What do you think are the psychosocial problems of biggest concern in adolescence? Please explain the rationale behind your answer and share what supports you think would help adolesc

Annual Research Review: Adolescent mental health in the digital age: facts, fears, and future directions

Candice L. Odgers,1 and Michaeline R. Jensen2

1Department of Psychological Science, University of California, Irvine, Irvine, CA, USA; 2University of North Carolina at Greensboro, Greensboro, NC, USA

Adolescents are spending an increasing amount of their time online and connected to each other via digital technologies. Mobile device ownership and social media usage have reached unprecedented levels, and concerns have been raised that this constant connectivity is harming adolescents’ mental health. This review synthesized data from three sources: (a) narrative reviews and meta-analyses conducted between 2014 and 2019, (b) large-scale preregistered cohort studies and (c) intensive longitudinal and ecological momentary assessment studies, to summarize what is known about linkages between digital technology usage and adolescent mental health, with a specific focus on depression and anxiety. The review highlights that most research to date has been correlational, focused on adults versus adolescents, and has generated a mix of often conflicting small positive, negative and null associations. The most recent and rigorous large-scale preregistered studies report small associations between the amount of daily digital technology usage and adolescents’ well-being that do not offer a way of distinguishing cause from effect and, as estimated, are unlikely to be of clinical or practical significance. Implications for improving future research and for supporting adolescents’ mental health in the digital age are discussed. Keywords: Mental health; adolescence; depression; Internet usage; social media.

Introduction Adolescents have been early and enthusiastic adop- ters of digital technologies. Nearly all adolescents (95%) in the United States have at least one mobile device of their own, and 89% own a smartphone (Rideout & Robb, 2018). Similarly, a 2014 study of young people between the ages of 9 and 16 living across seven European countries reported that 80% of youth owned either a mobile or smartphone (Mascheroni & �Olafsson, 2014). Worldwide, rates of Internet and mobile phone access vary dramatically across high versus low-income countries; however, overall, one in three users of the Internet worldwide are under the age of 18 (Keeley & Little, 2017) and across both advanced and emerging economies younger (under the age of 35) versus older people (Taylor & Silver, 2018) are more likely to have access to the Internet, smartphones and social media.

Access to mobile devices begins early. Among our sample of young adolescents attending public schools in a large Southeastern state, close to half (48%) of 11-year-olds reported owning a mobile phone with a steep increase in ownership to 85% of adolescents by age 14 (Odgers, 2018). Young people are also spending an increasing amount of time online, with recent estimates in the United States placing older adolescents (aged 13–18) online view- ing of screen media for nonschool purposes at 6.67 hr per day, with their younger peers (aged 8– 12) spending, on average, 4.6 hr on screen media each day (Rideout, 2015).

Adolescents’ constant connectivity has led to con- cerns about how digital technologies may be influ- encing multiple aspects of adolescents’ lives, ranging from their levels of physical activity and their ability to interact with others in ‘real life’ to a more recent focus on whether too much time online is contributing to mental health problems among young people. Dis- cussions about the potential negative effects of smart- phones and social media are taking place alongside growing concerns regarding adolescents’ mental health. Recent increases in rates of depression, anx- iety and suicide, especially among girls (Mojtabai, Olfson, & Han, 2016) who are the heaviest users of new media, have led some to claim that smartphones and social media may be driving increases in suicidal behaviors, depression, and loneliness (Rosenstein & Sheehan, 2018; Twenge, Joiner, Rogers, & Martin, 2018). Alternative explanations for these increases have been provided and skepticism voiced regarding the claim that digital technology usage has led to increases in adolescent depression and related men- tal health problems (Daly, 2018; Livingstone, 2018); however, much of the conversation about contempo- rary adolescents’ mental health implicates digital technology usage as contributing to the worsening of mental health symptoms and well-being.

This paper reviews existing research regarding the association between digital technology use and men- tal health, with a specific emphasis on the potential influences of digital technology usage on adolescents’ experiences of depression and anxiety. The review integrates three main sets of information including recent: (a) meta-analyses summarizing the associa- tions between digital technology usage and mental health among youth, (b) findings from large-scale public access surveys and preregistered studies, and

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© 2020 Association for Child and Adolescent Mental Health Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main St, Malden, MA 02148, USA

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(c) studies that have leveraged daily assessments of digital technology usage to understand both within- and between-person associations between adoles- cents’ digital technology usage and mental health. These three sources of information are triangulated to address the question of whether there are robust and practically significant associations between digital technology usage and adolescent mental health and, if so, for whom and under what circumstances digital technology usagemay amplify or reduce risk. Given a) the rapidly evolving nature of digital technologies usage among adolescents and b) the fact that a number of reviews and meta-analyses have recently been completed on this topic, a formal meta-analysis is not included. Instead, a synthesis of the main findings from recent reviews is provided alongside a review of key findings from large-scale datasets and daily and momentary studies. Finally, a set of future directions for research, policy and interventions are proposed, alongside a description of the steps that researchers, clinicians and policymakers will need to take to effectively support adolescents’ mental health in the digital age.

What do we currently know about the association between adolescent depression, mental health problems and digital technology usage? In the United States, there have been rapid and unprecedented increases in adolescent depressive symptoms (Keyes, Gary, O’Malley, Hamilton, & Schulenberg, 2019) and suicidal behavior (Burstein, Agostino, & Greenfield, 2019; Naghavi, 2019). Deaths by suicide have increased among every age group, but have been especially drastic among girls, where there has been a tripling of the suicide rate among 10- to 14-year-old girls from 1999 through 2017 (Hedegaard, Curtin, & Warner, 2018). It is important to note that the United States is an outlier with respect to these trends as rates of suicide worldwide continue to fall (Naghavi, 2019); nonethe- less, secular increases in emotional problems among young people have been observed, with increases in self-reported symptoms of anxiety and depression documented in countries such as Greece, Germany, Sweden, Iceland, Norway, China, and New Zealand from the 1980s onwards (Collishaw, 2015).

These increases have sounded alarms among par- ents, care providers and educators given the burden of disease and potentially devastating and deadly consequences for youth and their families. When plotted alongside increases in social media usage across this same time period, a powerful narrative has emerged that social media is driving changes in depressive symptoms and suicidal behaviors. Of course, the fact that two trend lines increase together does not mean that one phenomenon causes the other. Nonetheless, social media and digital technol- ogy usage has quickly emerged as a leading

candidate to explain the sudden jump in depression and related problems among girls.

Historically, adolescents who spent more time online were also more likely to report symptoms of depression and anxiety. But, these data come from a time when only a minority of young people were online, engaging in very different activities than what is seen today (in chat rooms talking with strangers versus online connecting with peers (George, Rus- sell, Piontak, & Odgers, 2018). Today, the majority of adolescents are online, typically connecting with offline friends and family (Reich, Subrahmanyam, & Espinoza, 2012). Moreover, as suggested by a recent synthesis of 37 studies, online communica- tion between young people is typically being used to support the ‘traditional’ tasks of offline friendships through arranging meet-ups, developing intimacy, and shows of affection (Yau & Reich, 2017).

Small associations still exist, as adolescents who report more depressive symptoms also tend to report spending more time online. However, as detailed below, a review of meta-analytic work and narrative reviews, recent large-scale public access and pre- registered studies, and daily and momentary assess- ments of digital technology usage and mental health, show that that associations between time online and internalizing symptoms are often (a) mixed between positive, negative, and null findings, (b) when pre- sent, are likely too small to translate into practically or clinically meaningful effects (explaining less than 0.5% of the variance in symptoms with poor adjust- ment for relevant confounding factors and estimates that are virtually always derived from correlation designs), and (c) are typically not distinguishable in terms of likely cause and effect. In addition, a recent systematic narrative review of 28 studies of online help-seeking behaviors indicated that many young people suffering from mental health problems are spending their time online searching for means of alleviating and better understanding their symptoms (Pretorius, Chambers, & Coyle, 2019).

Evidence Base 1. Meta-analytic studies and reviews

Six recent reviews summarizing the associations between digital technologies and adolescents’ mental health completed between the years of 2014 to 2019 are described below. The reviews were selected due to the fact that they targeted or included adolescent populations and included a focus specifically on the associations between amount of digital technology usage and mental health (see Table 1). The main results from each review are described briefly below, followed by a synthesis of findings and limitations across this work. Details on the individual studies included in the reviews are also provided in Table S1.

Three of the six reviews focused exclusively on adolescent or child populations. In one of the earliest and largest reviews, Best and colleagues (2014) conducted a systematic narrative review of 43

© 2020 Association for Child and Adolescent Mental Health

doi:10.1111/jcpp.13190 Adolescent mental health in the digital age 337

studies conducted between 2003 and 2013 focused on the association between online communication/ social media and well-being. Notably, their review included studies with wide ranging methodologies (e.g., other reviews, qualitative studies) and opera- tionalizations of digital technology use (e.g., technol- ogy-related problems and technology addiction alongside quantity of many different types of tech- nology use). Across studies, they observed contra- dictory evidence of mixed, null, and positive associations and emphasized the lack of robust causal research regarding the impact of social media on mental well-being among young people. With these limitations in mind, the authors then specu- lated on potential positive and negative impacts of social media for adolescents. Potential benefits of social media engagement that were identified included: increases in self-esteem, perceived social support and social capital, safe identity experimen- tation, and increased opportunities for self-disclo- sure. Specific potential harms of social media for well-being that were identified included: increased social isolation, depression, and cyberbullying.

In a 2017 systematic review, McCrae, Gettings and Pursell (2017) conducted a more focused review examining the association between social media use and depressive symptoms among children and adolescents (aged 5–18). Only 11 studies met eligi- bility for inclusion in the quantitative meta-analysis (focused on social networking sites and usage, restricted to English language publication, and con- ducted in general vs. clinical samples) resulting in a total N for the analysis of 12,646. The authors documented a small, but statistically significant, association between social media usage and depres- sive symptoms (r = .13, 95% CI: �.05 to 0.20), but noted the small number of studies, heavy reliance on cross-sectional designs (for 6 of the 11 studies), and difficulty in interpreting the clinical significance of

the findings due to the wide variation observed in sample sizes, methods, and results. The most recent systematic review in 2019 restricted the range of adolescents between 13 and 18 years of age and, again, only identified a small number of studies (N = 13) that met criteria for inclusion (Keles, McCrae, & Grealish, 2019). Eligibility for inclusion was determined based on age (13–18), measurement of social media usage as the exposure, measurement of depression, anxiety, or psychological distress by a validated instrument, and publication in peer reviewed journal, available in English. Of the 13 studies, 12 studies were cross-sectional. Again, the authors observed a general pattern of associations between social media usage and mental health problems, but noted that methodological limitations, the reliance on cross-sectional designs, and failure to include relevant mediators and moderators of associations, limited conclusions that could be drawn about the nature of this association. Impor- tantly, they highlighted the lack of longitudinal and experimental research in this area and, as such, emphasized that the relationship between social media and depression should be characterized in correlational versus causal terms.

The remaining three reviews included a mix of adults and adolescents in the sampling frame. Conclusions were consistent with those summarized for the adolescent populations above in that cross- sectional research designs, retrospective reporting of symptoms and digital technology usage, and small and mixed patterns of associations were the norm and often limiting factors in drawing reliable conclu- sions in this area (Baker & Algorta, 2016; Seabrook et al., 2016). For example, in a 2016 review exam- ining the association between frequency or time spent on SNS and depression, eight reported small positive associations, while twice as many found nonsignificant associations (Seabrook, Kern, &

Table 1 Recent Reviews on Youth Digital Technology Use and Mental Health

Study Design

Sample AgeMean (range) Sample size Mental health measure Tech use measure

Best et al. (2014) Systematic narrative review

Adolescents 43 studies Mental health and well- being

Online communication and social media

Baker et al. (2016) Systematic review of quant studies

Adolescents and Adults

30 studies Depression SNS

Seabrook et al. (2018) Systematic review

Adolescents and Adults

70 studies Depression and anxiety emphasis; Overall well- being

SNS

Huang (2010) Meta-analysis Adolescents and Adults

67 samples (61 studies) (N = 19,652)

Self-esteem, life satisfaction, loneliness and depression

SNS

Keles et al. (2017) Systematic review

13-18 13 papers Depression, anxiety and distress

Social media

McCrae et al. (2014) Systematic review

5 to 18 11 studies (N = 12,646)

Depression Social media

SNS, Social Networking Site.

© 2020 Association for Child and Adolescent Mental Health

338 Candice L. Odgers and Michaeline R. Jensen J Child Psychol Psychiatr 2020; 61(3): 336–48

Rickard, 2016). The authors concluded that the inconsistency across studies and lack of common themes or reproducible findings when varying mea- sures of SNS use were employed suggested that any association between social media and depression is likely to be conditional on a number of moderating factors and sensitive to variations in usage patterns, pre-existing vulnerabilities, and context. More recently, Huang (2017) performed a meta-analysis across 67 independent samples (61 studies), which included a mix of adolescents and young adults (N = 19,652). They reported that the mean correla- tion between time spent on social networking sites (SNS) and psychological well-being (comprised of self-esteem, life satisfaction, loneliness, and depres- sion) was r = �0.07 (95% CIs = �.04 to �.09), with associations for loneliness and depression that ranged from r’s = �0.08 and �.11, respectively. Main effects were not moderated by sample age or gender.

Table S1 provides additional details of the studies included in the six reviews which met inclusion criteria (adolescent sample; empirical analysis; available in English; measure of extent of digital technology use or engagement [i.e., studies which include only measures of technology-related prob- lems or ‘technology addiction’ excluded]; measures relevant to mental health [e.g., depression, anxiety, psychological well-being, loneliness, self-esteem]). The studies are summarized with respect to: the study design (cross-sectional, longitudinal, experi- mental), year of data collection, sample country, age of participants, measures of mental health and digital technology usage, and whether the study suggested that engagement with digital technology is harmful, helpful, or neither/unclear. Four main findings emerge from a review of the adolescent- focused studies detailed in this table. First, the majority of studies conducted to date are derived from cross-sectional surveys. Of the 29 studies included in Table S1, only 4 (14%) are longitudinal and only two studies included an experimental or quasi-experimental design. As a result, the ability to make causal inferences is extremely limited and does not allow for conclusions regarding whether increased time online or engagement with social media use causes changes in young people’s mental health.

The inconsistencies in the evidence reviewed and correlational nature of research to date raises ques- tions regarding how such a strong causal narrative has emerged regarding social media usage, time online, and adolescents’ mental health. An often- cited study when promoting the beneficial effects of reducing screen and social media time among ado- lescents comes from a study of Danish adults who were randomly assigned to take a break from Face- book. In this study, those assigned to take a Face- book break reported greater life satisfaction and more positive emotions compared to the control

condition who continued their Facebook use as usual (Tromholt, 2016). Results also suggested stronger effects among those whose use was already potentially problematic (as evidenced by heavy use, passive use, and envy of others on Facebook). However, the validity of this study and generalizabil- ity to adolescents is limited due to the fact that participants were unpaid adult volunteers recruited via Facebook ads, 86% of whom were women with an average age of 48 years, and all of whom were not blind to their condition prior to reporting on whether their mental health had improved after giving up Facebook. In contrast, experimental studies with college students have demonstrated that virtual communication can have positive impacts, with randomization to instant messaging and virtual communication leading to reductions in distress (Dolev-Cohen and Barak, 2013) and replenishment of self-esteem and perceived relational value after social exclusion (Gross, 2009). Additional experi- mental work with adolescent populations is sorely required, especially those that ensure participants are blind to study conditions and measure mental health using multiple informants.

Second, many studies have relied soley on screen time as the index of engagement with digital tech- nologies. Screen time is typically measured as the number of minutes or hours youth spend on a device or engaged in a particular online activity each day. The reliance on screen time metrics is a problem given that all screen time is not equal with respect to potential risks and benefits. Spending time on devices and screens is now a required part of many adolescents’ educational experiences and means of communication throughout the day with family and friends. Mobile devices have also become a primary means of accessing multiple modes of entertainment that have always appealed to adolescents, including streaming videos and movies, music, and gaming. In addition, screen time measures are typically gath- ered via retrospective self-reports from youth, which introduces recall bias, and are assessed alongside self-reported measures of mental health, which introduces common method or rater bias (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003) into the research design and analysis. Finally, reducing a complex and multi-dimensional set of experiences into a single index of retrospective self-reports of the amount of time that youth spend in front of screens does not correspond well with objective measures of time spent online (correlations between objectively mea- sured and retrospectively reported screen time are estimated to be ~r = .20 (Ellis, 2019)). Across the 29 studies reviewed in Table 1, only two included objective or informant-rated measures of screen time or social media usage, and the majority did not go beyond relying on time-based summaries (e.g., 2 hr per day online) to characterize usage.

Third, most studies to date have relied on relatively small, nonrepresentative samples, which limits the

© 2020 Association for Child and Adolescent Mental Health

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ability to both generalize back to the larger popula- tion of adolescents and to conduct adequately pow- ered interaction tests to identify which subpopulations may be most at risk, although there are exceptions to this trend (e.g., the Monitoring the Future Study and Millennium Cohort Study described in the next section). The vast majority of studies have been drawn from high-income and high-resource settings. Rates of mobile phone access and usage vary widely across low- to high-income settings, and potential impacts on adolescent health and well-being are likely to vary as well. This type of selective sampling and recruitment limits the gener- alizability of research findings and has resulted in conclusions being drawn almost exclusively from WEIRD (Western, Educated, Industrialized, Rich and Democratic) societies, an approach that is likely to heavily skew conclusions about potential impacts on adolescent mental health to a minority of adoles- cents worldwide (Henrich, Heine, & Norenzayan, 2010). The paucity of data from these settings impedes our understanding of potential impacts of digital technologies in middle- and low-income set- tings, where the vast majority of youth in the world are currently coming of age (World Health Organiza- tion, 2019).

Fourth, while a significant amount of time has been spent discussing issues related to negative impacts of digital technologies on adolescents, most empirical research on the effects of digital technolo- gies on well-being has focused on young children or adults (as evidenced by the small number of studies that met inclusion for the quantitative analyses above). More specifically, the early adolescent period has been neglected in prior research, despite the fact it is likely to be one of the most relevant times for understanding linkages between mental health and social media, as young people are making the transition biologically and socially to adolescence and, simultaneously, entering social media plat- forms and more complex digital environments. None of the studies reviewed above tested, or were pow- ered to test, whether associations differed by devel- opmental stage. Instead, when adolescence was considered separately, adolescents were treated as a homogenous group. Progress has been made in other areas with respect to mapping new media use on trajectories of adolescent brain development during this period (Crone & Konijn, 2018); however, what is currently needed is a developmentally cali- brated evaluation of the fit between the affordances and constraints of digital technologies and the core developmental tasks, competencies, and vulnerabil- ities that characterize the adolescent period more generally, and the transition to adolescence more specifically (Dahl, Allen, Wilbrecht, & Suleiman, 2018). Practically, there has been a blurring of the discussion in legal, clinical, and policy contexts between protections and screen time rules that are required for young children versus the approaches

required to help support and scaffold adolescents as they learn to navigate complex digital ecologies more independently.

To summarize, there has been widespread specu- lation that increases in depression and anxiety are being driven by changes in the way that adolescents interact with each other through social media and time online. The claims are that adolescents are increasingly losing out on opportunities for face-to- face interaction (Turkle, 2017), are likely to be harassed and victimized frequently online (Hamm et al., 2015), and are under constant assault by idealized and carefully curated images that may lead to upward social comparisons, envy, and, in turn, lower well-being and increasing rates of depression (Appel, Gerlach, & Crusius, 2016). However, a review of the existing research demonstrates inconsistent and primarily small associations between the quan- tity of digital technology usage and mental health, with no way to discern cause from effect. Additional research that is longitudinal, expands beyond WEIRD societies, integrates multiple indices of dig- ital technology usage and well-being, embeds exper- imental or quasi-experimental design features, and includes a sufficient, and representative number of young people spanning the entire adolescent period (ages 10–24) is needed. At present, narrative reviews and meta-analytic work do not support causal claims, or even strong and consistent correlational patterns, linking adolescents’ digital technology usage with mental health problems.

Evidence Base 2. Large-scale and multiple-cohort studies

Similar to findings from systematic reviews and meta-analyses, the most recent and rigorous large- scale and preregistered studies have not found strong support for a robust linkage between adoles- cents’ technology use and well-being. Using specifi- cation curve analysis across three national data sources of adolescents (N > 350,0000), two based in the United States and one in the UK, Orben and Przybylski (2019) demonstrated that choices related to the specification of variables capturing digital technology use, adolescent well-being, and con- founders can generate a myriad of effect sizes, with the most likely association being exceedingly small and explaining a small portion of the variance in well-being. More specifically, across their 3,221,225,472 analyses, technology use accounted for less than 1% (0.4%) of the variation in well-being. Again, the remaining small cross-sectional associa- tion between digital technology usage and well-being provided no credible way to disentangle cause from effect. In a related 2017 preregistered study of over 120,000 English adolescents, the authors found no robust associations between mental well-being and moderate use of digital technology (which character- izes use by most adolescents), with a measureable

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340 Candice L. Odgers and Michaeline R. Jensen J Child Psychol Psychiatr 2020; 61(3): 336–48

‘albeit small’ negative associations (less than 1% of the variation explained) for those with high levels of engagement (Przybylski & Weinstein, 2017).

In a recent re-analysis of the Monitoring the Future Study (notably the same study and data that was used to signal initial alarms regarding the connection between social media/digital technology usage and depression; (Twenge et al., 2018)), daily social media use was not found to be a moderately strong or consistent risk factor for adolescents’ depressive symptoms (Kreski et al., submitted). The study analyzed data from 8th and 10th grade students, across 2009 to 2017, to assess the rela- tionship between self-reported daily s

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