Screen Time,Social Media,and Adolescent Mental Health: What Science Says and What Policymakers Can Do

Abstract

Concerns about the impact of screen time and social media on adolescent mental health have prompted rapid policy responses worldwide, including age restrictions, platform regulations, and school-based interventions. However, the scientific evidence presents a far more nuanced picture than public debates typically suggest. Large-scale studies and meta-analyses consistently find that digital media use explains only a small proportion of variation in adolescent mental health outcomes often less than 1% of variance, comparable in magnitude to effects of eating potatoes or wearing eyeglasses. At the same time, risks are not evenly distributed: early adolescent girls and those engaged in image-based platforms may be more vulnerable, particularly through mechanisms such as sleep disruption, social comparison, and cyberbullying. This article reviews current evidence, distinguishes correlation from causation, and highlights key developmental and contextual differences that policymakers frequently overlook. It then examines major policy options including platform design regulation, age verification laws, parental controls, and digital literacy education, outlining their potential benefits and real-world trade-offs. Rather than advocating a single solution, the paper presents a framework for evidence-informed policymaking that emphasizes proportionality, equity, and adaptability. Effective policy should move beyond panic-driven responses toward targeted, developmentally informed strategies that protect adolescents while preserving their rights and access to beneficial digital spaces.

Keywords

screen time social media adolescent mental health adolescent mental health+social media+

Social Media

New research shows screen time has small average effects on teen mental health, but risks vary by age, gender, and how platforms are used. Smarter policy means moving beyond panic to focus on design, digital literacy, and targeted protections.

#YouthMentalHealth #DigitalPolicy

Key Points

Small effects, but not trivial risks. On average, screen time has only a modest statistical link to mental health outcomes (one exception being younger adolescent girls). Policymakers should resist blanket regulatory approaches and instead identify the most vulnerable sub-groups for targeted interventions.

Not all screen use is the same. Active communication such as chatting with friends, participating in group chats, or engaging creatively can be neutral or even beneficial for adolescent well-being. Passive scrolling through curated feeds and exposure to harmful content are more consistently linked to negative outcomes such as depression and poor body image (Marciano, Ostroumova et al., 2022). Regulation should distinguish between types of use and content, rather than treating all screen time as uniformly harmful.

Development matters more than many policies acknowledge. Early adolescence (10–14 years) is a neurologically and psychosocially sensitive period during which the brain is especially responsive to social reward, peer comparison, and emotional stimuli (Hutton et al., 2024). Adolescents in this age range interact with digital media differently than older teenagers or adults. Policies and educational programs should be age-differentiated rather than applying uniform rules across the 10–18 age range.

Policy trade-offs are unavoidable and must be honestly acknowledged. Measures such as age verification may protect some users but raise serious concerns about digital privacy, data collection, and the exclusion of vulnerable youth who rely on online communities for social support including LGBTQ+ youth and those experiencing isolation (Marwick et al., 2024). Any regulatory measure should be accompanied by a rigorous equity and rights-based assessment before implementation.

Education and platform design are the most promising levers. Digital literacy programs that teach young people how to critically evaluate content, recognize manipulative design, and manage their own usage show genuine promise. Structural changes to platform design such as removing algorithmic amplification of harmful content can reduce exposure to risk at scale (Osborne, 2025). Governments should prioritize sustained investment in evidence-based digital literacy curricula and enforce platform design standards through legislation with teeth.

Avoid panic; build adaptive, evidence-responsive policy systems. The evidence base is evolving rapidly. Findings from a study conducted in 2018 may not reflect how platforms function today, or how today's adolescents use them. Policies built on outdated or oversimplified science can cause harm by displacing effective interventions or restricting access to beneficial digital resources. Establish standing bodies that regularly review emerging evidence and are empowered to revise regulatory approaches accordingly.

Around the world, governments are moving quickly to regulate young people's digital lives. In Australia, a 2023 law banned children under 16 from social media entirely. In the United Kingdom, the Online Safety Act introduced new duties on platforms to protect minors. Across the United States, multiple states have passed or proposed legislation restricting children's access to social media platforms. Across Africa, including in Kenya, policymakers are increasingly debating how to respond to growing concern that smartphones and social media are harming the mental health of young people.

These concerns are understandable and, to a degree, warranted. Rates of anxiety, depression, and self-harm among adolescents have risen in many countries over the past two decades, a period that coincides with the proliferation of smartphones and social media (Thorisdottir et al., 2020). High-profile cases of cyberbullying, exposure to self-harm content, and the addictive design features of major platforms have understandably alarmed parents, educators, and public health professionals. The urgency is real.

But urgency can sometimes outpace evidence. Legislation shaped primarily by public outrage and media narratives, rather than by rigorous science, risks missing the true drivers of adolescent distress and inadvertently restricting access to the social connections, educational resources, and support communities that the internet also provides. Before designing policy, it is essential to understand what the science actually shows: where evidence is strong, where it is limited, and where the honest answer is still “we don't know yet.”

This article aims to do exactly that. It reviews what the scientific literature tells us about the relationship between screen time, social media, and adolescent mental health; explains the key nuances that are frequently lost in translation between research findings and policy debates; and outlines a framework for evidence-informed policymaking that is proportionate, equitable, and built to adapt as knowledge grows. It is written primarily for policymakers, public health professionals, educators, and engaged citizens, not for specialist researchers. It aims to make complex science accessible without sacrificing accuracy.

What the Science Shows

The Overall Picture: Small Average Effects

When researchers examine large, representative samples of adolescents and ask how much of the variation in mental health outcomes can be explained by digital media use, the answer is consistently: very little. A much-cited analysis (Orben & Przybylski, YEAR) found that digital technology use explained less than 0.4% of the variation in adolescent well-being, a statistical association so small that it was comparable to the effect of wearing eyeglasses or eating potatoes (Odgers & Jensen, 2020). More recent meta-analyses have reached similar conclusions: screen time is associated with worse mental health outcomes, but the association is typically weak and inconsistent across different studies and populations (Santos et al., 2023).

This does not mean screen time has no effect on any adolescent anywhere. It means that, on average, across diverse populations, the effect is small relative to other factors that shape adolescent mental health. Family environment, poverty, school climate, peer relationships, physical health, and access to mental health services all play considerably larger roles. A policy that focuses exclusively on digital technology while ignoring these upstream determinants is unlikely to make a meaningful difference in population-level mental health outcomes.

A useful analogy: if researchers measured the relationship between wearing blue jeans and adolescent depression, they might find a small positive correlation, not because jeans cause depression, but because both are associated with other variables. The key question is not whether an association exists, but whether it is causal, how large it is in practical terms, and for whom it matters most.

Correlation Is Not Causation: Why This Matters for Policy

Much of the public debate about screens and mental health rests on an implicit assumption that the relationship is causal: that social media use damages mental health. But the scientific literature does not firmly establish this. Most studies are correlational, meaning they observe that adolescents who spend more time on social media tend to report worse mental health, but they cannot distinguish between several possible explanations.

Social media use causes poor mental health. Poor mental health increases social media use (sometimes called the ‘digital refuge hypothesis,’ in which struggling adolescents turn to online spaces for connection or distraction. A third variable such as loneliness, family conflict, or academic stress drives both increased social media use and worse mental health simultaneously. Some combination of all three, varying across different individuals and contexts.

Longitudinal studies follow the same individuals over time and therefore provide stronger evidence about the direction of effects. They have generally found weaker associations than cross-sectional studies taken at a single point in time. A large longitudinal study (Coyne et al., 2020) that followed adolescents for eight years found no evidence that social media use prospectively predicted later mental health problems, controlling for baseline mental health. Similarly, a population-based cohort study in Australia found that the relationship between social media use and adolescent mental health was more complex and context-dependent than often assumed (Vijayakumar et al., 2025).

This nuance matters enormously for policy. If the primary direction of causality runs from mental health to social media use, rather than the reverse then restricting access to social media will not improve mental health. It may, in fact, remove a coping resource from adolescents who are already struggling. Effective policy must be grounded in an accurate causal model, not a plausible-sounding narrative.

Differences Matter: Who Is Vulnerable, and Under What Conditions

One of the most robust findings in the literature is that the relationship between digital media use and adolescent mental health is highly heterogeneous, meaning it varies considerably across individuals, age groups, genders, platform types, and modes of use. The question “does social media harm adolescents?” is therefore too broad to answer meaningfully. More useful questions are: which adolescents, on which platforms, using them in which ways, during which human developmental periods?

Several patterns emerge consistently across studies:

Gender Differences

Girls, particularly those aged 10–14, show stronger negative associations between social media use and mental health than boys (Thorisdottir et al., 2020). This likely reflects several converging factors: girls engage more heavily with image-based platforms where social comparison is prevalent; they are more likely to experience appearance-based cyberbullying; and they may be more susceptible to the internalization of idealized body images during the sensitive period of early adolescence.

Platform Type

Not all platforms are equivalent. Platforms built around image sharing, curated self-presentation, and appearance-based feedback (such as Instagram and TikTok) show stronger associations with poor body image and depression than platforms organized around direct communication or shared interests (van der Wal et al., 2025). The design affordances of a platform shape the psychological experiences it creates.

Mode of Use

Passive consumption, scrolling through feeds without interacting, is more consistently associated with negative outcomes than active, interactive use, such as direct messaging, creating content, or participating in communities (Marciano, Schulz et al., 2022). This distinction matters: restricting screen time without distinguishing passive from active use may inadvertently curtail the kinds of digital engagement that are neutral or beneficial.

Developmental Timing

Early adolescence is a developmentally sensitive period during which the brain's reward circuitry is particularly responsive to social feedback, and identity formation is closely tied to peer relationships (Hutton et al., 2024). The same platform features that are manageable for a 17-year-old may pose meaningfully greater risks for an 11-year-old.

Pre-Existing Vulnerabilities

Adolescents who are already experiencing mental health difficulties, social isolation, or family adversity may be both more likely to use social media intensively and more vulnerable to its potentially harmful features. A one-size-fits-all policy approach misses this important interaction.

Understanding Why: Mechanisms of Harm

Understanding why some adolescents experience harm from social media use and why others do not requires moving beyond simple time-on-screen measurements to examine the psychological and biological pathways through which digital media affects wellbeing. Research points to several interrelated mechanisms, which often operate simultaneously.

Sleep Disruption

One of the most consistently documented pathways runs through sleep. Late-night device use whether driven by social media engagement, gaming, or streaming is associated with later bedtimes, shorter sleep duration, and poorer sleep quality (Hutton et al., 2024). Adolescents require approximately 8–10 h of sleep per night for healthy neurological development, emotional regulation, and academic functioning. The blue light emitted by screens suppresses melatonin production, making it physiologically harder to fall asleep; but equally important is the psychological stimulation of social media, which activates attention, arousal, and social vigilance at the very moment the brain needs to wind down.

Sleep deprivation in adolescents is not merely a quality-of-life issue. It is a significant mental health risk factor in its own right, independently associated with depression, anxiety, impaired impulse control, and increased emotional reactivity. Policies and interventions that support healthy sleep whether through school start time reform, device-free bedroom norms, or platform-level restrictions on late-night notifications may therefore be among the highest-leverage strategies available.

Social Comparison and Body Image

Adolescence is a period of intense identity formation, during which young people are acutely sensitive to how they compare with peers. Social media platforms that are organized around curated self-presentation create an environment of continuous social comparison, often with algorithmically selected content designed to maximize engagement which frequently means surfacing aspirational, idealized, or emotionally provocative material. Exposure to heavily filtered, professionally lit images of bodies, lifestyles, and achievements can distort adolescents’ perceptions of what is normal or achievable, fueling dissatisfaction with their own appearance, social lives, and academic performance.

This mechanism is particularly well-documented in girls. Studies using experimental designs where participants are randomly assigned to increased or decreased Instagram use have found that reducing use leads to improvements in body image and mood, providing causal evidence that the platform's content environment, not merely the amount of time spent online, is driving harm (Osborne, 2025). Content that glorifies thinness, cosmetic procedures, or unrealistic beauty standards is particularly concerning during early adolescence, when body image is both highly salient and highly malleable.

Cyberbullying and Online Harassment

Cyberbullying is the use of digital platforms to deliberately harass, humiliate, or threaten another person is associated with significantly elevated rates of depression, anxiety, and suicidal ideation among adolescent victims (Agyapong-Opoku et al., 2025). Unlike traditional face-to-face bullying, cyberbullying can be perpetrated anonymously, can reach victims at any time of day or night, and can spread rapidly to large audiences. Content can persist online long after the initial incident, preventing the normal psychological recovery process that follows time-limited episodes of social aggression.

The harms of cyberbullying fall disproportionately on already-marginalized young people: those who are LGBTQ+, members of ethnic minorities, those with disabilities, or those who do not conform to dominant social norms. For these adolescents, the calculus of digital access is particularly complex: online communities may provide vital social support and affirming spaces, while simultaneously exposing them to targeted harassment. Policies that restrict access to digital spaces without providing offline alternatives for support may therefore cause greater harm to the young people they are ostensibly protecting.

Displacement of Beneficial Activities

A fourth proposed mechanism is displacement: the possibility that time spent on social media reduces the time available for activities that are more directly beneficial to mental health, such as physical exercise, face-to-face socialization, creative pursuits, and sleep. The evidence for displacement as a primary causal pathway is mixed many adolescents use social media in addition to, rather than instead of, these activities but it may be relevant for heavy users whose digital engagement genuinely crowds out other health-promoting behaviors (Zhu et al., 2023).

These mechanisms rarely operate in isolation. An adolescent who stays up until midnight scrolling Instagram, comparing herself to influencers, receiving critical comments about her appearance, and feeling unable to switch off because of social anxiety is experiencing sleep disruption, social comparison, cyberbullying, and displacement simultaneously. Effective intervention must address this complexity rather than focusing on a single variable.

Policy Options: What Are the Choices?

Policymakers have an expanding menu of potential responses to concerns about digital media and adolescent mental health. Each option has a different evidence base, a different target mechanism, a different set of stakeholders, and a different profile of benefits and risks. The following section reviews the major categories of intervention with reference to what the evidence currently supports.

Platform Design Regulation

Rather than restricting adolescents’ access to platforms, design regulation focuses on changing how platforms function. This category of intervention targets the structural features that research suggests are most harmful: algorithmically amplified content that promotes social comparison and emotional escalation; infinite scroll and autoplay features that erode users’ ability to self-regulate engagement; notification systems designed to interrupt sleep and maximize re-engagement; and content recommendation engines that funnel vulnerable users toward increasingly extreme material The White Hatter, 2026).

Advocates of design regulation argue that it addresses root causes, rather than symptoms, and that it does so at scale improving the digital environment for all users, rather than relying on individual adolescents and families to manage their own exposure (Ito et al. 2009; The White Hatter, 2026; Toda Peace Institute / Inter Press Service, 2025). The UK Online Safety Act, which places legally binding duties on platforms to conduct risk assessments and implement safety measures for child users, represents one of the more ambitious attempts to translate this logic into law (Marwick et al., 2024).

The challenges of design regulation should not be understated. Defining what constitutes a harmful design feature in legislation that can keep pace with rapidly evolving platforms is technically difficult. Enforcement against large, globally operating technology companies requires regulatory capacity, legal jurisdiction, and political will that many governments, particularly in the Global South may lack. And some proposed design interventions, such as limiting the visibility of “like” counts, have shown limited effectiveness in controlled studies (ref), suggesting that the mechanism of harm is more complex than initially assumed (Vijayakumar et al., 2025; World Health Organization, 2024; Zhu et al., 2023).

Age Verification and Access Restrictions

Age-based access restrictions requiring platforms to verify the age of users and exclude those below a specified threshold have become one of the most politically popular responses to concerns about adolescent social media use. Australia's ban on social media for under-16s, and various US state laws requiring parental consent for minors to create accounts, represent high-profile examples of this approach.

The intuitive appeal of age restrictions is clear: if the platforms are harmful, keep children off them. However, the evidence base for this approach is weaker than its political popularity might suggest (ref). For age verification to be effective, it must be technically robust, easily understandable, and not easily circumvented criteria that current verification technologies largely fail to meet. Research consistently shows that adolescents can and do use false ages, parental accounts, and virtual private networks to access restricted platforms (Marwick et al., 2024). This means age restrictions may create a false sense of protection without delivering meaningful reductions in exposure.

More concerning is the potential for age verification systems to cause collateral harm. Robust identity verification necessarily involves the collection of sensitive personal data from children and parents, creating new privacy and data security risks. Strict enforcement may cut off marginalized adolescents including LGBTQ+ youth, those experiencing domestic difficulties, or those in rural areas with limited offline social options from online communities that provide them with essential support. The question is not only whether restrictions protect some young people from harm, but whether they do so in ways that are proportionate and that do not create new harms for other vulnerable groups.

Parental Controls and Monitoring. Parental control tools including software that limits screen time, blocks certain types of content, or provides parents with visibility into their children's online activity are widely available and are actively promoted by platform companies and some governments as a primary response to online safety concerns. For younger children, parental supervision of digital media use has a reasonable evidence base: children who use digital media with parental guidance and within consistent household routines tend to have better outcomes than those who use it without any adult oversight (WHO, 2024).

However, the picture changes as children move into adolescence. Adolescence is developmentally characterized by the drive for increasing autonomy, privacy, and independence from parental authority psychological needs that are not pathological but are actually essential for healthy development into adulthood. Heavy parental surveillance of digital activity can undermine the trust and communication that are the most effective protective factors against adolescent risk-taking, both online and offline. Adolescents who feel monitored rather than guided are more likely to hide their online activity rather than seek help when they encounter distressing content or situations.

There are also significant equity concerns: parental control approaches assume that all parents have the time, technical literacy, language skills, and relationship quality needed to engage effectively in their children's digital lives. In many families, particularly those experiencing poverty, parental illness, or high work demands this assumption does not hold. Policies that rely heavily on parental controls as the primary protective mechanism may therefore deliver protection unevenly, with the most well-resourced families benefiting most.

Digital Literacy Education

Digital literacy education programs that teach young people how to think critically about online content, recognize persuasive and manipulative design, manage their own screen use, understand privacy and data practices, and seek help when they encounter harmful material is widely regarded by researchers as one of the most promising approaches to adolescent digital wellbeing (Osborne, 2025; WHO, 2024).

Unlike most other approaches, digital literacy education works with adolescents’ developmental needs rather than against them: it builds agency, competence, and critical thinking rather than imposing restrictions (Ito et al., 2009). It can be tailored to age and developmental stage. It has potential benefits beyond mental health, including for civic participation, academic skills, and economic opportunity. And it builds capacities that remain useful as platforms and technologies evolve, rather than targeting specific features that may change or disappear.

The limitations of digital literacy as a standalone solution are also important to acknowledge. Education takes time to deliver and may not reach adolescents at the moment of risk. Its effects depend on the quality of implementation, the training of educators, and the cultural and contextual relevance of the curriculum. And it places a significant burden of responsibility on young people themselves, rather than on the platforms whose design choices create many of the risks in the first place. Digital literacy is necessary but not sufficient; it works best as part of a broader ecosystem of protections.

Policy Implications: What the Science Supports

The scientific literature does not point toward a single, definitive policy solution. It does, however, support several principles that should guide how policymakers approach this complex issue. These principles are derived from the evidence reviewed above and reflect a commitment to proportionality, equity, and adaptability.

Focus on Design, Not Just Access

Improving how platforms are designed—reducing algorithmically amplified harmful content, eliminating features that undermine self-regulation, and strengthening safety by default is likely to be more effective and more equitable than restricting who can access them. Design changes operate at scale and do not require individual adolescents or families to change their behavior.

Target Risks, Not All Users

Policies should be calibrated to address the specific features and populations most consistently linked to harm: image-focused platforms for early adolescent girls; platforms without adequate content moderation; design features that promote passive, comparison-based scrolling. Blanket restrictions on all digital media use for all young people are not supported by the evidence.

Invest in Education

Digital literacy equips young people to manage risks independently, builds transferable skills, and supports the development of adolescent agency. Investment in high-quality, age-differentiated, and culturally responsive digital literacy education should be a cornerstone of any national digital wellbeing strategy.

Protect Equity and Rights

Any policy must be assessed against its impact on the most marginalized adolescents, including those from low-income households, LGBTQ+ youth, and those in rural or underserved communities. Policies that reduce access to digital spaces without providing adequate offline alternatives for social connection and support may cause net harm.

Build Adaptive Systems

The technology landscape changes quickly, and the evidence base will continue to develop. Regulatory frameworks should include mechanisms for ongoing monitoring, independent evaluation of policy effectiveness, and structured review cycles. Policies built for today's social media environment may be irrelevant or counterproductive in five years.

Implications for Practice

For educators, practitioners, families, and youth workers, the following practical implications follow from the evidence reviewed.

Encourage Balanced Use, Not Total Restriction

Research does not support complete bans on adolescent social media use. Rather, conversations should focus on how adolescents use platforms, what content they engage with, and whether their digital lives are displacing sleep, physical activity, or face-to-face connection.

Create Psychologically Safe Spaces for Open Conversations

Adolescents are far more likely to seek help when they encounter distressing online experiences if they believe adults will respond with curiosity and support rather than surveillance and punishment. Building trust is more protective than monitoring.

Prioritize Sleep

Supporting adolescents to maintain healthy sleep habits including device-free bedrooms and consistent bedtimes may be one of the most impactful interventions available to families and schools, given the strong evidence for sleep as a mediating pathway between digital media use and mental health.

Teach Critical Thinking and Media Literacy as Core Skills

These are not add-ons to the curriculum; they are foundational competencies for life in the twenty-first century. Schools should treat them accordingly.

Recognize Both Risks and Genuine Benefits

Digital spaces provide access to information, creative communities, peer support, and identity exploration that can be genuinely valuable, particularly for adolescents who are isolated, marginalized, or have limited access to offline resources. A risk-only framing misses this complexity and may inadvertently communicate to young people that their online lives are inherently problematic.

Conclusion

The relationship between screen time and adolescent mental health is real, but it is also often overstated, oversimplified, and stripped of the contextual nuance that is essential for effective policy. The evidence does not justify panic-driven measures or one-size-fits-all restrictions that treat all digital media use by all adolescents as uniformly harmful. Instead, it calls for measured, evidence-informed responses that recognize complexity, center the most vulnerable, and preserve the genuine benefits of digital connection and participation. Good policy in this space is not about eliminating risk entirely, an impossible and counterproductive goal. It is about managing risk wisely, in proportion to evidence, with attention to equity, and with sufficient humility to revise approaches as knowledge develops. The adolescents who will be most affected by today's policy decisions deserve nothing less than policymakers’ honest engagement with the evidence.

Policy Insights

The evidence base on digital media and adolescent mental health is now sufficient to support action, but it is not yet strong enough to mandate any single policy approach with high confidence. Large-scale reviews and longitudinal studies consistently demonstrate that: the average effects of social media use on adolescent mental health are small but real; effects are concentrated in identifiable subgroups (particularly early adolescent girls on image-focused platforms); multiple mechanisms especially sleep disruption and social comparison mediate harms; and no policy intervention has yet demonstrated clear, replicated effectiveness at population scale.

Given this evidence base, the strongest candidates for immediate implementation are (1) platform design regulation requiring safety-by-default features for child users, with independent enforcement; and (2) structured digital literacy education integrated into national school curricula. Both approaches target documented mechanisms of harm, have theoretical support in the literature, and can be implemented in ways that do not restrict adolescents’ access to beneficial digital spaces. Age verification and parental control approaches may have a role as supplementary measures for younger children, but they should not be treated as primary protective mechanisms given the evidence of limited effectiveness and potential for inequitable impact.

The primary stakeholders for implementation are national governments (who must legislate and fund), platform companies (who control design choices and content moderation systems), educational authorities (who must integrate digital literacy into curricula), public health agencies (who should lead evidence monitoring and evaluation), and civil society organizations (who represent the interests of young people and can hold other actors accountable). Meaningful engagement of young people themselves as advisors, researchers, and advocates is both ethically necessary and practically valuable.

The cost-benefit case for action is strongest for platform design regulation, where the costs are primarily borne by companies (through investment in safety engineering and compliance) rather than by families or governments, and where potential benefits reduced exposure to harmful content for millions of adolescents simultaneously are substantial. Digital literacy education requires sustained public investment in teacher training, curriculum development, and program evaluation, but the long-term returns in terms of adolescent agency, resilience, and civic participation extend well beyond mental health. Any serious national strategy for adolescent digital wellbeing will require both.

What is not supported by the evidence is inaction, on one hand, or reactive prohibition on the other. The evidence calls for sustained, proportionate, equity-conscious policy investment guided by the best available science and a commitment to updating that investment as the science develops.

Footnotes

ORCID iD

Rose Atieno Opiyo

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

Agyapong-Opoku

Adu

M. K.

Frimpong

Osei

Danso

Agyapong

V. I. O.

(2025). Effects of social media use on youth and adolescent mental health: A scoping review of reviews. Behavioral Sciences, 15(5), 574. https://doi.org/10.3390/bs15050574

Coyne

S. M.

Rogers

A. A.

Zurcher

J. D.

Stockdale

Booth

(2020). Does time spent using social media impact mental health? An eight-year longitudinal study. Computers in Human Behavior, 104, 106160. https://doi.org/10.1016/J.CHB.2019.106160

Hutton

J. S.

Dudley

Horowitz-Kraus

(2024). Digital media and developing brains: Concerns and opportunities. Current Addiction Reports, 11(3), 423–433. https://doi.org/10.1007/s40429-024-00545-3

Ito

Baumer

Bittanti

Boyd

Cody

Stephenson

B. H.

Horst

H. A.

Lange

P. G.

Mahendran

Martínez

K. Z.

Pascoe

C. J.

Perkel

Robinson

Sims

Tripp

(2009). Hanging out, messing around, and geeking out: Kids living and learning with new media. MIT Press. MacArthur Foundation Digital Media and Learning Series.

Marciano

Ostroumova

Schulz

P. J.

Camerini

A.-L.

(2022). Like this meta-analysis: Screen media and mental health. Professional Psychology: Research and Practice, 53(2), 205–214. https://doi.org/10.1037/pro0000426

Marciano

Schulz

P. J.

Camerini

A.-L.

(2022). Digital media use and adolescents’ mental health during the COVID-19 pandemic: A systematic review and meta-analysis. Frontiers in Public Health, 9, 793868. https://doi.org/10.3389/fpubh.2021.793868

Marwick

A. E.

Duportail

Gasser

Swire-Thompson

(2024). Child online safety legislation (COSL): A primer. PubPub. https://doi.org/10.21428/bfcb0bff.de78f444

Odgers

C. L.

Jensen

M. R.

(2020). Annual research review: Adolescent mental health in the digital age: Facts, fears, and future directions. Journal of Child Psychology and Psychiatry, 61(3), 336–348. https://doi.org/10.1111/JCPP.13190

Osborne

(2025). Balancing the benefits and risks of social media on adolescent mental health in a post-pandemic world. Child and Adolescent Psychiatry and Mental Health, 19(1), 10. https://doi.org/10.1186/s13034-025-00951-z

10.

Santos

J. P. M.

Tavares

D. M. S.

Ferreira

P. C. S.

Gomes

N. C.

(2023). The associations between screen time and mental health in adolescents: A systematic review. BMC Psychology, 11(1), 127. https://doi.org/10.1186/s40359-023-01166-7

11.

Thorisdottir

I. E.

Sigurvinsdottir

Kristjansson

A. L.

Allegrante

J. P.

Lilly

C. L.

Sigfusdottir

I. D.

(2020). Longitudinal association between social media use and psychological distress among adolescents. Preventive Medicine, 141, 106270. https://doi.org/10.1016/J.YPMED.2020.106270

12.

Toda Peace Institute / Inter Press Service. (2025). Rethinking digital platform design: A systems approach. https://toda.org/global-outlook/2025/rethinking-digital-platform-design-a-systems-approach.html

13.

van der Wal

R. C.

Valkenburg

P. M.

Beyens

(2025). Diverse platforms, diverse effects: Evidence from a 100-day study on social media and adolescent mental health. OSF Preprints. https://doi.org/10.31234/osf.io/qe9rn_v2

14.

Vijayakumar

Flannery

J. E.

Cheng

T. W.

Cosme

Flournoy

J. C.

Barendse

M. E. A.

Pfeifer

J. H.

(2025). The effects of social media on adolescent mental health: Findings from a population-based cohort study in Australia. OSF Preprints. https://doi.org/10.31219/osf.io/5znqk_v1

15.

The White Hatter. (2026). Platform design, age gating, and why language and intent matters in the social media legislation debate. https://www.thewhitehatter.ca

16.

World Health Organization. (2024). Addressing the digital determinants of young people's mental health and well-being: Web annex findings from an evidence review and policy mapping. WHO.

17.

Zhu

Griffiths

Eisenberg

M. E.

Gower

A. L.

McMorris

B. J.

Sieving

R. E.

(2023). Trajectories of screen time across adolescence and their associations with adulthood mental health and behavioral outcomes. Journal of Youth and Adolescence, 52(10), 2173–2188. https://doi.org/10.1007/s10964-023-01782-x