Young People's Play, Wellbeing and Learning: Psycho-Social and Virtual Geographies in Digital Play [1st ed.] 9783030600006, 9783030600013

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Young People’s Play, Wellbeing and Learning Psycho-Social and Virtual Geographies in Digital Play

Dimitra Hartas

Young People’s Play, Wellbeing and Learning

Dimitra Hartas

Young People’s Play, Wellbeing and Learning Psycho-Social and Virtual Geographies in Digital Play

Dimitra Hartas Centre for Education Studies University of Warwick Coventry, UK

ISBN 978-3-030-60000-6    ISBN 978-3-030-60001-3 (eBook) https://doi.org/10.1007/978-3-030-60001-3 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cover pattern © John Rawsterne/patternhead.com This Palgrave Pivot imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

Play is a cultural, social and gendered act situated within young people’s social reality. In the childhood literature, play is understood as an enjoyable activity that is spontaneous and voluntary with no extrinsic goals, an act that is not a means to an end but an end in itself. A fascinating aspect of children’s social development is the shift from family to peers that starts in late childhood and continues throughout the teenage years. With this the nature of play as activity, imagination and desire for connectedness also changes, becoming more enmeshed in peer interactions and friendships to support integration into social groups and form complex peer relations. In this book, play is understood loosely along the lines of peer interaction and group participation (online and offline) and play-based learning in pre- and mid-teenagers, with a focus on 14-year-olds in the UK.  Peer influence peaks in mid-adolescence where young people show a heightened desire for affiliation and become increasingly sensitive to social evaluation and comparison and their consequences for peer acceptance or rejection. An abundance of research evidence points to the fundamental importance of play for children’s social and emotional development and wellbeing (Pellegrini 2009). In the literature on play, free (unstructured) and guided (structured) are the two main types of play with each contributing differently to children’s learning and wellbeing. Free play involves unsupervised (or adult-free) play and appears to be particularly beneficial for social and socio-cognitive skills development and self-regulation in terms of supporting children to express emotions, follow social rules and apply social skills to solve conflict, all thought to support resilience. Unstructured v

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play has been linked to children’s mental and physical health, including promoting physical activity, mental wellbeing, and capacity for risk management and organisational skills (Whitebread 2017). Guided or structured play is also referred to as play-based learning, emphasising the use of play in promoting children’s learning. Another distinction in play is about its locality, outdoor and indoor play. Outdoor play, a form of unstructured play, is thought to be crucial for promoting healthy lifestyle and has been recently capitalised upon by numerous governments and public health campaigns to address concerns about child obesity. Outdoor spaces offer richer opportunities for play than indoor places with particular benefits for physical movement and exercise; mental wellbeing and restorative experiences; exploration, adventure, risk and independence; social bonds and rites of passage; imagination and aesthetic appreciation of the natural world, as well as the development of a sense of place and belonging (e.g., Lester and Maudsley 2007; Moss 2012). Research into the changing landscape of play has pointed to a decline in children’s independent use of outdoor space partly due to fears about traffic and ‘stranger danger’ but also because of rapid urbanisation and the widespread use of the internet (Alparone and Pacilli 2012; Holt et  al. 2013). As technology brings social and cultural changes, children’s play and peer interactions adapt to and reflect these changes. Technology has propelled a radical generational shift in young people’s experiences compared to their predecessors’. Today’s children and teenagers are different from previous generations in how they spend their time; they are the first cohort to have grown up with online social networking. Young people’s physical, cultural, social and virtual geographies are shifting with digital play becoming an inextricable part of their life. Children’s involvement with digital media and online gaming is increasingly seen as a form of play, as acts of creative interpretation of the real and imaginary and the development of social problem solving (Behrenshausen 2012), as a platform for social interactions and having fun (Buckingham and Sefton-Green 2003), or as a way of critically engaging with or even ‘subverting dominant values and showing agency’ (Hadley and Nenga 2004; Marsh and Richards 2013, 8). Digital play is about young people’s play and peer interactions mediated by technology. It is multidimensional and fluid because it is set against the rapid pace of technological innovation. The nature and cultural context of digital play are constantly changing, propelled by changes in technology and digital age. What we

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understood as digital play some years ago is different from what it is now. Through digital play, young people become active users of technologies and digital media content. In this book, I approached teenage engagement with social media as play and examined whether it replaces or complements play and peer interactions and friendships in the physical world. Rapid changes in the technology used by young people in digital play have given rise to many important questions regarding its short- and long-­ term effects on their learning and wellbeing but also on how they interact with their families and peers and develop social understanding. We live in the era of the ‘super-connected’ selves, but we do not understand what this means particularly for children and teenagers who are different in terms of disadvantage, disability, ethnicity or gender. Children’s personal agency in negotiating physical and virtual spaces and their effects on their wellbeing and learning are a fertile ground for debate and public policy. They are also a fertile ground for moral panic and increasing pressure to rapidly craft evidence-based policies to curb ‘harmful’ aspects of children’s digital encounters. Often, digital play is criticised in terms of depriving children from movement, negotiation and problem-solving skills in real situations, and for being a solitary experience. Virtual encounters are often seen as potentially toxic, influencing young people in an unmediated manner. Dominant discourses of childhood constitute children as active agents capable of meaning making and negotiating social understanding. As such, seeing children as passive recipients of culture and digital media who require adult support and supervision does not sit well with views of children as independent agents. We need to understand how and the extent to which systemic problems such as inequality, including gender inequality, relate to play and plight teenager’s life, especially girls.

What Is Virtual and What Is Real in Children’s Play? Virtual reality and virtual spaces have entered everyday conversations and are understood as cyberspaces different from ‘real’, material spaces and physical geographies. This juxtaposition denotes a separation between the ‘real’ and ‘virtual’ world, the latter seen as a collection of abstract artefacts and mental constructions. Virtual spaces evoke a sense of immateriality and impermanence, of social experiences of a different kind. And yet

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virtual geographies are not a product of imagination; they are ‘real’ spaces where young people interact with each other at home and school, in transit and workplaces, and these interactions form part of their life (often, the core of their life). Although technology mediated, these interactions are not less real than those occurring between humans in physical spaces. Our experiences of virtual and real worlds tend to be articulated along the binary language of real/virtual and physical/technological, denoting an opposition in these worlds. Technology does not sit outside the real world; it is part of it, shaping it and shaped by it. Young people experience social reality through a multitude of filters or lenses, through evocations of the natural world, tools and technology, literature, music and arts to mention but a few. These forms of experience are not in opposition with each other, nor are they mutually exclusive; they are all part of the fabric of social life. The boundaries between physical and virtual play and peer interactions are porous with young people moving between the virtual world and the physical world ‘as if one’ (Marsh 2010). Young people engage in complex online behaviours influenced by their social experiences in offline worlds. However, they do not just repeat these experiences but go a step further in ‘reconfiguring the representations of external realities’ (O’Mara and Laidlaw 2011, 35). Children and adolescents are simultaneously inside and outside of the imaginary virtual situations demonstrating a unique characteristic of digital play. This is because the themes of children’s digital play tend to be drawn from children’s everyday lives (Verenikina and Kervin 2011) and, conversely, children’s play in social and material situations draws upon their experiences in digital worlds. There seems to be a fuzziness, a conceptual blurring, between ‘physical’ and ‘virtual’ places that permeate each other, making digital play unique (Marsh 2010). Children create digital imaginary worlds where characters, story lines, objects and the rules of engagement are taken from their lived reality. Digital play is on a continuum of children’s play experiences enmeshed with or influenced by their physical play. Considering the multitude of technology-mediated social experiences, delineating the ways in which virtual reality and the digital world shape young people’s life is likely to be fraught with contradictions. There is no doubt technology is changing us and we need to grapple with the implications of this change. Digital play captures aspects of both real and virtual life, creating porous borderlands where children interact with each other and learn the rules of engagement often fraught with social and emotional

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challenges. The global reach of technologies has increased children’s visibility. Children from different geographies, cultures and social political contexts can interact and play with each other, challenging the existence of national boundaries. These global encounters bring to the fore new social experiences, behaviours and ways of communicating with each other that can enrich but also stretch young people’s coping mechanisms especially when interacting with others from different socioeconomic, spatial and cultural contexts, partly because these interactions often cannot be replicated in the social material world children occupy. Public consciousness conjures up new fears for young people. Risk discourses about the effects of digital play, social media in particular, on their wellbeing are in abundance and tend to be polarising. On the one hand, digital play is associated with violence, addiction, antisocial behaviour, passivity, obesity and overall poor physical health (Mustola et  al. 2018; Shin and Huh 2011), while on the other it shows ‘tech-savviness’ and is likely to help children to develop broader digital literacy skills (Mustola et al. 2018; Narine and Grimes 2009).These conversations reflect general worries about the ways in which technology changes society and perceptions of human nature and its effects on young people’s wellbeing and mental health. Large-scale surveillance, consensus resulting in self-­ censorious behaviour and the erosion of the boundaries between private and public life are legitimate worries. However, it is tempting to attribute mental ill health in young people to the presence of technology in their life and express moral panic rather than understand the ways in which societal changes interact with and are magnified by technology. What children do with their screen-based media ‘cannot be homogenised as a uniform or inevitably problematic activity’ (Blum-Rose and Livingstone 2017, 27). As with other technological advances, digital play, such as social media and gaming, offer a mirror to society to reflect the goodness in human nature but also social malaise, which can reach young people in direct and unmediated ways. Virtual encounters can enable and magnify social malaise, but they can also offer opportunities for socialisation and connectedness especially for marginalised young people.

About this Book In this book, I examined teenage structured (extra-curricular activities) and unstructured play (face-to-face interactions with friends and digital play). Digital play here refers to social and peer interactions mediated by

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digital devices, focusing on the frequency of these interactions and their associations with wellbeing and learning. I approached face-to-face peer interactions and digital play and their outcomes, including unintended outcomes, for young people’s learning behaviours and attitudes, educational aspirations and wellbeing through the lenses of social class, gender, ethnicity, disability and parenting. Much current research has focused on screen time alone as the unit of analysis with little consideration given to the kind and the social context of digital and face-to-face play. I hope to open up conversations about the socioeconomic and cultural milieu of face-to-face and digital play in teenagers by examining gender, poverty, ethnicity and disability. The quality of play and peer interactions is bound to be influenced by the structures of social class and families’ cultural capital which have been found to shape young people’s personal interests, relationships and autonomy. It could be that, depending on these structures, young people’s social, digital and learning networks enable or dis-­ empower them. Free, unstructured play is examined here through young people’s face-­ to-­face and online interactions with their peers, whereas guided play refers to extra-curricular activities organised by their parents to enhance social and cognitive skills and future employability. I examined both types of play, considering that face-to-face peer interactions are assumed to be in decline whereas online engagement (e.g., social media, gaming) has increasingly become dominant in young people’s social interactions in the twenty-first century. Free (digital and through interacting with friends in physical, material contexts) and guided play/extra-curricular activities are explored through the lenses of social class, gender, ethnicity and disability, drawing links between face-to-face and online interactions and teenagers’ wellbeing and learning within the social and cultural contexts of contemporary childhood and parenting cultures. Young people’s peer interactions, including digital play, are located within their wider socio-spatial contexts and experiences. They continue to shape and be shaped by the lives of their parents, peers, political and economic institutions and the wider culture. Institutions and culture are embedded and shaped by a digitalised environment that has the potential to magnify and transmit toxicity in the form of surveillance, early sexualisation, consumerism and misogyny, and reproduce inequality. Debates rage on the effects of young people’s use of social media and gaming in encouraging conformity, self-censorious attitudes and behaviours, and erosion in social trust, civic engagement and empathy. I have argued in a

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previous study that online social platforms have the potential to embolden social ills (manifested in the form of cyberbullying, everyday sexism, toxic upward comparisons) and promote inequality, including gender inequality, with girls being the ‘new high risk’ group (Hartas 2019). We know very little however about digital play and its association with teenagers’ wellbeing and learning attitudes and behaviours, and whether the frequency and types of online and offline engagement vary for young people who are different. A challenge for this book is to trek between adult anxiety and moral panic regarding digital play and what the data really tell us about young people socialising with each other online and offline. My goal is not to reach a consensus about the effects that face-to-face interactions, online gaming or social media use have on the lives of young people today but to understand how different groups of young people experience and derive meaning from face-to-face and digital play as well as extra-curricular activities. To this end, I investigated associations between face-to-face play and digital play, as well as extra-curricular activities in teenagers (i.e., 10–15-year-olds) and wellbeing, learning behaviours and school attitudes, and educational aspirations for typically developing young people but also for those who are different. Findings on face-to-face peer interactions, social media use, gaming and wellbeing are presented in the following chapters, revealing interesting trends about wellbeing, learning attitudes and aspirations and parenting especially for teenage girls as well as teenagers who are different. The findings emerging from the analyses in this book have interesting implications for debates about online and offline play. In studies on technology-­mediated play, the effects of social media use on wellbeing tend to be mixed. Social media can be a force for good and bad depending on how they are used individually but also collectively in their cumulative effects on society. I started this project by asking the following questions: Does digital play (a form of free play) relate to learning behaviours and social interactions with peers? Is it likely to enable a toxic social environment and reduced wellbeing in young people in the era of the ‘super-­ connected’ selves? Are there any associations between learning attitudes and behaviours and educational aspirations and teenagers’ face-to-face and virtual peer interactions? Do teenagers who interact with their peers’ face-­ to-­ face also interact online, or does one type of interaction replace the other?

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A novel aspect of this book is its exploration of current trends in both free and structured (parent-organised) play by drawing on data from national, longitudinal studies (i.e., MCS and Understanding Society) in the UK, particularly in relation to 10–15-year-olds’ wellbeing and learning behaviours and attitudes and educational aspirations. In so doing, I examined relationships between various forms of play (free and structured) and young people’s learning behaviours and attitudes as well as educational aspirations, rather than learning outcomes (e.g., academic achievement) per se. I hope to shed some light on holistic, less instrumental forms of play/peer interactions and young people’s attitudes to school, the behaviours they exhibit in class and the aspirations they have for the future. What makes this book distinctive is its evidence-based approach to free and guided play, especially for children whose childhoods and lived experiences are unequal by combining two distinct bodies of research on play. The first body focuses on the interplay between digital play and young people’s learning and wellbeing and the second on the relationship between digital play and traditional, face-to-face play and peer interactions. I brought these two strands together and examined them across young people’s socioeconomic, gendered, ethnic and social contexts by considering questions about social class, gender and difference and the role of parents in shaping (or conflating) play and learning. I also debated the nature of play and its various permutations, from a child-directed endeavour to an instrument towards meeting predetermined learning goals in an era of intensive parenting, taking an integrated approach that addresses both the learning and social/emotional needs of young people. Ultimately, the aim in this book was to look at teenage play as a continuum of social interactions and interrogate its relation to learning and wellbeing for typically developing teenagers but also those with disabilities (i.e., social emotional and behavioural difficulties) and disadvantage and its intersection with other markers of difference. Social media use and online gaming were measured along the hours young people spent on social networking sites and gaming and not in terms of patterns of usage, for example, active versus passive users, or users who engage actively in debates and socialising versus those who follow others digitally. So, while I could not examine differences between active and passive usage, I differentiated between using social media and gaming and their associations with self-reported feelings of connectedness and wellbeing as well as learning behaviours and attitudes. I further examined both digital and face-to-face interactions with peers on a normal school

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day and during weekends or when not in school. The book focuses on time spent online which, although useful in helping us to understand trends (e.g., being frequent or sporadic users) in teenage online engagement, it does not answer questions about its purpose, such as, engaging online to meet new people, socialise, make comparisons, scrutinise others or debate key issues that matter to their life. This is important because how young people engage with social media determines what benefits they get from them (Verdyun et  al. 2017). For example, active users who socialise with different groups across different communities are likely to increase their interconnectedness, whereas those who use social media for social comparison may experience and internalise a sense of lacking or non-belonging. How internet is used matters for teenagers’ wellbeing and learning but it also mirrors the social ecologies within which young people live. Many studies (discussed in the following chapters) have shown that social media use is higher among teenage girls than boys, while boys are more likely to participate in gaming, either via computer or a console. Also, the findings from a previous study of UK teenagers’ online activities showed that interacting on social media for more than four hours on a typical day was associated with socio-emotional difficulties, but not with lower levels of happiness, suggesting the need to differentiate between positive and negative markers of wellbeing. To this end, the MCS and Understanding Society data analyses in this book included both negative and positive feelings and differentiated between gaming and visiting social networking sites. One of the aims of this study was to examine changes in social media interaction and positive and negative markers of wellbeing with socioeconomic factors and to determine whether a relationship exists between social media interaction and wellbeing trajectories. Another aim was to examine whether social media use and wellbeing trajectories differ by gender, ethnicity and socioeconomic status. Future research is needed to understand the reasons teenagers use social media (rather than the frequency of use alone) and how different types of social media engagement relate to their wellbeing. Data Sources Used for This Book This study adds to the current literature by using longitudinal data from teenagers (10–15 years of age) in the UK.  I obtained the data sources from the Millennium Cohort Study (MCS) and Understanding Society

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(UK Household Longitudinal Study), both national and longitudinal datasets offering rich data on young people’s digital encounters (i.e., online gaming and social media), wellbeing, face-to-face social interactions and friendships and learning attitudes and behaviours. The Millennium Cohort Study (MCS), Wave 6, surveyed the cohort members and their families in 2015 when the young people were aged around 14. Age 14 is a significant age for many reasons, but primarily because it is a period when children are in between childhood and adulthood, when many trajectories are still possible, likely to be influenced by the choices and behaviours they engage in at this age. Interviews were conducted with 11,726 families. A survey response rate of 76.3% was achieved (of the eligible sample), and a co-operation rate of 78.5%. The survey response rate was lower than at MCS5 (81.4%). The 11,726 households contained a total of 11,884 cohort young people, including 142 sets of twins and eight sets of triplets. These sets were not included in this analysis to ensure independence of data. Ninety-seven percent of cohort members completed the young person interview. Understanding Society, which began in 2009, is conducted by the Institute for Social and Economic Research (ISER), at the University of Essex. The aim of Understanding Society is to understand short- and long-term effects of social and economic change in the UK at household and individual levels. It builds on and incorporates the British Household Panel Survey (BHPS), which began in 1991. Understanding Society is an annual survey of each adult member of a nationally representative sample. The same individuals are re-interviewed in each wave approximately 12 months apart. Data collection primarily uses computer-assisted personal interviewing (CAPI), but includes a telephone mop up, and for Wave 7 (collected during 2016), web-based interviews. Each person aged 16 or older participated in the individual adult interview and self-completed questionnaire. Young people aged 10 to 15 were asked to complete a paper self-completion questionnaire. For the purpose of this study, two subgroups were selected from the Wave 7 dataset: pre- and mid-adolescents (10–12 and 13–15 years old, respectively; N = 3635). For this book, I focused on the following questions: What are the national trends in pre- and mid-teenagers’ free (face-to-face interactions with friends, digital play) and parent-structured activities (i.e., extra-curricular activities)?

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What is the relationship between face-to-face play/peer interactions, extra-curricular activities and digital play? Does one type substitute or even replace the other? What are the associations between digital play (i.e., online gaming and visiting social networking sites) and teenagers’ wellbeing (i.e., moods and feelings; self-concept; life satisfaction, self-harm, victimisation), and learning behaviours and attitudes and educational aspirations? What are the associations between face-to-face interactions (unsupervised and out of school peer interactions) and teenagers’ wellbeing (i.e., moods and feelings; self-concept; life satisfaction, self-harm, victimisation), and learning behaviours and attitudes (i.e., behaviour in class, educational motivation, academic self-esteem) and educational aspirations? What are the associations between participation in extra-curricular activities (e.g., going to the library, theatre, doing sports) and teenagers’ wellbeing (i.e., moods and feelings; self-concept; life satisfaction, self-­ harm, victimisation), and learning behaviours and attitudes (i.e., behaviour in class, educational motivation, academic self-esteem) and educational aspirations? What are the trends in both online and offline play when childhoods are unequal? How are face-to-face peer interactions, extra-curricular activities, and digital play viewed through the lenses of gender, ethnicity, disability and families’ socioeconomic background? How do certain aspects of parenting (i.e., communication, emotional closeness, parental control and discipline) relate to free (face-to-face peer interactions and digital play) as well as guided (extra-curricular activities) play? Chapter Summaries Chapter 1 discusses and locates young people’s online and offline play within their virtual, social and emotional geographies. In an era of parent anxiety and ‘stranger fear’, rapid urbanisation and the resulting reduction in outdoor play, I discussed the shifting of children’s geographies from physical to nonmaterial worlds and what this means for teenagers’ developing sense of place. The traditional scale of time and place is blurred in digital spaces because interactions and conversations that would have been confined to a specific point in time and in a particular location (defined by specific cultural, historical and personal circumstances and memories) are

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now reproduced digitally. Nonetheless digital play is an intrinsic part of teenage life, as data on national trends in teenagers’ online play suggest. So are face-to-face peer interactions and participation in extra-curricular activities. Interestingly, one does not replace the other; they seem to coexist, with teenagers moving from physical peer interactions to virtual play seamlessly. Consistently with previous research, excessive use of social media was found to associate with reduced wellbeing, particularly for girls who seemed to be key consumers. However, this association was not the case for face-­to-­face interactions in that, as many teenagers who interacted with their friends often as those who did not reported positive and negative feelings. In relation to face-to-face interactions, online play is not intrinsically good or bad for teenagers’ wellbeing. However, it mirrors their social circumstances, and although online play can be a force for good in facilitating self-expression and connectivity, it reflects the experiences of unequal childhoods and teenage years. Chapter 2 considers teenage online and offline play through the lenses of social class, gender, ethnicity and disability. To this end, I examined the frequency of digital and face-to-face play and participation in extra-­ curricular activities across diverse groups along income, parent education and occupational status, gender, ethnicity and disability (i.e., ratings of social, emotional and behavioural difficulties). Inequalities in children’s life are reflected in their capacity to access outdoor and indoor play opportunities, and their play is differentiated by social group, with middle-class, female, younger and minority ethnic children facing greater restrictions in accessing outdoor spaces. I examined whether these restrictions, mostly evident in adult-organised play and activities, are also seen in digital play and unsupervised face-to-face peer interactions. The onus for children’s play and learning is increasingly being placed on parents who are involved in providing opportunities for play-based learning. MCS analyses showed that roughly similar numbers of teenagers across diverse socioeconomic groups participated in digital play, although teenagers from economically well-off families were more likely to participate in extra-curricular activities. Also, a roughly equal number of teenage boys and girls engaged in digital play, face-to-face peer interactions and extra-curricular activities. Interestingly, gender differences emerged when the type of digital play was considered, with boys preferring gaming and girls visiting social networking sites. Teenage online and offline play varied across different ethnic groups, with White teenagers spending more time with digital play and meeting friends face-to-face than any other ethnic group. Finally,

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teenagers with poor behaviour and emotional difficulties were more likely to spend an excessive amount of time online as did those who experienced bullying. Technology-mediated play and peer interactions can enrich teenagers’ life and help them to overcome some of the obstacles posed by social class, ethnicity and disability. At the same time, inequality, including gender inequality, and disability shape teenage play and their lived experiences with friends online and offline. Chapter 3 examines associations between play (both free and adult organised) and teenage learning behaviours, attitudes and educational aspirations. Rather than examining learning along the lines of subject-­ specific academic achievement, I wanted to capture the broad psycho-­ social dimensions of learning by looking into school behaviour and attitudes, motivation and educational aspirations and their relations to online and offline play. I wanted to know whether different forms of digital play (i.e., gaming and visiting social networking sites) and face-to-face peer interactions found different manifestations in the learning behaviours and attitudes of teenage girls and boys from different socioeconomic groups. The findings showed a drop in teenagers’ motivation, academic self-esteem and educational aspirations as time spent online increased (the drop was sharper for teenage girls). Interestingly, this was not the case when they saw their friends face-to-face despite that teenagers with low motivation and aspirations interacted with their friends more often than their peers with high motivation and aspirations. It appears that the frequency of face-to-face peer interactions does not relate to learning behaviours. In contrast, family socioeconomic status played an important role in shaping educational motivation and aspirations and academic self-esteem, ultimately reproducing educational outcomes. Regarding play-based learning, the correlations between participation in extra-curricular activities and learning behaviours and attitudes and aspirations were weak to modest. But teenagers who spent excessive amounts of time online were less likely to participate in extra-curricular activities. Finally, teenagers in high income families were more likely to participate in extra-curricular activities. Parent-organised educational activities and their effects on children’s learning and quality of educational experience were found to vary according to social class. Chapter 4 looks at teenage play and peer interactions in the era of intensive parenting. Across generations and cultures, parents are anxious to ensure that their children grow up to be happy adults. Parents influence peer interactions but also children show agency in how they relate to their

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peers, and this was captured by examining unsupervised, out of school peer interactions. For most teenagers, digital play and playing with friends unsupervised offered opportunities to move from an adult-structured and supervised social sphere to spaces where they have control over their interactions with others. Technology-mediated changes have introduced a degree of fluidity in what constitutes a responsible parent. In this chapter, the frequency of free play (i.e., digital play, face-to-face playing with friends unsupervised and out of school) and guided play for learning (i.e., extra-­ curricular activities) was analysed across different aspects of parenting such as control, discipline and emotional closeness and communication. The findings showed teenagers who connected emotionally with their parents engaged less often with digital media. Also, parent control and discipline were found to relate to hours spent online, whereas parent control related to the frequency of face-to-face peer interactions and participation in extra-curricular activities. Positive parenting was reflected in mediating teenagers’ digital engagement by having control over their whereabouts and encouraging activities that promote learning. Parents who maintained a strong emotional connection and open communication with their teenagers were likely to be more aware about their teenagers’ online and offline interactions. These findings paint a picture of families as non-instrumental places where parent-child interactions are emotionally and intellectually charged but not necessarily influential in shaping teenage play in its various permutations.

Virtual Encounters in the Time of the Coronavirus Pandemic I was writing the last sections of this book during the Coronavirus pandemic when the physical environment was in quarantine and our lives moved online. Young people appeared to adjust to ‘meeting’ their friends and playing digitally better than the older generations. Digital media can become a force for good in times of crisis—they help people in isolation, especially the most vulnerable in society and support social interactions and learning. They provide a ‘public square’ in a sense of a public virtual space to come together and celebrate or grieve, and this has important implications for our fragmented societies where collective action and the pursuit of collective solutions to problems most of us face have been in decline. As teenagers were forced indoors, physical proximity was replaced

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by virtual interactions, for meeting friends, learning and community participation. Virtual interactions may be all we have for the present time to sustain our human need for connection and help us to combat an epidemic of loneliness and social isolation especially as the social contract is under threat in this new post-pandemic world. Digital media can also be a source of fake news and polarised views, and highlight the ‘digital poverty’, particularly felt by disadvantaged groups. At present, virtual reality feels like a replacement of a physical world falling apart, offering tales of hope but also glimpses of a dystopian future. Coventry, UK

Dimitra Hartas

References Alparone, F. R., & Pacilli, M. G. (2012). On children’s independent mobility: The interplay of demographic, environmental, and psychosocial factors. Children’s Geographies, 10(1), 109–122. Behrenshausen, B.  G. (2012). The active audience, again: Player-centric game studies and the problem of binarism. New Media & Society, 15(6), 872–889. Blum-Ross, A., & Livingstone, S. (2017). Sharenting: Parent blogging and the boundaries of the digital self. Popular Communication, 15(2), 110–125. Buckingham, D., & Sefton-Green, J. (2003). Gotta catch’em all: Structure, agency and pedagogy in children’s media culture. Media, Culture & Society, 25(3), 379–399. Hadley, K. G., & Nenga, S. K. (2004). From Snow White to Digimon: Using popular media to confront Confucian values in Taiwanese peer cultures. Childhood, 11(4), 515–536. Hartas, D. (2019). The social context of adolescent mental health and wellbeing: Parents, friends and social media. Research Papers in Education, 1–19. https:// doi.org/10.1080/02671522.2019.1697734. Holt, L., Bowlby, S., & Lea, J. (2013). Emotions and the habitus: Young people with socio-emotional differences (re)producing social, emotional and cultural capital in family and leisure space-times. Emotion, Space and Society, 9, 33–41. https://doi.org/10.1016/j.emospa.2013.02.002. Lester, S., & Maudsley, M. (2007). Play, naturally: A review of children’s natural play (pp. 47–49). London: Play England, National Children’s Bureau. Marsh, J. (2010). Young children’s play in online virtual worlds. Journal of Early Childhood Research, 8(1), 23–39. https://doi.org/10.1177/1476718X. Marsh, J., & Richards, C. (2013). Play, media and children’s playground cultures. In Children, Media and Playground Cultures (pp.  1–20). London: Palgrave Macmillan.

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Moss, P. (2012). The relationship between early childhood and compulsory education: A properly political question. In Early childhood and compulsory education (pp. 10–58). Routledge. Mustola, M., Koivula, M., Turja, L., & Laakso, M.-L. (2018). Reconsidering activity and passivity in children’s digital play. New Media and Society, 20(1), 237–254. Narine, N., & Grimes, S.  M. (2009). The turbulent rise of the “child gamer”: Public fears and corporate promises in cinematic and promotional depictions of children’s digital play. Communication, Culture & Critique, 2(3), 319–338. O’Mara, J., & Laidlaw, L. (2011). Living in the iworld: Two literacy researchers reflect on the changing texts and literacy practices of childhood. English Teaching: Practice and Critique, 10(4), 149–159. Pellegrini, A. D. (2009). The role of play in human development. New York: Oxford University Press. Shin, W., & Huh, J. (2011). Parental mediation of teenagers’ video game playing: Antecedents and consequences. New Media & Society, 13(6), 945–962. Verduyn, P., Ybarra, O., Résibois, M., Jonides, J., & Kross, E. (2017). Do social network sites enhance or undermine subjective well-being? A critical review. Social Issues and Policy Review, 11(1), 274–302. Verenikina, I., & Kervin, L. (2011). iPads, digital play and pre-schoolers. He Kupu, 2(5), 4–19. Whitebread, D. (2017). Free play and children’s mental health. The Lancet Child & Adolescent Health, 1(3), 167–169.

Acknowledgements

The initial ideas researched and discussed in this book came from a European study funded by the Erasmus Plus fund where colleagues from Turkey, Italy, Spain and I, representing the University of Warwick, became interested in understanding how typically developing children as well as children with disabilities play and interact with their friends. Although within the context of the study the focus was on play for learning purposes, a rather instrumental focus I would add, the notion of free play emerged in our conversations as pivotal to most children’s life, from early to late childhood and teenage years. Ideas about digital play and face-to-­ face peer interactions and their relation to wellbeing and learning for preand mid-teens then started formulating which, ultimately, gave rise to this book. I am grateful to the UK Data Archive for allowing me access to the Millennium Cohort Study and also the Understanding Society datasets that offered a wealth of data on pre- and mid-teens’ play in all its permutations, ranging from social media and computer games to meeting with their friends unsupervised during the week and at weekends to participating in a wide range of extra-curricular activities. Last but not least, I would like to dedicate this book to my two teenage sons as a reminder of the occasionally interesting and often heated conversations we have had over the years about their friends and digital encounters in their life.

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Contents

1 Teenage Play and Peer Interactions: Virtual, Social and Emotional Geographies  1 2 Free and Guided Play and Unequal Childhoods 33 3 Play and Learning Behaviours, Attitudes and Aspirations 59 4 Teenage Free and Guided Play in the Era of Intensive Parenting 79 5 Conclusion: Teenagers in the Era of the ‘Super-Connected’ Selves 93 References105 Index121

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List of Tables

Table 1.1 Table 1.2 Table 1.3 Table 3.1 Table 3.2

% of 14-year-olds for social networking/computer games by gender, ethnicity, income, parent education, self-harm and peer interactions Social networking sites by gender, income and parent education on wellbeing measures Computer games by gender, income, education on wellbeing Social networking sites by gender, income, parent education on learning aspects Computer games by gender, income, parent education on learning aspects

9 18 20 64 66

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CHAPTER 1

Teenage Play and Peer Interactions: Virtual, Social and Emotional Geographies

Abstract  This chapter locates young people’s online and offline play within their virtual, social and emotional geographies. In an era of parent anxiety and ‘stranger fear’, rapid urbanisation and the resulting reduction in outdoor play, children’s geographies appear to shift from physical to nonmaterial worlds. As data on the national trends in teenagers’ online play showed, digital play is an intrinsic part of teenage life and so are face-­ to-­face peer interactions and participation in extra-curricular activities. Interestingly, one does not replace the other; they seem to coexist, with teenagers moving from physical peer interactions to virtual play seamlessly. Consistently with previous research, excessive use of social media was found to associate with reduced wellbeing, particularly for girls who seem to be key consumers. In contrast, this association was not found for face-­ to-­face interactions in that, as many teenagers who interacted with their friends often as those who did not reported positive and negative feelings in roughly equal measures. Online play is not intrinsically good or bad for teenagers’ wellbeing. It mirrors their social circumstances, and although online play can be a force for good in facilitating self-expression and connectivity, it also reflects the experiences of unequal childhoods and teenage years. Keywords  Mental health, Wellbeing, Emotional geographies, Physical geographies

© The Author(s) 2020 D. Hartas, Young People’s Play, Wellbeing and Learning, https://doi.org/10.1007/978-3-030-60001-3_1

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Children’s social geographies are shifting from physical, material to online worlds. And although children seem to treat these spaces as one fluid, interchangeable social space, one wonders whether they equally fulfil their promises for interconnectedness. Changes in young people’s spatial and psycho-social landscapes reflect current socio-political and economic realities whereby public spaces are becoming increasingly corporatised and rural places rapidly urbanised. Since the 1970s, according to a report written for the UK National Trust, the area where children are allowed to roam unsupervised around their homes has shrunk by 90%, redefining their geography of local places and sense of belonging. Our relationship with and psychological reactions to nature and urban landscapes have produced a large body of work within the fields of environmental psychology and psycho-geography. This work is based on explorations of rural, urban and suburban landscapes by drawing on a longstanding literary tradition which can be found in the work by William Blake and Thomas de Quincey in Britain and in the writings of Henry David Thoreau who wandered in the wild places of America. In France, in the mid-twentieth century, the situationist theorist Guy Debord (1958) introduced the concept of ‘dérive’, translated as drifting in a sense of allowing oneself to be drawn by the attractions of the terrain and the encounters one finds there to experience pure chance and authentic memories and feelings generated by landscapes. Modern psycho-geographers such as Ian Sinclair (e.g., Lights Out for the Territory: 9 Excursions in the Secret History of London 1997 and London Orbital: A Walk Around the M25 2002) talk about explorations of the urban environment through walking or the art of ‘drifting’—walking without a set agenda by putting aside all work and leisure activities and other usual motives for movement—to evoke the memories and histories of different landscapes and how they are experienced by the walker. The subjective influence of a place on emotions, with the voice of the walker being more explicit, is captured in these works. Ian Sinclair wrote in Lights Out for the Territory about walking as ‘the best way to explore and exploit the city; the changes, shifts, breaks in the cloud helmet, movement of light on water …’ (1997). This is walking as a way of embracing everything in the surrounding landscape, merging localities with history and memories and the walker’s lived experiences. For psycho-geographers, the art of ‘drifting’ is about encountering events that are unscheduled, unpredictable, chance encounters with the urban world outside the boundaries of the home and immediate

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neighbourhood. In so doing, we are afforded opportunities to interact with a landscape, its histories and myths and open up spaces and possibilities for meaningful social encounters and, most importantly, for interrogations of spaces and histories of social change, of how we change landscapes and how they change us. The desire for meaningful engagement with the physical world, both urban landscapes and nature, has resurfaced in the ‘new nature’ writing. An example of this is The Mountains of the Mind by Robert MacFarlane (2003) where engagement with nature is articulated as a deeply subjective experience in the form of a personal voice-driven narrative. The physical world is seen not as a projection of our needs, nor a means to an end but an end in itself and a place of wonder and solace.

Shifting Geographies and a Sense of Place As the boundaries between public and private, urban and rural spaces are continuously negotiated, young people walk less and increasingly seek virtual spaces to meet new people and socialise with friends. Although research on the benefits of children’s outdoor play and exploration of their neighbourhoods and local places abounds, we know little about what the diminishing contact of children with nature and other physical landscapes and the reduced chance encounters mean for their socialisation, learning and wellbeing. Young people also have chance social encounters in the virtual world, but they tend to be less contextualised within their own urban or rural landscapes, and the memories and histories virtual places evoke tend to be transient and, possibly, less nuanced and meaningful, especially with helping young people to develop a sense of place. Young people’s play and peer interactions are inextricably linked to physical and virtual spaces as biophysical entities but also as socio-cultural constructions. Play can function both as a driver for and an expression of changes in young people’s sense of place and their social and emotional experiences that define it. To articulate a sense of place through young people’s cognitive, affective and social experiences, Raymond et al. (2017) coined the phrase ‘embodied ecosystems’ which highlights the dynamic relations between mind, body, culture and physical places (nature and urban landscapes). Mapping the tangible and intangible aspects of a place is crucial to help us understand young people’s experiences of online and offline spaces and their interactions within them. Much research on children’s play has focused on the type of environments (e.g., outdoor, indoor) and degrees of structure and supervision they receive in these

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environments. And although there are many studies on digital play and peer interactions, mostly from a wellbeing perspective, there is little discussion on young people’s sense of place as a web of interconnected social, cultural, affective experiences in virtual spaces. In contrast, there is a large body of research on teenage sense of place in their interactions with physical environments that may shed light on their sense of place in nonmaterial spaces. Findings from studies in a variety of fields (Abbott-Chapman and Robertson 2009; Matthews et  al. 1998; Owens 1988) portrayed teenagers as ‘active cultural producers’ (Matthews et al. 1998) because of their tendency to mark and create special places that are imbued with meaning generated through memories, the values they placed upon them and the interactions that took place in them. In a study by Owens (1988), based on interviews with 25 white upper–middle-class adolescents aged 14–18 in the USA about their landscape preferences, teenagers reported to value natural spaces; places to be with their friends; places to be alone; places of relative privacy which from where they could see and not be seen; and places they could call their own. Furthermore, Abbott-Chapman and Robertson explored the meanings of accessing private and public space for young people aged 14–19 on the island state of Tasmania, Australia (2009). The authors found that the meanings teenagers attributed to places differed across gender, age and urban/rural dwelling. Specifically, more girls than boys chose familiar and home spaces, and younger children preferred the town centre whereas older children friends’ homes or local places within their neighbourhood. Young people dwelling in urban areas were more likely to consider their bedroom as a place of refuge and privacy whereas teenagers in rural areas found places of refuge in nature. Can a virtual space function as an ‘embodied ecosystem’ whereby connections between young people and virtual spaces are not only in the mind but also the product of interactions between teenagers’ lived experiences and the social and cultural attributes of a place? The fluidity of virtual spaces makes it difficult for young people to have an embodied perspective based on their emotional bonds with and cultural experiences of a place. Using the notions of ‘place identity’ and ‘place dependence’ as introduced by Jorgensen and Stedman (2006), I discuss possible differences in teenagers’ sense of place during digital and physical play. Place identity refers to the feelings, emotional bonds and experiences associated with a place, the meaning teenagers attribute to it but also the meaning and life purpose these places provide to them (Ujang and Zakariya 2015). Place

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dependence refers to the connections between a physical setting and the activities that take place within it, stressing the need to access a place for the activities to materialise. For digital places, place dependence and place identity are fluid. Although activities such as meeting friends or accessing information can take place in virtual spaces, they are not necessarily located within identifiable social and cultural contexts and do not depend on the physical parameters of a place to materialise. regarding place identity and young people’s emotional responses and experiences in virtual spaces, things are even more ambiguous. Social media and social networking can evoke intense emotional reactions and influence young people’s affective and cognitive experiences, self-expression and identity formation. But it is less clear whether teenagers develop strong emotional bonds with virtual spaces to call them a place of their own. It is possible they see virtual spaces as functional only without the need to forge social bonds or emotional connections with them, or it could be that the emotional experiences accrued in virtual places are unidirectional and not shared experiences. Young people do make distinctions between places that are functional and places with an emotional value (Jorgensen and Stedman 2006), but it is not clear whether these distinctions can also be applied to virtual spaces or whether making distinctions in the first place depends on the activities on offer and the people who populate these spaces. For instance, an online gaming environment may be both functional and a place where social bonding occurs among participants, whereas accessing information from an online platform is purely functional. Also, structured play such as participation in extra-curricular activities (as discussed in Chap. 4) reflect both place dependence and place identity in that young people engage in functional activities for the purpose of developing skills and, at the same time, socialise with peers and, often, form social and emotional bonds with them. In physical, material places teenagers’ sense of a place evolves along activities, the social bonds and emotional experiences accrued, and the meanings generated by the participants. Although digital engagements are meaningful, we do not know how teenagers’ sense of place is shaped within them or as a result of them. A sense of place is subjective and is formed through a series of interpretive possibilities which can be both conflicting—bringing together contrasting meanings or emotional states—and comforting in finding solace in a locality. During online encounters, a sense of place relies on young people’s lived experiences

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(both positive and negative), capacity to question their own relationship with the places they visit and awareness of the impermanence of virtual places. Perceptions, real or imagined, can still thrive in digital spaces along with notions of insider/outsider and self/other. However, active dialogue and the display of empathy between the users often do not materialise in virtual places.

Physical and Virtual Geographies and Play Children’s play is often rooted in physical places defined by experiences, mostly childhood experiences and memories about events that happened in a specific location, which help them to build a coherent sense of self and a sense of belonging. The traditional scale of time and place is blurred in digital spaces because interactions and conversations that would have been confined to a specific point in time and a particular location (defined by cultural, historical and personal circumstances and memories) are now reproduced digitally, reaching people not included in the original interaction who may have little understanding of the particularities of a place and the actors within it. In cyberspaces, a sense of place becomes fluid, ever changing and more pluralistic but also hard to pin down and commit to memory and storytelling. And although stories and descriptions of events are in abundance online, it is not clear how the emotionality of a story or experience of an event is disclosed and received by young people. Young people, especially those who are different and may experience marginalisation as a result, have limited access to physical environments and ‘real-life’ peer interactions, seeking virtual encounters in the cyberspace. To make sense of these shifts and what they mean for young people’s wellbeing and social connectedness, we need a nuanced understanding about their peer interactions and play in virtual environments. After all, digital worlds are part of the young people’s worlds and may open new possibilities for ‘drifting’ and exploring digital landscapes with their own memories and histories. For example, as a study by Freeman et al. (2016) showed, young people interacted with both physical and digital worlds as they visited nature in their locality via a child-operated Geographical Information System (GIS). The boundaries between virtual and physical spaces appear to be porous, and it is possible for teenagers to interact with them in a seamless manner. A digitally mediated sense of place could also offer teenagers meaningful social experiences and memories and help them to construct a coherent self. But we still do not know how a sense of

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place is evoked in digital worlds and its implications for play, social connectedness and wellbeing. Virtual interactions can be as complex and nuanced as real-life interactions, but more expansive and reductive at the same time. Virtual reality has accentuated young people’s sense of what is private and what is public and how to negotiate the boundaries between the two in ways that are meaningful for their life. Through play, young people interact in physical and virtual geographies which, consciously managed or not, act directly on their mood and behaviour and social interactions, being influenced not only by the people they meet but also the structures of the places they visit and the experiences they gain there. By being immersed in physical and virtual geographies, young people develop an understanding of the nuances of complex digital and physical material worlds, and experiment with different modes of self-expression and identity formation to navigate social structures, norms and expectations (Black et al. 2015). As technology changes society, particularly with the move to artificial intelligence and machine learning, the human becomes the focus, with young people engaging in a perpetual project of self-improvement to augment human capacity and achieve happiness. We do not know how they relate to each other and develop criticality to deal with conformism and ‘chambers of ideas’ found in some virtual encounters and build resilience. Social media offer a platform for teenagers, unmediated by adults, to have a voice, listen to others and interact with people globally. As such, young people’s voice can have a global reach; at the same time, this visibility may decrease their wellbeing due to loss of privacy, reduced local interactions and the possibility of becoming a target for exploitation. In a market-based society, the pressure for young people to demonstrate their value and outperform their peers and, in so doing, strive towards often unrealistic goals is immense, having a negative impact on their social relationships. When engaging with social media or other platforms, young people are likely to be dealing with digital systems that are profit driven and competitive, that do not operate within a culture-specific ethical framework but globally within multiple and even conflicting social, contexts. Young people are not mono-dimensional in their thoughts and social behaviour, as they are often portrayed in social media sites, but complex and ambiguous. However, they appear to have internalised their constantly being evaluated and ranked, with metrics becoming important to their life, and this may have implications for how they relate to each other

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online. Digital platforms facilitate ranking and increase individual misery through intensified projections of society’s ills. Virtual encounters are not divorced from real-life experiences; they reflect and even magnify our material world. They augment trends in society already set in motion such as large-scale surveillance and loss of privacy, inequality, including gender inequality, and the diminishing of civic engagement. They can also facilitate having a voice which can have pros and cons, voice for voiceless teenagers but also for trolls who inject toxicity in conversations and encourage young people to be self-censorious. At a deeper level, online social encounters could promote conformity, a customised future for young people where free will, self-determination and autonomy are compromised. Replacing human decision making with algorithmic predictions, rankings and recommendations is a unique feature of the internet. This is far removed from the world of teenage faceto-­face play in social material worlds where they have control over the processes and decisions that underpin their interactions and play. These are big issues fraught with contradictions and controversy. To start untangling teenage digital play and face-to-face peer interactions, an important first step is to delineate current national trends in teenagers’ online and offline engagement when playing and socialising with their peers.

National Trends in Teenage Offline and Online Play In analysing the frequency of face-to-face interactions with friends (Table 1.1), teenagers (e.g., 14-year-olds) were asked ‘When not at school, how often do you spend time with your close friends?’, with 37.4% responding ‘most days’; 34.7% ‘at least once a week’ and 27.9% ‘once a month/less often’. They were also asked about time spent playing unsupervised with friends during the weekends, with 60% responding ‘most weekends’; 22.5% ‘at least once a month’ and 17.5% ‘less often than once a month’. These findings showed that around two thirds of young people reported to often interact with their friends out of school and most weekends. Likewise, over half played with friends (unsupervised by adults) most days or at least once a week. Although most young people interacted and played with friends frequently, around a quarter did not. In terms of physical proximity to peers, nearly half of 14-year-olds said that most of their friends live in the same area as they do whereas 39% said some of their friends live nearby, with around 13% of young people stating that none of

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Table 1.1  % of 14-year-olds for social networking/computer games by gender, ethnicity, income, parent education, self-harm and peer interactions Social networking / Computer games 0–2 hours

2–5 hours

7–5 hours or more

Gender: M 63.4/37.9 24.6/38.7 12/23.3 F 39.8/80.4 33.9/14.5 26.2/5.1 Ethnicity: White 50.1/57.6 30.1/27 19.8/15.4 Mixed 54.4/64.4 24.3/22.1 21.4/13.5 Indian 62.6/71.4 26.4/23 11.0/5.7 Pakistani/Bangladeshi 62.5/67.5 23.4/24.5 14.1/8.1 Black 48.1/66.6 28.3/22 23.7/10.4 Income quintile: 1 50.7/55.3 26.2/27.9 23.1/16.7 2 46.1/57.3 29.6/25.9 24.3/16.8 3 48.2/55.1 31.2/29.6 20.6/15.3 4 51.6/60.2 30.9/26.1 17.4/13.7 5 58.9/66.1 28.2/24.1 12.8/9.8 Parent education level: 1 49.5/52.3 25.9/28.6 24.6/19.1 2 46.3/55.6 30.5/27.7 23.2/16.7 3 51.3/57.7 30/27.8 18.7/14.6 4 53.8/60.9 30.6/26.3 15.6/12.8 5 58/66.5 25.9/23.2 16.1/10.4 Self-harm: Yes 33.3/63.7 30.9/22.9 35.8/13.5 No 54.2/58.6 29.3/27.2 16.5/14.3 Friends-unsupervised 1 42.8/59.1 32.6/27.3 24.6/13.6 2 59.3/62.4 28.7/24.9 11.9/12.7 3 71.7/55.8 18.6/26.2 9.7/18 Friends (out of school) 1 40.2/57.4 32.2/27.1 27.6/15.5 2 51.7/60.2 31.3/26.9 17/12.9 3 64.5/61.2 24.3/25.2 11.2/13.6 % of 10–15-year-olds on using computer for schoolwork/social networking/gaming >1 hours 1–3 hours 4–7 hours or more Age 10–12 44.9/49.7/48.4 57.8/35.3 /54.4 67.9/18.9 /44.9 13–15 55.1/50.3/51.6 42.2/64.7/45.6 32.1/81.1 /55.1 (continued)

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Table 1.1 (continued) Social networking / Computer games

Gender Male Female

0–2 hours

2–5 hours

7–5 hours or more

47.7/56.6/36.3 52.3/43.4/63.7

48.3/43.2/76.9 51.7/56.8/23.1

56.6/33.9/87.8 43.4/66.1/12.2

N = 11,115 (14-year-olds); N = 3313 (10–15-year-olds) Notes: Chi-square tests were significant for gender (700.1); ethnicity (234); income (159.7); parent education (103.9); self-harm (392.5); peer interactions—unsupervised (686); peer interactions at weekends (510) pointing to significant relationships between these variables and frequency of visiting social networking sites. Similarly, chi-square tests were significant for gender (287.6); ethnicity (134); and income (104), but not significant for parent education; self-harm; peer interactions—unsupervised; peer interactions at weekends pointing to a significant relationships between the frequency of online gaming and gender, ethnicity and income. There were no significant associations between the frequency of online gaming and parent education; self-harm; and peer interactions (unsupervised and at weekends). Regarding 10–15–year-olds, significant differences were found for schoolwork computer (102.4); social networking (135.06) and gaming (11.6) between 10–12 and 13–15-year-olds. Likewise, significant differences between boys and girls were found for work computer use (112); social networking (78) and gaming (110)

their friends live in the same areas as they do. Nearly 87% said they attend the same school as their friends. These findings suggest that most young people interacted and played with each other and formed friendships within their local geographies. These findings also tell us that face-to-face interactions are still an important feature of teenage life. Peer influence is a counterpoint to parental influence throughout adolescence, and as parental influence declines during adolescence, peer relationships become important (Viner et  al. 2012). Positive peer interactions and relationships are essential to young people’s physical and mental health (Heydenberk and Heydenberk 2017). Young people gain positive social experiences by spending time with friends out of school and in adult-unsupervised activities and during digital play. In probing online interactions in 12–15-year-olds in the UK (Table 1.1), analyses of data from Understanding Society (US) painted an interesting picture. Nearly half (46%) reported to spend less than 1 hour, 37% 1–3 hours and 17% 4 to 7 hours or more daily interacting with friends through social websites (with 70% stating they belong to a social website). Also, 63% of 12–15-year-olds reported to spend less than 1 hour; 29% 1–3 hours and 8% 4 to 7 hours or more playing games on a console on a

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normal school day (with 89% having a game console such as Playstation). Teenagers were also asked how many hours they spend using a computer for schoolwork, with 69% stating less than 1 hour, 15% 1–3 hours and 16% 4 to 7 hours or more daily. Interesting age differences emerged when pre (10–12-year-olds) and mid (13–15-year-olds) teenagers’ frequency of online engagement was compared. Specifically, 10–12-year-olds were more likely than 13–15-year-­ olds to use a computer for schoolwork for more than 1 hour a day, and over twice as many 10–12 as 13–15-year-olds used a computer for schoolwork for 4 to 7 hours or more daily. The opposite was found for time spent on social networking, whereby compared to mid-teens, pre-teens were 60% less likely to spend 4–7 hours or more on a school day. The difference in the percentage of pre- and mid-teens who reported to spend less than 1 hour visiting social networking sites was small, but as they moved into mid-adolescence, it increased fourfold, in that over 4 times as many mid-teens as pre-teens reported to visit social networking sites for 4 to 7 hours or more daily. Regarding console games, a roughly equal number of pre- and mid-teens played for less than 1 hour, 1–3 hours and 4 to 7 hours or more. It appears that as children moved into mid-adolescence, they spent more time on social media whereas the time spent on console games remained stable over the same period. This is consistent with findings from previous analyses of the Understanding Society dataset by Booker and colleagues whereby engagement in social media increased with age for both boys and girls (2018). Mid-adolescence is a midpoint between childhood and adulthood; it is a time where many trajectories are open to young people, especially new social experiences. In light of the increased time mid-teens spent on social media, I delved into in-depth analyses of their encounters with social media by analysing 14-year-olds’ frequency of social media use, using data from the Millennium Cohort Study (MCS). The findings showed that slightly over half (51%) of 14-year-olds spent less than 2 hours, less than a third (29%) spent 2–5 hours and around 1 in 5 spent 5–7 hours or more on social media daily (Table 1.1). Around 60% of 14-year-olds played console games for less than 2 hours, around 32% for 2–5 hours and 14% for 5–7 hours or more in a typical day. As discussed in Chap. 2, interesting gender differences emerged whereby over twice more girls than boys spent 5–7 hours or more visiting social networking sites, and considerably more boys than girls played console games.

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It is important to understand these trends in online engagement in relation to young people’s face-to-face interactions in the physical material world. Amongst 14-year-olds who met their friends frequently (i.e., most days in an unsupervised context), a quarter visited social media and around 13% gamed for 5–7 hours or more daily. Interestingly, fewer young people who rarely (i.e., once a month or less often) played unsupervised with friends used social media (10%) and played console games (18%). Compared to 14-year-olds who seldom played with friends unsupervised, there were three times more who frequently did and who also used social media for 5–7 hours or more daily. Similar patterns emerged for 14-year-olds who often played with friends out of school/in the weekend, in that over a quarter (28%) of those who played most weekends with friends also used social media for 5–7 hours or more daily, whereas roughly equal numbers played with friends face to face and gamed online. It appears that most 14-year-olds who often interacted with friends face to face also spent 5–7 hours or more on social media. The reverse was true for gaming in that the number of 14-year-olds who gamed online was roughly the same irrespective of how often they interacted face-­ to-­face with friends, unsupervised or out of school in weekends. Also, amongst 14-year-olds who rarely played with friends face-to-face, nearly three quarters used social media for less than 2 hours in a typical day. The findings showed that the hours spent on gaming did not differ based on how often teenagers interacted with their friends face to face. In contrast, social media use was more frequent among those who interacted with their friends face to face most days and weekends. For most young people, spending excessive time on social networking sites was not at the expense of face-to-face peer interactions. Interestingly, young people who spent less than 2 hours on social media were found to see their friends face to face far less frequently. What is observed here is a ‘rich-getting-richer’ phenomenon in that teenagers who used social media (but not gaming) excessively (5–7 hours or more daily) also interacted frequently with their peers, face to face. It is possible that excessive use of social media is fuelled by face-to-face peer interactions and vice versa. Previous empirical studies have also supported the ‘rich-get-richer and poor-get-poorer’ hypothesis, which suggests that social skills practiced during face-to-face interactions can transfer online to replicate and amplify differences in offline social success (Reich 2016). The ‘rich-getting-richer’ phenomenon was also observed by Davis (2012), but it was more about quality rather than frequency of peer interactions and friendships whereby

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young people whose offline friendship quality was perceived to be high accrued greater benefits from online interactions. Research on peer interactions has highlighted the importance of social competence in children’s development and the risks of lacking social skills for physical, social, emotional and academic outcomes. Most research about social competence in children and adolescents has focused on face-­ to-­face interactions with very few studies examining social skills and competence in online interactions. In this study, roughly equal numbers of teenagers interacted with their peers across social media, gaming and face-­ to-­face, suggesting a seamless movement between virtual and physical places. It seems that teenagers are socially active across platforms and their social skills are practised and applied not only in offline but also online interactions. Reich reviewed research on online social interactions and identified components of social competence (e.g., adaptability, social skills, perspective-­taking, social problem-solving skills) present in offline settings to also transfer to online contexts (2017). Although there are challenges in examining the ways in which young people’s social competence and capacity to form and maintain relationships transfer from offline to online interactions, the findings from the MCS and US analyses suggest a degree of transferability of social skills across online and offline environments. Questions however remain about which skills are more likely to transfer between online and offline spaces. Also, we cannot make any inferences about the extent to which the digital interactions were embodied and whether teenagers’ sense of a place is similar across their digital and face-­ to-­face encounters. Social interactions today are increasingly technologically mediated, with many children and teenagers interacting with others online, but not at the expense of their offline interactions in that teenagers who used social media also interacted with each other face to face frequently. One mode of social interaction did not seem to displace the other; they have a symbiotic existence. However, unlike face-to-face interactions, digital encounters offer a different type of socialisation. Social skills, emotional connectedness, disclosure and empathy depend, to a great extent, on being able to read facial expressions, emotions and body language (e.g., Cash et al. 2013). Online encounters cannot and should not displace face-­ to-­face interactions necessary for young people to develop empathy and emotional intelligence. Empathy is rooted in small group interactions bounded by history, culture and a collective sense of the common good.

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Although it is possible for teenagers to develop empathy for people they meet in the cyberspace, it is certainly more challenging because they do not know their history and may have very little in common. The same argument applies to young people’s duty of care towards themselves and others. Social encounters in the virtual world may not offer the same opportunities as real-life encounters to enable young people to form the emotional connections required to understand other’s perspective. The nature of digital play is thus different from face-to-face play with regard to emotional bonding in that, in online encounters, teenagers may develop a false sense they know others, their life and histories, and believe they are in a position to scrutinise them and pass judgement about them. Meaning making during social interactions is anchored in the social and cultural contexts that surround people’s life and we know very little as to how meaning making during social encounters is mediated by technology. Limited face-to-face interactions with peers could deprive children from exposure to conflict situations, risk and negative experiences such as insult or exclusion and this can also be detrimental to their development of emotional resilience, which is the bedrock for wellbeing. Teenagers’ social media use is not inherently harmful. However, it remains unclear how social media use relates to positive and negative social outcomes and the ways in which they influence teenagers’ lived experience and wellbeing. As Weinstein (2018) argued the ‘either/or’ approach (social media have either a positive or a negative influence on wellbeing) is not useful nor is it holistic. Instead, a ‘both/and’ model is promoted in that teenagers’ experience of social networking can be positive in one instance and negative in another, or it can vary over time depending on the social, cultural and familial circumstances that surround their life. Although the relationship between digital play and wellbeing is multi-­ faceted and cannot adequately be captured by examining time spent online alone, I examined it in its social context by looking into digital media use and wellbeing through the lenses of inequality, including gender inequality, and in relation to other aspects of teenagers’ social life such as face-to-­ face peer interactions.

Teenage Online and Offline Play and Wellbeing Young people’s wellbeing is intrinsically linked with their capacity to learn and make sense of the world and their place in it. But when the social world is changing fast, mediated by technology, it becomes difficult to

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define its parameters and the multitude of ways we experience it. Unsurprisingly, wellbeing also becomes difficult to define and understand. Wellbeing is not just absence of problems but also young people’s agency in constructing a coherent self and identity and contributing to their communities creatively and productively (Hartas 2019). Subjective wellbeing is about how people see themselves and evaluate their lives at present and over time (Diener et al. 1985; Statham and Chase 2010). In the literature, wellbeing has been studied from a hedonic perspective (life satisfaction by focusing on what makes life pleasurable and people happy) and eudaimonic perspective (good relationships with others, social support, personal growth) (Samman 2007). Statham and Chase approached psychological/mental health and wellbeing as synonymous (2010). Mental health and wellbeing share similar domains in that low mood and negative feelings and tendencies towards self-harm are likely to reduce young people’s wellbeing, how they see themselves and how happy they feel. The shift from physical to virtual geographies and how this relates to young people’s emotional geographies is of interest considering that their physical geographies are shrinking, and online engagement is becoming pivotal in their social life. Compared to previous generations, teenagers today spend considerably more time indoors engaging with digital platforms for play, socialisation and learning. Yet, we know very little about the interplay of online engagement, offline interactions and wellbeing especially across diverse groups of young people. This is particularly important as rates of mental ill health in young people are on the rise. Teenagers operate within a complex web of social relationships and influences. Social relationships in teenage years are affecting and affected by teenagers’ wellbeing, reinforcing the importance of locating wellbeing within young people’s social interactions, online and offline. To better understand the virtual and physical geographies of pre- and mid-teenagers and how they influence their emotional geographies, I examined wellbeing in relation to digital play and offline peer interactions. Although there is fluidity in how wellbeing is defined and measured, I focused on both positive (i.e., life satisfaction; self-concept, including self-­ image) and negative feelings (i.e., low feelings and moods, self-harm and a sense of victimisation). Specifically, I examined associations between hours spent on digital play (i.e., online games; visiting social networking sites) and face-to-face peer interactions and 14-year-olds’ wellbeing expressed in terms of life satisfaction; self-concept, including self-image;

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feelings and moods, self-harm and victimisation. I also examined whether these associations differed for boys and girls. For the purpose of these analyses, measures of wellbeing were taken from the MCS dataset and were defined as follows: Life satisfaction: This is adapted from the Satisfaction with Life scale by Diener et al. (1985). The coefficient alpha for the scale has ranged from 0.79 to 0.89, indicating that the scale has high internal consistency (in other words most of the items of the scale reflect life satisfaction). A composite variable (M = 2.5 and SD = 1.1) was created with the following items: ‘How happy is CM (Cohort Member) with school’ (58.9% happy, 29.2% somewhat happy, 11.9% not happy); ‘How happy is CM with school work’ (54.5% happy, 33.5% somewhat happy, 11.9% not happy); ‘How happy is CM with the way they look’? (38.5% happy, 41.2% somewhat happy, 20.3% not happy); ‘How happy is CM with family’ (75.8% happy, 16.8% somewhat happy, 7.3% not happy); ‘How happy is CM with friends’ (75.6% happy, 17.9% somewhat happy, 6.5% not happy); and ‘How happy is CM with life as a whole?’ (62.9% happy, 27% somewhat happy, 10.1% not happy). These statements were measured on a scale 1–7 with 1 being ‘completely happy’ to 7 ‘not happy at all’. Increased scores indicated lower life satisfaction. Self-concept: This scale is a measure of young people’s self-concept (Rosenberg 1965). It includes the following items: ‘On the whole, ‘I am satisfied with myself’ (26.5% strongly agree, 58.7% agree, 14.8% disagree/ strongly disagree); ‘I feel I have a number of good qualities’ (27.6% strongly agree, 60.3% agree, 12.1% disagree/ strongly disagree); ‘I am able to do most things as well as other people’ (30.1% strongly agree, 58.8% agree, 11.1 disagree/ strongly disagree); ‘I am a person of value’ (25.7% strongly agree, 61.4% agree, 12.9 disagree/ strongly disagree); and ‘I feel good about myself’ (26.7% strongly agree, 54.9% agree, 18.4 disagree/ strongly disagree). These statements were measured via a Likert scale and the internal consistency for the Rosenberg Scale ranges from 0.77 to 0.88 with test-retest reliability ranging from 0.82 to 0.85. As the scores increase, self-concept becomes lower. The Short Moods and Feelings (SMF) Questionnaire: The Short Mood and Feelings Questionnaire (SMFQ-short), child version, is a 13-item subscale from a longer 33-item questionnaire (the original MFQ). The items are based on the Diagnostic and Statistical Manual-III (DSM)-III criteria for depression: ‘I felt miserable or unhappy’ (40.4% not true, 51.8% sometimes true, 7.8% true); ‘I did not enjoy anything at all’

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(68.7% not true, 27.6% sometimes true, 3.7% true); ‘I felt so tired I just sat around and did nothing’ (45.9% not true, 42.7% sometimes true, 11.4% true); ‘I was very restless’ (56.5% not true, 35.3% sometimes true, 8.1% true); ‘I felt I was no good anymore’ (71.5% not true, 21% sometimes true, 7.5% true); ‘I cried a lot’ (73.9% not true, 19% sometimes true, 7.1% true); ‘I found it hard to think properly or concentrate’ (48.4% not true, 39.7% sometimes true, 11.9% true); ‘I hated myself’ (75.4% not true, 17.7% sometimes true, 6.9% true); ‘I was a bad person’ (79.3% not true, 16.8% sometimes true, 3.9% true); ‘I felt lonely’ (65.8% not true, 25% sometimes true, 9.1% true); ‘I thought nobody really loved me’ (77.5% not true, 15.9% sometimes true, 6.6% true); ‘I thought I could never be as good as other kids’ (68.3% not true, 22.8% sometimes true, 8.9% true); and ‘I did everything wrong’ (74.6% not true, 19.3% sometimes true, 6.1% true). This is a screening and not a diagnostic tool and thus it should only be used an indicator of depressive symptoms. The internal reliability coefficient for the survey has been found to be good (Cronbach’s alpha = 0.85), suggesting that the shortened version of the survey adapted from the long version is reliable (Angold et al. 1995). Young people were asked to complete the SMF questionnaire to assess feelings and behaviours associated with depressive characteristics over a fortnight. For the composite variable, M = 1.4 and SD = 0.45. Self-harm: A question was asked about whether CM has self-harmed in the past year, with 14.6% answering ‘Yes’ and 86.4% ‘No’. Victimisation: this is a composite measure based on the following items with dichotomous answers (Yes, No): ‘CM was insulted, threatened, shouted at’ (43% Yes, 57% No); ‘been physically violent towards CM’ (21.8% Yes, 78.2% No); ‘hit or used a weapon against CM’ (3.1% yes, 96.9% No); ‘stolen something from CM’ (7.2% Yes, 92.8% No); ‘sexually assaulted CM’ (2.8% Yes, 97.2% No). Higher scores indicated reduced victimisation. For the composite variable: M = 9.2 and SD = 0.9. Digital Play and Wellbeing in Teenage Boys and Girls I examined the relationship between teenage boys’ and girls’ wellbeing (i.e., life satisfaction, self-concept / self-image, feelings and moods, self-­ harm, victimisation) and frequency of digital play by using descriptive statistical analyses (see Tables 1.1, 1.2 and 1.3). Initial gender analyses showed that, compared to boys, 14-year-old girls reported significantly

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Table 1.2  Social networking sites by gender, income and parent education on wellbeing measures Moods and feeling

Self-concept

Social networking

Gender M (SD)

Income M (SD)

Parent education M (SD)

0- less than 2 hours

M 1.28 (0.32) F 1.42 (0.44)

2- less than 5 hours

M 1.32 (0.36) F 1.52 (0.28)

5 to 7 hours or more

M 1.42 (0.42) F 1.71 (0.56)

0- less than 2 hours

M 1.71 (0.50) F 1.92 (0.56)

2- less than 5 hours

M 1.73 (0.51) F 2.04 (0.57)

5 to 7 hours or more

M 1.78 (0.56) F 2.20 (0.62)

1 1.3 (0.38) 2 1.3 (0.41) 3 1.3 (0.38) 4 1.3 (0.38) 5 1.3 (0.36) 1 1.4 (0.43) 2 1.4 (0.49) 3 1.4 (0.44) 4 1.4 (0.43) 5 1.4 (0.43) 1 1.5 (0.50) 2 1.6 (0.54) 3 1.6 (0.54) 4 1.6 (0.56) 5 1.6 (0.54) 1 1.8 (0.50) 2 1.8 (0.56) 3 1.8 (0.52) 4 1.7 (0.53) 5 1.7 (0.54) 1 1.9 (0.54) 2 1.9 (0.59) 3 1.9 (0.57) 4 1.8 (0.55) 5 1.8 (0.56) 1 2.1 (0.64) 2 2.1 (0.62) 3 2.1 (0.60) 4 2.0 (0.65) 5 2.1 (0.63)

1 1.3 (0.34) 2 1.3 (0.37) 3 1.3 (0.39) 4 1.3 (0.38) 5 1.3 (0.38) 1 1.4 (0.46) 2 1.4 (0.45) 3 1.4 (0.47) 4 1.4 (0.44) 5 1.4 (0.44) 1 1.6 (0.54) 2 1.6 (0.55) 3 1.6 (0.57) 4 1.5 (0.52) 5 1.6 (0.51) 1 1.8 (0.54) 2 1.8 (0.53) 3 1.7 (0.52) 4 1.7 (0.53) 5 1.7 (0.56) 1 1.9 (0.57) 2 1.9 (0.57) 3 1.9 (0.59) 4 1.8 (0.56) 5 1.9 (0.55) 1 2.08 (0.63) 2 2.13 (0.65) 3 2.10 (0.68) 4 2.03 (0.60) 5 2.04 (0.61) (continued)

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Table 1.2 (continued) Moods and feeling

Social networking

Gender M (SD)

Life satisfaction

0- less than 2 hours

M 2.25 (1.0) 1 2.4 (1.1) F2.43 (1.06) 2 2.4 (1.1) 3 2.3 (1.0) 4 2.26 (0.9) 5 2.20 (0.9) M2.35 1 2.6 (1.1) (1.03) 2 2.7 (1.1) F2.64 (1.09) 3 2.5 (1.0) 4 2.4 (1.0) 5 2.3 (1.0) M 2.58 1 2.8 (1.2) (1.11) 2 3.0 (1.2) F 3.09 (1.2) 3 2.9 (1.2) 4 2.9 (1.2) 5 2.9 (1.2) M 9.2 (0.98) 19.3 (1.0) F 9.4 (0.87) 2 9.2 (0.99) 3 9.3 (0.98) 4 9.3 (0.95) 5 9.2 (0.99) M 9.03 (1) 1 9.2 (1.0) F 9.2 (8.9) 2 9.1 (1.0) 3 9.1 (1.0) 4 9.1 (0.97) 5 9.2 (0.97) M 8.9 (1.1) 1 9.0 (1.07) F 9.0 (1.0) 2 8.9 (1.07) 3 8.9 (1.07) 4 9.0 (0.9) 5 9.0 (0.9)

2- less than 5 hours

5 to 7 hours or more

Victimisation

0- less than 2 hours

2- less than 5 hours

5 to 7 hours or more

Income M (SD)

Parent education M (SD) 1 2.3 (1.0) 2 2.3 (1.0) 3 2.3 (1.0) 4 2.3 (0.99) 5 2.2 (1.0) 1 2.6 (1) 2 2.5 (1) 3 2.5 (1) 4 2.4 (1) 5 2.5 (1) 1 2.9 (1) 2 2.9 (1) 3 2.9 (1) 4 2.9 (1) 5 2.9 (1) 1 9.3 (0.92) 2 0.92 (0.93) 3 0.93 (0.89) 4 0.92 (0.98) 5 0.92 (0.92) 1 9.2 (0.99) 2 9.1 (0.97) 3 9.1 (0.98) 4 9.1 (0.97) 5 9.1 (0.98) 1 9.0 (1) 2 8.9 (1) 3 9.0 (1) 4 9.0 (1) 5 8.9 (1)

N = 11,310−11,293 (the notation 1 to 5 under the Income and Parent Education columns denotes quintiles 1 = top and 5 = bottom quintile; and parent education levels, 1 = no educational qualifications to 5 = qualifications at postgraduate degree level) Notes: A series of Analyses of Variance (ANOVAs) were conducted. Statistically significant differences emerged between gender and all measures of wellbeing (Moods and Feeling, Self-Concept, Life Satisfaction and Victimisation) with regard to the frequency of social networking. No significant differences were found between these wellbeing measures and (i) parent income and (ii) parent education

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Table 1.3  Computer games by gender, income, education on wellbeing Moods and feeling

Self-concept

Computer games

Gender M (SD)

Income M (SD)

Parent education M (SD)

0- less than 2 hours

M 1.28 (0.32) F 1.42 (0.44)

2- less than 5 hours

M 1.32 (0.36) F 1.52 (0.28)

5 to 7 hours or more

M 1.42 (0.42) F 1.71 (0.56)

0- less than 2 hours

M 1.71 (0.50) F 1.92 (0.56)

2- less than 5 hours

M 1.73 (0.51) F 2.04 (0.57)

5 to 7 hours or more

M 1.78 (0.56) F 2.20 (0.62)

1 1.4 (0.4) 2 1.5 (0.5) 3 1.4 (0.4) 4 1.4 (0.4) 5 1.4 (0.4) 1 1.3 (0.4) 2 1.4 (0.4) 3 1.3 (0.4) 4 1.3 (0.4) 5 1.3 (0.4) 1 1.4 (0.4) 2 1.4 (0.4) 3 1.4 (0.4) 4 1.3 (0.3) 5 1.4 (0.4) 1 1.9 (0.5) 2 2 (0.6) 3 1.9 (0.5) 4 1.9 (0.5) 5 1.8 (0.5) 1 1.8 (0.5) 2 1.8 (0.5) 3 1.8 (0.5) 4 1.8 (0.5) 5 1.7 (0.5) 1 1.9 (0.5) 2 1.9 (0.5) 3 1.8 (0.5) 4 1.7 (0.5) 5 1.8 (0.5)

1 1.4 (0.4) 2 1.4 (0.4) 3 1.4 (0.4) 4 1.4 (0.4) 5 1.4 (0.4) 1 1.3 (0.4) 2 1.4 (0.4) 3 1.3 (0.4) 4 1.3 (0.4) 5 1.3 (0.4) 1 1.4 (0.4) 2 1.4 (0.4) 3 1.4 (0.4) 4 1.4 (0.4) 5 1.3 (0.4) 1 1.9 (0.5) 2 1.9 (0.5) 3 1.9 (0.5) 4 1.8 (0.5) 5 1.8 (0.5) 1 1.8 (0.5) 2 1.9 (0.5) 3 1.8 (0.5) 4 1.8 (0.5) 5 1.8 (0.5) 1 1.9 (0.6) 2 1.8 (0.5) 3 1.8 (0.5) 4 1.8 (0.5) 5 1.8 (0.5) (continued)

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Table 1.3 (continued) Moods and feeling

Computer games

Gender M (SD)

Life satisfaction

0- less than 2 hours

M 2.25 (1.0) 1 2.5 (1.1) F2.43 (1.06) 2 2.6 (1.1) 3 2.6 (1.1) 4 2.4 (1.1) 5 2.3 (1.1) M2.35 1 2.5 (1.1) (1.03) 2 2.5 (1.1) F2.64 (1.09) 3 2.4 (1.1) 4 2.3 (0.9) 5 2.2 (0.9) M 2.58 1 2.7 (1.1) (1.11) 2 2.8 (1.1) F 3.09 (1.2) 3 2.6 (1.1) 4 2.4 (1.1) 5 2.5 (1.1) M 9.2 (1) 1 9.3 (0.9) F9.3 (1) 2 9.2 (0.9) 3 9.2 (0.9) 4 9.2 (0.8) 5 9.3 (0.9) M 9.1 (0.9) 1 9.2 (0.9) F9.1 (0.9) 2 9.1 (0.9) 3 9.1 (0.9) 4 9.1 (0.9) 5 9.1 (0.9) M 9.0 (1) 1 9.0 (0.9) F 9.0 (0.9) 2 9.0 (0.9) 3 9.0 (0.9) 4 9.0 (0.9) 5 9.0 (0.9)

2- less than 5 hours

5 to 7 hours or more

Victimisation

0- less than 2 hours

2- less than 5 hours

5 to 7 hours or more

Income M (SD)

Parent education M (SD) 1 2.5 (1.1) 2 2.5 (1.1) 3 2.4 (1.1) 4 2.4 (1.1) 5 2.4 (1.1) 1 2.4 (1.1) 2 2.4 (1.1) 3 2.3 (1.1) 4 2.3 (1.1) 5 2.4 (1.1) 1 2.8 (1.1) 2 2.6 (1.1) 3 2.5 (1.1) 4 2.8 (1.1) 5 2.4 (1.1) 1 9.3 (0.9) 2 9.2 (0.9) 3 9.3 (0.9) 4 9.2 (0.9) 5 9.2 (0.9) 1 9.2 (0.9) 2 9.1 (0.9) 3 9.1 (0.9) 4 9.2 (0.9) 5 9.0 (0.9) 1 9.0 (0.9) 2 9.0 (0.9) 3 9.0 (0.9) 4 8.9 (0.9) 5 9.0 (0.9)

N = 11,310−11,293 (the notation 1 to 5 under the Income and Parent Education columns denotes quintiles 1 = top and 5 = bottom quintile; and parent education levels, 1 = no educational qualifications to 5 = qualifications at postgraduate degree level) Notes: A series of Analyses of Variance (ANOVAs) were conducted. Statistically significant differences emerged between gender and these measures of wellbeing (Moods and Feeling, Self- Concept, Life Satisfaction) with regard to the frequency of gaming. No significant differences were found between gaming and these wellbeing measures and (i) parent income and (ii) parent education

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less satisfaction with life; lower self-image and negative feelings and moods. They were also more likely to report self-harm. Specifically, nearly two thirds of girls and a third of boys reported that they were not satisfied with their life; nearly four times more girls than boys reported low self-concept; and around a quarter of boys and three quarters of girls reported negative mood and feelings and attempts at self-harm. In considering these findings through the lenses of digital play, amongst 14-year-olds who reported to spend 5 to 7 hours or more daily on social media, twice as many reported to have self-harmed during the past 6 months. In contrast, over half of young people who did not report self-­ harm spent less than 2 hours on gaming or on social media. The number of young people who reported self-harm and those who did not was roughly equal for those spending 5 to 7 hours or more on gaming. It appeared that the number of 14-year-olds reporting self-harm increased for those who spent many hours on social media but not for those who spent similar amounts of time gaming. Time spent on digital play had a differential effect on wellbeing in that it was found to associate with reduced wellbeing more strongly than time spent on gaming. A decrease in wellbeing, in other words, was much steeper for young people who used social media than for those who gamed. In looking across all measures of wellbeing, both boys and girls reported more negative feelings and moods, less positive self-image, lower life satisfaction and a higher level of victimisation as they spent more time on social networking sites and computer gaming. The gender differences however were steeper for girls. Consistently, findings from a recent analysis of the MCS dataset revealed stark differences in the number of teenage girls and boys who reported self-harm, with girls being three times more than boys (Hartas 2019). Specifically, the previous study found that one in ten teenagers reported depressive characteristics and low mood and, among them, teenage girls were significantly more likely to experience low mood (78% vs 22%). Similar trends were seen in their self-reports of happiness and self-­image. A quarter of teenagers felt completely unhappy, with girls nearly doubling the rate (63% vs 37%). Over a quarter of young people reported a low sense of their own value including poor self-image, with girls being over three times more likely than boys (79% vs 21%) (see Hartas 2019 for discussion). Consistently, a large body of research studies (Devine and Lloyd 2012; Kelly et al. 2018; Koles and Nagy 2012; Pantic et al. 2012; Royal College of Paediatrics and Child Health 2018; Twenge 2017) found the

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relationship between increased social media use and reduced wellbeing to be stronger for teenage girls who fared less well across measures of wellbeing. Kelly and colleagues also found associations between social media use and depressive symptoms, with the associations being stronger for girls, who were more likely to face online harassment, low self-esteem and body image, largely explaining these associations. Likewise, Devine and Lloyd showed that engagement with social networking is likely to decrease overall psychological wellbeing in girls (2012). This study also reflects these trends. Teenage girls spending 5–7 hours or more on social media reported, on average, more negative feelings and moods, lower self-­ concept and life satisfaction, and a higher level of victimisation. Teenage girls fare less well than boys and this has important implications regarding gender equality especially as, globally, concerns about young people’s mental health are on the rise (e.g., International NGO 2013; WHO 2002). In the UK, the Mental Health of Children and Young People in Great Britain study (2004) found that 1 in 10 children aged 5 to 16 years have a diagnosable mental disorder, with a higher prevalence found in boys. Ten years later, the Mental Health Difficulties in Early Adolescents study (Finch et  al. 2014) compared two cross-sectional groups aged 11 and 13 and found an increase in self-reports of emotional problems among girls. Specifically, teenage girls were found to report lower life-satisfaction, self-esteem, emotional wellbeing and resilience compared with younger girls whereas boys’ measures remained stable. Girls and women are at higher risk than boys and men for mental health difficulties and many studies have corroborated the rise in depressive symptoms and self-harm in girls (e.g., Girlguiding 2015; Twenge 2017; Torikka et  al. 2014; WHO 2002). And these gender differences are reflected in (or magnified by) their digital play. More recently, the Royal College of Paediatrics and Child Health reported moderately strong associations between social media use and depressive symptoms, particularly in girls, but evidence for an association between social media use and behaviour problems, anxiety, hyperactivity and inattention and poor self-esteem was weak (2018). The link between victimisation, mostly in the form of bullying, and wellbeing is also seen in other studies whereby victimisation, understood as an ‘intention to cause physical or emotional harm’, was found to associate with depression, self-­ harm and suicide (Espelage and Holt, 2013). Victimisation does not allow space for conflict resolution necessary to build resilience and autonomy in

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young people. And this can have serious consequences for teenagers who already report reduced wellbeing. Consistently with previous research (e.g., Pantic et al. 2012; Kelly et al. 2018; Twenge 2017), the findings from the MCS and US analyses showed a graded relationship between hours spent visiting social networking sites and wellbeing. There is however another body of research that paints a different picture (e.g., Ito et  al. 2009; Przybylski and Weinstein 2017; Reich et al. 2012). In a study by Przybylski and Weinstein, online social networking was found to increase social support and self-esteem and reduce social anxiety and isolation especially for young people who face marginalisation or are different in terms of disability (2017). The authors suggested a non-linear relationship between quantity of social media use and wellbeing. Specifically, in a large-scale, representative survey of English youth, associations between digital media use and mental wellbeing were described by quadratic functions, which support a “Goldilocks Hypothesis”: moderate frequency of social media use was not found to be ‘intrinsically harmful and may even be advantageous in a connected world’ (Przybylski and Weinstein 2017, 204). Moreover, studies have shown positive outcomes of using online platforms for interest-driven learning (Ito et al. 2009), self-expression and reaching out and friendships maintenance (Reich et al. 2012), and self-disclosure and a sense of belonging to a community (Davis 2012). More recently, in a study based on approximately 20,000 telephone interviews with parents, the relationship between their children’s technology use and wellbeing was examined (Przybylski and Weinstein 2019). Children’s wellbeing was defined along attachment to caregiver, emotional resilience, curiosity and positive affect. The results revealed that limiting children’s digital device use is not necessarily beneficial for wellbeing. Family context and interactions and emotional bonds between parents and children were found to be more important than screen time per se. These studies suggest that it is not only time spent online but also the nature and quality of interactions teenagers have that matters as well as the social milieu within which they operate. I discuss teenage social, cultural and familial contexts and their relation to online and offline play in Chap. 4. Digital media offer access to spaces not controlled by adults and this is important considering that young people’s access to physical public spaces has been reduced over time. Clearly, the role of social media in 14-year-­ olds’ wellbeing is multi-faceted. Teenage girls and boys with negative feelings and moods and a diminished self-concept may be more drawn to

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social media for socialisation because they, compared to face-to-face interactions, offer a controlled setting (Lin et al. 2016). Conversely, teenagers who spend considerable amounts of time on social media subsequently may develop depressive characteristics due to limited exposure to real-life interactions which offer rich opportunities for empathy and relatedness and civic engagement (Pantic et al. 2012). Although in some cases social media support networking (Ellison et al. 2007), it is questionable whether such activities promote civic engagement, social trust and a real sense of community during teenagers’ peer interactions. Some online platforms are known to promote toxic social comparison propelled by unrealistic standards of beauty, airbrushed body images and ‘glamorous’ lifestyles, cyber bullying and, most importantly, a new form of consensus based not on debate and reasoned argument but on ‘likes’ and ‘favourites’ (Hartas 2019). Finally, more generally, social media may have a dampening effect on the development of a critical, less conformist self (Haidt 2017; Twenge 2017). Face-to-Face Peer Interactions and Wellbeing A 2016 report from Public Health England estimated that 6,95,000 children in England aged 5–16 years (i.e., 10% of all children in England) had a clinically significant mental health illness. The conditions reported include anxiety, depression, conduct disorders, self-harm and suicidal feelings. One of the explanations the authors offered was the reduction in opportunities for free, adult unsupervised play whereas children engage in self-initiated activities and test skills about self-regulation, how to deal with risk, challenge themselves and test their own limits (Brussoni et al. 2015). A systematic review by Brussoni and colleagues consistently found that free play contributes to children’s physical and mental health, arguing that risky encounters in face-to-face peer interactions and play allow children to experience positive stress which has been found to increase resilience and self-regulation (2015). To better understand trends with regard to 14-year-olds’ face-to-face peer interactions and wellbeing, I examined associations between interacting with friends (unsupervised in a typical school day and out of school in weekends) and self-reported life satisfaction, feelings and moods, self-­ concept (including self-image) and happiness. Among 14-year-olds who saw their friends unsupervised most days, a roughly equal split was found in the percentage (around a third) of teenagers who are happy and those

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who are not. Likewise, a third of young people with a positive and a third with a negative self-concept reported to see their friends most weekends. The same picture emerged with feelings and moods in that as many (around a third) 14-year-olds who reported positive as those who reported negative feelings and moods played with their friends most weekends. Amongst those who played with friends most school days, around three quarters stated they are satisfied with life. If we focus on the 14-year-olds who are not satisfied with life, most of them (over 60%) also played with friends most days whereas only 1 in 5 rarely played with friends. Roughly as many (around a third) 14-year-olds who are satisfied with life as those who are not reported to see their friends most weekends which suggests that many 14-year-olds interact with peers most days during the week and most weekends regardless of whether or not they reported to be satisfied with their life and to experience negative feelings and moods and low self-­ concept. The split between those who reported to be happy with their life and have high self-concept (around 60%) and those who did not is roughly equal amongst those who played with friends often. A slightly lower number of 14-year-olds who reported to be less happy and to have low self-­ concept (including self-image) played rarely with their friends. As many young people who reported positive as those who reported negative feelings and moods played with friends most days. In the same vein, there were no differences between the frequency with which 14-year-olds played with friends during the week and the weekend and self-reports of victimisation and self-harm. Across measures of life satisfaction, self-harm and victimisation, the number of 14 years old boys and girls who played with friends unsupervised most days as well as most weekends remained roughly the same. What Makes Teenagers Happier: Online or Offline Play? The findings about online and offline peer interactions and wellbeing in 14-year-olds present an interesting picture. Both boys and girls reported more negative feelings and moods, less positive self-image, lower life satisfaction and a higher level of victimisation and self-harm as they spent more time on social networking sites and online gaming. However, this was not the case for face-to-face interactions in that, roughly equal numbers of young people who played with friends most days and weekends reported positive and negative feelings and moods, life satisfaction and happiness, victimisation and self-harm. In other words, among 14-year-olds who

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played with their friends frequently, the split between those who reported negative feelings, low life satisfaction and unhappiness and those who reported positive feelings, high life satisfaction and happiness was roughly the same. Although more frequent engagement with social media and gaming was found to associate with reduced wellbeing in 14-year-olds, this was not the case with frequent face-to-face interactions. Reduced wellbeing does not exist outside teenagers’ physical material life; however, mental health difficulties in 14-year-olds were highlighted as their engagement with the digital world became more frequent and this trend was pronounced for 14-year-old girls. This is consistent with recent findings from the Youth Index (2019) which was based on a YouGov survey on attitudes and wellbeing of teenagers. It showed that just under half of young people who often use social media now feel more anxious about their future when they compare themselves to others on sites and apps such as Instagram, Twitter and Facebook. Likewise, around half agreed that social media makes them feel ‘inadequate’. Over half (57%) thought social media creates ‘overwhelming pressure’ to succeed and 60% found it difficult not to compare their life to others online. Nearly 1 in 5 young people disagreed with the statement ‘I find life really worth living’ and more than a quarter disagreed that that their life has a sense of purpose. There were positive feelings expressed about social media too. A third of people said being on social media makes them feel they have a voice for their generation and influence positive change in society, and more than a quarter said it made them happy. Moreover, four out of ten young people said they feel more confident online than they do in person, rising to almost half among 16–18-year-olds. However, playing sport (44%), earning enough money to live how they want (62%) and spending time with family (77%) were more likely to associate with happiness. Clearly, the findings on the associations between online interactions and wellbeing are mixed. Nevertheless, many commentators have argued that the observed spike in depression and anxiety among teenagers, girls in particular, appears to have coincided with an increase in social media use with girls being the primary consumers (Haidt 2017; Shensa et al. 2017; Twenge 2017). Notwithstanding, reduced wellbeing is not brought up by technology alone; it reflects society’s ills, most likely emboldened and magnified by technology which removes ‘checks and balances’ that usually exist in traditional communities, shaped by norms, customs and cultures. Virtual encounters bring to the fore, in an unmediated manner, real or perceived societal threats. Reported increases of cyber-bullying, sexual

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abuse and the sheer amount of time children spend on sedentary activities are all examples of this threat (Livingstone and Bulger 2013). Finally, digitally enabled social networks diminish diversity in teenager’s social interactions primarily through the creation of ‘echo chambers’, which may erode their ability to think for themselves. Digital media trigger instant responses to complex societal issues and encourage endless comparison of self-worth. Post truths, lies and propaganda increase confusion in an already fragmented world, testing young people’s concept of truth as well as their capacity for being critical. This has the potential to degrade civil discourse and propel mistrust in the public sphere and, ultimately, work against real communities by creating fake communities that appear to be defined along similar principles. The digital world has the potential to redefine human interactions by removing subtlety and nuance and, also, as Marina Gorbis argued, ‘serendipity and ambiguity from our interactions. And this ambiguity and complexity is what is the essence of being human’ (2018, 1). Virtual encounters amplify existing confirmation biases and sensationalist interactions that lack nuance of understanding, promoting tribalism and devolution of open societies and pluralities. In online interactions, young people could be sacrificing independence, privacy and power over choice and convenience.

References Abbott-Chapman, J., & Robertson, M. (2009). Adolescents’ favourite places: Redefining the boundaries between private and public space. Space and Culture, 12(4), 419–434. Angold, A., Costello, E.  J., Messer, S.  C., Pickles, A., Winder, F., & Silver, D. (1995). The development of a short questionnaire for use in epidemiological studies of depression in children and adolescents. International Journal of Methods in Psychiatric Research, 5, 237–249. Black, J., Castro, J. C., & Lin, C.-C. (2015). Youth practices in digital arts and new media: Learning in formal and informal settings. New  York: Palgrave Macmillan. Booker, C., Yvonne, J. K., & Sacker, A. (2018). Gender differences in the associations between age trends of social media interaction and well-being among 10–15 year olds in the UK. BMC Public Health BMC, 18, 321. Brussoni, M., Gibbons, R., Gray, C., Ishikawa, T., Beate, E., Sandseter, H., … Tremblay, M. C. (2015). What is the relationship between risky outdoor play and health in children? A systematic review. International Journal of Environmental Research and Public Health, 12, 6423–6454.

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Cash, S., Thelwall, M., Peck, S., Ferrell, J., & Bridge, J. (2013). Adolescent suicide statements on MySpace. Cyberpsychology, Behavior and Social Networking, 16, 166–174. Davis, K. (2012). Friendship 2.0: Adolescents’ experiences of belonging and self-­ disclosure online. Journal of Adolescence, 35(6), 1527–1536. Debord, G. (1958). Definitions. Internationale Situationniste #1 (Paris, June 1958). Translated by Ken Knabb. Devine, P., & Lloyd, K. (2012). Internet use and psychological well-being among 10-year-old and 11-year-old children. Child Care in Practice, 18(1), 5–22. Diener, E. D., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71–75. Ellison, N.  B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computing Communication, 12(4), 1143–1168. Espelage, D., & Holt, K. (2013). Suicidal ideation and school bullying experiences after controlling for depression and delinquency. Journal of Adolescent Health, 53, 27–31. Finch, L., Hargrave, R., Nichols, J., & van Vliet, A. (2014). Measure what you treasure: Well-being and young people, how it can be measured and what the data tell us. New Philanthropy Capital. Retrieved May 28, 2014, from http:// www.thinknpc.org/ publications/measure-what-you-treasure/. Freeman, C., van Heezik, Y., Stein, A., & Hand, K. (2016). Technological inroads into understanding city children’s natural life-worlds. Children’s Geographies, 14(2), 158–174. Girlguiding. (2015). Girls’ Attitude Survey 2015. Retrieved March 1, 2016, from http://new.girlguiding.org.uk/latest-updates/making-a-difference/ girls-attitudes-survey-2015. Gorbis, M. (2018). Without social organizations, social technologies will eat us alive. Accessed from https://boingboing.net/2018/11/26/without-socialorganizations.html on 26th October 2020. Haidt, J. (2017). The unwisest idea on campus: Commentary on Lilienfeld (2017). Hartas, D. (2019). The social context of adolescent mental health and wellbeing: Parents, friends and social media. Research Papers in Education, 1–19. https:// doi.org/10.1080/02671522.2019.1697734 Heydenberk, R. A., & Heydenberk, W. R. (2017). Bullying reduction and subjective wellbeing: The benefits of reduced bullying reach far beyond the victim. International Journal of Wellbeing, 7(1), 12–22. International NGO. (2013). Council on violence against children. Violating children’s rights: Harmful practices based on tradition, culture, religion or superstition. Geneva. Ito, M., Baumer, S., Bittanti, M., Boyd, D., Cody, R., Herr-Stephenson, B., … Tripp, L. (2009). Hanging out, messing around, and geeking out: Kids living and learning with new media. Cambridge, MA: The MIT Press.

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Jorgensen, B., & Stedman, R. (2006). A comparative analysis of predictors of sense of place dimensions: Attachment to, dependence on, and identification with lakeshore properties. Journal of Environmental Management, 79(3), 316–327. Kelly, Y., Zilanawala, A., Booker, C., & Sacker, A. (2018). Social media use and adolescent mental health: Findings from the UK Millennium Cohort Study. E Clinical Medicine, 6, 59–68. Koles, B., & Nagy, P. (2012). Who is portrayed in Second Life: Dr. Jekyll or Mr. Hyde? Journal of Virtual Worlds Research, 5(1), 1–17. Lin, L. y., Sidani, J.  E., Shensa, A., Radovic, A., Miller, E., Colditz, J.  B., … Primack, B. A. (2016). Association between social media use and depression among U.S. young adults. Depression and Anxiety, 33(4), 323–331. https:// doi.org/10.1002/da.22466 Livingstone, S., & Bulger, M. (2013). A global agenda for children’s rights in the digital age. Recommendations for developing UNICEF’s research strategy. London: The London School of Economics and Political Science/ UNICEF Office of Research—Innocenti. MacFarlane, R. (2003). The mountains of the mind: A history of a fascination. London: Granta. Matthews, H., Limb, M., & Percy-Smith, B. (1998). Changing worlds: The microgeographies of young teenagers. Tijdschr voor economische en Soc geografie, 89(2), 193–202. Owens, P. E. (1988). Natural landscapes, gathering places, and prospect refuges: Characteristics of outdoor places valued by teens. Children’s Environment Q, 5, 17–24. Pantic, I., Damjanovic, A., Todorovic, J., Topalovic, D., Bojovic-Jovic, D., Ristic, S., & Pantic, S. (2012). Association between online social networking and depression in high school students: Behavioral physiology viewpoint. Psychiatria Danubina, 24, 90–93. Przybylski, A. K., & Weinstein, N. (2019). Digital screen time limits and young children’s psychological well-being: Evidence from a population-based study. Child Development, 90(1), e56–e65. Przybylski, A. K., & Weinstein, N. A. (2017). Large scale test of the Goldilocks hypothesis: Quantifying the relations between digital screens and the mental well-being of adolescents. Psychological Science, 28(2), 204–215. Raymond, C. M., Giusti, M., & Barthel, S. (2017). An embodied perspective on the co-production of cultural ecosystem services: Toward embodied ecosystems. Journal of Environmental Planning and Management, 61, 778–799. Reich, S. M. (2016). Connecting offline social competence to online peer interactions. Psychology of Popular Media Culture. https://doi.org/10.1037/ ppm0000111.

1  TEENAGE PLAY AND PEER INTERACTIONS: VIRTUAL, SOCIAL… 

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Reich, S. M. (2017). Connecting offline social competence to online peer interactions. Psychology of Popular Media Culture, 6(4), 291–310. https://doi. org/10.1037/ppm0000111 Reich, S. M., Subrahmanyam, K., & Espinoza, G. (2012). Friending, IMing, and hanging out face-toface: Overlap in adolescents’ online and offline social networks. Developmental Psychology, 48(2), 356–368. Rosenberg, M. (1965). Society and the Adolescent Self-image. Princeton, NJ: Princeton University Press. Royal College of Paediatrics and Child Health. (2018). Written evidence submitted to the House of Commons Science and Technology Committee (SMH0156). Samman, E. (2007). Psychological and subjective well-being: A proposal for internationally comparable indicators. Oxford Development Studies, 35(4), 459–486. Shensa, A., Escobar-Viera, C. G., Sidani, J. E., Bowman, N. D., Marshal, M. P., & Primack, B. A. (2017). Problematic social media use and depressive symptoms among U.S. young adults: A nationally-representative study. Social Science & Medicine. https://doi.org/10.1016/j.socscimed.2017.03.061 Sinclair, I. (1997). Lights out for the territory: 9 excursions in the secret history of London. London: Penguin Books. Sinclair, I. (2002). London orbital: A walk around the M25. London: Penguin Books. Statham, J., & Chase, E. (2010). Childhood wellbeing: A brief overview. Childhood Wellbeing Research Centre. Retrieved from http://www.cwrc.ac.uk/documents/CWRC_Briefing_paper.pdf. The Youth Index. (2019). Retrieved from https://www.princes-trust.org.uk/ about-the-trust/research-policies-reports/youth-index-2019. Torikka, A., Kaltiala-Heino, R., Rimpelä, A., Marttunen, M., Luukkaala, T., & Rimpela, M. (2014). Self-reported depression is increasing among socio-­ economically disadvantaged adolescents—Repeated cross-sectional surveys from Finland from 2000 to 2011. BMC Public Health, 14, 408. Twenge, J. (2017). Have Smartphones destroyed a generation? The Atlantic. Retrieved November 5, 2017, from https://www.theatlantic.com/magazine/archive. Ujang, N., & Zakariya, K. (2015). Place attachment and the value of place in the life of the users. Procedia Social and Behavioral Science, 168, 373–380. Viner, R., Ozer, E. M., Denny, S., Marmot, M., Resnick, M., Fatusi, A., & Currie, C. (2012). Adolescence and the social determinants of health. Lancet, 379, 1641–1652. Weinstein, E. (2018). The social media see-saw: Positive and negative influences on adolescents’ affective well-being. New Media & Society, 20(10), 3597–3623. World Health Organisation. (2002). Gender and mental health. Department of Gender and Women’s Health; Department of Mental Health and Substance Dependence, pp. 1–4. Geneva: WHO.

CHAPTER 2

Free and Guided Play and Unequal Childhoods

Abstract  This chapter approaches teenage online and offline play through the lenses of social class, gender, ethnicity and disability. The frequency of digital and face-to-face play and participation in extra-curricular activities was examined across diverse groups in terms of income, parent education and occupational status, gender, ethnicity and disability. Inequalities in children’s life are reflected in their capacity to access outdoor and indoor play opportunities. Analyses showed that adult—organised play and activities and also digital play and unsupervised face-to-face peer interactions differed along social class lines. Although roughly similar numbers of teenagers across diverse socioeconomic groups participated in digital play, teenagers from economically well-off families were more likely to participate in structured play such as extra-curricular activities. Also, similar numbers of teenage boys and girls engaged in digital play, face-to-face peer interactions and extra-curricular activities. Gender differences emerged when the type of digital play was considered, with boys preferring gaming and girls visiting social networking sites. Teenage online and offline play varied across different ethnic groups, with White teenagers spending more time with digital play and meeting friends face-to-face than any other ethnic group. Finally, teenagers with poor behaviour and emotional difficulties were more likely to spend an excessive amount of time online as did those who experienced bullying. Clearly, inequality, including gender inequality, and disability shape teenage online and offline play.

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Keywords  Social class, Gender, Ethnicity, Disability, Inequality

In this chapter I examined play, including digital play, face-to-face peer interactions and guided play, through the lenses of social class, gender, ethnicity and disability (i.e., social emotional and behavioural difficulties). These markers of difference have been found to influence young people’s social experiences and life chances, reflecting and reproducing their unequal childhoods. Inequalities in children’s life influence their capacity to access outdoor and indoor play opportunities. Children’s play is differentiated by social group, with middle-class, female, younger and minority ethnic children likely to face greater restrictions (Karsten 2005; Mackett 2013; Tucker and Matthews 2001). There is a consensus that children and young people now face greater restrictions on meeting friends in public spaces and playing unsupervised than in previous generations (Holt et  al. 2013; Loebach and Gilliland 2016; Witten et al. 2013). In an era of parental anxiety, more parents drive their children to different places to meet other children and partake in enrichment activities (Carver et al. 2013; Schwanen 2007) or offer paid-­ for structured activities, mostly through participation in extra-curricular clubs. Aside from the social capital accrued by families and the social reproduction that occurs at school, peer cultures also develop their own systems of inclusion and exclusion (Pasquier 2008). The criteria for exclusion and inclusion are socioeconomically defined, gendered, and race— coded in that teenage peer interaction and play reproduce how they perceive and are perceived by others (Winkler Reid 2015). Technologies can enrich children’s lives by helping them to overcome physical, socio-economic and cultural barriers as well as obstacles posed by gender, disability or ethnic differences. Young people can maintain relationships with friends and family members located in different cities or overseas digitally (Longhurst 2013) and can also explore virtual landscapes and interact with peers from different backgrounds around the world (Ash and Gallacher 2011). Social media use or online gaming could help children maintain friendships unencumbered by geographical distance; this is particularly important for children with disabilities as well as children of minority ethnic backgrounds in the era of mass migration.

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Social Class and Online and Offline Play Social class differences in the form of income inequality and child poverty are particularly topical, with UK levels increasing for the first time in almost two decades. In 2017, the Social Mobility and Child Poverty Commission compared the prospects of UK children from poorer backgrounds in terms of academic attainment, future employment and standard of living, demonstrating considerable differences in terms of life chances (Social Mobility and Child Poverty Commission 2017). Poverty rates in the UK are consistently high amongst children and their parents, with 30% of children now living in poverty. Of the 12 million working-age adults and children in poverty, 8 million live in families where at least one person is in work (JRF Analysis Unit 2017). Young people are realising that employment is no longer leading to lower poverty. Changes to benefits and tax credits for working-age families, rising inflation and high housing cost are reducing the incomes of many of those on low incomes, affecting young people most profoundly (Pickett and Wilkinson 2007, 2015). Poverty and disadvantage assume a crucial role in children’s social development. Both income inequality and poverty have been consistently linked to the quality of peer interactions and social relationships in general (Pickett and Wilkinson 2015). The social and economic context of families shape young people’s play. Children in households with low income tend to display more difficulties with social behaviour than their economically better-off peers. Family income and parent education and the social and cultural capital accrued are likely to affect the frequency with which teenagers play electronic games and visit social networking sites, interact with friends face-to-face and engage in guided play and extra-curricular activities. Research has shown that children in families with low income and parents with low education have more electronic devices in their bedrooms and are higher screen media consumers and more infrequent readers (e.g., Cingel and Krcmar 2013; Gentile and Walsh 2002). Furthermore, socio-economic factors are likely to have differential effects on pre- and mid-teenage boys and girls and those with/without disabilities. In this context, one wonders to what extent play matters for young people’s social development considering the social and cultural constraints they and their families face and how these constraints shape their wellbeing and sense of their place in the world.

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Digital Play, Family Income and Parent Education and Occupational Status In examining teenage digital play through social class lenses, the frequency of digital play and gaming was analysed along parent education, parent occupation status and family income (Table 1). Measures of family income (taken from the UK whole sample of the MCS) were based on the Organisation for Economic Cooperation and Development (OECD) equivalised income quintiles, with 17.2% families being in the first quintile; 16.9% in the second quintile; 20.3% in the third quintile; 22.9% in the fourth quintile and 22.6% in the fifth (highest) quintile. Parent educational qualifications were measured on a spectrum of no qualifications to qualifications at a degree and higher degree level. Specifically, 6.4% of parents were at National Vocational Qualification (NVQ) level 1 (no academic qualifications); 26% in NVQ level 2 (GCSEs); 16.8% in NVQ level 3 (A-levels); 36.9% in NVQ level 4 (degree) and 13.9% NVQ level 5 (higher degree). Parent occupational status was measured along the following categories: professional / managerial (40%); intermediate (22%); semi-employed / self-employed (9%); low supervisory / technical (47%); and semi-routine / routine employment (25%). The findings on the associations between the frequency of digital play and parent occupational status showed that, amongst the managerial and professional classes, 16% and 11% of 14-year-olds visited social media sites and played computer games respectively for 5–7 hours or more daily. Amongst the intermediate self-employed, 18% and 13% and the Technical/ Semi-Routine and Routine categories, 22% and 17% of 14-year-olds respectively spent 5–7 hours or more daily using social media and gaming. These figures showed a slight increase in the percentage of young people spending many hours daily online on social media or gaming as parent occupational status became lower. Similar patterns in time spent online were observed with other proxies of socio-economic status, such as family income and parent education. Compared to families with income at the top quintile where nearly 13% and 10% of 14-year-olds reported to spend 5–7 hours or more on social media and gaming respectively, 23% and 17% of young people in the bottom quintile used social media and gamed for 5–7 hours or more. Likewise, 16% and 10% of young people with educated parents (compared to 25% and 19% of 14-year-olds whose parents have low educational qualifications) spent 5–7 hours or more on social media and gaming. These findings showed that nearly twice as many young people in families with low

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income and parent education used social media and gamed online for 5 to 7 hours or more daily. In contrast, the number of 14-year-olds who spent less than 2 hours on social media or gaming was roughly the same across parent education and income groups. The socioeconomic differences were highlighted when young people engaged with online activities excessively with the differences in numbers of young people being steeper when family income rather than parent education was considered. Consistently with previous analyses of the Understanding Society dataset, Booker et al. (2018) found associations between social position and social media interaction in that teenagers from families with lower education or income interacted more frequently on social media and, among girls, lower income was associated with more frequent social media interaction at age ten. Interestingly, families’ socioeconomic background seems to relate to not only the amount of time spent online but also adult perceptions of the usefulness of digital play. In a comparative ethnographic analysis of three middle schools that varied by social class and ethnicity, Rafalow found differences in how teachers perceived and responded to young people’s digital engagement (for play or learning purposes). At a school with a majority working-class Latino youth, young people’s digital engagement was seen as irrelevant or not useful to learning and social interactions; at a school with mostly middle-class Asian American youth, students’ digital involvement was seen as an obstacle to their learning and academic success; and at a private school with mainly wealthy White youth, students’ digital engagement was positioned as essential to their learning and school success (Rafalow 2018). The transformation of digital play into social and cultural capital necessary for socialisation, learning and school success was largely shaped by social class. As the findings from the present analyses showed, working-­ class teenagers tend to spend more hours on online activities than their economically better-off peers, accruing social and technological skills that may not be seen as important by their teachers or parents and thus less likely to be translated into learning. Face-to-face Peer Interactions, Extra-Curricular Activities and Family Income, Parent Education and Occupational Status I examined the frequency of face-to-face peer interactions and participation in parent-organised extra-curricular activities in relation to parent education, income and occupational status. Specifically, I drew on data

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from the MCS to delineate associations between young people’s socioeconomic reality and play and examined whether 14-year-olds in low-income families engage more in free rather than guided play, as well as the frequency of play-based learning in households with parents with low education and occupational status. Free play, including digital play, is thought to be more impoverished in impacting child life chances and social mobility than structured play activities such as extra-curricular activities favoured by middle-class parents. There is also a counterargument that free play is a cornerstone for children’s social behaviour development and wellbeing. The findings showed as many 14-year-olds (around 58%) in the highest as in the lowest income quintile played with friends most days whereas a smaller percentage, 15% in the highest and 23% in the lowest income group, rarely played with friends. Across income groups, a roughly equal number of 14-year-olds saw their friends most weekends although the percentage of young people who saw their friends unsupervised, most days, was higher in the bottom (42%) than the top (30%) income quintile. Although across income, roughly the same number of 14-year-olds played with friends often, the percentage of young people in the highest quintile who often played with friends was relatively smaller which suggests that fewer young people in middle-class families played with friends unsupervised most days. Likewise, roughly equal percentages of young people, (ranging from 56% to 64%) across parent education levels played with their friends most days. More young people (43%) with parents with low education than those with parents with degrees (32%) saw their friends most weekends. One explanation is that educated parents are more likely to spend time with their children during weekends engaging in parent-organised cultural and social activities whereas young people in households with parents with low education spend less time in organised activities and more time with their peers (Lareau 2003). The number of 14-year-olds playing unsupervised with friends most days was stable across different parent occupational status categories (i.e., managerial, intermediate, self-employed, low supervisory/semi-routine and routine) ranging between 60% and 65%. Similarly, across occupational status, near equal numbers of 14-year-olds played with their friends most weekends, with a slightly higher percentage (43%) of young people from the semi-routine routine/routine category compared to managerial occupations (33%) interacting with their friends most weekends. In sum, these findings suggest that, compared to families with parents with low

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education, occupational status and income, relatively fewer 14-year-olds see their friends often during the week or at weekends in economically better-off families with educated parents in professional/managerial occupations. An interesting picture emerged when probing parent organised play such as extra-curricular activities in 14-year-olds from different socioeconomic backgrounds. Compared to 14-year-olds whose parents have degrees (M = 29), those with parents with low education (M = 32), on average, engaged in extra-curricular activities less frequently. Likewise, compared to those with family income in the highest quintile (M = 29), teenagers in households with income at the bottom quintile participated in extra-curricular activities less often (M  =  31). Overall, young people whose parents’ education and family income were high engaged more frequently in extra-curricular activities than those in households with lower income and parent education. Finally, the same trends were found with parent occupational status in that 14-year-olds in families with parents in professional/managerial positions (M  =  32) engaged more frequently with extra-curricular activities than those with parents in semi-routine and routine employment (M  =  29). The findings about young people’s participation in extra-curricular or enrichment activities reflect unequal childhoods and teenage years. This inequality accentuates the debate on young people having limited access to public spaces in that they are also excluded from other forms of play, organised and supervised by adults, which they enjoy. Unequal Play and Peer Interactions Children have unequal childhoods and thus unequal opportunities to engage with play, especially extra-curricular activities. Across socioeconomic groups, a roughly equal number of young people played with their friends face to face frequently during the week and the weekends. Minor variations to this trend were observed in families with low income and parent education where slightly more teenagers saw friends most days and weekends. The same trend also emerged in households with parents in semi-routine to routine occupations (compared to parents in managerial occupations) whereby more 14-year-olds played with friends most weekends. Young people in families with high income and parent education and occupational status spent less time on seeing friends and more time on organised activities although the gaps in free and organised play between

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poor and better-off families are weak to modest. These trends reflect those in Lareau’s seminal study on unequal childhoods (2003) which found that children from different socioeconomic backgrounds are exposed to different play activities. Compared to their well-off peers, children living in poverty were more likely to engage in free play with peers, including digital play (e.g., social media) whereas children in middle-class families engage in structured activities with a strong focus on learning (e.g., extra-­ curricular activities, sports, library visits). Lareau’s study drew a distinction between aspects of ‘concerted cultivation’ (reflected in parent-structured activities/play-based learning) that are likely to predict educational aspirations and those that are not (2003). She found that middle-class parents were more active with ‘concerted cultivation’ whereby they engaged in organising activities and play for their children for the purpose of enhancing their learning. In contrast, working-­ class parents were more likely to engage in ‘natural growth’ in terms of ensuring their children’s basic needs (shelter and food) are met, with children spending more time interacting with other children than in organised, extra-curricular activities. This raises questions about the patterns of play in children who may not fit into middle-class lifestyles, especially children who experience disadvantage. It is important to stress that, in this study, socioeconomic differences in play were found to be modest. Since Lareau’s study in 2002, parents across socioeconomic groups increasingly spend more time with their children’s learning and social development. Over the last decade, the gap between middle-class and working-class children’s engagement with guided play and adult-organised activities has narrowed (Hartas 2011). Across socioeconomic groups, parents engage routinely with their children’s learning through structured activities such as reading, helping with homework and organising extra-curricular activities (e.g., sports) for their children (Dermott and Pantazis 2014; Hartas 2011, 2012). In an earlier study I found that parents across socioeconomic groups spend roughly the same amount of time interacting with their children although the quality of interaction may be different in that poverty makes parenting taxing and parents may have fewer resources to access to enhance their children learning (Hartas 2011). Furthermore, the findings suggest that both forms of play (free—face-­ to-­face and digital play—and guided play such as extra-curricular activities) are of interest to young people (as we see in Chap. 4, many teenagers participated in extra-curricular activities). This suggests that dualist

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distinctions between free and structured play are simplistic in that young people engage in both depending on the social constraints and affordances in their life. Although play choices were affected by social class as well as other markers of difference (gender, ethnicity and disability as discussed in the next sections), young people seemed to move seamlessly between indoor and outdoor, real and virtual, structured and unstructured peer interactions and play. Adult structured and resourced extra-curricular activities are not necessarily construed by young people as supervisory or potentially limiting of their choices. Their participation in extra-curricular activities should be seen through the lenses of social reproduction as class identities shape it. Working-class children had more free time to interact with friends due to having fewer opportunities to engage in paid-for extra-­ curricular activities. In considering Bourdieu’s (1986) theory of social and cultural capital, parents differ across various forms of capital which is likely to influence families’ affinity with technology/digital platforms and access to extra-­ curricular activities. Young people’s choices about the types of digital encounters (in term of content, proficiency in using digital devices or capacity to deal with upward comparisons and toxicity in social media) are likely to vary along parents’ access to different forms of capital. Young people from lower-income, less educated families may encounter less responsive parental involvement and a less stimulating physical environment (e.g., fewer digital resources at home), or less support in dealing with the negative influences of social media than children in more affluent families. Inequality affects children’s social development and wellbeing directly through social comparisons whereby children are aware of the social positioning of their families, and indirectly through having an impact on parents’ quality of life and wellbeing. Inequality may also work through epigenetic differences whereby the psycho-social environment affects gene expression during development (Cabieses et al. 2016). Inequality has been found to associate with increased status anxiety across socioeconomic groups; reduced solidarity and a tendency towards maximising self-­ improvement to develop a competitive edge. Teenagers are aware of their social positioning and social status and how they are perceived by their peers. Status differentiation has been found to impact on children’s peer interactions in that children were less likely to find their peers kind and helpful in unequal rich countries (Pickett and Wilkinson 2017). Moreover, Elgar and colleagues examined inequality and bullying in adolescents in

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different countries and found a strong relationship between income inequality and bullying, highlighting the impact of inequality on peer-­ directed violence (Elgar et al. 2016). Social class affects peer interactions along the lines of respect, solidarity and social recognition, constituting less well-off young people as having a lesser social value.

Gender and Online and Offline Play Gender is a social structure that shapes young people’s lived experiences, including the norms, goals and expectations they bring to their social relationships (Rose and Rudolph 2006). A study by Braun and colleagues showed that gender played a role in pre-teens’ choice of friends, with children choosing peers who are similar in terms of gender and engagement in gender-typed activities (2016). In the same study, children often cited a masculine outlook and characteristics as reasons why they liked their peers, and feminine behaviours as reasons why they did not like them. It appears that feminine characteristics and behaviour were likely to be devalued raising important questions about the ways in which dominant views about femininity and masculinity are likely to influence peer interactions and relationships. Among girls, friendships tend to be conducted ‘face to face’ focusing on emotional self-disclosure, while male friendships are conducted ‘side by side’, focusing on activities centred on common interests. Moreover, girls tended to prefer dyadic relationships rather than participation in larger, hierarchically structured groups. Boys focused more than girls on matters of dominance and maintenance of social status and have larger and more integrated social networks than girls (Gillespie et al. 2015). In a meta-analysis, Hall found that girls showed higher expectations of ‘symmetrical reciprocity’, linked to trust, loyalty and commitment from their peer interactions (2011). They were also more likely than boys to value intimacy, self-disclosure and empathic understanding and affective communication in terms of talking about emotions. Hall also found boys to be more likely to consider social status as an important feature of peer interactions, although both boys and girls were equally interested in sharing activities and companionship (2011). In considering the salience of gender, online and offline play and peer interactions are gendered processes of socialisation. In the MCS sample, there were 50.1% boys and 49.9% girls. In probing gender differences in the frequency with which 14-year-olds played, roughly equal numbers of boys and girls engaged in digital play; played

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unsupervised with friends face-to-face, most days and weekends; and participated in extra-curricular activities organised by their parents. Gender differences were revealed in the type of online encounters young people had, with boys preferring gaming and girls using social media. Specifically, twice more girls than boys spent 5 to 7 hours or more visiting social networking sites, whereas over four times more boys than girls spent 5 to 7 hours or more on gaming in a typical day. Nearly twice as many girls as boys played console games less than 1 hour, but a gender reversal occurred in that over three times and over seven times more boys than girls played games 1–3 hours and 4–7 hours or more respectively. A roughly equal number of boys and girls spent less than an hour visiting social networking sites. Gender differences appeared when teenagers spent 4 to 7 hours or more online, and in the type of digital engagement (social media, or gaming). In contrast, near equal numbers of girls and boys interacted frequently with their friends unsupervised and participated in extra-curricular activities. Although as many girls as boys engaged face to face, the dynamics of their interactions are likely to be different. Indeed, the structure and nature of peer interactions and friendship networks are often characterised by gender differences (Stehlé et al. 2011). Girls tend to operate in smaller networks that consist of emotionally intimate relationships, while boys surround themselves with larger friendship groups characterised by joint participation in extra-curricular activities (Perry and Pauletti 2011, 6). Furthermore, the gender differences regarding digital play are consistent with those emerging from previous surveys of children which routinely find that boys are more likely than girls to play online games with people they do not know or have met before (Rideout et al. 2010) and play for longer (Beavis et al. 2015; Santaliestra-Pasías et al. 2014). Girls Online Consistently with the findings from the MCS analyses, twice as many girls as boys (11% of girls compared to 5% of boys) have been found to spend over 3 hours visiting social networking sites (Office for National Statistics 2015). Girls spend more time on social media than boys, and thus they are more likely to encounter challenges as diverse as cyberbullying, upward comparisons and body shaming and everyday sexism. Socialisation pressures through body image control to be expressly feminine, along with

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post-feminist career and role aspirations influenced by misogynistic attitudes are associated with deterioration in teenage girls’ mental health (Shensa et al. 2017). Girls are also exposed to earlier sexualisation (APA 2007) through peer pressure and influence from female role models in pop culture and social media. Issues related to digital play (i.e., social media use) and gender inequality have become particularly prominent lately considering the rise in suicide rates among girls. Although suicide rates have increased for both sexes, three times as many 12–14-year-old girls killed themselves in 2015 as in 2007, compared with twice as many boys (Girlguiding 2015; Twenge 2017). A combination of psychological, economic and social factors (e.g., lack of control or power, gender inequality) is likely to be responsible for this difference (e.g., Blau et al. 2006; Branisa et al. 2014; International NGO 2013). All these studies agree that there is ‘something deeply worrying about girls’ wellbeing’ (Finch et al. 2014, 8). Social media has become an inextricable part of teenage girls’ life. They can be a force for good, but they also have the potential to augment existing gender stereotypes and inequality. Gender inequality is the result of human behaviour at a systemic level and influences how people behave and interact through norms and values and codes of conduct that find expression in traditions and cultural practices. The distribution of power between men and women in the private and public spheres is unequal and this constrains women’s opportunities and their capabilities to live the life they value (Sen 1999). Thus, to understand the basis of gender inequality in young people’s peer interactions, we need to understand how social structures such as social media influence behaviour as they frame gender-­ relevant meanings which may form the basis of gender roles and stereotypes.

Ethnicity and Online and Offline Play Children and young people from different ethnic groups are likely to experience online and offline peer interactions differently. Opportunities for accessing indoor and outdoor play spaces and levels of independent mobility vary by ethnicity (Roe 2018; Phoenix and Husain 2007) mostly due to differences in parental styles and social norms across different ethnic groups. Ethnic minority groups not only live disproportionately in substandard, overcrowded housing but they also have reduced access to outdoor recreational opportunities, including poorer access to urban parks

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and poorer quality parks (Roe 2018). Accounting for the intersectionality between gender and ethnicity, O’Brien et al. (2000) found that both have an impact on how much children feel part of their local neighbourhoods, with Asian girls being allowed out on their own less often than other children. Archer (2003), likewise, found that Asian Muslim young people interpreted gendered approaches to outdoor play as encouraged by parents’ anxiety about racist harassment and attacks. While parents from certain ethnic groups impose restrictions because of gendered cultural reasons, the issue of neighbourhood safety from racist attack is a key concern for many parents. A qualitative study in the UK by Chahal and Julienne (1999) found that parents whose children had suffered racist harassment or attacks did not allow them the freedom to move about the neighbourhood by themselves. The formation and maintenance of friendships, the dynamics of peer acceptance and rejection, and the factors that exacerbate or protect against aggression and victimisation are likely to be influenced by contextual factors such as the racial/ethnic composition of neighbourhoods and schools and everyday abuse associated with ethnic identities that are not represented in the dominant culture. Minority parents’ decisions about their children’s experience of outdoor and indoor play are mostly influenced not by the type of parenting (along the lines of permissive, authoritarian and authoritative parenting) as is often the case for White European/ American parents but by the lived experiences of racism in their communities. Peer relationships and friendship are often thought to have an informal social cohesive property, enabling young people from diverse social and ethnic backgrounds to mix socially (Hollingworth and Archer 2010). The literature around friendship across social and ethnic divides (e.g., Harris 2014) tends to focus more on adolescents and young adults than on pre-­ teenage children. Although little research exists on pre-adolescent friendships and peer interactions in ethnically diverse contexts, Iqbal and colleagues showed that peer interactions along ethnicity boundaries are not much different in light of other markers of difference such as social class (manifested through ‘materialities’ and possessions) which are more sharply felt (2017). Young people navigate diverse relationships in sophisticated ways through cultural openness and hybridity as well as cultural defensiveness (Harris 2014; Sedano 2012). Sedano in an in-depth study of ‘Moroccan’ and ‘Gypsy’ 7- to 13-year-old children in Andalucía argued that ‘ethnicity

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is not a divisive force in children’s friendships, rather it is the gradual construction of shared cultural patterns’ (2012, 382) that influences socialisation and friendship formation. The construction of shared cultural patterns was observed with migrant arrivals who were socially accepted after their initial ‘strangeness’ in the eyes of their classmates was no longer there (Sedano 2012). In examining ethnic differences in the hours 14-year-olds spent online visiting social network sites, around 50% White, 54% Mixed, 63% Indian, 62% Pakistani/Bangladeshi and 48% Black young people spent 0–2 hours, whereas around 20% of young people of White or Mixed heritage, 11% Indian, 14% Pakistani/Bangladeshi and 24% Black young people reported to spend 5 to 7 or more hours daily. A similar pattern emerges for the frequency of gaming with around 57% of White, 64% of Mixed heritage, 71% Indian, 67% Pakistani/Bangladeshi and 48% Black young people reported to spend 0–2 hours daily. Spending 5–7 hours or more daily gaming was reported by 15% White, 13% Mixed, 5% Indian, 8% Pakistani/ Bangladeshi and 26% Black young people. Compared to White and Black young people, a significantly smaller percentage of Indian and Pakistani/ Bangladeshi young people reported to spend 5 to 7 hours or more gaming or visiting social media. These ethnic differences reflect broader cultural differences in Asian communities where children are encouraged to socialise face-to-face with their extended families and community members. Consistently, in a study by Orben et  al. (2019), Asian adolescents were found to use social media less and their increase in use with age was lower than in White British adolescents. I also examined associations between the frequency of face-to-face peer interactions and ethnicity, revealing interesting results. Amongst young people who reported to often interact with their friends unsupervised and at weekends, respectively, 88% and 90% were White; 2% and 1% were of Mixed race; 2% and 1% were Indian; 5% were Pakistani/Bangladeshi; and 3% were Black. These findings suggest marked differences in how young people from diverse ethnic groups experience peer interactions, showing significantly fewer minority ethnic 14-year-olds spending time with their friends unsupervised by adults. Similarly, the frequency of participation in extra-curricular activities across different ethnic groups was found to vary. Although White young people were found, on average, to participate in extra-curricular activities more often than any other ethnic group, the differences were stark between White (M = 31) and Black (M = 27) 14-year-­ olds, with the latter group participating significantly less often.

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Social, Emotional and Behavioural Difficulties in Teenagers and Play In examining play in young people with disabilities, much research has focused on issues of accessibility of playgrounds and leisure facilities especially for children who are wheelchair bound. Pyer and Bush (2009) and McKendrick et al. (2000) found that families with disabled children tend to have less access to leisure places and activities compared to their typically developing peers. There seems to be a disproportionate absence of families with disabled children from play areas, leisure activities and nature and this is troubling given the importance of outdoor play for children’s socialisation and wellbeing. Few studies (with the exception of Orben et al. 2019) have examined access to play for children and young people who have invisible disabilities, especially disabilities likely to impact on social development and social behaviour. For this book, to examine the interplay between disability and play, I focused on play and peer interactions (both online and offline) in young people who were reported by their parents to display social emotional and behavioural difficulties (e.g., hyperactivity, peer problems, emotional difficulties) and bullying because the implications of poor behaviour are wide ranging for peer interactions, friendships and wellbeing. For instance, children who are hyperactive are likely to present antisocial behaviour as teenagers and adults (Mohr-Jensen and Steinhausen 2016). Similarly, children with conduct problems such as stealing, telling lies, bullying, are more likely to display problems with moderating their behaviour, interacting with their peers and have an overall poor mental health (Berkout et  al. 2011). Also, children with emotional problems (e.g., anxiety, worry, social withdrawal) face difficulties with peer relationships and forming friendships. In contrast, children who were thought to display prosocial behaviour in terms of being cooperative and empathic in their interactions with others are more likely to engage in positive relationships and have friends (Eisenberg et al. 2006). To this end, I analysed MCS data collected via the Strengths and Difficulties Questionnaire (SDQ) (Goodman et al. 2000), which consists of five scales with five items each: Emotional Symptoms, Conduct Problems, Hyperactivity, Peer Problems and Prosocial (cooperative behaviour). In each subscale, scores for each of the five items (e.g., ‘often seems worried’, ‘considered of others’ feelings’, ‘easily distracted’) were summed, giving a range of 0–10, and the total difficulties score, which is the sum of

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all problem SDQ domains (i.e., Emotional Symptoms, Conduct Problems, Hyperactivity and Peer Problems), had a range of 0–40. The SDQ has a good test-retest reliability of 0.85 (Goodman et al. 2000). The questionnaire was completed by the young people’s parents. The mean and standard deviation for Emotional problems is M = 2.9, SD = 2.5; for Conduct Problems, M = 7.9, SD = 2.1; for Hyperactivity/ Inattention, M = 15.73, SD = 3.04; for Prosocial, M = 7.72, SD = 2.1; and for Total Difficulties, M = 40.45, SD = 7.1. Social, Emotional and Behavioural Difficulties, Prosocial Behaviour and Digital Play I examined associations between hours spent online gaming and using social media and young people’s social behaviour (internalising and externalising behaviour difficulties and prosocial behaviour). As prosocial behaviour increased, young people were less likely to spend 4 to 7 or more hours playing games or visiting social networking sites. The reverse was observed for behaviour difficulties in that as externalising behaviour difficulties (e.g., hyperactivity, peer problems, conduct problems) increased, teenagers were more likely to spend 5–7 hours or more gaming and using social media. Although the associations were modest, young people with behavioural and emotional difficulties were more likely to spend excessive time online, whereas those with prosocial behaviour spent less time. Although bidirectional, these associations are not causal and thus we cannot determine whether teenagers who already have behavioural and social difficulties are more likely to spend excessive amounts of time online daily, or whether spending many hours online triggers poor behaviour and negative emotions. Previous studies on adolescent ratings of behaviour found that the emotional symptoms subscale of the SDQ was associated with sedentary behaviour for girls but not for boys. Verduyn and colleagues compared active and passive social media interactions showing that the degree of activity or passivity may be linked with social emotional wellbeing, social capital and upward comparison (2017). Orben and colleagues employed parallel growth models that showed significant gender differences. Worse social emotional ratings were associated with greater social media interaction at age ten and the changes over time were also significant for girls. The authors found that social behaviour at older ages among girls was associated with how much they interacted on social media at age ten, but

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this was not the case for boys. This is one of the first studies to show such stark differences between social media interaction and social behaviour in boys and girls. Indeed, and consistently with a recent study by Hartas (2019), associations between SDQ measures, gender and age showed that while socio-emotional difficulties decreased as boys move from pre- to mid-adolescence the reverse was true for girls (Orben et al. 2019). For young people who are different in terms of disability or special educational needs, technology-mediated social experiences have the potential to be facilitative in supporting communication and social interactions. Digital play offers an alternative social reality and space for peer interactions that are perhaps more welcoming and less judgemental for young people with disabilities. In this study, because the focus of the analyses was on the frequency of digital play, it is difficult to deconstruct what was about digital play, social media, that associated with poor behaviour and emotional difficulties. In the literature on social, emotional and behavioural difficulties, children who were rated high on externalising behavioural problems such as hyperactivity or conduct problems appeared to engage in independent outdoor play more often (e.g., Aggio et al. 2017). Outdoor play has been an important strategy to encourage children with hyperactivity to engage in physical activity to help them with self-regulation. Furthermore, it is established that higher levels of physical activity can decrease the odds of developing depression in children (Korczak et  al. 2017). Thus, taken together, outdoor play and peer interactions may be useful means by which children with externalising or internalising behaviour problems socialise and gain health benefits which may potentially have a protective effect on their wellbeing. Unsurprisingly, lower levels of prosocial behaviour were associated with higher levels of independent outdoor play. It is likely that children with prosocial behaviour spend most of their time in helping others or volunteering whereas those with low prosocial levels spend most of their concessionary time outdoors playing unsupervised. The social geographies of disability intersect with other markers of difference (e.g., age, gender, social class, ethnicity and parenting cultures), often magnifying inequality in childhood experiences during social interactions, predominantly in public spaces (Holt 2010). Holt used the notion of ‘embodied social capital’ to investigate intersections between physical landscapes, social spaces and individuals with disability. For Holt, ‘embodied social capital’ refers to ‘powerful norms and values embedded in everyday practices within specific social networks’ that frame discourses on

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disability, exclusion and identity (2010, 26). Everyday practices that trigger exclusion in young people with disabilities occur across different social material spaces, when playing with friends out of school or during extra-­ curricular activities. The presence of markers of difference in public spaces were also articulated in Ryan’s auto-ethnographic studies, specifically of the ways in which “small, almost unremarkable” (2005, 73) social occurrences (for example, stares by others) when children with disability are in public spaces enhance children’s sense of alienation and of not-belonging in these spaces. Ryan considered public spaces to be ‘saturated’ with implicit norms and judgements about ‘im/proper’ conduct, and thus ‘transgressive’ behaviours are stigmatised as ‘unacceptable’ (2008). In public spaces characterised by implicit norms, disability becomes ‘noticed’, ‘other’, ‘significant’, or ‘disruptive’ for onlookers. Interactions within public spaces that trigger feelings of hurt, embarrassment and stigma often result in spatial/social exclusions. Young people do not feel they belong in that they often feel the need to offer explanations about who they are, to constantly translate their existence into what onlookers can understand and accept, with their parents often feeling the need to ‘negotiate, mediate and manage’ their presence, with the onus placed on them to resolve stigma (2008, 732). This has significant implications for how outdoor space and interactions are experienced by young people with disabilities as a constant process of perception management to reverse the process of ‘othering’. Social, Emotional and Behavioural Difficulties, Play and Bullying Relationships with peers are of central importance to children throughout childhood and teenage years. They provide a source of companionship and entertainment, help in solving problems, personal validation and emotional support and contribute to identity development. In turn, children who enjoy positive relationships with peers appear to experience emotional wellbeing, positive beliefs about the self, and values for prosocial forms of behaviour and social interaction that are stronger and more adaptive than do children without positive peer relationships (Wentzel 2017). Bullying has been found to exert strong influences on children’s social and emotional development. Initial analyses of measures of bullying from MCS revealed interesting results. Specifically, in the MCS there are

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separate measures for perpetrator and victim, each based on two items: For perpetrator, ‘How often CM hurts or picks on other children?’ (4.6% once a week to once a month, 23.1% less often, 72.2% never) and ‘How often CM bullied other children online?’ (1.6% once a week to once a month, 13.5% less often, 84.9% never). For victim: ‘How often other children hurt or pick on CM?’ (15.3% once a week to once a month, 33% less often, 51.8% never) and ‘How often other children bullied CM online?’ (4.5% once a week to once a month, 24.3% less often, 71.2% never). The MCS analyses showed that around 68% of 14-year-olds felt that they were rarely victims of bullying whereas 5% stated they were often bullied by other children, with around a quarter responding being bullied sometimes. When asked about being the perpetrators of bullying, around 86% responded ‘almost never’, 1% admitted to bullying others often and over 10% to sometimes bully other children. Viewed through the frequency of peer interactions, amongst 14-year-olds who often interacted with their friends unsupervised and at weekends, 5% reported to often become victims and 1% perpetrators; 14% reported to sometimes become victims and 26% perpetrators and 68% reported to almost never become victims and 84% perpetrators. Similar percentages emerged for young people who interacted with their friends less often, suggesting that roughly equal numbers of 14-year-olds reported of being victims or perpetrators, regardless of how often they interacted with their friends. In analysing the frequency of being a bullying perpetrator through digital play, amongst young people who used social media for 5 to 7 hours or more in a typical day, around 1% reported to often bully other children, 1 in 5 (20%) sometimes and 78% almost never. A different picture emerged with regard to being a victim of bullying. Amongst 14-year-olds who spent 5 to 7 hours or more on social media, 10% reported to often become a victim; 30% sometimes and 60% almost never. These findings showed that over a third of 14-year-olds who spend excessive amount of time on social media sometimes see themselves as victims of bullying but only around 20% see themselves as perpetrators. Likewise, amongst 14-year-­ olds who gamed 5 to 7 hours or more, 2% reported to often bully others, 17% sometimes and 81% almost never, whereas 7% often saw themselves as victims, 28% sometimes and 65% almost never. The differences in the frequency of bullying, either as a perpetrator or a victim, between young people who used social media or gamed for 5 to 7 hours or more and those who used it for less than 2 hours is modest, showing slightly more

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young people experiencing bullying as the hours they spent online increased. In further examining bullying within a wider age range (10–15-year-­ olds), the Understanding Society data provided two separate constructs for bullying, that is, physical and verbal. Regarding physical bullying (‘How often do you get physically bullied?’) with 83.7% of 10–15-year-­ olds stating ‘Never’, 12.4% ‘Not much (1–3 times in 6 months)’ and 3.9% ‘Quite a lot (more than 4 times in 6 months)/A lot (a few times every week)’. Regarding verbal bullying (‘How often do you get bullied in other ways e.g., verbal abuse?’) with 68.8% of 10–15-year-olds stating ‘Never’, 21.6% ‘Not much (1–3 times in 6 months)’ and 9.5% ‘Quite a lot (more than 4 times in 6 months)/A lot (a few times every week)’. The results showed that around 15% of young people experienced physical bullying, on average, 3–4 times in 6 months. Less than a quarter of 10–15-year-olds experienced verbal bullying 1–3 times in 6 months but 1  in 10 experienced it quite a lot.

Teenage Play and Difference Looking at teenagers’ play, including digital play, through the lenses of gender, ethnicity, social class and social emotional and behavioural difficulties, some interesting trends emerged. Compared to young people in well-off families, more teenagers in low socioeconomic status families engaged in free, face-to-face and digital play with peers than in extra-­ curricular activities although the gap is narrow. Also, although roughly equal numbers of teenage girls and boys interacted with their friends frequently, gender differences emerged in the time they spent online visiting social networking sites, with girls spending more times on social media whereas boys on gaming. Also, more White and Black teenagers than any other ethnic group spent excessive time online, and White teenagers predominantly reported to often interact with their friends face to face. Teenagers with social, emotional behavioural difficulties were found to spend many hours online gaming or on social media, whereas those with prosocial behaviour spent much less time online. Bullying also seems to feature in some young people’s life. A significant number of 14-year-olds sometimes saw themselves as victims of bullying and this varies slightly based on how often they interact with their friends face to face or online. Although relatively more young people who interacted with their friends often or spent excessive amount of time on social media or gaming

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reported being a victim, bullying (either as a perpetrator or victim) seems to be a dominant feature in the life for around one in five 14-year-olds. Finally, although the frequency of physical bullying was relatively low, one in ten 10–15-year-olds experienced verbal bullying often. Clearly how teenagers interact with their peers online and offline reflects their social structural and psychological realities. Inequality and other markers of difference underpin teenage play and interactions and their lived experiences with friends.

References Aggio, D., Gardner, B., Roberts, J., Johnstone, J., Stubbs, B., Williams, G., … Smith, L. (2017). Correlates of children’s independent outdoor play: Cross-­ sectional analyses from the Millennium Cohort Study. Preventive Medicine Reports, 8, 10–14. American Psychological Association. (2007). Report of the APA task force on the sexualization of girls. Retrieved February 3, 2016, from http://www.apa.org/ pi/women/programs/girls/report.aspx. Archer, L. (2003). ‘Race’, masculinity and schooling: Muslim boys and education. Buckingham: Open University Press. Ash, J., & Gallacher, L. A. (2011). Cultural geography and videogames. Geography Compass, 5, 351–368. https://doi.org/10.1111/j.1749-8198.2011.00427 Beavis, C., Muspratt, S., & Thompson, R. (2015). Computer games can get your brain working: Student experience and perceptions of digital games in the classroom. Learning, Media and Technology, 40(1), 21–42. Berkout, O. V., Young, J. N., & Gross, A. M. (2011). Mean girls and bad boys: Recent research on gender differences in conduct disorder. Aggression and Violent Behavior, 16(6), 503–511. Blau, F., Brinton, M., & Grusky, D. (2006). The declining significance of gender? New York: Russell Sage Foundation. Booker, C., Yvonne, J. K., & Sacker, A. (2018). Gender differences in the associations between age trends of social media interaction and well-being among 10–15 year olds in the UK. BMC Public Health BMC, 18, 321. Bourdieu, P. (1986). The forms of capital. In J. G. Richardson (Ed.), Handbook for theory and research for the sociology of education (pp.  241–258). Oxford: Greenwood Press. Branisa, B., Klasen, S., Ziegler, M., Drechsler, D., & Jütting, J. (2014). The institutional basis of gender inequality: The social institutions and gender index (SIGI). Feminist Economics, 20(2), 29–64. https://doi.org/10.1080/1354570 1.2013.850523 Braun, H. (Ed.). (2016). Meeting the Challenges to Measurement in an Era of Accountability. Routledge.

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Cabieses, B., Pickett, K.  E., & Wilkinson, R.  G. (2016). The impact of socioeconomic inequality on children’s health and well-being (pp. 244–265). New York, NY: Oxford University Press. Carver, A. B., Watson, B. S., & Hillman, M. (2013). A comparison study of children’s independent mobility in England and Australia. Children’s Geographies, 11(4), 461–475. https://doi.org/10.1080/14733285.2013.812303 Chahal, K., & Julienne, L. (1999). We can’t all be white!: Racist victimisation in the UK. York: York Publishing Services/Joseph Rowntree Foundation. Cingel, D. P., & Krcmar, M. (2013). Predicting media use in very young children: The role of demographics and parent attitudes. Communication Studies, 64(4), 374–394. Dermott, E., & Pantazis, C. (2014). Gender and poverty in Britain: Changes and continuities between 1999 and 2012. Journal of Poverty and Social Justice, 22(3), 253–269. Eisenberg, N., Spinrad, T. L., & Sadovsky, A. (2006). Empathy-related responding in children. Handbook of Moral Development, 517, 549. Elgar, F., Gariepy, G., Torsheim, T., & Currie, C. (2016). Early-life income inequality and adolescent health and wellbeing. Social Science and Medicine, 174, 197–208. Finch, L., Hargrave, R., Nichols, J., & van Vliet, A. (2014). Measure what you treasure: Well-being and young people, how it can be measured and what the data tell us. New Philanthropy Capital. Retrieved May 28, 2014, from http:// www.thinknpc.org/ publications/measure-what-you-treasure/. Gentile, D. A., & Walsh, D. A. (2002). A normative study of family media habits. Journal of Applied Developmental Psychology, 23(2), 157–178. Gillespie, B. J., Lever, J., Frederick, D., & Royce, T. (2015). Close adult friendships, gender, and the life cycle. Journal of Social and Personal Relationships, 32(6), 709–736. https://doi.org/10.1177/0265407514546977 Girlguiding. (2015). Girls’ Attitude Survey 2015. Retrieved March 1, 2016, from http://new.girlguiding.org.uk/latest-updates/making-a-difference/ girls-attitudes-survey-2015. Goodman, R., Ford, T., Simmons, H., Gatward, R., & Meltzer, H. (2000). Using the Strengths and Difficulties Questionnaire (SDQ) to screen for child psychiatric disorders in a community sample. The British Journal of Psychiatry, 1776, 534–539. Hall, J.  A. (2011). Sex differences in friendship expectations: A meta-analysis. Journal of Social and Personal Relationships, 28(6), 723–747. https://doi. org/10.1177/0265407510386192 Harris, A. (2014). Young people and everyday multiculturalism. London: Routledge. Hartas, D. (2011). Families’ social backgrounds matter: Socio-economic factors, home learning and young children’s language, literacy and social outcomes. British Educational Research Journal, 37(6), 1469–3518.

2  FREE AND GUIDED PLAY AND UNEQUAL CHILDHOODS 

55

Hartas, D. (2012). Inequality and the home learning environment: Predictions about seven-year-olds’ language and literacy. British Educational Research Journal, 38(5), 859–879. Hartas, D. (2019). The social context of adolescent mental health and wellbeing: Parents, friends and social media. Research Papers in Education, 1–19. https:// doi.org/10.1080/02671522.2019.1697734 Hollingworth, S., & Archer, L. (2010). Urban schools as urban places: School reputation, children’s identities and engagement with education in London. Urban Studies, 47(3), 584. Holt, L. (2010). Young people’s embodied social capital and performing disability. Children’s Geographies, 8, 25–37. https://doi.org/10.1080/ 14733280903500158 Holt, L., Bowlby, S., & Lea, J. (2013). Emotions and the habitus: Young people with socio-emotional differences (re)producing social, emotional and cultural capital in family and leisure space-times. Emotion, Space and Society, 9, 33–41. https://doi.org/10.1016/j.emospa.2013.02.002 International NGO. (2013). Council on violence against children. Violating children’s rights: Harmful practices based on tradition, culture, religion or superstition. Geneva. Iqbal, H., Neal, S., & Vincent, C. (2017). Children’s friendships in super-diverse localities: Encounters with social and ethnic difference. Childhood, 24(1), 128–142. JRF Analysis Unit. (2017). UK Poverty 2017. York: Joseph Rowntree Foundation. Retrieved January 5, 2018, from https://www.jrf.org.uk/report/ uk-poverty-2017. Karsten, L. (2005). It all used to be better? Different generations on continuity and change in urban children’s daily use of space. Children’s Geographies, 3(3), 275–290. https://doi.org/10.1080/14733280500352912 Korczak, D. J., Madigan, S., & Colasanto, M. (2017). Children’s physical activity and depression: A meta-analysis. Pediatrics, 139(4). Lareau, A. (2002). Invisible inequality: Social class and childrearing in black and white families. American Sociological Review, 67, 747–776. Lareau, A. (2003). Unequal Childhoods. Berkeley. Loebach, J.  E., & Gilliland, J.  A. (2016). Free range kids? Using GPS-derived activity spaces to examine children’s neighborhood activity and mobility. Environment and Behavior, 48(3), 421–453. Longhurst, R. (2013). Using Skype to mother: Bodies, emotions, visuality, and screens. Environment and Planning D: Society and Space, 31, 664–679. https://doi.org/10.1068/d20111 Mackett, R.  L. (2013). Children’s travel behaviour and its health implications. Transport Policy, 26, 66–72. McKendrick, J.  H., Bradford, M.  G., & Fielder, A.  V. (2000). Kid customer? Commercialization of playspace and the commodification of childhood. Childhood, 7(3), 295–314.

56 

D. HARTAS

Mohr-Jensen, C., & Steinhausen, H. C. (2016). A meta-analysis and systematic review of the risks associated with childhood attention-deficit hyperactivity disorder on long-term outcome of arrests, convictions, and incarcerations. Clinical Psychology Review, 48, 32–42. O’Brien, M., Rustin, M., Jones, D., & Sloan, D. (2000). Children’s independent spatial mobility in the urban public realm. Childhood: A Global Journey of Child Research, 7(3), 257–277. Office for National Statistics. (2015). Measuring national well-being: Insights into children’s mental health and well-being. London: Office for National Statistics. Orben, A., Dienlin, T., & Przybylski, A. K. (2019). Social media’s enduring effect on adolescent life satisfaction. PNAS. https://doi.org/10.1073/ pnas.1902058116. Pasquier, D. (2008). From parental control to peer pressure: Cultural transmission and conformism. In The international handbook of children, media and culture (pp. 448–459). London: Sage. Perry, D.  G., & Pauletti, R.  E. (2011). Gender and adolescent development. Journal of Research on Adolescence, 21(1), 61–74. Phoenix, A., & Husain, F. (2007). Parenting and ethnicity. Joseph Rowntree Foundation. Pickett, K. E., & Wilkinson, R. G. (2007). Child wellbeing and income inequality in rich societies: Ecological cross sectional study. Bmj, 335(7629), 1080. Pickett, K. E., & Wilkinson, R. G. (2015). Income inequality and health: A causal review. Social Science & Medicine, 128, 316–326. Przybylski, A. K., & Weinstein, N. A. (2017). Large scale test of the Goldilocks hypothesis: Quantifying the relations between digital screens and the mental well-being of adolescents. Psychological Science, 28(2), 204–215. Pyer, M., & Bush, M. (2009). Disabled families in flux: Removing barriers to family life. London: Scope. Rafalow, M. H. (2018). Disciplining play: Digital youth culture as capital at school. American Journal of Sociology, 123(5), 1416–1452. Rideout, V., Foehr, U., & Roberts, D. (2010). Generation M2: Media in the lives of 8–18 year-olds. Kaiser Family Foundation. Retrieved from http://www.kff. org/entmedia/upload/8010.pdf Roe, J. (2018). Ethnicity and children’s mental health: Making the case for access to urban parks. The Lancet Planetary Health. Rose, A. J., & Rudolph, K. D. (2006). A review of sex differences in peer relationship processes: Potential trade-offs for the emotional and behavioral development of girls and boys. Psychological Bulletin, 132(1), 98. Ryan, S. (2005). ‘People don’t do odd, do they?’ Mothers making sense of the reactions of others towards their learning disabled children in public places. Children’s Geographies, 3(3), 291–305.

2  FREE AND GUIDED PLAY AND UNEQUAL CHILDHOODS 

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Ryan, L., Sales, R., Tilki, M., & Siara, B. (2008). Social networks, social support and social capital: The experiences of recent Polish migrants in London. Sociology, 42(4), 672–690. Santaliestra-Pasías, A. M., Mouratidou, T., Verbestel, V., Bammann, K., Molnar, D., Sieri, S., … Hadjigeorgiou, C. (2014). Physical activity and sedentary behaviour in European children: The IDEFICS study. Public Health Nutrition, 17(10), 2295–2306. Schwanen, T. (2007). Gender differences in chauffeuring children among dual-­ earner families. The Professional Geographer, 59(4), 447–462. Sedano, L. J. (2012). On the irrelevance of ethnicity in children’s organization of their social world. Childhood, 19(3), 375–388. Sen, A. (1999). Development as freedom. New York: Knopf. Shensa, A., Escobar-Viera, C. G., Sidani, J. E., Bowman, N. D., Marshal, M. P., & Primack, B. A. (2017). Problematic social media use and depressive symptoms among U.S. young adults: A nationally-representative study. Social Science & Medicine. https://doi.org/10.1016/j.socscimed.2017.03.061 Social Mobility & Child Poverty Commission. (2017). State of the Nation 2016: Social Mobility in Great Britain. Stehlé, J., Voirin, N., Barrat, A., Cattuto, C., Isella, L., Pinton, J. F., … Vanhems, P. (2011). High-resolution measurements of face-to-face contact patterns in a primary school. PLoS One, 6(8), e23176. Tucker, F., & Matthews, H. (2001). ‘They don’t like girls hanging around there’: Conflicts over recreational space in rural Northamptonshire. Area, 33(2), 161–168. Twenge, J. (2017). Have Smartphones destroyed a generation? The Atlantic. Retrieved November 5, 2017, from https://www.theatlantic.com/magazine/archive. Verduyn, P., Ybarra, O., Résibois, M., Jonides, J., & Kross, E. (2017). Do social network sites enhance or undermine subjective well-being? A critical review. Social Issues and Policy Review, 11(1), 274–302. Wentzel, K. R. (2017). Peer relationships, motivation, and academic performance at school. In A.  J. Elliot, C.  S. Dweck, & D.  S. Yeager (Eds.), Handbook of competence and motivation: Theory and application (pp.  586–603). The Guilford Press. Winkler Reid, S. (2015). Making fun out of difference: Ethnicity–race and humour in a London school. Ethnos, 80(1), 23–44. Witten, K., Kearns, R., Carroll, P., Asiasiga, L., & Tava’e, N. (2013). New Zealand parents’ understandings of the intergenerational decline in children’s independent outdoor play and active travel. Children’s Geographies, 11(2), 215–229.

CHAPTER 3

Play and Learning Behaviours, Attitudes and Aspirations

Abstract  This chapter examines associations between play (both free and adult organised) and teenage learning behaviours, attitudes and educational aspirations. Specifically, different forms of digital play (i.e., gaming and visiting social networking sites) and face-to-face peer interactions were analysed to determine their associations with learning behaviours and attitudes, motivation and educational aspirations of teenage girls and boys from different socioeconomic groups. The findings showed a drop in teenagers’ motivation, academic self-esteem and educational aspirations as time spent online increased (the drop was sharper for teenage girls). This was not the case when they interacted with their friends, face-to-face, despite that teenagers with low motivation and aspirations interacted with their friends more often than their peers who have high motivation and aspirations. Also, family socioeconomic status played an important role in shaping educational motivation and aspirations and academic self-esteem, ultimately reproducing educational outcomes. Furthermore, teenagers in high income families were more likely to participate in extra-curricular activities. Finally, although teenagers who spent excessive time online were less likely to participate in extra-curricular activities, the correlations between participation in extra-curricular activities and learning behaviours and attitudes and aspirations were modest. Keywords  Play-based learning, School attitudes, Educational aspirations

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Play-based learning, as a pedagogical approach, utilises play to promote children’s learning. Much research in this area has focused on early years learning, mostly on the development of pre-literacy and numeracy skills through play. However, we know little about associations between digital play and face-to-face peer interactions and learning behaviours and attitudes and educational aspirations in teenagers. The use of play as a tool to support learning has been a point of contest. Research has shown that replacing free with guided play in early years is likely to have a negative impact on children’s self-regulation and social skills development (Berk 2018; Blum and Parette 2015). The instrumentality of play-based learning raises interesting questions about the nature and scope of play and whether the developmental and learning outcomes we wish to achieve through it reflect the developmental and learning needs of children and young people. Most importantly, it raises questions about whether guided play for the purpose of learning is beneficial, for whom and for what kind of learning, and the social context and conditions that are conducive to guided play for teenagers. Similar questions have been raised in the literature on digital play as a pedagogical tool to enhance attitudes to learning and educational aspirations in teenagers. The use of digital play as a means of supporting learning has also been contested. There are arguments that technology-mediated learning is challenging young people’s cognitive capabilities in multiple ways, including their capacity for analytical thinking, memory, focus, creativity, reflection and mental resilience, memory formation, contextual thinking, conversational depth and attention (Blum and Parette 2015; Shaw and Tan 2015). Some researchers see digital play as an integral aspect of children’s play and learning, but others consider it ‘not to have a presence in the physical realm’, arguing that it encourages ‘passivity’, thus preventing children from actively engaging in learning and developing cognitive skills and social understanding (Blum and Parette 2015, 166). By and large, public debates about young people gaming and using social media ‘generally construct children as dependent and passive’ (Shaw and Tan 2015, 12) with digital media being often thought of as ‘cold, inert, inactive, and devoid of life’ (McClure and Sweeny 2015, 252). Moral discourses about digital games leading to antisocial behaviour and violence where digital players are seen as victims are also in abundance (Marsh and Millard 2000). In contrast, there is evidence that young people who enjoy positive relationships with their peers (online or offline) tend to be engaged and do well academically in comparison to those who

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experience difficulties with peer interactions and friendships (Wentzel 2017). Children’s social competence with peers has been consistently found to relate to academic achievement throughout the school-age years. In light of this, it is of interest to examine teenage learning behaviours and attitudes through free and guided play to better understand the links between these behaviours and digital play, face-to-face peer interactions and extra-curricular activities. Most studies have focused on the effects of gaming and social media use on children’s wellbeing (see Chap. 1 for details). However, we know very little about play, including digital play and peer interactions, in relation to teenage learning behaviours, school attitudes and educational aspirations. I focused on these aspects of learning rather than subject-specific academic achievement per se to capture the broad psycho-social dimensions of learning, school behaviour and aspirations. In so doing, I approached learning indirectly through young people’s academic self-­ esteem, educational motivation, school attitudes and behaviours and educational aspirations. I examined whether different forms of play such as digital play (i.e., gaming and visiting social networking sites) and face-to-­ face peer interactions and extra-curricular activities find different manifestations in the learning behaviours and attitudes of teenagers from diverse groups. Questions about whether digital play and face-to-face interactions with peers are reflected differently in the learning behaviours and aspirations of boys and girls and between well-off and disadvantaged young people were addressed in the following sections.

Digital Play, Academic Motivation, Self-Esteem and Aspirations in Teenage Boys and Girls In delineating relationships between digital play and 14-year-olds’ behaviours and attitudes to learning and educational aspirations, I analysed the frequency of digital play along measures of academic self-esteem, educational motivation, class behaviour and educational aspirations. Specifically, these measures were defined as follows: Academic self-esteem, as a composite variable, was constructed through a series of statements that tap onto academic self-esteem. These were: ‘I am good at English’ (17.5% disagree; 59.7% agree, 22.8% strongly agree), ‘I am good at Maths’ (21.1% disagree; 51.8% agree, 27.1% strongly agree), ‘I am good at Science’ (21.7% disagree; 53.7% agree, 24.7% strongly

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agree) and ‘I am good at PE’ (24.4% disagree; 40.1% agree, 35.5% strongly agree), measured with a Likert scale. Higher scores indicated higher academic self-esteem. For the composite variable, M = 2.9 and SD = 0.5. Educational motivation, as a composite variable, was based on the following items: ‘How often do you feel unhappy at school?’ (13.2% all/ most of the time; 52.9% some of the time; 33.9% never); ‘How often do you get tired at school?’ (40.7% all/ most of the time; 50.8% some of the time; 8.4% never); ‘How often do you feel school is a waste of time?’ (14.7% all/ most of the time; 43.1% some of the time; 42.1% never); ‘How often is it difficult to keep mind on work at school?’ (28.2% all/ most of the time; 56.3% some of the time; 15.5% never); ‘How often do you try your best at school?’ (90.5% all/most of the time; 9.2% some of the time; 0.3% never); ‘How often do you find school interesting?’ (49.1% all/most of the time; 45.4% some of the time; 5.5% never), with the last 2 items being reverse coded. These items were measured via a Likert scale ranging from ‘all of the time’ to ‘never’. A composite variable was created with a good internal consistency (a = 0.78). Higher scores indicated higher educational motivation. For the composite variable, M = 17.4 and SD = 2.9. School Attitudes and behaviours, as a composite variable was based on two items: ‘How often does Cohort Member (CM) misbehave in lessons’ (6.6% most of the time, 45.9% sometimes, 47.4% never); and ‘How often does CM miss school without permission?’ (3% most of the time, 6% sometimes and 91% never). For the composite variable, M  =  3.8 and SD  =  1.4. Regarding educational aspirations, there were two separate measures (with scores ranging from 0 to 100), the first question was on whether the young person plans to stay in on formal education post 16 (M  =  86.32, SD  =  20.6) and the second question was on whether the young person is planning to go to university (M = 70.16, SD = 28.2). Academic self-esteem measured how young people saw themselves as learners. Over three quarters of 14-year-olds agreed they were good across school subjects. Educational motivation measured how young people felt about schooling in terms of whether they get tired; think school is a waste of time; having difficulty in keeping their mind on work at school, or whether they find school to be interesting and try their best. Around half of 14-year-olds stated they feel unhappy about school, get tired, find it difficult to keep their mind at work and think school is a waste of time some of the time. Around 90% reported that they try their best most of the time and around 50% often found school to be interesting. Regarding school attitudes and class behaviours, over 90% of young people stated

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they never missed school without permission and reported to often behave well in lessons. For educational aspirations, over three quarters of 14-year-­ olds plan to stay on in formal education post 16 and around 70% plan to go to university. Overall, 14-year-olds’ attitudes to learning and school are positive, with nearly three quarters of them thinking about post-16 education and university studies. In looking through the lenses of digital play, gender and socioeconomic status, the results showed that educational motivation and academic self-­ esteem dropped for both teenage boys and girls as the time they spent online visiting social networking sites and gaming increased (Tables 3.1 and 3.2). Regarding school attitudes and class behaviour, for girls the drop was steeper whereas for boys, self-ratings remained stable irrespective of how much time they spent online. Compared to teenage girls who spent less than two hours daily, those who spent 5 to 7 or more hours reported more negative attitudes and behaviour towards school. Likewise, a graded relationship emerged between educational aspirations and time spent online; as time spent online increased both teenage boys’ and girls’ educational aspirations decreased. The drop in educational aspirations was particularly marked for girls who reported to spend 5 to 7 hours or more (compared to boys who also spent 5 to 7 hours or more) daily visiting social networking sites. Also, compared to 14-year-olds in families with income at the top quintile and parents with high education, young people in less well-off families with parents with fewer educational qualifications reported significantly less motivation and lower academic self-esteem, and this pattern was evident irrespective of how many hours they spent online gaming or visiting social networking sites. Teenagers who spent excessive hours online reported much lower educational aspirations, whereas their reported school attitudes and class behaviour remained stable across socioeconomic groups (but not across gender groups). It seems that time spent online visiting social networking sites and gaming associated with 14-year-olds’ educational aspirations but not with motivation and academic self-esteem which were found to differ along socioeconomic lines. The drop in educational aspirations and school attitudes and behaviour was steeper for teenage girls. An interesting picture emerged when comparing young people’s wellbeing and learning attitudes and behaviour in relation to digital play. Specifically, time spent online was found to relate more strongly to 14-year-olds’ wellbeing (as seen in Chap. 1) than to their learning

Table 3.1  Social networking sites by gender, income, parent education on learning aspects Educational motivation

Academic self-esteem

School attitudes / behaviours

Social networking

Gender M (SD)

Income M (SD)

Parent education M (SD)

0- less than 2 hours

M 18.03 (2.6) F 18.29 (2.8)

2- less than 5 hours

M 17.21 (2.8) F 17.36 (2.8)

5 to 7 hours or more

M 16.29 (3.0) F 15.85 (3.2)

0- less than 2 hours

M 3.06 (0.5) F 2.9 (0.5)

2- less than 5 hours

M 3.05 (0.51) F 2.9 (0.49)

5 to 7 hours or more

M 3.01 (0.58) F 2.86 (0.52)

0- less than 2 hours

M 3.7 (1.3) F 3.8 (1.1)

2- less than 5 hours

M 3.7 (1.6) F 3.8 (1.4)

5 to 7 hours or more

M 3.7 (1.7) F 4.0 (1.8)

1 17.9 (3.0) 2 17.8 (2.9) 3 17.9 (2.7) 4 18.3 (2.5) 5 18.4 (2.5) 1 16.9 (3.1) 2 16.8 (3.0) 3 17.2 (2.9) 4 17.4 (2.6) 5 17.7 (2.5) 1 15.83 (3.4) 2 15.63 (3.2) 3 15.86 (3.1) 4 16.36 (3.1) 5 16.39 (3.1) 1 2.9 (0.5) 2 2.9 (0.5) 3 2.9 (0.4) 4 3.0 (0.5) 5 3.1 (0.5) 1 2.9 (0.5) 2 2.9 (0.4) 3 2.9 (0.3) 4 3.0 (0.5) 5 3.0 (0.5) 1 2.8 (0.5) 2 2.8 (0.5) 3 2.9 (0.5) 4 2.9 (0.5) 5 3.0 (0.5) 1 3.7 (1.3) 2 3.7 (1.3) 3 3.8 (1.2) 4 3.8 (1.1) 5 3.8 (1.1) 1 3.8 (1.6) 2 3.9 (1.7) 3 3.9 (1.5) 4 3.7 (1.3) 5 3.7 (1.3) 1 3.8 (1.8) 2 4.0 (1.8) 3 4.0 (1.8) 4 3.9 (1.6) 5 3.8 (1.6)

1 17.8 (3.0) 2 17.8 (2.7) 3 18.2 (2.7) 4 18.2 (2.6) 5 18.1 (2.4) 117.1 (3.0) 2 17.1 (2.9) 3 17.2 (2.9) 4 17.4 (2.7) 5 17.4 (2.5) 1 15.3 (3.4) 2 15.9 (3.2) 3 16.3 (3.2) 4 16.1 (3.0) 515.8 (3.0) 1 2.9 (0.51) 2 2.9 (0.48) 3 3.0 (0.52) 4 3.0 (0.50) 5 3.0 (0.52) 1 2.9 (0.46) 2 2.9 (0.48) 3 2.9 (0.57) 4 3.0 (0.49) 5 3.0 (0.47) 1 2.8 (0.58) 2 2.8 (0.52) 3 2.9 (0.58) 4 2.9 (0.52) 5 2.9 (0.56) 1 3.8 (1.4) 2 3.8 (1.3) 3 3.7 (1.2) 4 3.7 (1.1) 5 3.8 (1.2) 1 3.8 (1.5) 2 3.8 (1.5) 3 3.8 (1.4) 4 3.8 (1.4) 5 3.8 (1.5) 1 3.8 (1.8) 2 3.9 (1.8) 3 3.8 (1.6) 4 3.8 (1.7) 5 3.9 (1.8) (continued)

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Table 3.1 (continued) Educational motivation

Social networking

Gender M (SD)

Income M (SD)

Parent education M (SD)

Educational aspirations: Stay post 16

0- less than 2 hours

M 84.5 (21.7) F 90.3 (17.9)

2- less than 5 hours

M 82.66 (22) F 89.61 (16.1)

5 to 7 hours or more

M 81.64 (15.1) F 85.38 (16.9)

0- less than 2 hours

M 67.7 (28.2) F 76.7 (26.2)

2- less than 5 hours

M 65.02 (29.5) F 74.7 (26.1)

5 to 7 hours or more

M 61.12 (30.3) F 68.89 (28.5)

1 82.6 (23) 2 82.0 (23) 3 84.4 (21) 4 89.2 (18) 5 91.5 (16) 1 82.8 (22) 2 83.3 (22) 3 84.6 (21.4) 4 88.5 (17.7) 5 92.1 (14.4) 1 80.68 (14.2) 2 80.67 (24.8) 3 83.25 (22.0) 4 86.5 (19.9) 5 91.5 (16.2) 1 63.9 (30.3) 2 66.6 (29.6) 3 67.9 (29.0) 4 73.2 (26.8) 5 78.6 (22.9) 1 64.4 (29.5) 2 64.2 (30.7) 3 68.4 (28.5) 4 72.4 (26.3) 5 79.7 (22.7) 1 59.0 (31.2) 2 61.4 (30.8) 3 67.2 (28.1) 4 70.3 (28.0) 5 76.1 (24.7)

1 80.72 (23.4) 2 82.8 (23.2) 3 86.5 (20.6) 4 89.4 (18.2) 5 91.9 (15.0) 1 85.1 (18.5) 2 84.0 (21.8) 3 86.9 (18.8) 4 89.1 (18.0) 5 89.1 (17.3) 1 78.7 (25.6) 2 82.9 (22.2) 3 86.3 (20.4) 4 87.1 (20) 5 89.2 (18.6) 1 56.0 (29.6) 2 62.8 (30.3) 3 69.5 (27.4) 4 76.7 (24.9) 5 81.0 (21.2) 1 58.6 (31.7) 2 64.0 (30.3) 3 70.8 (26.5) 4 76.3 (24.6) 5 79.3 (23.0) 1 54.1 (30.9) 2 63.0 (29.8) 3 68.7 (30.1) 4 71.8 (25.9) 5 78.1 (24.7)

Educational aspirations: Go to university

N = 11,310−11,293 (the notation 1 to 5 under the Income and Parent Education columns denotes quintiles 1 = top and 5 = bottom quintile; and parent education levels, 1 = no educational qualifications to 5 = qualifications at postgraduate degree level) Notes: A series of Analyses of Variance (ANOVAs) were conducted. Statistically significant differences emerged between gender and all measures of learning (Educational Motivation, Academic Self-Esteem, School Attitudes/Behaviours, Educational Aspirations) with regard to the frequency of social networking. No significant differences were found between these measures (except for educational aspirations) and (i) parent income and (ii) parent education

Table 3.2  Computer games by gender, income, parent education on learning aspects Educational motivation

Academic self-esteem

School attitudes / behaviours

Computer games

Gender M (SD)

Income M (SD)

Parent education M (SD)

0- less than 2 hours

M 18 (2.8) F17.5 (3)

2- less than 5 hours

M 17.6 (2.7) F16.9 (3.0)

5 to 7 hours or more

M 16.8 (2.9) F 15.6 (3.4)

0- less than 2 hours

M 3.1 (0.52) F 2.9 (0.50)

2- less than 5 hours

M 3.0 (0.51) F2.8 (0.51)

5 to 7 hours or more

M 2.9 (0.5) F 2.8 (0.5)

0- less than 2 hours

M 3.7 (1.4) F 3.9 (1.3)

2- less than 5 hours

M3.7 (1.4) F3.9 (1.5)

5 to 7 hours or more

M 3.7 (1.6) F 4.0 (1.8)

1 17.4 (3.2) 2 17.2 (3.2) 3 17.4 (3) 4 17.7 (2.7) 5 18.1 (2.7) 1 17.2 (3) 2 17.1 (2.9) 3 17.3 (2.8) 4 17.7 (2.6) 5 17.8 (2.5) 1 16.1 (3.3) 2 16 (3.2) 3 16.6 (2.9) 4 17.2 (2.8) 5 17.2 (2.8) 1 2.9 (0.5) 2 2.9 (0.5) 3 2.9 (0.5) 4 3.03 (0.49) 5 3.0 (0.5) 1 2.9 (0.5) 2 2.9 (0.5) 3 2.9 (0.5) 4 3.4 (0.49) 5 3.1 (0.48) 1 2.9 (0.5) 2 2.8 (0.5) 3 2.9 (0.5) 4 3.0 (0.48) 5 3.0 (0.49) 1 3.8 (1.5) 2 3.9 (1.5) 3 3.8 (1.4) 4 3.8 (1.2) 5 3.8 (1.2) 1 3.7 (1.5) 2 3.8 (1.6) 3 3.8 (1.5) 4 3.7 (1.3) 5 3.7 (1.2) 1 3.8 (1.8) 2 3.8 (1.7) 3 3.9 (1.7) 4 3.7 (1.5) 5 3.7 (1.4)

1 17.4 (3.2) 2 17.3 (3.0) 3 17.7 (3) 4 17.7 (2.8) 5 17.8 (2.7) 1 17.2 (3.1) 2 17.3 (2.7) 3 17.5 (2.7) 4 17.5 (2.7) 517.5 (2.6) 1 15.6 (3.3) 2 16.4 (3.1) 317.1 (3.0) 417.04 (2.8) 5 16.7 (2.8) 1 2.9 (0.5) 2 2.9 (0.5) 3 2.9 (0.5) 4 3.03 (0.49) 5 3.0 (0.52) 1 2.8 (0.5) 2 2.9 (0.5) 3 2.9 (0.5) 4 3.03 (0.49) 5 3.0 (0.52) 1 2.9 (0.5) 2 2.9 (0.5) 3 2.9 (0.5) 4 3.03 (0.49) 5 3.0 (0.52) 1 3.8 (1.5) 2 3.9 (1.4) 3 3.7 (1.2) 4 3.8 (1.3) 5 3.8 (1.4) 1 3.7 (1.5) 2 3.8(1.4) 3 3.8 (1.2) 4 3.7 (1.3) 5 3.8 (1.4) 1 3.9 (1.5) 2 3.9 (1.4) 3 3.7 (1.2) 4 3.8 (1.3) 5 3.6 (1.4) (continued)

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Table 3.2 (continued) Educational motivation

Computer games

Gender M (SD)

Educational aspirations: Stay post 16

0- less than 2 hours

M 86.1 (21.4) 1 85.2 (21.8) F 89.7 (17.9) 2 84.5 (21.9) 3 86.4 (20.6) 4 90.0 (17.5) 5 93.3 (14.2) M 83.1 (22.0) 1 79.9 (24.7) F 86.8 (19.3) 2 80.2 (24.0) 3 82.9 (21.2) 4 86.7 (19.2) 5 89.2 (16.7) M 80.1 (23.3) 1 76.4 (24.6) F 80.6 (24.1) 2 76.6 (25.2) 3 79.0 (23.9) 4 85.5 (20.0) 5 87.0 (21.2) M 69.2 (28.5) 1 66.6 (30.2) F 75.1 (25.5) 2 67.8 (30.1) 3 71.3 (27.8) 4 75.2 (25.9) 5 80.4 (22.2) M 65.8 (28.3) 1 62.6 (29.3) F 70.8 (27.1) 2 62.1 (29.6) 3 64.0 (28.8) 4 70.3 (26.6) 5 75.5 (24.1) M 61.9 (29.9) 1 53.1 (30.9) F 63.7 (31.1) 2 57.5 (30.6) 3 63.8 (29.6) 4 64.4 (29.6) 5 73.8 (25.4)

2- less than 5 hours

5 to 7 hours or more

Educational aspirations: Go to university

0- less than 2 hours

2- less than 5 hours

5 to 7 hours or more

Income M (SD)

Parent education M (SD) 1 84 (22.4) 2 85.0 (22.2) 3 88.7 (18.6) 4 91.3 (16.3) 5 92.6 (14.2) 1 79.7 (21.4) 2 82.6 (21.5) 3 84.2 (21.8) 4 86.1 (20.2) 5 89.0 (17.6) 1 76.7 (25.3) 2 78.3 (24.6) 3 82.8 (20.9) 4 83.8 (22) 5 84 (22.3) 1 58.8 (30.6) 2 66.6 (29.9) 3 72.5 (27.0) 4 78.6 (23.6) 5 82.3 (21.1) 1 55.2 (29.2) 2 59.8 (29.2) 3 66.5 (28.3) 4 72.3 (26.1) 5 78.2 (22.3) 1 50.6 (31.8) 2 57.4 (31.3) 3 65.0 (27.7) 4 69.8 (27.4) 5 70.0 (26.4)

N = 11,310−11,293 (the notation 1 to 5 under the Income and Parent Education columns denotes quintiles 1 = top and 5 = bottom quintile; and parent education levels, 1 = no educational qualifications to 5 = qualifications at postgraduate degree level) Notes: A series of Analyses of Variance (ANOVAs) were conducted. Statistically significant differences emerged between gender and all measures of learning (Educational Motivation, Academic Self-Esteem, School Attitudes/Behaviours, Educational Aspirations) with regard to the frequency of gaming. No significant differences were found between these measures (except for educational aspirations) and (i) parent income and (ii) parent education

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behaviours and attitudes. Although educational aspirations were found to decrease as time spent on gaming and social media increased, socioeconomic factors (income and parental education) were found to exert a much stronger influence than the frequency of digital play alone, particularly for educational motivation, academic self-esteem and aspirations to go to university. Parent education and the intellectual and cultural capital accrued revealed stronger associations than income alone with regard to 14-year-olds’ aspirations, motivation and academic self-esteem. This is consistent with previous research (Aarseth 2017; Hartas 2011; Crozier et al. 2011) on associations between social class, measured via income and parent education, and children’s learning attitudes and behaviours and academic performance, pointing to differential effects of parent income and education on children’s learning behaviours. Clearly, family socioeconomic status plays an important role in shaping educational motivation and aspirations and academic self-esteem, ultimately reproducing educational outcomes. Parent involvement with children’s education and family educational resources and the effects they have on children’s learning and quality of their educational experiences vary according to social class. Although there was a drop in aspirations as the hours young people spent online increased, their educational motivation and attitudes to learning differed significantly across parent education and family income and the economic, intellectual and cultural capital they accrued (and not along hours spent online). Cultural capital is typically understood along exposure to highbrow cultural activities such as museums, theatre and films and transmission of academic skills through homework help and provision of paid-off extra-curricular activities that are typically rewarded in the school system (Lareau and Weininger 2003). Common to these ideas is that the most important transmission of cultural capital occurs in the family, in the form of promoting a wider culture of learning at home. Research on middle-class families has shown how different fractions have different resources, orientations and types of involvement with their children’s learning. Families with more cultural capital (typically found in families with educated parents) are often more liberal in their educational strategies whereas those with more economic capital are more competitive and position oriented (Aarseth 2017, Crozier et al. 2011; Vincent et al. 2004). Children’s educational outcomes are differentiated based on socioeconomic factors with parent education yielding stronger differences than income (e.g., Hartas 2011), suggesting that educated parents are more

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resourceful in terms of accessing resources, services and expertise to support their children’s education even when family income is low. Furthermore, the different contributions of economic and cultural capital to children’s learning could be explained by considering notions of social positioning and social reproduction. Families with economic capital have been found to be anxious and competitive about social reproduction, experiencing a ‘fear of falling’ in terms of their children’s social position (e.g., Ehenreich 1989; Vincent and Ball 2007). Educated parents with intellectual and cultural capital, on the other hand, reported a ‘fear of fading’, manifested in terms of their children being ordinary and not fulfilling their potential (Aarseth 2017). Parents with economic capital as well as those with cultural and intellectual capital engage in what Lareau called ‘concerted cultivation’, but there are significant differences in how they approach their children’s learning and educational outcomes (2002). Parents with economic capital are more instrumental and goal-oriented, placing an emphasis on homework and grades whereas parents with cultural capital are more emotionally attuned to their children, encouraging them to pursue their interests and fulfil their potential (Aarseth 2017). Access to the capital generating aspects of digital media was found to differentiate across families’ socioeconomic background, specifically parents’ resources and capital orientation. In families with cultural capital parents are likely to approach digital play as an important artefact and tool for socialisation that (if used well) can enhance their children’s learning and social connectedness. As such, they may be more relaxed than parents with economic capital about their children spending time online socialising or gaming because they take a less instrumental approach to learning, seen as a process likely to occur not only in class or during homework but also through engagement with technology and its cultural and affective expressions. This harmonises well with results from various studies (Hartas 2011; Spruyt et al. 2016). In an earlier study I found that a home culture of learning characterised by conversations on topical issues (e.g., politics, movies) and book reading for enjoyment rather than as part of homework was found to associate with children’s learning and academic achievement (Hartas 2011). In families with cultural capital, a culture of learning tends to be widespread at home and likely to support self-realisation and self-­ accomplishment. In contrast, children in families with more economic capital tend to approach learning instrumentally as an investment in their future material living conditions and social status (Spruyt et al. 2016).

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Regarding gaming, as the hours increased the educational motivation and aspirations in terms of staying on education post 16 and attending university decreased (academic self-esteem and school attitudes and behaviour remained roughly the same). And these changes were irrespective of income and parent education. The drop in motivation and aspirations was steeper when young people engaged in social media than in gaming. Gaming is thought to allow more creativity in terms of personalising characters and developing narratives rather than passive consumption of content. As Mustola and colleagues argued, gaming environments as a whole can ‘be seen as co-created worlds constituted of the imaginations of the game designer and the player’ (2018, 241). This greatly depends on the flexibility of the game in enabling gamers to build structures, create avatars or content and customise or subvert the game’s environment. Wirman suggested that gaming tends to be more productive because children are less likely to be passive consumers of content (2009). This can be seen when children actively creating new worlds and narratives, and when players and game developers co-create fiction. A key difference between gaming and social media is that although both include engagement, activity, learning and topicality (see Mustola et al. 2018), gaming is less likely than social media to function as a magnifier of social toxicity and more likely to offer a platform for young people to meet, play together and be creative. Game-based interactions create opportunities for socialisation that are similar to offline peer interactions in terms of being unstructured and unsupervised by adults where children agree to develop and follow the rules of a game. In considering the implications of gaming for learning, games are likely to be seen as learning tools which can offer creative opportunities. For example, in England, gaming in general is seen as an important tool for acquiring basic literacy skills (e.g., phonics) that can be trained through memorisation and recall, whereas game-based learning in Scotland is associated with the creativity and design of games, crucial skills for this generation of learners (Meyer et al. 2011). Compared to social media, gaming is more likely to be accepted as a learning tool whose capacity varies between mechanical memorisation of skills to being creative in acquiring and testing knowledge (Kruikemeier et al. 2014). With social media, young people tend to consume rather than produce content or ideas and are more likely to be exposed to upward comparisons and bullying and subjected to stereotyped roles and expectations resulting in constructing identities that do not reflect their real life.

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The spectrum of social behaviours, cognitive engagement and degree of criticality and learning is thought to be better promoted in gaming than in using social media. As Kruikemeier and colleagues argued, a player ‘does not merely consume media contents or artifacts, but also produces something—an experience, social or economic capital, new meanings—by engaging with a video game’ (2014, 906). This is thought to take place during gaming, but not so much in social media unless the social and cultural capital incurred by using social media helps young people to engage critically with trends and act against stereotypes and expectations placed on them due to gender, race and class. These issues can also be present in ‘real-life’ peer interactions and, thus, it is not clear how face-to-face games are better than digital ones in helping children to learn social skills without adult involvement.

Face-to-face Play, Learning Attitudes and Aspirations in Teenage Boys and Girls A growing body of research has shown that peers influence educational outcomes (Akerlof and Kranton 2002), but how peer interactions relate to the psycho-social aspects of learning has not received close attention especially for teenagers. During the teenage years, social relationships outside of the home take on increased significance for socialisation, mental health and school success (Bagwell and Schmidt 2013). Ability to succeed in life is now well recognised to include socio-emotional skills, positive attitudes and behaviour to learning and aspirations. Attitudes towards school and learning are linked with young people’s social and affective responses towards school, teachers, fellow students and their educational aspirations. How young people see themselves as learners fosters school success, educational aspirations and future collegiate hopes and desires (Heckman and Mosso 2014). In a similar vein with digital play, I examined associations between face-­ to-­face peer interactions and 14-year-olds’ behaviours and attitudes to learning and aspirations through analyses of academic self-esteem, educational motivation, class behaviour and educational aspirations. The findings showed around two-thirds of young people who often played with friends unsupervised reported to be generally interested in school. Among young people who played with friends most weekends, there was a roughly equal split between those who said they were interested in school most

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days/sometimes and those who were hardly ever or never interested in school. For 14-year-olds who played unsupervised most days, around two-­ thirds stated that they sometimes do their best at school and slightly over a half stated they hardly ever/never do their best at school. Over a half of young people who were interested in school (54%) and nearly two-thirds who reported to do their best at school (62%) played with their friends most weekends compared to those who were not interested in school (34%) and were less inclined to do their best (38%). These findings suggest that trying to do well at school was not incompatible with interacting with friends most weekends. Playing with friends most days appeared to take place irrespective of whether 14-year-olds reported to be interested in school, although there was a drop in the numbers of 14-year-olds who hardly ever did their best at school. Nevertheless, most young people who often played with friends were also reported to do their best at school. Nearly half of 14-year-olds who expressed low educational motivation and a third of those with high motivation saw their friends most weekends, suggesting that a higher number of young people with low motivation often interacted with their friends. Also, around a third of 14-year-olds with high and a third with low academic self-esteem saw their friends most weekends. It appears that their academic self-esteem was not linked to how often they interacted with their friends. The number of people who played with friends most days was roughly equal (around 60%) for those who reported high and those who reported low academic self-esteem. Young people who rarely played with their friends unsupervised or outside school were, on average, slightly more likely to remain in education post 16 and aspire to go to university compared to those who played with friends most days and weekends. It is important to note that the differences between these groups were very small. The relationship between peer interactions (online and offline) and educational aspirations and motivation can be understood through two main processes: peer selection and peer socialisation. Peer selection refers to the tendency for young people to become friends with like-minded peers and thus young people with high aspirations are likely to seek and interact with others who have similarly high aspirations. Peer socialisation relies on peer influence in terms of young people being influenced by their peers’ norms and values (Raabe and Wölfer 2019). Peer interactions are important in fostering adolescent identities (Deaux and Martin 2003), and peer norms associated with aspirations and motivation to do well (or not) academically are internalised during play.

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Extra-Curricular Activities, Learning Attitudes and Aspirations in Teenage Boys and Girls In the literature of play, play-based learning has been contested for its instrumentality (Katz 2008; Vincent and Ball 2007). Many argue that adult-organised and structured/guided play is no longer play as a child-­ determined activity, unstructured and open to possibilities, but an activity with goals pre-determined by adults. Within it, children are viewed through human capital lenses whereby the child is constructed as a future citizen and worker, requiring the right parental investment to succeed in life. As such, mere playing is seen as not meeting the goals of intensive parenting in properly investing in children’s life to maximise their educational outcomes and life chances (see Chap. 4 for a discussion on intensive parenting and play). Furthermore, questions have been raised as to whether participation in extra-curricular activities (non-sporting activities in particular) results in the over-scheduling of children (Katz 2008), with some identifying a causal link between the decline of free play and the rise of mental health difficulties in young people (e.g., Gray 2012). This point is contested by others who have found that the intensity of participation in organised, out-of-school activities is positively associated with psychological flourishing, civic engagement and educational attainment (Mahoney and Vest 2012). Extra-curricular activities in this book refer to play-based learning organised and structured by adults. For between a quarter and a third of young people, participation in extra-curricular activities was found to be an integral part of their social and educational world. Specifically, the frequency of teenage participation in activities was broken down as follows: ‘go to cinema’ (2.9% most days/at least once a week, 30.6% at least once a month, 48.8% several times a year, 17.7% never/almost never); ‘go to watch live sports’ (10.2% most days/at least once a week, 24.1% at least once a month/several times a year, 65.8% never/almost never); ‘sing in a choir or play in a band or orchestra’ (13.3% at least once a week/once a month, 9.8% several times a year, 83.5% never/almost never); ‘read for enjoyment (not for school)’ (21.2% most days, 17.3% at least once a week, 16.9% at least once a month, 13.3% several times a year, 31.3% never/ almost never); ‘go to youth clubs/scouts/girlguides or other organised activities’ (37.5% most days/at least once a week, 12% at least once a month/several times a year, 50.6% never/ almost never); ‘go to

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museums/galleries, visit historic place/stately homes’ (9.6% at least once a month, 30.1% several times a year, 30% once a year or less, 30.3% never/ almost never); and ‘attend a religious service’ (16% most days at least once a week, 16.7% at least once a month/ several times a year, 13.5% once a year or less, 54.2% never). As with digital play and face-to-face peer interactions, I examined the relationship between the frequency of participation in extra-curricular activities and 14-year-olds’ behaviours and attitudes to learning (i.e., academic self-esteem, educational motivation, class behaviour) and educational aspirations. Teenagers with high academic self-esteem participated in extra-­ curricular activities more often (M = 30) than those with low self-esteem (M = 32). Also, a graded relationship between being interested in school (M = 28 vs M = 34), being best at school (M = 29 vs. M = 34) and the frequency of participation in extra-curricular activities was found in that 14-year-olds who reported to be interested in and do their best at school also reported more frequent participation. Correlational analyses between educational aspiration and the frequency of participation in extra-­curricular activities showed weak to modest positive relationships for young people planning to stay on post 16 and aspiring to go to university. Finally, compared to young people with high educational motivation (M = 29), those with low (M = 33) were less likely to engage with extra-curricular activities frequently. It is important to note that the relationships between participation in extra-curricular activities and educational aspirations were weak to modest (around 0.2 coefficient). Consistently, previous analyses of data from Understanding Society have shown that participation in extra-curricular activities did not make a significant contribution to young people’s educational aspirations whereas what mattered instead was their families’ cultural capital. A culture of learning at home manifested through participation in cultural and play activities, mostly organised by parents, has been found to be a strong predictor of teenagers’ educational aspiration and post-16 choices (Hartas 2014). Parent-encouraged participation in cultural activities and literary conversations that stimulated intellectual interests and aspirations was more likely in families with material resources and cultural capital (e.g., Archer et al. 2014; Hartas 2012), whereas working-class parents were more likely to offer learning support as a direct response to school demands (Ritblatt et  al. 2002). These findings raised interesting

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questions about the type and context of play-based learning and its effectiveness, highlighting wider issues about parent interventions in children’s life. Clearly, parents feel responsible to maximise opportunities for their children’s learning and thus access educational opportunities in the form of play-based learning. Ultimately, whether digital play, peer interactions or extra-curricular activities support teenage learning behaviours and attitudes depends on the cultural capital of families rather than the frequency of play per se. It is important to consider however that engagement with digital media means that young people are spending less time building and maintaining relationships with actual people. Having good friends is crucial for mental health and wellbeing, and although virtual encounters support the development of skills, they also contribute to isolating us rather than helping us build strong relationships and community cohesion.

References Aarseth, H. (2017). Fear of falling—Fear of fading: The emotional dynamics of positional and personalized individualism. Sociology, 1–16. https://doi. org/10.1177/0038038517730219 Akerlof, G. A., & Kranton, R. E. (2002). Identity and schooling: Some lessons for the economics of education. Journal of Economic Literature, 40(4), 1167–1201. Archer, L., DeWitt, J., & Willis, B. (2014). Adolescent boys’ science aspirations: Masculinity, capital, and power. Journal of Research in Science Teaching, 51(1), 1–30. Bagwell, C., & Schmidt, M. (2013). Friendships in childhood and adolescence. Guilford Press. Berk, L. E. (2018). The role of make-believe play in development of self-­regulation. tema. [en línea]. Retrieved from http: //www. child-encyclopedia.com/playbased-learning/accordingexperts/role-make-believe-play-development-selfregulation. Publicado: Febrero. Blum, C., & Parette, H. P. (2015). Universal design for learning and technology in the early childhood classroom. In Young children and families in the information age (pp. 165–182). Dordrecht: Springer. Crozier, G., Reay, D., & James, D. (2011). Making it work for their children: White middle-class parents and working-class schools. International Studies in Sociology of Education, 21(3), 199–216. Deaux, K., & Martin, D. (2003). Interpersonal networks and social categories: Specifying levels of context in identity processes. American Sociological Review, 66(2), 101–117. https://doi.org/10.2307/1519842 Ehenreich, B. (1989). Fear of falling: The inner life of the middle class. New York: Pantheon.

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Gray, R. (2012). Physical health and mental illness: A silent scandal. International Journal of Mental Health Nursing, 21(3). Hartas, D. (2011). Families’ social backgrounds matter: Socio-economic factors, home learning and young children’s language, literacy and social outcomes. British Educational Research Journal, 37(6), 1469–3518. Hartas, D. (2012). Inequality and the home learning environment: Predictions about seven-year-olds’ language and literacy. British Educational Research Journal, 38(5), 859–879. Hartas, D. (2014). Parenting, family policy and children’s well-being in an unequal society: A new culture war for parents. London: Palgrave Macmillan. Heckman, J., & Mosso, S. (2014). The economics of human development and social mobility. Annual Review of Economics, 6(1), 689–733. Katz, C. (2008). Childhood as spectacle: Relays of anxiety and the reconfiguration of the child. Cultural Geographies, 15(1), 5–17. https://doi.org/10.1177/ 147447400708577 Kruikemeier, S. (2014). How political candidates use Twitter and the impact on votes. Computers in Human Behavior, 34, 131–139. Lareau, A. (2002). Invisible inequality: Social class and childrearing in black and white families. American Sociological Review, 67, 747–776. Lareau, A., & Weininger, E. B. (2003). Cultural capital in educational research: A critical assessment. Theory and Society, 32(5/6), 567–606. Mahoney, J. L., & Vest, A. E. (2012). The over-scheduling hypothesis revisited: Intensity of organized activity participation during adolescence and young adult outcomes. Journal of Research on Adolescence, 22(3), 409–418. Marsh, J., & Millard, E. (2000). Literacy and popular culture: Using children’s culture in the classroom. Sage. McClure, M., & Sweeny, R. W. (2015). Participatory youth culture: Young children as media and MOC makers in a post-millennial mode. In K. L. Heider & M.  R. Jalongo (Eds.), Young children and families in the information age: Applications of technology in early childhood (pp. 245–254). Dordrecht: Springer Netherlands. Meyer, B., Sørensen, B. H., & Hanghøj, T. (2011). Making connections—Global and local issues in researching the policy of serious games in education. In S.  Egenfeldt-Nielsen, B.  Meyer, & B.  H. Sørensen (Eds.), Serious games in education: A global perspective (pp.  59–83). Aarhus; Copenhagen: Aarhus University Press. Mustola, M., Koivula, M., Turja, L., & Laakso, M.-L. (2018). Reconsidering activity and passivity in children’s digital play. New Media and Society, 20(1), 237–254. Raabe, I., & Wölfer, R. (2019). What is going on around you: Peer milieus and educational aspirations. European Sociological Review, 35(1), 1–14. https:// doi.org/10.1093/esr/jcy048

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Ritblatt, S. N., Beatty, J. R., Cronan, T. A., & Ochoa, A. M. (2002). Relationships among perceptions of parent involvement, time allocation, and demographic characteristics: Implication for policy formation. Journal of Community Psychology, 30(5), 519–549. Shaw, P., & Tan, Y. (2015). Constructing digital childhoods in Taiwanese children’s newspapers. New Media & Society, 17(11), 1867–1885. Spruyt, B., De Keere, K., Keppens, G., Roggemans, L., & Vam Droogenbroeck, F. (2016). What is it worth? An empirical investigation into attitudes towards education amongst youngsters following secondary education in Flanders. British Journal of Sociology of Education, 37(4), 586–606. Vincent, C., & Ball, S. (2007). Making up’ the middle-class child: Families, activities and class dispositions. Sociology, 41(6), 1061–1077. Vincent, C., Ball, S. J., & Kemp, S. (2004). The social geography of childcare: Making up a middle‐class child. British Journal of Sociology of Education, 25(2), 229–244. Wentzel, K. R. (2017). Peer relationships, motivation, and academic performance at school. In A.  J. Elliot, C.  S. Dweck, & D.  S. Yeager (Eds.), Handbook of competence and motivation: Theory and application (pp.  586–603). The Guilford Press. Wirman, H. (2009). On productivity and game fandom. Transformative Works and Cultures, 3. Retrieved December 12, 2015. https://doi.org/10.3983/ twc.2009.0145.

CHAPTER 4

Teenage Free and Guided Play in the Era of Intensive Parenting

Abstract  This chapter considers teenage play and peer interactions in the era of intensive parenting. Parents influence their children’s peer interactions but also children show agency in how they relate to their peers and this was captured by examining unsupervised, out of school peer interactions. In this chapter, the frequency of free play (i.e., digital play, face-to-­face playing with friends unsupervised and out of school) and guided play (i.e., extra-curricular activities) was analysed across different aspects of parenting such as control, discipline and emotional closeness and communication between parents and teenagers. The findings showed teenagers who connected emotionally with their parents engaged less often with digital media. Also, parent control was found to relate to hours spent online, face-to-face peer interactions and participation in extra-curricular activities. Positive parenting was reflected in mediating teenagers’ digital engagement by having control over their whereabouts and encouraging activities that promote learning. Finally, parents who maintained a strong emotional connection and open communication with their teenagers were more aware about their teenagers’ online and offline interactions. Keywords  Intensive parenting, Responsible parent, Adult-­ structured play

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Parents are expected to socialise their children and teach them values and accepted norms in society. In the era of intensive parenting, parents are instrumental in providing diverse learning opportunities to their children, being attuned to their feelings and fostering emotional bonds, autonomy and healthy habits. Parents exert a variety of effects that simultaneously influence young people’s socialisation and wellbeing in divergent directions. The politicisation of parenting (e.g., Faircloth et al. 2013; Hartas 2014) and the growing policy intervention in family life (Gillies et  al. 2017; Wainwright and Marandet 2013) have implications for how children experience play, including digital play and peer interactions, not only in public but also private spheres. Parenting influences the social geographies of teenage play and the types of play teenagers engaged with. To better understand teenagers’ play through parenting lenses, I examined associations between certain aspects of parenting and 14-year-olds’ play, including digital play, face-to-face peer interactions and participation in extra-curricular activities. Through an analysis of guided play, parents’ heightened sense of responsibility to conform to policy-driven cultures of intensive parenting were revealed as well as insights on parents’ ethics of care. In 2007 the World Health Organization (WHO) developed a framework to delineate key dimensions of positive parenting, especially for teenagers, along the lines of connection, behaviour control, respect for individuality, appropriate behaviour modelling and provision and protection (WHO 2007). In the context of online and offline play, these aspects of positive parenting inform the ways in which parents mediate children’s digital engagement; control their children’s whereabouts in face-to-face peer interactions; and structure play to promote learning and skills development for the future. According to WHO, parent mediation and control are about ‘supervising and monitoring adolescents’ activities, establishing behavioural rules and consequences for misbehaviour, and conveying clear expectations for behaviour’ (2007, 11). Parent mediation translates into parent control and discipline while respecting teenagers’ need for autonomy and independence to explore virtual and physical spaces and interact with their peers. At the same time, parents who maintain a strong emotional connection with their children are likely to be more open and aware of their children’s peer interaction online and offline. In the digital era, parents are expected to monitor their children’s access to digital media and mediate their influence on their wellbeing. Often, parents feel challenged about balancing fears about internet addiction,

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cyberbullying and fear of strangers, on the one hand, and helping their children to develop digital skills and digital literacy on the other. A survey of 6400 European parents of children aged 6–14 (in France, Germany, the Netherlands, Spain, Poland, Italy, Sweden and the UK), conducted by Livingstone and colleagues, found parents to be somewhat concerned about their children’s online interactions and experiences in virtual spaces which can take various forms from being exposed to violent images and data tracking to cyberbullying and digital identity theft and advertisements for unhealthy lifestyles (Livingstone et al. 2017a). Their findings showed two forms of parental mediation to emerge: restrictive and enabling. The consequences from these two forms of mediation present a fine balance between managing online risk and promoting opportunities for learning and positive social experiences and this has implications for reproducing social inequalities. Low-income parents who are less skilled with digital media and the internet have been found to pose restrictions to their children’s internet access, resulting in missing opportunities for forming social networks and learning, accentuating the digital divide and economic inequalities (Livingstone et  al. 2017b). This is consistent with studies showing that in low- and medium-income countries parents tend to impose restrictions to their children’s access to the internet whereas in higher-income countries they see internet as a tool to enhance digital skills for competiveness. Internet use and digital play in teenagers are strongly influenced by the broader family and psycho-social context and affective relationships. Understanding how parenting and family dynamics both influence and are influenced by social media use is crucial to unpick the role parents’ interactions with their children and understand the family context of teenage play and peer interactions. Most studies have explored child characteristics (gender, personality traits) and parent allowance of digital media use. For example, children who tend to present challenging behaviours (crying, arguing, limited self-regulation) tend to get higher screen time allowance from their parents. However, we know little about how parenting relates to teenagers’ screen time as well as peer interactions and play-based learning. For this book, I examined digital and face-to-face play as well as extra-­ curricular activities through the lenses of parenting and parent-child interactions, including parental control about 14-year-olds’ whereabouts; parent discipline; communication and emotional closeness between young people and their parents; and parental involvement with children’s learning through organising extra-curricular activities and homework support.

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Parent control, as a composite variable, was created with the items ‘When CM goes out, how often do parents know where?’ (64.4% Always, 27% Usually and 8.6% Sometimes/Never); ‘When CM goes out, how often do parents know who with? (58% Always, 31% Usually and 10.9% Sometimes/Never); ‘When CM goes out, how often do parents know what CM does? (48.3% Always, 36% Usually and 15.7% Sometimes/ Never). Parent discipline was constructed from the following statements: Does your parent: ‘Tell you off or shout at you’ (91.9% Yes, 8.1% No); ‘Ground you, stop you going out or from seeing your friends’ (41.6% Yes, 58.4% No); and ‘Punish you in some other way’ (29.8% Yes, 70.2% No). Emotional closeness and communication with parents consisted of the following items: ‘How close is CM with mother?’ 43.3% responded being ‘extremely close’; 38.1% ‘very close’; and 18.6% ‘fairly close’/‘not very close’; ‘How close is CM with father?’ 31.5% responded ‘extremely close’; 36.5% ‘very close’; and 31.9% ‘fairly close’/‘not very close’; ‘How often does CM argue with mother’, 7.5% responded most days; 17.7% more than once a week; 30.6% ‘less than once a week’; 44.2% hardly ever/never; and ‘How often does CM argue with father’, 4.7% responded most days; 10.7% more than once a week; 25.6% less than once a week; 59.1% hardly ever/never. Extra-curricular activities (as described in Chap. 3) encompassed cultural events, library visits, discussions of books at home and other intellectual and social pursuits. These activities are thought to be influential in enhancing learning opportunities for language, literacy and maths skills development. Adult-organised play and enrichment activities are criticised for not offering opportunities for chance encounters during supervised peer interactions, especially considering the reduction in unsupervised play in childhood with the rise of intensive parenting (Whitebread 2017).

Digital Play and Parent-Young Person Interaction, Communication and Emotional Closeness Findings from analysing MCS and Understanding Society datasets showed parenting to be intensive but also characterised by emotional closeness and frequent communication between parents and teenagers. The findings on parent control in terms of parents knowing about their 14-year-olds’ whereabouts indicated that nearly two-thirds of parents always knew where their teenagers were, with around a half knowing what their

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teenagers did and who they were with. Regarding parental discipline, most young people said their parents would ‘tell them off’ and less than half stated they were often grounded and not allowed to go out to see their friends. Parent-young person communication was defined along the frequency with which young people talked to parents about things that matter to them but also argued with them. Over three-quarters of teenagers said to be very close to their parents whereas one in two teenagers said they hardly ever argued with their parents. Nearly two-thirds and a half of young people often talked with their mother and father respectively about matters important to them. In general, the findings pointed to positive relationships between teenagers and parents. In examining digital play and aspects of parenting, amongst 14-year-­ olds who engaged with digital media excessively (5–7 hours or more daily), there was a 39% increase in experiencing lower parent control and 15% decrease in parent discipline. In terms of parent-young person emotional connectedness, teenagers who felt close to their mother were 11% less likely to spend 5–7 hours or more daily on social media. In contrast, those who felt less close were 20% more likely to spend 5–7 hours or more on social media. Interestingly, compared to teenagers who received help with homework less frequently, those who received support most days were 28% more likely to visit social networking sites 5–7 hours or more daily. It is often the case that young people who receive homework support from their parents are weak students who also tend to spend many hours online although this does not suggest a causal relationship. There was no association found between the frequency of gaming and parent control and discipline which suggests that gaming did not seem to feature in how parents interacted with their teenagers on matters of discipline. Strong associations emerged between young person-parent communication and hours spent online. Compared to young people who hardly ever argued with their mother, those who did most days were 36% more likely to spend 4–7 or more hours visiting social networking sites. Teenagers who often talked with their father and mother about things that matter to them were 33% and 40% respectively less likely to spend 4–7 hours or more visiting social networking sites. Compared to young people who hardly ever talked with their mother about things that matter to them, those who often did were 40% less likely to play console games 4–7 hours or more. It seems that open and positive communication between parents and young people set the stage for parental alertness and autonomy support which are linked to young people’s internet monitoring and

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wellbeing (e.g., Grolnick et al. 2015; Vansteenkiste and Ryan 2013). By being informed about their children’s whereabouts, parents were able to provide autonomy support and encouraged explorations but also were proactive in alerting young people to the possibility of risk and violence in their virtual encounters. In the literature on parent allowance and mediation regarding children’s digital play, notions of ‘restrictive and active mediation’ are discussed. Restrictive mediation involves autonomy restricting and autonomy granting. The former refers to parents banning social media use as a form of punishment and the latter is about granting social media use as a reward (Coyne et al. 2017; Radesky et al. 2016). Active mediation on the other hand fosters an active approach to using media and showing criticality in discussing their content and their effects on children’s social interactions and wellbeing. Active mediation is more likely to take place in families with educated parents who also use digital tools for communication, socialisation and learning. Teenagers in these contexts are likely to use social media to interact with their peers and their parents and other family members, increasing family interconnectedness. The findings in this study revealed an interesting relationship between parent control over their children and digital play, consistent with the findings from a study by Padilla-Walker and Coyne (2011) in which parents who exercised low control over their 10- to 11-year-olds were more likely to allow excessive screen exposure. In contrast, parents who exercised control and used both active and restrictive mediation techniques were better able to moderate their children’s screen use, suggesting that restrictive mediation can be applied through parent control over their children’s online interactions. Furthermore, positive communication and emotional closeness between parents and 14-year-olds in this study were found to relate to spending less time on social media, pointing to a form of active mediation being in action. It appears that restrictive and active mediation are not mutually exclusive and can be applied simultaneously although they reflect different parenting practices, that is, restrictive mediation is associated with control whereas active mediation with positive communication and emotional closeness.

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Face-to-face Play and Parent-Young Person Interaction, Communication and Emotional Closeness As already discussed in previous chapters, peer interactions have important implications for children’s learning and wellbeing. Exposure to risk through play during childhood is believed to assist with developing risk-­ management strategies and coping mechanisms, and the ability to negotiate decisions about teenage substance use and relationships (Ungar 2009). Interacting with friends unsupervised offers opportunities to engage with and manage risk as part of the play. Venturing out without adults offers opportunities for experimentation with uncertainty and different ways of overcoming fears in young people’s interaction with nature and the built environment (Sandseter 2009). Analyses of associations between parenting aspects and face-to-face peer interactions revealed interesting results. Amongst 14-year-olds who hardly ever argued with their mother and father, nearly 60% played with friends unsupervised most days, whereas only one in five played with friends rarely. Also, whether or not young people’s arguments with parents most days was not found to relate to how often they played with their friends. A slightly higher percentage (42%) of 14-year-olds who often argued with their father and mother compared to those who hardly did (36%) played with their friends most weekends. The difference is small suggesting that the frequency of interacting with friends most days unsupervised and at weekends is high for most 14-year-olds regardless of how often they argued with their parents. As many 14-year-olds who were close to their mother and father as those who were not interacted with their friends most weekends. Similarly, amongst those who played with friends unsupervised often, the percentage of young people who reported closeness to their mother and father and those who did not is roughly the same. Closeness to parents was not found to relate to how often they played with friends face to face. A similar trend was found regarding discipline. Roughly equal numbers (around a third) of 14-year-olds who were disciplined by their parents and those who were not saw their friends most weekends. Around 30% of 14-year-­ olds whose parents exercised strong control about their whereabouts interacted with their friends most weekends, compared to over a half whose parents exercised low control. For parents who exercised control, fewer young people reported to interact with friends most weekends.

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In summary these findings suggest that emotional connectedness and verbal arguments between 14-year-olds and their parents were not found to associate with how often they played with their friends unsupervised during the week and at weekends. Also, as many as a third of 14-year-olds who were often disciplined by their parents as those who were not interacted with their friends often. In contrast, parent control about their whereabouts was found to be significant in that fewer 14-year-olds played with friends most days and weekends in families where parental control about where, when and with whom young people were with was high.

Extra-curricular Activities and Parent-Young Person Interaction, Communication and Emotional Closeness Extra-curricular activities are institutional and adult organised whose aim tends to be instrumental in maximising children’s skills and competitiveness in the market. Such activities are approached as ‘rational’ forms of play that offer young people the opportunity to develop physical, social and emotional skills while also contributing, albeit indirectly, to learning and school performance (Bradley and Conway 2016). In contrast to the decline of free play (Gray 2012; Holt et al. 2013), children’s participation in extra-curricular activities through cultural and sporting clubs have grown rapidly in size and scope in recent years. Their expansion is driven by consumer demand, state policy and parenting anxiety (Holloway and Pimlott-Wilson 2014; Karsten 2005; Katz 2008; Vincent and Ball 2007). Indeed, their growth reflects intensive parenting cultures in which middle-­class parents seek to ensure that their children have enjoyable and productive childhoods during which they develop social and cultural capital valuable in adult life (Karsten 2005; Lareau 2002; Vincent and Ball 2007). These instrumental forms of play and participation have contributed to a new phenomenon of the ‘overscheduled child’ (Katz 2008, 11) or the ‘Renaissance child’ (Vincent and Ball 2007, 888) who often participates in a mix of sporting and cultural activities in parallel with school commitments. As parents become increasingly concerned about political-­ economic futures and downward social mobility in western societies, they are keen to offer paid-off extra-curricular activities designed to bolster their children’s competitiveness and skills valued by the market. This is not to say that parents’ concerns and decisions are not rational, especially in

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light of current policy discourses about the role of parents in enhancing their children’s life chances and promote social mobility (Holloway and Pimlott-Wilson 2014). The findings showed that most parents in this study actively organised extra-curricular activities for their 14-year-olds. Between a quarter and a third of young people often went to cinema and attended youth clubs and around 30% went to galleries and museums and visited historic places several times a year. What is largely missing from this picture, however, is an analysis of these activities through the lens of parenting behaviours. In Chap. 2, extra-curricular activities were examined in relation to unequal childhoods by looking into markers of difference (e.g., gender, ethnicity, socioeconomic status). In this chapter, examining associations between parent-young person communication, parent control and discipline and 14-year-olds’ participation in extra-curricular activities revealed interesting relationships. Whether or not 14-year-olds argued with mother and father and were disciplined by them made little difference in the frequency with which they engaged in extra-curricular activities. In contrast, 14-year-­ olds whose parents exercised high control (M  =  30) over their whereabouts participated in extra-curricular activities more frequently compared to those whose parents exerted low control (M = 33).

Parenting Cultures and Teenage Play Parent-child emotional connectedness, communication, control and discipline were found to relate to 14-year-olds’ excessive use of social media and gaming, but not with the frequency with which they interacted with their friends face to face and participated in extra-curricular activities (except for parent control). Parent-child communication and emotional connectedness as well as parent control and discipline related to how many hours 14-year-olds spent online, whereas parent control related to the frequency of face-to-face peer interactions and participation in extra-­ curricular activities. These findings highlight the fluidity in interactions between parents and teenagers and how they relate to different forms of play (digital, face to face, extra-curricular activities). They also paint a picture of families as non-instrumental places where parent-child interactions are emotionally and intellectually charged, but not necessarily influential in shaping teenage play in its various permutations. Parent-child interactions encompass a broad array of family resources, values, dialogic practices and cultural discourses which are likely to

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influence the importance placed on child social development and play, particularly play-based learning. Parent-child practices form the core of the ‘family habitus’ (Archer et al. 2014) that influences children’s social development through a combination of parents’ attitudes and emotional connectedness to their children, communication and cultural practices and forms of parent control and discipline. Aspects of the family habitus that encourage dialogic interactions between parents and adolescents may support play, especially play for learning purposes, although parent control was found to have a dampening effect on excessive digital play and face-­ to-­face, unsupervised peer interactions. In comparing 14-year-olds’ frequency of digital play, face-to-face peer interactions and participation in extra-curricular activities, the findings showed that whether or not teenagers participated in extra-curricular activities did not associate with the hours spent online visiting social networking sites or gaming or meeting friends face to face. This suggests that digital play, face-to-face peer interaction and participation in extra-­ curricular activities operate in parallel rather than in competition with each other. Although the remit of extra-curricular activities is different from that of unstructured play (digital or face to face) which is understood as a pleasurable activity, initiated by the young people themselves, both are popular among young people across demographic groups (as shown in Chap. 2). Young people did not see extra-curricular activities as competing with their digital play and peer interactions. This is consistent with a study by Holloway and Pimlott-Wilson (2014) in which children enjoyed doing extra-­curricular activities with their friends, and thought they would be bored without them, especially those they enjoyed. They also took pride in their achievements in gaining skills which gave them a sense of accomplishment. From children’s perspective, participation in extra-curricular activities was not seen as a threat to their free play. As Holloway argued, for many working-­class children, organised activities offered a welcome change from playing out with their friends. Middle-class children’s participation in extra-­curricular activities was more frequent, but they too valued them alongside free play (2014). Much literature on parenting and teenage digital use centres on discourses of the ‘responsible parent’ being a good gatekeeper of children’s screen time use and ensuring that the use of digital media is such that promotes learning and wellbeing. The notion of the responsible parent is located within neoliberal discourses whereby parents are construed as key agents in enhancing their children’s life chances through accessing

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educational resources (both online and offline) and mediating their children’s online exposure. The findings in this chapter revealed that aspects of parenting relate to the frequency of social media use but not so much to face-to-face peer interactions and participation in extra-curricular activities. Also, as discussed in Chap. 2, 14-year-olds in families with high income and parent education tended to spend less time playing online and interacting with peers unsupervised and more time in participating in extra-curricular activities. Although positive communication and emotional connectedness, as well as control and discipline, between parents and teenagers shape how much time they spent online, they did not appear to relate to face-to-face interactions and participation in extra-curricular activities (except for parent control). In contrast, social class was found to associate with all types of play, that is, digital play, face-to-face interactions and participation in extra-­curricular activities. This is consistent with previous studies (e.g., Rideout et  al. 2010), where children from low-income families were found to spend more time online on social and entertainment sites (games, TV, video, social networking) whereas those from wealthier families spent time on learning/enrichment activities. The difference in how children spend their time is typically discussed along a ‘time-wasting gap’ between poor and economically better off children, being a measure of good parenting rather than of social class. Discussions on parenting and social media are often framed along discourses of risk whereby parents are not in control of what their children do in the virtual world. These notions of risk constitute children as vulnerable to internet dangers whereas the home environment and parenting are reconfigured as places where safety measures should be applied. Rarely are they referred to as reflections of social class. Research suggests that many parents across diverse groups believe in the importance of enrichment activities and that the gap in participation is getting narrower (Holloway and Pimlott-Wilson 2014). However, middle-class parents are more likely to access these activities and maintain them through mostly mothers’ work to support children take part in these activities (e.g., transport, materials, time allocated to organise activities). For less well-off parents, working long hours to earn income together with poor health relating to inequality, limiting their ability to support and protect young people, there is less monitoring of teenage digital encounters and limited access to enrichment activities. The findings have important implication beyond teenage online and offline play and play-based learning. They revealed interesting

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relationships between aspects of parenting or more precisely mothering (considering that the majority of respondents in MCS and Understanding Society datasets were mothers), and young people’s play and peer interactions, raising questions about the ethic of care itself (McDowell 2004; Schwiter 2013) and the ways in which mothering cultures manifest themselves in young people’s online and offline peer interactions, primarily driven by notions of risk in the era of parent anxiety. Parents are increasingly expected to provide enrichment activities to their children to develop physical and social skills in a risk-free environment. The findings however showed unequal access to extra-curricular activities based on social class, illuminating the role of play-based learning in reproducing social inequalities considering that middle-class children accrue social and cultural capital through the formation of social networks beyond their schools or immediate neighbourhood, at the same time as they developed their social skills (Bourdieu 1986; Holloway and Pimlott-Wilson 2014). From Bourdieu’s capital analysis, three interrelated types of capital are used to define how families engage with their daily parenting practices: economic capital, cultural capital and social capital (1986). Economic capital entails all material properties a person possesses, income and other financial assets. Cultural capital refers to parents’ cultural dispositions and knowledge they have about culture. Cultural capital is shaped and shapes tastes, norms and values, objectified in commodities and consumables, both in a materialistic way (e.g., acquired media technologies at home) and in a symbolic way (e.g., shared understanding and perceived meaning of media content). Social capital is defined by all the social obligations, connections and relationships that parents have with schools and civic institutions, communities, work environment, manifested in forming both bonding and capital in their interactions with diverse groups. Different forms of capital influence parenting practices and how they relate to their children, including opportunities they offer for play and peer interactions.

References Archer, L., DeWitt, J., & Willis, B. (2014). Adolescent boys’ science aspirations: Masculinity, capital, and power. Journal of Research in Science Teaching, 51(1), 1–30. Bourdieu, P. (1986). The forms of capital. In J. G. Richardson (Ed.), Handbook for theory and research for the sociology of education (pp.  241–258). Oxford: Greenwood Press.

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Bradley, J. L., & Conway, P. F. (2016). A dual step transfer model: Sport and non-­ sport extracurricular activities and the enhancement of academic achievement. British Educational Research Journal, 42(4), 703–728. Coyne, S. M., Radesky, J., Collier, K. M., Gentile, D. A., Linder, J. R., Nathanson, A. I., … Rogers, J. (2017). Parenting and digital media. Pediatrics, 140(Suppl. 2), S112–S116. Faircloth, C., Hoffman, D. M., & Layne, L. L. (2013). Parenting in global perspective: Negotiating ideologies of Kinship, self and politics. London: Routledge. Gillies, V., Edwards, R., & Horsley, N. (2017). Challenging the politics of early intervention: Who’s ‘saving’ children and why. Bristol: Policy Press. Gray, R. (2012). Physical health and mental illness: A silent scandal. International Journal of Mental Health Nursing, 21(3). Grolnick, W. S., Raftery-Helmer, J. N., Flamm, E. S., Marbell, K. N., & Cardemil, E.  V. (2015). Parental provision of academic structure and the transition to middle school. Journal of Research on Adolescence, 25, 668–684. Hartas, D. (2014). Parenting, family policy and children’s well-being in an unequal society: A new culture war for parents. London: Palgrave Macmillan. Holloway, S.  L., & Pimlott-Wilson, H. (2014). Enriching Children, Institutionalizing Childhood? Geographies of Play, Extra-Curricular Activities, and Parenting in England. Annals of the Association of American Geographers, 104(3), 613–627. https://doi.org/10.1080/00045608.2013.846167 Holt, L., Bowlby, S., & Lea, J. (2013). Emotions and the habitus: Young people with socio-emotional differences (re)producing social, emotional and cultural capital in family and leisure space-times. Emotion, Space and Society, 9, 33–41. https://doi.org/10.1016/j.emospa.2013.02.002 Karsten, L. (2005). It all used to be better? Different generations on continuity and change in urban children’s daily use of space. Children’s Geographies, 3(3), 275–290. https://doi.org/10.1080/14733280500352912 Katz, C. (2008). Childhood as spectacle: Relays of anxiety and the reconfiguration of the child. Cultural Geographies, 15(1), 5–17. https://doi.org/10.1177/ 147447400708577 Lareau, A. (2002). Invisible inequality: Social class and childrearing in black and white families. American Sociological Review, 67, 747–776. Livingstone, S., Nandi, A., Banaji, S., & Stoilova, M. (2017b). Young adolescents and digital media uses, risks and opportunities in low- and middle-income countries: A rapid evidence review. London: DFID/ODI: Gender and Adolescence, Global Evidence. [online]. Livingstone, S., Ólafsson, K., Helsper, E. J., Lupiáñez-Villanueva, F., Veltri, G. A., & Folkvord, F. (2017a). Maximizing opportunities and minimizing risks for children online: The role of digital skills in emerging strategies of parental mediation. Journal of Communication, 67(1), 82–105.

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McDowell, L. (2004). Work, workfare, work/life balance and an ethic of care. Progress in Human Geography, 28(2), 145–163. Padilla-Walker, L. M., & Coyne, S. M. (2011). “Turn that thing off!” parent and adolescent predictors of proactive media monitoring. Journal of Adolescence, 34(4), 705–715. Radesky, J. S., Peacock-Chambers, E., Zuckerman, B., & Silverstein, M. (2016). Use of mobile technology to calm upset children: Associations with social-­ emotional development. JAMA Pediatrics, 170(4):397–399. pmid:26928293. Rideout, V., Foehr, U., & Roberts, D. (2010). Generation M2: Media in the lives of 8–18 year-olds. Kaiser Family Foundation. Retrieved from http://www.kff. org/entmedia/upload/8010.pdf Sandseter, E.  B. H. (2009). Characteristics of risky play. Journal of Adventure Education and Outdoor Learning, 9, 3–21. Schwiter, K. (2013). Neoliberal subjectivity—Difference, free choice and individualised responsibility in the life plans of young adults in Switzerland. Geographica Helvetica, 68(3), 153–159. Ungar, M. (2009). Too safe for their own good: How risk and responsibility help teens thrive. Toronto: McClelland & Stewart. Vansteenkiste, M., & Ryan, R. M. (2013). On psychological growth and vulnerability: Basic psychological need satisfaction and need frustration as a unifying principle. Journal of Psychotherapy Integration, 23(3), 263. Vincent, C., & Ball, S. (2007). Making up’ the middle-class child: Families, activities and class dispositions. Sociology, 41(6), 1061–1077. Wainwright, E., & Marandet, E. (2013). Family learning and the socio spatial practice of ‘supportive’ power. British Journal of Sociology of Education, 34(4), 504–524. https://doi.org/10.1080/01425692.2012.72387. Whitebread, D. (2017). Free play and children’s mental health. The Lancet Child & Adolescent Health, 1(3), 167–169. World Health Organisation. (2007). Helping parents in developing countries improve adolescents’ health. Geneva. [online]. Retrieved June 27, 2018.

CHAPTER 5

Conclusion: Teenagers in the Era of the ‘Super-Connected’ Selves

Abstract  We live in an era of ‘super-connected’ selves and young people’s social encounters and sense of place are shifted as their physical geographies shrink. Different permutations of teenage play (digital play, extra-­ curricular activities, face-to-face peer interactions) appear to coexist, reinforcing rather than replacing each other. Digital play does not seem to hamper teenage engagement with the physical world, face-to-face relationships and learning. This shows that the boundaries of digital and face-­ to-­face peer interactions are blurred and better understood when placed on a continuum of social experience. It is also true that online and offline teenage play reflects and reproduces social inequality. Social class, ethnicity, disability and gender differences are reflected in teenagers’ digital and face-to-face play. Questions still remain about notions of safe place and what virtual encounters do to young people’s mental health and wellbeing and the extent to which a wider social malaise is enabled by digital play/ social media. The democratisation of the internet has offered opportunities for young people’s voice to be heard but has also brought new challenges as self-expression becomes a process of peer validation, offering glimpses of a customised future and a sense of place that is very different from what psycho-geographers imagined. Keywords  Super-connected selves, Sense of place, Gender inequality

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Play is a social act, reflecting and reproducing unequal childhoods. It is also shaped by societal changes, the rapid rise of technology and urbanisation, the increasing corporatisation of public spaces and the degradation of the natural environment. Since the 70s, young people’s physical geographies have shrunk whereas virtual spaces have expanded. Many childhood theorists argue that children’s free play, unstructured and unsupervised by adults, is in decline being gradually replaced by adult-organised play for the purpose of learning and the development of new skills. Clearly these trends shape and are shaped by the orthodoxy of intensive parenting but also by wider social and economic changes. It is less clear however whether teenagers experience the dichotomy between free play and play with predetermined goals, and whether the shifting childhood geographies from physical to virtual spaces open new frontiers for teenage socialisation. Much research on children’s play has focused on face-to-face interactions in early and primary school years. Yet we know little about play and peer interactions across diverse groups of teenagers and their associations with wellbeing and learning/school attitudes and behaviours and educational aspirations. The findings from the MCS and Understanding Society analyses in this book showed that young people engaged in online and offline play as if one, moving from physical to virtual environments seamlessly. The national trends in the hours 14-year-olds spend online and offline highlighted a ‘rich-get-richer’ paradigm whereby the more hours they spent online, the more frequently they met with friends face to face. Excessive use of social media appeared to be fuelled by face-to-face peer interactions and vice versa. Likewise, play-based learning in the form of extra-curricular activities was found to coexist along with other forms of play, showing that different permutations of play operate in parallel rather than in competition with each other. The imaginative nature of play and the fulfilment of interacting with peers underpinned both digital and face-­ to-­face play as well as play-based activities. Digital play did not appear to hamper teenage engagement with the physical world, face-to-face relationships and learning. This shows the impossibility of separating digital from face-to-face encounters during peer interactions in that their boundaries are blurred and better understood when placed on a continuum of social experience. The differences observed in 14-year-olds’ play were expressed along the online/offline axis and also markers of inequality and disability. Young people in families with low income and parent education were found to spend excessive time online. Socioeconomic differences were also

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modestly reflected in face-to-face peer interactions and significantly in play-based learning where more young people from middle-class families participated in extra-curricular activities. Furthermore, young people’s wellbeing was seen through the lenses of online and offline play. Consistently with previous research, the findings pointed to associations between excessive social media use and reduced wellbeing in teenagers. Also, young people with poor behaviour and social emotional difficulties were more likely to spend excessive time on social media and gaming. We cannot draw causal conclusions between mental health and wellbeing and time spent in virtual environments, but it is safe to assume that by keeping young people in a continual state of anxiety, anger, fear by encouraging them to believe that everyone else is better off than they are, is detrimental for their wellbeing albeit profitable for companies who rely on consumerism generated through young people’s digital encounters. We should not forget that digital encounters can also be a force for good by introducing technologies and products that provide young people with a sense of wellbeing and a space for self-expression and learning. For most young people virtual encounters are guided by the desire to educate themselves, communicate with others and share their experiences, and create networks of enterprise and culture, particularly important in a global society. This does not mean that technology-mediated social interactions, including digital play, do not bring new challenges to the fore. The effects of digital play are subtle and long term, encouraging teenagers to live a customised life facilitated by their digital encounters within shifting spatial and psycho-social spaces. Excessive digital play (e.g., social media use) competes with other forms of socialisation and learning, magnifying society’s ills and threatening human autonomy, agency and capability building in the long run. And this raises important questions about play and peer interactions for today’s young people. As different virtual platforms fight to capture their attention with promises that networked artificial intelligence will amplify human capabilities on tasks such as complex decision making, the question to ask is whether play (in all its permutations) can still fulfil the human need for connectedness and exploration, or whether it can become a tool to engineer an even more customised future. More questions however remain: is ill mental health in young people directly associated with increased virtual encounters? Or is reduced wellbeing a sign of a wider social malaise enabled by digital play, social media in particular? As De Almeida and colleagues argued, there is a dichotomy between virtual environments and physical, material environments, as well

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as ‘between human–computer interaction and human–human interaction’ (De Almeida et al. 2015, 2). However, it is overly simplistic to consider one superior to the other. As machine learning advances, the gap between human-human and human-computer interactions is likely to narrow, although we do not know what this means for young people’s socialisation and wellbeing. In a similar vein to interactions in the physical world, virtual interaction can be positive and negative. A key difference however is that interactions in the physical world are contextualised, operating within defined cultural and socioeconomic parameters within which individuals exercise agency, whereas virtual interactions are not, promoting an abstract version of interactivity and interconnectivity. As Murray argued ‘interactivity cannot be a design goal in itself’, stressing the importance of virtual encounters to also promote agency and capability building for the people involved in the interaction (2011, 12).

Space and the ‘Super-Connected’ Selves In examining teenage online and offline play, issues about personal agency and technology-mediated selfhood, a sense of place in nonmaterial worlds, childhood geographies and safe places take on new meanings. Space and selfhood are interlinked through young people’s interactions, with notions of safe space being redefined as we move from offline to online encounters. As Djohari and colleagues attested, a safe space is a fluid concept that encompasses informal networks found in social contexts such as families, education and social institutions (2018). Safe places matter in young people’s life. Through online and offline peer interactions and play, young people co-produce safe places, places for experimentation and self-­ expression. In young people’s extra-curricular activities, safe space refers to material locations where they are kept safe from strangers and risks, places condoned by parents or other adults. A safe space as a material location has increasingly been subjected to surveillance and restricted freedom of movement by a risk adverse society fearful of children as both perpetrators and ‘victims’ of unsafe neighbourhoods (Hartas 2014; Rudner 2012). Increasingly, a safe space is portrayed as a sanitised space within which children interact socially, a view that is far removed from that espoused by psycho-geographers. Safe spaces are thought to offer an emotional, intellectual and social safety to enable young people to engage critically with the world around them and contest dominant discourses that silence them, especially people

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who are different and whose childhoods and teenage experiences are unequal (Bucher and Lee Manning 2005; Fetner et  al. 2012).Virtual spaces are safe as long as they encompass a set of conditions where young people feel free to experiment with new ideas about selfhood and identity, encounter unorthodox or ‘dangerous’ ideas, engage in debate, make mistakes and develop creative learning behaviours and attitudes. Increasingly however, digital spaces function less as safe spaces or a ‘comfort zone’ for young people to learn something new and have a voice about aspects of life they may otherwise self-censure to avoid social criticism. In most virtual spaces free speech and debate are policed, if not curtailed, and self-­ censorship is encouraged. Instead of debate, echo chambers are formed where racism, intolerance and misogyny rein. Echo chambers and pressure to submit to ideal bodies and lives do not enable young people to ‘express themselves, to play and experiment with multiple selves, and to resist, negotiate, escape or rewrite the social and structural pressures that influences control over many aspects of their lives’ (Djohari et al. 2018, 351). Virtual spaces created on social media may be less of safe spaces and more of surveillance spaces where young people are subjected to predetermined modes of expression and identity formation with direct implications for their wellbeing, socialisation and learning. Some commentators believe that we live in the age of attention economy and the challenges we face are, on both individual and collective levels, challenges of self-­ regulation (Williams 2018). We seem to have lost the capacity to concentrate, being perpetually distracted, in that ‘digital technologies have transformed our experiential world into a never-ending flow of potential informational rewards’ (2018, 1). By being exposed to a torrent of information and instant rewards we may stop attending and noticing other experiences, goals we set but did not find the time to pursue them, landscapes of possibility that did not materialise. Echo chambers fuel further societal fragmentation because we no longer talk about collective goals and shared interests, moving further away from agreeing what common good looks like. It is not hard to see the consequences of fragmentation at a collective level for teenage social interactions. Selfhood and space are interwoven, and this goes at the heart of young people’s social interactions and play. Horton and Kraftl stressed the importance of the affective qualities of space, to consider ‘space’ as a ‘verb’ of becoming which describes a dynamic social and material relationship, a way of being and interacting that continually makes the conditions required for free expression, playful exploration or escape (2006, 86).

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Djohari and colleagues stressed that it is what people ‘do’ and their interaction with space that explain how and why ‘safe spaces’ become mentally, physically and emotionally restorative and not whether space is physical or material as an entity (2018). Safe places are not fixed but evolving social configurations as children move through virtual and material worlds where the boundaries are blurred. Virtual and face-to-face encounters could equally be toxic or empowering. Young people operate within spaces that are not just a background to their activities but an integral part of their life. And although young people move seamlessly across their boundaries, virtual and material spaces differ in whether they allow them to shape and reshape safe places and along this their own identities and self-hoods, or whether they are determined by it or subject to it. As Djohari and colleagues argued ‘safe spaces are co-created, co-imagined and co-experienced, born out of ongoing, renewing and ever-evolving relationships with others’ (2018, 353). It matters to young people to co-construct safe spaces to enable them to grapple with conflicting feelings and develop a sense of belonging and rootedness, a sense of place.

A Sense of Virtual Place Social media foster the perception of imaginative access whereby social media users interact with a rural or urban setting as a place. This is driven by a process called by Escalas ‘narrative transportation’, which refers to virtual mobility that takes viewers mentally and emotionally to a nonmaterial place. Considering that a sense of place is adaptable and unique for each individual, one may argue that it can be mediated by social media. However, this would require a shift in our sense of place which is constructed based on second-order rather than direct experiences of physical places gained by experiencing a place through technology. As such, people’s experience of a place is not obtained directly through their physical senses but emerges from someone else’s personal reflections. As Dameria and colleagues commented, ‘a person’s shared experience becomes another person’s inspiration for dreaming’ in social media (2018, 9). Young people can still develop a sense of a place mediated by technology through indirect experience and meaning attributed to it because a sense of a place should not be constrained by its physicality or materiality. A place can be physical as well as psychological and imaginative, and interactions within such places create a legitimate lived experience, albeit an impermanent one, for young people.

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Are Virtual Places Unequal? The democratisation brought by the internet has not removed inequalities, including gender inequalities, in how young people interact digitally but also in terms of accessing extra-curricular activities. The mechanisms of exclusion may be different in virtual places but no less powerful. Who speaks and who gets heard are important questions and we should not assume that because the internet have given a ‘voice’ and a mode of expression to a generation of young people, their voices are heard. The social, cultural and economic structures that determine who gets heard and who does not are hierarchical and, as we saw in Chap. 2, young people, girls in particular, have unequal access to physical and virtual spaces, so the assumption that all young people can have a voice and be heard in the cyberspace is contested. In the popular culture, social media are seen as allowing girls and young women to express themselves by offering a platform to articulate their identities (often marginalised identities), communicate their own perspectives and experiences, creatively document their life worlds, seek support and validation from peers and forge relationships (Kearney 2011; Mazzarella 2010). At the same time, certain forms of self-expression, such as self-disclosure, and narrow representations of femininity (e.g., thin bodies) are ascribed more value than others in the process of commodification of young women’s identity, which is encouraged through upward comparisons as well as discourses of female empowerment. Although social media offer them a platform to have a voice and express their identities, teenage girls’ ascribed value according to narrow criteria and ‘branding’ is likely to affect negatively how they see and value themselves. The process of self-expression becomes a process of peer validation and self-promotion where ideas and worldviews do not matter as much as how the self is presented and validated. Teenage girls are compelled to perform acts of femininity that encourage self-disclosure and self-exposure presented as being acts of self-determination, driven by a liberated and empowered self. Girls online are expected to personally reconcile the ambivalences and tensions generated by gender inequality rather than approaching this as a political problem requiring political solutions. We need to understand the cultural conditions that are responsible for commodification of girls’ self-expression and identity formation and the pressure of branding—packaging and selling—the self to gain peer validation and acceptance in virtual places.

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In a society where the market is the ultimate arbiter of social interactions and where the onus is placed on individuals to reverse inequality, including gender inequality, the trends in how teenage girls use social media exemplify a form of neoliberal feminism (Rottenberg 2014), a type of feminism that does not challenge the neoliberal order but enables it by ‘inaugurating new organisations of gendered social relations predicated on the framing of individual subjects as self-managing, self making, entrepreneurial actors’ (Toffoletti and Thorpe 2018, 17). As Rottenberg observed, ‘the neoliberal feminist subject is thus mobilized to convert continued gender inequality from a structural problem into an individual affair’ (2014, 420), taking personal responsibility for her own wellbeing, educational opportunities and life chances. And if she is found not managing the self as well as expected, it is then the self to blame rather than the socioeconomic and cultural conditions that gave rise to gender inequality in the first place. A more nuanced approach to understanding associations between social media and girls’ wellbeing is to examine what having a voice and an online presence mean through the lens of neoliberal feminism. Banet-Weiser observed a shift from ‘the politics of visibility to economies of visibility’, with girls and young women investing in themselves through prescribed forms of self-care and self-advancement along notions of ‘branding’ as a means of reducing the effects of gender inequality on their life (2015, 55). Banet-Weiser distinguishes between the ‘politics of visibility’ which have been articulated by second-wave feminism along the lines of recognising inequality and power dynamics and how they affect women’s life and the ‘economies of visibility’ whereby visibility is not for the purpose of ascertaining women’s social and economic rights but for self-promotion as a means of maximising profit. The malaise young women are more likely than men to experience on social media sites reflects a wider social malaise of transforming citizens into consumers, sellers and buyers in neoliberal societies. Visibility of predetermined forms of feminine selfhood in social media becomes the new currency whose value fluctuates along ‘likes’ and ‘shares’, having a deleterious impact on young women’s identity construction. The feminine body is commodified and largely subject to evaluation, judgement and scrutiny, becoming an object for general consumption while at the same time young women are told that they exercise freedom and choice (Banet-Weiser 2015). The effects of these are magnified for young people who have experienced unequal childhoods and marginalisation, and whose currency

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in online platforms may be reduced as a result. Even if they are in the ‘right’ demographic group (White, thin bodied, young) to grab attention and enhance their visibility, the pressure on young women to perform in certain ways is bound to affect negatively how they relate to others and their general wellbeing. Ultimately the message they receive is that, instead of promoting collective forms of activism towards social injustice, inequality and discrimination, teenage girls should work on the self in terms of raising their self-esteem and self-presentation to meet impossible, narrow and arbitrary body standards in online competitions. Social media are not intrinsically good or bad but a tool whose uses are shaped by the wider social and cultural contexts that surround young people’s life. Goodwin and colleagues argued that social media facilitate the promotion of forms of self-presentation akin to neoliberal self-branding because they operate within neoliberal societies (Goodwin et  al. 2016). Digital media promote self-enhancement not achieved through equal opportunities, quality education and access to public services but by increasing the visibility of highly curated bodies. Hypersexualised images which, through the lenses of second-wave feminism, were seen as attempts at women’s objectification by the patriarchy are now promoted by young women themselves to meet expectations to portray a confident and self-­ empowered sexuality, often appropriating the language of rights and social justice along the way. Young people, girls and women in particular, are portrayed as having the freedom and choice to ‘enjoy life’ and this creates a dissonance with their lived experiences which, especially for marginalised young people, are often choiceless. Young people’s online and offline interactions are mirrors to the present culture where ideas are replaced by feelings and debates are reduced to ‘likes’ and ‘shares’. Young people have always used what tools society offers to explore, experiment, socialise and learn from each other and, as discussed in this book, teenage play’s boundaries are porous moving from visiting social network sites and gaming to meeting friends out of school and participating in extra-curricular activities. At the same time, teenagers seek places of refuge and lived experiences away from adults. But they should be aware that their super-connected selves are mostly exposed to what the gatekeepers online allow citizens to access, with filtering, fake news, self-censorship and eco chambers being the products of a larger social ecology. Ideally, young people can benefit from both physical and virtual interactions. However, for this to happen, we need a new political and moral renaissance.

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Final Thoughts I hope I offered a balanced view on how UK teenagers interact online and offline through the lenses of social class, gender and other markers of difference. Although the mechanisms through which online and offline play translates into wellbeing and learning are multi-faceted and difficult to untangle, it is true to say that play, in all its permutations, is central to teenage life. Online interactions mirror society, albeit in an amplified manner, and young people’s use of digital technologies has given them new modes of self-expression and creative engagement with the world, beyond their immediate physical geographies. Whether a sense of place and belonging for this generation can be found in their virtual encounters remains to be seen. Will they, through digital play, develop new ways to connect people and places, redraw boundaries physical and social? Would they be able to commit memories and storytelling to digital spaces? I do not have answers to these questions and feel somewhat ambivalent about digital media in particular as fora for teenage socialisation and interconnectedness and, more generally, about the internet as a space of possibility and wander, of connecting with spaces and their histories, at least in the way the psycho-geographers of the mid-twentieth century did.

References Banet-Weiser, S. (2015). Media, markets, gender: Economies of visibility in a neoliberal moment. The Communication Review, 18, 53–70. Bucher, K., & Manning, M. L. (2005). Creating safe schools. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 79(1), 55–60. https:// doi.org/10.3200/TCHS.79.1.55-60 Dameria, C., Akbar, R., & Indradjati, P.  N. (2018). Whose sense of place? Re-thinking place concept and urban heritage conservation in social media era. In IOP conference series: Earth and environmental science (Vol. 158, No. 1, p. 012010). IOP Publishing. De Almeida, A. N., Delicado, A., & De Almeida Alves, N. (2015). Internet, children and space: Revisiting generational attributes and boundaries. New Media & Society, 17(9), 1436–1453. Djohari, N., Pyndiah, G., & Arnone, A. (2018). Rethinking ‘safe spaces’ in children’s geographies. Children’s Geographies, 16(4), 351–355. Fetner, T., Elafros, A., Bortolin, S., & Drechsler, C. (2012). Safe spaces: Gay-­ straight alliances in high schools. Canadian Review of Sociology/Revue Canadienne de Sociologie, 49(2), 188–207. https://doi.org/10.1111/ j.1755-618X.2011.01290

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Goodwin, I., Griffin, C., Lyons, A., McCreanor, T., & Barnes, H.  M. (2016). Precarious popularity: Facebook drinking photos, the attention economy, and the regime of the branded self. Social Media + Society, 2, 1–13. Hartas, D. (2014). Parenting, family policy and children’s well-being in an unequal society: A new culture war for parents. London: Palgrave Macmillan. Horton, J., & Kraftl, P. (2006). What else? Some more ways of thinking and doing children’s geographies. Children’s Geographies, 4(1), 69–95. https://doi. org/10.1080/14733280600577459 Kearney, M. C. (2011). Mediated girlhoods: New explorations of girls’ media culture. New York, NY: Peter Lang. Mazzarella, S. (2010). Girl wide web 2.0: Revisiting girls, the internet, and the negotiation of identity. New York, NY: Peter Lang. Murray, J. H. (2011). Inventing the medium: Principles of interaction design as a cultural practice. Cambridge, MA; London: The MIT Press. Rottenberg, C. (2014). The rise of neoliberal feminism. Cultural Studies, 28, 418–437. Rudner, J. (2012). Public knowing of risk and children’s independent mobility. Progress in Planning, 78(1), 1–53. https://doi.org/10.1016/j. progress.2012.04.001 Toffoletti, K., & Thorpe, H. (2018). Female athletes’ self-representation on social media: A feminist analysis of neoliberal marketing strategies in “economies of visibility”. Feminism & Psychology, 28(1), 11–31. Williams, J. (2018). Technologies driving us to distraction. The Guardian. Retrieved March 2019, from https://www.theguardian.com/commentisfree/2018/may/27/world-distraction-demands-new-focus.

References

Aarseth, H. (2017). Fear of falling—Fear of fading: The emotional dynamics of positional and personalized individualism. Sociology, 1–16. https://doi. org/10.1177/0038038517730219 Abbott-Chapman, J., & Robertson, M. (2009). Adolescents’ favourite places: Redefining the boundaries between private and public space. Space and Culture, 12(4), 419–434. Aggio, D., Gardner, B., Roberts, J., Johnstone, J., Stubbs, B., Williams, G., … Smith, L. (2017). Correlates of children’s independent outdoor play: Cross-­ sectional analyses from the Millennium Cohort Study. Preventive Medicine Reports, 8, 10–14. Akerlof, G., & Kranton, R. (2000). Economics and identity. The Quarterly Journal of Economics, 115(3), 715–753. Akerlof, G. A., & Kranton, R. E. (2002). Identity and schooling: Some lessons for the economics of education. Journal of Economic Literature, 40(4), 1167–1201. Alparone, F. R., & Pacilli, M. G. (2012). On children’s independent mobility: The interplay of demographic, environmental, and psychosocial factors. Children’s Geographies, 10(1), 109–122. American Psychological Association. (2007). Report of the APA task force on the sexualization of girls. Retrieved February 3, 2016, from http://www.apa.org/ pi/women/programs/girls/report.aspx. Angold, A., Costello, E.  J., Messer, S.  C., Pickles, A., Winder, F., & Silver, D. (1995). The development of a short questionnaire for use in epidemiological studies of depression in children and adolescents. International Journal of Methods in Psychiatric Research, 5, 237–249.

© The Author(s) 2020 D. Hartas, Young People’s Play, Wellbeing and Learning, https://doi.org/10.1007/978-3-030-60001-3

105

106 

REFERENCES

Archer, L. (2003). ‘Race’, masculinity and schooling: Muslim boys and education. Buckingham: Open University Press. Archer, L., DeWitt, J., & Willis, B. (2014). Adolescent boys’ science aspirations: Masculinity, capital, and power. Journal of Research in Science Teaching, 51(1), 1–30. Ash, J., & Gallacher, L. A. (2011). Cultural geography and videogames. Geography Compass, 5, 351–368. https://doi.org/10.1111/j.1749-8198.2011.00427 Bagwell, C., & Schmidt, M. (2013). Friendships in childhood and adolescence. Guilford Press. Banet-Weiser, S. (2015). Media, markets, gender: Economies of visibility in a neoliberal moment. The Communication Review, 18, 53–70. Beavis, C., Muspratt, S., & Thompson, R. (2015). Computer games can get your brain working: Student experience and perceptions of digital games in the classroom. Learning, Media and Technology, 40(1), 21–42. Behrenshausen, B.  G. (2012). The active audience, again: Player-centric game studies and the problem of binarism. New Media & Society, 15(6), 872–889. Berk, L. E. (2018). The role of make-believe play in development of self-­regulation. tema. [en línea]. Retrieved from http: //www. child-encyclopedia.com/playbased-learning/accordingexperts/role-make-believe-play-development-selfregulation. Publicado: Febrero. Berkout, O. V., Young, J. N., & Gross, A. M. (2011). Mean girls and bad boys: Recent research on gender differences in conduct disorder. Aggression and Violent Behavior, 16(6), 503–511. Black, J., Castro, J. C., & Lin, C.-C. (2015). Youth practices in digital arts and new media: Learning in formal and informal settings. New  York: Palgrave Macmillan. Blau, F., Brinton, M., & Grusky, D. (2006). The declining significance of gender? New York: Russell Sage Foundation. Blum, C., & Parette, H. P. (2015). Universal design for learning and technology in the early childhood classroom. In Young children and families in the information age (pp. 165–182). Dordrecht: Springer. Blum-Ross, A., & Livingstone, S. (2017). Sharenting: Parent blogging and the boundaries of the digital self. Popular Communication, 15(2), 110–125. Booker, C., Yvonne, J. K., & Sacker, A. (2018). Gender differences in the associations between age trends of social media interaction and well-being among 10–15 year olds in the UK. BMC Public Health BMC, 18, 321. Bourdieu, P. (1986). The forms of capital. In J. G. Richardson (Ed.), Handbook for theory and research for the sociology of education (pp.  241–258). Oxford: Greenwood Press. Bradley, J. L., & Conway, P. F. (2016). A dual step transfer model: Sport and non-­ sport extracurricular activities and the enhancement of academic achievement. British Educational Research Journal, 42(4), 703–728.

 REFERENCES 

107

Branisa, B., Klasen, S., Ziegler, M., Drechsler, D., & Jütting, J. (2014). The institutional basis of gender inequality: The social institutions and gender index (SIGI). Feminist Economics, 20(2), 29–64. https://doi.org/10.1080/1354570 1.2013.850523 Braun, H. (Ed.). (2016). Meeting the Challenges to Measurement in an Era of Accountability. Routledge. Braun, S. S., & Davidson, A. J. (2017). Gender (Non) conformity in middle childhood: A mixed methods approach to understanding gender-typed behavior, friendship, and peer preference. Sex Roles, 77, 16–29. https://doi. org/10.1007/s11199-016-0693-z Brussoni, M., Gibbons, R., Gray, C., Ishikawa, T., Beate, E., Sandseter, H., … Tremblay, M. C. (2015). What is the relationship between risky outdoor play and health in children? A systematic review. International Journal of Environmental Research and Public Health, 12, 6423–6454. Bucher, K., & Manning, M. L. (2005). Creating safe schools. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 79(1), 55–60. https:// doi.org/10.3200/TCHS.79.1.55-60 Buckingham, D., & Sefton-Green, J. (2003). Gotta catch’em all: Structure, agency and pedagogy in children’s media culture. Media, Culture & Society, 25(3), 379–399. Cabieses, B., Pickett, K.  E., & Wilkinson, R.  G. (2016). The impact of socioeconomic inequality on children’s health and well-being (pp. 244–265). New York, NY: Oxford University Press. Carver, A. B., Watson, B. S., & Hillman, M. (2013). A comparison study of children’s independent mobility in England and Australia. Children’s Geographies, 11(4), 461–475. https://doi.org/10.1080/14733285.2013.812303 Cash, S., Thelwall, M., Peck, S., Ferrell, J., & Bridge, J. (2013). Adolescent suicide statements on MySpace. Cyberpsychology, Behavior and Social Networking, 16, 166–174. Chahal, K., & Julienne, L. (1999). We can’t all be white!: Racist victimisation in the UK. York: York Publishing Services/Joseph Rowntree Foundation. Cingel, D. P., & Krcmar, M. (2013). Predicting media use in very young children: The role of demographics and parent attitudes. Communication Studies, 64(4), 374–394. Corbis, M. (2018). A.I. experts warn of loss of free will, need for morality. The Washington Times. Accessed online (2020) from https://www.washingtontimes.com/news/2018/dec/11/i-experts-warn-loss-free-will-need-morality/. Coyne, S. M., Radesky, J., Collier, K. M., Gentile, D. A., Linder, J. R., Nathanson, A. I., … Rogers, J. (2017). Parenting and digital media. Pediatrics, 140(Suppl. 2), S112–S116. Crozier, G., Reay, D., & James, D. (2011). Making it work for their children: White middle-class parents and working-class schools. International Studies in Sociology of Education, 21(3), 199–216.

108 

REFERENCES

Dameria, C., Akbar, R., & Indradjati, P.  N. (2018). Whose sense of place? Re-thinking place concept and urban heritage conservation in social media era. In IOP conference series: Earth and environmental science (Vol. 158, No. 1, p. 012010). IOP Publishing. Davis, K. (2012). Friendship 2.0: Adolescents’ experiences of belonging and self-­ disclosure online. Journal of Adolescence, 35(6), 1527–1536. De Almeida, A. N., Delicado, A., & De Almeida Alves, N. (2015). Internet, children and space: Revisiting generational attributes and boundaries. New Media & Society, 17(9), 1436–1453. Deaux, K., & Martin, D. (2003). Interpersonal networks and social categories: Specifying levels of context in identity processes. American Sociological Review, 66(2), 101–117. https://doi.org/10.2307/1519842 Debord, G. (1958). Definitions. Internationale Situationniste #1 (Paris, June 1958). Translated by Ken Knabb. Dermott, E., & Pantazis, C. (2014). Gender and poverty in Britain: Changes and continuities between 1999 and 2012. Journal of Poverty and Social Justice, 22(3), 253–269. Devine, P., & Lloyd, K. (2012). Internet use and psychological well-being among 10-year-old and 11-year-old children. Child Care in Practice, 18(1), 5–22. Dezuanni, M., O’Mara, J., & Beavis, C. (2015). ‘Redstone is like electricity’: Children’s performative representations in and around mine craft. E-Learning and Digital Media, 12(20), 147–163. Diener, E. D., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71–75. Djohari, N., Pyndiah, G., & Arnone, A. (2018). Rethinking ‘safe spaces’ in children’s geographies. Children’s Geographies, 16(4), 351–355. Ehenreich, B. (1989). Fear of falling: The inner life of the middle class. New York: Pantheon. Eisenberg, N., Spinrad, T. L., & Sadovsky, A. (2006). Empathy-related responding in children. Handbook of Moral Development, 517, 549. Elgar, F., Gariepy, G., Torsheim, T., & Currie, C. (2016). Early-life income inequality and adolescent health and wellbeing. Social Science and Medicine, 174, 197–208. Ellison, N.  B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computing Communication, 12(4), 1143–1168. Espelage, D., & Holt, K. (2013). Suicidal ideation and school bullying experiences after controlling for depression and delinquency. Journal of Adolescent Health, 53, 27–31. Faircloth, C., Hoffman, D. M., & Layne, L. L. (2013). Parenting in global perspective: Negotiating ideologies of Kinship, self and politics. London: Routledge.

 REFERENCES 

109

Fetner, T., Elafros, A., Bortolin, S., & Drechsler, C. (2012). Safe spaces: Gay-­ straight alliances in high schools. Canadian Review of Sociology/Revue Canadienne de Sociologie, 49(2), 188–207. https://doi.org/10.1111/j.1755618X.2011.01290 Finch, L., Hargrave, R., Nichols, J., & van Vliet, A. (2014). Measure what you treasure: Well-being and young people, how it can be measured and what the data tell us. New Philanthropy Capital. Retrieved May 28, 2014, from http:// www.thinknpc.org/ publications/measure-what-you-treasure/. Freeman, C., van Heezik, Y., Stein, A., & Hand, K. (2016). Technological inroads into understanding city children’s natural life-worlds. Children’s Geographies, 14(2), 158–174. Freier, N. G., & Kahn, P. H., Jr. (2009). The fast-paced change of children’s technological environments. Children, Youth and Environments, 19, 1–11. Ganong, L. H., Coleman, M., Fiestman, R., Jamison, T., & Markham, M. S. (2012). Communication technology and post-divorce co-parenting. Family Relations: An Interdisciplinary Journal of Applied Family Studies, 61, 397–409. https:// doi.org/10.1111/j.1741-3729.2012.00706 Gentile, D. A., & Walsh, D. A. (2002). A normative study of family media habits. Journal of Applied Developmental Psychology, 23(2), 157–178. Gillespie, B. J., Lever, J., Frederick, D., & Royce, T. (2015). Close adult friendships, gender, and the life cycle. Journal of Social and Personal Relationships, 32(6), 709–736. https://doi.org/10.1177/0265407514546977 Gillies, V., Edwards, R., & Horsley, N. (2017). Challenging the politics of early intervention: Who’s ‘saving’ children and why. Bristol: Policy Press. Girlguiding. (2015). Girls’ Attitude Survey 2015. Retrieved March 1, 2016, from http://new.girlguiding.org.uk/latest-updates/making-a-difference/ girls-attitudes-survey-2015. Goodman, R., Ford, T., Simmons, H., Gatward, R., & Meltzer, H. (2000). Using the Strengths and Difficulties Questionnaire (SDQ) to screen for child psychiatric disorders in a community sample. The British Journal of Psychiatry, 1776, 534–539. Goodwin, I., Griffin, C., Lyons, A., McCreanor, T., & Barnes, H.  M. (2016). Precarious popularity: Facebook drinking photos, the attention economy, and the regime of the branded self. Social Media + Society, 2, 1–13. Gorbis, M. (2018). Without social organizations, social technologies will eat us alive. Accessed from https://boingboing.net/2018/11/26/without-socialorganizations.html on 26th October 2020. Gray, R. (2012). Physical health and mental illness: A silent scandal. International Journal of Mental Health Nursing, 21(3). Grolnick, W. S., Raftery-Helmer, J. N., Flamm, E. S., Marbell, K. N., & Cardemil, E.  V. (2015). Parental provision of academic structure and the transition to middle school. Journal of Research on Adolescence, 25, 668–684.

110 

REFERENCES

Hadley, K. G., & Nenga, S. K. (2004). From Snow White to Digimon: Using popular media to confront Confucian values in Taiwanese peer cultures. Childhood, 11(4), 515–536. Haidt, J. (2017). The unwisest idea on campus: Commentary on Lilienfeld (2017). Hall, J.  A. (2011). Sex differences in friendship expectations: A meta-analysis. Journal of Social and Personal Relationships, 28(6), 723–747. https://doi. org/10.1177/0265407510386192 Hancock, R., & Gillen, J. (2007). Safe places in domestic spaces: Two-year-olds at play in their homes. Children’s Geographies, 5(4), 337–351. https://doi. org/10.1080/14733280701631775 Harris, A. (2014). Young people and everyday multiculturalism. London: Routledge. Hartas, D. (2011). Families’ social backgrounds matter: Socio-economic factors, home learning and young children’s language, literacy and social outcomes. British Educational Research Journal, 37(6), 1469–3518. Hartas, D. (2012). Inequality and the home learning environment: Predictions about seven-year-olds’ language and literacy. British Educational Research Journal, 38(5), 859–879. Hartas, D. (2014). Parenting, family policy and children’s well-being in an unequal society: A new culture war for parents. London: Palgrave Macmillan. Hartas, D. (2019). The social context of adolescent mental health and wellbeing: Parents, friends and social media. Research Papers in Education, 1–19. https:// doi.org/10.1080/02671522.2019.1697734 Heckman, J., & Mosso, S. (2014). The economics of human development and social mobility. Annual Review of Economics, 6(1), 689–733. Hewitt, R. J., Pera, F. A., García-Martín, M., Gaudry-Sada, K. H., Hernández-­ Jiménez, V., & Bieling, C. (2020). Mapping adolescents’ sense of place and perceptions of change in an urban–rural transition area. Environmental Management, 65(3), 334–354. Heydenberk, R. A., & Heydenberk, W. R. (2017). Bullying reduction and subjective wellbeing: The benefits of reduced bullying reach far beyond the victim. International Journal of Wellbeing, 7(1), 12–22. Hollingworth, S., & Archer, L. (2010). Urban schools as urban places: School reputation, children’s identities and engagement with education in London. Urban Studies, 47(3), 584. Holloway, S.  L., & Pimlott-Wilson, H. (2014). Enriching Children, Institutionalizing Childhood? Geographies of Play, Extra-Curricular Activities, and Parenting in England. Annals of the Association of American Geographers, 104(3), 613–627. https://doi.org/10.1080/00045608.2013.846167 Holloway, S. L., & Valentine, G. (2003). Cyberkids: Children in the information age. London: Routledge. Holt, L. (2010). Young people’s embodied social capital and performing disability. Children’s Geographies, 8, 25–37. https://doi.org/10.1080/14733280 903500158

 REFERENCES 

111

Holt, L., Bowlby, S., & Lea, J. (2013). Emotions and the habitus: Young people with socio-emotional differences (re)producing social, emotional and cultural capital in family and leisure space-times. Emotion, Space and Society, 9, 33–41. https://doi.org/10.1016/j.emospa.2013.02.002 Horton, J., & Kraftl, P. (2006). What else? Some more ways of thinking and doing children’s geographies. Children’s Geographies, 4(1), 69–95. https://doi. org/10.1080/14733280600577459 International NGO. (2013). Council on violence against children. Violating children’s rights: Harmful practices based on tradition, culture, religion or superstition. Geneva. Iqbal, H., Neal, S., & Vincent, C. (2017). Children’s friendships in super-diverse localities: Encounters with social and ethnic difference. Childhood, 24(1), 128–142. Ito, M., Baumer, S., Bittanti, M., Boyd, D., Cody, R., Herr-Stephenson, B., … Tripp, L. (2009). Hanging out, messing around, and geeking out: Kids living and learning with new media. Cambridge, MA: The MIT Press. Jorgensen, B., & Stedman, R. (2006). A comparative analysis of predictors of sense of place dimensions: Attachment to, dependence on, and identification with lakeshore properties. Journal of Environmental Management, 79(3), 316–327. JRF Analysis Unit. (2017). UK Poverty 2017. York: Joseph Rowntree Foundation. Retrieved January 5, 2018, from https://www.jrf.org.uk/report/ uk-poverty-2017. Kagohara, D. M., van der Meer, L., Ramdoss, S., O’Reilly, M. F., Lancioni, G. E., Davis, T.  N., … Sigafoos, J. (2013). Using IPods® and IPads® in teaching programs for individuals with developmental disabilities: A systematic review. Research in Developmental Disabilities, 34, 147–156. https://doi. org/10.1016/j.ridd.2012.07.027 Karsten, L. (2005). It all used to be better? Different generations on continuity and change in urban children’s daily use of space. Children’s Geographies, 3(3), 275–290. https://doi.org/10.1080/14733280500352912 Katz, C. (2008). Childhood as spectacle: Relays of anxiety and the reconfiguration of the child. Cultural Geographies, 15(1), 5–17. https://doi. org/10.1177/147447400708577 Kearney, M. C. (2011). Mediated girlhoods: New explorations of girls’ media culture. New York, NY: Peter Lang. Kelly, Y., Zilanawala, A., Booker, C., & Sacker, A. (2018). Social media use and adolescent mental health: Findings from the UK Millennium Cohort Study. E Clinical Medicine, 6, 59–68. Kemp, S. (2004). The social geography of childcare: Making up a middle-class child. British Journal of Sociology of Education, 25(2), 229–244.

112 

REFERENCES

Kline, S., Dyer-Witheford, N., & De Peuter, G. (2003). Digital play: The interaction of technology, culture, and marketing. Montreal & Kingston; London. Ithaca: McGill-Queen’s University Press. Koles, B., & Nagy, P. (2012). Who is portrayed in Second Life: Dr. Jekyll or Mr. Hyde? Journal of Virtual Worlds Research, 5(1), 1–17. Korczak, D. J., Madigan, S., & Colasanto, M. (2017). Children’s physical activity and depression: A meta-analysis. Pediatrics, 139(4). Kruikemeier, S. (2014). How political candidates use Twitter and the impact on votes. Computers in Human Behavior, 34, 131–139. Lareau, A. (2002). Invisible inequality: Social class and childrearing in black and white families. American Sociological Review, 67, 747–776. Lareau, A. (2003). Unequal Childhoods. Berkeley. Lareau, A., & Weininger, E. B. (2003). Cultural capital in educational research: A critical assessment. Theory and Society, 32(5/6), 567–606. Lester, S., & Maudsley, M. (2007). Play, naturally: A review of children’s natural play (pp. 47–49). London: Play England, National Children’s Bureau. Lin, L. y., Sidani, J.  E., Shensa, A., Radovic, A., Miller, E., Colditz, J.  B., … Primack, B. A. (2016). Association between social media use and depression among U.S. young adults. Depression and Anxiety, 33(4), 323–331. https:// doi.org/10.1002/da.22466 Livingstone, S. (2008). Taking risky opportunities in youthful content creation: Teenagers’ use of social networking sites for intimacy, privacy and self-­ expression. New Media and Society, 10, 393–411. https://doi. org/10.1177/1461444808089415 Livingstone, S., & Bulger, M. (2013). A global agenda for children’s rights in the digital age. Recommendations for developing UNICEF’s research strategy. London: The London School of Economics and Political Science/ UNICEF Office of Research—Innocenti. Livingstone, S., Nandi, A., Banaji, S., & Stoilova, M. (2017b). Young adolescents and digital media uses, risks and opportunities in low- and middle-income countries: A rapid evidence review. London: DFID/ODI: Gender and Adolescence, Global Evidence. [online]. Livingstone, S., Ólafsson, K., Helsper, E. J., Lupiáñez-Villanueva, F., Veltri, G. A., & Folkvord, F. (2017a). Maximizing opportunities and minimizing risks for children online: The role of digital skills in emerging strategies of parental mediation. Journal of Communication, 67(1), 82–105. Loebach, J.  E., & Gilliland, J.  A. (2016). Free range kids? Using GPS-derived activity spaces to examine children’s neighborhood activity and mobility. Environment and Behavior, 48(3), 421–453. Longhurst, R. (2013). Using Skype to mother: Bodies, emotions, visuality, and screens. Environment and Planning D: Society and Space, 31, 664–679. https://doi.org/10.1068/d20111

 REFERENCES 

113

MacFarlane, R. (2003). The mountains of the mind: A history of a fascination. London: Granta. Mackett, R.  L. (2013). Children’s travel behaviour and its health implications. Transport Policy, 26, 66–72. Mahoney, J. L., & Vest, A. E. (2012). The over-scheduling hypothesis revisited: Intensity of organized activity participation during adolescence and young adult outcomes. Journal of Research on Adolescence, 22(3), 409–418. Marsh, J. (2010). Young children’s play in online virtual worlds. Journal of Early Childhood Research, 8(1), 23–39. https://doi.org/10.1177/1476718X Marsh, J., & Millard, E. (2000). Literacy and popular culture: Using children’s culture in the classroom. Sage. Marsh, J., & Richards, C. (2013). Play, media and children’s playground cultures. In Children, Media and Playground Cultures (pp.  1–20). London: Palgrave Macmillan. Matthews, H., Limb, M., & Percy-Smith, B. (1998). Changing worlds: The microgeographies of young teenagers. Tijdschr voor economische en Soc geografie, 89(2), 193–202. Mazzarella, S. (2010). Girl wide web 2.0: Revisiting girls, the internet, and the negotiation of identity. New York, NY: Peter Lang. McClure, M., & Sweeny, R. W. (2015). Participatory youth culture: Young children as media and MOC makers in a post-millennial mode. In K. L. Heider & M.  R. Jalongo (Eds.), Young children and families in the information age: Applications of technology in early childhood (pp. 245–254). Dordrecht: Springer Netherlands. McDowell, L. (2004). Work, workfare, work/life balance and an ethic of care. Progress in Human Geography, 28(2), 145–163. McKendrick, J.  H., Bradford, M.  G., & Fielder, A.  V. (2000). Kid customer? Commercialization of playspace and the commodification of childhood. Childhood, 7(3), 295–314. Meyer, B., Sørensen, B. H., & Hanghøj, T. (2011). Making connections—Global and local issues in researching the policy of serious games in education. In S.  Egenfeldt-Nielsen, B.  Meyer, & B.  H. Sørensen (Eds.), Serious games in education: A global perspective (pp.  59–83). Aarhus; Copenhagen: Aarhus University Press. Mohr-Jensen, C., & Steinhausen, H. C. (2016). A meta-analysis and systematic review of the risks associated with childhood attention-deficit hyperactivity disorder on long-term outcome of arrests, convictions, and incarcerations. Clinical Psychology Review, 48, 32–42. Moss, P. (2012). The relationship between early childhood and compulsory education: A properly political question. In Early childhood and compulsory education (pp. 10–58). Routledge.

114 

REFERENCES

Murray, J. H. (2011). Inventing the medium: Principles of interaction design as a cultural practice. Cambridge, MA; London: The MIT Press. Mustola, M., Koivula, M., Turja, L., & Laakso, M.-L. (2018). Reconsidering activity and passivity in children’s digital play. New Media and Society, 20(1), 237–254. Narine, N., & Grimes, S.  M. (2009). The turbulent rise of the “child gamer”: Public fears and corporate promises in cinematic and promotional depictions of children’s digital play. Communication, Culture & Critique, 2(3), 319–338. Noels, K. A., Leavitt, P. A., & Clément, R. (2010). “To See Ourselves as Others See Us”: On the implications of reflected appraisals for ethnic identity and discrimination. Journal of Social Issues, 66(4), 740–758. https://doi. org/10.1111/j.1540-4560.2010.01673.x O’Brien, M., Rustin, M., Jones, D., & Sloan, D. (2000). Children’s independent spatial mobility in the urban public realm. Childhood: A Global Journey of Child Research, 7(3), 257–277. O’Mara, J., & Laidlaw, L. (2011). Living in the iworld: Two literacy researchers reflect on the changing texts and literacy practices of childhood. English Teaching: Practice and Critique, 10(4), 149–159. Office for National Statistics. (2015). Measuring national well-being: Insights into children’s mental health and well-being. London: Office for National Statistics. Orben, A., Dienlin, T., & Przybylski, A. K. (2019). Social media’s enduring effect on adolescent life satisfaction. PNAS. https://doi.org/10.1073/ pnas.1902058116. Owens, P. E. (1988). Natural landscapes, gathering places, and prospect refuges: Characteristics of outdoor places valued by teens. Children’s Environment Q, 5, 17–24. Padilla-Walker, L. M., & Coyne, S. M. (2011). “Turn that thing off!” parent and adolescent predictors of proactive media monitoring. Journal of Adolescence, 34(4), 705–715. Pantic, I., Damjanovic, A., Todorovic, J., Topalovic, D., Bojovic-Jovic, D., Ristic, S., & Pantic, S. (2012). Association between online social networking and depression in high school students: Behavioral physiology viewpoint. Psychiatria Danubina, 24, 90–93. Pasquier, D. (2008). From parental control to peer pressure: Cultural transmission and conformism. In The international handbook of children, media and culture (pp. 448–459). London: Sage. Pellegrini, A. D. (2009). The role of play in human development. New York: Oxford University Press. Perry, D.  G., & Pauletti, R.  E. (2011). Gender and adolescent development. Journal of Research on Adolescence, 21(1), 61–74. Phoenix, A., & Husain, F. (2007). Parenting and ethnicity. Joseph Rowntree Foundation.

 REFERENCES 

115

Pickett, K. E., & Wilkinson, R. G. (2007). Child wellbeing and income inequality in rich societies: Ecological cross sectional study. Bmj, 335(7629), 1080. Pickett, K. E., & Wilkinson, R. G. (2015). Income inequality and health: A causal review. Social Science & Medicine, 128, 316–326. Porter, G., Hampshire, K., Milner, J., Munthali, A., Robson, E., De Lannoy, A., …, Abane, A. (2015). Mobile phones and education in Sub-Saharan Africa: From youth practice to public policy. Journal of International Development. https://doi.org/10.1002/jid.3116. Przybylski, A. K., & Weinstein, N. (2019). Digital screen time limits and young children’s psychological well-being: Evidence from a population-based study. Child Development, 90(1), e56–e65. Przybylski, A. K., & Weinstein, N. A. (2017). Large scale test of the Goldilocks hypothesis: Quantifying the relations between digital screens and the mental well-being of adolescents. Psychological Science, 28(2), 204–215. Pyer, M., & Bush, M. (2009). Disabled families in flux: Removing barriers to family life. London: Scope. Raabe, I., & Wölfer, R. (2019). What is going on around you: Peer milieus and educational aspirations. European Sociological Review, 35(1), 1–14. https:// doi.org/10.1093/esr/jcy048 Radesky, J. S., Peacock-Chambers, E., Zuckerman, B., & Silverstein, M. (2016). Use of mobile technology to calm upset children: Associations with social-­ emotional development. JAMA Pediatrics, 170(4):397–399. pmid:26928293. Rafalow, M. H. (2018). Disciplining play: Digital youth culture as capital at school. American Journal of Sociology, 123(5), 1416–1452. Raymond, C. M., Giusti, M., & Barthel, S. (2017). An embodied perspective on the co-production of cultural ecosystem services: Toward embodied ecosystems. Journal of Environmental Planning and Management, 61, 778–799. Reich, S. M. (2016). Connecting offline social competence to online peer interactions. Psychology of Popular Media Culture. https://doi.org/10.1037/ ppm0000111. Reich, S. M. (2017). Connecting offline social competence to online peer interactions. Psychology of Popular Media Culture, 6(4), 291–310. https://doi. org/10.1037/ppm0000111 Reich, S. M., Subrahmanyam, K., & Espinoza, G. (2012). Friending, IMing, and hanging out face-toface: Overlap in adolescents’ online and offline social networks. Developmental Psychology, 48(2), 356–368. Rideout, V., Foehr, U., & Roberts, D. (2010). Generation M2: Media in the lives of 8–18 year-olds. Kaiser Family Foundation. Retrieved from http://www.kff. org/entmedia/upload/8010.pdf Ritblatt, S. N., Beatty, J. R., Cronan, T. A., & Ochoa, A. M. (2002). Relationships among perceptions of parent involvement, time allocation, and demographic characteristics: Implication for policy formation. Journal of Community Psychology, 30(5), 519–549.

116 

REFERENCES

Roe, J. (2018). Ethnicity and children’s mental health: Making the case for access to urban parks. The Lancet Planetary Health. Rose, A. J., & Rudolph, K. D. (2006). A review of sex differences in peer relationship processes: Potential trade-offs for the emotional and behavioral development of girls and boys. Psychological Bulletin, 132(1), 98. Rosenberg, M. (1965). Society and the Adolescent Self-image. Princeton, NJ: Princeton University Press. Rottenberg, C. (2014). The rise of neoliberal feminism. Cultural Studies, 28, 418–437. Royal College of Paediatrics and Child Health. (2018). Written evidence submitted to the House of Commons Science and Technology Committee (SMH0156). Rudner, J. (2012). Public knowing of risk and children’s independent mobility. Progress in Planning, 78(1), 1–53. https://doi.org/10.1016/j. progress.2012.04.001 Ryan, S. (2005). ‘People don’t do odd, do they?’ Mothers making sense of the reactions of others towards their learning disabled children in public places. Children’s Geographies, 3(3), 291–305. Ryan, L., Sales, R., Tilki, M., & Siara, B. (2008). Social networks, social support and social capital: The experiences of recent Polish migrants in London. Sociology, 42(4), 672–690. Samman, E. (2007). Psychological and subjective well-being: A proposal for internationally comparable indicators. Oxford Development Studies, 35(4), 459–486. Sandseter, E.  B. H. (2009). Characteristics of risky play. Journal of Adventure Education and Outdoor Learning, 9, 3–21. Santaliestra-Pasías, A. M., Mouratidou, T., Verbestel, V., Bammann, K., Molnar, D., Sieri, S., … Hadjigeorgiou, C. (2014). Physical activity and sedentary behaviour in European children: The IDEFICS study. Public Health Nutrition, 17(10), 2295–2306. Schwanen, T. (2007). Gender differences in chauffeuring children among dual-­ earner families. The Professional Geographer, 59(4), 447–462. Schwiter, K. (2013). Neoliberal subjectivity—Difference, free choice and individualised responsibility in the life plans of young adults in Switzerland. Geographica Helvetica, 68(3), 153–159. Sedano, L. J. (2012). On the irrelevance of ethnicity in children’s organization of their social world. Childhood, 19(3), 375–388. Sen, A. (1999). Development as freedom. New York: Knopf. Shaw, P., & Tan, Y. (2014). Race and masculinity: A comparison of Asian and Western models in men’s lifestyle magazine advertisements. Journalism & Mass Communication Quarterly, 91(1), 118–138. Shaw, P., & Tan, Y. (2015). Constructing digital childhoods in Taiwanese children’s newspapers. New Media & Society, 17(11), 1867–1885.

 REFERENCES 

117

Shensa, A., Escobar-Viera, C. G., Sidani, J. E., Bowman, N. D., Marshal, M. P., & Primack, B. A. (2017). Problematic social media use and depressive symptoms among U.S. young adults: A nationally-representative study. Social Science & Medicine. https://doi.org/10.1016/j.socscimed.2017.03.061 Shin, W., & Huh, J. (2011). Parental mediation of teenagers’ video game playing: Antecedents and consequences. New Media & Society, 13(6), 945–962. Sime, D., & Fox, R. (2014). Home abroad: Eastern European children’s family and peer relationships after migration. Childhood, 22(3), 377–393. Sinclair, I. (1997). Lights out for the territory: 9 excursions in the secret history of London. London: Penguin Books. Sinclair, I. (2002). London orbital: A walk around the M25. London: Penguin Books. Smith, K. (2013). Chapter 6—Playing for health. In K. Smith (Ed.), Digital outcasts (pp. 125–155). Boston: Morgan Kauffman. Social Mobility & Child Poverty Commission. (2017). State of the Nation 2016: Social Mobility in Great Britain. Spruyt, B., De Keere, K., Keppens, G., Roggemans, L., & Vam Droogenbroeck, F. (2016). What is it worth? An empirical investigation into attitudes towards education amongst youngsters following secondary education in Flanders. British Journal of Sociology of Education, 37(4), 586–606. Statham, J., & Chase, E. (2010). Childhood wellbeing: A brief overview. Childhood Wellbeing Research Centre. Retrieved from http://www.cwrc.ac.uk/documents/CWRC_Briefing_paper.pdf. Stehlé, J., Voirin, N., Barrat, A., Cattuto, C., Isella, L., Pinton, J. F., … Vanhems, P. (2011). High-resolution measurements of face-to-face contact patterns in a primary school. PLoS One, 6(8), e23176. Strasburger, V.  C., Jordan, A.  B., & Donnerstein, E. (2012). Children, adolescents, and the media: Health effects. Pediatric Clinics of North America, 59, 533–587. https://doi.org/10.1016/j.pcl.2012.03.025 Tarapdar, S., & Kellett, M. (2013). Cyberbullying: Insights and age-comparison indicators from a youth-led study in England. Child Indicators Research, 6, 461–477. https://doi.org/10.1007/s12187-012-9177-z Tava’e, N. (2010). Investigating the long-term effectiveness of green prescription on the health of Pacific women in Auckland City and counties Manukau (Doctoral dissertation, University of Auckland). The Youth Index. (2019). Retrieved from https://www.princes-trust.org.uk/ about-the-trust/research-policies-reports/youth-index-2019. Thorpe, H., Toffoletti, K., & Bruce, T. (2017). Sportswomen and social media: Bringing third-wave feminism, postfeminism, and neoliberal feminism into conversation. Journal of Sport and Social Issues, 41(5), 359–383. Toffoletti, K., & Thorpe, H. (2018). Female athletes’ self-representation on social media: A feminist analysis of neoliberal marketing strategies in “economies of visibility”. Feminism & Psychology, 28(1), 11–31.

118 

REFERENCES

Torikka, A., Kaltiala-Heino, R., Rimpelä, A., Marttunen, M., Luukkaala, T., & Rimpela, M. (2014). Self-reported depression is increasing among socio-­ economically disadvantaged adolescents—Repeated cross-sectional surveys from Finland from 2000 to 2011. BMC Public Health, 14, 408. Tucker, F., & Matthews, H. (2001). ‘They don’t like girls hanging around there’: Conflicts over recreational space in rural Northamptonshire. Area, 33(2), 161–168. Twenge, J. (2017). Have Smartphones destroyed a generation? The Atlantic. Retrieved November 5, 2017, from https://www.theatlantic.com/magazine/archive. Ujang, N., & Zakariya, K. (2015). Place attachment and the value of place in the life of the users. Procedia Social and Behavioral Science, 168, 373–380. Ungar, M. (2009). Too safe for their own good: How risk and responsibility help teens thrive. Toronto: McClelland & Stewart. Van de Werfhorst, H. G., & Hofstede, S. (2007). Cultural capital or relative risk aversion? Two mechanisms for educational inequality compared 1. The British Journal of Sociology, 58(3), 391–415. Vansteenkiste, M., & Ryan, R. M. (2013). On psychological growth and vulnerability: Basic psychological need satisfaction and need frustration as a unifying principle. Journal of Psychotherapy Integration, 23(3), 263. Verduyn, P., Ybarra, O., Résibois, M., Jonides, J., & Kross, E. (2017). Do social network sites enhance or undermine subjective well-being? A critical review. Social Issues and Policy Review, 11(1), 274–302. Verenikina, I., & Kervin, L. (2011). iPads, digital play and pre-schoolers. He Kupu, 2(5), 4–19. Vincent, C., & Ball, S. (2007). Making up’ the middle-class child: Families, activities and class dispositions. Sociology, 41(6), 1061–1077. Vincent, C., Ball, S. J., & Kemp, S. (2004). The social geography of childcare: Making up a middle‐class child. British Journal of Sociology of Education, 25(2), 229–244. Viner, R., Ozer, E. M., Denny, S., Marmot, M., Resnick, M., Fatusi, A., & Currie, C. (2012). Adolescence and the social determinants of health. Lancet, 379, 1641–1652. Wainwright, E., & Marandet, E. (2013). Family learning and the socio spatial practice of ‘supportive’ power. British Journal of Sociology of Education, 34(4), 504–524. https://doi.org/10.1080/01425692.2012.72387. Weinstein, E. (2018). The social media see-saw: Positive and negative influences on adolescents’ affective well-being. New Media & Society, 20(10), 3597–3623. Wentzel, K. R. (2017). Peer relationships, motivation, and academic performance at school. In A.  J. Elliot, C.  S. Dweck, & D.  S. Yeager (Eds.), Handbook of competence and motivation: Theory and application (pp.  586–603). The Guilford Press.

 REFERENCES 

119

Whitebread, D. (2017). Free play and children’s mental health. The Lancet Child & Adolescent Health, 1(3), 167–169. Wilkinson, R. G., & Pickett, K. E. (2007). The problems of relative deprivation: Why some societies do better than others. Social Science & Medicine, 65(9), 1965–1978. Williams, J. (2018). Technologies driving us to distraction. The Guardian. Retrieved March 2019, from https://www.theguardian.com/commentisfree/2018/may/27/world-distraction-demands-new-focus. Winkler Reid, S. (2015). Making fun out of difference: Ethnicity–race and humour in a London school. Ethnos, 80(1), 23–44. Wirman, H. (2009). On productivity and game fandom. Transformative Works and Cultures, 3. Retrieved December 12, 2015. https://doi.org/10.3983/ twc.2009.0145. Witten, K., Kearns, R., Carroll, P., Asiasiga, L., & Tava’e, N. (2013). New Zealand parents’ understandings of the intergenerational decline in children’s independent outdoor play and active travel. Children’s Geographies, 11(2), 215–229. World Health Organisation. (2002). Gender and mental health. Department of Gender and Women’s Health; Department of Mental Health and Substance Dependence, pp. 1–4. Geneva: WHO. World Health Organisation. (2007). Helping parents in developing countries improve adolescents’ health. Geneva. [online]. Retrieved June 27, 2018. Young, K. (2013). Researching young people’s online spaces. In K. Te Riele & R. Brooks (Eds.), Negotiating ethical challenges in youth research (pp. 163–176). New York: Routledge.

Index

A Academic motivation, 61–71 Academic outcomes, 13 Academic self-esteem, 62, 71, 74 Active mediation, 84 Activity, 70 Adult-organised play, 94 Advertisements, 81 Affective communication, 42 Affective experiences, 4 Age, 49 A-levels, 36 Algorithmic predictions, 8 Alienation, 50 Antisocial behaviour, 47 Anxiety, 23, 25, 47 Appropriate behaviour modelling, 80 Aspirations, 61–75 Attachment to caregiver, 24 Attitudes to learning, 71, 74 Authoritative parenting, 45

B Behavioural difficulties, 47, 52 Behavioural rules, 80 Behaviour control, 80 Behaviour problems, 23 Blake, William, 2 Body image, 23 Body shaming, 43 Bullying, 23, 41, 47, 50–52, 70 C Capital analysis, 90 Childhood, vii Childhood geographies, 96 Child poverty, 35 Children’s play, 3 Choir, 73 Cinema, 73, 87 Civic engagement, 8 Class behaviour, 71, 74

© The Author(s) 2020 D. Hartas, Young People’s Play, Wellbeing and Learning, https://doi.org/10.1007/978-3-030-60001-3

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122 

INDEX

Class differences, 35 Class identities, 41 Commitment, 42 Companionship, 42 Competence, 13 Concerted cultivation, 40, 69 Conduct disorders, 25 Conduct problems, 47 Confirmation biases, 28 Connection, 80 Console games, 11, 43 Control, 87 Cooperative, 47 Cooperative behaviour, 47 Coping mechanisms, 85 Corporatisation, 94 Cultural activities, 86 Cultural barriers, 34 Cultural capital, 90 Cultural experiences, 4 Cultural producers, 4 Culture of learning, 69 Curiosity, 24 Cyberbullying, 27, 43, 81 D Data tracking, 81 de Quincey, Thomas, 2 Debord, Guy, 2 Depression, 25, 49 Depressive characteristics, 25 Depressive symptoms, 23 Digital engagements, 5 Digital identity theft, 81 Digital literacy, 81 Digital media, vi Digital places, 5 Digital play, 4, 44, 51, 52, 63, 80, 82–84, 88 Digital skills, 81 Digital spaces, 6

Disability, 34, 41 Discipline, 80, 83, 85, 87 Diversity, 28 Dyadic relationships, 42 E Echo chambers, 28 Economic capital, 69, 90 Educated parents, 38 Educational aspirations, 68, 71, 74 Educational motivation, 61, 62, 70, 71, 74 Embodied ecosystem, 3, 4 Embodied perspective, 4 Embodied social capital, 49 Emotional bonds, 4, 24 Emotional closeness, 81–87 Emotional connectedness, 86, 87 Emotional difficulties, 47 Emotional experiences, 3, 5 Emotional problems, 23 Emotional resilience, 14, 24 Emotional self-disclosure, 42 Emotional symptoms, 47 Emotional wellbeing, 23 Empathic, 47 Empathy, 6, 13 Engagement, 70 Epigenetic differences, 41 Ethic of care, 90 Ethnic differences, 34 Ethnic groups, 44 Ethnicity, 41, 46, 49, 52 Eudaimonic perspective, 15 Expectations for behaviour, 80 Experimentation, 85 Exploitation, 7 Extra-curricular activities, 5, 37–40, 43, 73–75, 81, 82, 86–88 Extra-curricular clubs, 34

 INDEX 

F Facebook, 27 Face-to-face interactions, 10, 13 Face-to-face peer interactions, 8 Face-to-face play, 8, 71–72, 85–86 Family habitus, 88 Family income, 35–39 Fear of strangers, 81 Free play, 38, 73, 94 Free time, 41 Friendship, 45, 47 G Galleries, 74, 87 Gaming, 12, 13, 43, 46, 52, 60, 70, 83, 88 GCSEs, 36 Gender, 34, 41, 42, 49, 52 Gender inequality, 8, 44 Gender-typed activities, 42 Goal-oriented, 69 Goldilocks Hypothesis, 24 Gorbis, Marina, 28 Grades, 69 Guided play, 60, 80–90 H Happiness, 26 Hedonic perspective, 15 Hierarchically structured groups, 42 Home spaces, 4 Homework, 40, 69 Homework support, 81 Human capital lenses, 73 Human–computer interaction, 96 Hyperactivity, 23, 47, 49 Hypersexualised images, 101 I Identity formation, 5 Inattention, 23

123

Income, 68 Independent mobility, 44 Inequality, 35 Informational rewards, 97 Instagram, 27 Instant rewards, 97 Intellectual capital, 69 Intensive parenting, 80–90, 94 Internet addiction, 80 Intimacy, 42 Invisible disabilities, 47 Isolation, 24 L Learning, 69, 70 Learning attitudes, 71–75 Leisure activities, 47 Life satisfaction, 16, 23, 26 Likes, 101 Local interactions, 7 Loyalty, 42 M MacFarlane, Robert, 3 Mass migration, 34 Mechanical memorisation, 70 Mental health, 10, 23, 25, 27, 47, 73, 95 Mental ill health, 15 Mid-adolescence, 11 Millennium Cohort Study (MCS), 11 Museums, 74, 87 N Narrative transportation, 98 Natural environment, 94 Natural growth, 40 Negative feelings, 23 Networking, 25 New nature, 3 Nuance, 28

124 

INDEX

Numeracy, 60 NVQ, 36 O Occupational status, 37–39 Offline axis, 94 Online axis, 94 Online games/online gaming, vi, 5, 26, 43 Orchestra, 73 Outdoor play, 3, 49 Outdoor play spaces, 44 Overcrowded housing, 44 Overscheduled child, 86 P Parental anxiety, 34 Parental education, 68 Parental influence, 10 Parental investment, 73 Parental involvement, 81 Parental styles, 44 Parent anxiety, 90 Parent control, 82, 86, 87 Parent discipline, 81 Parent education, 35–39 Parenting cultures, 49, 87–90 Parent interventions, 75 Peer acceptance, v Peer influence, 10 Peer interactions, 3, 4, 6, 10, 47, 71, 80, 85, 88 Peer problems, 47 Peer relationships, 10 Physical bullying, 52 Physical environments, 6 Physical geographies, 15, 94 Physical play, 4

Physical proximity, 8 Physical spaces, 6 Place dependence, 4, 5 Place identity, 4, 5 Play-based learning, 60 Play areas, 47 Play choices, 41 Politicisation of parenting, 80 Pop culture, 44 Positive affect, 24 Positive self-image, 26 Positive stress, 25 Pre-literacy, 60 Privacy, 8 Prosocial behaviour, 47 Provision and protection, 80 Psycho-geographers, 2 Psycho-geography, 2 Psycho-social context, 81 Public spaces, 2, 34, 39 Q Quality of interaction, 24, 40 R Racist attack, 45 Racist harassment, 45 Ranking, 8 Reading for enjoyment, 69 Relationships, 85 Religious service, 74 Resilience, 23 Respect, 42 Respect for individuality, 80 Responsible parent, 88 Responsive parental involvement, 41 Restrictive mediation, 84 Risk-management strategies, 85

 INDEX 

Role aspirations, 44 Royal College of Paediatrics and Child Health, 23 S School attitudes and behaviours, 62 School commitments, 86 School demands, 74 Screen exposure, 84 Screen time allowance, 81 Sedentary activities, 28 Self-concept, 16, 23, 24 Self-harm, 26 Self-disclosure, 42 Self-esteem, 23, 24, 61–71 Self-expression, 5 Self-harm, 16, 17, 25, 26 Selfhood, 96 Self-initiated activities, 25 Sensationalist interactions, 28 Sense of belonging, 2, 6 Sense of place, 3, 4, 6 Sense of self, 6 Sexism, 43 Sexual abuse, 27–28 Sexualisation, 44 Shares, 101 Sinclair, Ian, 2 Small group interactions, 13 Social and cultural capital, 37, 41 Social anxiety, 24 Social bonds/social bonding, 5 Social capital, 90 Social class, 41, 49, 52 Social comparison, 25, 41 Social competence, 13 Social connectedness, 7, 69 Social development, v, 41 Social experiences, 3 Social geographies, 2, 49, 80

125

Social interactions, 7 Socialisation, 96 Social media, 5, 11, 12, 43, 44, 46, 52, 70 Social milieu, 24 Social Mobility and Child Poverty Commission, 35 Social networking, 5, 12, 26, 43, 88 Social network sites, 46 Social norms, 44 Social positioning, 41, 69 Social recognition, 42 Social relationships, 71 Social reproduction, 41, 69 Social status, 42 Social toxicity, 70 Social value, 42 Social withdrawal, 47 Societal changes, 94 Societal threats, 27 Socioeconomic backgrounds, 39 Socioeconomic differences, 40 Socioeconomic status, 52 Solidarity, 41, 42 Sports, 73 Stately homes, 74 Status differentiation, 41 Stereotyped roles, 70 Storytelling, 6 Strengths and Difficulties Questionnaire, 47 Structured activities, 34 Structured play, vi, 5 Substance use, 85 Subtlety, 28 Suicidal feelings, 25 Suicide rates, 44 Super-connected, vii, 96–98 Supervision, 3 Surveillance, 8 Symmetrical reciprocity, 42

126 

INDEX

T Technology-mediated learning, 60 Technology-mediated selfhood, 96 Technology-mediated social experiences, viii Teenage play, 87–90 Thoreau, Henry David, 2 Topicality, 70 Transferability of social skills, 13 Trolls, 8 Trust, 42 Twitter, 27 U UK National Trust, 2 Understanding Society dataset, 11, 37 Unequal childhoods, 39 Unstructured play, v–vi Upward comparisons, 43, 70 Urban environment, 2 Urbanisation, 94

Urban parks, 44 Usefulness of digital play, 37 V Verbal arguments, 86 Victimisation, 16, 17, 23, 26 Violent images, 81 Virtual encounters, 6 Virtual geographies, 7, 15 Virtual landscapes, 34 Virtual place, 3, 5, 98–101 Virtual platforms, 95 Virtual spaces, vii, 3–5 W Wellbeing, 7, 15, 23, 24, 27, 41, 47, 63, 96 World Health Organization (WHO), 80 Y Youth clubs, 73, 87 Youth Index (2019), 27