyne, 2009; Ozonoff, 2010, 2011). The present studies of the hindsight effect in university football are presented in this context. Because the participants, measuring procedures and games were somewhat different from the previous studies of football, they constitute a systematic replication.

Moderating Factors in the Hindsight Effect In studies of the factors that may moderate the hindsight effect, it has been proposed that self-relevance (e.g., Pezzo and Beckstead, 2008) and expertise (e.g., Christensen-Szaalanski and Willham, 1991) may play a role. However, in the studies where non-athletes estimated the results of games, these factors were not significant (Leary, 1981; Roese and Maniar, 1997). In the present research, it was reasoned that a person’s interest in football might reflect how relevant the outcomes would be for them. Consequently, as noted above, interest was included as a subject variable in some of the studies. It was also reasoned that a person’s knowledge of football would reflect their expertise. In previous research, expertise has been captured by measuring procedural knowledge. People with skilled knowledge (e.g., physicians, sports players; Christensen-Szaalanski and Willham 1991; Gray et al., 2007) who were familiar with the task were compared with other people

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who were unfamiliar with the task. It has also been captured in non-practitioners (spectators at football games) by asking about the frequency of their attendance at games (Bonds-Raacke et al., 2001; Roese and Maniar, 1997) or by self-rated knowledge (Sanna and Schwarz, 2003). However, in the present research, expertise in non-practitioners was captured by their semantic knowledge of football (win/loss records) and by their personal rating of their own knowledge. In order to examine the hindsight bias with students who had a wider range of interest and knowledge than in the previous studies of sport, where the participants were fans attending games, the present samples were taken from the general university population rather from spectators. In addition, as mentioned earlier, sex of participant was included as a variable in the analyses (in all games but one). In all the studies, care was taken to explicitly inform participants in the postgame condition exactly what the outcome of the game was. This ensured that they knew the result when making their judgments.

Examining Hindsight Bias in the Present Studies: Design and Measurement Between 1990 and 2006, eight studies were conducted. In all of them, the focus game involved the local football team, the Bishop’s University Gaiters. In some of them, scores for other games involving Quebec universities were also investigated. In the first six studies, a between-subjects design (“hypothetical” design, Hoffrage and Pohl, 2003; Pohl et al., 2002) was employed. Here, one group of participants was contacted before a game and asked to predict the outcome by stating which team they thought would win and by estimating the number of points each team would score. A second group of participants was contacted after the game and asked to state the outcome that they would have predicted if they had been contacted before the game. The estimates from the first group are referred to as predictions and the estimates from the second group are referred to as “postdictions”. In the last two studies, a within-subjects design (“memory” design, Hoffrage and Pohl, 2003; Pohl et al., 2002) was employed. Here, a group of participants was contacted before a game and asked to predict the outcome. The same people were contacted after the game and asked to record what they had predicted before the game. The initial estimates are again referred to as predictions, but the estimates made after the game are referred to as memory recalls. In both cases, and following the shift index defined by Pohl (2007), hindsight bias would be indicated if the postgame judgments were closer to the actual outcome that pregame judgments. Previous studies of the hindsight bias in football have investigated it by comparing the difference between the team scores before the game and after the game (Leary, 1981; Roese and Maniar, 1997; Sanna and Schwarz, 2003). Hindsight bias was measured by the degree to which the score difference moved in the direction of the actual difference. Although a comparison could also have been made for the scores for each team considered separately, it has been argued that the score difference is a more appropriate statistic because the estimates for the two teams are not independent (Sanna and Schwarz, 2003). However, in the present studies, particular attention was paid to the estimated scores for the Bishop’s team, because all the participants were students at that university. In addition, it is possible to obtain evidence of a hindsight bias with each team considered separately while at the same time not having a hindsight bias for the difference scores. For example, assume the predicted score for the two teams was 30-20 (difference = +10), the actual score was 22-14 (difference = +8) and

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the estimated score after the game was 25-15 (difference = +10). Because the two difference scores are the same, there is no evidence of hindsight bias. However, the score for the first team moved from 30 to 25, which is in the direction of 22 and demonstrates a hindsight bias. Similarly, the score for the second team moved from 20 to 15, which is in the direction of 14, and also demonstrates a hindsight bias. Consequently, analyses were conducted on difference scores before and after the games but also on the estimated scores for each team before and after the games. In all the present studies, the participants were members of the university population, recruited at various locations on and off campus. In all studies except the first one, sex of participant was recorded, permitting a comparison of score estimates (and the hindsight bias) between men and women. However, although it was observed whether women and men provided different estimates for the number of points for each team (particularly in Bishop’s games), the major focus here was in whether sex was a moderating factor in the hindsight bias. As noted above, in some studies, information was also gathered about the participants’ interest in university football and their knowledge of university football. This permitted an investigation of the relationship between interest or knowledge on the one hand and score estimates (particularly hindsight bias) on the other. As with sex of participant, the major focus was on whether interest and knowledge were moderating factors in the hindsight bias rather than whether the estimates themselves differed between people who varied in interest or in knowledge. For each game, predicted scores were compared with actual scores. If they were significantly different, there is the possibility of a hindsight bias effect, because estimates made after the game could logically be closer to the actual score than those made before the game. On the other hand, if predicted and actual scores were not significantly different, a hindsight bias is excluded, because estimates made after the game could not be closer than those made before. This follows the condition established by Pohl (2007) for demonstrating hindsight bias. The point was illustrated very clearly in Leary’s (1982) study of the hindsight bias with the estimation of votes in 1980 U.S. presidential election. He found that the hindsight effect occurred in the estimates for two candidates (John Anderson, Ronald Reagan), but not for Jimmy Carter. However, in Carter’s case the pre-election (predicted) estimates were not significantly different from the actual vote, leaving no room for hindsight bas to occur.

Evaluating the Role of Surprise Measuring Surprise In addition, in the present studies, estimated score differences between teams made before the game were classified as significantly favouring the first team (a win for the first team), as not significant (as not favouring either team), or as significantly favouring the second team (a win for the second team). By comparing these classifications with the result of the game (a win for the first team or a win for the second team), it was possible to judge whether or not the outcome was surprising. As with the previous studies of the hindsight bias in sport, it was then possible to test Pezzo’s (2003) model of surprise by comparing the hindsight results with the predictions derived from his model.

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Testing Pezzo’s Model of Surprise This was accomplished using the classification scheme presented in Table 1. Predictions were first of all classified as a win for the first team, a win for neither team, or as a loss for the first team. Wins were then classified as less than 7 points, as 7 to 14 points as 14 to 21 points, or as more than 21 points Outcomes were classified as a win for the first team or a loss for the first team by less than 7 points, by 7 to 14 points, by 14 to 21 points, or by more than 21 points. For predicted wins (either the first team or the second team in the game), outcomes that matched predictions were classified as not surprising. Outcomes that did not match predictions were classified as surprising and then into various degrees of surprise. The initial classification as simply not surprising or surprising was used to test Pezzo’s (2003) model. However, it was thought that the finer distinctions might be useful because some studies show that the hindsight effect is a function of different degrees of surprise (e.g., Calvillo and Gomes, 2001; Ofir and Mazursky, 1997). For predicted nonsignificant differences (no win for either team), wins of less than 7 points were classified as not surprising. Wins of more than 7 points were classified as surprising and then into different degrees of surprise. The logic behind the different degrees of surprise was as follows. As noted above, if a win was predicted and a win occurred, it was classified as not surprising if the size of the win corresponded to the predicted size (< 7 points, 7-14 points, 14-21 points, > 21 points). If the win fell into the adjacent category (e.g., predicted win of 14-21 points and outcome a win of 7-14 points or a win of > 21 points), then it was classified as a small surprise. Wins in more distant categories were then classified as a somewhat small surprise or as a medium surprise. See the top left and bottom right segments of Table 1. Table 1. Classification Scheme for Surprise Outcome T1>T2 T121 14 >21 T1>T2 (T1 win, T2 loss) 14 ssS sS NS sS slS lS vlS exlS >21 mS ssS sS NS lS vlS exlS SH T1=T2 Not NS sS ssS mS NS sS ssS mS significant T121 lS vlS exlS SH mS ssS sS NS Note. T1 = Team 1, T2 = Team 2; NS = no surprise, sS = small surprise, ssS = somewhat small surprise, mS = medium surprise, slS = somewhat large surprise, lS = large surprise, vlS = very large surprise, exlS = extremely large surprise, SH = shock. Prediction

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As noted above, if no win for either side was predicted, then a win of less than 7 points was classified as not surprising. A win in the adjacent category (7-14 points) was then classified as a small surprise, and then wins in more distant categories were classified as a somewhat small surprise (14-21 points) or as a medium surprise (> 21 points). See the middle of the table. Finally, if a loss was predicted for a team, but that team won, or if a win was predicted for a team and that team lost, all outcomes were classified as surprising. However, the smallest reversal (predicted win or loss of less than 7 points for a team and then a loss or win of less than 7 points for that team) was classified as a somewhat small surprise. It was judged that any reversal would be more than a small surprise. In other words, the category of a small surprise was kept for predicted wins or losses than were wins or losses in an adjacent category. This practice is consistent with the claim (Pezzo, 2003) that negative outcomes are generally more surprising than positive outcomes. Returning to reversals of expectations, unexpected wins or losses were then classified as a medium surprise, a somewhat large surprise, a large surprise, a very large surprise, an extremely large surprise, or as a shock, depending on how large the difference was between the predicted size of the win or loss and the outcome. See the top right and bottom left segments of the table. For example, if Team 1 was predicted to win by more than 21 points and lost by less than 7 points, that outcome was classified as a large surprise. Bigger losses were then classified as a very large surprise (7-14 points), as an extremely large surprise (1421 points) or as a shock (> 21 points).

Testing McKelvie’s Extended Model of Surprise Thus, surprise could range from no surprise to shock, with eight degrees of surprise. To connect these nine categories with the version of Pezzo’ (2003) model of surprise that was combined with the results of studies that differentiated degrees of surprise (see above), I propose a more finely-tuned model of surprise (McKelvie’s extended model of surprise). If the result was not surprising, there would be no sense-making activity and therefore no hindsight effect. If the outcome was a small or a somewhat small surprise, sense-making activity would occur and would probably be successful because it would be easy to explain the result, leading to a hindsight effect. If the result was a medium or a somewhat large surprise, sensemaking activity would occur and may or may not be successful. If it was successful, the hindsight effect would occur and if it was not successful, the hindsight bias would not occur. If the outcome was a large or a very large surprise, sensemaking activity would occur but would probably not be successful, leading to “resultant surprise” (Pezzo, 2003) and no hindsight effect. Finally, if the outcome was an extremely large surprise or a shock, sense-making activity would occur but would probably be unsuccessful. The resultant surprise may be so strong that people would underestimate what they might have known, resulting in reversed hindsight.

Statistical Procedures Alpha was set at .05 for the decision about whether or not effects were judged to be statistically significant. However, because results for the effect of time that approached this traditional benchmark were also considered as worthy of consideration by some of the

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researchers who investigated the hindsight effect with sports materials (Ash, 2009) and sports teams (Pezzo, 2003; Tykocinski et al., 2002), trends for the effect of time that approached significance (p < .10) were treated as follows. First, a general ANOVA included time of testing (before and after the game) and team and, if the information was available, sex of participant. Second, three analyses examined the effect of time (with sex if available) on the estimates for each team considered separately and for the difference scores. Because the effect of time was the main focus of the present research, these three analyses were carried out as planned comparisons even if the interaction between time of testing and team was not significant in the initial ANOVA. In these three comparisons, if the effect of time was clearly not significant (p > .10) or clearly significant (p < .05, p = .05), no further analyses were conducted. However, it the effect of time approached significance (.05 < p < .10) when sex of participant was included as a variable, the three analyses were repeated with the data collapsed over sex of participant (i.e. three t-tests were conducted for the effect of time). At this point, if p was less than equal to .05, the effect of time was classified as significant. However, if p still fell between .05 and .10, it was considered to be not significant. For the studies in which information was available for interest or knowledge, the same strategy was followed, except that interest and knowledge were included throughout as subject variables.

Summary of the Present Studies In the discussion of each study, the major focus was on whether or not hindsight effects occurred. Implications for Pezzo’s (2003) model of surprise were also presented. In addition, the accuracy of initial estimates (prediction) was observed, to ascertain whether the hindsight effect was excluded. Finally, the subject variables of sex of participants valence, self-involvement, and expertise were considered, where relevant. For my extended model in which different levels of surprise were differentiated, discussion was postponed until all eight studies had been presented.

STUDY 1 The first study was designed to examine the hindsight effect among general undergraduate students who were asked to predict or postdict the scores in a university football game in 1990. Also tested was Pezzo’s (2003) model of surprise, according to which there would be no hindsight effect if the results were not surprising, and there might be a hindsight effect if the results were surprising. The issue of outcome valence was also pertinent, because there has been evidence that the hindsight effect is greater with a neutral outcome than with positive or negative outcomes (which did not differ) (Guilbault et al., 2004), but also that the hindsight effect is greater with positive than with negative outcomes (Pezzo and Beckstead, 2008).

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Method Participants The participants were 60 Bishop’s University undergraduate students who were recruited at various locations either on campus (e.g., in residence, in the library, in the dining hall) or off campus but close to the university (e.g., in apartments, in restaurants). Thirty were tested before the game in question and 30 were tested afterwards. Both samples were selected by convenience and participants were not assigned randomly. Sex was not recorded. Materials and Procedure The game took place on Saturday, November 17, 1990. The teams were Bishop’s University and the University of Saskatchewan. The score was 13-41 in favour of Saskatchewan. These teams were the winners of two of the four leagues in Canadian University Football and the teams were playing for the right to appear in the final national championship game for the Vanier Cup. The game was scheduled to be a home game for Bishop’s (in the town of Lennoxville, Quebec), but poor weather dictated that it had to be moved to the stadium belonging to McGill University in Montreal. This meant that the game was played at a location that was closer to Bishop’s than to Saskatchewan, but not on home turf. The first group of participants was tested on Thursday, November 15 or Friday, November 16. They were interviewed individually and asked to state which team they thought would win the upcoming football game between Bishop’s University and the University of Saskatchewan. Then they were asked to predict the number of points for each team. Replies were recorded on a standard form. The second group of participants was tested on Sunday, November 18 or Monday, November 19. They were also interviewed individually. First, they were informed of the score in the game. That is, they were told the number of points obtained by each team. Second, they were asked to state what they would have thought if they had been asked in the two days before the game to say which team would win. Then they were asked to state what they would have thought if they had been asked to predict the number of points for each team.

Results The raw data consisted of the number participants stating that Bishop’s or Saskatchewan would win and the number of points for each team. A difference score was also calculated by subtracting the number of points from Saskatchewan from the number of points for Bishop’s. Consequently a positive number indicates a win for Bishop’s and a negative number indicates a win for Saskatchewan. The mean number of points for each team and the mean difference scores before and after the game are shown in Table 2. Of the 30 participants tested before the game, 17 predicted that Bishop’s would win and 13 predicted that Saskatchewan would win (i.e., Bishop’s would lose). Of the 30 participants tested after the game, 13 stated that they would have predicted that Bishop’s would win and 17 stated that they would have predicted that Saskatchewan would win (i.e., Bishop’s would

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lose). chi square test conducted on A chi square contingency test on these counts showed that the two patterns (17, 13 before; 13, 17 after) were not significantly different. A 2 X 2 (Time X Team) mixed ANOVA with time as a between subjects variable and team as a within subjects variable was conducted on the estimated number of points for each team before and after the game. None of the effects were significant. In addition, to focus clearly on any effects of time and possible hindsight bias, planned independent samples t-tests were conducted to compare the points for each team and for the difference in points between teams before and after the game. None of the three effects of time were significant. In addition, to establish whether there was room for a hindsight bias to occur, singlesample t-tests were carried out to compare the scores before the game with the actual scores. All three tests were statistically significant: t(29) = 4.75, p < .001 (Bishop’s), t(29) = 12.16, p < .001 (Saskatchewan), and t(29) = 12.74, p < .001 (difference score). The Bishop’s score was higher than the actual number of points obtained by Bishop’s, the Saskatchewan score was lower than the actual number of points obtained by Saskatchewan, and the difference score was higher than the actual difference. Finally, to provide a framework for judging whether or not the outcome was surprising or not, the mean difference score before the game was compared to 0. A significant positive value would indicate a predicted Bishop’s win, a significant negative value would indicate a predicted Bishop’s loss, and a nonsignificant value would indicate that neither a win or a loss was predicted. This test was not significant.

Discussion The number of people predicting a Bishop’s win before the game (17/30) was slightly larger than the number of people postdicting a Bishop’s win after the game (13/30). Because Bishop’s lost the game this change is in the direction of a hindsight bias effect. However, the decline was not statistically significant. For all three points scores (Bishop’s, Saskatchewan, difference), the mean scores before the game were significantly different from the actual score. This indicates that there was room for the scores to change in the direction of the actual score, allowing for the possibility of a hindsight bias effect. In addition, the difference between the estimated team scores before the game was not significant, indicating that a win was not clearly predicted for either team. According to Table 1, Saskatchewan’s win by 28 points was classified as surprising, and more specifically a medium surprise. Of course, to people interested in Bishop’s, it would have been disappointing too. Table 2. Mean Number of Estimated Points in Each Condition in Study 1 Time Bishop’s Saskatchewan n M SD M SD Before 30 20.87 9.07 20.37 9.29 After 30 20.60 8.29 24.10 9.26 Actual Score 13 41 Note. Difference = Bishop’s estimate – Saskatchewan estimate.

Team Difference M SD +0.50 12.26 -3.50 12.78 -28

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Table 2 shows that the mean number of points for Bishop’s before the game is 20.9. The mean number after the game is slightly smaller (20.6) and closer to the actual score of 13. For Saskatchewan, the mean number of points before and after is 20.4 and 24.1 respectively. This increase is also in the direction of the Saskatchewan score of 41. Finally, the mean difference before and after is 0.5 and -3.5 respectively. The change over time is in the direction of the actual difference of -28. However, although there was room for all three original estimates to change in the direction of the actual score none of these trends was statistically significant. In short, for the postdiction score estimates, there was no evidence of hindsight bias in Study 1. The present outcome was classified as surprising (medium surprise). According to Pezzo’s (2003) model of surprise, the hindsight effect will not occur when the results are not surprising. However, the hindsight effect will occur when the results are surprising, but only if participants succeed in making sense of them. In the present case, the results were surprising but there was no hindsight effect. If Pezzo’s model is correct, this implies that participants were not able to make sense of the outcome. Perhaps the extreme disappointment of losing a very important semi-final game may have prevented the students thinking too much about it. In addition, although the evidence relating outcome valence to the hindsight effect was mixed in previous studies of sport, the present explanation of the results for surprise would be consistent with Pezzo and Beckstead’s (2008) finding that the hindsight bias is smaller with a disappointing outcome than with a happy outcome. Sex of participant was not recorded in Study 1. One reason for not replicating some of the previous reports of the hindsight bias in team sports might be that the effect is stronger in men than in women and that most of the participants in previous studies were men. Perhaps men are more interested in football than women, and therefore more self-involved. Greater self-involvement may lead to greater sense-making and consequently greater hindsight (Pezzo, 2003). On the other hand, if men are more knowledgeable about football then women, this might imply less hindsight, because hindsight has been found to be lower in experts than in nonexperts (Christensen-Szaalanski and Willham, 1991). However, it should also be recognized that, in the studies of sports, there was no evidence of a relationship between the hindsight effect self-involvement or expertise (Leary, 1981; Roese and Maniar, 1997). Nevertheless, it can be asked if the previous reports of hindsight in sports could have been due to the fact that more men than women were tested. In some cases, the number of men and women were reported, but in others they were not. In addition, results were never broken down by sex of participant. In one study (Leary, 1981), there was a similar number of men and women, in one (Roese and Manier, 1997), there were more men, in one (Bonds-Raake et al., 2001), there were more women, and in the three others (Sanna and Schwarz, 2003, Pezzo, 2003; Tykocinski et al., 2002), the numbers of men and women were not reported. Overall, from these number so men and women, it does not seem likely that previous reports of the hindsight effect in sport were due to sex of participant. However, because the results in these studies were not broken down by sex of participant, one purpose of Study 2 was to include an equal number of men and women in order to investigate any sex difference in the hindsight bias at football games. In addition, there were two experimental conditions after the game. In one, participants were told the outcome of the game and in the other no mention was made of the outcome. Knowing the outcome of the

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game is important as a condition for the hindsight effect. Providing this information ensures that people know the result. However, it is interesting to ask whether there would be evidence of bias in a general sample of people when it is not made explicit. It was expected that if the hindsight bias occurred in this study, it would be stronger in the condition in which the participants were clearly informed of the score in the match.

STUDY 2 Method Participants The participants were 71 (35 women, 36 men) Bishop’s University undergraduate students. As in Study 1, they were recruited at various locations on and off campus. Twenty four were tested before the game in question and 47 were tested afterwards. Both samples were again selected by convenience and were not assigned randomly to the pre- and postgame conditions. However, the 47 people tested after the game were assigned randomly to two test conditions (game score not specified and game score specified), with matching for sex. Materials and Procedure The game took place on Saturday, September 24, 1994. The teams were Bishop’s University and the University of Ottawa. The score was 17-23 in favour of Ottawa. The game was part of the regular season schedule and was played at home.The first group of participants was tested on Thursday, September 22 or Friday, September 23. As in Study 1, they were interviewed individually and asked to state which team they thought would win the upcoming football game. Then they were asked to predict the number of points for each team. The other two groups of participants were tested on Sunday, September 25 or Monday, September 26. Participants in the no outcome condition were asked to state what they would have thought if they had been asked in the two days before the game to say which team would win. Then they were asked to state what they would have thought if they had been asked to predict the number of points for each team. Table 3. Mean Number of Estimated Points in Each Condition in Study 2 Time n 24 24

Bishop’s M SD 21.46 10.83 18.79 8.64

Ottawa M 13.88 17.63

Before After No Outcome After 23 20.52 7.66 18.22 Outcome Actual Score 17 23 Note. Difference = Bishop’s estimate – Ottawa estimate.

SD 6.31 6.95

Difference M SD +7.58 13.63 +1.17 12.92

7.17

+2.30 -6

10.39

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Participants in the outcome condition were informed of the score after which they were asked the same two questions about the game. As in Study 1, all responses were written down on a standard form. In addition, the sex of the participant was recorded.

Results As in Study 1, the raw data consisted of the number participants stating that Bishop’s or Ottawa would win and the number of points for each team. A difference score was also calculated by subtracting the number of points from Ottawa from the number of points for Bishop’s. The mean scores in each condition are shown in Table 3. Of the 24 participants tested before the game, 19 predicted that Bishop’s would win and 5 predicted that Ottawa would win (i.e., Bishop’s would lose). Of the 24 participants tested after the game and not explicitly told the outcome, 15 stated that they would have predicted that Bishop’s would win and 9 stated that they would have predicted that Ottawa would win (i.e., Bishop’s would lose). Of the 23 participants tested after the game and explicitly told the outcome, 16 stated that they would have predicted that Bishop’s would win and 7 stated that they would have predicted that Ottawa would win. A chi square test conducted on the number of Bishop’s wins before and after the game in the two outcome conditions was not significant. Inspection of the frequencies indicated that they were similar for women and for men. A 3 X 2 X 2 (Time Condition X Sex X Team) mixed ANOVA with time and sex as between subjects variables and team as a within subjects variable was conducted on the estimated number of points for each team before the game and after the game in the two outcome conditions. Only the effect of team was significant, F(1, 65) = 5.98, p = .017. Table 3 shows that scores were higher for Bishop’s than for Ottawa. To examine the effect of time alone (without sex as a factor), three planned 3 X 2 (Time Condition X Team) ANOVAs were conducted on the Bishop’s estimates, on the Ottawa estimates and on the difference scores. One of these ANOVAs (Ottawa) showed a marginally significant effect of time condition: F(2, 65) = 2.79, p = .069. Scores were lowest before the game (mean = 13.9) and then tended to increase after the game in the no outcome condition (17.6) and in the outcome condition (18.2). Inspection of these means shows that the effect of time was slightly greater between the pre-game condition and the post-game condition in which participants were told the outcome than between the pre-game condition and the postgame condition in which they were not. Because it is more relevant to the hindsight effect to be sure that participants know the outcome, another set of analyses were performed with these two conditions. In these three 2 X 2 (Time X Sex) ANOVAs for Bishop’s, for Ottawa and for the difference scores, one effect was significant: time for Ottawa, F(1, 43) = 4.81, p = .034. Estimates were higher after the game than before the game. In addition, single-sample t-tests were conducted to compare the scores before the game with the actual scores. Two tests were statistically significant: t(23) = 7.09, p < .001 (Ottawa), and t(23) = 4.88, p < .001 (difference), and the one for Bishop’s approached significance, t(23) = 2.02, p = .056. The score for Ottawa was lower than the actual number of points and the difference score was greater than the actual difference. The Bishop’s score tended to be greater than the actual number of points. Because this could show a significant hindsight effect if the Bishop’s estimate after the game was slightly below 17 points (which was the

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actual Bishop’s score), it was considered to be significant for present purposes. Finally, the mean of the difference scores before the game was compared to 0 with a single-sample t-test. It was significant, t(23) = 2.73, p = 012, indicating that Bishop’s was predicted to win the game.

Discussion As in Study 1, there was no significant difference between the number of people predicting a Bishop’s win before the game and the number of people postdicting a Bishop’s win after the game, whether or not the people tested afterwards were told about the outcome. In all three cases (Bishop’s, Ottawa, difference), the mean scores before the game were significantly different from the actual score. This indicates that there was room for the scores to change in the direction of the actual score, allowing for the possibility of a hindsight effect. In addition, and unlike Study 1, the difference between the estimated team scores before the game was significant, indicating that a win was predicted for Bishop’s by 7.6 (8) points. According to Table 1, Ottawa’s win by 28 points was classified as surprising and, more specifically, a very large surprise (and, of course, disappointing). Table 3 shows that the mean number of points for Bishop’s before the game is 21.5. The mean number after the game is smaller (18.8) in the no outcome condition and slightly smaller (20.5) in the outcome condition, with both scores closer to the actual score of 17. For Ottawa, the corresponding number of mean number of points before and after were 13.3, 17.6, and 18.2 respectively. Both increases are in the direction of the actual Ottawa score of 23. Finally, the mean differences before and after are 7.6, 1.2 and 2.3 points respectively. Both changes over time are in the direction of the actual difference of -6. However, although there was room for all three original estimates to change in the direction of the actual score only one of these trends was statistically significant: the change for Ottawa from before the game to after the game in the outcome condition. Given that the outcome of the game was classified as surprising (a large surprise), this hindsight effect is consistent with the previous research involving sports events and, possibly, with Pezzo’s (2003) model of surprise. In the previous studies in which sporting outcomes were judged, it was found that when the outcome was surprising, there was a hindsight effect. At the same time, it should be noted that present outcome was classified as a large surprise. Two reports with non-sports studies found that the hindsight effect was reversed when the outcome was highly surprising (Calvillo and Gomes, 2011; Ofir and Mazursky, 1997). Although the previous and present classifications were not on a common scale, it might have been expected that the hindsight effect would be reduced with high surprise. Notably, this is what happened for the Bishop’s score and the difference score, where the hindsight effect did not occur. In addition, the defeat would have been disappointing for Bishop’s students. Past research has shown that the hindsight effect is smaller for selfrelevant negative outcomes than for self-relevant positive outcomes (Pezzo and Beckstead, 2008). Perhaps the results for Bishop’s and Ottawa can be fitted to Pezzo’s sense-making model as follows. Hindsight occurred with Ottawa because participants tried to make sense of their high score, and succeeded. However, hindsight did not occur with Bishop’s because, as in Study 1, participants did not wish to think too much about their disappointing score. Of

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27

course, this reasoning is speculative because participants were not asked about their deliberations when making their postdictive estimates. Finally, sex of participant was not significant at any point in the analysis. This contradicts the suggestion made above that the hindsight bias might be stronger for men than for women because men were more interested (had greater self-involvement) or that it might be weaker in men because they were more knowledgeable. Consequently, in the next study, sex was again examined, but personal interest in football was also measured. It was speculated that the hindsight effect might be more likely to occur to people who were more interested because the outcome would be more self-relevant to them. Knowledge of football was also measured in Study 3. From previous research (Christensen-Szaalanski and Willham, 1991; Gray, et al., 2007), it was speculated that the hindsight effect might be more likely to people who had less knowledge (were less expert). At the same time, it should be noted that there was no effect of expertise on the hindsight effect in one football game study (Roese and Maniar, 1997).

STUDY 3 Method Participants The participants were 88 (44 women, 44 men) Bishop’s University undergraduate students, again sampled by convenience on and off campus. Forty four were tested before the game and 44 were tested afterwards. The two groups were not assigned randomly to the preand post-game conditions but they were matched for sex of participant. Materials and Procedure This regular season home game between Bishop’s University and Queen’s University took place on Saturday, October 5, 1996. The score was 13-21 in favour of Queen’s. On Thursday, October 3 or Friday, October 4 before the game or on Sunday October 6 and Monday October 7 after the game, participants made estimates in the same manner as in Studies 1 and 2. Before providing their postdictive judgments, those tested after the game were informed of the number of points for each team. After making their judgments, they rated their personal interest in university football on a scale from 0 to 6 where 0 was labeled no interest at all, 4 was labeled moderately interested and 6 was labeled extremely interested. Finally, they were told that before the present game, Bishop’s had played four games and Queen’s had played five, and they were asked to state what they thought the win-loss record was for each team. A correct response for each record was awarded 1 point so that the possible scores were 0, 1, or 2.

Results Again, the raw data consisted of the number of participants stating that Bishop’s or Queen’s would win and the number of points for each team.

28

Stuart J. McKelvie Table 4. Mean Number of Estimated Points in Each Condition in Study 3

Bishop’s Queen’s n M SD M Before 44 25.93 11.84 21.43 After 44 22.05 8.81 18.52 Actual Score 13 21 Note. Difference = Bishop’s estimate – Queen’s estimate. Time

SD 14.55 7.05

Difference M +4.50 +3.52 -8

SD 15.94 10.93

The difference score was also calculated by subtracting the number of points from Queen’s from the number of points for Bishop’s. The mean scores in each condition are shown in Table 4. Of the 44 participants tested before the game, 31 predicted that Bishop’s would win and 13 predicted that Queen’s would win (i.e., Bishop’s would lose). Of the 44 participants tested after the game, 30 stated that they would have predicted that Bishop’s would win and 14 stated that they would have predicted that Queen’s would win (i.e., Bishop’s would lose). A chi square test conducted on the number of Bishop’s wins before and after the game in the two outcome conditions was not significant. Frequencies were similar for women and for men. A 2 X 2 X 2 (Time X Sex X Team) mixed ANOVA with time and sex as between subjects variables and team as a within subjects variable was conducted on the estimated number of points for each team before the game and after the game. The only significant effect was team, F(1, 84) = 7.42, p = .008. Table 4 shows that scores were higher for Bishop’s than for Queen’s. The next step was to conduct 2 X 2 (Time X Sex) ANOVAs on the Bishop’s scores, the Queen’s scores and the difference scores. For Queen’s and for the difference score, none of the effects were significant. However, for Bishop’s, the effect of time approached significance, F(1, 84) = 3.00, p = .087. Scores tended to decline over time. In accordance with the strategy outlined earlier, the scores were collapsed over sex and an independent samples t-tests was conducted for the effect of time. Once more, it approached significance, t(86) = 1.75, p = .084. However, and again following the strategy outlined above, this effect was classified as not significant. In addition, as in Studies 1 and 2, single-sample t-tests were conducted to compare the scores before the game with the actual scores. Two tests were statistically significant: t(43) = 7.24, p < .001 (Bishop’s), and t(43) = 5.20, p < .001 (difference). The Bishop’s score was higher than the actual number of points and the difference score was higher than the actual difference. A comparison of the mean difference score before the game to 0 approached significance, t(43) = 1.87, p = 068, suggesting a predicted win for Bishop’s.

Interest and Knowledge Scores for interest and knowledge were almost significantly related, r(N = 88) = .189, p = .078. However, when this relationship was examined with a one-way ANOVA with the three levels of knowledge as the independent variable, it was not significant. Sex differences in interest and knowledge were also examined.

29

Hindsight Bias

For interest, men scored higher than women, t(86) = 2.81, p = .006. For knowledge, the effect of sex was not significant. See descriptive statistics in Table 5. The subject variable of interest was examined by assigning people with score of 4 or more out of 6 (at least moderate interest) to the higher group and those with a score of 2 or less out of 6 to the lower group. That is, data were not considered from people who chose 3. A 2 X 2 X 2 X 2 (Time X Interest X Sex X Team) mixed ANOVA was then conducted on the estimated number of points for each team. The only significant effect was team, F(1, 65) = 5.08, p = .028. Then, for Bishop’s, for Queen’s and for the difference scores, 2 X 2 X 2 (Time X Interest X sex) ANOVAs were conducted. For Bishop’s, the effect of time approached significance, F(1, 80) = 3.88, p = .052. Finally, for the interest analysis, to examine whether there might be an effect of time for people with different levels of interest when the data were collapsed over sex, three 2 X 2 (Time X Interest) between groups ANOVAs were conducted. However, there were no significant effects. The three levels of knowledge (higher = 2, moderate = 1, lower = 0) were examined with a 2 X 3 X 2 X 2 (Time X Knowledge X Sex X Team) mixed ANOVA. Again, the only significant effect was team, F(1, 76) = 7.64, p = .007. Table 5. Sex Differences in Interest and Knowledge in All Studies Women n M

SD

Men n

M SD Study 3 (1996) Interest 44 2.88 1.43 44 3.75 1.60 1 Knowledge 44 1.05 0.78 44 1.14 0.80 Study 5 (1999) Interest 123 2.51 1.75 124 3.67 1.87 Knowledge1 123 0.78 0.71 124 1.17 0.82 Study 6 (2002) Interest 68 2.72 1.79 69 3.32 1.89 Knowledge1 69 1.41 0.67 70 1.47 0.61 Study 7 (2003) Bishop’s Interest 27 3.00 1.93 23 3.81 2.00 Other Interest 27 1.26 1.63 23 2.89 2.22 Knowledge2 27 1.61 1.27 23 3.22 2.01 Study 8 (2006) Bishop’s Interest 39 2.53 1.73 35 3.14 2.00 Other Interest 39 1.13 1.45 35 1.49 1.50 Knowledge1 38 0.92 0.75 35 1.26 0.74 Knowledge2 38 3.18 2.63 35 4.20 2.76 3 Knowledge 38 3.68 1.12 35 4.06 1.59 Notes. *p = .058. Maximum score = 6 (interest), 2 (knowledge1: win-loss record in Bishop’s game), 6 (knowledge2: subjective rating of Quebec university football), 6 (knowledge3: win-loss record of all Quebec teams).

30

Stuart J. McKelvie

In the subsequent three 2 X 3 X 2 (Time X Knowledge X Sex) ANOVAs, one for each team and one for the difference scores, only one effect was significant: the three-way interaction for Bishop’s, F(2, 76) = 5.70, p = .005. For the six effects of time, trends were different (see Table 6): scores tended to be higher after the game than before in one case (women with the lowest level of knowledge), very similar in two cases (men with the middle and the highest level of knowledge), and tended to be higher before the game than after in three cases (men with the lowest level of knowledge and women with intermediate and the highest levels of knowledge). However, only one of these comparisons was significant: the higher scores before the game for women with an intermediate level of knowledge, t(16) = 2.52, p = 023. The corresponding descriptive statistics were as follows: M = 30.33, SD = 10.46 (before) and M = 18.33, SD = 9.70 (after). Finally, as with interest, the data were collapsed over sex and three 2 X 3 (Time X Knowledge) ANOVAs were conducted. Again, there were no significant effects.

Discussion As in Studies 1 and 2, there was no significant difference between the number of people predicting a Bishop’s win before the game and the number of people postdicting a Bishop’s win after the game. The same result occurred for men and for women. Therefore, in terms of win counts, there was no evidence of hindsight bias. In two cases (Bishop’s estimate, difference score), the mean scores before the game were significantly different from the actual score. This indicates that there was room for the scores to change in the direction of the actual score, allowing for the possibility of a hindsight effect. However, this was not the case for Queen’s, where the estimated score before the game was not significantly different from the actual score, thereby precluding any hindsight effect. In addition, the difference between the estimated team scores before the game was almost significant, indicating that a win was predicted for Bishop’s by 7.6 (8) points. Table 6. Mean Number of Estimated Points for Bishop’s by Women and Men in Each Interest Condition in Study 3 Knowledge and Time n Higher Knowledge Before 7 After 7 Moderate Knowledge Before 9 After 9 Lower Knowledge Before 6 After 6 Actual Score

Women

Men M

M

SD

n

29.86 21.00

12.93 7.30

7 10

21.00 21.90

9.40 7.49

30.33 18.33

10.46 9.70

8 8

20.25 22.75

5.70 11.02

19.67 28.67

8.21 9.97

7 4

33.14 21.25

17.07 2.06

13

SD

Hindsight Bias

31

Whether or not this is considered as significant, the 8-point win by Queen’s can be classified as surprising. If it is considered to be not significant, meaning that neither team was expected to win, Table 1 indicates that the Queen’s win by more than 7 points is a small surprise. If it is considered to be significant, Table 1 indicates that the Queen’s win is a somewhat large surprise. Perhaps it is best to err on the side of caution and classify the predicted win as not significant, but classify the outcome as somewhat small rather than simply small. Table 4 shows that the mean number of points for Bishop’s before the game is 25.9. The mean number after the game is smaller (22.1) and closer to the actual score of 13, which demonstrates a hindsight trend. For Queen’s, the corresponding number of mean number of points before and after were 21.4 and 18.5 respectively. This decline is in the direction of the actual Queen’s score of 21, but because the original score is not significantly difference from 21 (meaning that there is no room for the hindsight effect to occur), the resulting score is actually further away from 21 than the original one. Finally, the mean differences before and after are 4.5 and 3.5 and the decline is in the direction of the actual difference of -8. In fact, none of the three trends was statistically significant, although the decline for Bishop’s approached significance. Given that the outcome of the game was surprising (with the decision of somewhat small to medium), the marginally significant hindsight trend for Bishop’s is consistent with the previous research involving actual sports events. If treated as evidence of hindsight, it can be accounted for in Pezzo’s model by assuming that participants were able to make sense of the outcome. However, the present outcome, like the outcomes in Studies 1 and 2, was unpleasant for Bishop’s students, and there was no evidence of hindsight in these two studies. Perhaps it is more parsimonious to treat the Bishop’s trend as not significant, which was the case in Studies 1 and 2. Indeed, the present result with the difference score is not significant. According to Pezzo’s (2003) model, this suggests the moderate surprise was accompanied by a failure to make sense of the disappointing result, as in Studies 1 and 2. Also, as in Study 2, sex of participant was not significant at any point in the analysis. In addition, the present results do not support suggestion that the hindsight effect might be stronger for people who had more interest in university football or who had less knowledge about it. Notably, Leary’s (1981) investigation of the hindsight effect in sport also failed to detect this relationship. One advantage of the present study is that a wider range of interest and knowledge were represented than in previous studies because the participants were not simply fans who were attending game. This indicates that the present absence of a relationship is not simply due to a restriction of range, which was the problem that Sanna and Schwarz (2003) encountered with their ratings of subjective knowledge. In the first three studies, the only significant evidence of the hindsight bias occurred in Study 2 for the number of points for Ottawa when it was the opposing team. Although this result was not replicated in Study 3, the original score estimate for the opposing team (Queen’s) was accurate, indicating that there was no room for the hindsight effect to occur. The purpose of Study 4 was to conduct another investigation of the hindsight effect when Ottawa was the opposing team. In this case, the game was played away rather than at home.

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Stuart J. McKelvie

STUDY 4 Method Participants The participants were 54 (30 women, 24 men) Bishop’s University undergraduate students recruited as before. Twenty nine were tested before the game and 25 were tested after. Materials and Procedure The regular season game took place between Bishop’s and Ottawa on Saturday, October 24, 1998 and was held in Ottawa. The score was 25-28 in favour of Ottawa. Participants were tested on Thursday, October 22 or Friday, October 23 before the game on Sunday, October 26 or Monday October 27 after the game. As in Studies 1 to 3, they made predictions or postdictions for which team would win and for the number of points for each team. Before providing their estimates, participants tested after the game were informed of the score.

Results Of the 28 participants tested before the game, 20 predicted that Bishop’s would win and 8 predicted that Ottawa would win (i.e., Bishop’s would lose). Of the 25 participants tested after the game, 17 stated that they would have predicted that Bishop’s would win and 8 stated that they would have predicted that Ottawa would win (i.e., Bishop’s would lose). A chi square test conducted on the number of Bishop’s wins before and after was not significant. Frequencies were similar for women and for men. The mean scores in each condition are shown in Table 7. A 2 X 2 X 2 (Time X Sex X Team) mixed ANOVA was conducted on the estimated number of points for each team before the game and after the game. Two effects were significant: team F(1, 50) = 6.43, p = .014, and sex, F(1, 50) = 4.63, p = .036. Scores were higher for Bishop’s than for Ottawa and were also generally higher for men than for women. Because the major issue here was whether sex moderated the hindsight effect, the means for the main effect of sex are not shown. However, it is noted below that the sex difference occurred for Ottawa, not Bishop’s. Table 7. Mean Number of Estimated Points in Each Condition in Study 4 Bishop’s Ottawa n M SD M Before 29 22.79 8.80 19.45 After 25 18.68 6.12 17.56 Actual Score 25 28 Note. Difference = Bishop’s estimate – Ottawa estimate. Time

SD 7.70 8.31

Difference M SD +3.21 12.16 +1.12 11.66 -3

Hindsight Bias

33

As before, 2 X 2 (Time X Sex) ANOVAs were conducted for each team separately and for the difference scores. For Bishop’s, the effect of time approached significance, F(1, 50) = 3.86, p = .055. Scores tended to be higher before the game than after the game. For Ottawa, the effect of sex was significant, F(1, 50) = 4.23, p = .045. Men scored higher than women. For the difference scores, none of the effects was significant. Finally, because the effect of time for Bishop’s approached significance, a simple comparison for the effect of time collapsed over sex was conducted. It also approached significance, t(52) = 1.96, p = .055. In accordance with the strategy outline earlier, this effect was deemed to be not significant. In addition, single-sample t-tests were conducted to compare the scores before the game with the actual scores. Two tests were statistically significant: t(23) = 5.98, p < .001 (Ottawa), and t(23) = 2.75, p = .01 (difference). The score for Ottawa was lower than the actual number of points and the difference score was greater than the actual difference. Finally, a singlesample t-test comparing the mean of the pre-game difference scores to 0 was not significant, indicating that neither side was expected to win.

Discussion As in the first three studies, there was no significant difference between the number of people predicting a Bishop’s win before the game and the number of people postdicting a Bishop’s win after the game. The same result occurred for both women and men. In two cases (Ottawa estimate, difference score), the mean scores before the game were significantly different from the actual score, indicating that there was room for the scores to change in the direction of the actual score, allowing for the possibility of a hindsight bias effect. However, this was not the case for Bishop’s, which therefore precluded a hindsight effect. In addition, and like Study 1, the difference between the estimated team scores before the game was not significant, indicating that neither side was predicted to win. According to Table 1, Ottawa’s narrow win by only 3 points was classified as not surprising (although probably somewhat disappointing). Table 5 shows that the mean number of points for Ottawa before and after the game were 19.4 and 17.6, which indicates that the score tended to move away from the actual number of points (28). The mean differences before and after were 3.2 and 1.1 points respectively, a change that is in the direction of the actual difference of -3. Neither of these effects over time was significant, thus not providing any evidence of hindsight bias. Indeed, the trend for Ottawa is in the opposite direction. The marginally significant change in scores over time for Bishop’s is difficult to interpret as a hindsight effect because the predicted score was close to the actual score. However, the main outcome of Study 4 is that there was no evidence of hindsight bias. Thus, the effect for Ottawa in Study 2 was not replicated. With reference to the issue of surprise, the present results of no hindsight are consistent with Pezzo’s sense-making model according to which participants do not feel the need to make sense of a result that is not surprising. They are also consistent with the finding that the hindsight bias is reduced when the outcome is negative (Pezzo and Beckstead, 2008). Finally, sex of participant was not significant as a factor at any point in the analysis of the hindsight effect, which is consistent with the results of the first three studies. However, it was noted earlier that other subject variables such as interest or knowledge may be more likely to

34

Stuart J. McKelvie

be associated with hindsight. Although this did not occur in Study 3, these possibilities were reexamined in Study 5 by once again comparing estimates for people classified as higher and lower in interest and higher or lower in knowledge. The role of interest in university football was also investigated in another way in Study 5. In Studies 1 to 4, it was assumed that the participants, who were undergraduate students at Bishop’s university, would vary in their interest in and knowledge about university football. However, because the university is a small institution that has historically supported its football team, many students are likely to have a special interest in the local team. That is, they would be self-involved. The degree to which hindsight might occur when that kind of interest is low or even absent was examined by asking participants to also provide judgments for other games that were played the same day. Most participants would probably have very little personal involvement in or allegiance to these teams. From the arguments presented in this paper, it might be expected that the hindsight effect would be lower with the other games than with the Bishop’s game. However, including other games also provided an opportunity to examine the relationship between valence and the hindsight effect that was found by Guilbault et al. (2004) in their meta-analysis: the hindsight effect was greater for neutral outcomes than for positive or negative outcomes. From this result, it can be predicted that the effect would be greater for the games with other teams than for the Bishop’s game, whether or not Bishop’s won or lost. At the same time, people who were interested in university football in general would probably be aware of the implications of these other results for league standings. Together, these considerations suggest that the effect of interest might be a significant factor in the hindsight effect not only for the Bishop’s game, but also for the other games not involving Bishop’s. Another interesting feature of Study 5 is that, as in Study 3 where interest and knowledge were included as subject variables, the opposing team was Queen’s University. In that study, there was some weak evidence of a hindsight effect for Bishop’s in terms of a marginally significant difference between pregame and postgame estimates. To increase power, and perhaps detect weaker hindsight effects as significant, the number of participants in Study 5 was much greater than those in Studies 1 to 4.

STUDY 5 Method Participants The participants were 243 (121 women, 122 men) Bishop’s University undergraduate students, recruited as before. One hundred and twenty three were tested before the game and 120 were tested afterwards. The two groups were not assigned randomly to the pre- and postgame conditions but they were matched for sex of participant. Materials and Procedure This regular season home game between Bishop’s University and Queen’s University took place on Saturday, October 2, 1999. The game was played away at Queen’s. The score was 35-14 in favour of Bishop’s.

35

Hindsight Bias

On Thursday, September 30 or Friday, October 1 before the game or on Sunday October 3 or Monday October 4 after the game, participants made estimates in a similar manner as in the first four studies. That is, before the game, they stated which team they thought would win and they stated what they thought the score would be. Before providing their postdictive judgments, participants tested after the game were informed which team had won after which they stated which team they would have chosen to win if they had been asked before the game. Then they were told the score in the game and after which they stated what they thought the score would have been and what they would have said if they had been asked before the game. After making their judgments for Bishop’s and for Queen’s (whether predictive or postdictive), participants rated their personal interest in university football on the scale from 0 to 6 where 0 was labeled no interest at all, 4 was labeled moderate and 6 was labeled extremely interested. Then they were told that before the present game, Bishop’s had played four games and Queen’s had played five, and they were asked to state what they thought the win-loss record was for each team. As before, a correct response for each record was awarded 1 point so that the score ranged from 0 to 2. Two other games in Quebec university football were played on October 2. In one, Concordia University beat McGill University 45-0. In the other, the University of Ottawa beat Université Laval 34-27. After they had answered the questions about the Bishop’s game and about their interest and knowledge, participants provided estimates for the number of points for each team before the games (what they thought the scores would be) or after the games (what they would have thought and said if they had been asked before the games).

RESULTS Bishop’s Game General Hindsight Bias Of the 123 participants tested before the game, 69 predicted that Bishop’s would win and 54 predicted that Queen’s would win (i.e., Bishop’s would lose). Of the 120 participants tested after the game, one did not respond. Of the remaining 119, 71 stated that they would have predicted that Bishop’s would win and 48 stated that they would have predicted that Queen’s would win (i.e., Bishop’s would lose). A chi square test conducted on the number of Bishop’s wins before and after the game in the two outcome conditions was not significant. Frequencies were similar for women and for men. Table 8. Mean Number of Estimated Points in Each Condition for the Bishop’s Game in Study 5 Bishop’s Queen’s n M SD M Before 29 22.79 8.80 19.45 After 25 18.68 6.12 17.56 Actual Score 35 14 Note. Difference = Bishop’s estimate – Queen’s estimate. Time

SD 7.70 8.31

Difference M SD +3.21 12.16 +1.12 11.66 +21

36

Stuart J. McKelvie

The mean scores in each condition for the Bishop’s game are shown in Table 8. A 2 X 2 X 2 (Time X Sex X Team) mixed ANOVA with time and sex as between subjects variables and team as a within subjects variable was conducted on the estimated number of points for each team before the game and after the game. None of the effects was significant. In addition, 2 X 2 (Time X Sex) ANOVAs were conducted on the predicted scores, the postdicted scores and the difference scores. None of these effects was significant either. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. All three tests were statistically significant: t(122) = 11.57, p < .001 (Bishop’s), t(123) = 7.44, p < .001 (Queen’s) and t(123) = 12.96, p < .001 (difference). The Bishop’s score was lower than the actual number of points, the Queen’s score was lower than the actual number of points, and the difference score was higher than the actual difference. A comparison of the mean difference score before the game to 0 was not significant, indicating no preference for either team.

Interest and Knowledge as Moderators Scores for interest in university football and knowledge of records for Bishop’s and Queen’s were significantly related, r(N = 247) = .408, p < .001. A one way ANOVA of interest scores with the three levels of knowledge as the independent variable was significant: F(2, 244) = 26.16, p < .001. A post hoc Scheffé test showed that the interest scores were higher for knowledge levels 2 than for knowledge levels 0 and 1, which did not differ from each other. Sex differences were examined for interest scores and for knowledge scores. In both cases, men scored significantly higher than women. For interest, t(245) = 5.00, p < .001, and for knowledge, t(245) = 4.05, p < .001. See Table 5. The subject variable of interest was examined by assigning people with score of 4 or more out of 6 (at least moderate interest) to the higher group and those with a score of 2 or less out of 6 to the lower group. That is, as before, data were not considered from people who chose 3. A 2 X 2 X 2 X 2 (Time X Interest X Sex X Team) mixed ANOVA was then conducted on the estimated number of points for each team. The interaction between interest and team was significant, F(1, 210) = 20.72, p < .001. This occurred because participants with greater interest in university football estimated higher scores for Bishop’s (M = 24.08, SD = 9.82) than for Queen’s (M = 21.06, SD = 12.82), whereas participants with less interest estimated lower scores for Bishop’s (M = 19.36, SD = 12.90) than for Queen’s (M = 25.75, SD = 14.31). This also meant that estimated scores for Bishop’s were higher for people with more interest than for people with less interest and that estimated scores for Queen’s were higher for people with less interest than for people with more interest. In addition, there was a significant three-way interaction between time, interest, sex, F(1, 210) = 8.52, p = .004. Inspection of the mean scores in each condition indicated that scores were higher after the game than before the game for both lower interest women and higher interest men, whereas they were lower after the game than before the game for both higher interest women and lower interest men. To find out if these trends occurred for each team and for the difference scores, three separate 2 X 2 X 2 (Time X Interest X Sex) ANOVAs were conducted. For Bishop’s, there

37

Hindsight Bias

was a significant effect of interest, F(1, 210) = 12.18, p = .001. Scores were higher for people with higher interest (M = 24.80, SD = 9.82) than for people with lower interest (M = 19.36, SD = 12.90). For Queen’s, there was also a significant effect of interest, F(1, 210) = 9.93, p = .002, but it was accompanied by a significant interaction between time, interest and sex, F(1, 210) = 6.85, p = .01. These results are shown in Table 9. For lower interest, scores for women seem to be higher after the game than before, whereas scores for men seem to be higher before the game than after. For higher interest, scores seem to be similar before and after the game. However, post hoc t-tests were not significant for any of the four comparisons over time. It can also be seen from Table 9 that the score for lower interest men (M = 32.9) seems to be higher than any of the others (22.0, 22.9, 28.8) before the game, but was similar to them after (24.7, 26.7, 19.6, 21.9). To examine these trends, two 2 X 2 (Interest X Sex) ANOVAs were conducted on scores before the game and after the game. Before the game, there was a significant effect of interest, F(1, 110) = 6.57, p = .012, and a significant interaction between interest and sex, F(1, 110) = 8.52, p = .004. Scores were higher for lower interest than for higher interest, but only for men. After the game, none of the effects were significant. That is, men had a higher estimate before the game but not after the game. For difference scores, the effect of interest was significant: F(1, 210) = 18.11, p < .001. Scores were higher for people with more interest (M = 4.27, SD = 14.93) than for people with less interest (M = -5.38, SD = 20.51). That is, people with more interest favoured Bishop’s and people with less interest favoured Queen’s. Turning to the effect of knowledge, a 2 X 3 X 2 X 2 (Time X Knowledge X Sex X Team) mixed ANOVA showed the knowledge X team interaction was significant: F(2, 231) = 7.65, p = .001. Participants with the most knowledge (score of 2) estimated higher scores for Bishop’s (M = 25.03, SD = 10.42) than for Queen’s (M = 17.68, SD = 10.77), whereas participants with both intermediate knowledge (score of 1) and the least knowledge (score of 0) estimated lower scores for Bishop’s (M = 21.24, SD = 12.15 for intermediate; M = 21.04, SD = 12.79 for lowest) than for Queen’s (M = 25.80, SD = 12.69 for intermediate; M = 24.87, SD = 14.05 for lowest). This analysis was followed up with 2 X 3 X 2 (Time X Knowledge X Sex) ANOVAs on the scores for Bishop’s alone, for Queen’s alone and for the difference score. Table 9. Mean Number of Estimated Points by Women and Men in Each Interest Condition for Queen’s in Study 5 Interest and Time n Higher Interest Before 24 After 17 Lower Interest Before 31 After 15 Actual Score

M

Women SD

n

Men M

SD

22.92 19.59

12.12 12.99

44 32

18.18 21.84

10.00 12.87

22.00 26.70

13.28 13.85 14

32 22

32.93 24.73

18.93 11.44

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Stuart J. McKelvie

Table 10. Mean Number of Estimated Points by Women and Men in Each Knowledge Condition for Queen’s in Study 5 Knowledge Highest Intrermediate Lowest

n 20 54 47

M 21.50 24.74 22.79

Women SD 11.95 12.77 13.94

n 53 37 32

Men M 16.25 27.35 27.94

SD 10.03 12.57 13.87

n 73 91 79

Total M 17.68 25.80 24.87

SD 10.77 12.69 14.05

Table 11. Mean Estimated Number of Points in Each Condition for Other Games in Study 5 Time

Concordia McGill Difference M SD M SD M SD 26.36 10.91 18.46 10.78 +7.86 14.27 25.74 11.69 18.10 13.86 +7.71 19.77 45 0 +45 Laval Ottawa Difference Before 123 20.12 12.69 25.15 12.95 -4.78 14.41 After 124 23.10 12.76 23.35 12.41 -0.90 17.48 Actual Score 27 34 -7 Note. Differences = Concordia estimate – McGill estimate, Laval estimate – Ottawa estimate. n Before 123 After 124 Actual Score

For Bishop’s, there were no significant effects. For Queen’s, the effect of knowledge was significant, F(2, 231) = 5.81., p = .003, and it was accompanied by a significant interaction between knowledge and sex, F(2, 231) = 3.32, p = .038. Overall, post hoc Scheffé tests showed that estimated scores were lower for people with most knowledge than for this with less knowledge, but this only held for men. See Table 10. For difference scores, there was a significant main effect of knowledge, F(2, 231) = 6.03, p = .003. From post hoc Scheffé tests, scores were significantly higher (M = 6.89, SD = 16.49) for people with the highest level of knowledge than for people with an intermediate level (M = -3.90, SD = 18.14) or the lowest level of knowledge (M = -2.68, SD = 18.69). That is, people with higher knowledge favoured Bishop’s over Queen’s, where people with intermediate and lower knowledge favoured Queen’s over Bishop’s.

Other Games The estimated scores for the two other games (Concordia-McGill, Laval-Ottawa) were treated in the same manner as the scores for the Bishop’s-Queen’s game, with the exception that knowledge was not included as a subject variable because it referred only to the Bishop’s game. For both games, the chi square tests showed no significance for the number of people predicting and postdicting wins and losses, and frequencies were similar for men and for women.

39

Hindsight Bias Table 12. Mean Estimated Number of Points by Women and Men in Each Interest Condition for Concordia-McGill Game in Study 5

Sex Women Men Interest Higher Lower

n

Concordia M SD

McGill M SD

Difference M SD

123 124

24.49 27.60

11.72 10.67

19.42 17.15

12.06 12.67

7.86 7.71

14.27 19.77

119 101

28.68 22.12

11.02 10.97

16.39 20.51

11.63 13.39

12.16 1.80

18.31 15.40

Concordia-McGill: General Hindsight Bias For the game between Concordia and McGill (see Table 11), the 2 X 2 X 2 (Time X Gender X Team) mixed model ANOVA yielded two significant effects: team, F(1, 243) = 50.47, p < .001, and the interaction between gender and team, F(1, 243) = 6.10, p = .014. Scores were higher for Concordia than for McGill, and this effect was stronger for men than for women (see Table 12). Scores for Concordia alone, McGill alone and the differences alone were examined with 2 X 2 (Time X Sex) ANOVAs. For Concordia (see Table 12), the effect of sex was significant, F(1, 243) = 4.75, p = .03. Men estimated more points than women. For McGill, none of the effects were significant. For difference scores (Concordia – McGill), sex was significant, F(1, 243) = 5.46, p = .02. Men estimated a higher score difference in favour of Concordia than women. These means are not reported because they do not involve a hindsight effect. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. For the Concordia-McGill game, all three tests were statistically significant: t(246) = 26.38, p < .001 (Concordia), t(246) = 23.17, p < .001 (McGill) and t(246) = 33.98, p < .001 (difference). The Concordia mean score was lower than the actual number of points, the McGill mean score was higher than the actual number of points, and the mean difference score was lower than the actual difference. A comparison of the mean difference score before the game to 0 was also significant, t(246) = 7.11, p < .001, indicating a preference for Concordia. Concordia-McGill: Interest as Moderator Another set of analyses were conducted with interest as a subject variable. Knowledge was not considered because it only reflected knowledge for the record of the teams in the Bishop’s game. For Concordia vs. McGill, a 2 X 2 X 2 X 2 (Time X Interest X Sex X Team) mixed model ANOVA showed that there were two significant effects: team, F(1, 212) = 30.94, p < .001, and the interaction of interest and team, F(1, 212) = 14.67, p < .001. Scores were higher for Concordia than for McGill, and this effect was much stronger for participants who were higher than interest than for those who were lower in interest (see Table 12). For Concordia alone, the 2 X 2 X 2 (Time X Interest X Sex) showed a significant effect of interest, F(1, 212) = 13.86, p < .001. Scores were higher for participants who were higher than interest than for those who were lower in interest. For McGill alone, none of the effects were significant. For the difference scores, the effect of interest was significant, F(1, 212) =

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13.92, p < .001. The difference in favour of Concordia was higher for participants who were higher in interest than for those who were lower in interest. See Table 12. None of the effects involving time were significant.

Laval-Ottawa: General Hindsight Effects For the game between Laval and Ottawa, the 2 X 2 X 2 (Time X Gender X Team) mixed model ANOVA yielded two significant effects: team, F(1, 243) = 6.35, p = .012, and the interaction between time and team, F(1, 243) = 5.17, p = .024. Scores were higher for Ottawa than for Laval, and this effect only occurred before the game (see Table 11). Scores for Laval alone, Ottawa alone and the differences alone were examined with 2 X 2 (Time X Sex) ANOVAs. For Laval, the effect of time approached significance, F(1, 243) = 3.38, p = .067. In accordance with the strategy followed earlier, the data were collapsed over sex and compared for time. Here, t(243) = 1.84, p = .067. Again following the previous guideline, this effect was not significant. For Ottawa, none of the effects were significant. However, for difference scores (Laval – Ottawa), the effect of time approached significance, F(1, 243) = 3.59, p = .059. Collapsing over sex, t(243) = 1.90, p = .058, which is not significant. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. All three tests were statistically significant: t(246) = 6.62, p < .001 (Laval), t(246) = 12.08, p < .001 (Ottawa) and t(246) = 4.06, p < .001 (difference). The Laval mean score was lower than the actual number of points, the Ottawa mean score was lower than the actual number of points, and the mean difference score was higher (less negative) than the actual difference. A comparison of the mean difference score before the game to 0 was also significant, t(246) = 2.76, p < .001, indicating a preference for Ottawa. Laval-Ottawa: Interest as Moderator For Laval vs. Ottawa, a 2 X 2 X 2 X 2 (Time X Interest X Sex X Team) mixed model ANOVA showed that there were two significant effects: team, F(1, 212) = 4.91, p = .028, and the interaction between time and team, F(1, 212) = 3.96, p < .048. These results were the same as were found above in the analysis without interest as a factor. For Laval alone, the 2 X 2 X 2 (Time X Interest X Sex) showed a significant effect of time, F(1, 212) = 4.41, p = 037. Again, this was the same pattern as shown earlier: Scores were higher after the game than before the game. None of the effects for Ottawa alone or for the difference scores were significant.

Discussion Bishop’s Game As in the first four studies, there was no significant difference between the number of people predicting a Bishop’s win before the game and the number of people postdicting a Bishop’s win after the game, for either men or for women. For all three measures based on the number of points estimated (Bishop’s score, Queen’s score, difference score), the mean scores before the game were significantly different from the actual score. This indicates that there was room for the scores to change in the direction of

Hindsight Bias

41

the actual score, allowing for the possibility of a hindsight effect. In addition, the difference between the estimated team scores before the game was not significant. That is, neither team was predicted to win. According to Table 1, the Bishop’s win by 21 points would be classified as a surprise and, more specifically, a somewhat small surprise. Note, however that 21 points was exactly on the border of the categories 14-21 and > 21. If it is considered to be in the latter category, the Bishop’s win would be classified as a medium surprise. Table 7 shows that the mean number of points for Bishop’s before the game is 22.8. The mean number after the game is smaller (18.7) and further away from the actual score of 35. For Queen’s, the corresponding number of mean number of points before and after were 19.5 and 17.6 respectively. This decline is in the direction of the actual Queen’s score of 14, but is not significant. Finally, the mean differences before and after the game are 3.2 and 1.1, but the decline is in the direction away from the actual difference of 21. In short, there was no evidence of the hindsight effect with the Bishop’s game. In particular, there was no support for the suggestion that the marginally-significant hindsight trend for the Bishop’s estimates that was found in Study 3 with Queen’s as the opposing team might become significant here. The absence of a hindsight effect is also notable in view of the larger sample size in Study 5 compared to Study 3. Given that the outcome of the game was classified as surprising (a somewhat small or possibly medium surprise), these results would be consistent with Pezzo’s model if it is assumed that the students were not able to make sense of the outcome. Moreover, because the win would have been a positive experience, the lack of a hindsight effect is inconsistent with the previous finding that the bias is stronger with positive than with negative outcomes (Pezzo and Beckstead, 2008). In addition, when discussing previous studies here, it was suggested that participants might have difficulty making sense of an unexpected outcome for Bishop’s because it was disappointing and they did not wish to dwell on it. In this case, however, the outcome was positive. It seems less likely that students would avoid thinking about a win than a loss. Interest and knowledge were positively related, and men scored higher than women on both factors. However, neither interest or knowledge were related to the hindsight effect and, as in the Studies 2, 3, and 4, sex of participant was not a significant factor. Therefore, the present results, like those of Study 3, do not support the suggestion that the hindsight effect might be stronger for people who had more interest in university football or who had less knowledge about it. However, it is notable that people who were higher in interest and who were higher in knowledge gave estimates that favored Bishops and people who were lower in interest and who were lower in knowledge gave estimates that favored Queen’s This suggests that people who were higher in interest and who were more knowledgeable about team records were more loyal to Bishop’s. People who were lower and who were more knowledgeable were actually more accurate in their judgments because Queen’s won the game.

Other Games For both the McGill-Concordia and Laval-Ottawa games, the chi square tests on the number of people (men or women) estimating wins and losses before and after the game were not significant. This was the same result that was obtained with the Bishop’s game.

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For both games, the three scores (the estimate for each team and for the difference score) were significantly different from the actual scores, which means that there was room for a hindsight effect. For the McGill-Concordia game, Concordia was expected to win by 8 points. Their win by 45 points was classified as a surprise and, more specifically, as a somewhat small surprise (see Table 1). For the Laval-Ottawa game, Ottawa was expected to win by 5 points. From Table 1, their win by 7 points was also classified as a surprise and, more specifically, as a small surprise. Note, however, the 7 points is on the border between < 7 point and 7 to 14 points. If the 7 is considered to be in the lowest category, the outcome would be classified as not surprising. For the McGill-Concordia game, men estimated a higher score for Concordia than women, and a higher difference in favor of Concordia than women. Given the clear win by Concordia, this indicates that men were more accurate. However, the hindsight effect did not occur for men or for women on any of the three measures (estimate for each team, difference score). Because the result was classified as a surprise (a somewhat small surprise), the absence of any hindsight effect is consistent with Pezzo’s (2003) model if it is assumed that the students could not make sense of the result. For the Laval-Ottawa game, there were no sex differences in the estimates. There was some evidence of a hindsight effect for the Laval estimate, but it was only marginally significant and remained so when the sex of participant was removed from the analysis. Consequently, the trend was not considered to be significant. Because the result was classified as surprising (a small surprise), the absence of any hindsight effect is again consistent with Pezzo’s (2003) model if it is assumed that the students could not make sense of the result. In both of these games, Bishop’s students may not have tried to make sense of the results because they did not mean much to them. That is, the lack of sense-involvement may have given them little motive to explain the outcome to themselves. On the other hand, if the outcome was considered to be not surprising, the absence of a hindsight effect is clearly consistent with Pezzo’s model. Considering the factor of interest in football, people who were higher in interest, like the men, estimated a higher score for Concordia and a greater difference in favor of Concordia over McGill than people who were lower in interest. However, this factor was not related to the measure of hindsight. Moreover, for the Laval-Ottawa game, interest was not significant in any of the analyses. In summary, there was no evidence of the hindsight bias in Study 5. In particular, it was not more prominent in the Bishop’s game where self-involvement would have been higher than in the other games. And by the same token, it was not more prominent in the other games where the outcome would have been more emotionally neutral. In addition, there was no support for the suggestion that interest might be a factor in the hindsight effect in either the Bishop’s game or the other games. The purpose of Study 6 was to once more examine the hindsight effect in a Bishop’s game and in other games. In addition, sex of participant, interest, and knowledge were again included as factors. However, one difference between this study and the previous one was that all the games were played between teams from the Quebec league and teams from the league in Atlantic Canada (a crossover weekend).

Hindsight Bias

43

STUDY 6 Method Participants The participants were 137 (68 women, 69 men) Bishop’s University undergraduate students, recruited as before. Seventy were tested before the game and 67 were tested afterwards. The two groups were not assigned randomly to the pre- and post-game conditions but they were matched for sex of participant. Materials and Procedure This regular season home game between Bishop’s University and St. Francis Xavier University took place on Saturday, October 19, 2002 at Bishop’s. The score was 22-7 in favour of St. Francis Xavier. Although Bishop’s played in the Quebec-Ontario league and St. Francis Xavier played in the Atlantic league, on this day there were crossover games between teams in the two leagues. On Thursday, October 17 or Friday, October 18 before the game or on Sunday October 20 or Monday October 21 after the game, participants made estimates in the same manner as in the first five studies. Before providing their postdictive judgments, participants tested after the game were informed of the number of points for each team. After making their judgments for Bishop’s and for St. Francis Xavier (whether predictive or postdictive), participants rated their personal interest in university football on the scale from 0 to 6 where 0 was labeled no interest at all, 4 was labeled moderate and 6 was labeled extremely interested. Then they were told that before the present game, Bishop’s and St. Francis Xavier had each played six games, and they were asked to state what they thought the win-loss record was for each team. As before, a correct response for each record was awarded 1 point so that the score ranged from 0 to 2. Three other games with Quebec university teams were played on October 19. McGill University beat Mount Allison University 39-2, Université Laval beat Acadia University 3514 and St. Mary’s University beat Concordia University 49-17. After participants had answered the questions about interest in university football and about knowledge of the Bishop’s and St. Francis Xavier records, they provided estimates for the number of points for each team for these games. Unfortunately, as noted above, an error was made and the knowledge data were also only gathered for pre-game participants. Consequently, no analyses from estimates of the scores for the other games were conducted with this kind of knowledge as a subject variable.

RESULTS Bishop’s Game General Hindsight Bias Of the 70 participants tested before the game, 20 predicted that Bishop’s would win and 50 predicted that St. Francis Xavier would win (i.e., Bishop’s would lose). Of the 67

44

Stuart J. McKelvie

participants tested after the game, 18 stated that they would have predicted that Bishop’s would win and 49 stated that they would have predicted that St. Francis Xavier would win (i.e., Bishop’s would lose). A chi square test conducted on the number of Bishop’s wins before and after the game in the two outcome conditions was not significant. Frequencies were similar for women and for men. The mean scores in each condition for the Bishop’s game are shown in Table 13. A 2 X 2 X 2 (Time X Sex X Team) mixed ANOVA with time and sex as between subjects variables and team as a within subjects variable was conducted on the estimated number of points for each team before the game and after the game. The effect of team was significant, F(1, 133) = 71.08, p < .001. Scores were higher for St. Francis Xavier than for Bishop’s. In addition, 2 X 2 (Time X Sex) ANOVAs were conducted on the Bishop’s, the St. Francis scores and the difference scores. None of these effects were significant. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. Two were statistically significant: t(69) = 4.91, p < .001 (Bishop’s), t(69) = 2.90, p = .005 (St. Francis Xavier). Both predicted scores were higher than the actual scores. A comparison of the mean difference score before the game to 0 was significant, t(69) = 6.38, p < .001, indicating an expected win for St Francis Xavier (loss for Bishop’s).

Interest and Knowledge as Moderators Scores for interest in university football and knowledge of records for Bishop’s and St. Francis Xavier were not significantly related. Sex differences were examined for interest scores and for knowledge scores. They were not significant in either case. See Table 5. As before, the subject variable of interest was examined by assigning people with a score of 4 or more out of 6 (at least moderate interest) to the higher group and those with a score of 2 or less out of 6 to the lower group. That is, data were not considered from people who chose 3. A 2 X 2 X 2 X 2 (Time X Interest X Sex X Team) mixed ANOVA was then conducted on the estimated number of points for each team. As above, the effect of team was significant, F(1, 111) = 47.25, p < .001. However, two other effects approached significance: time, F(1, 111) = 3.69, p = .057, and the interaction between time and interest, F(1, 111) = 3.88, p = .051. When this analysis was repeated without sex as a factor, the effect of team was significant, F(1, 115) = 51.12, p < .001, the effect of interest was significant, F(1, 115) = 4.42, p = .038, but the interaction between time and interest again only approached significance, F(1, 115) = 3.64, p = .059. Table 13. Mean Estimated Number of Points in Each Condition for the Bishop’s Game in Study 6 Bishop’s St Francis Xavier n M SD M SD Before 70 12.40 9.21 27.04 14.53 After 67 12.06 9.12 24.61 13.22 Actual Score 7 22 Note. Difference = Bishop’s estimate – St. Francis Xavier’s estimate. Team

Difference M SD -14.64 19.22 -12.55 18.32 -15

45

Hindsight Bias Table 14. Mean Estimated Number of Points in Each Knowledge Condition for the Bishop’s Game in Study 6 Knowledge Highest Intermediate Lowest

n 11 54 72

Bishop’s M SD 17.64 8.65 12.06 7.84 11.54 9.91

St. Francis Xavier M SD 17.91 8.10 24.20 13.57 28.31 14.34

Difference M SD -0.27 13.04 -12.15 17.58 -16.76 19.47

Scores were generally higher for participants who were higher in interest than those who were lower in interest. To follow up these effects for each team and for the difference scores, three separate 2 X 2 X 2 (Time X Interest X Sex) ANOVAs were then conducted. However, none of the effects was significant. Turning to the effect of knowledge, a 2 X 3 X 2 X 2 (Time X Knowledge X Sex X Team) mixed ANOVA showed both the effect of team, F(1, 125) = 18.40, p < .001, and the knowledge X team interaction was significant: F(2, 125) = 3.26, p = .042. Scores were estimated to be higher for St. Francis Xavier than for Bishop’s, but this was true for participants with the most knowledge and for participants with intermediate knowledge, not for those with least knowledge (see Table 14.) This analysis was followed up with 2 X 3 X 2 (Time X Knowledge X Sex) ANOVAs on the scores for Bishop’s alone, for St. Francis Xavier alone and for the difference scores. For Bishop’s, there were significant interactions between time and knowledge, F(2, 125) = 3.43, p = .036, and between time and sex, F(1, 125) = 4.78, p = .031 (see Table 15). When knowledge was intermediate, scores were higher before the game than after the game, t(52) = 2.10, p = .041, but there was no effect of time for the other two knowledge conditions. Although scores tended to decline over time for women and to increase over time for men, neither difference was significant. Similarly, although scores tended to be higher for women than for men before the game, and slightly higher for men for women after the game, neither difference was significant. For St. Francis Xavier, none of the comparisons were significant. However, for difference scores, the effect of knowledge was significant, F(2, 125) = 3.26, p = .042. Post hoc Scheffé tests showed that difference scores were smaller (more negative) in the intermediate knowledge and highest knowledge conditions than in the lowest knowledge condition (see Table 15). That is, people with the highest knowledge and with intermediate knowledge favoured St. Francis Xavier over Bishop’s more than people with the lowest knowledge.

Other Games The estimated scores for the other three games were treated in the same manner as the scores for the Bishop’s-St. Francis Xavier game, with the exception that knowledge was not included as a subject variable because it referred only to the Bishop’s game. It had been planned to gather information about the records of the other teams but, as was noted in the procedure, the data were not gathered for post-game participants.

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Table 15. Mean Estimated Number of Points as a Function of Objective Knowledge and of Sex for Bishop’s in Study 6

Knowledge Highest Intermediate Lowest Sex Women Men

Before n M

SD

After n

M

SD

7 27 36

16.14 14.22 10.31

9.14 8.59 9.39

4 27 36

20.35 9.89 12.78

8.26 6.46 10.39

34 36

14.35 10.56

10.31 7.72

34 33

11.94 12.18

9.31 9.06

Table 16. Mean Estimated Number of Points for Other Games in Study 6 Time

McGill Mount Allison Difference M SD M SD M SD 30.60 15.30 14.69 10.30 +15.91 19.38 30.86 13.71 8.74 8.22 +22.12 17.42 39 2 +37 Laval Acadia Difference Before 68 26.94 13.96 17.81 10.22 +9.13 14.81 After 66 26.21 11.12 15.38 8.34 +10.83 15.02 Actual Score 35 14 +21 Concordia St. Mary’s Difference Before 68 20.22 12.06 24.13 12.02 -3.91 15.56 Women 33 21.73 13.13 25.00 13.26 -3.27 14.91 Men 35 18.80 10.96 23.31 10.85 -4.51 16.34 After 66 17.79 9.87 29.56 12.96 -11.77 17.61 Women 34 21.09 10.15 27.65 14.57 -6.55 19.04 Men 32 14.28 8.36 31.59 10.84 -17.31 14.23 Actual Score 17 49 -32 Note. Differences = McGill – Mount Allison, Laval – Acadia, Concordia – Saint Mary’s. n Before 68 After 66 Actual Score

For all three games, the chi square tests showed no significance for the number of people predicting and postdicting wins and losses, for men or for women.

McGill-Mount Allison: General Hindsight Bias Points estimates for each game are shown in Table 16. For the game between McGill and Mount Allison, the 2 X 2 X 2 (Time X Gender X Team) mixed model ANOVA yielded significant effects of time, F(1, 130) = 4.33, p = .039, and of team, F(1, 130) = 141.57, p < .001, and an effect that approached significance for the interaction between time and team, F(1, 130) = 3.80, p = .053. Table 15 shows that scores were higher before than after the game and for McGill than for Mount Allison. The effect of time was clear for Mount Allison but actually slightly in the other direction for McGill.

47

Hindsight Bias

Scores for McGill alone, for Mount Allison alone and for the differences alone were examined with 2 X 2 (Time X Sex) ANOVAs. For McGill, there were no significant effects. For Mount Allison, the scores were significantly higher before the game than after the game, F(1, 130) = 13.85, p < .001. For the difference scores, the effect of time approached significance, F(1, 130) = 3.80, p = .053. In accordance with the strategy followed previously, the data were collapsed over sex and the effect of time was examined by itself for the difference scores. Again, it approached significance, t(132) = 1.95, p = .053. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. For the McGill-Mount Allison game, all three tests were statistically significant: t(133) = 6.61, p < .001 (McGill), t(133) = 11.57, p < .001 (Mount Allison) and t(133) = 11.20, p < .001 (difference). The McGill mean score was lower than the actual number of points, the Mount Allison mean score was higher than the actual number of points, and the mean difference score was lower than the actual difference. A comparison of the mean difference score before the game to 0 was also significant, t(133) = 11.79, p < .001, indicating a preference for McGill.

McGill-Mount Allison: Interest as a Moderator Another set of analyses were conducted with interest as a subject variable. For McGill vs. Mount Allison, a 2 X 2 X 2 X 2 (Time X Interest X Sex X Team) mixed model ANOVA showed that there was a significant effect of team, F(1, 107) = 146.30, p < .001, and a significant interaction between time and team, F(1, 107) = 6.48, p = .012. None of the effects of interest was significant. For McGill alone, the 2 X 2 X 2 (Time X Interest X Sex) showed no significant effects. For Mount Allison alone, there was a significant effect of time, F(1, 107) = 11.88, p = 001. Scores were higher before the game than after the game. For the difference scores, there was also a significant effect of time, F(1, 107) = 6.48, p = .012. Scores were higher after the game than before the game. Laval-Acadia: General Hindsight Bias For the game between Laval and Acadia, the 2 X 2 X 2 (Time X Sex X Team) mixed model ANOVA yielded a significant effects of team, F(1, 1303) = 61.67, p < .001. From Table 15, it can be seen that scores were higher for Laval than for Acadia. In addition, there were two interaction effects that approached significance: time and sex, F(1, 130) = 3.00, p = .085, and time, sex and team, F(1, 130) = 3.63, p = .059. Scores for Laval alone, Acadia alone and the differences alone were examined with 2 X 2 (Time X Sex) ANOVAs. For Laval, the interaction between time and sex was significant, F(1, 130) = 5.15, p = .025. Table 17. Mean Estimated Number of Points by Women and Men for Laval in the Laval –Acadia Game in Study 6

Women Men

Before n M 33 29.67 35 24.37

SD 14.52 13.10

After n 34 32

M 24.03 28.53

SD 12.49 9.08

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Although scores tended to decline over time for women and to increase over time for men (see Table 17), t-tests on each of these effects were not significant. For Acadia alone, none of the effects were significant. For the differences alone, the interaction between time and sex approached significance, F(1, 130) = 3.63, p = .059. The effect of time was not significant for women, but it was significant for men, t(65) = 2.11, p = .038. Scores increased over time. This was probably due to the trend with the scores for Laval (see Table 17). Single-sample t-tests were conducted to compare the scores before the game with the actual scores. For the Laval-Acadia game, all three tests were statistically significant: t(133) = 6.81, p < .001 (Laval), t(133) = 3.22, p = .002 (Acadia) and t(133) = 8.58.20, p < .001 (difference). The Laval mean score was lower than the actual number of points, the Acadia mean score was higher than the actual number of points, and the mean difference score was lower than the actual difference. A comparison of the mean difference score before the game to 0 was also significant, t(133) = 30.30, p < .001, indicating a preference for Laval.

Laval-Acadia: Interest as a Moderator For Laval vs. Acadia, a 2 X 2 X 2 X 2 (Time X Interest X Sex X Team) mixed model ANOVA showed only a significant effects of team, F(1, 107) = 50.90, p < .001. None of the effects of interest were significant. A series of three 2 X 2 X 2 (Time X Interest X Sex) ANOVAs showed there were no significant effects for Laval alone, for Acadia alone, or for the difference scores alone. However, there were three effects involving time that approached significance: for Laval, the interaction between time and sex, F(1, 107) = 3.26, p = .074; for Acadia, the main effect of time, F(1, 107) = 2.89, p = .092; and for the difference scores, the interaction between time and sex, F(1, 107) = 3.20, p = .076. In accordance with the approach in the previous studies, the second effect for Acadia was followed up by conducting a 2 X 2 (Time X Interest) ANOVAs without sex as a factor. However, it was not significant. Concordia-St. Mary’s: General Hindsight Bias For the game between Concordia and St. Mary’s, the 2 X 2 X 2 (Time X Gender X Team) mixed model ANOVA yielded a significant effects of team, F(1, 130) = 31.65, p < .001. From Table 15, it can be seen that scores were higher for St. Mary’s than for Concordia. In addition, there were two significant interaction effects and one that approached significance: time and team, F(1, 130) = 8.17, p = .005, sex and team, F(1, 130) = 4.54, p = .035, and time, sex and team, F(1, 130) = 2.86, p = .093. Scores for Concordia alone, St. Mary’s alone and the differences alone were examined with 2 X 2 (Time X Sex) ANOVAs. For Concordia, the effect of sex was significant, F(1, 130) = 6.79, p = .01. Scores were higher for women than for men. For St, Mary’s, the effect of time was significant, F(1, 130) = 6.40, p = .013. Scores were higher after the game than before the game. See Table15. For the differences alone, there were two significant main effects and one interaction effect that approached significance: time, F(1, 130) = 8.17, p = .005, sex, F(1, 130) = 4.54, p = 035, and the time X sex interaction, F(1, 130) = 2.86, p = .093. Difference scores, although all negative, were higher before the game than after the game, and scores for women were higher than scores for men. Over time, the decline in the difference scores over time was not significant for women, but it was significant for men, t(65) = 3.40, p = .001. See Table 17.

Hindsight Bias

49

Single-sample t-tests were conducted to compare the scores before the game with the actual scores. For the Concordia-St. Mary’s game, all three tests were statistically significant: t(133) = 2.12, p < .001 (Concordia), t(133) = 20.17, p < .001 (St. Mary’s) and t(133) = 16.49, p < .001 (difference). The Concordia mean score was higher than the actual number of points, the St. Mary’s mean score was lower than the actual number of points, and the mean difference score was greater (less negative) than the actual difference. A comparison of the mean difference score before the game to 0 was also significant, t(133) = 5.30, p < .001, indicating a preference for St. Mary’s.

Concordia-St. Mary’s: Interest as a Moderator For Concordia vs St. Mary’s, a 2 X 2 X 2 X 2 (Time X Interest X Sex X Team) mixed model ANOVA showed a significant effect of team, F(1, 107) = 17.54, p < .001, the interaction between time and team, F(1, 107) = 6.70, p = .011, and the interaction between team and sex, F(1, 107) = 4.61, p = .034. A series of three 2 X 2 X 2 (Time X Interest X Sex) ANOVAs was conducted for Concordia alone, for St. Mary’s alone, or for the difference scores alone. For Concordia, the effect of sex was significant, F(1, 107) = 6.12, p = .015, because scores were higher for women than for men, and the interaction between interest and sex was significant, F(1, 107) = 6.33, p = .013. Because this interaction does not involve time, which might indicate a hindsight effect, these means are not shown in Table 15, but it occurred because the sex difference appeared with participants who had lower interest and not with participants who had higher interest. For St. Mary’s alone, there was a significant effect of time, F(1, 107) = 5.90, p = 017. Scores were higher after the game than before. For the difference score alone, the effects of time, F(1, 107) = 6.67, p = .011, and of sex, F(1, 107) = 4.61, p = .034, were significant. Scores declined over time and where higher for women than for men.

DISCUSSION Bishop’s Game Once again, there was no significant difference between the number of people predicting a Bishop’s win before the game and the number of people postdicting a Bishop’s win after the game, and there were no sex differences in the number of cases in each category. Of the three cases (Bishop’s score, St. Francis score, difference score), the first two were significantly different from the actual score, allowing for the possibility of a hindsight effect. The difference between the estimated team scores before the game was not different from the actual difference and the difference itself was in favour or St. Francis. According to Table 1, the expected loss of 14.6 points was matched by the actual loss of 15 points, indicating no surprise. Table 12 shows that the mean number of points for Bishop’s before the game is 12.0. The mean number after the game is smaller (12.1) and closer to the actual score of 7, but was not significant. For St. Francis Xavier, the corresponding number of mean number of points before and after were 27.0 and 24.6 respectively. This decline is in the direction of the actual score of 22, but was not significant. Finally, the mean differences before and after the game

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are -14.6 and -12.6 but the decline is in the direction away from the actual difference of -15 (and also not significant). However, as noted above, there was no room for a hindsight effect for the difference score. Thus, there was no evidence of the hindsight effect with the Bishop’s game. Because the outcome of the game was not surprising, these results are consistent with Pezzo’s model because it postulates no hindsight if there is no surprise. The lack of a hindsight bias and the disappointing loss for Bishop’s are also consistent with the finding that the hindsight bias is stronger with positive than with negative outcomes (Pezzo and Beckstead, 2008). Contrary to the results of Study 5, interest and knowledge were unrelated to each other, and there was no sex difference on either factor. Estimated scores were generally higher for people who were higher than lower in interest. The interaction between time and interest approached significance in two analyses, but this was not sufficient to classify it as significant under the guidelines adopted in this study. On the other hand, there were some notable effects of knowledge. Most importantly, there was evidence of a hindsight effect with the estimated Bishop’s score for people who were intermediate in knowledge. In addition, people with the most knowledge and an intermediate level of knowledge predicted a higher score for St. Francis than for Bishop’s. Because St. Francis won the game, this indicates that people with more knowledge were more accurate in their estimates than people with the least knowledge. This effect also appeared on the difference score: the estimates in favor of St. Francis was significant for the top two knowledge groups. Note also that, when knowledge was included as a factor, there was a significant interaction between sex and time for Bishop’s estimates, suggesting that there was a hindsight effect for women but not for men. However, this interaction did not appear in the original analysis without knowledge as a factor or in the analysis with interest as a factor. Consequently, it was not interpreted as reliable evidence of a hindsight effect.

Other Games For the other three games involving the crossover between the Quebec and Maritime league, the chi square tests on the number of people (men or women) estimating wins and losses before and after the game were again not significant. For all three games, the three scores (the estimate for each team and for the difference score) were significantly different from the actual scores, which permits the possibility of a hindsight effect. For the McGill-Mount Allison game, McGill was expected to win by 15.1 points. Their win by 37 points was classified as surprising and, more specifically, as a small surprise; see Table 1). For the Laval-Acadia game, Laval was expected to win by 9.1 points. From Table 1, their win by 21 points was classified as surprising and, more specifically, a small surprise. Given that 21 is on the borderline between 14-21 points and > 21 points, the win by 21 points might be classified as a somewhat small surprise. For the Concordia-St. Mary’s game, St. Mary’s was expected to win by 3.9 points. The St. Mary’s win by 32 points was a surprise and, more specifically, a medium surprise. For the McGill-Mount Allison game, the predicted score for McGill was 30.6 points and the postdicted score was 30.86 points, which is a change in direction of the actual scores of

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51

39. However, it was not significant. For Mount Allison, the pre- and post-game estimates were 14.7 and 8.7 points, which is a change in the direction of the actual score of 2 points. Because this decline was significant, it demonstrates the hindsight effect. For the difference score, the pre- and post-game estimates were 15.9 points and 22.1 points, but the two marginally significant tests of this change do not justify classifying it as a significant hindsight effect. Because the McGill-Mount Allison result was classified as surprising (a small surprise), the lack of a hindsight effect for the McGill estimate and for the difference estimates is consistent with Pezzo’s (2003) model if it is assumed that participants did not have success making sense of the outcome. The significant hindsight effect for the Mount Allison estimate is consistent with the model if it is assumed that participants were successful in making sense of it. For the Laval-Acadia game, the predicted and postdicted scores for Laval were 26.94 and 26.2 points respectively, which is a small and nonsignificant change away from the actual score of 35. For Acadia, the pre- and post-game estimates were 17.8 and 15.4 points, which is a nonsignificant change in the direction of the actual score of 14 points. For the difference score, the pre- and post-game estimates were 14.8 points and 15.0 points, which is a nonsignificant change in the direction of the actual difference of 21 points. Because the outcome of this game was classified as a surprise (a small surprise or perhaps a somewhat small surprise), the absence of hindsight effects is consistent with Pezzo’s (2003) model if it is assumed that participants were not successful in making sense of them. However, it should also be noted that there was one significant effect of sex in this game: the estimates for Laval tended increased over time for men, from 24.4 to 28.5, which is in the direction of the actual number of points (35). This is a hindsight effect, and is consistent with the Pezzo model if it is assumed that the men were able to make sense of the outcome. However, they also tended to decrease over time for women (from 29.7 to 24.0), but this effect was not significant. For the Concordia vs St. Mary’s game, the predicted and postdicted scores were as follows: 20.2 and 17.7 for Concordia, which was a change towards the actual score of 17; 24.1 and 29.6 for St. Mary’s, which was a change towards the actual score of 49; and -3.9 and -11.8, which was a change towards the actual difference of -32. Of these three changes, two of them were significant (for St. Mary’s and for the difference), indicating hindsight effects. However, for the difference score, the hindsight effect was only significant for men. Because the outcome of this game was a surprise (a medium surprise), the two hindsight effects are consistent with Pezzo’s (2003) model in which participants succeed in making sense of the result. The nonsignificant changes with Concordia and with the difference score for women may have occurred because participants could not make sense of them. In addition, there was one other significant effect of sex: women estimated more points for Concordia than men. Finally, as in Study 5, interest in football was also examined as a possible moderating variable in the hindsight effect. However, it was not significant at any point in the analyses. In summary, there was no evidence of a hindsight bias for the Bishop’s game in Study 6, but it did appear in two of the other three games: for the Mount Allison score in the McGillMount Allison game and for the St. Mary’s score and the difference score (with men) in the Concordia St. Mary’s game. Thus, the hindsight effect was slightly more prominent in the other games where the outcome would have been more emotionally neutral to Bishop’s students. This result is consistent with the finding of a stronger hindsight effect for neutral outcomes than for positive or negative outcomes (Guilbault et al., 2004). However, there was

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no support for the suggestion that interest or knowledge might be a factor in the hindsight effect.

STUDIES 7 AND 8 In Studies 1 to 6, a between-subjects design (hypothetical design) was employed. However, because pre- and post-game estimates were obtained from different people who were not randomly assigned, it is possible that post-game estimates that are closer to the actual results than pre-game estimates are not evidence of hindsight but rather of better accuracy in the sample tested after the game. Consequently, in the final two studies, the same participants were tested both before and after the games (memory design). This permits a direct examination of how a person’s post-game estimate of what they predicted before the game compares with their actual pre-game estimate. Interest and knowledge were also reexamined as possible factors in the hindsight effect. However, they were measured slightly differently than in the previous studies. Participants had rated their personal interest in university football, which was a general measure. Here, they rated their interest in how Bishop’s performed in football and then their interest in how the other Quebec teams performed. It was hoped that these more specific measure might reveal an effect of interest on the hindsight effect, particularly for Bishop’s. For knowledge in the previous studies, participants had answered an objective question about the season record for Bishop’s and for the team they were playing. Here, they gave a subjective rating of their knowledge about university football in Quebec. The previous scale for knowledge only range from 0 to 2, but this one ranged from 0 to 6. Moreover, in Study 8, an expanded measure of knowledge was obtained by seeking information about the win/loss records of teams in the Bishop’s game and in the other games.

STUDY 7 Method Participants The participants were 50 (23 women, 27 men) Bishop’s University undergraduate students, recruited as before. They were tested both before and after the game. Materials and Procedure This regular season home game between Bishop’s University and the University of Montreal (Université de Montréal) took place on Saturday, October 4, 2003 at Bishop’s. The score was 53-22 in favour of Montreal. Two other games among Quebec university teams were played on the same day. Laval University (Université Laval) beat Concordia University 38-30 and McGill University beat the University of Sherbooke (Université de Sherbrooke) 63-0. On Thursday, October 2 or Friday, October 3 before the game, participants were questioned first about the Bishop’s-Montreal game. Unlike in the first five studies,

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53

participants were not asked an initial question about which team they thought would win the game. Rather, they simply estimated how many points they thought each team would score. Immediately afterwards, they made similar estimates for the Laval-Concordia game and then for the Sherbrooke-McGill game. After making their judgments for all three games, participants answered two interest questions on the scale from 0 to 6 where 0 was labeled no interest at all, 4 was labeled moderate and 6 was labeled extremely interested. First, they rated their interest in how the Bishop’s university football performs. Second, they rated their global interest in how the four other teams in the league perform. Finally, participants rated their knowledge about university football in Quebec on the same 6-point scale with the amendment that “interest” was replaced by “knowledge” on the scale. Note again that, in the previous studies, interest referred to personal interest in university football, whereas here it referred to specific interest in Bishop’s performance and then to interest in the other Quebec teams. In addition, in the previous studies, knowledge was measured objectively by asking participants to state the records of the teams in the Bishop’s game. In this study they provided a subjective estimate of their general knowledge about Quebec university football. On Sunday, October 4 or Monday, October 5, the same participants were contacted. First, they were told the score in the Bishop’s-Montreal game. Then they were asked to state what they had thought the score would be (what they remembered saying before). Immediately afterwards, the same procedure was followed for the Laval-Concordia game and then for the Sherbrooke-McGill game.

RESULTS Bishop’s Game General Hindsight Bias Of the 50 estimates before the game, 18 predicted that Bishop’s would win and 31 predicted that Montreal would win (i.e., a Bishop’s loss). One person did not choose a winner but gave the teams the same number of points. Of the 50 recalled estimates after the game, 19 indicated a Bishop’s win and 31 indicated a Montreal win (i.e., a Bishop’s loss). A chi square test conducted on the number of Bishop’s wins before and after the game in the two outcome conditions was not significant. Frequencies were similar for women and for men. The mean scores in each condition for the Bishop’s-Montreal game are shown in Table 18. A 2 X 2 X 2 (Sex X Time X Team) mixed ANOVA with sex as a between subjects variable and both time and team as within subjects variables was conducted on the estimated number of points for each team before the game and after the game. The effect of team was significant, F(1, 48) = 8.45, p = .006. Estimates scores were higher for Montreal than for Bishop’s. In addition, three 2 X 2 (Sex X Time) mixed model ANOVAs were conducted on the pregame scores and on the postgame memory scores for each team and for the difference scores. None of the effects was significant. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. Two were statistically significant: t(49) = 8.04, p < .001 (Montreal), t(49) = 6.15, p < .001 (difference). For Montreal, the estimate was lower than the actual score. For

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the difference score, the estimate was higher (less negative) than the actual score. A comparison of the mean difference score before the game to 0 was significant, t(49) = 2.40, p = .02, indicating an expected win for Montreal (a loss for Bishop’s).

Interest and Knowledge as Moderators In this study, there were three subject variables that reflected interest or knowledge: subjective interest in Bishop’s football, subjective interest in other Quebec teams and subjective knowledge about Quebec university football. Correlations among these three variables were all significant: r(N = 50) = .633, p < .001 for Bishop’s interest and other interest, r(N = 50) = .641, p < .001 for Bishop’s interest and knowledge, and r(N = 50) = .830, p < .001 for other interest and knowledge. In addition, analyses of sex differences showed that scores were significantly higher for men than for women for interest in other teams, t(48) = 2.91, p = .006, and for knowledge, t(48) = 3.33, p = .002. The mean scores are shown in Table 5. Following the procedure for the study of interest in the studies above, scores on each variable between 4 and 6 were classified as higher and those between 0 and 2 were classified as lower. First, Bishop’s interest was included as a factor in a 2 X 2 X 2 X 2 (Sex X Bishop’s Interest X Time X Team) mixed model ANOVA on estimated scores for the Bishop’s game. There were two significant effects: team, F(1, 39) = 13.96, p = .001, and the interaction between Bishop’s interest and team, F(1, 39) = 9.90, p = .003. Inspection of the mean scores (see Table 19) indicated that scores were higher for Montreal than for Bishop’s, but only for participants who were lower in Bishop’s interest. As in previous studies, this analysis was followed up by considering the difference scores and the scores for each team separately with 2 X 2 X 2 (Sex X Bishop’s Interest X Time) mixed model ANOVAs. Table 18. Mean Estimated Number of Points in Each Condition for the Bishop’s Game in Study 7 Bishop’s n M SD Before 50 24.52 16.00 After 50 25.00 16.03 Actual Score 22 Note. Difference = Bishop’s – Montreal. Team

Montreal M SD 33.22 17.40 35.40 16.16 53

Difference M SD -8.70 25.63 -10.40 24.45 -31

Table 19. Mean Estimated Number of Points as a Function of Bishop’s Interest for the Bishop’s Game in Study 7

Before Higher Lower After Higher Lower

n

Bishop’s M SD

Montreal M SD

Difference M SD

27 16

30.33 13.94

16.00 11.30

29.70 40.81

18.20 15.35

0.63 -26.87

23.24 20.82

27 16

28.67 18.88

17.14 13.68

32.85 41.88

16.90 17.17

-4.19 -23.00

26.64 18.13

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For Bishop’s, the effect of interest was significant, F(1 39) = 8.36, p = .006, and the interaction between interest and time approached significance, F(1, 39) = 3.58, p = .066. In general, people with a higher interest in Bishop’s gave higher estimates than people with a lower interest in Bishop’s. In line with the strategy outlined earlier, the marginally significant interaction on Bishop’s scores was reexamined without sex as a factor with a 2 X 2 (Bishop’s Interest X Time) mixed model ANOVA. Here, the interaction between interest and time was significant, F(1, 41) = 4.22, p = .046. Inspection of the mean scores in the four conditions (see Table 19) shows that participants who had a higher interest in Bishop’s gave higher estimates than people with a lower interest in Bishop’s at both time periods. However, the difference was greater before the game. For the effect of time, there was almost no difference for people with higher interest. However, for people with lower interest, scores tended to increase over time. Statistical comparisons showed that, for people with a higher interest in Bishop’s the effect of time was not significant, and for those with a lower interest, the increase over time approached significance, t(15) = 1.96, p = .068. As just noted, scores tended to be higher after the game than before the game. For Montreal considered alone, none of the effects were significant. For the difference score, the effect of interest in Bishop’s was significant, F(1, 39) = 9.90, p = .003. Scores were higher (less negative) for participants who had a higher interest in Bishop’s than for people who had a lower interest in Bishop’s (see Table 19). Because interest in the previous studies referred to Quebec university football in general, a second interest variable was formed by combining the two measures here. Participants were classified as higher or lower in Quebec university football if they scored above 3 (4, 5, 6) or below 3 (2, 1, 0) on both measures: interest in Bishop’s and interest in other Quebec teams. Like the measure of interest in the previous studies, this combined measure reflected interest in university football in general. Table 20. Mean Estimated Number of Points by Women and Men as a Function of Quebec Interest in the Bishop’s Game in Study 7

Interest Sex Higher Women Men Total Lower Women Men Total Total Women Total Men All

n

Bishop’s Before M SD

After M

2 9 11

42.50 27.11 29.91

26.16 10.53 14.00

9 5 14 11 14 25

10.67 18.20 13.36 16.45 23.93 20.6

9.39 14.38 11.49 17.46 12.31 14.95

SD

Montreal Before M SD

After M

SD

29.50 24.00 25.00

12.02 10.61 10.47

8.50 22.67 20.09

2.12 13.76 13.59

12.00 25.56 23.09

7.07 13.67 13.58

16.78 21.00 18.29 19.09 22.93 21.24

12.46 16.42 13.52 12.85 12.43 12.50

46.11 30.00 40.36 39.27 25.29 31.44

16.69 7.91 15.96 21.33 12.21 17.90

45.56 36.40 42.29 39.45 29.43 33.64

16.77 10.74 15.14 20.35 13.40 17.19

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However, it was formulated by combining two measures rather than by obtaining ratings on a single global question. Still with reference to the Bishop’s game, a 2 X 2 X 2 X 2 (Sex X Quebec Interest X Time X Team) mixed model ANOVA yielded three significant effects and two effects that approached significance: Quebec interest X team, F(1, 29) = 18.66, p < .001, sex X Quebec interest X team, F(1, 29) = 6.44, p = .019, Quebec interest X time X team, F(1, 29) = 5.39, p = .03, Quebec interest X time, F(1, 21) = 4.28, p = .051, and team X time, F(1, 21) = 3.12, p = .092. For Bishop’s alone, a 2 X 2 X 2 (Sex X Quebec Interest X Time) mixed model ANOVA showed that there were two significant effects: Quebec interest, F(1, 21) = 6.61, p = 018, and the interaction between Quebec interest and time, F(1, 29) = 7.31, p = .013. Table 21 shows that scores were higher for participants who were higher in Quebec interest than those who were lower in Quebec interest, but this difference was greater before the game than after the game. Although the comparisons for the effect of time gave no significant effects, it can be seen that the scores for people with lower interest tended to move up. For Montreal alone, the effect of Quebec interest was significant, F(1, 21) 11.74, p = .003, and two other effects approached significance: the effect of time, F(1, 29) = 3.33, p = .082, and the interaction between sex and time, F(1, 21) = 4.13, p = 055. For the main effect of Quebec interest, scores were generally higher for participants who were lower in Quebec interest than those who were higher in Quebec interest (Table 20). The effect of time was examined directly with a paired-samples t-test without sex as a variable, but it was not significant. For difference scores alone, two effects were significant: the interaction between Quebec interest and time, F(1, 21) = 5.39, p = .03, and the interaction between sex and Quebec interest, F(1, 21) = 6.44, p = .019. In addition, two effects approached significance: time, F(1, 21) = 3.12, p = .092, and the interaction between sex, Quebec interest and time, F(1, 21) = 3.56, p = .073. Because the two significant effects were embedded within the three-way interaction, the latter is shown in Table 20. Table 21. Mean Estimated Number of Points for Difference Scores by Women and Men as a Function of Quebec Interest, for Bishop’s in Study 7

Interest Higher

Sex

n

Before M

SD

After M

SD

Women Men

2 9 11

34.00 4.44 9.81

28.28 19.99 23.29

17.50 -1.56 1.91

19.09 20.76 1.91

Women Men

9 5 14 11 14

-35.55 -11.80 -27.00 -22.82 -1.36

20.76 11.54 21.08 34.84 18.76

-28.78 -15.40 -24.00 -17.50 -1.56

14.55 14.72 15.53 19.09 20.76

Total Lower

Total Total Women Total Men

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It can be seen that the difference scores tend to decline over time for people with higher interest in Quebec university football, and to increase over time for people with lower interest. The biggest decline occurred with higher interest women. Also, collapsing the data over time, scores are higher for women than for men with participants who are higher in interest and scores are lower for women than for men with participants who are lower in interest. Thirdly, turning to the effect of subjective knowledge, a 2 X 2 X 2 X 2 (Sex X Knowledge X Time X Team) mixed ANOVA showed that only one trend approached significance: team, F(1, 38) = 4.00, p = .053. The follow-up tests on scores for Bishop’s alone, for Montreal alone and for differences scores yielded no significant effects at all.

Other Games The estimated scores for the other two games (Laval-Concordia, Sherbrooke-McGill) were treated in the same manner as the scores for the Bishop’s-Montreal game. In both games, the chi square tests for the number of people predicting and postdicting wins and losses were not significant, either for men or for women.

Laval-Concordia: General Hindsight Bias Scores for the points estimates in each game are shown in Table 22. For the game between Laval and Concordia, the 2 X 2 X 2 (Time X Sex X Team) mixed model ANOVA yielded significant effects of time, F(1, 46) = 5.47, p = .024, and of team, F(1, 46) = 16.33, p < .001, and an effect that approached significance for the interaction between time and team, F(1, 46) = 3.51, p = .067. Table 22 shows that scores were higher for Laval than for Concordia, and the difference was greater before the game than after. Scores were also higher before than after the game, but only for Laval. Scores for Laval alone, for Concordia alone and for the differences alone were examined with 2 X 2 (Time X Sex) ANOVAs. Table 22. Mean Estimated Number of Points for Other Games in Study 7 Time

Laval Concordia M SD M SD 42.18 21.06 26.69 15.44 35.96 15.73 26.94 18.36 30 38 Sherbrooke McGill Before 48 7.88 11.56 54.73 22.20 Women 22 11.95 15.12 60.05 20.44 Men 26 4.42 5.67 50.23 23.02 After 48 8.21 13.34 55.19 22.00 Women 22 12.36 17.86 56.23 21.65 Men 26 4.69 6.19 54.31 22.69 Actual Score 0 61 Note. Differences = Laval – Concordia, Sherbrooke - McGill. n Before 48 After 48 Actual Score

Difference M SD +15.50 24.16 +9.02 22.87 -8 Difference -46.85 23.58 -48.09 23.34 -45.81 24.20 -46.98 28.58 -43.86 32.45 -49.62 25.22 -61

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For Laval, there a significant effect of time, F(1, 46) = 7.75, p = .008. Scores were lower after the game than before. For Concordia, the scores were significantly higher for women than for men, F(1, 46) = 6.16, p = .017. For the difference scores, the effect of time approached significance, F(1, 46) = 3.85, p = .067. In accordance with the strategy followed previously, the data were collapsed over sex and the effect of time was examined by itself for the difference scores. Again, it approached significance, t(47) = 1.96, p = .056. The difference score tended to decline. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. For the Laval-Concordia game, all three tests were statistically significant: t(49) = 3.97, p < .001 (Laval), t(49) = 5.34, p < .001 (Concordia) and t(49) = 6.88, p < .001 (difference). The Laval mean score was higher than the actual number of points, the Concordia mean score was lower than the actual number of points, and the mean difference score was higher than the actual difference. A comparison of the mean difference score before the game to 0 was also significant, t(49) = 4.50, p < .001, indicating a preference for Laval.

Laval-Concordia: Interest and Knowledge as Moderators Turning to the analyses for interest, Bishop’s interest was not included as a factor because Bishop’s was not playing in this game. However, a 2 X 2 X 2 X 2 (Sex X Quebec Interest X Time X Team) mixed model ANOVA was conducted on the estimates for the Laval-Concordia game. The only significant effect was team: F(1, 19) = 6.46, p = .02. For Laval alone, a 2 X 2 X 2 (Sex X Quebec Interest X Time) mixed ANOVA showed that two effects approached significance: the interaction between Quebec interest and time, F(1, 19) = 3.06, p = .096, and the interaction between sex and Quebec interest, F(1, 19) = 3.77, p = .067. In the first case, the analysis was repeated without sex as a factor. The 2 X 2 (Quebec Interest X Time) ANOVA showed that there was a significant effect of time, F(1, 21) = 7.52, p = .012, and a significant Quebec interest X time interaction, F(1, 21) = 5.60, p = .028. Scores were higher before the game than after the game for participants who were lower in interest, t(13) = 3.34, p = .005, but there was no significant effect of time for participants who were higher in interest. See Table 23. For Concordia alone, one effect approached significance: Quebec interest, F(1, 19) = 3.73, p = .069. For the difference score, there were no significant effects. Turning to the effect of subjective knowledge, a 2 X 2 X 2 X 2 (Sex X Knowledge X Time X Team) mixed ANOVA showed one significant effect: team, F(1, 36) = 6.29, p = .017. Table 23. Mean Estimated Number of Points as a Function of Quebec Interest for Laval and McGill in Study 7 Quebec Interest n Higher Lower

9 14

Higher Lower Total

9 14 23

Before M Laval 39.11 45.86 McGill 55.67 56.50 56.17

SD

After M

SD

10.56 20.38

38.44 36.79

11.72 16.89

22.69 20.24 20.72

54.78 49.07 51.30

18.19 19.06 18.52

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The follow-up tests on scores for Laval alone, for Concordia alone and for differences scores yielded no significant effects at all.

Sherbrooke-McGill: General Hindsight Bias For the game between Sherbrooke and McGill, the 2 X 2 X 2 (Time X Sex X Team) mixed model ANOVA yielded two significant effects: team, F(1, 46) = 173.44, p < .001, and sex, F(1, 46) = 4.84, p = .033. From Table 22, it can be seen that scores were higher for McGill than for Sherbrooke and were also generally higher for women than for men. Scores for Sherbrooke alone, for McGill alone, and for the differences alone were examined with 2 X 2 (Time X Sex) ANOVAs. For Sherbrooke, the effect of sex was significant, F(1, 46) = 7.79, p = .008. Women scored higher than men. For McGill alone, the interaction between sex and time approached significance, F(1, 46), 3.74, p = .059. Women appeared to score higher than men before the game more than after the game. Also, scores tended to decline over time for women but to increase over time for men (see Table 22). For the differences alone, none of the effects was significant. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. For the Sherbrooke-McGill game, all three tests were statistically significant: t(49) = 4.68, p < .001 (Sherbrooke), t(49) = 2.05, p = .046 (McGill) and t(49) = 4.24, p < .001 (difference). The Sherbrooke mean score was higher than the actual number of points, the McGill mean score was lower than the actual number of points, and the mean difference score was higher (less negative) than the actual difference. A comparison of the mean difference score before the game to 0 was also significant, t(49) = 14.40, p < .001, indicating a preference for McGill. Sherbrooke-McGill: Interest and Knowledge as Moderators Turning again to the analysis for Quebec interest, a 2 X 2 X 2 X 2 (Sex X Quebec Interest X Time X Team) mixed model ANOVA was conducted. The only significant effect was team: F(1, 19) = 47.28, p < .001. For Sherbrooke alone, a 2 X 2 X 2 (Sex X Quebec Interest X Time) mixed ANOVA showed no significant effects. However, for McGill alone, the effect of time was significant, F(1, 19) = 4.77, p = .042. Scores were higher before the game than after the game (see Table 23). For the difference scores, none of the effects were significant. Turning to the effect of subjective knowledge, a 2 X 2 X 2 X 2 (Sex X Knowledge X Time X Team) mixed ANOVA showed one significant effect: team, F(1, 36) = 34.27, p = .001. This was accompanied by a three-way interaction between sex, team, and time that approached significance: F(1, 36) = 3.84, p = .058. For Sherbrooke alone, there were no significant effects. However, for McGill alone, there was a significant interaction between sex and time, F(1, 36) = 5.23, p = .028. Although t-tests for the effect of gender were not significant, women appeared to score higher than men before the game more than after the game. Also, although t-tests for the effect of time were not significant, scores tended to decline over time for women but to increase over time for men (Table 24). For the difference scores, none of the effects were significant.

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Table 24. Mean Estimated Number of Points by Women and Men McGill in Study 7 (with Subjective Knowledge as a Factor in the Analysis) Sex Women Men

n 19 21

Before M 59.68 48.76

SD 21.27 24.11

After M 54.32 53.43

SD 21.59 21.94

DISCUSSION Bishop’s Game The number of people who predicted a win for Bishop’s was similar before and the pattern of numbers was similar for men and for women. For the predicted Bishop’s score, Montreal score, and difference score, the last two were significantly different from the actual score, indicating that a hindsight effect was possible. The predicted Bishop’s score was not different from the actual score, precluding any hindsight effect in this case. The predicted outcome was a win for Montreal by 8.7 points. The Montreal win by 31 points was classified as a surprise and, more specifically, a somewhat small surprise. Table 17 shows that the mean number of points for Bishop’s before and after the game were 24.5 points and 25.0 points respectively, a small nonsignificant change away from the actual score of 22 points. Of course, there was no room for a hindsight effect from the initial estimates. The changes for Montreal (33.2 to 35.4, a move towards 53) and for the difference score (-8.70 to -10.40, a move towards -31) were also both small and not significant. These results show no evidence of the hindsight effect. According to Pezzo’s (2003) model, if the outcome is a surprise, which it was here (and somewhat small), the hindsight effect will occur if participants can make sense of the result. In this case, according to Pezzo’s model, Bishop’s students did not make sense of the result. Perhaps, as in previous studies above, the loss was disappointing and not one that they wished to dwell upon. Also notable is that fact that the surprise was classified as small: a loss was predicted and a loss occurred. Under these circumstances, little cognitive processing may have been required. There were no sex differences associated with the estimates for the Bishop’s game or with interest on Bishop’s football performance. However, men indicated greater interest in other Quebec teams than women, and men indicated that they had more knowledge about Quebec university football than women. In addition, the three measures (two for interest, one for knowledge) were all significantly related to each other. Perhaps this occurred because they were all subjective estimates. In the studies above, knowledge was measured objectively. Interest was examined as a factor in two ways: as a measure of interest in Bishop’s performance and as a measure of Quebec university football team performance in general. Although the second measure was obtained by combining ratings for interest in Bishop’s and in the other teams, it is similar in meaning to the global ratings of interest obtained in the previous studies. However, it is a stricter measure: people were classified as higher or lower if they score higher or lower on both interest in Bishop’s and interest in other teams. People

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who were more interested in Bishop’s gave higher estimates for Bishop’s scores than people who were less interested. Perhaps greater interest indicates greater attachment to Bishop’s and a general wish for a good outcome. However, this difference was greater before the game than after, because people with lower interest tended to give higher estimates for the Bishop’s score after the game than before. This indicated a hindsight effect because the pre and post game estimates were 13.9 points and 18.9 points, and Bishop’s scored 22 points. Perhaps people with lower interest thought that they had been too pessimistic before the game. Turning to the measure of general interest in Quebec university football, in which the higher and lower interest groups were fairly strictly defined by including people who were higher or lower on both Bishop’s interest and other Quebec team interest, students with more interest gave higher estimates for Bishop’s scores and lower estimates for Montreal scores than students with less interest. In other words, as with the measure of Bishop’s interest, people with more interest favored Bishop’s more than people with less interest. In addition, for the Bishop’s scores, this effect was greater before the game than after the game, because the estimates for students with more interest tended to decrease over time and scores for student with less interest tended to increase over time (both hindsight effects). As a corollary to this, the difference scores also declined over time for people with higher interest in Quebec university football, which represents a hindsight effect, and tended to increase over time for people with lower interest. The biggest decline (showing a hindsight effect) occurred with higher interest women. Thus, there was evidence of a hindsight effect for the Bishop’s estimate for people with a lower interest in Bishop’s, for people with a lower interest in Quebec teams and for people with a higher interest in Quebec teams. In addition, there was a notable sex difference in the tendency to favor Bishop’s or to favour Montreal. People with more interest in Quebec university football favored Bishop’s (the difference score was positive) and people with less interest favored Montreal (the difference was negative). However, this effect was much larger for women than for men. In contrast to the various effects of interest, there were no effects of knowledge of Quebec university football in any of the analyses.

Other Games For the other two games the chi square tests on the number of people (men or women) estimating wins and losses before and after the game were again not significant. Therefore there is no evidence of hindsight bias from these counts. For both games, the three scores (the estimate for each team and for the difference score) were significantly different from the actual scores, which permits the possibility of a hindsight effect. For the Laval-Concordia game, Laval was expected to win by 15.5 points. Concordia’s win by 8 points was classified as a surprise and, more specifically, as a large surprise (see Table 1). For the Sherbrooke-McGill game, McGill was expected to win by 46.9 points. From Table 1, their win by 61 points was not surprising. For the Laval-Concordia game, the predicted score for Laval was 42.2 points and the postdicted score was 36.0 points, which is a change in direction of the actual scores of 30. This was significant and constitutes a hindsight effect. For Concordia, the pre-post scores were 26.7 and 26.9, which did not differ significantly. For difference scores, estimate tended to decline over time from 15.5 to 9.0 towards that actual difference of -8, but the change was

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not significant. In terms of Pezzo’s (2003) model, the outcome of the Laval-Concordia game was a surprise (a large surprise), and the hindsight effect for the Laval scores may have occurred because participants were able to make sense of the change. The lack of a hindsight effect with the Concordia and difference scores may have been the result of participants not being able to make sense of the changes. Although not connected to the hindsight effect, there was one significant effect of sex in these analyses: for Concordia, women estimated higher scores than men. Interest in football was again examined as a possible moderating variable in the hindsight effect for the other games. Here, interest was defined in terms of the general measure that was constructed from both Bishop’s interest and interest in other Quebec teams. In the game between Laval and Concordia, for people who had lower interest in Quebec university football, scores declined over time for Laval, indicating a hindsight effect. This qualifies the general hindsight effect for Laval (see above), and suggests it occurred mainly because of the participants who had lower Quebec interest. This is contrary to the proposal that selfinvolvement might be higher when interest is higher and that the hindsight effect might be more likely with more self-involvement. For the Sherbooke-McGill game, the predicted score for Sherbrooke was 7.9 points and the postdicted score was 8.2 points, which is a small nonsignificant change away from the actual scores of 0. For McGill, the pre-post scores were 54.7 and 55.2, was a small nonsignificant change towards the actual score 61 points. For difference scores, the estimates over time were also similar and nonsignificant (-46.9, -47.0, compared to the actual difference of -61). These results, which do not show a hindsight effect, are consistent with Pezzo’s (2003) model because the outcome of the game was not surprising, which implies that there would be no sense-making activity and consequently no hindsight effect. In the game between Sherbooke and McGill, when Quebec football interest was a factor in the analysis, scores declined over time for McGill, but they moved away from the actual score, indicating a reverse hindsight effect. However, this trend runs counter to the results with all participants, where there was almost no difference for the McGill scores before and after the game (see Table 21). In addition, there was also evidence that the decline occurred for women (a reverse hindsight effect), whereas scores increased over time for men (a hindsight effect). This interaction approached significance in the main analysis (means in Table 21), but was significant in the analysis where subject knowledge of Quebec university football was included as a factor (means in Table 24). The reverse hindsight effect for women is difficult to account for from previous research. When that effect has occurred (Calvillo and Gomes, 2011; Ofir and Mazursky, 1997), the outcome was extremely surprising. In the present game, the outcome was not surprising. In addition, the hindsight effect for men is inconsistent with Pezzo’s (2003) model according to which the hindsight effect will not occur if the result is not surprising. However, it should be noted that these two results for women and men only occurred when subjective knowledge was included as a factor in the analysis. Like the reverse hindsight effect that appeared when Quebec interest was included as a factor, they did not appear in the original analysis with all participants. In addition, the hindsight effects that occurred here were not a function of Quebec interest or knowledge. Consequently, they will be noted, but will not be treated as reliable effects unless they are replicated in Study 8. In summary, there was some evidence of the hindsight bias for the Bishop’s game in Study 7: for Bishop’s estimates with people who were lower in Bishop’s interest and in

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63

Quebec interest, and for people higher in Quebec interest. For the other games, there was a hindsight effect for Laval estimates, especially with people who were lower in Quebec interest. Thus, in Study 7, the hindsight effect appeared sparingly, and for both the Bishop’s game and for another game not involving Bishop’s. Unlike Study 6, the effect was not slightly more prominent in the other games where the outcome would have been more emotionally neutral to Bishop’s students. However, unlike Study 6, there was some support for the suggestion that interest in university football might be a factor in the hindsight effect. The effect actually occurred more often when interest was lower, which is contrary to the hypothesis that hindsight would be associated with higher self-involvement. In the final study, the procedure was similar to that in Study 7, except that another measure of objective football knowledge in Quebec was added. Participants were asked to state the win-loss records for all Quebec university football teams, not just for Bishop’s and their opponent. The major goal was to investigate again whether or not the hindsight effect would occur with the memory design. However, it also afforded another opportunity to reexamine whether interest might be a factor in the effect.

STUDY 8 Method Participants The participants were 73 (38 women, 35 men) Bishop’s University undergraduate students, recruited as before. As in Study 7, they were tested both before and after the game. Materials and Procedure This regular season game between Bishop’s University and McGill University took place on Saturday, October 28, 2006 at McGill. The score was 14-0 in favour of McGill. Two other games among Quebec university teams were played on the same day. University of Montreal (Université de Montreal) beat Laval University (Université Laval) 7-2 and Sherbrooke University (Université de Sherbrooke) beat Concordia University 29-15. On Thursday, October 26 or Friday, October 2 before the game, participants were questioned first about the Bishop’s-McGill game. As in Study 7, they estimated how many points they thought each team would score. Immediately afterwards, they made similar estimates for the Laval-Montreal game and then for the Concordia-Sherbrooke game. After making their judgments for all three games, participants answered the same two interest questions as in Study 7 on the scale from 0 to 6 where 0 was labeled no interest at all, 4 was labeled moderate and 6 was labeled extremely interested. First, they rated their interest in how the Bishop’s university football performs. Second, they rated their global interest in how the four other teams in the league perform. Thirdly, again as in Study 7, participants rated their personal knowledge about university football in Quebec on the same 6-point scale with the amendment that “interest” was replaced by “knowledge” on the scale. Finally, football knowledge was measured objectively by giving participants the total number of games played by the six teams and by asking them to state the number of wins and losses for each team. Note that in previous studies where knowledge was measured objectively,

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participants were only tested on team records in the Bishop’s game. Here, they were tested on their knowledge of team records for all three games. A correct response for each record was awarded 1 point so that, with six teams, the score ranged from 0 to 6. On Sunday, October 29 or Monday, October 30, the same participants were contacted. First, they were told the score in the Bishop’s-McGill game. Then they were asked to state what they had thought the score would be (what they remembered saying before). Immediately afterwards, the same procedure was followed for the Laval-Montreal game and then for the Concordia-Sherbrooke game.

RESULTS Bishop’s Game General Hindsight Bias Of the 73 estimates before the game, 28 predicted that Bishop’s would win and 44 predicted that McGill would win (i.e., a Bishop’s loss). One person did not choose a winner but gave the teams the same number of points. Of the 73 recalled estimates after the game, 23 indicated a Bishop’s win and 50 indicated a McGill win (i.e., a Bishop’s loss). A chi square test conducted on the number of Bishop’s wins before and after the game in the two outcome conditions was not significant. In addition, frequencies were similar for women and for men. The mean scores in each condition for the Bishop’s-McGill game are shown in Table 25. A 2 X 2 X 2 (Sex X Time X Team) mixed ANOVA with sex as a between subjects variable and both time and team as within subjects variables was conducted on the estimated number of points for each team before the game and after the game. The effects of time, F(1, 71) = 6.69, p = .012, and of team were significant, F(1, 71) = 13.50, p < .001. Estimated scores were generally higher before the game than after the game and were also higher for McGill than for Bishop’s. In addition, three 2 X 2 (Sex X Time) mixed model ANOVAs were conducted on scores for each team and for the difference scores. For the estimated scores for Bishop’s, there was a significant effect of time, F(1, 71) = 7.11, p = .009. Estimates were higher before the game than after the game. For McGill and for the difference scores, none of the effects were significant. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. Table 25. Mean Estimated Number of Points in Each Condition for the Bishop’s Game in Study 8 Bishop’s n M SD Before 73 15.85 10.20 After 73 13.32 9.59 Actual Score 0 Note. Difference = Bishop’s – Montreal. Team

McGill M 22.99 21.33 14

SD 14.38 13.88

Difference M SD -7.14 18.92 -8.01 17.54 -14

Hindsight Bias

65

All three were statistically significant: t(72) = 13.49, p < .001 (Bishop’s), t(72) = 5.35, p < .001 (McGill), and t(72) = 3.21, p = .002 (difference). In all three cases, the estimates were higher than the actual score. A comparison of the mean difference score before the game to 0 was significant, t(72) = 3.18, p = .002, indicating an expected win for McGill (a loss for Bishop’s).

Interest and Knowledge as Moderators There were four subject variables that reflected interest and knowledge: subjective interest in Bishop’s football, subjective interest in other Quebec teams subjective knowledge about Quebec university football, and objective knowledge about Quebec university football. Of the six correlations, three were significant, two approached significance, and one was not significant. The three significant ones were r(N = 73) = .680, p < .001 for Bishop’s interest and other Quebec team interest, r(N = 73) = .339, p < .001 for other Quebec interest and objective knowledge, and r(N = 73) = .712, p < .001 for subjective knowledge and objective knowledge. The two that approached significance were r(N = 73) = .222, p =.059 for Bishop’s interest and objective knowledge, and an identical value of r(N = 73) = .222, p =.059 for other Quebec interest and subjective knowledge. The correlation between Bishop’s interest and subjective knowledge was not significant, r(N = 73) = .123, p = .298. Sex differences were examined for each measure. None of them were significant, although men almost scored higher than women for objective knowledge of the win-loss records of teams in the Bishop’s game, t(71) = 1.93, p = .058. See Table 5. As before, for interest, scores between 4 and 6 were classified as higher and those between 0 and 2 were classified as lower. First, Bishop’s interest was included as a factor in a 2 X 2 X 2 X 2 (Sex X Bishop’s Interest X Time X Team) mixed model ANOVA on estimated scores for the Bishop’s game. There were two significant effect: time, F(1, 58) = 6.40, p = .014, and team, F(1, 58) = 10.82, p = .002. Estimated scores declined over time and were higher for McGill than for Bishop’s. As in previous studies, this analysis was followed up by considering the difference scores and the scores for each team separately with 2 X 2 X 2 (Sex X Bishop’s Interest X Time) mixed model ANOVAs. For Bishop’s, the effect of time was significant, F(1, 58) = 4.75, p = .033. Scores were higher before the game than after the game. For the difference scores, none of the effect were significant, but for McGill considered alone, the effect of time approached significance, F(1, 58) = 3.05, p = .086. In accordance with the practice adopted in this report, the estimates for McGill were collapsed over sex and examined with a 2 X 2 (Bishop’s Interest X Time) ANOVA. However, the effect of time was not significant. Again following the procedure in Study 7, a second interest variable was formed by combining the two measures here. Participants were classified as higher or lower in Quebec university football if they scored above 3 (4, 5, 6) or below 3 (2, 1, 0) on both interest measures: interest in Bishop’s and interest in other Quebec teams. Still with reference to the Bishop’s game, a 2 X 2 X 2 X 2 (Sex X Quebec Interest X Time X Team) mixed model ANOVA yielded one significant effect and one effect that approached significance: the interaction between team and Quebec interest, F(1, 32) = 4.87, p = .035, and the effect of team, F(1, 32) = 3.13, p = .086. The effect of team was significant in the main analysis and indicated that scores were higher for McGill than Bishop’s The estimates for the significant interaction are shown in Table 26.

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Table 26. Mean Estimated Number of Points as a Function of Quebec Interest for the Bishop’s Game in Study 8

n

Bishop’s M SD

Before Higher 8 17.75 Lower 28 14.89 After Higher 8 18.00 Lower 28 11.64 Note. Difference = Bishop’s – McGill.

McGill M SD

Difference M SD

6.18 10.88

16.23 23.93

11.54 10.33

1.13 -9.04

11.29 14.83

5.58 9.97

16.23 22.07

11.54 12.37

1.13 -10.43

11.38 13.28

Table 27. Mean Estimated Number of Points as a Function of Subjective Knowledge for the Bishop’s Game in Study 8

Before Higher Lower After Higher Lower

n

Bishop’s M SD

McGill M

SD

Difference M SD

27 45

17.59 14.56

9.87 10.32

22.37 23.51

12.56 15.60

-4.78 -8.96

17.08 19.98

27 45

17.07 10.76

10.20 9.01

19.15 22.89

10.55 13.53

-2.07 -12.13

16.69 16.91

It can be seen that people who were lower in Quebec interest estimated higher scores for McGill than for Bishop’s, whereas people who were higher in Quebec interest estimates similar scores for the two teams. Another way of looking at these results is that Bishop’s estimates were similar for people who were higher or lower in Quebec interest, whereas McGill estimates were higher for people who were higher in Quebec interest. For Bishop’s alone and for McGill alone, 2 X 2 X 2 (Sex X Quebec Interest X Time) mixed model ANOVAs showed that there were no significant effects. However, for difference scores alone, the effect of Quebec interest was significant, F(1, 32) = 4.87, p = .035. It can be seen (Table 26) that the difference scores were lower (more negative) for people who were lower in Quebec interest than for people who were higher in Quebec interest. That is, people who were lower in Quebec interest favored McGill over Bishop’s whereas people who were high in Quebec interest did not favor either team. Third, for subjective knowledge, scores were skewed and very few people chose the higher levels. Consequently, to permit a reasonable number in each category, scores on each variable between 3 and 6 were classified as higher (n = 27) and those between 0 and 2 were classified as lower (n = 46). A 2 X 2 X 2 X 2 (Sex X Subjective Knowledge X Time X Team) mixed ANOVA yielded three significant effects: time, F(1, 68) = 6.44, p = .013, team, F(1, 68) = 11.84, p = 001, and the interaction between time, team, and subjective knowledge, F(1, 68) = 5.96, p = .017. Inspection of Table 27 suggests that Bishop’s scores tended to decline

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over time for lower knowledge participants and that McGill scores tended to decline over time for higher knowledge participants. In accordance with the present procedure for analyzing data, 2 X 2 X 2 (Sex X Subjective Knowledge X Time) ANOVAs were conducted for difference scores and for each team considered separately. For Bishop’s estimates, the effect of time was significant, F(1, 68) = 4.80, p = .032, and the effect of subjective knowledge approached significance, F(1, 68) = 3.64, p = .061. Bishop’s scores declined over time. For McGill estimates, the effect of time approached significance, F(1, 68) = 3.55, p = .064. In accordance with the present procedures, the data were collapsed over sex, and examined with a 2 X 2 (Subjective Knowledge X Time) ANOVA. However, the effect of time was not significant. For difference scores, one effect was significant: the interaction between subjective knowledge and time, F(1, 68) = 5.96, p = .017. Table 27 shows that scores declined over time for people who were lower in knowledge and rose slightly over time for people who were higher in knowledge. Fourth, and finally, for objective knowledge, the distribution was skewed. To account for this, and to obtain somewhat similar numbers in each category, people were classified as higher if they scored from 3 to 6 and lower if they scored 0 or 1. A 2 X 2 X 2 X 2 (Sex X Objective Knowledge X Time X Team) mixed ANOVA showed significant effects of time, F(1, 47) = 6.08, p = .017, team, F(1, 47) = 8.25, p = .006, and of the interaction between objective knowledge and team, F(1, 47) = 6.38, p = .015. See Table 28. The interaction between objective knowledge and time also approached significance, F(1, 47) = 3.15, p = .083. Scores declined over time, and for Bishop’s and McGill were similar for people who were higher in objective knowledge, but were higher for McGill than for Bishop’s for people who were lower in objective knowledge. For the interaction between knowledge and time that was almost significant, the data were collapsed over sex and examined with a 2 X 2 X 2 (Objective Knowledge X Time X Team) ANOVA. Again the interaction was almost significant, F(1, 49) = 3.75, p = .058. Follow-up 2 X 2 X 2 (Sex X Objective Knowledge X Time) ANOVAs were conducted on the estimates for each team alone and for the difference scores. For Bishop’s, the effect of time was significant, F(1, 47) = 4.05, p = .05. Scores declined over time. For McGill, the effect of objective knowledge was significant, F(1, 47) = 6.50, p = .014, and the effect of time approached significance, F(1, 47) = 3.72, p = .06. Scores tended to be higher for people with lower knowledge than for people with higher knowledge. Table 28. Mean Estimated Number of Points as a Function of Objective Knowledge for the Bishop’s Game in Study 8

Before Higher Lower After Higher Lower

n

Bishop’s M SD

McGill M

SD

Difference M SD

21 30

15.57 15.10

8.59 11.47

16.67 27.00

11.10 15.22

-1.10 -11.90

15.49 21.07

21 30

14.71 10.53

8.98 8.85

16.19 22.93

9.96 16.06

-1.48 -7.90

14.44 17.53

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For the difference scores, the effect of knowledge was significant, F(1, 47) = 6.38, p = .015. Scores were higher (less negative) for people with higher knowledge than for people with lower knowledge. That is, the score difference between Bishop’s and McGill was smaller for people with higher knowledge than for people with lower knowledge. To put this another way, people with lower knowledge favored McGill and people with higher knowledge did not.

Other Games For both games, the chi square tests showed no significance for the number of people predicting and postdicting wins and losses, either for men or for women.

Laval-Montreal: General Hindsight Bias For the game between Laval and Montreal, the mean points scores in each condition are shown in Table 29. A 2 X 2 X 2 (Sex X Time X Team) mixed ANOVA with sex as a between subjects variable and both time and team as within subjects variables was conducted on the estimated number of points for each team before the game and after the game. Both the main effects of time, F(1, 1, 71) = 16.10, p < .001, and of team, F(1, 71) = 26.39, p < .01, as well as the interaction between time and team, F(1, 71) = 12.36, p < .001, were significant. Inspection of Table 29 shows that estimates were higher for Laval than for Montreal and decline over time, but only for Laval and not for Montreal. Three 2 X 2 (Sex X Time) mixed model ANOVAs were conducted on scores for each team and for the difference scores. For Montreal, none of the effects were significant. However, for both Laval, F(1, 71) = 25.66, p < .001, and for the differences scores, F(1, 71) = 12.36, p < .001, there were significant effects of time. Estimates were higher before the game than after the game. Table 29. Mean Estimated Number of Points for Other Games in Study 8 Time

Laval Montreal M SD M SD Before 31.51 15.09 19.53 13.25 After 24.08 12.14 19.44 12.78 Actual Score 2 7 Concordia Sherbrooke Before 73 25.21 11.93 19.19 11.81 Women 38 27.06 12.79 17.79 12.05 Men 35 23.20 10.75 20.71 11.51 After 73 21.08 11.00 20.52 11.38 Women 38 22.03 11.68 19.61 11.55 Men 35 20.06 10.28 21.51 11.28 Actual Score 15 29 Note. Difference = Laval – Montreal, Concordia – Sherbrooke. n 73 73

Difference M SD +11.97 18.58 +4.64 13.69 -5 Difference +6.01 13.49 +9.26 12.45 +2.49 13.86 +0.56 12.90 +2.42 11.66 -1.46 14.02 -14

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Single-sample t-tests were conducted to compare the scores before the game with the actual scores. All three were statistically significant: t(73) = 16.62, p < .001 (Laval), t(73) = 8.11, p < .001 (Montreal), and t(73) = 7.83, p < .001 (difference). In all three cases, the estimates were higher than the actual score. A comparison of the mean difference score before the game to 0 was significant, t(73) = 5.55, p < .001, indicating an expected win for Laval.

Laval-Montreal: Interest and Knowledge as Moderators As in Study 7 with the other teams, participants were classified as higher or lower in interest in Quebec university football if they scored above 3 (4,5,6) or below 3 (2,1,0) on both interest measures: interest in Bishop’s and interest in other Quebec teams. A 2 X 2 X 2 X 2 (Sex X Quebec Interest X Time X Team) mixed model ANOVA yielded three significant effects: team, F(1, 32)=14.46, p=.001, the interaction between time and team, F(1, 32) = 4.93, p=.039, and the interaction between sex and Quebec interest and team, F(1, 32)=4.62, p = .039. In addition, the effect of time approached significance, F(1, 32) = 3.34, p = .077. The first two effects also appeared in the main analysis above. Data for the three-way interaction are shown in Table 30. The interaction seems to be due to the high estimate for Laval that was given by women who were higher in Quebec interest. Estimates for Laval alone, for Montreal alone and for difference scores were examined with 2 X 2 X 2 (Sex X Quebec Interest X Time) mixed model ANOVAs. For Laval alone, there was a significant effect of time, F(1, 32) = 7.06, p = .012. Scores were higher before the game than after the game. In addition, the interaction between sex and Quebec interest approached significance, F(1, 32) = 3.17, p = .084. This trend was due to the relatively high estimate from women with higher Quebec interest. For Montreal alone, none of the effects were significant. For the difference scores, there was a significant effect of time, F(1, 32) = 4.93, p = .034, and a significant interaction between sex and interest, F(1, 32) = 4.62, p = .039. Difference scores declined over time. Difference scores were highest for women who were higher in Quebec interest. Table 30. Mean Estimated Number of Points by Women and Men as a Function of Quebec Interest for Laval and Montreal in Study 8

Interest Sex Higher Women Men Total Lower Women Men Total

n

Laval Before M

4 4 8 17 11 28

SD

Montreal Before M SD

After M

SD

37.00 22.00 29.50

6.78 11.91 12.04

15.50 19.50 17.50

3.70 3.79 4.07

19.75 17.75 18.75

5.62 6.18 5.57

19.58 24.64 21.57

10.38 14.22 12.04

19.83 17.27 18.82

19.53 11.31 16.58

23.71 16.81 21.00

20.72 9.80 17.37

SD

After M

43.50 27.00 35.25

15.97 14.99 16.83

30.77 31.09 30.89

18.52 15.10 16.96

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Table 31. Mean Estimated Number of Points as a Function of Subjective Knowledge for the Laval-Montreal Game in Study 8

Before Higher Lower After Higher Lower

n

Laval M

SD

Montreal M SD

Difference M SD

27 45

33.63 30.04

13.45 16.10

20.41 19.00

15.49 12.03

13.22 11.04

17.88 19.31

27 45

29.56 20.73

11.81 11.35

22.19 17.89

15.30 11.02

7.37 2.84

14.91 12.90

Table 32. Mean Estimated Number of Points as a Function of Objective Knowledge for the Laval-Montreal Game in Study 8

Before Higher Lower After Higher Lower

n

Laval M

SD

Montreal M SD

Difference M SD

21 30

32.19 29.77

13.54 16.70

15.86 22.67

7.23 17.47

16.33 7.10

13.97 22.94

21 30

27.38 22.67

11.63 12.16

17.24 22.97

7.54 17.36

10.14 -0.30

8.56 16.69

The difference scores are not shown separately in Table 30, but it can be seen that this effect accrues from the high estimates for Laval from women who were higher in Quebec interest (Ms = 43.5 points before the game and 37.0 points after the game). For subjective knowledge, a 2 X 2 X 2 X 2 (Sex X Subjective Knowledge X Time X Team) mixed ANOVA yielded five significant effects: subjective knowledge, F(1, 68) = 4.41, p = .039, time, F(1, 68) = 11.54, p = .001, team, F(1, 68) = 23.54, p < .001, the interaction between subjective knowledge and time, F(1, 68) = 4.32, p = .042, and the interaction between time and team, F(1, 68) = 9.70, p = .003. Inspection of Table 31 suggests that estimates were higher for people with higher knowledge than for people with lower knowledge, both before the game than after the game, and that estimates were also higher for Laval than for Montreal. Scores seemed to decline over time more for people who were lower in knowledge than for people who were higher in knowledge, and for Laval more than for Montreal. Next, 2 X 2 X 2 (Sex X Subjective Knowledge X Time) ANOVAs were conducted for difference scores and for each team considered separately. For Laval estimates, scores declined over time, F(1, 68) = 19.38, p < .001. For Montreal, there were no significant effects. For difference scores, scores declined over time, F(1, 68) = 9.70, p = .003. For objective knowledge, a 2 X 2 X 2 X 2 (Sex X Objective Knowledge X Time X Team) mixed ANOVA showed significant effects of time, F(1, 47) = 4.57, p = .038, team, F(1, 47) = 12.71, p = .001, the interaction between objective knowledge and team, F(1, 47) = 6.70, p = .013, and the interaction between time and team, F(1, 47) = 4.76, p = .034. See Table 32.

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71

Because team was involved in three of these effects, interpretation was based on the three followup tests. The 2 X 2 X 2 (Sex X Objective Knowledge X Time) ANOVAs were conducted on the estimates for each team alone and for the difference scores. For Laval, the effect of time was significant, F(1, 47) = 9.02, p = .004. Scores declined over time (see Table 32). For Montreal, only the effect of objective knowledge approached significance, F(1, 47) = 3.30, p = .076. Scores tended to be higher for people who were lower in knowledge than for people who were higher in knowledge (Table 32). For the difference scores, the effects of time, F(1, 47) = 4.76, p = .034, and of objective knowledge, F(1, 47) = 6.70, p = .013, were significant. Scores declined over time, and were higher for people who were higher in objective knowledge than for people who were lower (Table 32). Together, for the analysis that included objective knowledge as a factor, these results indicate that scores declined over time for Laval, were higher for Laval than for Montreal, and were higher for people with lower knowledge than for people with higher knowledge for Montreal.

Concordia-Sherbrooke: General Hindsight Bias For the game between Concordia and Sherbrooke, the mean scores in each condition are shown in Table 29. A 2 X 2 X 2 (Sex X Time X Team) mixed ANOVA with sex as a between subjects variable and both time and team as within subjects variables was conducted on the estimated number of points for each team before the game and after the game. Significance occurred for the main effect of team, F(1, 71) = 5.90, p = .018, the interaction between time and team, F(1, 71) = 11.99, p = .001, and the interaction between sex and team, F(1, 71) = 4.15, p = .045. Table 29 shows that estimates were higher for Concordia than for Sherbrooke, but only before the game. It also appears that scores declined over time for Concordia but not for Sherbrooke. The interaction between sex and team occurred because women tended to give higher estimates for Concordia than men, whereas men tended to give higher estimates to Sherbrooke than men (see Table 29). Also, women gave generally higher scores to Concordia than to Sherbrooke, whereas men did not. Three 2 X 2 (Sex X Time) mixed model ANOVAs were conducted on scores for each team and for the difference scores. For Concordia, the effect of time was significant, F(1, 71) = 12.59, p = .001. Scores declined over time. For Sherbrooke, none of the effects were significant. For the differences scores, the effects of time, F(1, 71) = 11.99, p = .001, and of sex were significant, F(1, 71) = 4.15, p =.045. The difference scores declined over time and were higher for women than for men. From Table 29, it can be seen that women gave generally higher scores to Concordia than to Sherbrooke, whereas men did not. Single-sample t-tests were conducted to compare the scores before the game with the actual scores. All three were statistically significant: t(73) = 7.30, p < .001 (Concordia), t(73) = 7.26, p < .001 (Montreal), and t(73) = 12.86, p < .001 (difference). For Concordia and for the differences scores, the estimates were higher than the actual score, and for Sherbrooke they were lower. A comparison of the mean difference score before the game to 0 was significant, t(73) = 3.87, p < .001, indicating an expected win for Concordia. Concordia-Sherbrooke: Interest and Knowledge as Moderators A 2 X 2 X 2 X 2 (Sex X Quebec Interest X Time X Team) mixed model ANOVA yielded one significant effects: the interaction between sex and team, F(1, 32) = 6.88, p = .013. This interaction also appeared in the main analysis above.

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Estimates for Concordia alone, for Sherbrooke alone and for difference scores were examined with 2 X 2 X 2 (Sex X Quebec Interest X Time) mixed model ANOVAs. For Concordia alone, there was a significant effect of sex, F(1, 32) = 5.42, p = .026. As noted above, women gave higher estimates than men. For Sherbrooke alone, none of the effects were significant. For the difference scores, there was a significant effect of sex, F(1, 32) = 6.88, p = .013, an effect that was also found in the main analysis. For subjective knowledge, a 2 X 2 X 2 X 2 (Sex X Subjective Knowledge X Time X Team) mixed ANOVA yielded three significant effects: team, F(1, 68) = 5.51, p = .022, the interaction between sex and team, F(1, 68) = 4.08, p = .047, and the interaction between time and team, F(1, 68) = 6.89, p = .011. All three effects appeared above. Next, 2 X 2 X 2 (Sex X Subjective Knowledge X Time) ANOVAs were conducted for difference scores and for each team considered separately. For Concordia estimates, scores declined over time, F(1, 68) = 7.76, p = .007. For Sherbrooke, there were no significant effects. For difference scores, scores declined over time, F(1, 68) = 6.89, p = .011, and there was a significant effect of sex, F(1, 68) = 4.08, p = .047. These effects also appeared above. Finally, for objective knowledge, a 2 X 2 X 2 X 2 (Sex X Objective Knowledge X Time X Team) mixed ANOVA showed three significant interactions: between time and team, F(1, 47) = 6.51, p = .014, between sex and team, F(1, 47) = 5.37, p = .025, and between objective knowledge and team, F(1, 47) = 11.36, p = .002. The first two effects appeared above, but the third one indicated that estimates were generally higher for Concordia than for Sherbrooke for people who were higher in objective knowledge but not for those who were low in objective knowledge (see Table 33). Also, for Sherbrooke but not for Concordia, people who were lower in objective knowledge gave higher estimates than people who were higher. For the three separate followup tests, 2 X 2 X 2 (Sex X Objective Knowledge X Time) ANOVAs were conducted on the estimates for each team alone and for the difference scores. For Concordia, the effect of time was significant, F(1, 47) = 6.29, p = .016. Again, scores declined over time. For Sherbrooke, the effect of objective knowledge was significant, F(1, 47) = 11.13, p = .002. People who were lower in knowledge gave higher estimates than people who were higher in knowledge. For the difference scores, the effects of time, F(1, 47) = 6.51, p = .014, of objective knowledge, F(1, 47) = 11.36, p = .013, and of sex, F(1, 47) = 5.37, p = .025, were significant. Table 33. Mean Estimated Number of Points as a Function of Objective Knowledge for the Concordia Sherbrooke Game in Study 8

Before Higher Lower After Higher Lower

n

Concordia M SD

Sherbrooke M SD

Difference M SD

21 30

23.81 25.30

11.47 12.70

15.14 23.63

7.28 13.24

+8.67 +1.67

13.88 12.11

21 30

21.90 19.80

10.52 11.64

15.95 23.67

6.37 12.30

+5.95 -3.87

13.20 10.90

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73

Scores declined over time, were higher for people who were higher in objective knowledge than for people who were lower, and were higher for women than for men. For the analysis with objective knowledge, the new result here was the association with team. Estimates were higher for Concordia than for Sherbrooke for people with higher knowedge but not for people with lower knowledge. Also, estimates were higher for people with lower knowledge than for people with higher knowledge for Sherbrooke but not for Concordia.

DISCUSSION Bishop’s Game The number of people who predicted a win for Bishop’s was similar both before and afer the game, and the numbers were similar for men and for women. The predicted Bishop’s score, McGill score, and difference score were all significantly different from the actual score, indicating that a hindsight effect was possible. The predicted outcome was a win for McGill by 7 points. The McGill win by 14 points was classified as not surprising (see Table 1). Notably, 7 and 14 were at the extremes of the same category, which might be considered as close to a difference that could be considered a surprise, but a small surprise. Table 25 shows that the mean number of points for Bishop’s before and after the game were 15.85 points and 13.32 points respectively, a significant change towards the actual score of 0 points. This constitutes a hindsight effect. The changes for Montreal (22.90 to 21.30, a move towards 14) and for the difference score (-7.14 to -8.01, a move towards -14) were both small and not significant. Given that the present outcome was classified as not surprising, lack of a hindsight effect for McGill and for the difference scores is consistent with Pezzo’s (2003) model. However, the hindsight effect for Bishop’s is not. Of the outcome is not a surprise then, according the model, no processing is necessary, and there will be no hindsight bias. However, f the present outcome is considered as a surprise (small), the Bishop’s hindsight effect is consistent with the model if participants made sense of it, and the other two results of no hindsight effect are consistent if participants did not make sense of them. However, apart from the surprise model, because the Bishop’s loss would have been a negative outcome, the hindsight effect for Bishop’s is not consistent with the finding that the hindsight effect is less likely under negative circumstances than under positive ones (Pezzo and Beckstead, 2008). For the Bishop’s game, there were no sex differences in the score estimates, including the hindsight effect, and no sex differences in the scores for interest or for knowledge. In addition, although the correlations among the four scores for interest and for knowledge were all positive, only some of them were significant The two interest scores were significantly related to each other and the two knowledge scores were significantly related to each other, and . interest on other Quebec teams was significantly related to objective knowledge. Notably, in Study 7, the three subjective scores were all related significantly to each other, but in Study 8, neither interest score was significantly related to subjective knowledge. As in Study 7, interest was examined as a factor in two ways: as a measure of interest in Bishop’s performance and as a measure of Quebec university football team performance in

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general. There were no interactions between interest and time, indicating that there were no differential hindsight effects as a function of interest. However, interest was a factor in the estimates for each team. People who were lower in interest favored McGill over Bishop’s whereas people who were higher in interest did not. This result is somewhat similar to the relationship between interest team preference in Study 7, where people with more interest in both Bishop’s and Quebec university football favored Bishop’s and people with less interest favored Montreal. This suggests that people who were more interested in Quebec football in general and, in Study 8, in Bishop’s performance in particular, may have been demonstrating their loyalty to Bishop’s. However, subjective knowledge was a factor in the hindsight effect for difference scores, which declined over time for people who were lower in knowledge but not for people who were higher in knowledge. Inspection of Table 27 indicates that the major reason for the decline in scores was a decline in the Bishop’s estimate. Consequently, there seems to be evidence here for a hindsight effect on Bishop’s scores for people with lower subjective knowledge. Objective knowledge was not a factor in the hindsight effect but, like interest, it was related to the estimates for each team. That is, like interest, people who were lower in knowledge favored McGill over Bishop’s whereas people who were higher in interest did not. It seems that people who were more interested in Quebec university football and who knew more about it favored Bishop’s in their estimates. It is ironic that people who knew more about football were less accurate in their assessment of the outcome of the game than people who knew less. Those who knew more predicted that the score would be similar for each team and those who knew less predicted that McGill would win, which was the actual result. Again, those who knew more may have been loyal to Bishop’s.

Other Games For both games the chi square tests on the number of people (men or women) estimating wins and losses before and after the game were not significant. As in all other games, with or without Bishop’s, there is no evidence of hindsight bias from these counts. For the game between Laval and Montreal, the predicted Laval score, Montreal score, and difference score were all significantly different from the actual score, indicating that a hindsight effect was possible. The predicted outcome was a win for Laval by 12.0 points. According to Table 1, the Montreal win by 5 points was classified as a surprise (medium surprise). Table 29 shows that the mean number of points for Laval before and after the game were 15.9 points and 13.3 points respectively, a significant change towards the actual score of 2 points. This is a hindsight effect. The changes for Montreal (19.5 to 19.4, a move towards 7) and for the difference score (12.0, 4.6, a move towards -5) were both not significant. Given that the present outcome was classified as a medium surprise, the hindsight effect for Laval is consistent with Pezzo’s (2003) model if it is assumed that participants were able to make sense of the result. The lack of a hindsight effect of Montreal and for the difference score fit the model if it is assumed that participants could not makes sense of them. As in Study 7, interest for other teams was measured by interest in Quebec university football team performance in general. There were no interactions between interest and time, indicating that there were no differential hindsight effects as a function of interest. However, women who were higher in interest predicted a higher score for Laval than women who were lower in interest. This was the only sex difference in estimates for this game.

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75

Subjective knowledge was a factor in the hindsight effect in one place: scores in general declined over time more for people were lower than higher in subjective knowledge. However, although the three-way interaction between subjective knowledge, time and team was not significant, it can be seen that the larger decline over time occurred with the estimates for Laval. That is, the hindsight effect for Laval estimates was enhanced for people who were lower in subjective knowledge. Objective knowledge was not a factor in the hindsight effect, but people with lower objective knowledge estimated higher scores for Montreal (approximately 23) than people with higher objective knowledge (approximately 16). Given that Montreal scored 7 points, the people with higher knowledge were more accurate. For the game between Concordia and Sherbrooke, the predicted Concordia score, Sherbrooke score, and difference score were all significantly different from the actual score, indicating that a hindsight effect was possible. The predicted outcome was a win for Concordia by 6.0 points. The Sherbrooke win by 14 points was classified as a surprise (medium surprise) (Table 1). Because 14 is on the borderline between the categories of . 24). In the third cases, with team as the unit, the 2 X 2 (Surprise X Sex ANOVA showed that the effect of surprise was significant, F(1, 60) = 12.32, p = .001. Table 36. Standardized Effect Sizes for Changes over Time as a Function of Surprise

Game as Unit Team 1 Team 2 Difference Score Team as Unit

No Surprise n M

SD

Surprise n M

SD

6 6 6 12

0.32 0.34 0.20 0.32

26 26 26 52

0.26 0.30 0.28 0.28

-0.18 -0.07 0.05 -0.13

0.21 0.20 0.20 0.20

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The hindsight bias was greater when the outcome was surprising than when it was not surprising. Therefore, although there was no relationship between surprise and hindsight with the box score counts, the hindsight effect was found to be greater when the game outcome was surprising when the data were quantified with effect sizes. These results support Pezzo’s (2003) model of surprise. In particular, the mean effect size when there was no surprise was close to zero (see Table 36), as Pezzo’s model predicts. This result is also consistent with the box score count with no surprise, where only one out of 12 outcomes showed hindsight. In contrast, when the outcome of the game was surprising, the mean effect size for the hindsight effect is approximately d = 0.20. Although small by Cohen’s (1977) guidelines, it is significantly greater than the effect with no surprise. If Pezzo’s model is correct, this occurred because at least in some games participants were able to make sense of the score. In the present paper, an extended version of Pezzo’s model was proposed, but it was not possible to test it because there was an insufficient number of cases in the different categories of surprise. However, the support for Pezzo’s model stands in contrast to the null results that were obtained with the box score measure, which is less sensitive to amounts of change of time than the standardized effect size measure. In future research, both Pezzo’s model and McKelvie’s extended model could perhaps be tested by experimentally manipulating outcomes to create different degrees of surprise. In addition, perhaps along the same lines as Sanna and Schwarz’s (2003) investigation of counterfactual thinking and the number of reasons considered for game outcomes, sensemaking activities might also be manipulated to examine their effects on participants’ postgame judgments. If more studies are conducted with actual games, it would be useful to have a more equal balance of wins and losses for the local team. It was unfortunate that, in the eight games with the local team in the present study, Bishop’s was only victorious in one of them.

Moderator Variables The moderator variables of sex of participant, self-involvement, and expertise were also examined quantitatively. To examine sex as a factor in the hindsight effect, a comparison was made between the effect sizes for women and men in Bishop’s games and the other games, keeping separate the teams in each game. For this analysis, there were only seven Bishop’s games rather than eight because sex of participant was not recorded in Study 1. In the 2 X 2 X 2 (Game X Sex X Team) mixed ANOVA, none of the effects were significant, particularly sex, F(1, 28) = 0.02, p = .894, although the interaction between game and sex approached significance, F(1, 28) = 3.08, p = .09. As Table 37 shows, there was a trend in which the changes over time (in the hindsight direction) were slightly greater for men than for women in the other games. For difference scores (Table 37), the 2 X 2 (Game X Sex) between-groups ANOVA also failed to show any significant effects, particularly for sex, F(1, 28) = 0.48, p = .493, or for the interaction between game and sex, F(1, 28) = 2.65, p = .115. These results, showing no sex differences in the hindsight effect are in accord with the results of the simple counts in the box score analysis.

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Table 37. Standardized Effect Sizes for Changes over Time for All Participants and for Women and Men for Bishop’s Games and Other Games

Bishop’s Games Women Men Other Games Women Men Other Teams

n 8 7 7 9 9 9 27

Team 1 M 0.06 0.07 0.03 0.12 0.13 0.27 0.17

SD 0.29 0.38 0.31 0.25 0.31 0.25 0.23

Team 2 M 0.19 0.27 -0.01 0.20 0.09 0.23

SD 0.25 0.39 0.31 0.22 0.27 0.32

Difference M SD 0.14 0.19 0.17 0.29 0.08 0.12 0.20 0.25 0.09 0.26 0.32 0.34

Table 38. Standardized Effect Sizes for Changes over Time for Each Team in Bishop’s Games and Other Games as a Function of Interest and for all Games as a Function of Objective Knowledge

n Interest Bishop’s Games Higher 3 Lower 7 Other Games Higher 3 Lower 9 Objective Knowledge Higher 4 Intermediate 4 Lower 4

Team 1 M SD

Team 2 M SD

Difference M SD

0.19 0.08

0.06 0.18

0.24 0.06

0.28 0.18

0.13 0.15

0.09 0.10

0.14 0.09

0.19 0.13

0.32 0.25

0.41 0.29

0.21 0.14

0.40 0.23

0.12 0.39 -0.04

0.32 0.19 0.31

0.02 0.19 0.04

0.20 0.17 0.55

-0.38 0.25 0.13

0.36 0.17 0.27

To investigate self-involvement as a factor in the hindsight effect, a comparison was firstly made between the eight Bishop’s games and the nine other games, the hypothesis being that the hindsight effect would be greater for the Bishop’s games. An effect size was derived for each team in each game, and the data were analyzed with 2 X 2 (Game X Team) mixed model ANOVA. None of the effects were significant, showing that the means, which are shown in Table 38, did not differ, F(1, 15) = 0.15, p = .700 (Game), F(1, 15) = 1.80, p = .200 (Team), and F(1, 15) = 0.12, p = 731 (interaction between Game and Team). The means for the difference scores (see Table 37) for the Bishop’s game and the other games were also not significantly different, t(15) = 0.52, p = .611. In addition, a comparison was made between estimates for Bishop’s and all other teams (i.e., the Bishop’s opponents and the teams in all the other games), but this was also not significant, t(32) = 1.10, p = .277 (see Table 38 lower part). Thus, there was no evidence that effect sizes were greater in Bishop’s games than in other games, or for Bishop’s than for all other teams, both of which might be expected if selfinvolvement was a factor in the hindsight effect.

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As a second approach to self-involvement, the subject variable of interest was examined as a possible moderator of the hindsight effect. Here, both measures of general interest (the global measure, the combined measure for Bishop’s and for other teams) were considered together. That is the comparisons of people classified as higher or lower could refer to any of these measures of interest. A 2 X 2 X 2 (Game X Interest X Team) mixed ANOVA gave no significant effects, particularly for interest, F(1, 12) = 1.21, p = .293, or for the interaction between game and interest, F(1, 12) = 0.28, p = .609. A 2 X 2 (Game X Interest) ANOVA on the difference scores also gave no significant effect for interest, F(1, 12) = 0.04, p = .838, or for the interaction between game and interest, F(1, 12) = 0.13, p = .724. See Table 38. To examine this variable further, all teams were considered individually and effect sizes were compared for people who were higher and lower in interest. The hindsight effect sizes were not significantly different, t(30) = 1.05, p = .343 (see Table 39). Thus, there was no evidence that the hindsight effect was greater for people who were higher in interest than for those who were lower in interest, as might be expected if the hindsight effect was related to selfinvolvement. These results are consistent with the box score counts, which did not show that the hindsight effect was more likely when self-involvement was higher. Finally, with regard to expertise, knowledge was examined as a possible moderator of the hindsight effect, the hypothesis being from past research that the effect would be greater for people with less knowledge than for people with more knowledge (Christensen-Szaalanski and Willham, 1999; Gray et al., 2007). In addition, the box score count produced one significant result that was similar that: in two cases, the hindsight effect occurred for people who were lower in subjective knowledge but not for people who were higher in objective knowledge. However, and again with the box score counts, when knowledge was measured objectively, one other significant hindsight effect occurred: for estimates of the Bishop’s score for people who were intermediate in their objective knowledge compared to people who were higher or lower. For the present analysis of effect sizes, objective knowledge of the team records for the Bishop’s game was the only measure that was repeated sufficiently often across the studies (four times) to justify including it as a factor. Considering each game as the unit 3 X 2 (Objective Knowledge X Team) mixed ANOVA gave no significant effects, particularly for knowledge, F(2, 9) = 1.35, p = .308, or for the interaction between knowledge and team, F(2, 9) = 0.69, p = .528. See Table 38. Taking each team as the unit, a one-way ANOVA with knowledge as the factor was also not significant, F(2, 21) = 2.02, p = .158 (see Table 40). However, when the effect size for the difference scores for each game were examined, the one-way ANOVA showed that there was a significant effect of objective knowledge, F(2, 9) = 5.84, p = .024. A post hoc Newman-Keuls tests showed that the effect size was smaller for the highest level of knowledge (score = 2) than for the intermediate (score = 1) or lowest levels (score = 0), which did not differ. See Tables 38 and 39. This was not the same effect that occurred with the box score count, where the hindsight bias occurred for people with intermediate knowledge when they judged the Bishop’s score. Thus, considering the effect sizes for the changes over time in the estimates for each team, the hindsight effect was not greater for people who were lower in knowledge than for those who were intermediate or higher in knowledge, as would be expected from previous research on expertise (Christensen-Szaalanski and Willham, 1999; Gray et al., 2007) and in two cases with the box score count in the present investigation.

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Table 39. Standaridized Effect Sizes for Changes over Time for All Games as a Function of Interest and of Objective Knowledge Team Scores n M Interest Higher 16 Lower 16 Objective Knowledge Higher 8 Intermediate 8 Lower 8

SD

Difference Scores n M SD

0.22 0.13

0.27 0.20

8 8

0.18 0.14

0.31 0.18

-0.003 0.29 0.07

0.42 0.20 0.25

4 4 4

-0.38 0.25 0.13

0.36 0.17 0.27

However, the significant effect of objective knowledge with difference scores indicated that the hindsight effect was lowest for people with most knowledge (-0.38) compared to those with intermediate knowledge (0.25) or the least knowledge (0.13) (Tables 38 and 39). In contrast to the nonsignificant result with teams as the unit, this finding is consistent with the previous reports that the hindsight is greater for people who are relatively lower in knowledge. Notably, the lowest score is negative, showing a reversed hindsight effect for people with the highest knowledge. In previous research, the only cases of reverse hindsight occurred when surprise was high (Calvillo and Gomes, 2011; Ofir and Mazursky, 1997). Although the present result is new, and perhaps intriguing, it was based on only four cases (see Tables 38 and 39, and on a measure that only reflected knowledge of win/loss records of teams in Bishop’s games. It did not occur in Study 8 with a more extensive measure of knowledge based on the win/loss records of six teams. Future research should examine this question again, to find out if the finding can be replicated.

CONCLUSION The major goal of the present investigation was to investigate if the hindsight effect, which has been found in the laboratory and with real-life events, could be reliably replicated with a real-life sporting event: Canadian university football games. It was also hoped that the results would have implications for theory, particularly Pezzo’s (2003) surprise model that the hindsight effect occurs when people can make sense of an unexpected outcome. The possible moderating roles of subject variables (sex, self-involvement, and expertise of the participants) were also examined. Based on the box count score of significant and nonsignificant differences between preand post-game estimates, the vast majority of the tests for hindsight were not significant. The effect only appeared sporadically throughout the eight studies. However, when it was documented by combining effect sizes, the effect was significant, but very small. This might indicate that the hindsight effect rarely occurs in the present real-life situation, or it might indicate that, like some other phenomena (Leher, 2010; Schooler, 2011), an apparently robust effect has become weaker over time.

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Turning to theory, based on box score counts, neither Pezzo’s (2003) model of surprise or McKelvie’s extended model of surprise received empirical support. However, the analysis of effect sizes showed that the hindsight bias was greater for surprising than for non surprising outcomes, as predicted by Pezzo’s model. There were no sex differences and no evidence that hindsight was more prevalent in people who were more self-involved with football. However, there was some support for the contention that hindsight bias might be more likely to occur with people who are less knowledgeable about football. In addition, there was evidence of a loyalty effect in which participants who were more interested in university football (both in general and more specifically in Bishop’s), gave estimates that favoured Bishop’s. Indeed, loyalty or allegiance is another cognitive bias that could be included when sport is the event being studied. In future research, more attention should be also given to investigating the hindsight effect in everyday life, with people who have different degrees of expertise. In addition, to provide information about the reasoning processes postulated by Pezzo’s model, information about participants’ sense-making activities should be gathered, and to provide a rigorous test of McKelvie’s extended model of surprise, events with a wide variety of outcomes should be included. Finally, these naturalistic studies could be complimented by experimental investigations in which the degree of surprise is manipulated.

AUTHOR NOTE Send correspondence to Stuart J. McKelvie, Department of Psychology, Bishop’s University, 2600 College Street, Sherbrooke, Quebec J1M 1T3, Canada, or e-mail ([email protected]).

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In: Advances in Psychology Research. Volume 96 Editor: Alexandra M. Columbus

ISBN: 978-1-62417-250-2 © 2013 Nova Science Publishers, Inc.

Chapter 2

N-METHYL-D-ASPARTATE ENHANCING AGENTS: A NEW CLASS OF NOVEL ANTIPSYCHOTIC DRUGS Huey-Jen Chang,1,2 Hsien-Yuan Lane1,3 and Guochuan E. Tsai*4 1

Institute of Clinical Medical Science, China Medical University, Taichung, Taiwan 2 Department of Psychiatry, Taichung Veterans General Hospital, Chiayi and Wanqiao Branch, Chiayi, Taiwan 3 Department of Psychiatry, China Medical University Hospital, Taichung, Taiwan 4 Department of Psychiatry, Harbor-UCLA Medical Center, US

ABSTRACT Glutamatergic neurotransmission, particularly through the N-methyl-D-aspartate (NMDA) receptor, has drawn attention for its emerging role in the pathophysiology of schizophrenia. This chapter reviews the symptom domains of schizophrenia and their importance in predicting the long-term outcomes of this illness, the evolution of the concept in the pathophysiology of schizophrenia from the dopaminergic, serotonergic to glutamatergic hypothesis through decades, the physiology of each type of glutamate receptors, the evidence of NMDA receptor dysfunction in schizophrenia based on various clinical models and genetic studies. The clinical efficacy and safety of currently available NMDA-enhancing agents, either as adjuncts to typical/atypical antipsychotics or as monotherapy, in schizophrenic patients, particularly those with refractory negative and cognitive symptoms are under studies and revealing encouraging results. Novel antipsychotics acting to correct this dysfunction are on the way for development.

* Correspondence: Guochuan Emil Tsai, MD, PhD, Department of Psychiatry, Harbor-UCLA Medical Center HH212, 1000 W. Carson Street, Torrance, CA 90509, USA, Tel.: +1 310 781 1401; fax: +1 310 781 1093, Email address: [email protected].

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1. INTRODUCTION Clinical manifestation of schizophrenia consists of multiple symptom dimensions, including positive symptoms, negative symptoms, and neurocognitive deficits (Keefe et al., 1999; Heaton et al., 2001). Positive symptoms may fluctuate during the course of the illness, but negative symptoms and cognitive dysfunction remain relatively constant (Tamminga et al., 1998). Each of these symptoms contributes to the morbidity of the illness, leading to various functional impairments, such as performance of independent living skills, social functioning, and occupational/educational performance and attainment. In particular, negative symptoms and neurocognitive deficits have high predictive values for long-term disability, and has become a target for therapy (Green 1996; Weinberger and Gallhofer 1997; Velligan et al., 1997; Sharma and Antonova, 2003; Milev et al., 2005; Lysaker and Davis, 2005). Based on the proposed neurochemical hypothesis, from dopamine (DA) to serotonin, the development of antipsychotics has made a remarkable step in ameliorating symptoms of schizophrenia. Typical antipsychotics treat the positive symptoms of schizophrenia, but they have little effect on negative and cognitive symptoms (Smith et al., 2010; Tandon et al., 2008). Although atypical antipsychotics have demonstrated more efficacy on alleviating negative symptoms and cognitive impairments, these results are inconsistent and modest (Leucht et al., 1999; Keefe et al., 1999); therefore, most schizophrenic patients still suffer from lifelong illness and deteriorating function (Tsuang et al., 2000; Hwu et al., 2002; Malla and Payne, 2005; Abbott 2010; Insel 2010). Moreover, the side-effect profiles of atypical antipsychotics, including weight gain, hyperglycemia, diabetes mellitus, hyperlipidemia, metabolic syndrome, and sudden cardiac death, gravely compromise their clinical value (Gaulin et al., 1999; Lindenmayer et al., 2001; Lu et al., 2004; Bai et al., 2006; Lane et al., 2006; Lin et al., 2009; Ray et al., 2009; Hong et al., 2010; Liou et al., 2010), thus leaving substantial rooms for further development of new pharmacological agents that have better efficacy but devoid of these detrimental side effects (Kane and Malhotra, 2003; Tsai and Lin, 2010; Insel 2010). Over the last 2 decades, alternative neurochemical models of schizophrenia have been developed based on the observation that the psychotomimetic agents phencyclidine (PCP) and ketamine induced psychotic symptoms and neurocognitive dysfunction which resemble schizophrenia more closely than those of amphetamine/DA agonist induced (Krystal et al.,1994) by blocking neurotransmission at N-methyl-D-aspartate (NMDA) subtype glutamate receptor (NMDAR). Therefore, the emerging role of glutamatergic neurotransmission in the pathophysiology of schizophrenia has gained more attention (Lane et al., 2010; Tsai and Lin, 2010; Insel 2010; Olney and Farber, 1995). This has lead researchers to focus on glutamatergic neurotransmission and NMDAR as a basis for new drug development and a growing number of compounds targeting NMDAR have entered preclinical and clinical testing.

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2. EVOLUTION OF THE CONCEPT IN PATHOPHYSIOLOGY OF SCHIZOPHRENIA 2.1. Dopamine Hypothesis and Conventional Antipsychotics Chlorpromazine was the first antipsychotic drug discovered. The era of effective pharmacological treatment of schizophrenia began with the introduction of chlorpromazine in the early 1950s (Davis et al, 1991; Tamminga, 2005). Haloperidol and other conventional antipsychotics with similar pharmacological profile to chlorpromazine were introduced in the late 1950s (Janssen et al., 1959; Ayd and Blackwell, 1972). The DA hypothesis was formulated based upon clinical observations that the conventional antipsychotic medication can improve the positive symptom of schizophrenia. Clinical psychopharmacological research with these drugs proceeded rapidly since then. On the basis of neuropharmacological research in rodent with haloperidol and chlorpromazine, Carlsson and Lindquist founded their seminal hypothesis in 1963, that a hyperactivity of central DA transmission is responsible for the symptoms of schizophrenia and the blockade of DA receptors is responsible for the clinical effects of antipsychotic drugs (Carlsson and Lindqvist, 1963; Carlsson 1988). A major line of evidence supporting the DA hypothesis was provided by a challenge model of DA agonist. It was found that high doses of amphetamine, which release DA in the mesolimbic system (Beier et al., 1994), induce psychotic symptoms (e.g. delusion and hallucination) that closely resemble schizophrenic symptoms in healthy participants (Bell 1973). In addition, it was found that low doses of dopaminergic agonists that typically do not induce positive symptoms in healthy participants can induce positive symptoms in participants with schizophrenia (Janowsky et al., 1973). However, the dopaminergic hyperactivity model is limited by the fact that the DA agonists employed in these experiments were only able to induce positive, but not negative symptoms. Therefore, the scope of DA hyperactivity in producing schizophrenic symptoms is limited to positive symptoms. Creese and collaborators demonstrated molecular blockade of DA receptors by conventional antipsychotics with X-ray crystallography (Creese et al., 1975). Other neurochemical brain imaging studies also helped to clarify and refine the original DA hypothesis by allowing close examinations of pre-synaptic activity, intrasynaptic levels of DA, and post synaptic receptors. For further support of the DA hypothesis, the clinical doses of typical antipsychotics were found to correlate very well with their ability to block D2 receptors in the mesolimbic (A10) pathways (Seeman 1987). However, this correlation is a circular argument since the development of conventional antipsychotics was based upon their potency of D2 blockade. Chronic administration of these therapeutically effective antipsychotics produces a nearly complete inhibition of the firing of DA neurons, which project from the ventral tegmentum (VTA) to the limbic forebrain (Lehmann and Ban, 1997), but D2 receptor occupancy does not necessarily correlate with clinical benefit (Jones and Pilowsky, 2002). Some patients taking therapeutic doses of typical antipsychotic drugs not only failed to benefit from the treatment, but also had levels of central D2 receptor blockade in excess of 90% (Wolkin et al., 1989; Pilowsky et al., 1993). This finding obviated the pharmacokinetic explanations that poor clinical effect was the result of low brain penetration or increased wash-out of typical

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antipsychotic drugs in treatment-resistant individuals. Indeed, some patients who responded well to treatment showed remarkably low levels of D2 receptor blockade (Pilowsky et al., 1993; Jones and Pilowsky, 2002). In summary, failure to respond clinically, in particular the negative symptoms and neurocognitive deficits, is not a function of antipsychotic uptake or binding in the CNS (Wolkin et al., 1989). Furthermore, the correlations between the clinical efficacy of antipsychotic drugs and the in vitro binding affinity of the muscarinic cholinergic, histaminergic (H1), serotonergic (5-HT2) and α-1 receptors, are also poor (Peroutka and Snyder, 1980). Increased striatal D2 receptor density was reported by some authors (Lee and Seeman, 1980; Mackay et al., 1982), but these findings were questioned on the basis that the data were obtained by studying antipsychotic-treated patients. Typical antipsychotic therapy could, in itself, cause D2 receptor upregulation (Clow et al., 1980). Study of drug-naive people with schizophrenia using positron emission tomography (PET) and single photon emission computerized tomography (SPECT) imaging techniques could control for this confounding factor (Meisenzahl et al., 2007). Though an increase in the level of both tonic and phasic dopaminergic transmission in patients with schizophrenia was demonstrable (Grace 1991), these studies did not, on the whole, support an increased striatal D2 receptor density in schizophrenia (Farde et al., 1990; Martinot et al., 1990; Pilowsky et al., 1994). Modern neuroimaging procedures revealed the crucial role of a hyperdopaminergic system in schizophrenia pathology. The association with an elevation of striatal D2 receptors has recently been further studied using IBZM SPECT after application of amethylparatyrosine (AMPT) to acutely deplete DA in the synaptic cleft (Abi-Dargham et al., 1998) with the finding of an elevated number of striatal D2 receptors in schizophrenia (Klemm et al., 1996). In a similar study investigating the effect on both D1 and D2 receptors, AMPT induced DA depletion uncovered D2 receptors, but it did not do so for D1 receptors. It has been speculated that the relative up-regulation of D2 receptors in schizophrenia (Vorugant et al., 2001) may reflect constantly increased, basal DA levels (Seeman and Kapur, 2000). The current version of DA hypothesis proposes that the mesolimbic DA hyperactivity may be partially responsible for the positive symptoms whereas the mesocortical DA hypoactivity may contribute to the negative symptoms (Guillin et al., 2007). The ventral tegmental area (VTA) gives rise to the mesocortical and mesolimbic DA systems, which are involved in cognition, memory, reward and behavioral control (Glowinski et al., 1984; Williams and Goldman-Rakic, 1995; Robbins 2000; Tzschentke and Schmidt, 2000; Schultz 2004). Psychotic and cognitive/negative symptoms in schizophrenia appear to be associated with an overactivity of the mesolimbic pathway and a hypofunction of the mesocortical pathway, respectively (Carlsson 1988; Laruelle et al., 1996; Abi-Dargham et al., 2000). But the DA hypothesis has limitations. Typical antipsychotics were initially introduced in the hope of reversing the deteriorating course that characterizes schizophrenia. Typical antipsychotics did indeed reduce psychotic symptoms, but patients continued to have problems with their ability to think clearly, function effectively, or relate emotionally to others. In the 21st century, the therapeutic efficacy has been redefined, with the goal of seeking a treatment that will ameliorate all the domains of the illness, including negative symptoms and cognitive impairments, in addition to positive symptoms (Lieberman et al., 2008). Although a primary aberration in DA function in schizophrenia cannot be ruled out,

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the possible involvement of other amine, amino acid, or peptide transmitters in schizophrenia cannot be disregarded (Carlsson 1978).

2.2. Serotonin Hypothesis and Atypical Antipsychotics Serotonin has been implicated in a variety of behaviors and functions that are disturbed in schizophrenia, such as cognition, sensory gating, mood, aggression sexual drive, appetite, energy level, pain sensitivity, and sleep, which are clearly relevant to the pathophysiology of positive/negative symptoms and cognitive impairments (Meltzer 1995). However, as schizophrenia is a heterogeneous illness and the serotonergic neurotransmission is a complex system, Meltzer and Fatemi (1996) have suggested that no single type of abnormality of the serotonergic or other neurotransmitter system is likely to explain the characteristics of all patients who meet criteria for this illness. A comprehensive examination of serotonergic function, in relation to dopaminergic activity in a wide range of schizophrenic patients, need to be carried out. Functional alterations in the serotonergic system affect multiple neurotransmitter systems (e.g., glutamate, GABA, norepinephrine, acetylcholine, and DA) (Roth and Meltzer, 2000) and cause the various similar behavioral disturbances as in schizophrenia. Therefore, pharmacologic manipulation of the serotonergic system may be the target for treatment of positive/negative symptoms and cognitive function, as well as modulate extrapyramidal function. Kapur and Remington (1996) and Schmidt et al. (1993) have reviewed the clinical and preclinical evidence, which supports this hypothesis. In the 1950's serotonin's possible role in schizophrenia was first recognized when the challenge of the potent synthetic hallucinogenic drug, lysergic acid diethylamide (LSD), which stimulates 5-HT2A receptors (Roth and Meltzer, 1995), resulted in psychosis like symptoms (Claridge 1994; Vardy and Kay, 1983). These observations eventually led to a preliminary hyper-serotonin hypothesis for schizophrenia (Akhondzadeh 2006). This hypothesis was further evidenced by the mechanism of clozapine, which showed a strong 5HT2A receptor antagonism but weak direct dopaminergic antagonist effect, has provided dramatic improvements in patients who were resistant to typical antipsychotics. Clozapine, a prototype of atypical antipsychotic drugs, has been shown to be more effective in reducing symptoms of schizophrenia than the older typical antipsychotics (Kane and McGlashan, 1995; Buchanan et al., 1998; Ashby and Wang, 1996; Meltzer et al., 1999). Therefore, the principal mechanism of symptom relief with atypical antipsychotics is postulated to be via serotonin antagonism other than D2 blockade (Meltzer 1989). This hypothesis was confirmed with the study result of a substantial relief of patients’ negative symptoms and motoric side effects in combined use of typical antipsychotics with a 5-HT2 antagonist, such as ritanserin (Akhondzadeh et al., 2008). 5-HT2A receptor antagonism is of value in an antipsychotic drug. The ratio of 5-HT2A/D2 affinities (Lee et al., 2003) distinguish between typical and atypical antipsychotics (Meltzer et al., 1989) better than any other known pharmacologic feature. Risperidone and olanzapine, both of which have high 5-HT2A receptor blocking activity relative to their D2 affinity, have demonstrated their greater efficacy for treating negative symptoms of schizophrenia and produce fewer extrapyramidal symptoms than haloperidol (Nyberg et al., 1999; Kapur et al., 1998; Kapur et al., 1999). The evidence of the ratio of dopaminergic to serotonergic activity

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was demonstrated by the low CSF ratio of HVA/5-HIAA, which correlated with antipsychotic response to clozapine (Risch and Lewine, 1995; Soderstrom et al., 2003). In addition, clozapine behaves as a partial agonist at 5-HT1A receptors, but haloperidol and other antipsychotics lack this property. Thus, an enhancement of frontocortical DA with the efficacy against negative symptoms and reduction in extrapyramidal side effect profile may be, in part, mediated via activation of 5-HT1A receptors (Rollema et al., 1997). PET studies permit measurements of 5-HT receptor density in the brains of schizophrenic patients, both on and off medication. Farde et al. (1992) and Nyberg et al. (1999) found that mean D2 receptor occupancy was lower than mean 5-HT2A receptor occupancy for atypical antipsychotics during successful treatment, indicating D2 receptor antagonism alone does not explain the efficacy of these medications. Taken together, these findings were consistent with the hypothesis that the efficacy of clozapine depends on a combined effect on 5-HT and DA neurotransmission and with the notion of a combined 5-HT/DA discrepancy in schizophrenia, implicating that clozapine may be most effective in decreasing serotonergic than dopaminergic activity and in preserving prefrontal dopaminergic activity, therefore the cognitive function. There is a strong evidence indicating that the 5-HT system modulates dopaminergic activity and vice versa (Gobert and Millan, 1999; Ichikawa et al., 2001a; Minabe et al., 2001; Bortolozzi et al., 2005). This interaction occurs at the level of the cell bodies in the VTA, substantia nigra (Abi-Dargham et al., 1997), and medial and dorsal raphe (Azmitia and Whitaker-Azmitia 1995) as well as at various terminal areas of these nuclei. Multiple types of 5-HT and DA receptors may be involved. To date, the 5-HT1A, 5-HT2A and D2 receptors appear to be the most important for these interactions. Decreased 5-HT activity from median raphe neurons in the accumbens might lead to disinhibition of mesolimbic DA neurons; one effect of which might be an increase in positive symptoms (Kusljic et al., 2003). 5-HT2A antagonists may increase DA release in the prefrontal cortex by a direct action at 5-HT2A receptors on DA nerve terminals (Pehek et al., 2006) and may attenuate the effect of decreased prefrontal glutamatergic activity that inhibits burst firing of VTA DA neurons (Scruggs et al., 2000). 5-HT2A antagonists might reduce negative and cognitive symptoms through these mechanisms. Tonic release of DA in the mesolimbic system is dependent upon stimulation of 5-HT receptors (Bowers et al., 2000). Thus, the 5-HT agonist 1-(2,5dimethoxy-4-iodophenyl)-2-aminopropane (DOI) potentiates DA-induced DA synthesis and release. Blockage of this effect by 5-HT antagonists may contribute to their ability to decrease negative symptoms (Claustre et al., 2003). In comparison to the typical antipsyhcotics, atypical agents act at a wider range of receptors both centrally and peripherally such as dopaminergic, serotonergic, α-adrenergic and muscarinic receptors, upon which not only the therapeutic effects but also adverse effects were exerted. Long-term antipsychotic drug treatment alleviates but does not cure the core symptoms, leaving patients struggling for the deteriorating course with remarkable burden. Meta-analyses suggest that all atypical antipsychotics are associated with fewer extrapyramidal symptoms and less frequent use of anti-Parkinsonian medication than their conventional counterparts. However, this may occur at the expense of a different group of adverse effects, such as obesity, diabetes, hyperlipidemia and associated cardiovascular risk. Overall, the action of atypical antipsychotics through the serotonergic system has gained more understanding but still remained obscure and unlikely to overcome the unmet medical needs for negative and cognitive deficits.

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2.3. Glutamatergic Hypothesis D2 receptor blockade has been an obligatory mechanism of action present in typical antipsychotics that effectively treat positive symptoms of schizophrenia and have been approved by regulatory agencies since 1950s. 5-HT2A receptor blockade plays a contributory role in the actions of the atypical antipsychotics (Marek et al., 2010), thus have advantages over typical antipsychotics in terms of greater efficacy for positive and negative symptoms, some beneficial effects on cognitive functioning, and fewer extrapyramidal side effects in treating schizophrenia (He et al., 2009). Nevertheless, substantial unmet medical needs remain for the treatment of negative symptoms and cognitive dysfunction (Marek et al., 2010). Several lines of evidence suggest that the NMDAR is involved in schizophrenia pathophysiology. Studies of post-mortem brain and cerebrospinal fluid have revealed a lower density of glutamatergic receptors and lower levels of glutamate in patients with schizophrenia than in healthy comparison subjects (Mechri et al., 2001). Neuroimaging studies suggested cortical hypofunction, mediated by glutamatergic neurotransmission, during rest or the performance of cognitive tasks (Marek et al., 2010). The most compelling evidence is provided by the psychomimetic effects of the NMDA antagonists, PCP and ketamine (Mechri et al., 2001). Both of them induce psychiatric and physiological changes resembling schizophrenia more closely than the symptoms induced by amphetamine, a DA agonist (Kudoh et al., 2002; Radant et al., 1998; Krystal et al., 1994). As opposed to amphetamine- induced psychosis that resembles the positive symptoms associated with schizophrenia, PCP causes not only positive symptoms similar to amphetamine, but also negative symptoms and cognitive deficits associated with schizophrenia (Mouri et al., 2007; Nabeshima et al., 2006; Krystal et al, 1994; Adler et al., 1999; Umbricht et al., 2000). Therefore, in addition to the DA and serotonin hypotheses, the NMDA hypofunction model of schizophrenia has recently gained extensive attention (Green et al., 2000; Deutsch et al., 1989; Coyle and Puttfarcken, 1993; Tsai et al., 1995; Mohn et al., 1999; Farber et al., 1999). The glutamate dysfunction hypothesis is not inconsistent with a role for DA in the pathogenesis of this disease or with the current therapeutic approach for schizophrenia, which relies on drugs that act through DA receptor blockade or the combined antagonism of DA and serotonin receptors (Meltzer 1991). Glutamate and DA have been reported to exhibit reciprocal actions at subcortical structures (Nieollon et al., 1983), and therefore DA receptor blockade may act to balance primary glutamatergic insufficiency (Carlsson et al., 1997). Consequently, enhancing NMDA receptor neurotransmission has been considered as a novel treatment approach, in particular via the glycine modulatory component of neurotransmission at these receptors to avoid the excitotoxicity mediated through the glutamate site (Coyle and Puttfarcken, 1993; Leeson and Iversen, 1994; Tsai and Coyle, 2002; Kantrowitz et al., 2010; Lane et al., 2010; Stahl 2007).

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3. GLUTAMATERGIC PHYSIOLOGY 3.1. Glutamate Receptors: Ionotropic and Metabotropic Glutamate is the most abundant amino acid neurotransmitter in the mammalian brain, being present in over 50% of synapses. One of the major functions of glutamate receptors appears to be the modulation of synaptic plasticity, which is vital for learning and memory, sensory transmission and coordination, and control of respiration and blood pressure (Stoll et al., 2007). Glutamate receptors can be divided into two groups, ionotropic glutamate receptors (iGluRs) and metabotropic glutamate receptors (mGluRs), according to the mechanism by which their activation gives rise to a postsynaptic current or leads to G-protein activation (Palmada and Centelles 1998). iGluRs comprise a family of ligand-gated ion channels (Stoll et al., 2007). There are 3 subtypes of ionotropic receptors named NMDA, alpha-amino-3hydroxy-5-methyl-4-isoxazole-4-propionic acid (AMPA) and Kainate receptors (Lodge 2009). mGluRs are divided into 3 groups: mGluRI, mGluRII, and mGluRIII (Bonsi et al., 2005; Hinoi et al., 2001; Chu and Hablitz, 2000; Endoh 2004). Among these receptors, NMDAR is the best studied and most relevant subtype of glutamate receptors to understand the pathophysiology of schizophrenia. mGluRs activate a signaling cascade that involves G proteins. An increase or decrease in the number of iGluRs on a post-synaptic cell may lead to longterm potentiation or long-term depression of that cell, respectively (Pérez-Otaño 2005; Asztély and Gustafsson, 1996). Additionally, mGluRs may modulate synaptic plasticity by regulating post-synaptic protein synthesis through second messenger systems (Weiler and Greenough, 1993).

Ionotropic Glutamate Receptor All iGluRs are ligand-gated nonselective cation channels, which participate in synaptic transmission by directly opening ion channels upon glutamate and glycine site binding, allowing ion flow (K+, Na+, Ca2+) and causing excitatory post-synaptic current (EPSC), which is depolarizing and if in abundance may trigger an action potential in the post-synaptic neuron (Baskys et al., 1992). At resting membrane potential, the channel of NMDAR is blocked by Mg2+. The removal of Mg2+, upon depolarization caused by activation of the kainate and/or AMPA receptors, permits the NMDA channel to open for ionic influx (Johnson and Ascher, 1990; Goff and Coyle, 2001) (Fig. 1). The ionotropic receptors are located in the postsynaptic membrane and play critical roles in synaptic plasticity (Stoll et al., 2007). AMPA and kainate receptors play the primary role in mediating fast excitatory postsynaptic potential (EPSP) responsible for excitatory neurotransmission. The NMDAR, mediates the slower component of the EPSP, serves a different role (Goff and Coyle, 2001). At many synapses in the brain, transient activation of NMDARs leads to a persistent modification in the strength of synaptic transmission mediated by AMPA receptors. Kainate receptors can also act as the induction trigger for long-term changes in synaptic transmission (Bortolotto et al., 1999).

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Glycine (or D-serine, Dalanine, D-cycloserine)

Glutamate

Na+ Ca++

NR1 NR2

Polyamine

Extracellular

NR1 NR2

PCP Mg++ Intracellular

NR1

K+

NR2

Figure 1. Structure of NMDA receptor subunits. The NMDA receptors form tetrameric channels comprising two copies of NR1 and NR2 subunits. The receptor is gated by the co-agonists glutamate and glycine (or D-serine, D-alanine, D-cycloserine). Mg++, magnesium, is a channel blocker which is released upon depolarization. PCP, phencyclidine, is also a NMDA channel blocker.

These disparate functions suggest alternate modes of regulation. NMDAR plays a critical role in a major form of use-dependent synaptic plasticity known as long-term potentiation (Lynch 2004). In long-term potentiation, a brief period of high-intensity excitatory synaptic activity, which markedly depolarizes the neurons and recruits NMDARs, results in a subsequent persistent increase in synaptic efficacy. Long-term potentiation is the underlying mechanism of memory formation (Cooke and Bliss, 2006; Bliss and Collingridge, 1993).

Metabotropic Glutamate Receptor mGluRs, which belong to subfamily C of G protein-coupled receptors, are divided into three groups based upon functional activity and structure (Marino and Conn, 2006), with a total of eight sub-types. The mGluRs are composed of three distinct regions: the extracellular region, the transmembrane region, and the intracellular region (Barbado et al., 2009). The extracellular region is composed of a Venus Flytrap (or VFT) module that binds glutamate (Pin and Acher, 2002) and a cysteine-rich domain that is thought to play a role in transmitting the conformational change induced by ligand binding from in the VFT module to the transmembrane region (Muto et al., 2007). The transmembrane region consists of seven transmembrane domains and connects the extracellular region to the intracellular region where G protein coupling occurs (Pin and Acher, 2002). Glutamate binding to the extracellular region of an mGluR causes G proteins bound to the intracellular region to be phosphorylated, affecting multiple biochemical pathways and ion channels in the cell (Platt

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2007). By the complex signal transduction and anatomical distribution, mGluRs can either increase or decrease the excitability of the post synaptic cell, thereby causing a wide range of physiological effects.

Post-synaptic

Secondary messengers

↑Ca++

Primary effector

↑Ca++ ↑Na+

G-proteins mGluR1/5

NMDAR

KainateR

AMPAR

mGluR2/3

Glycine

mGluR1/5

Gly-T1

+ Glu

Sarcosine Glycine

Glycine

GCS

D-serine

L-Serine

DAOA(G72) ASC-1

serine recemase

D-serine

D-serine D-alanine

± DAAO

OH-pyruvate

DAAO

OH-pyruvate

Astrocyte

Pre-synaptic

Figure 2. The ionotropic glutamate receptors, N-methyl-D-aspartate (NMDA), α-amino-3-hydroxy-5methyl-4-isoxazolepropionic acid (AMPA) and kainate subtypes, largely function to mediate fast receptor transmission. The known potential regulators and drug targets of NMDA synapse include the “glycine” co-agonist site, serine racemase, D-amino acid oxidase (DAAO), D-amino acid oxidase activator (DAOA, G72) and D-serine uptake site (ASC-1). Glutamate is agonist; glycine and D-serine are co-agonists of the NMDA receptor. D-serine is synthesized by serine racemase from L-serine. Dserine is localized to both neurons and glial cells and is uptaken via ASC-1. D-serine is metabolized by DAAO into hydroxyl pyruvate. Role of DAOA as an activator or inhibitor is unclear. Glycine is uptaken by GlyT-1 and metabolized to L-serine by GCS. Sarcosine inhibits the glycine uptake through GlyT-1. The metabotropic glutamate receptors, mGluR1-8, have a diverse synaptic localization and function pre- and postsynaptically to modulate neurotransmitter release and postsynaptic excitability, respectively. ASC-1, arginine-serine-cysteine transporter-1; DAAO, D-amino acid oxidase; DAOA, Damino acid oxidase activator; GCS, glycine cleavage system; Glu, glutamate; GlyT-1, glycine transporter 1.

mGluRs are linked to second messenger systems and affect neuronal metabolism, leading to alterations in glutamate release (Fig. 2). Proteins called PDZ proteins frequently anchor mGluRs near enough to NMDARs to modulate their activity (Barbado et al., 2009). Group I receptors, consisting of mGluR1 and mGluR5, function predominantly to potentiate both presynaptic glutamate release and postsynaptic NMDA neurotransmission (Herrero et al., 1992; Rodriguez-Moreno et al., 1998; Reid et al., 1999; Thomas et al., 2000). Thus increase the activity of NMDARs (Goto et al., 2009; Dingledine et al., 1999). Conversely, group II

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(mGluRs 2 and 3) and Group III (mGluRs 4, 6, 7 and 8) receptors serve to limit glutamate release, particularly during conditions of excitotoxity, from the synaptic cleft (Trombley and Westbrook, 1992; Pin and Duvoisin, 1995; Takahashi et al., 1996) (Fig. 2). Accordingly, mGluRs have been shown to be involved in neurotoxicity and neuroprotection (Siliprandi et al., 1992; Baskys et al., 2005) in addition to synaptic plasticity (Bonsi et al., 2005; Endoh 2004). Overstimulation of glutamate receptors causes neurodegeneration and neuronal damage through a process called excitotoxicity. Excessive glutamate, acting on the glutamate receptors, over-activate glutamate receptors (specifically NMDARs), causing high levels of Ca2+ to influx into the postsynaptic cell (Dubinsky 1993). In high concentrations, Ca2+ activate a cascade of cell degradation processes recruiting proteases, lipases, nitric oxide synthase, and a number of enzymes that damage cell structures to cell death (Manev et al., 1989). In the presence of group I mGluR agonists, excessive amounts of NMDA, has been found to cause more damage to neurons (Pin and Acher, 2002). On the other hand, agonists of group II (Platt 2007) and III mGluRs tend to protect neurons from excitotoxicity (Gill et al., 1998; Weaver et al., 1996) by reducing NMDAR activity (Conn et al., 2005). The significance of glutamate receptors in excitotoxicity is associated with many neurodegenerative diseases. Schizophrenia is one of these diseases thought to be mediated, at least in part, through stimulation of glutamate receptors (Gillessen et al., 2002). mGluRs are also considered to affect dopaminergic and adrenergic neurotransmission (Wang and Brownell, 2007). At present, agonists and antagonists for mGluRs are under clinical development by various pharmaceutical companies for treatment of schizophrenia. LY354740—a group II agonist— has been found to reverse effects of NMDA antagonists in both rodents and humans (Krystal et al., 2005; Moghaddam and Adams, 1998) suggesting a potential role in treatment of schizophrenia, but the finding was not replicated.

3.2. NMDA Receptors The NMDAR has been demonstrated to play an important role in neurocognition and neurotoxicity (Lipson and Rosenberg, 1994; Kalia et al., 2008). It is the best studied and most relevant subtype of glutamate receptors to the understanding of the pathophysiology of schizophrenia and. Disturbance of the NMDAR results in psychosis resembles the clinical manifestations of schizophrenia. The NMDAR is composed of multiple subunits including NR1 and either NR2 (NR2 AD) or NR3 (NR3 A-B) to form heteromeric receptor-channels with different pharmacologic and biophysical characteristics (Laurie and Seeburg, 1994). NR1 and NR2(A-D) subunits are obligatory for a functional NMDAR, and contain binding sites for glycine/D-serine (glycine B site) and glutamate respectively (Fig. 1). NR2 subunits show distinct regional and developmental distribution, with NR2A and NR2B being expressed primarily in the forebrain, NR2C in cerebellar granule cells, and NR2D being expressed during fetal development in the midbrain and diencephalon. NR3 subunits require both NR1 and NR2 subunits to form functional NMDARs. NR3A receptors are expressed primarily during development, and NR3B are only found in somatic neurons in brainstem and spinal cord. Co-agonists binding at both the glycine and glutamate sites are required for the activation of the NMDAR via channel opening (Stone 2011; Mayer et al., 1989).

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In schizophrenia, the mRNA expression of the NR2A subunit of the NMDAR has been found to be decreased in a subset of inhibitory interneurons in the cerebral cortex (Bitanihirwe et al., 2009). Imaging studies using a novel SPECT tracer for the NMDAR (123I)CNS-1261 (Pilowsky et. al., 2006) have reported reduced NMDAR binding in the hippocampus of medication-free patients. This study represents the first direct demonstration of NMDAR deficiency in schizophrenia, but it remains to be replicated in a larger group of patients, The role of glutamatergic neurons in regulating other neurons’ function have been strongly implicated in the pathophysiology of schizophrenia. These include GABA interneurons (Lewis et al., 2005) and DA neurons, which are dependent on the activation of NMDARs (Johnson et al., 1992). The findings of clinical efficacy of D2 receptor antagonist and increased probability of developing schizophrenia after cannabis use during adolescence are consistent with deficient NMDAR function in schizophrenia and provide the key pharmacological clues to the pathophysiology of schizophrenia (Moghaddam 2005). Cannabinoid CB1 receptor and D2 receptors are localized presynaptically on glutamate terminals and work to inhibit the release of glutamate. Cannabis, reduces glutamate release, in particular in corticostriatal regions (Gerdeman and Lovinger, 2001), leading to deficient activation of NMDARs, whereas reduced D2 receptor function produces modest increase in glutamate release (Cepeda et al., 2001; Yamamoto and Davy, 1992). Clinically, augmentation through the NMDA-glycine site is preferred to avoid the excitotoxicity mediated through the glutamate site (Coyle 1993; Leeson and Iversen, 1994; Tsai and Coyle, 2002; Kantrowitz et al., 2010; Lane et al., 2010). Other than glycine, endogenous ligands, such as D-serine and D-alanine, also bind the co-agonist site (Johnson and Ascher, 1987). D-alanine, which is present only in the pituitary, is less likely to play a physiological role in the neocortex, thus most studies focused on the binding of D-serine and glycine on the Dserine/glycine site of NMDAR (Furukawa and Gouaux, 2003). Distribution of D-serine parallels to that of NR1 and D-serine evokes a maximum response that is indistinguishable from that of glycine (Furukawa and Gouaux, 2003; Kalbaugh et al., 2004). Interestingly, serine racemase (SR), which converts L-serine to D-serine, has a parallel distribution as Dserine while D-amino acid oxidase (DAAO), which metabolizes D-serine, has a reciprocal anatomical distribution from D-serine. NMDA antagonists are used as anesthetics for animals and sometimes humans, and are also used as recreational drugs due to their hallucinogenic properties, in addition to their unique effect of dissociation at elevated dosages (Anderson 2003). NMDA antagonists, such as PCP or ketamine, could induce psychosis which resembles schizophrenia more closely than the amphetamine/DA agonist induced (Krystal et al., 1994). The former causes not only positive symptoms similar to the latter, but also negative symptoms and cognitive deficits associated with schizophrenia (Buchanan et al., 2007; Yang et al., 2010). The physiologic manifestations of schizophrenia such as hypofrontality, impaired prepulse inhibition and enhanced subcortical DA release are demonstrated by these antagonists as well (Coyle et al., 2002).

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3.3. AMPA/Kainate Receptors AMPA Receptors AMPA receptors are responsible for the bulk of fast glutamatergic neurotransmission and they function cooperatively with NMDARs in the brain to maintain overall integrity of glutamatergic synapses (Bekkers and Stevens, 1989; Young and Fagg, 1990; Desce et al., 1992; Raiteri et al., 1992). Activation of AMPA receptor depolarizes the synaptic membrane to allow Ca2+ influx through unblocked NMDA channels in a voltage-dependent manner. Ca2+ influx, in turn, is required (Beattie et al., 2000; Lu et al., 2001) to trigger AMPA trafficking to the synaptic membrane which is critical for normal synaptic function and plasticity (Malinow and Malenka, 2002; Bredt and Nicoll, 2003). Therefore agents that potentiate neurotransmission via one type of glutamate receptor would permit activation of other types as well. AMPA receptors desensitize quickly following direct stimulation. Thus, direct agonists have limited prolonged stimulatory effect. However, indirect modulators, termed ampakines, may be able to stimulate AMPA receptors without causing desensitization. Ampakines have been found to stimulate cognitive performance in animal models (Hampson et al., 1998), and are currently under development for treatment of cognitive disorders such as schizophrenia, Alzheimers disease, or aging-related memory decline. But there is no convincing finding thus far. Animal models of GluR1 subunit of AMPA receptor knockouts (KO) exhibited a range of behaviors considered relevant to certain symptoms of schizophrenia, such as locomotor hyperactivity in open field test and in response to a novel object, disorganized social behaviors during a dyadic conspecific encounter, and deficits in prepulse inhibition of the acoustic startle response. Treatment with the DA antagonist and haloperidol effectively normalized locomotor hyperactivity in open field test, demonstrating behavioral abnormalities potentially pertinent to schizophrenia in GluR1 KO together with evidence of dysregulated DA function (Wiedholz 2008).

Kainate Receptors Kainate receptors are composed of the low affinity GluR5-7 subunits, and the high affinity KA1 and KA2 subunits (Hollmann and Heinemann, 1994). The GluR5-7 subunits assemble into homomeric complexes, or heteromerically coassemble with KA1 and KA2, resulting in receptors with distinct pharmacological properties, suggesting that subunit composition, at least in part, determines the functional properties of the kainate receptor (Lerma 1998). The functions of kainate receptors have begun to be elucidated for their role in synaptic transmission and plasticity in the brain in the last decade. Some of the actions of kainate receptors are ionotropic, others seem to utilize noncanonical signaling pathway by linking receptor activation to G-proteins and second-messenger cascades and invoke metabotropic roles. Specific subunits of kainate receptors have been demonstrated to associate with G proteins. Therefore, kainate receptors expedite long-lasting signalling by novel metabotropic modes of action (Rodríguez-Moreno and Sihra, 2007; Lerma 2008). Kainate receptor binding has been studied in multiple brain regions in schizophrenia by several independent groups. [3H]kainate binding has been reported to be elevated in multiple cortical areas in schizophrenia (Deakin et al., 1989; Nishikawa et al., 1983), decreased in the

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hippocampus, parahippocampal gyrus (Kerwin et al. 1990) and infragranular laminae of the prefrontal cortex (Meador-Woodruff et al., 2001), and unchanged in striatal regions (Nishikawa et al., 1983; Noga et al., 1997). These data add to the growing literature implicating ionotropic glutamate receptor disturbances in schizophrenia, and indicate that in addition to AMPA and NMDA receptors, the kainite receptors are also abnormally expressed in this illness.

4. GLUTAMATERGIC MODELS OF SCHIZOPHRENIA: EVIDENCE OF NMDA RECEPTOR HYPOFUNCTION IN SCHIZOPHRENIA 4.1. Clinical Presentations Following NMDA Antagonist Administration Much evidence suggests that hypofunction of NMDA receptor mediated neurotransmission is a critical deficit in schizophrenia (Bachus and Kleinman, 1996; Coyle, 1996; Olney and Farber, 1995). Over the last 2 decades, the involvement of the NMDA system in schizophrenia is further evidenced by the effects of the noncompetitive antagonists of NMDAR, PCP and ketamine, both of which induce psychiatric and physiological changes resembling schizophrenia more closely than the symptoms induced by amphetamine, which facilitates DA agonism (Kudoh et al., 2000; Radant et al., 1998; Krystal et al., 1994). These compounds function primarily by binding to a site within the ion channel of the NMDAR that blocks cations influx, thereby acting as a noncompetitive antagonist (Jentsch and Roth, 1999). This finding suggests that the dysfunction of NMDARs in particular or the glutamatergic system in general may contribute to the pathogenesis of schizophrenia and leads researchers to work on new drug development based on glutamatergic neurotransmission and MNDARs (Olney and Farber, 1995; Tsai and Coyle, 2002). As opposed to amphetamine- induced psychosis that resembles the positive symptoms associated with schizophrenia (Bell 1973), PCP and ketamine causes not only positive symptoms similar to amphetamine, but also negative symptoms and cognitive deficits associated with schizophrenia (Mouri et al., 2007; Nabeshima et al., 2006, Krystal et al., 1994; Adler et al., 1999; Umbricht et al., 2000). Consequently, intensive research studies are in progress in order to understand the NMDA mechanisms underlying this debilitating disease and advance the therapeutic strategies based upon the NMDA perspective.

4.1.1. Nonpsychotic Population In the earlier decades, studies of ketamine and PCP have opened up a new gateway for understanding the pathogenesis of schizophrenia. When subanesthetic dose was infused intravenously to normal or healthy subjects, ketamine produces an amotivational state characterized by blunted affect, withdrawal, and psychomotor retardation (Cohen et al., 1962) as well as psychotic symptoms in the form of suspiciousness, disorganization, and visual or auditory illusions (van Berckel 1998). Significant increase in Brief Psychiatric Rating Scale (BPRS) total scores and symptom composite scores like Scale for the Assessment of Negative Symptoms (SANS) and Scale for the Assessment of Positive Symptoms (SAPS) were

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examined (Hetem 2000; van Berckel 1998). Dissociative symptoms are also prominent, with depersonalization in particular as an important early feature of the schizophrenia prodrome (Krystal 1994). Low dose ketamine significantly increased PPI in normal subjects (van Berckel 1998; Duncan et al., 2001; Abel et al., 2003). During smooth pursuit eye tracking, ketamine induces nystagmus and abnormalities that are among the characteristics of schizophrenia (Mechri et al., 2001). Cognitive deficits, including impaired performance on the Wisconsin Card Sorting Test, continuous performance vigilance test, verbal declarative memory, delayed word recall, and verbal fluency tests were demonstrated as well (Krystal 1994; Cohen et al., 1962; Malhotra et al., 1996; Newcomer et al., 1999).

4.1.2. Subjects with Schizophrenia Further studies in patient with schizophrenia provided interesting clues to the possible underlying etiology of schizophrenia. Chronic PCP abusers have commonly been misdiagnosed as being schizophrenic, whereas PCP administration exacerbates symptoms in chronic stabilized schizophrenic patients (Luby et al., 1959; Allen and Young, 1978; Krystal et al., 1994). One study with administration of subanesthetic doses of PCP (0.1 mg/kg) to chronic schizophrenics, PCP dramatically exacerbated the schizophrenic symptoms (Lasagna and Pearson, 1965; Luby et al., 1959). Patients became more assertive, hostile, and unmanageable, and these changes lasted not a few hours (as in normals) but from four to six weeks (Luby 1981), suggesting the substantial NMDA vulnerability of this population. Studies with subanesthetic dose of ketamine, showed an exacerbation or worsening of positive and negative symptoms with further decrements in recall and recognition memory in patients with schizophrenia (Lahti, 1995; Malhotra et al., 1997; Tamminga 1999; Mechri, et al., 2001). 4.1.3. Animal Studies Other evidences are provided by the animal models. One study with rats repeatedly treated with PCP and MK-801(another NMDA channel blocker) under an escalating dosing regimen produced a stable and persistent disruption of PPI. Startle magnitude increased progressively and dose-dependently (Li 2011). Two other studies with rats treated with PCP repeatedly exhibit hyperlocomotion as an index of positive symptoms, a social behavioral deficit in a social interaction test and enhanced immobility in a forced swimming test as indices of negative symptoms. They also showed sensorimotor gating deficits and cognitive dysfunctions in several learning and memory tests. Some of these behavioral changes endure after withdrawal from repeated PCP treatment (Nabeshima et al., 2006; Mouri 2007). One study with rats under sub-chronic PCP treatment demonstrated impaired 5-Choice Continuous Performance Test (CPT) performance in a manner consistent with impaired vigilance in patients with schizophrenia (Barnes et al., 2011). A recent study with rats under subanesthetic dose of Ketamine treatment showed hyperlocomotion and stereotypic movements. The activity of respiratory chain complexes in the striatum, hippocampus, and prefrontal cortex was affected (de Oliveira 2011). In addition, several studies further investigated the acute effects of the non-competitive NMDA antagonists on the gene expression of several enzymes, which were suggested to play important roles in the regulation of NMDAR via the D-serine metabolism. Ketamine administration in rats produced a dose-dependent and transient elevation in the levels of SR and DAAO mRNAs in all the brain areas (Takeyama et al., 2006). MK-801 administration in rats also produced a significant increase in the

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expression of SR mRNA in almost all brain areas (Yoshikawa et al., 2004; Hashimoto et al., 2007), whereas no significant changes were found in the level of DAAO mRNA in most brain areas (Yoshikawa et al., 2004). In addition, the administration of MK-801 caused a slight but significant elevation in the concentrations of D-serine in the cortex and striatum (Hashimoto et al., 2007). These findings suggest that there is a relationship between the gene expression of the D-serine-related enzymes and the blockade of the NMDAR.

4.2. Genetic Linkage and Association Studies Genetic studies in schizophrenia have been performed extensively over the last two decades, generating thousands of published reports and being cataloged in the SchizophreniaGene (SZGene) database of the Schizophrenia Research Forum (Shi et al., 2008). Up to 20 susceptibility genes, replicated or not, have been identified to be associated with schizophrenia (Norton et al., 2006; O'Tuathaigh et al., 2007; Shi et al., 2008). These new findings have engendered excitement because replicate studies have attained greater consistency than in the past (Shirts and Nimgaonkar, 2004) and delivered promising insights into the nature of schizophrenia (Owen 2004). Exploratory haplotype analysis confirmed association with schizophrenia toward the 5' end of AKT1 (Thiselton et al., 2008). Functional analyses indicate that the G72 (now called D-amino acid oxidase activator (DAOA)) gene product plays a role in the regulation of NMDAR, but at the molecular level, the picture still remains unclear (Abou et al., 2006). Linkage dysequilibrium mapping and genetic association studies have identified promising and novel "positional candidates", neuregulin-1(NRG1) on chromosome 8p-p21, G72 13q34, dysbindin (DTNBP1) on 6p22.3, proline dehydrogenase (PRODH) on 22q11, catechol-Omethyltransferase (COMT), also on 22q11, and DAAO (McGuffin et al., 2004). Neuregulin1, Dysbindin, DAAO and G72 in the variant forms reduce glutamatergic activity in brain. Proline is a precursor of glutamate, and it seems to be a neuromodulator of glutamatergic transmission in the brain. COMT, as one of the two enzymes degrading catecholamines, plays a significant role in the cortical DA metabolism (Schosser 2004). Gene regulator-of-Gprotein-signaling-4 (RGS4), a modulator of the function of multiple G-protein-linked neurotransmitter receptors, was also identified. Gene-expression-analyses of postmortem cerebral cortex discovered that the transcription of RGS4 is diminished in prefrontal cortex in schizophrenics (Schosser 2004). There are also genes related to the glutamatergic neurotransmission systems, such as ionotropic glutamate receptor genes (GRIN1, GRIN2A, GRIN2B and GRIK3), mGluR genes (GRM3) and the G72/G30 locus (Qin et al., 2005; Cherlyn et al., 2010; Zhao et al., 2006). Recent findings revealed the important roles of schizophrenia-linked genes, NRG1 and ERBB4 (Li et al., 2007; Wen et al., 2010). NMDAR hypofunction is considered a key detrimental consequence of the excessive Neuregulin 1β-ErbB4 (NRG1β-ErbB4) signaling found in schizophrenics. NRG1β-ErbB4 signaling causes hypofunction of NMDARs in the hippocampus and prefrontal cortex by suppressing the enhancement of synaptic NMDAR currents via the nonreceptor tyrosine kinase Src. during theta-burst stimulation and preventing induction of long-term potentiation at hippocampal Schaffer collateral-CA1 synapses. Moreover, NRG1β-ErbB4 signaling prevented theta burst-induced phosphorylation of glutamate receptor NMDAR2B subunit (GluNR2B) by inhibiting Src kinase activity. There it was proposed that NRG1-ErbB4

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signaling participates in cognitive dysfunction in schizophrenia by aberrantly suppressing Src-mediated enhancement of synaptic NMDAR function (Pitcher et al., 2011). SR, an enzyme catalyzing the formation of D-serine from L-serine, was also examined in one study for its genetic role in the susceptibility to schizophrenia and the regulation of serum D-serine levels. Genetic association analyses showed no significant association between SR/DAO ratio and schizophrenia. Decreased serum D-serine levels in schizophrenics were replicated, but Dserine levels did not correlate with SR/DAO genotypes. This concludes that SR/DAO is not likely to be a major genetic determinant in the development of schizophrenia or control of serum D-serine levels (Yamada et al., 2005). More advanced study reported recently is that the Consortium on the Genetics of Schizophrenia used a custom array of 1,536 single-nucleotide polymorphisms (SNPs) to interrogate 94 functionally relevant candidate genes for schizophrenia and identify associations with 12 heritable neurophysiological and neurocognitive endophenotypes in data collected. Associations with endophenotypes were observed for 46 genes of potential functional significance. Many of the genes interact on a molecular level, and eight genes (e.g., NRG1 and ERBB4) displayed evidence for pleiotropy, revealing associations with four or more endophenotypes. The results collectively support a strong role for genes related to glutamate signaling in mediating schizophrenia susceptibility (Greenwood et al., 2011).

4.3. Animal Genetic Models Studies in animal genetic models further support the implication of dysfunctional NMDAR in the pathophysiology of schizophrenia. NMDAR–deficient (Nr1neo -/-) mice display an increase in both motor activity and stereotypic behavior similar to that observed in normal mice infused with PCP or MK-801. Treatment with either haloperidol or clozapine attenuated these increased locomotion and stereotypy, with clozapine more effective than haloperidol. In addition to altered motor activity, Nr1neo -/- mice displayed deficits in sexual and social behavior. These behavioral deficits can also be improved by treatment with clozapine, a significant 5HT2A antagonist (Mohn et al., 1999). These results are in agreement with previous pharmacological studies (Martin et al., 1998). The evidence presented suggests that monoaminergic transmission also plays a role in these behavioral changes. The response of Nr1neo -/- mice to antipsychotics addresses the question of how symptoms of schizophrenia can be treated with drugs that act on dopaminergic and serotonergic systems, yet to be associated with a dysfunction of the glutamatergic system (Mohn et al., 1999); this is likely due to the close interaction among the dopaminergic, serotonergic and glutamatergic neurotransmission. DAAO, has been recently identified as a risk factor for schizophrenia through genetic association studies, is further evaluated as a target for schizophrenia. A strain of mice has been identified lacking DAAO activity (ddY/DAO-) due to a single point mutation (G181R) in DAAO (Sasaki et al., 1992). ddY/DAO- mice have elevated levels of D-amino acids, including increased D-serine in serum and brain compared to wild-type mice (Hashimoto et al., 1983; Morikawa et al., 2001), and these mutant mice have been shown to have increased NMDA receptor-mediated excitatory postsynaptic currents and enhanced hippocampal LTP (Maekawa et al., 2001), which is widely accepted as the best molecular correlates of learning and memory (Bliss and Collingridge, 1993; Collingridge and Bliss, 1995; Bear and Malenka,

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1994; Malenka and Bear, 2004). At the behavioral level, the increase in hippocampal LTP is manifested by improved cognitive performance in the Morris water maze compared with wild-type mice (Maekawa et al., 2005). The studies by Labrie et al. (2008; 2010) further demonstrated that mice carrying the hypofunctional DAAO (G18R) mutation promoted adaptive learning in response to changing conditions and displayed an improvement in the performance of NMDAR-NR1 (Grin1) D481N mutant mice with deficient NMDAR glycine site activation in behavioral tasks relevant to the negative and cognitive symptoms of schizophrenia (Labrie et al., 2009). Together, these findings suggest that diminished DAAO activity and elevation in D-serine could have therapeutic impact on the negative and cognitive symptoms found in schizophrenics (Almond et al., 2006; Labrie et al., 2009). Pharmacological studies suggest that the glycine transporter-1, GlyT-1, functions to maintain subsaturating glycine concentrations at synaptic NMDAR. To illustrate further the role of GlyT-1, mutant mice were generated by inactivating gene encoding GlyT-1 through insertion of a PGK-Neo cassette in place of exons 2 and 3. Homozygous GlyT-1(-/-) mice died within 12 h of birth. Heterozygous GlyT-1(+/-) mice with 50% reduction in expression of GlyT1 as compared with wild type littermates enhance hippocampal NMDAR function and memory retention as well as protects against an amphetamine-induced disruption of sensory gating (Tsai et al, 2004). The potential in developing novel drugs through the action of GlyT1 inhibition to ameliorate cognitive deficits and psychotic symptoms in schizophrenia was foreseeable. To elucidate physiologic roles of D-serine, mutant mice with SR deletion (SR-/-) have been shown to display a remarkable reduction in D-serine levels with alterations in NMDA neurotransmission, decreased LTP, and spatial memory deficits (Basu and Tsai et al., 2009). Neurotransmitter deficiency is often associated with receptor supersensitivity that may be manifested in increased receptor protein levels, as exemplified by DA receptors (Kostrzewa et al., 2008). It is therefore speculated that in the deficiency of D-serine, surface expression of NMDARs will likely be increased, leading to receptor supersensitivity. The study of SR deleted mice revealed NMDA receptor supersensitivity and LTP to exogenous D-serine application (Basu et al., 2009). This is further evidenced by increased NR1 NMDAR protein levels in SR-/- mice. Injection of NMDA directly into the striatum of SR-/- mice in order to assess the functional consequences of increased receptor was performed and a 50% augmentation in NMDA-elicited lesion volume was detected. This gives the clue that direct injections of NMDA in D-serine deficit state may expose the NMDAR to overwhelming stimulation (Mustafa et al., 2010). Excessive glutamatergic signaling in the prefrontal cortex may contribute to the pathophysiology of schizophrenia. Glutamatergic signaling is regulated by a family of glutamate transporters: glial glutamate and aspartate transporter (GLAST; excitatory aminoacid transporter 1), glial glutamate transporter-1 (GLT-1; excitatory amino-acid transporter 2), excitatory amino-acid carrier 1 (EAAC1; excitatory amino-acid transporter 3), and excitatory amino-acid transporter 4 (EAAT4) (Karlsson et al., 2009). The glutamate transporter GLAST (EAAT1) regulates extracellular glutamate levels via uptake into glia. Promoting presynaptic glutamate modulation via group II metabotropic glutamate (mGlu2/3) receptor activation can exert antipsychotic efficacy (Woolley et al., 2008). GLAST KO mice exhibited phenotypic abnormalities thought to model certain positive symptoms of schizophrenia (psychomotor agitation and supersensitivty to psychotomimetics), which were exaggerated by administration of NMDAR antagonist MK-801 and were rescued

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by treatment with either haloperidol or the mGlu2/3 agonist, LY379268 (Karlsson et al., 2008). Further evaluation of phenotypic endpoints demonstrate that gene deletion of GLAST produces selective phenotypic abnormalities, such as abnormal social behavior characterized by reduced initiation of social interactions, poor nesting, and impaired pairwise visual discrimination learning, related to the negative and cognitive symptoms of schizophrenia (Karlsson et al., 2009). Possible effects of excitotoxicity resulting from loss of GLAST would contribute to the increased vulnerability to neurotoxicity (Choi 1988). GLAST-deficient mice provide one useful tool for elucidating the role for glutamate transporters in the pathophysiology of schizophrenia (Karlsson et al., 2009).

5. THERAPEUTIC TARGETS BASED ON GLUTAMATE MODELS OF SCHIZOPHRENIA 5.1. NMDA Receptor Glycine-Site Agonists The NMDAR is unique in that in addition to the glutamate recognition site, it also contains a modulatory site that binds the endogenous full agonists, glycine and D-serine (Dunlop and Neidle, 1997; Snyder and Kim, 2000; Baranano et al., 2001; Tsai et al., 2006). Glycine binds to a modulatory glycine-B strychnine-insensitive binding site on the NR1 subunit of the NMDAR complex and acts as an essential co-agonist for activation of the NMDAR. Thus, several approaches have emerged aimed towards modulating this glycine binding site (Kinney and Sur, 2005). D-serine is synthesized in protoplasmic astrocytes by SR that converts L- to D-serine (Sawa and Snyder, 2003.) and is degraded by DAAO (Verrall et al., 2007). D-serine is a more potent agonist than glycine at the glycine-B site and has a greater ability to penetrate the blood brain barrier (Hashimoto and Oka, 1997), these findings suggests that D-serine administration may also have a beneficial effect in schizophrenic patients (Kinney and Sur, 2005). As central and peripheral D-serine levels are reduced in schizophrenic patients, impaired D-serine function in patients could contribute to NMDAR hypofunction (Hashimoto et al., 2003, 2005; Yamada et al., 2005). Several controlled clinical trials have shown that co-administration of D-serine or glycine in conjunction with antipsychotics can ameliorate some symptoms of the disorder (Tsai et al., 1998; Goff and Coyl, 2001; Heresco-Levy et al., 2005). D-alanine, a full agonist, binds weakly to this site as well but probably does not play a physiological role. D-cycloserine, an anti-tuberculosis drug, is a partial agonist at the glycine site (Sawa and Snyder, 2003), thus it is only about half as effective as full agonists (ie, glycine, D-serine) in potentiating NMDA activation. In high concentrations of glycine and D-serine, D-cycloserine may even function as a net antagonist, leading to decreased NMDA neurotransmission.

5.2. Glycine Transport Inhibitors Extracellular glycine levels can be regulated via uptake by 2 types of high affinity glycine transporters, GlyT-1 and GlyT-2 (Depoortere 2005). GlyT-2 has a more limited distribution

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and is thought to provide the principal glycine uptake mechanism at inhibitory glycinergic synapses (Liu et al., 1993; Jursky and Nelson, 1995; Zafra et al., 1995), whereas GlyT1 is widely expressed both in peripheral tissues and in the CNS where it is present predominantly on glial cells and has been proposed to mainly function at excitatory synapses by regulating glycine levels at the coagonist binding site of NMDAR (Smith et al., 1995; Berger et al., 1998; Roux and Supplisson, 2000). As GlyT-1 plays a crucial role in maintaining the concentration of glycine within NMDA synapses at a subsaturating level, and the anatomical distribution of Gly-T-1 is co-localized with the NMDAR. An alternative approach to enhance NMDA neurotransmission is by blocking the reuptake of glycine through GlyT-1. This mechanism is analogous to that of using a serotonin reuptake inhibitor to enhance serotonergic neurotransmission (Tsai 2008). The studies of GlyT-1 inhibitor, a sarcosine (N-methylglycine) analogue, N[3-(4’fluorophenyl)3-(4’ phenylphenoxy)propyl]sarcosine (Aubrey and Vandenberg 2001; Chen et al., 2003), and the GlyT-1 knockdown mutation have demonstrated the critical role that GlyT1 plays in enhancing NMDA neurotransmission (Tsai 2004). Sarcosine, which is an endogenous inhibitor of GlyT-1, has shown clinical efficacy while being administered as addon therapy to typical and atypical antipsychotics or as monotherapy, thereby supporting its NMDA-enhancing and antipsychotic function (Tsai et al., 2004, Lane et al., 2005, 2009). Several other prototypic glycine-transport inhibitors, including glycyldodecylamide, (Toth and Weiss, 1986; Javitt et al., 1997), Org24461 and Org24598, (Harsing et al., 2003; Brown et al., 2001) and SSR504734 (Depoortere et al., 2005), have shown encouraging preclinical results. One GlyT-1 inhibitor is currently under clinical development by Roche at Phase III.

5.3. DAAO Inhibitors DAAO is a flavoenzyme that metabolizes certain D-amino acids, particularly the endogenous NMDAR co-agonist, D-serine. Studies of D-serine revealed lower serum levels in schizophrenic patients as compared to healthy controls (Boks et al., 2007). Therefore, DAAO has the potential to modulate NMDAR function via D-serine breakdown (Verrall et al., 2010) and contribute to the reduction in NMDAR-mediated neurotransmission (Mothet et al., 2000), thus increased DAAO is associated with susceptibility to schizophrenia via Dserine decrements (Chumakov et al., 2002; Liu et al., 2004; Schumacher et al., 2004; Wood et al., 2007). In addition, its putative activator, G72 (DAOA), also shows association with the disorder (Chumakov et al., 2002; Detera-Wadleigh and McMahon, 2006; Li and He, 2007; Yue et al., 2007; Liu et al., 2006; Kapoor et al., 2006; Wood et al., 2007; Bendikov et al., 2007). Several lines of evidence are in support of the above mentioned notion: in genetic studies, DAAO shows associations to schizophrenia in several, though not all, studies (Verrall et al., 2010); in postmortem studies, the gene expression and mean DAAO activity are higher in the schizophrenia patients group compared with the control group (Madeira et al., 2008; Habl et al., 2009) and in animal models, genetic mutation of DAAO in rodents shows reversal of schizophrenia-like phenotypes and elevation in brain levels of D-serine (Konno et al., 2010; Labrie et al., 2008, 2010). Taken together, inhibition of DAAO and elevation in D-serine may be suggestive of potential therapeutic benefits.

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6. THERAPEUTIC EFFECTS EXERTED BY ENHANCING NEUROTRANSMISSION MEDIATED BY NMDA RECEPTORS The most comprehensive review of NMDA enhancers is a meta-analysis (Tsai and Lin, 2010). It included all published, randomized, double-blind trials of the NMDA-enhancing agents and reviewed 26 studies with about 800 patients with schizophrenia. The clinical efficacy on different symptom domains, efficacy among different NMDA-enhancing agents, effects of different concomitant antipsychotic agents, the dose-response and the side effects were examined. Clinical efficacy of these enhancers, either used as adjuncts to antipsychotics or primary therapy, on the core symptoms was summarized in Table 1. Table 1. Characteristics of clinical trials of NMDA-enhancing agents and their therapeutic effects on major symptom domains of schizophrenia

Potkin et al. 1992 Javitt et al. 1994 Heresco-Levy et al. 1996 Heresco-Levy et al. 1999 Potkin et al. 1999 Evins et al. 2000 Javitt et al. 2001 Heresco-Levy et al. 2004 Diaz et al. 2005 Buchanan et al. 2007 Rosse et al. 1996 Heresco-Levy et al. 1998 Goff et al. 1999 van Berckel et al. 1999 Heresco-Levy et al. 2002 Duncan et al. 2004 Goff et al. 2005 Tsai et al. 1998 Tsai et al. 1999 Heresco-Levy et al. 2005 Lane et al. 2005a Lane et al. 2010b Tsai et al. 2004 Lane et al. 2006 Lane et al. 2008 Tsai et al. 2006 a

Drug and daily dose

Concomitant Antipsychotics

Subject Duration Positive Negative Cognitive no. (weeks) symptoms symptoms symptoms

Glycine 15 g Glycine 0.4 g/kg

NA NA

18 14

6 8

+

+

+ NA

Glycine 0.8 g/kg

TYP+CLO

11

6

-

+

+

Glycine 0.8 g/kg

TYP+CLO

19

6

+

+

+

Glycine 30 g Glycine 60 g Glycine 0.8 g/kg

CLO CLO TYP+CLO+ATYP

19 27 12

12 8 6

NA -

NA + +

NA +

Glycine 0.8 g/kg

ATYP

14

6

+

+

+

Glycine 60 g CLO Glycine 60 g or D-CS TYP+ATYP 50 mg D-CS 10 or 30 mg TYP

11

28

-

NA

NA

157

16

NA

-

-

13

4

+

-

NA

D-CS 50 mg

TYP+CLO+ATYP

9

6

-

+

-

D-CS 50 mg

TYP

46

8

+

-

-

D-CS 100 mg

TYP

26

8

-

-

NA

D-CS 50 mg

TYP+ATYP

16

6

-

+

NA

D-CS 50 mg

TYP

22

4

-

-

-

D-CS 50 mg D-serine 30 mg/kg D-serine 30 mg/kg

TYP TYP+ATYP CLO

55 29 20

24 6 6

+ -

+ -

+ -

D-serine 30 mg/kg

ATYP

39

6

+

+

+

D-serine/Sarcosine 2 g D-serine/Sarcosine 2 g Sarcosine 2 g Sarcosine 2 g Sarcosine 1 or 2 g D-alanine 100 mg/kg

ATYP (risperidone) ATYP TYP+ATYP CLO NONE TYP+ATYP

65 51 38 20 20 32

6 6 6 6 6 6

+ + + + +

+ + + + +

+ + + NA +

acute patients,b chronically stable patients ATYP, atypical antipsychotics other than clozapine; CLO, clozapine; D-CS, D-cycloserine; TYP, typical antipsychotics. (+), positive therapeutic effect; (-), no therapeutic effect; NA, data not available.

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6.1. Glycine 6.1.1. Glycine Added to Typical Antipsychotics Since 1990, the efficacy of glycine as adjuvant therapy to typical antipsychotics in ameliorating negative symptoms and cognitive deficits was investigated in several small-scale double-blinded and open-label clinical trials. Three of these studies showed significant improvement in negative symptoms with glycine add-on treatment (Javitt et al., 1994; Heresco-Levy et al., 1999; Javitt et al., 2001). One study (Rosse et al., 1989) with 6 patients in which no beneficial effects were observed regarding the negative symptoms of schizophrenia. However, a low dose of glycine (10.8 g/day) given in this study might explain the lack of effectiveness. In 2007, the Cognitive and Negative Symptoms in Schizophrenia Trial (CONSIST), a randomized double-blind study with a duration of 16 weeks and with the participation of 4 sites in the United States and one site in Israel, was published (Buchanan et al., 2007). A total of 157 patients were recruited and randomized to glycine, D-cycloserine and placebo groups. The study suggested that glycine is not an effective therapeutic option for treating negative symptoms or cognitive impairments as there was no significant SANS total score differences between glycine and placebo subjects. However, post hoc analyses found that, among subjects receiving typical antipsychotics, the 8 subjects randomly assigned to glycine had a greater decrease in the SANS total score compared to the 7 subjects randomly assigned to placebo. Moreover, tendencies to greater negative symptom reductions for both the glycine and D-cycloserine groups compared with placebo were observed in inpatients, but not in outpatients. However, there were no significant glycine/placebo differences on the cognitive summary measure. In terms of adverse effect, new or worsened nausea was more frequent in glycine subjects versus placebo subjects (Buchanan et al., 2007). Three other trials (Heresco-Levy et al., 1996, 1999; Javitt et al., 2001) evaluated the cognitive effects of glycine based on PANSS cognitive subscale, showing a beneficial effect in cognitive functioning. Nevertheless, it is noteworthy that these studies were conducted on a relatively small sample size and under short-term glycine treatment (Chaves et al., 2009). 6.1.2. Glycine Added to Atypical Antipsychotics A 6-week double-blind placebo-controlled crossover trial with high-dose glycine added to olanzapine and risperidone (Heresco-Levy et al., 2004) revealed a significant reduction in negative symptoms and a significant improvement in cognitive impairments. One short-term trial (Javitt et al., 2001) also provided evidence for a significant reduction in negative symptoms and a beneficial effect in cognitive functioning based on PANSS cognitive subscale. However, these clinical trials were conducted on small samples over short-term periods. In 2007, the CONSIST (Buchanan et al., 2007) again suggested that glycine is not an effective therapeutic option for treating negative symptoms or cognitive impairments as there were no significant differences in change in the SANS total score and in the average cognitive domain Z scores between glycine and placebo subjects. 6.1.3. Glycine Added to Clozapine Approximately 40-70% of treatment-resistant schizophrenic patients fail to benefit from clozapine monotherapy or are partial responders. During the last 2 decades several clozapine adjunctive agents have come into clinical practice (Kontaxakis et al., 2005). From 1996 to

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2005 the efficacy of glycine as clozapine adjuncts had been evaluated in several clinical trials. Seven trials (Potkin et al., 1999; Heresco-Levy et al., 1996, 1999; Evins et al., 2000; Javitt et al., 2001; Diaz et al., 2005; Leiderman et al., 1996) were published. Five of them (HerescoLevy et al., 1996; Evins et al., 2000; Javitt et al., 2001; Diaz et al., 2005; Leiderman et al., 1996) did not find significant improvements in positive symptoms. One study (Potkin et al., 1999) found worsening of positive symptoms. Four trials (Heresco-Levy et al., 1996; Heresco-Levy et al., 1999; Javitt et al., 2001; Leiderman et al., 1996) showed significant reductions in negative symptoms and the improvements persisted even following glycine discontinuation. Cognitive functioning was assessed in only four trials (Heresco-Levy et al., 1996, 1999; Evins et al., 2000; Javitt et al., 2001) and three of them found positive change in cognition under assessment by the PANSS cognitive subscale.

6.2. D-Serine There were 5 clinical trials with D-serine as adjuvant therapy to antipsychotic treatment (Tsai et al., 1998; Tsai et al., 1999; Heresco-Levy et al., 2005; Lane et al., 2005; Kantrowitz et al., 2010). Two trials (Tsai et al., 1998; Lane et al., 2010) evaluated the addition of Dserine to typical antipsychotics, with significant improvements in positive, negative and cognitive symptoms as well as some performance in WCST. Four trials (Tsai et al., 1999; Heresco-Levy et al., 2005; Lane et al., 2005; Kantrowitz, et al., 2010) evaluated the addition of D-serine to atypical antipsychotics. Two of the trials demonstrated encouraging outcomes. The most recent study (Kantrowitz et al., 2010) published in 2010 performed with adjunctive D-serine at dose-escalation (30, 60 or 120 mg/kg body weight/day) and the findings suggested beneficial effects in treatment of positive symptoms, negative symptoms, and neurocognitive dysfunction at doses of 60 and 120 mg/kg/day, and increase of plasma D-serine levels correlated with improved symptomatic and neuropsychological function. There is renal side effect when D-serine dose is high. The other study (Heresco-Levy et al., 2005) also demonstrated significant improvements in positive, negative and cognitive symptoms. However, one study (Lane et al., 2005) with D-serine and risperidone cotreatment in acute exacerbating patients and another study with adding D-serine to clozapine (Tsai et al., 1999) did not find beneficial effects in any of the three core symptoms for treatment of schizophrenia.

6.3. D-Alanine There is only one clinical trial (Tsai et al., 2006) investigate the efficacy of D-alanine as adjuncts to antipsychotics, with thirty-two schizophrenic patients enrolled in a 6-week double-blind, placebo-controlled trial of D-alanine (100 mg/kg/day), which was added to their stable antipsychotic regimens, including various typical antipsychotics and risperidone (Tsai et al., 2006). Patients receiving D-alanine treatment revealed significant improvements in positive and negative symptoms. Cognitive symptoms assessed by the cognitive subscale of PANSS also showed improvement. In addition, D-alanine was well tolerated, and no significant side effect was noted (Tsai el al., 2005). The positive findings of D-alanine on schizophrenic symptoms, particularly the negative and cognitive domains, further strengthen

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the hypothesis of potentiation of NMDA neurotransmission through the NMDA glycine site as the therapeutic targets in schizophrenia.

6.4. D-Cycloserine 6.4.1. D-Cycloserine Added to Typical Antipsychotics Seven trials evaluated the addition of D-cycloserine to typical antipsychotics (Goff et al., 1995; Goff et al., 1999; Goff et al., 2005; van Berckel et al., 1999; Heresco-Levy et al., 2002; Duncan et al., 2004; Buchanan et al., 2007). Three of them (Goff et al., 1995, 1999; HerescoLevy et al., 2002) exhibit significant reductions in negative symptoms, while three other studies (van Berckel et al., 1999; Duncan et al., 2004; Goff et al., 2005; Buchanan et al., 2007) did not find a significant change in negative symptoms. In addition, one trial (Goff et al., 1995) demonstrated equivocal improvement of cognitive function at the dose of 50 mg/day, while four other trials (Goff et al., 1999, 2005; Duncan et al., 2004; Buchanan et al., 2007) did not find significant changes in cognitive symptoms. One study (van Berckel et al., 1999) with doses of 100 mg/day showed exacerbation of psychotic symptoms and exhibited prominent negative symptoms. This finding may be explained by the antagonistic effects of D-cycloserine at higher dose at the glycine recognition site of the NMDA receptor due to competition with the endogenous agonist glycine or an interaction with the effects of antipsychotics on NMDA mediated neurotransmission (van Berckel et al., 1999). 6.4.2. D-Cycloserine Added to Atypical Antipsychotics Four trials evaluated the effect of D-cycloserine added to second-generation antipsychotics (Heresco-Levy et al., 1998; Heresco-Levy et al., 2002; Evins et al., 2002; Buchanan et al., 2007) and none of them detected any significant change in positive symptoms. Three of these studies (Heresco-Levy et al., 1998; Heresco-Levy et al., 2002; Evins et al., 2002) demonstrated a significant reduction in negative symptoms at the dose of 50 mg/day. CONSIST (Buchanan et al., 2007) showed no significant effect of D-cycloserine at 50 mg/day on negative symptoms. Two trials (Evins et al., 2002; Buchanan et al., 2007) examined the effects on cognitive function and resulted in no significant change. 6.4.3. D-Cycloserine Added to Clozapine There were three trials evaluated the addition of D-cycloserine to clozapine (HerescoLevy et al., 1998; Goff et al., 1996, 1999). No significant effect on cognitive or positive symptoms was observed in any of the trial. One trial with D-cycloserine given at a dose of 50 mg/day (Heresco-Levy et al., 1998) found amelioration of negative symptoms. However, the other two trials (Goff et al., 1996, 1999) with D-cycloserine given at the same dose showed worsened negative symptoms.

6.5. Sarcosine There are four double-blind placebo-controlled clinical trials studying the effects of sarcosine as adjuncts to stable antipsychotic regimens. The first trial (Tsai et al., 2004)

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evaluated the addition of sarcosine (2 g/day) to typical antipsychotics and to risperidone, revealing significant improvements in the positive, negative and cognitive symptoms of schizophrenia. The second trial (Lane et al., 2005) evaluated the addition of sarcosine (2 g/day) or D-serine (2 g/day) to risperidone in patients with acute exacerbation of schizophrenia, revealing significant improvements in positive, negative, and cognitive symptoms and the therapeutic effects of arccosine are superior to D-serine. As previous studies found no beneficial effects of glycine, D-serine, and D-cycloserine as add-on therapies to clozapine, one trial (Lane et al., 2006) with sarcosine (2 g/day) co-treated with clozapine was also examined, which exhibited no improvement in the core symptoms. Addition of sarcosine to an existing antipsychotic regimen has shown its efficacy for both chronically stable and acutely ill patients. However, the efficacy of these agents as a primary antipsychotic agent has not yet been demonstrated. Therefore, Lane et al. (Lane et al., 2008) evaluated the effect of sarcosine monotherapy on 20 acutely symptomatic antipsychotic-naïve patients with schizophrenia, who were randomly assigned to receive 1 or 2 g of sarcosine daily. Though patients receiving the 2 g daily dose were more likely to respond, in order to fully assess the therapeutic effect of sarcosine, placebo- or active-controlled, larger-sized studies are needed. One recent double-blind, placebo-controlled study (Lane et al., 2010) recruiting 60 patients with chronic schizophrenia compared the effects of sarcosine and Dserine add-on to existing stable antipsychotics. The results showed that sarcosine therapy was more efficacious than D-serine for all outcome measures.

7. PERSPECTIVES D-Amino Acid Oxidase Inhibitors Therapeutic effects in ameliorating negative symptoms and cognitive impairments have been observed in some clinical trials with D-serine, (Tsai et al., 1998; Lane et al., 2010; Heresco-Levy et al., 2005; Kantrowitz et al., 2010) D-cycloserine, (Goff et al., 1995, 1999; Heresco-Levy et al., 1998, 2002; Evins et al., 2002), and D-alanine (Tsai et al., 2006) as adjuncts to typical or atypical antipsychotics. A meta-analysis concluded that D-serine is beneficial for negative symptoms, with a trend effect on cognitive symptoms (Tuominen et al., 2005). These findings suggest that DAAO, through the process of degradation of D-serine, Dalanine (Verrall et al., 2010; Smith et al., 2010) and other D-amino acids (Vanoni et al., 1997), may contribute to NMDA hypofunction, thus inhibition of DAAO is receiving attention as a potential alternative therapeutic means to enhance NMDAR function in schizophrenia (Adage et al., 2008; Duplantier et al., 2009; Ferraris et al., 2008; Sparey et al., 2008; Hashimoto et al., 2009; Smith et al., 2009; Horio et al., 2009; Williams 2009). The therapeutic potential of DAAO inhibitors is relatively unexplored and remains at preclinical stage, therefore, extensive further study is required to establish their efficacy, tolerability, and mechanism (Verrall et al., 2010). However, our recent findings reveal that a DAAO inhibitor is much more efficacious than other NMDA-enhancing agents in improving the symptoms of schizophrenia. Furthermore, it improves the cognition as measured by a comprehensive MATRICS-like battery.

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Modulators of Metabotropic Receptors G-protein-coupled mGluRs have now emerged as a new area of excitatory amino acid research (Schoepp et al., 1999) and therapeutic targets for psychiatric disorders, such as schizophrenia, depression and anxiety with their regulatory roles in glutamatergic transmissions (Yasuhara and Chaki, 2010). LY404039 is a selective agonist for mGlu2/3 receptor (Rorick-Kehn et al., 2007) and has shown antipsychotic potential in animal studies. The first mGluR2/3 agonist entered into monotherapy clinical efficacy trials for schizophrenia was LY-2140023 (an oral prodrug of LY404039), which showed significant efficacy in improving positive and negative symptoms, comparable to that of olanzapine and placebo (Patil et al., 2007). However, a follow-up study revealed a greater placebo effect; a multicenter, inpatient, phase II, double-blind, placebo-controlled dose ranging study of LY2140023 in patients with DSM-IV schizophrenia (ClinicalTrials.gov identifier NCT00520923), which leaves inconclusive results (Eli Lilly 2009; Kinon et al., 2011). Other than mGluR2/3, the development of allosteric modulators of mGluRs, including mGluR5 (Kanuma et al., 2010; Spear et al., 2011), mGlu1 (Lesage et al., 2010), as novel drugs in treatment of schizophrenics is on the way to decipher the therapeutic potential, efficacy and safety margin of these compounds.

CONCLUSION There is a new trend in the pharmacological approaches treating schizophrenia. Beyond DA and serotonin hypotheses which have dominated theories of schizophrenia for decades, dysfunction of glutamatergic system resulting in hypofunction of NMDA receptors has emerged as playing a pivotal role in the pathogenesis of schizophrenia based on the physiology of glutamate receptors, animal models, genetic studies, and clinical trials. These findings are encouraging as some of the clinical trials with compounds modulating the glutamate receptors, such as agonists of glycine binding site and glycine transporter inhibitor, have shown promising results in mitigating positive symptoms as well as negative symptoms and cognitive deficits, which usually respond poorly to typical antipsychotics and only respond partially to atypical antipsychotics. However, there are some promising results remain to be resolved and confirmed, thus extensive studies are still on the way, such as preliminary studies of DAAO inhibitors and mGluR modulators. We anticipate the development of more efficacious medications that work to substantially attenuate, if not alleviate, the full range of symptoms of schizophrenia in the near future.

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In: Advances in Psychology Research. Volume 96 Editor: Alexandra M. Columbus

ISBN: 978-1-62417-250-2 © 2013 Nova Science Publishers, Inc.

Chapter 3

HUMANISTIC PSYCHOLOGY AND THE MENTAL HEALTH WORKER Elliot Benjamin Transpersonal Psychology Program Director, Akamai University, Hilo, HI, US

ABSTRACT This article discusses the precarious relationship of humanistic psychology to the mental health worker in our current managed care, empirically based, behaviorally focused, excessively medication-oriented mental health system. Some of the challenges, frustrations, and potential successes of bringing real and nurturing human relationships in the context of humanistic psychology into the day-to-day involvements with clients for the mental health worker are described. Some of the particular ethical dilemmas of the mental health worker attempting to work in this context of humanistic psychology are discussed, inclusive of the enormous difficulties of bringing humanistic psychology into the all pervasive medical model that controls mental health practice in our society. Through a series of case descriptions, the author provides a narrative account of his own experiences in attempting to bring the authentic nurturing relationship context of humanistic psychology into his various mental health worker jobs. The author reaches the conclusion that this relationship context of humanistic psychology is in actuality being practiced by many mental health workers without knowing it by name. He further concludes that in spite of the challenges and frustrations of engaging in real and nurturing relationships with clients as part of the mental health worker’s job in our current society, the core ingredients of empathy, authenticity, and realness of bond between client and mental health worker, which are the hallmarks of humanistic psychology, are apparently being practiced with partial success through the cleverness, flexibility, and humaneness of mental health workers in spite of the enormous obstacles against this kind of humanistic practice.

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INTRODUCTION In this day and age, humanistic psychology and the mental health worker are in a precarious relationship. The mental health worker, especially in contemporary Western society, is expected to deliver treatment based upon “empirically supported” behavioral objectives, is generally working for a mental health agency funded by the state and utilizing strict psychiatric classification guidelines, and has been educated to be familiar and appreciative of the widespread usage and “benefits” of psychiatric medications. Where one might ask is there room for the quaint old notions of empathy, unconditional positive regard, authenticity, genuineness, etc. that were introduced by Carl Rogers, one of the key founders of humanistic psychology, over a half century ago? (Benjamin, 2008a; Elkins, 2007, 2009a; Rogers, 1961). The mental health worker, as I am using the term, typically is a young or middle-aged adult with or without a college degree, who is working with mentally disturbed children or adults in a mental health program. If the mental health worker has a college degree, he or she is likely to have majored in a psychology related field. It is somewhat ironic that in my own case, having decided to become a mental health worker after semi-retiring from a long career as a mathematics professor, in spite of all my esoteric ideas and writings about humanistic psychology, my official mental health worker classifications were Behavioral Specialist, Direct Support Worker, and Mental Health Rehabilitation Technician/Community. These do not sound like very humanistic titles; the titles reflect the current thinking in our modern “scientific” world of psychology. I was trained as a mental health worker to apply strict behaviorist psychology to the clients who were in my care, in particular Applied Behavioral Analysis (Kearney, 2008). How does a mental health worker with a humanistic psychology orientation survive in today’s mental health system? In David Elkins’ recent Journal of Humanistic Psychology article entitled. The Medical Model in Psychotherapy: Its Limitations and Failures, he concluded with the following: It is radical to suggest that the best way to deal with the medical model is to reject it completely. However, in our day, psychotherapy is under unprecedented attack by the very institutions that should be supporting it. The medical establishment has little respect for what we do, and the health insurance industry would like nothing better than to turn psychotherapy into a “quick-fix” center owned by Wall Street or replace it with an inexpensive pill….It may be time for humanistic psychologists to start another revolution in psychology. This time the revolution would involve rejecting the medical model, breaking away from the medical establishment, and telling managed care and the health insurance industry that we will no longer require their services. (p. 82) I find Elkins’ portrayal of the damaging effects of both the medical model and managed care, as well as his recommended remedies of preserving humanistic psychology (Elkins, 2007, 2008, 2009a, 2009b) to be timely, cogent, and tremendously important for humanistic psychologists to pay very careful attention to. However, I believe there are rich alternative contexts where humanistic psychology can be practiced, one of which is the context of community mental health fieldwork; i.e. mental health work in the homes and communities in which clients live and work, practiced by mental health workers who are not licensed

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psychotherapists, of which I was one. From my own experiences as a mental health worker, in particular over a three year span from 2007 to 2010, I found that most of the mental health workers in my agencies had a basic “humanistic” deep down desire to relate genuinely and caringly to their clients, but were saddled with an overwhelming amount of behavioral expectations from their supervisors and agencies. In order to keep their jobs they had little choice but to go along with the required behavioral programs, counting the number of targeted behaviors exhibited, checking off the extensive lists of treatment data sheets, monitoring their clients taking their prescribed psychiatric medications, and accounting for how they spent all their time with clients in accordance with the behavioral objectives of the program. These complicating external challenges to relating to clients in an authentic humanistic person-centered way (Rogers, 1961) are especially difficult to overcome due to the standardized short-term therapy allotment enforced by managed care (Elkins, 2008). However, in spite of all these behavioral, medical, and managed care expectations and requirements, I have seen that the humanistic realness and genuineness and empathy of the mental health worker somehow tends to sneak into their relationships with their clients. When you are spending 6 to 40 hours a week with one client, it is difficult to not become personally and emotionally involved with your client. It becomes a rather sophisticated learning skill to satisfy the behavioral expectations and requirements of your mental health agency while retaining the humaneness and dignity of the client/mental health worker relationship that you feel in your bones, in spite of the fact that you know this relationship may be time-bound in the context of managed care short-term therapy. I believe that the extended organic immersion of the mental health worker into the lives of his/her clients could be a very real source of therapeutic value for clients. This kind of extended involvement into the lives of clients is rich with possibilities of experiential and phenomenological value, incorporating potential heuristic and autoethnographic research methodologies that focus upon the experiences of the participants and the researcher, into a humanistic psychology context (Benjamin, 2012; Camic, Rhodes, and Yardley, 2003; Chang, 2008; Ellis, 2009; McQuade, 2006; Moustakas, 1990, 1994; Rogers, 1961; Sela-Smith, 2001). A vivid illustration of intensive organic experiential mental health work is given by Annie McQuade in her portrayal of her own immersion into the lives of mentally disturbed people living in the streets (McQuade, 2006). In comparison to the client visiting the professional office of a therapist for 50 minutes a week, there is a tremendous opportunity for the mental health worker to truly understand and have impact upon the actual day-to-day realities that mental health clients experience. However, it is also true that the mental health worker is generally not trained in the basic ingredients that have been found to nourish therapist/client interactions, inclusive of empathy, authenticity, and realness of bond with client (Elkins, 2007; Wampold, 2001), which are simultaneously the hallmarks of humanistic and existential psychology (May, 1969; Rogers, 1961; Schneider, Bugental, and Pierson, 2001, Schneider, 2008; Watkins and Bohart, 2001). To complicate matters even more, in addition to the mental health worker not being trained in the above beneficial qualities of a psychotherapist, the mental health worker is being trained in our contemporary “evidence based” behavioral and medication-oriented psychology society (Benjamin, 2008a; Elkins, 2007, 2009b, Watson and Bohart, 2001). However, as I have indicated above, I believe that the essential human qualities of empathy, authenticity, and realness of bond are sneaking through the cracks regardless of the official

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behavioral expectations of our managed care society. As Elkins has described the essential difference between mainstream psychology and humanistic psychology: “humanistic psychologists view psychotherapy not so much as ‘treatment for mental illness’ as a liberating interpersonal process that helps clients to grow and that provides support during critical times.” (Elkins, 2009b, p. 285). It is precisely this “helps clients to grow and provides support during critical times” that I see as the primary potential humanistic impact of the mental health worker on his/her clients. However, as I mentioned above, mental health workers are saddled with many rules and restrictions from the state, their mental health agencies, and managed care administrators in regard to how they are able to relate to their clients. Certainly a number of these rules and restrictions are involved with preserving the rights and safety of mental health clients. But I believe it is also the case that some of these rules and restrictions are quite arbitrary and have the effect of preventing the mental health worker from contributing in a constructive manner to the humanistic vision that Elkins (2009b) has described (see above). This humanistic vision that Elkins has described is consistent with the first of three components of evidence-based practice as set forth by the American Psychological Association (APA; 2005), namely, “best research evidence.” Elkins (2007), utilizing Wampold’s (2001) extensive research studies comparing the effectiveness of a wide variety of psychotherapy practices, concluded that one of the core ingredients of successful psychotherapy is the combination of empathy, authenticity, and realness of client and therapist bond, which happens to be one of the hallmarks of humanistic psychology (Rogers, 1961; Watkins and Bohart, 2001). The American Psychological Association’s (2005) third component of evidence-based practice, namely “patients’ characteristics, values, and context,” are especially relevant to the humanistic community mental health work that I am advocating for. The extensive involvement of the mental health worker in the lives of his/her clients ranges through the various ingredients highlighted in the APA’s (2005) Policy Statement on Evidence-Based Practice in Psychology, inclusive of being responsive to the patient/client’s specific problems, strengths, personality, sociocultural context, preferences, behavior, familiar factors, employment stressors, major life events, and so on. However, the mental health worker has virtually no official power in the therapeutic hierarchy in which he/she works in a mental health agency. As was conveyed to me in the context of one of my mental health worker training workshops, we (in my former capacity as a mental health worker) are at the bottom rung of the ladder in regard to having input on decisions made in the treatment of our clients. It was suggested that we advocate for our clients the best we can, but how seriously we are taken will depend upon the personalities and interests of our supervisors and agency administrators. The fact that I had a Masters in counseling, was a registered State of Maine counselor, facilitated monthly psychology and mental health workshops at one of my former mental health agencies, and at the time was working on my candidacy essays to obtain a PhD in psychology, did not at all change this relatively powerless scenario for me. Since my PhD psychology degree is not clinical and I have not obtained a counseling license, to this day I still have no more power and influence with mental health clients than any mental health worker at any mental health agency. If I were to decide to once again work in the community as a mental health worker, I simply would become a mental health worker with two PhDs (mathematics and psychology), and a commitment to having real and authentic relationships with my mental health clients—no more and no less.

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It is in the context of a person making a commitment to having real and authentic relationships with mental health clients that I believe lies the greatest potential value and impact that mental health workers can make in the context of humanistic psychology. In this article I will describe some of my own challenges, difficulties, and successes that I experienced in assimilating my behavioral work as a mental health worker into a bona fide humanistic psychology context, through a narrative description of my work with some of my mental health clients at four mental health agencies that I had worked for. In one of my mental health agency jobs, for one year I had conducted monthly training sessions for mental health workers, inclusive of workshops that I developed entitled “Treating the Person First in a Medication Oriented Society,” “Creativity and Mental Disturbance,” and “Ethical Dilemmas in the Human Sciences.” My workshops were geared toward informal discussion of psychological, philosophical, and mental health issues, and I frequently heard about the challenges and issues that mental health workers in my groups continually faced in trying to maintain authentic supportive relationships with their clients. These challenges and issues often pertained directly to some of the rules and restrictions of the state and my mental health agency that I have alluded to above, and I will be describing some of my own experiences with overcoming these challenges and issues in the context of working with my mental health clients. The aspect of being intimately and directly involved in the lives of mental health clients by spending many hours a week with them in their homes and communities is an incredibly rich source of therapeutic value. It is my contention that these kinds of community-based therapeutic relationships may very well be a possible means of (unofficially) practicing humanistic psychology as well. I would like to see mental health workers be able to tap into this therapeutic value and potential in a much greater capacity then they presently are able to do. I believe that incorporating existential and humanistic psychology into the training of mental health workers as a significant part of their training would be a highly effective way of contributing to this potential therapeutic value for mental health clients.

ETHICS AND THE MENTAL HEALTH WORKER The mental health worker is trained assiduously in the practice of ethical guidelines and proper reporting procedures in his/her work with clients for a mental health agency. These ethical guidelines are set forth to the mental health worker as firm boundaries that must not be crossed, as the consequence of violating these boundaries is immediate dismissal from the job. However, it is ironic that at the 2009 annual APA meeting in Toronto, Melba Vasquez, veteran board member, co-author of the APA ethical guidelines, and candidate at the time for upcoming APA president (she subsequently did become the next APA president), gave a workshop entitled “Psychotherapy Outside the Box—Boundary Crossings Versus Boundary Violations” (APA, 2009). In this workshop, Vasquez proceeded to describe the ambiguous nature of the APA ethical guidelines when it comes down to actual face-to-face contact with real people in a psychotherapy context. Vasquez described how she frequently engaged in what she referred to as “boundary crossings” when she decided that it was in the best interest of her clients for her to do so. This included attending social events of her Latino clients, hugging clients, and sharing aspects of her own personal life with her clients. These

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“boundary crossings” were what she considered to be of extreme importance in maintaining the rapport between her and her Latino clients, and these are in harmony with the substantial research which has demonstrated that the core ingredients of successful psychotherapy include the empathy, authenticity, and realness of client and therapist bond that Carl Rogers (1961) formulated more than half a century ago as the guiding principles of humanistic psychology (see also Bohart and Tallman, 1999; Elkins, 2007; Wampold, 2001). It is ironic though that when it comes to ethical guidelines and boundaries for the mental health worker, the subtleties and ambiguity of ethical practices that APA ethical guidelines co-author Vasquez described, is so easily dismissed. It might be instructive to take a brief detour from the pragmatic situations of ethical guidelines and rules for the mental health worker, to put this whole ethics topic in a wider context. Lawrence Hinman (2008) described the extremes of ethical absolutism and ethical relativism, and advocated for a middle ground of ethical pluralism, in which one formulates generic ethical and moral principles that are shaped by the particular circumstances of individual human beings in a variety of social contexts. Hinman related his view of ethical pluralism to the Aristotelian version of practical wisdom, virtue, and character, as follows: Aristotle’s account of practical wisdom also provides a useful insight into ethical pluralism. The virtuous person always acts in light of a general conception of human flourishing. Each of the moral theories we have studied in this book contributes to our understanding of human flourishing, and the virtuous person of practical wisdom is able to balance these competing theories in particular situations, discerning which is most morally significant in a specific case….Moreover, in the Aristotelian view, it is not simply a question of telling the truth or lying; it is also a matter of how the truth is told (with care and consideration about its impact or with crassness), when it is told, and to whom it is told. (Hinman, 2008, pp. 287-288). Hinman’s description of ethical pluralism and Aristotelian practical wisdom is highly consistent with the ethical boundary crossings described by Vasquez, and which appears to be increasingly appreciated in its complexity and subtleties by APA. However, for the mental health worker employed by a mental health agency, these kinds of ethical complexities and subtleties are all but lost, as the overriding rules of thumb are the firm rules, restrictions, and boundaries handed down by the administrators of the agency, and which I would place under the heading of ethical absolutism. The higher level ethical considerations portrayed by Vasquez is also consistent with the higher levels of moral development described by a number of psychologists and philosophers. In philosopher Ken Wilber’s view: There is general and ample agreement that human development goes through at least three broad stages: the human at birth is not yet socialized into any sort of moral system (it is “preconventional”); the human then learns, from itself and from others, a general moral scheme that represents the basic values of the society it is raised in (it becomes “conventional”); and with even further growth, the individual may come to reflect on its society and thus gain some modest distance from it and gain a capacity to criticize or reform it (the individual is to some degree “postconventional”). (p. ix)

In my own role of mental health worker at the two mental health agencies I worked for during the last two years of my community mental health work, I worked under the same inflexible “conventional” ethical guidelines and boundaries as my counterparts. However, I

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was also well aware of the complexities of dealing with ethical guidelines in real live situations with mental health clients, and my background and commitment to the foundations of humanistic psychology put me in continual conflict with the policies of my mental health agencies vs. the higher ethical (Aristotelian “postconventional”) inclinations that were deep within me. The examples that I will give from my mental health agency work illustrate the kind of conflict that I continually faced in my work, and I believe that this kind of conflict is prevalent in the day-to-day interactions of mental health workers with their clients. I will begin my personal/professional illustrations of humanistic psychology and the mental health worker with a description of my initial mental health work as a part of a counseling internship at a mental health agency, with a child diagnosed as having Asperger’s Syndrome. My mental health/counseling work at this agency lasted only 6 weeks, as I was promptly fired from my job, as I describe below.

MY INITIAL CAREER CHANGE EXPERIENCE AS A MENTAL HEALTH WORKER I began my late-in-life career transition from mathematics professor to mental health worker in 2007, as I managed to find a mental health agency willing to employ me as a mental health worker while I started to satisfy the requirements of my counseling internship to obtain a counseling license. But to cut to the chase, I was fired after 6 weeks. I will never forget the shock of one morning being called away from the kids I was working with, first thing in the morning about 20 minutes after I arrived for work, being sent to a large conference room with only my immediate supervisor and the human resources director present, and being told that I was being asked to resign effective immediately, or else I would be terminated effective immediately with additional adverse consequences for my future mental health job prospects. I was then followed back to my working space, and with the children I had been working with and other staff watching, I had to retrieve my belongings and drive home, now an unemployed mental health worker. With all my unhappiness and complaints of my 21 years as a mathematics professor, never could I even have imagined a scenario like this taking place. Why did I get fired from my initial mental health job in my new career? Of course the answer to this question depends upon who is giving the answer, but I think it is safe to say that I did not adhere to the ethical guidelines and rules of my mental health agency when it conflicted with my inner sense of what felt right to me when relating to my clients. Or in a more theoretical context, I could say that I chose to listen to my “postconventional” higher ethical values in opposition to the “conventional” ethical rules and restrictions that my mental health agency required me to follow. This was in large part related to disagreements that I had about how a child was physically restrained at my agency, my written communication with a parent in response to a child’s personal request for me to do so, and to my inclination to encourage the creative interests of my little client diagnosed with Asperger’s Syndrome that were in conflict with some of the structured behavioral expectations of my agency’s program, as I describe below. However, from my perspective nearly 5 years later, I can see that I was naïve about the political ramifications of how much I asserted myself at my agency, and I

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subsequently learned that my strengths and inclinations were working in community mental health where I had a relative degree of freedom and independence, as opposed to working in a continual fishbowl atmosphere at a structured hierarchical mental health agency. As it turned out, I managed to soon find another mental health job, in which I stayed for more than three years (a relatively stable period of time in mental health work with the quick turnover in the field) along with a second mental health job that I kept for more than two years. For a few years I had found my niche as a mental health worker in late life, and I was certainly considered by my agencies to be quite the mental health worker oddity, having a PhD in mathematics and a Masters in counseling, and I was in the process of obtaining a second PhD, in psychology. Although I enjoyed teaching monthly continuing education training workshops at my second mental health agency, what was most important to me in my new career as a mental health worker was the way in which I worked with my clients, for I believe that I somehow managed to retain the essence of humanistic psychology in my dayto-day work with mental health clients. I chose to accept the rigid pronouncement of the State of Maine’s licensing board that none of my coursework from my Masters in counseling program in the 1970s would count towards my counseling license, presumably because my coursework could not accurately be described due to the fact that my school, Boston State College, was incorporated into the University of Massachusetts back in the 1980s. I chose to accept my being merely a “registered” State of Maine counselor, knowing that not obtaining a counseling license would prevent me from obtaining any kind of reasonably paid mental health job with any kind of respectable status or significant influence in my mental health community. I chose this because at my advanced age and career I did not want to take a lot of courses I had already taken and that I had little current interest in. My tremendous desires and inclinations were to pursue my interests in humanistic and transpersonal psychology as part of my PhD psychology program at Saybrook University, and this is precisely what I decided to do. However, an unexpected consequence of my decision involved me being able to truly experience the I-thou relationships which Martin Buber (1970) eloquently wrote about, while I found a way of practicing the essence of humanistic psychology in regard to the authentic relationships I experienced with my mental health clients (Bohart and Tallman, 1999; Elkins, 2007). My poor economic and low career status as a mental health worker was well worth it to me, as I was far happier in my 3 years of employment as a mental health worker than I was for the previous 21 years I was employed as a mathematics professor. As I will describe below, in many respects I was able to engage with my clients in ways that transcended the medical model, managed care system that I officially worked for, and I can relate well to Maureen OHara’s advice about practicing humanistic psychology outside of the medical establishment, as cited in Elkins (2009a): The age-old idea of work as something akin to a sacred calling, a vocation inspired by a desire to serve humanity, drives many therapists who choose to buck the tide of managed care yet still want to be in private practice. Another powerful moral incentive is their determination to remain free and independent. Certainly, the ideal of service is more compelling than any hopes of getting rich. It is an ideal that these clinicians often believe has been misplaced by the therapeutic community over the last decade or two. (p. 82)

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I can also relate well to Elkins’ (2009a) conclusion in his article The Medical Model in Psychotherapy: “We might also feel more in charge of our professional lives, sleep a little better at night, and have more passion and excitement about going to work each day.” (p. 83). Although Elkins and O’Hara are talking about leaving the medical model entirely and going into private practice as a psychotherapist, I believe there is an opportunity to engage in community mental health field work on the official lowest level of the totem pole, while experiencing authentic therapeutic relationships with mental health clients. Due to its minimal economic rewards and status it is not work that I would have intentionally chosen, but it is work that I am grateful for the privilege having been able to experience, as I will now describe. In my initial 6 week career transition job as a mental health worker and counselor intern, the child I was most involved with was a 7 year old boy diagnosed with Asperger’s Syndrome as well as Attention Deficit/Hyperactive Disorder (ADHD; see DSM-IV-TR; American Psychiatric Association, 2000). I will give this child the fictitious name Charles, and describe some of my experiences of working with Charles in a humanistic capacity. As I learned during my month and a half of internship, when a child is diagnosed with ADHD it is virtually impossible for this diagnosis to be removed. The reason for this is due to the fact that the child is put on various psychiatric medications, and the assumption is that the ADHD symptoms are improving because of the medications, but without the medications it is assumed that the ADHD symptoms would be much more severe (Baughman and Hovey, 2006; Benjamin, 2008a; Breggin, 2008; Degrandpre, 2000; Healy, 2002). Charles was certainly a child who liked to be active and move around a lot, but when he was involved in an activity that he enjoyed, his attention span and activity absorption were truly remarkable. Charles had demonstrated intensive focus and absorption in a number of diverse activities, such as playing one of my mathematics enrichment Numberama games (Benjamin, 1993), playing the electronic keyboard and learning drumming rhythms, putting together a water pipes puzzle, playing the number game Yatze, creatively putting various structures in the water sprinkler on the playground, and playing Bingo. These qualities and characteristics I had observed in 7 year old Charles (and participated in) were in my mind the prime ingredients of a potential future creative scientist. This is consistent with studies that have shown a definite trend of scientific creativity, especially in the area of physics, in children with high level forms of Autism (Baron-Cohen, 2000; Fitzerald, 2004). Charles’ diagnosis of Asperger’s Syndrome implied that he had significant problems in the social context of interacting appropriately in mutually engaging ways with other children (see DSM-IV TR; American Psychiatric Association, 2000). I did not disagree with this description of Charles, as he certainly did have problems in his interacting with other children, and he also needed to learn to be more adaptable in regard to constructively engaging in activities that he may not have been particularly interested in but were expected of him as part of my agency’s program. Intensive absorption in a particular area of interest is a common feature of Asperger’s syndrome (Fitzgerald, 2005; Webb et al., 2005). However, this kind of intensive absorption is also a dominant feature in what has been described as “eminent creativity” (Runco and Richards, 1997) and in my own definition of the “successful creative artist” (Benjamin, 2008b). But as I read over all his psychological and psychiatric evaluations, it struck me that this intelligent and creative child was essentially viewed and classified according to his problem

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areas rather than his strengths. Charles was not being treated with respect, appreciation, and openness to his potential areas of creativity, in a humanistic psychology therapeutic context. Charles had seemed to take a genuine liking to me, and I wondered if he somehow sensed that I saw what was special in him; i.e. I saw his deep potential artistic self that yearned to emerge. Little Charles had been given numerous and varied medications since he was 4 years old, and it appeared that his problems were directly related to the early neglect and possible abuse from his biological parents, although it is quite possible that he may have also been adversely affected by all the medications he was taking (Baughman and Hovey, 2006; Benjamin, 2008a; Breggin, 2008; Degrande, 2000; Healy, 2002). The community mental health center that Charles and I took part in was quite structured and socially oriented. The programs of activity of this agency were extremely behaviorally focused, and although their programs of activity appeared to be beneficial to most of the children who took part in them, I must also say that their appreciation of a child’s potential creative interests and abilities were severely lacking. Whatever I was able to accomplish with Charles in regard to helping the potential creative artist/scientist in him to emerge in the short period of time I worked for this agency, I needed to do when virtually no-one else was around. Charles was the child I most looked forward to working with in my mental health agency internship site. I saw my Artistic Theory of Psychology (Benjamin, 2008b) in a microcosm when I was in the presence of Charles. The intelligence and creativity were there, but so was the aloofness, the “in his own world” quality, and the social difficulties of interacting appropriately with his peers. Thus the healthy adjustment to society factor in my definition of the successful creative artist (Benjamin, 2008b) was going to be a severe challenge for Charles to achieve. Our mental health agency’s extreme emphasis upon behavioral programming contained various individually designed behavioral reinforcement treatment plans. I believe that this environment was likely effective in helping Charles learn how to be more “normal” in his social interactions with other children, and I am in agreement with the agency that this was a fundamental and important learning task for Charles to accomplish. However, I also think that the potential creative abilities of Charles should have been more appreciated and included in his treatment plan, and this is where humanistic psychology could have filled an important gap in Charles’ treatment program. But in my capacity as a mental health worker I was severely limited to make any substantial changes in Charles’ behaviorally oriented treatment program, and it certainly did not help Charles by my involuntary departure from the agency. From a humanistic psychology and education perspective, during his free time at the agency, i.e. aside from the group structured social activities, Charles should have been able to choose activities of his own choice and free will (Rogers, 1961, 1969; Neill, 1960), rather than the limited range of social emphasis activities the agency allowed him to choose from. But perhaps the biggest lesson I learned from this whole frustrating experience was in the context of the politics involved in trying to bring real and nurturing human relationships into the realm of the day-to-day work of a mental health worker.

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MATHEMATICS ENRICHMENT/MENTAL HEALTH WORKER AT A CHILDREN’S MENTAL HOSPITAL In my “Art and Mental Disturbance” article (Benjamin, 2008b) I have given some illustrations of my work in a humanistic psychology context with severely disturbed mental health clients which stemmed from my mental health worker night attendant job at a mental hospital more than 30 years ago. I will now give a more recent illustration of an experience I had in which I found myself in an unexpected humanistic and artistic psychology context with a teenage girl at a mental hospital for children (see Benjamin, 2009). In fall of 2001 I was volunteering to give my mathematics enrichment Numberama lessons (Benjamin, 1993) 1 hour every other week for 4 months at a children’s mental hospital in Maine, and I found myself having a rather unique mental health worker experience. The patient at the hospital who had the most impact upon me was a girl of 15 or 16, whom I shall refer to as Allison. I did not have access to the clinical files of the children I worked with at the hospital; therefore I can only make educated guesses regarding their diagnoses. Allison struck me initially as an angry and combative teenage girl who had no interest whatsoever in taking part in my proposed Numberama activities, even though she was part of a group of four or five hospital residents, all of whom younger than she was, who were scheduled to be in my group. However, somehow or other it came about that Allison and I shared a rather unusual interest within the hospital environment: Paganism. For a number of years I had been attending yearly Neopagan festivals with my son in western New York State (Benjamin, 2004), and when Allison made some comment about being interested in Witchcraft, an uncanny chord was struck between us, much to the surprise of the other children and the hospital staff. Gradually Allison began to confide in me all about her mystical experiences, extrasensory perceptions, magical powers, and so on. I realized that it was quite likely that Allison was diagnosed with some kind of Schizophrenic disorder and quite likely with Borderline Personality Disorder, related to her general angry and combative ways of relating to nearly everyone at the hospital (see DSM-IV TR; American Psychiatric Association, 2000). But I found myself gradually disclosing to Allison things about my life and my relationship with my Wicca girlfriend at the time that I shared with very few people. It turned out that Allison herself was Wicca, that she was brought up this way in her family, and she strongly recommended to me to read the classic pagan novel The Mists of Avalon (Bradley, 1983). I took Allison’s advice quite to heart and proceeded to read this thick book even though I rarely read novels, and I found myself thoroughly relating to the Wicca focus of the legend of King Arthur. Thus each time I came to the hospital to do my Numberama lessons, Allison would become more and more friendly to me, and even willingly agreed to participate in my Numberama group activities, occasionally acknowledging that my teaching strategies and program did have some value. Allison was not someone who particularly enjoyed mathematics, but the rapport we established in a humanistic psychology context (Elkins, 2007; Rogers, 1961) was strengthened as she was able to view me as primarily a math teacher and not another “shrink” to work with her as part of a social service agency. For me, I felt like I was entering some kind of bizarre no-man’s-land in a somewhat similar way to my experience of working at a mental hospital as a night attendant and subsequently as a group facilitator for ex-mental patients at my community mental health center in Massachusetts in

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1980 (Benjamin, 2008b). The bond that I was establishing with Allison was part of a truly nourishing and creative life process for both of us, in the fundamental context of the basic principles of humanistic psychology and psychotherapy (Elkins, 2007; Rogers, 1961). When I would arrive at the hospital to do my Numberama lessons I could often hear Allison yelling at staff members, threatening and formidable in her anger. But as soon as she would see me her anger and bad mood would begin to evaporate, as she very much looked forward to being with someone whom she could truly talk to about the things that mattered most to her in life. Somehow we always found some time to talk, either before or after my Numberama lessons, and the words that come to me to describe Allison at these times are in the context of “sweet” and “charming.” Finally Allison was sent home from the hospital, and my initial Numberama experience at the hospital in a humanistic psychology authentic relationship context came to a natural end. Allison had conveyed to me how she learned to stop talking about her interest in Wicca, magic, and extrasensory perception with the psychologists whom she was required to be treated by and who gave her large doses of psychiatric medications. She knew very well that the only way she would ever be considered “normal” enough to be sent home was if she pretended to no longer have these unusual thoughts and images. And I knew far too well how right Allison was about this from my own life experience as well as from some of my radical readings in psychology, which have been further reinforced by some of my more recent radical psychology readings and writings: (Benjamin, 2008a, 2008b; Elkins, 2009a; Grof, 1985; Jamison, 1993; Jung, 1936; Feinstein and Krippner, 1997; Krippner, 1975; Laing, 1967; Lukoff, 1985; Maslow, 1971; Panter et al., 1995; Richards, 2000-2001; Runco and Richards, 1997; Scotton, Chinon, and Battista, 1996; Szasz, 1974; Tart, 1975; Wilber, 1995). I am now fully aware and confident that in a number of contemporary views of mental disturbance, a premium is put on the creative expression of the mystical experiences inside an individual like Allison. I like to believe that in my brief mathematics enrichment/mental health worker engagement with Allison, I offered her the experience of realness, empathy, and genuineness that are the hallmarks of humanistic psychology (Elkins, 2007; Rogers, 1961). I look upon my experience with Allison in a much more successful and satisfying way compared to my experience with Charles (as described above), regarding how I was able to engage in a productive, authentic, and empathic therapeutic relationship with a patient in a mental hospital while in an official mathematics enrichment/ mental health worker capacity.

THE CHALLENGES OF PRACTICING HUMANISTIC PSYCHOLOGY AS A MENTAL HEALTH WORKER As can be seen from my previous two personal illustrations of trying to practice humanistic psychology through engaging in authentic nurturing relationships with clients while in a mental health worker context, there are some very real challenges that can make it difficult or impossible to accomplish this, but there is also room for actions to meet these challenges, at least some of the time. To further illustrate these kinds of challenges, I will describe some of my more recent experiences working with clients in the mental health agencies that I was employed at as a mental health worker Behavioral Specialist and Direct Support Worker.

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At the mental health agency that I was employed at for more than three years, I was required to follow state treatment plans which included various objective reinforcements of desired behaviors along the lines of Applied Behavior Analysis (Kearney, 2008). However, my clinical director frequently coupled this strict behavioral outlook with a decidedly humanistic and even transpersonal perspective, talking about the priorities of building “caring relationships with firm boundaries” with clients, and advising us to follow our inner spiritual guidance and our place in the universe. At first this seemed completely contradictory to me, as I believed that humanistic and transpersonal psychology were at the opposite ends of the spectrum from behavioral psychology. However, the timing was such that I experienced Steve Hayes’ Acceptance and Commitment Therapy (ACT) at around the same time that I started this job, and I realized it was indeed possible to combine behavioral psychology with humanistic and even transpersonal psychology (Benjamin, 2007; Hayes, Strousal, and Wilson, 1999). It should be mentioned though that this is a sensitive and delicate process, and it requires a highly unusual combination of qualities in a mental health worker or clinician to effectively accomplish this. However, toward the end of my employment at this agency, my clinical supervisor began talking about the “interchangeability” of mental health workers being assigned to work with clients. I believe that this was directly related to using the allotted number of hours the state allowed the agency for reimbursements, and is one of the key challenges of practicing humanistic psychology for the mental health worker, as I will describe below. To illustrate concretely the challenges of bringing a humanistic psychology orientation into behavioral community mental health work, that can be feasibly met at least on some level, I would like to describe my work with a 16-year-old boy with whom I had been working on and off for 2 years, for generally 8 hours a week. For the first 6 months of our working together, I had been successfully building up a trusting and enjoyable personal relationship with this boy that focused upon doing things in the community such as tennis, bowling, billiards, hiking, bicycle riding, roller skating, getting together with his adult friends, and so on. While we would be engaged in these activities, my client gradually would open up to me more about his inner feelings, concerns, and goals. However, because of the limit to state funding, our work together needed to come to an end, even though I believe my client would have greatly benefited from being in a continued therapeutic relationship with me (Elkins, 2008; Miller, 1996). My agency rules were very strict in regard to preserving our boundaries with clients, and once the official work with a client ends, any kind of continued contact was strictly forbidden (see my above discussion in the section “Ethics and the Mental Health Worker”). During the whole course of our work together, I was required to go through my supervisor for any communications with my client or his family between our sessions. These are the agency rules I needed to follow in order to maintain my mental health job, as establishing firm boundaries with clients had been strongly impressed upon us in no uncertain terms. However, at the same time I was aware deep down that these extreme boundary conditions felt to me like they were antithetical to the core ingredients of humanistic psychology, especially the ingredients of therapist genuineness and the authenticity of the client/therapist relationship (Elkins, 2007; Rogers, 1961), and I was thinking of myself as being in a “therapeutic” mental health worker relationship with this client. Indeed from a multicultural perspective these artificial boundary conditions may be construed to be quite

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counter-productive to effective psychotherapy with clients (Alsup, 2008). I wanted to be able to stay in contact, at least occasionally, with my client after our official working together time ended, and to see how he would be doing in working toward his goals. It felt “inhuman” to me to so abruptly cut off from him simply because the state refused to reimburse my agency any longer, and I subsequently learned that research studies have supported my intuitive strong feelings that this abrupt and premature ending to our relationship was not beneficial to my client (Elkins, 2008; Miller, 1996). I was indeed in the midst of the conventional vs. postconventional ethics deliberations that Wilber (1995) has described (see above), but I also was facing the significant added complication of being in danger of losing my job if I chose to follow my higher ethical values. Although I gradually learned to accept and make the best of the reality of the state and my agency’s policies in this regard, I believe that this abrupt and artificial severing of the relationship between the client and mental health worker displays the extreme challenge of maintaining a humanistic context of relating to clients for a novice mental health worker who is working in our managed care mental health system (Elkins, 2008, 2009a, 2009b; Miller, 1994). This personal/professional situation I have described brings the whole issue of professional mental health ethics sharply into focus (see above), as there are no stipulations against remaining in contact with a client after a session ends in the ethical guidelines put out by the American Counseling Association (1995), and this is consistent with the American Psychological Association perspective on ethical practices as described by Vasquez (APA, 2009; see above). However, my story with this teenage client did not end after my initial 6-month period of working with him, as a year and a half later he and his mother requested that I work with him again (there was an official 6-month waiting period between state approved treatment plans), which I did for another 3 months. In the year and a half since I had worked with my client he had significantly regressed, as he recently had been placed in residence in a mental hospital after being suspended from school for assaulting a teacher, and he had criminal charges placed against him for destroying property. At my initial meeting with my client, his mother, and my mental health supervisor, my client refused to come out of his room, and I was quite apprehensive about working with him again. However, it turned out that my client and I re-established our bond of working together in a harmonious way, he made progress in his ability to constructively control his anger, and he soon transitioned into a public high school. But the ethical conflicts between the “conventional” ethical restrictive guidelines of my mental health agency and my “postconventional” ethical values by no means abated. I found myself immersed into my client’s world as he became increasingly more comfortable and trusting of me, divulging to me his privileged information in regard to not taking his prescribed medications, smoking marijuana, and so on. I considered the trust my client was placing in me to be sacred. However, it was pointed out to me by one of my mental health worker colleagues that if I were in an official counseling relationship with my client then I would have the option of not divulging privileged information he reveals to me, but in my present mental health worker capacity I was required to document and officially communicate to my supervisor any “controversial” information my client shared with me. The situation became more and more complicated for me, especially as I was sympathetic to my client’s experience of his mother being

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exceedingly controlling, authoritarian, condescending, and focused on solely the negative aspects of his behaviors toward her. I was also very affected by all that I had learned (and was teaching) about the dangers and questionable benefits of psychiatric medications (Baughman and Hovey, 2006; Benjamin, 2008a; Breggin, 2008; Degrandpre, 2000; Healy, 2002). As it turned out, my second time period of working with my client ended rather abruptly, as he was caught with a bag of marijuana that he obtained with the help of his father, and his mother decided that she did not want me to continue to work with him. However, the larger issues regarding the ethical conflicts for a mental health worker trying to retain a humanistic way of working in a traditional managed care, medication-oriented, behavioral setting remained with me. One crucial aspect that enabled me to survive in this humanistic context for more than three years was directly related to the humanistic style of supervision that I had been very fortunate to continually experience from my immediate supervisor in one of my agencies. My strong values of relating in a real way to my clients, retaining the freedom to be responsive to my clients’ needs and interests as much as possible, bending the agency rules without breaking them when the situation appeared to me to be warranted, and so on had all been wonderfully supported by my supervisor. I sometimes forgot that things would have been very different for me if this were not the case, but I describe in the next section a brief scenario that I experienced with a different supervisor who was much less humanistic and sensitive, and had a much more rigid behavioral way of working, which resulted in a very unfortunate termination between my agency and my client. The ethical dilemmas for the humanistic mental health worker in today’s mental health agencies are very real and immense. As I continually experienced during my late-in-life employment as a mental health worker, these ethical dilemmas bring to the surface a confusing array of one’s strong values vs. much of what humanistic practitioners agree are harmful and detrimental practices of our managed care, medication-oriented, behavioral mental health system (Elkins, 2008, 2009a, 2009b; Miller, 1994, 1996). Having a supervisor who can support the mental health worker coming to terms with his/her best course of action in these ethically confusing circumstances is ideal, though by no means common from what I learned in my communications with my mental health worker colleagues. However, in my own psychology and mental health trainings that I facilitated in a humanistic education style (Rogers, 1969) and have briefly described above, I gave my mental health worker colleagues the opportunity to discuss their professional ethical workrelated confusions and issues. From the feedback I received, my mental health worker colleagues greatly appreciated this, and my trainings were popular at my agency for more than a year. I believe that humanistic mental health workers who have the educational qualifications may contribute greatly to the plight of others in the field by offering these kinds of humanistic education open-ended ethical issues discussion groups at their own agencies, though of course this requires the support of openminded administrators who have some appreciation of the humanistic perspective to mental health, which may or may not be feasible at one’s particular mental health agency.

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ANECDOTES FROM THE EXPERIENCE OF A MENTAL HEALTH WORKER At this point I would like to supplement my above description with a few anecdotes of my work with some mental health clients that I believe further illustrates some of the challenges as well as opportunities that mental health workers are currently facing in our managed care, medical model mental health system. In particular, my next example illustrates the pitfalls of behavioral psychology when it is not feasible to assimilate it into a humanistic psychology context, with the mental health worker caught in an unworkable no-win situation. In my same community mental health job as described above, I had entered the home of my new 15-year-old cognitively impaired mental health client to work with him for the first time. As soon as I walked in the door, my new supervisor greeted me with my client’s comprehensive educational diagnostic report and the visual reinforcement star board that she wanted me to be using with him. This went completely against my instincts, as I knew that I first needed to build up a personal relationship with my client, establishing rapport and a positive association between us so that he would be looking forward to me working with him. I was not closed to eventually utilizing some kind of behavioral reward system with visual cues, but only in due time after I had built up a bona fide relationship with him, along the basic tenets of the core principles of humanistic psychology (Bohart and Tallman, 1999; Elkins, 2007; Rogers, 1961; Schneider, Bugental, and Pierson, 2001). Suffice it to say that I stuck to my principles and began building up just this kind of relationship with my client, as I refused to be involved with the behavioral visual reward system until I had done so. It is also interesting that while I was building up a humanistic relationship with both my client and his stepfather, I found myself calming down the stepfather who wanted to throw my supervisor out of his house for working so mechanically with my client, who was not responding well to her efforts. Unfortunately this story does not have a happy ending, as when I returned from being away for 2 weeks for a professional conference and vacation, I was informed that the family had decided to terminate their involvement with my agency, because they were not willing to work with my supervisor in their home. With this same agency, I had been working for 3 months with a severely disturbed physically large 17-year-old boy with Asperger’s Syndrome, who had threatened to kill people at his school. This client had great difficulty spending much time with any mental health worker, and was exceedingly emotionally dependent on his parents. I gradually succeeded in developing a constructive relationship with my client, taking him out in the community to go bowling, and spending 4 hours a week with him. However, my agency was frustrated that there were many more hours the state was willing to fund for this client that were being wasted, at a significant financial loss to the agency. My concerns that increasing the number of hours for this client would backfire and become antithetical to any progress he was making fell on deaf ears. Other staff members were brought in to increase the number of hours working with this client to a total of approximately 15 hours a week. It did not take very long for my client to have an extreme “melt down,” physically assault his parents, and have a lawsuit filed against him. My client’s involvement with my agency came to an abrupt end, and another lesson of the insensitivity of my mental health agency to the real needs of their mental health clients vs. the financial needs of the agency was impressed upon me.

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To give an example of some of my more positive mental health experiences at this same agency, I will give a short account of my work with a highly aggressive and impulsive physically strong 7-year-old client, diagnosed with Pervasive Developmental Disorder and Mood Disorder (see DSM-IV TR; American Psychiatric Association, 2000). I was called into the case after the previous female mental health worker decided she could no longer work with this client, as his physical aggression, frequent assaultive episodes, and boundary violations of her were more than she could handle. I was able to establish firm boundaries with this client, and he appreciated that I responded to what he was persistently and singlemindedly interested in doing. What was this persistent and single-minded activity my 7-yearold client was so interested in doing? We developed the routine of riding bicycles in search of beer bottles. My little client had his entire garage filled to capacity with beer bottles and cans that he and his mother would return for extra cash. It was not just beer bottles and cans that he would collect, as soda bottles and cans, and nonalcoholic beverages of various types also made their appearance in our outings and his garage, but his passion was undoubtedly for finding beer bottles. He would repeatedly ask me about how different beers taste, and his favorite beer bottle outing was to drive to the dancing bar in a nearby town and rummage through the parking lot and woods in search of beer bottles. We thus established a harmonious relationship through my responding to his somewhat questionable 7-year-old interests, in which he made significant progress in his abilities to control his highly negative behaviors. Focusing upon beer bottles is not something I would generally recommend for working with a 7-year-old, but in this case I believe it represents an example of effective mental health work in a humanistic psychology context of establishing a real, authentic, caring relationship with a very difficult little client. I will also note that my supervisor in this case, who is the same humanistically oriented supervisor I described above, had sufficient understanding,. appreciation, and trust in how I was working with this client to allow me to pursue this rather unconventional way of working with a 7-year-old child. I would like to give one final personal/professional illustration of the challenge of imparting humanistic psychology in the context of the job of a mental health worker. In the mental health worker job that I was employed at for more than 2 years while simultaneously working for my above mental health agency, I was working 20 hours a week with a moderately impaired developmentally disabled 21-year-old male client who had Down’s syndrome (see DSM-IV TR; American Psychiatric Association, 2000). In this capacity, my mental health worker job official expectations predominantly involved working on daily living skills, although a few months ago my client transitioned into a community integration program with higher level community skill expectations. There were the usual state checklists with tabulating the number of times he needed assistance or a reminder to use the bathroom, make a store purchase, practice safety skills, etc. His chart was quite thick, and contained a number of reports of difficult interactions with previous mental health workers in which he had become physically assaultive and destructive of property. However, I was introduced to working with this client by job shadowing with his transitioning mental health worker who had an obvious enjoyment and a very natural humanistic attitude toward working with him. We went to his favorite place: the gazebo in the park, and I watched him happily take out all his toys and coloring books from his briefcase and industriously color in one of his coloring books for more than an hour. I learned how sweet and gentle and cooperative this young man could be, as long as he was given the time and space he needed to do things in his own way, and not be rushed beyond what his natural organic constitution could tolerate.

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It was not very difficult for me to learn how to juxtapose my agency’s official state checklist requirements with allowing my client to have the relaxed time and space that he needed. I found that given my intention to be in this kind of humanistic relationship with my client, he was more than willing to meet me halfway when there were time constraints and expectations of him that did need to get done, such as his volunteer work, and so on. The upshot is that my client and I enjoyed a harmonious and comfortable working relationship for more than 2 years, which included us playing music together, extending to performing for his community center with me playing the piano or drum and him playing the bongo, a regular routine of us going to the gazebo in the park and playing our drum and bongo together, and a regular structure of going to the library where my client looked through picture books and magazines for 1 to 2 hours, while I industriously made progress in the books I needed to read for my doctoral psychology program or grade the mathematics homework assignments for the online mathematics courses I was teaching. However, I also saw how my client could react quite negatively to mental health workers who rushed him and ordered him to do things without being sensitive to his slow nature and unique ways of going about things. My client went every day to a community mental health center for developmentally disabled adults, and it is a credit to the mental health workers at this agency how flexibly and caringly they treated him. My client generally was the only one still eating his lunch at the table long after everyone else has finished eating, and the mental health workers and supervisors at this community center were patient and responsive to his eating needs. When they played Bingo, my client had a very difficult time leaving before the games ended, and this was always a conflict for me as I was told that the community center and my agency could not “double dip” as the state would not pay for both agencies to work with him at the same time. For a while this was quite a challenging situation for me to deal with, but the community center ended up unofficially bending their rules, letting me spend time with my client for him to finish the Bingo game he was playing when I arrived, even giving him a little prize at the end of each game, that is supposed to be given only to people who win the game. This was most definitely bending the rules, but the other clients did not seem to mind, as everyone seemed to realize that it was a small price to pay for my client to remain happy and not throw a tantrum, and for me to be able to continue to work with him. Somehow my client and I had an uncanny click of personalities, in which we each needed a good deal of slow low-key time, and our library time together served this purpose very well for both of us. Our sharing of library time was a continuous positive central core of our mutually satisfying relationship, although unfortunately my client’s mother did not appreciate the therapeutic value of our sharing of this slow library time together. This eventually developed into a major issue of how I spent my time with my client, and it led to the termination of my mental health worker job at this agency about a year and a half ago—and to my relationship with my client. This made me feel quite sad, especially as my more than three years of mental health work with my other mental health agency had ended a few months before this—for administrative reasons that I was informed about by phone one day, being told that my job was ending effective immediately. Losing both my mental health worker jobs was very difficult for me to deal with, and it felt to me like a continuity with how I was immediately fired from my counseling internship mental health job (see above), but it is representative of one of the many challenges facing the mental health worker trying to practice in a humanistic psychology context of relating to his/her clients.

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With regard to my client’s love of music, I was continually impressed with the very real sense of rhythm that he displayed in our drumming sessions, as when I kept our beat going with syncopated rhythms and truly lost myself in the process, he was very much in synch with me, and we were “cooking.” This drumming experience seemed to be something of a higher self experience for him, as in these precious moments he was no longer a moderately retarded Down’s syndrome client, but he was a human being experiencing the inherent joys of making music and feeling the life fulfilling rhythms of the universe. He greatly enjoyed moving his body to the rock and roll music we listened to on my car radio as we were riding along, singing in his hoarse incoherent voice that frequently brought joy and laughter to me in his presence. When I was on vacation or in a training workshop and couldn’t work with him, he would tell me that he missed me, and after working with him for a while he would ask me if I missed him as well. I once conveyed to him that my brother had died, and he was able to genuinely understand and feel my sadness. This young man became very special to me, and very much a part of my life. The time we spent together was very comfortable and fulfilling for both of us, and our relationship to me was a hallmark of humanistic psychology relating in a context that goes way beyond intellectual understanding. My client and I were both fortunate to have been involved in a humanistically oriented mental health agency that demonstrated an understanding and appreciation of my client’s needs and personality. When it was discovered that due to state regulations my client could no longer “work” his 2 days a week at my agency, consisting of between half an hour and an hour each day of taking out the garbage, taking the bottles to the recycling center, and watering the plants, my agency and his parents came up with a creative solution. His parents ended up consistently sending a weekly check to my agency so that my client was able to continue the parts of his “work” that was state allowed as long as he didn’t get paid. But my agency transformed my client’s check into a bona fide agency check, and my client still had his employee mailbox. As far as my client knew, he was still one of the “workers” at my agency, we still went there 2 days a week, he still went to the bank afterwards to cash his check and then on to McDonalds, and all was well. This to me was a prime example of an inspiring and effective way of pooling family and agency resources to maintain a humanistic way of relating to a client in spite of the obstacles that were presented by managed care and the state.

CONCLUSION In conclusion, the mental health worker and humanistic psychology are in a complicated relationship. From my experiences as a mental health worker, it is very clear to me that there is a rich source of opportunity to be engaged with clients in an authentic, real, and caring relationship that is the essence of humanistic psychology. On the other hand, mental health workers are continually saddled with many rules, regulations, and restrictions by both their mental health agencies and the state, which seriously threaten and interfere with this potentially humanistic way of relating to their clients. In my own mental health work I have worked through ethical deliberations on a number of occasions, and I was fortunate to be working for one agency that had an essentially humanistic orientation, and at another agency

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where I had a direct supervisor with a humanistic perspective in relating to both her staff and clients. However, many mental health workers are not as fortunate as I was in this regard, and even with all the humanistic supports and understanding that I experienced at my agencies, I also learned how tenuous and exceedingly difficult it can be to maintain a humanistic perspective of relating to clients in these modern times. I learned from firsthand experience that a mental health worker who wants to relate to his/her clients in a humanistic psychology context needs to proceed with the utmost caution and skill, walking the tightrope between humanistic relating and the rules and requirements of his/her mental health agency and the state. I believe this can be accomplished, but that it will require a concerted effort to teach these skills to mental health workers who have this desire. I view my own monthly training workshops that I facilitated for a year at one of my agencies as a modest step in this direction. I taught about the established dangers of an excessive use of psychiatric medications, the conflicts of interest for psychiatrists and the pressures exerted upon them by large pharmaceutical companies, and an alternative viewpoint in relation to Asperger’s Syndrome, Bipolar Disorder, and mental disturbance in general, involving creative potential in its most positive aspects. I also offered my fellow mental health workers an educational atmosphere involving safe, confidential, open-ended discussions of various ethical dilemmas that included an opportunity to share what was currently going on for them in regard to ethical issues they faced in their day-to-day work with clients. This turned out to be an enriching engagement for me as well, and it was one where my advanced educational qualifications were acknowledged and respected by my agency administrators, as having a PhD was attractive to my agency and the state in regard to me offering these trainings (even a PhD in mathematics). However, it was also the case that due to budget concerns my trainings were eventually put on hold, as fulltime in-house staff temporarily took over all trainings. Eventually I was allowed to continue my trainings, though soon my job ended due to the conflicts with my client’s mother that I described above. The budget constraints that put my workshops on hold is another example of the challenging scenario of trying to practice humanistic psychology, and in this case humanistic education as well, in the harsh day-to-day realities of our current mental health system. However, I believe my trainings were a creative channel for me in which humanistic psychology filtered through, whether or not it was known by that name. Perhaps offering these kinds of training workshops at mental health agencies may be a way that others who have the necessary educational requirements can take advantage of. From what I experienced, it is highly unusual for anyone with a PhD, or even a Masters degree, to be working as an ordinary mental health worker for a mental health agency. But the opportunity to experience a client’s world in his/her own home and community for 8+ hours a week is rich with therapeutic potential that is way beyond what one can learn from a client through a weekly 1hour office visit, or even a weekly 1-hour visit in the client’s home, where the problem behaviors may very well not be seen, and the natural ongoing relationship over time between client and mental health worker is not experienced. It is also work that I continually found to be refreshingly “human” and rejuvenating, although quite challenging as well. Perhaps it may be work that others like me who are near retirement age and have a humanistic psychology perspective along with higher degrees may want to consider. Perhaps we can form a network

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of mental health workers or former mental health workers with a humanistic psychology background and perspective who have Masters degrees and PhDs; but then again perhaps I am dreaming. At any rate, I believe that this kind of concerted effort is most definitely warranted, as from my own experience as a mental health worker I have found that there is a large network of mental health workers who very much want to work with their clients in an empathic, authentic, and real way; i.e. in a humanistic psychology context of relating.. In the past year and a half since my mental health worker jobs ended, I have completed my PhD psychology degree, and returned to Academia in full gear, teaching various oncampus and online courses in psychology and online courses in mathematics, and recently I got promoted to the position of Transpersonal Psychology Director at Akamai University. I now find myself in the position of supervising students in various stages of their education in psychology, including overseeing their experiences in the community in psychology, ranging from service-learning projects to Masters theses to Doctoral dissertations. I make a strong humanistic psychology presentation in all my psychology on-campus classes and with all my psychology online students, and I believe that I have been quite effective in getting the humanistic psychology message out there to my students. In my new role as Transpersonal Psychology Director, I have made a concerted effort to include humanistic psychology as a required part of the transpersonal psychology curriculum at Akamai University for all transpersonal psychology students (see www.akamaiuniversity.us). I feel good about my continued work in the field of humanistic psychology, but I also know that it is largely because of the more than three years of “ordinary” mental health work in the community that I experienced in late life that I am now able to effectively promote humanistic psychology in the context of mental health work in Academia. I miss my mental health work, and I frequently dream about my developmentally disabled client, reliving the conflicts and frustrations I experienced with his mother while I was trying so hard to keep my job and continue working with him. However, I realize that it has been my path to return to Academia, and I have accepted this; but I will be eternally grateful for the opportunity that I have been given to experience the challenges and the joys of bringing humanistic psychology into the job of the mental health worker. I intend to continue to do what I am able to in this endeavor—from the positions I now have in the academic world.

REFERENCES Alsup, R. (2008). Existentialism of personalism: A Native American perspective. In K. J. Schneider (Ed.), Existential-integrative psychotherapy (pp. 121-128). New York: Routledge. American Counseling Association. (1995). Code of ethics and standards of practice (rev. ed.). Alexandria, VA: Author. American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders (4th ed., text revision). Washington, DC: Author. American Psychological Association Statement (2005). Policy statement on evidence-based practices in psychology. Retrieved January 19, 2010, from http://www.apa.org/practice/ resources/evidence/ebpstatement.pdf

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American Psychological Association (2009). 117th convention: August 6 – 9, 2009: Convention program. Washington, DC: Author. Baron-Cohen, S. (2000). Autism: Deficits in folk psychology exist along superiority in folk physics. In S. Baron-Cohen, H. Tager-Flusberg, and D. Cohen (eds.), Understanding other minds. Oxford, U.K.: Oxford University Press. Baughman, F., with Hovey, C. (2006). The ADHD fraud: How psychiatry makes patients out of normal children. Oxford, UK: Trafford. Benjamin, E. (1993). Numberama: Recreational Number Theory in the school system. Swanville, ME: Natural Dimension Publications. Benjamin, E. (2004). On neopaganism. PagaNet News, 12. Benjamin, E. (2008a). The person vs. the pill. AHP Perspective, February/March, 23-25. Benjamin, E. (2008b). Art and mental disturbance. Journal of Humanistic Psychology, 48(1), 61-88. Benjamin, E. (2009). Artistic psychology, mathematical giftedness, and mental disturbance in children. Unpublished manuscript. Benjamin, E. (2012). An experiential exploration of life after death through the ostensible communications of mediums with deceased persons. Available from ProQuest Dissertations and Thesis Database. Saybrook University, San Francisco. Bohart, A., and Tallman, K. (1999). How clients make therapy work: The process of active self-healing. Washington, DC: American Psychological Association. Breggin, P. (2008). Medication madness: A psychiatrist exposes the dangers of mood altering drugs. New York.: St. Martin’s Press. Bradley, M. Z. (1983). The mists of Avalon. New York: Knopf. Buber, M. (1970). I and thou. (W. Kaufman, Trans.). New York: Scribner. (Original work published 1923) Camic, P. M., Rhodes, J. E., and Yardley, L. (2003). Qualitative research in psychology: Expanding perspectives in methodology and design. Washington, DC; American Psychological Association. Chang, R. T. (2008). Autoethnography as method (Developing autoethnographic inquiry). Walnut Creek, CA: Left Coast Press. Degrandpre, R. (2000). Ritalin nation: Rapid fire culture and transformation of human consciousness. New York: Norton. Elkins, D. (2007). Empirically supported treatments: The deconstruction of a myth. Journal of Humanistic Psychology, 47(4), 474-500. Elkins, D. (2008). Short-term linear approaches to psychotherapy: What we now know. Journal of Humanistic Psychology, 48(3), 413-431. Elkins, D. (2009a). The medical model in psychotherapy: Its limitations and failures. Journal of Humanistic Psychology, 49(1), 66-84. Elkins, D. (2009b). Why humanistic psychology lost its power and influence in Amercian psychology: Implications for advancing humanistic psychology. Journal of Humanistic Psychology, 49(3), 267-291. Ellis, C. (2009). Revision: Autoethnographic reflections if life and work (Writing Lives). Walnut Creek, CA: Left Coast Press. Feinstein, D., and Krippner, S. (1997). The mythic path. New York: Tarcher. Fitzgerald, M. (2004). Autism and creativity. New York: Brunner-Routledge.

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Fitzgerald, M. (2005). The genesis of artistic creativity: Asperger’s syndrome and the arts. Philadelphia: Jessica Kingsley. Grof, S. (1985). Beyond the brain. Birth, death, and transcendence in psychotherapy. Albany: State University of New York Press. Hayes, S., Strousahl, K. and Wilson, K. (1999). Acceptance and Commitment Therapy: An experiential approach to behavior change. New York: Guildford. Healey, D. (2002). The creation of psychopharmacology. Cambridge, MA: Harvard University Press. Hinman, L. M. (2008). Ethics: A pluralistic approach to moral theory (4th ed.). Belmont, CA: Thomson Wadsworth. Jamison, K.R. (1993). Touched with fire: Manic-depressive illness and the artistic temperament. New York: Free Press. Jung, C. G. (1961). Modern man in search of a soul. New York: Harcourt Brace. Kearney, A. J. (2008). Understanding Applied Behavioral Analysis. London: Jessica Kingsley. Krippner, S. (1975). Song of the siren: A parapsychological odyssey. New York: Harper and Row. Laing. R.D. (1967). The politics of experience. New York: Ballantine. Lukoff, D. (1988). Transpersonal psychotherapy with a manic-depressive artist. Journal of Transpersonal Psychology, 20(1), 10-20. Maslow, A. H. (1971). The farther reaches of human nature. New York: Penguin. May, R. (1969). Love and will. New York: Dell. McQuade, A. (2006). Revisiting the interiors: Serving the mentally ill living in the streets. AQAL: Journal of Integral Theory and Practice, 1(4), 116-150. Retrieved March 1, 2009, from http://aqualjournal.integralinstitute.org/public/Issues/aspx Miller, I. J. (1994). What managed care is doing to outpatient mental health: A look behind the veil of secrecy. Boulder, CO: Boulder Psychotherapists’ Press. Miller, I. J. (1996). Time-limited brief therapy has gone too far: The result is invisible rationing. Professional Psychology: Research and Practice, 27, 567-576. Moustakas, C. (1990). Heuristic research. Design, methodology, and applications. Thousand Oaks, CA: Sage. Moustakas, C. (1994). Phenomenological research methods. Thousand Oaks, CA: Sage. Neill, A. S. (1960). Summerhill: A radical approach to childrearing. New York: Hart. Panter, B., Panter, M. L., Virshup, E., and Virshup, B. (eds.). (1995). Creativity and madness: Psychological studies of art and artists. Burbank, CA: Aimed. Richards, R. (2000-2001). Creativity and the schizophrenia spectrum: More and more Interesting. Creativity Research Journal, 13(1), 111-132. Rogers, C. R. (1961). On becoming a person. Boston: Houghton Mifflin. Rogers, C. R. (1969). Freedom to learn. Columbus, OH: Merill. Runco, M., and Richards, R. (eds.). (1997). Eminent creativity, everyday creativity, and health. London: Ablex. Schneider, K. J., Bugental, J. F. T., and Pierson, J. F. (eds.). (2001). The handbook of humanistic psychology: Leading edges in theory, research, and practice. London: Sage. Schneider, K. J. (ed.). (2008). Existential-integrative psychotherapy. New York: Routledge. Scotton, B. W., Chinon, A. B., and Battista, J. R. (1996). Textbook of transpersonal psychiatry. New York: Basic.

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Sela-Smith, S. (2002). Heuristic research: A review and critique of Moustakas’ method. Journal of Humanistic Psychology, 42(3), 53-58. Szasz, T. (1974). The myth of mental illness. New York: HarperCollins. Tart, C. T. (ed.). (1975). Transpersonal psychologies: Perspectives on the mind from seven great spiritual traditions. New York: Harper and Row. Wampold, B. E. (2001). The great psychotherapy debate: Models, methods, and findings. Mahwah, NJ: Lawrence Erlbaum. Watkins, J. C., and Bohart, A. (2001). Humanistic-existential therapies in the era of managed care. In K. J. Schneider, J. F. T. Bugental, and J. F. Pierson (eds.), The handbook of humanistic psychology: Leading edges in theory, research, and practice. London: Sage. Webb, J. T., Amend, E. R., Webb, N. E., Goerss, J. Beljan, P., and Olenchak, F. R. (2005). Misdiagnosis and dual diagnoses of gifted children and adults: ADHD, bipolar, OCD, Asperger’s, depression, and other disorders. Scottsdale, AZ: Great Potential Press. Wilber, K. (1995). Sex, ecology, and spirituality. Boston: Shambhala.

Bio for Elliot Benjamin Elliot Benjamin has a PhD in mathematics from the University of Maine, and a PhD in psychology from Saybrook University with a concentration in Consciousness and Spirituality. He is the director of the Transpersonal Psychology Program at Akamai University, and teaches psychology at various locations, both on-campus and online, as well as teaching mathematics online. Dr. Benjamin was a mathematics professor for 21 years, and has published over 85 articles in the fields of humanistic and transpersonal psychology, spirituality and awareness of cult dangers, creative art and mental disturbance, progressive politics, pure mathematics, and mathematics enrichment. His most recent book, entitled Modern Religions: An Experiential Analysis and Exposé, is currently available at www.lulu.com, Dr. Benjamin lives in Maine and enjoys playing the piano, tennis, and ballroom dancing.

In: Advances in Psychology Research. Volume 96 Editor: Alexandra M. Columbus

ISBN: 978-1-62417-250-2 © 2013 Nova Science Publishers, Inc.

Chapter 4

INEFFICIENT NEURAL CONTROL OF ATTENTION IN ADOLESCENT CHRONIC CANNABIS ABUSE Yalchin Abdullaev* University of Oregon, and Pioneer Pacific College, US

ABSTRACT Control of attention is a key mechanism underlying behavior regulation. This chapter details the aspects of attention, language, and movement functions in terms of their underlying brain activity that covary with the chronic use of cannabis throughout adolescence. We compare task performance and brain activation differences in tasks involving attention, language, and movement between young adults with a history of chronic cannabis use during adolescence and matched non-user control subjects. Two tasks were used to activate attention networks: the Attention Network Task (ANT) and the use generation task. In the ANT, subjects responded to a left- or right-pointing central arrow which was surrounded by 4 arrows pointing in the same (congruent condition: →→→→→) or opposite (incongruent condition: →→←→→) direction by pressing one of the two buttons under their left or right thumb. Other conditions of ANT mapped alerting and orienting components of attention by using central or peripheral cues preceding the target. Chronic users differ from control subjects in showing poorer performance (longer reaction time and more errors) on tasks requiring processing of incongruent stimuli reflecting the executive attention network, but not in networks related to alerting or orienting components of attention in the ANT. Functional MRI of brain activity shows stronger activation within the right prefrontal cortex in chronic users compared to the control group specifically on ANT trials requiring executive attention. The use generation task also reveals significantly stronger activation of the same right prefrontal area in users compared to controls. These results suggest that chronic cannabis users develop less efficient executive attention in conflict resolution tasks, demanding more activation in the right prefrontal areas to resolve conflict. Aspects of brain activity related to motor output (button press in the ANT) demonstrates that chronic users seem to activate ipsilateral primary motor cortex as well in addition to the expected strong *

Please send correspondence to: Yalchin Abdullaev, MD, PhD. Lewis Center for Neuroimaging, Department of Psychology, University of Oregon, Eugene, OR 97403, USA. E-mail: [email protected].

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Yalchin Abdullaev contralateral primary motor cortex. Significantly stronger ipsilateral primary motor cortex activation in cannabis users may indicate the presence of pathological mirror movements, when the unintended hand passively mirrors the movement of the intended hand. This developmentally normal phenomenon usually disappears in childhood, and is considered developmental pathology if persists beyond the age of 10.

Keywords: Attention, conflict resolution, mirror movements, functional MRI, cannabis, right prefrontal cortex, substance abuse

INTRODUCTION Cannabis is the most frequently abused illicit drug both within the general population and among adolescents at the 8th-12th-grade school level [Johnston et al., 2008]. Adolescence is also a period of intensive development and neural maturation of brain regions in charge of higher cognitive functions and behavior, including the frontal lobe circuitry [Gogtay et al., 2004], which in turn is correlated with brain maturation and progress in intelligent activity [Shaw et al., 2006]. The high prevalence of cannabis use during this sensitive period in adolescence raises questions about possible negative impacts of cannabis on the underlying neurocognitive systems such as the attention networks. Attention is a key cognitive function for controlling many cognitive functions and behavior [Posner & Petersen, 1990; 2012; Posner & Raichle, 1997; Posner & Rothbart, 2007; Posner, 2012; Abdullaev & Posner, 2009; Aston-Jones et al., 1999]. Difficulties in attention have been associated with a number of negative outcomes during childhood and adolescence [Rothbart & Posner, 2001; Dishion & Connell, 2006]. Attention difficulties [Gardner et al., 2006; Salo et al., 2011] and smaller orbitofrontal cortex volumes [Cheetham et al., 2012] may accompany use of cannabis, tobacco and other drugs in early adolescence, and cannabis abuse may undermine the development of cognitive networks in adolescence [Meier et al., 2012]. In this chapter we review our recent functional magnetic resonance imaging (fMRI) studies in two attention tasks that compared a group of subjects with repeated, longitudinal reports of cannabis use throughout the adolescence with a demographically matched control group. Several previous studies have examined the neural and cognitive patterns associated with acute and chronic use of cannabis [Lundqvist, 2005; Bava & Tapert, 2010]. There are studies that show a number of cognitive impairments related to chronic cannabis use [Croft et al., 2001; Bava & Tapert, 2010; Meier et al., 2012], including increased future risk for early psychotic episodes and schizophrenia [Allebeck et al., 1993; Linszen et al., 1994; Van Mastrigt et al., 2004; Veen et al., 2004; Barnes et al., 2006; Mauri et al., 2006; Moore et al., 2007; Compton et al., 2009]. Some forms of cannabis may cause acute psychosis leading to violent crimes in susceptible individuals [Chlebowski & Leonard, 2012]. There are also studies which do not detect significant behavioral deficits associated with cannabis use, but show changes in the brain activations [Quickfall & Crockford, 2006; Hardling et al., 2012]. These changes often involve prefrontal or limbic regions including the anterior cingulate cortex. A number of studies have shown reduced activation in attention-related brain areas that lasts beyond the period of acute use [Schwartz et al., 1989; Pope et al., 2001; Bolla et al., 2002, 2005; Eldreth et al., 2005]. These effects show similarity to those found in attention deficits and cerebral regional blood flow changes observed during acute use [Pope &

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Yurgelin-Todd, 1996; O'Leary et al., 2002; Jacobus et al., 2012]. However, the particular brain areas involved and the direction of the difference between users and controls are still not clear. Also, the brain imaging studies (including our present work) look at correlations of cannabis use with task performance and brain activity, and do not reveal the cause-effect relationship. One reason for the complex and sometimes contradictory results found in previous studies of cannabis users may be that specific tasks used to assess attention rely on different neural systems. The Attention Network Task (ANT) [Fan et al., 2005; Abdullaev et al., 2010] is designed to separate activity of three basic facets of attention including alertness, orienting to visual stimuli and executive control. The task allows the determination of attention networks, which are likely to differ between cannabis users and control subjects. However, the ANT is a simple task, requiring only a key press in the direction of an arrow and producing very few errors. Thus it is challenging to detect individual differences in performance on the ANT, and moreover, completion of the ANT requires little effort. A more difficult task that involves the same executive attention network, but is entirely different in surface properties, requires the person to generate a use for a series of visually presented nouns [Posner et al., 1988; Petersen et al., 1988; 1989; Rachle, 1994; Raichle et al., 1994; Posner & Raichle, 1997; Caplan et al., 1999; Chiarello et al., 2006]. Subjects view a rapid (e.g., every 1.5 s) presentation of single nouns on the computer monitor one word at a time. In one block, their task is just to read the words. In the second block they generate a use for each noun of the same word list as fast as possible (e.g., hammer – pound, broom – sweep). This task is more difficult than ANT. Comparison of the use generation to the reading task usually produces a strong anterior cingulate activation related to the executive attention, among other regions [Carter et al., 1999]. We applied both the ANT and the use generation task to activate the executive attention network by two quite different methods. The ability to override a prepotent response by use of attention control is the defining characteristic of the executive function. The executive brain network has been associated with the ability to select and manage attention demands in high-level information processing tasks where there is a conflict between different stimuli or responses. This network is also related to many aspects of self-regulation during child and adolescent development [Rothbart & Posner, 2001]. Due to the difficulty drug users have in self-regulation [Wills & Dishion, 2004] and based on the previous results with the conflict effect [Gruber & Yurgelin-Todd, 2005], we hypothesized that chronic cannabis users would differ from normal controls mainly in the operation of this network [Abdullaev et al., 2010]. Subjects in the ANT experiment were 14 cannabis users (4 females, mean age 19.5 yrs, SD = 0.8) and 14 normal control subjects (4 females, mean age 19.7 yrs, SD = 1.4). There was no statistically significant difference between the ages of the two groups. The use generation task was added later in the study, and 7 users (1 female, mean age 19.6 yrs, SD = 0.9) and 7 normal controls (2 females, mean age 20 yrs, SD = 0.2) of the above sample participated. Details of subjects are described elsewhere [Abdullaev et al., 2010]. The first 7 users and 7 controls were recruited from the Project Alliance study, which included about one thousand cannabis users in Portland, Oregon [Dishion & Kavanagh, 2005], and the last 7 users and 7 controls were added through local advertisements in Eugene, Oregon. In the Project Alliance sample, all subjects reported on their cannabis and every other drug use yearly from age 12 through 18. Thus, this sample provided an opportunity to select heavy cannabis users with no significant alcohol or other drug use, which is relatively rare in

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drug abuse studies. The average age of onset of cannabis use in our sample was 14.7 (range 12-16), with average use of 132 days/year (range 71-196 days/year) for an average length of 5.1 years (range 4-7 years). Any subject reporting any cannabis use was excluded from the control group. Alcohol use was allowed within 1-2 days/week and did not differ between the cannabis users and control groups. Subjects were excluded if they reported more alcohol use. Subjects were also excluded if they reported using other drugs more than 4 times a year. Thus, selection of the cannabis users from very large sample allowed us to selectively choose only those subjects not using any other drugs except cannabis. This assured that there was no difference between groups in usage of other drugs. The subjects agreed not to use cannabis at least 48 hours before the fMRI scan or consume tobacco or caffeinated beverages on the day of the scan. Lack of substance use was confirmed with the urine drug screen in the MRI scan day in the first 7 subjects, and was based on self-report in the second group of 7 subjects. Urine samples were collected during the visit for the MRI scan and were sent to a commercial clinical laboratory for comprehensive drug screen. Additional three subjects from the user group and five subjects from the control group were excluded from the analysis because of excessive head movements in the fMRI data. Each subject had 5 runs of the ANT experiment with 48 trials in each run (see details below). Within the remaining 14 subjects in the user group, two subjects had 2 of the 5 ANT runs excluded from analysis for excessive head movements. With the 14 subjects of the control group, 53 out of 70 total runs of ANT were analyzed as 17 runs were excluded for excessive head movements. As a result, the user group had 14 subjects with 66 runs of the ANT, and the control group had 14 subjects with 53 runs of ANT.

ATTENTION NETWORK TEST (ANT) In the ANT, we used two target (congruent and incongruent) and three cue conditions (Central cue, Spatial cue, and No-cue) (Figure 1). Each target consisted of five arrows presented above or below the fixation point, pointing in the same left or right direction (→→→→→ or ←←←←←) in the congruent condition (50% of trials). In the incongruent condition (remaining 50% of trials), the central arrow pointed in the direction opposite to the four surrounding arrows (→→←→→ or ←←→←←). Subjects were instructed to look at the central plus sign, and had to shift their attention from the central plus sign to the target stimulus in each trial to determine the correct response. There were three warning conditions to introduce the alerting and orienting components of attention: Center-cue (alerting, temporally informative), Spatial-cue (alerting plus spatially orienting, both temporally and spatially informative), and No-cue (used as a baseline for the remaining two conditions). A third of all trials had a central cue, a third had a spatial cue, and a third did not have any cue (No-cue condition). The central cue was an asterisk (*) replacing the fixation point at the center of the monitor for 150 ms, and the spatial cue was an asterisk presented for 150 ms either above or below the fixation point. Spatial cues predicted the target location with 100% certainty, i.e. if in a given trial the spatial cue was presented above the fixation, then the 5arrow target was also presented at the same spot above the fixation point. Participants were asked to look at the central fixation point and press the left button with the left thumb if central arrow pointed to the left, and press the right button with the right thumb if the central

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arrow pointed to the right (Figure 1). To introduce the spatial orienting component of attention, the targets were presented either slightly above or below the central fixation point. Thus the subject had to shift the spatial attention from the central fixation point to the target location before responding. In the ANT, we used an event-related fMRI design with a pseudorandom (predetermined unpredictable) order of different targets and cues within a block [Buckner et al., 1996] with the same interstimulus and intertrial intervals used in the previous ANT study [Fan et al., 2005]. The plus sign remained on the center of the screen, and was only replaced for 150 ms by an asterisk in the trials of the Central-cue condition. The target stimulus followed after a variable interval [Abdullaev et al., 2010]. Five runs of ANT were presented, and each run had 48 trials with a different pseudorandom (predetermined unpredictable) order of conditions and intervals. The six trial types (3 cue conditions by 2 target conditions) followed each other equally often. Responses were recorded with two buttons on an MRI-compatible button box. Reaction times (RT) were measured from the target onset to the button press. The percent of errors was computed as a measure of accuracy. These were averaged for each subject and for each task condition. Repeated-measures analyses of variance (ANOVAs) were run for each attention network with condition (e.g., incongruent and congruent) and group (cannabis users and control subjects) factors. Significant main effects and interactions were followed by pairwise comparisons using t-test statistics. The three attentional networks for the behavioral analysis were defined as follows to produce a positive score: Alerting effect = RT No-cue – RT Center-cue Orienting effect = RT Center-cue – RT Spatial-cue Conflict effect = RT Incongruent – RT Congruent

Figure 1. Schematic description of the attention network test (ANT) [Fan et al., 2005].

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In the fMRI data, we looked at the brain activity related to the target stimuli. Four cue types preceding the target (no cue, central cue, spatial cue up, or spatial cue down), two target positions (up or down relative to the central plus sign), two target congruency types (congruent or incongruent), and two target directions (central arrow pointing left or right) created 24 target types. Each of the 24 types of stimuli was modeled in the fMRI analysis. The brain activity related to the alerting network of attention was isolated by statistical comparison of the Center-cue condition (including all target stimuli following the Center cue) to the No-cue condition (including all the target stimuli without any preceding cue). The remaining target types (incongruent, congruent, left, right, up, or down) were equally distributed between these two conditions, and the only difference was that in the Center-cue condition the target stimulus followed a central cue stimulus providing information on when the target will occur. Note that this Center-cue-vs-No-Cue comparison in fMRI data is the opposite of the subtraction used in the behavioral data, but both subtractions isolate the same alerting component of attention in the fMRI and behavioral data respectively. Brain activity related to the orienting network of attention was isolated by statistically comparing the Spatial-cue condition to the Center-cue condition. Again the remaining target types were equally distributed between the two conditions, and the only difference was that the spatial cue preceding the target provided additional information about the future location of the target. Note that this Spatial-cue-vs-Central-cue comparison is again opposite to the behavioral analysis where we subtracted the RTs of the Spatial-cue condition from the slower RTs of the Center-cue condition. In the fMRI data, however, the opposite subtraction was aimed to isolate brain regions demonstrating stronger activation in response to the spatial cue. Finally, the same incongruent-vs-congruent comparison was used to isolate the executive attention network in both the behavioral and fMRI data. Before conducting all these taskrelated comparisons in the fMRI data, we looked at the Left-vs-Right (and the reverse Rightvs-Left) contrast comparing the trials where a target was an arrow pointing to the left and left hand button press was used as a response to the trials where the target was an arrow pointing to the right and the right hand button press was used. All other task conditions and stimulus types (congruent, incongruent, up, down, cue types) were equally distributed between these Left and Right conditions, allowing us to verify the correctness of the entire data acquisition, conversion and analysis pipeline. We expected that with each hand button press, we should see the ipsilateral cerebellum and the contralateral primary motor cortex activation. In the process of this verification, we discovered an inadvertent left-right hemisphere switch in the code of the MRIConvert program, it was reported to programmers and fixed, helping several labs with upcoming publications. The final results demonstrated significant contralateral primary motor cortex and the ipsilateral cerebellum activation with each hand use (Figure 10). Next, we conducted the second verification, comparing Up-vs-Down (and the reverse Downvs-Up) contrast. Targets were presented above the fixation point in 50% of trials, and below the fixation point in the remaining 50% of trials. All other conditions and stimulus types (incongruent, congruent, left, right, cue types) were equally distributed between the Up and Down conditions. As expected, the only significant activations in this comparison were found in the primary visual cortex. The Up-vs-Down contrast showed that stimuli presented above the fixation point in the visual field activated part of the visual cortex below the calcarine fissure. And as expected in the Down-vs-Up contrast, the target stimuli presented below the fixation point in the visual field activated part of the visual cortex above the calcarine fissure (Figure 9).

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THE USE GENERATION TASK In the use generation task, stimuli consisted of a list of 100 nouns [Abdullaev & Posner, 1998; Abdullaev et al., 2002]. Based on the table of most frequently generated responses to each word (available in Abdullaev & Posner, 1998, page 12), we divided the word list into two equal parts: (1) 50 easy words, which had one dominant response generated by the majority of subjects, and (2) 50 more difficult words, for which there were several different common responses chosen by subjects. Each of these two lists was used for the use generation and for the passive reading task. In each trial, a randomly picked word from the list replaced the fixation point on the center of a computer monitor for 150 ms. All 100 words were displayed in a blocked design with a fixed interstimulus interval of 1.5 s. A set of easy and difficult words were presented separately within a block with a 6 s delay between them. The order of presentation of easy and difficult words within a block was counterbalanced across subjects. Each word was presented once within a block. This block was repeated twice. In the first block, the subject’s task was to read each word silently (the reading task). In the second block, the subjects saw the same words (in a different random order), and their task was to silently think of a use for each word (e.g., hammer – pound; broom – sweep). All subjects received the same task instructions in a written form and carried out 30 practice trials before the experiment with a different set of words. In each block and for each subject, words were presented in a new random order. Details of the experiments are provided elsewhere [Abdullaev et al., 2010].

FUNCTIONAL MRI (FMRI) Each brain imaging session included a 46 s auto-alignment scan that automatically oriented any subsequent acquisition independent of the position of the head to assure optimal coverage for each subject and consistency across subjects. A true FISP 3-plane multiple slice scout was run next for 63 s. For functional MRI, the EP2D-BOLD (Blood oxygen level dependent) sequence was run with TR = 2000 ms, TE = 30 ms, flip angle = 80 degrees, Field of View (FOV) = 200 mm, 64 x 64 matrix, spectral fat saturation, bandwidth = 2604. The whole brain was covered with 32 contiguous 4 mm thick slices acquired in interleaved ascending manner. Steady state was established by the scanner running 2 TRs prior to any image acquisition or optical trigger pulse. Each EP2D_BOLD sequence of ANT lasted about 9 min and delivered 48 ANT trials. This was repeated five times to collect five runs of ANT data. Structural MRI scan was run between the third and fourth ANT runs. For the structural scan, the 3D Magnetization Prepared Rapid (modified inversion recovery) Gradient Echo (MPRAGE) TR = 2500 ms, TE = 4.38 ms, TI = 1100, flip angle = 8 degrees, FOV = 256, 160 slices, 130 Hz bandwidth was run for 8 min to acquire T1 weighted 1 mm3 resolution anatomical images with optimized gray-white matter contrast. In the last 14 subjects (7 cannabis users and 7 controls), another EP2D-BOLD sequence was run for 6 min at the end to collect the use generation data. Identical center slice location and angulation with respect to the functional acquisition allowed optimal co-registration. All MRI scanning parameters were identical for both tasks. We kept acceptable head motion under 1 mm.

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Statistical analysis based on the General Linear Modeling (GLM) was used for fMRI data analysis as implemented in the FSL (FMRIB Software Library). All fMRI data were analyzed using FEAT (FMRIB Expert Analysis Tool) available as part of FSL (freely available at www.fmrib.ox.ac.uk/fsl) [Smith et al., 2004; Beckmann et al., 2006]. Preprocessing included separating images of brain from the rest of the images of the head tissue using the Brain Extraction Tool (BET) [Smith, 2002], pre-whitening for local autocorrelation correction using FILM (FMRIB Improved Linear Model) [Woolrich et al., 2002], motion correction based on rigid-body transformations using MCFLIRT (Motion Correction FMRIB Linear Image Registration Tool) [Jenkinson et al., 2002], spatial smoothing using a Gaussian kernel of 6 mm full width at half maximum (FWHM), mean-based intensity normalization of all volumes by the same factor, a high-pass temporal filtering (Gaussian-weighted LSF straight line fitting, with sigma = 100 s) as implemented in FSL [Smith et al., 2004; Beckmann et al., 2006]. The model was convolved with double-gamma basis functions to account for delays and undershoots in the hemodynamic response. Modeled regressors were targets in ANT and words in the use generation task. Explanatory variables were created by convolving the stimulus onset times within each task condition with a standard double gamma hemodynamic response function using FSL’s FEAT tool. GLM analysis conducted a multiple linear regression analysis to obtain hemodynamic parameter estimates for each explanatory variable and statistical maps were created for the task-related contrasts (e.g., Incongruent-vsCongruent, Spatial-cue-vs-Central-cue, Central-cue-vs-No-cue in ANT, Use generation-vsReading in the use generation task, etc.) using a fixed effects analysis. In the use generation task, we also had a 30 s baseline period in front of each block with no stimuli except a central plus sign for fixation. Each condition of the task was also compared to the baseline period to verify the directionality of the differences in the above contrasts. For the ANT task, we did use a baseline period in a previous study comparing the PTSD patients to matched control subjects [Leskin et al., 2007] and found that the congruent condition never caused stronger activation than the incongruent condition. Even though the null events and baseline condition can be added after the fact, the present ANT study never presented a need for that. Specific comparisons of interest were done using GLM for all individual runs, separately for each subject group, and for between-group comparisons using a fixed-effect model with clusterlevel statistical threshold of Z > 2.3 (unless otherwise noted) and P < 0.05 corrected for multiple comparisons according to the Gaussian Random Fields [Worsley et al., 1992; Beckmann et al., 2003; Woolrich et al., 2004]. These contrast activation maps were registered to each subject’s own high-resolution structural image and then to the MNI 152-standard template using a 12-parameter affine registration by the FSL’s FLIRT tool. The high resolution structural MRI images of individual subjects standardized to the MNI space were averaged within each group to create an average structural template for the group using FSLVBM tools. These average structural brain images of our subjects are shown in all figures except Figure 9 which used the MNI_152 standard brain image. All images shown in the figures were flipped from FSL’s default radiological view to a neurological view so that in all figures the left hemisphere is shown on the left side. MNI coordinates were converted to Talairach space and were used to retrieve anatomical labels from the BrainMap database [Fox et al., 2005].

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BEHAVIORAL PERFORMANCE IN THE ANT The ANT allows a measure of the efficiency of three different attention networks. The reaction times (RT) for each cue and conflict condition and network scores are shown in Table 1.

Congruent

Alerting

Orienting

Executive

649 616 624 590

Incongruent

No Cue

610 587

Spatial Cue

Overall Users Control

Central Cue

Table 1. Mean Reaction Times (Standard Deviations) and attention network scores for users and controls in ANT (in milliseconds) [from Abdullaev et al., 2010]

562 546

655 (62) 619 (55)

566 (57) 553 (51)

33 34

54 44

89 66

Executive attention was measured as the difference in reaction times (RT) between incongruent and congruent conditions (Figure 1 and Table 1). The task in each condition was to press the left or right button to indicate the direction of the central arrow. This attention task is more demanding in the incongruent condition because of the flankers pointing in the opposite direction. All other factors (cue types, up or down location, left or right hand button press) were equally balanced between the incongruent and congruent conditions. We performed a two-way repeated measures ANOVA of RTs with group (cannabis users and controls) and congruency (incongruent and congruent conditions) as factors. The group main effect was not significant, F(1,26)=1.3, P=0.26. As expected, the congruency effect was quite large and statistically significant, F(1,26)=342.4, P