How smartphone usage affects well-being and learning among children and adolescents is a concern for schools, parents, and policymakers. Combining detailed admi
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Hall JA Ten myths about the effect of social media use on well-being J. Med. Internet Res. • Dissing AS et al. Smartphone interactions and mental well-being in young adults: A longitudinal study based on objective high-resolution smartphone data Scand. J. Public Health • Beyens I et al. The effect of social media on well-being differs from adolescent to adolescent Sci. Rep. • Valkenburg PM Social media use and well-being: What we know and what we need to know Curr. Opin. Psychol. • Panova T et al. Is smartphone addiction really an addiction? J. Behav. Addict. • Heffer T et al. The longitudinal association between social-media use and depressive symptoms among adolescents and young adults: An empirical reply to Twenge et al. (2018) Clin. Psychol. Sci. • Stavrova O et al. Does using social media jeopardize well-being? The importance of separating within- from between-person effects Soc. Psychol. Personal. Sci. • Lawrence D et al. Reciprocal relationships between trajectories of loneliness and screen media use during adolescence J. Child Fam. Stud. • Cunningham S et al. Social media and depression symptoms: A meta-analysis Res. Child Adolesc. Psychopathol. • Hall JA et al. Experimentally manipulating social media abstinence: results of a four-week diary study Media Psychol. • Panayiotou M et al. Time spent on social media among the least influential factors in adolescent mental health: preliminary results from a panel network analysis Nat. Ment. Health • Johannes N et al. Objective, subjective, and accurate reporting of social media use: No evidence that daily social media use correlates with personality traits, motivational states, or well-being Technol. Mind Behav. • Johannes N et al. No effect of different types of media on well-being Sci. Rep. • Meier A et al. Computer-mediated communication, social media, and mental health: A conceptual and empirical meta-review Communic. Res. • Bruce LD et al. Loneliness in the United States: A 2018 national panel survey of demographic, structural, cognitive, and behavioral characteristics Am. J. Health Promot. • Schemer C et al. The impact of Internet and social media use on well-being: A longitudinal analysis of adolescents across nine years J. Comput. Mediat. Commun. • Hall JA et al. Two tests of social displacement through social media use Inf. Commun. Soc. • Hampton KN Social media and change in psychological distress over time: The role of social causation J. Comput. Mediat. Commun. • Steinsbekk S et al. The new social landscape: Relationships among social media use, social skills, and offline friendships from age 10-18 years Comput. Human Behav. • Odgers CL The great rewiring: is social media really behind an epidemic of teenage mental illness? Nature
Phone-Free Schools Movement | Protecting Student Well-Being
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Social Media Use and Well-Being Across Adolescent Development
Importance Social media’s association with adolescent well-being remains debated. Heavy use has been associated with distress, while abstinence may cause missed connections. Objective To investigate 3-year longitudinal associations between after-school social media use and adolescent well-being using a large longitudinal cohort dataset modeled within a repeated cross-sectional framework. Design, Setting, and Participants This cohort study included Australian students in grades 4 through 12 (2019-2022). After-school social media use was self-reported and grouped as none, moderate, or highest. Well-being was assessed using 8 validated indicators (eg, happiness, life satisfaction, emotional regulation), dichotomized as high vs low. Well-being was assessed concurrently with social media use during the annual school-based survey in each year of data collection. Data analysis was conducted from June to July 2025. Exposures Self-reported after-school social media use between 3 pm and 6 pm (weekdays), classified into 3 categories: none (0 h/wk), moderate (>0 to <12.5 h/wk), and highest (≥12.5 h/wk). Main Outcomes and Measures The primary outcome was overall well-being, measured as the mean score across 8 validated domains (happiness, optimism, life satisfaction, worry, sadness, perseverance, emotional regulation, and cognitive engagement), dichotomized as high vs low (<3 on a scale of 1-5). Secondary outcomes were each individual well-being indicator, similarly dichotomized. Mixed-effects logistic models were used for analyses, stratified by sex and adjusted for demographic covariates. Results The analytic sample included 100 991 adolescents, contributing 173 533 observations (86 582 [49.9%] observations from female participants; mean [SD] age, 13.5 [2.2] years). A U-shaped association was observed between after-school social media use and well-being. Compared with moderate users, adolescents with the highest use had greater odds of low well-being (grades 7-9, girls: odds ratio [OR], 3.13 [95% CI, 2.88-3.39]; boys: OR, 2.25 [95% CI, 1.86-2.72]), while nonusers also had higher odds of low well-being in later adolescence (grades 10-12, girls: OR, 1.79 [95% CI, 1.41-2.27]; boys: OR, 3.00 [95% CI, 2.01-4.46]). These patterns were consistent across survey years and robust to sensitivity analyses. Conclusions and Relevance In this cohort study of students in grades 4 through 12, social media’s association with adolescent well-being was complex and nonlinear, varying by age and sex. While heavy use was associated with poorer well-being and abstinence sometimes coincided with less favorable outcomes, these findings are observational and should be interpreted cautiously.
The effect of social media on well-being differs from adolescent to adolescent
The question whether social media use benefits or undermines adolescents’ well-being is an important societal concern. Previous empirical studies have mostly established across-the-board effects among (sub)populations of adolescents. As a result, it is still an open question whether the effects are unique for each individual adolescent. We sampled adolescents’ experiences six times per day for one week to quantify differences in their susceptibility to the effects of social media on their momentary affective well-being. Rigorous analyses of 2,155 real-time assessments showed that the association between social media use and affective well-being differs strongly across adolescents: While 44% did not feel better or worse after passive social media use, 46% felt better, and 10% felt worse. Our results imply that person-specific effects can no longer be ignored in research, as well as in prevention and intervention programs.
Reciprocal Relationships between Trajectories of Depressive Symptoms and Screen Media Use during Adolescence
Adolescents are constantly connected with each other and the digital landscape through a myriad of screen media devices. Unprecedented access to the wider world and hence a variety of activities, particularly since the introduction of mobile technology, has given rise to questions regarding the impact of this changing media environment on the mental health of young people. Depressive symptoms are one of the most common disabling health issues in adolescence and although research has examined associations between screen use and symptoms of depression, longitudinal investigations are rare and fewer still consider trajectories of change in symptoms. Given the plethora of devices and normalisation of their use, understanding potential longitudinal associations with mental health is crucial. A sample of 1,749 (47% female) adolescents (10–17 years) participated in six waves of data collection over two years. Symptoms of depression, time spent on screens, and on separate screen activities (social networking, gaming, web browsing, TV/passive) were self-reported. Latent growth curve modelling revealed three trajectories of depressive symptoms (low-stable, high-decreasing, and low-increasing) and there were important differences across these groups on screen use. Some small, positive associations were evident between depressive symptoms and later screen use, and between screen use and later depressive symptoms. However, a Random Intercept Cross Lagged Panel Model revealed no consistent support for a longitudinal association. The study highlights the importance of considering differential trajectories of depressive symptoms and specific forms of screen activity to understand these relationships.
Smartphone interactions and mental well-being in young adults: A longitudinal study based on objective high-resolution smartphone data
Aims: To investigate the effects of objectively measured smartphone interactions on indicators of mental well-being among men and women in a population of young adults. Methods: A total of 816 young adults (mean±SD age 21.6±2.6 years; 77% men) from the Copenhagen Network Study were followed with objective recordings of smartphone interactions from calls, texts and social media. Participants self-reported on loneliness, depressive symptoms and disturbed sleep at baseline and in a four-month (interquartile range 75–163 days) follow-up survey. Multiple linear regression was used to analyse the association between smartphone interactions and mental well-being separately for men and women. Results: A higher number of smartphone interactions was associated with lower levels of loneliness at baseline and the same pattern appeared for depressive symptoms, although this was less pronounced. A high level of smartphone interaction was associated with lower levels of disturbed sleep for men, but not for women. In follow-up analyses, a high versus low level of smartphone interaction was associated with an increase in loneliness and depressive symptoms over time for women, but not for men. Conclusions: Smartphone interactions are related to better mental well-being, which may be attributed to the beneficial effects of an underlying social network. Over time, accommodating a large network via smartphone communication might, however, have negative effects on mental well-being for women.
Appnome analysis reveals small or no associations between social media app-specific usage and adolescent well-being
The debate on how social media use (SMU) influences adolescent well-being is mostly based on self-reports of SMU. By collecting data and screenshots donated from 374 Swiss adolescents (Meanage = 15.71; SDage = 0.82) over 2 weeks, we created “Appnomes”—app-specific usage metrics on screentime, number of activations, and number of notifications per participant per day derived, and associated them with daily hedonic and eudaimonic well-being. Longer TikTok time predicted lower eudaimonic well-being (β = − 0.08) daily but higher positive emotions (β = 0.06) the next day; longer use of WhatsApp predicted negative emotions (β = 0.06) while more screen activations for WhatsApp predicted greater feelings of connection (β = 0.08). Instagram notification was positively related to increased feeling of focused (β = 0.06) the next day. YouTube screen unlocks predicted more feeling of meaning (β = 0.07) the next day. More Snapchat screentime predicted less relaxed, less competent, and less positive emotions (with − 0.07 < β < − 0.06). Results pointed towards minimal or no effects, challenging the moral panic on the detrimental impact of SMU on teen well-being.
The association between adolescent well-being and digital technology use
The widespread use of digital technologies by young people has spurred speculation that their regular use negatively impacts psychological well-being. Current empirical evidence supporting this idea is largely based on secondary analyses of large-scale social datasets. Though these datasets provide a valuable resource for highly powered investigations, their many variables and observations are often explored with an analytical flexibility that marks small effects as statistically significant, thereby leading to potential false positives and conflicting results. Here we address these methodological challenges by applying specification curve analysis (SCA) across three large-scale social datasets (total n = 355,358) to rigorously examine correlational evidence for the effects of digital technology on adolescents. The association we find between digital technology use and adolescent well-being is negative but small, explaining at most 0.4% of the variation in well-being. Taking the broader context of the data into account suggests that these effects are too small to warrant policy change.
Smartphones and Cognition: A Review of Research Exploring the Links between Mobile Technology Habits and Cognitive Functioning
While smartphones and related mobile technologies are recognized as flexible and powerful tools that, when used prudently, can augment human cognition, there is also a growing perception that habitual involvement with these devices may have a negative and lasting impact on users’ ability to think, remember, pay attention, and regulate emotion. The present review considers an intensifying, though still limited, area of research exploring the potential cognitive impacts of smartphone-related habits, and seeks to determine in which domains of functioning there is accruing evidence of a significant relationship between smartphone technology and cognitive performance, and in which domains the scientific literature is not yet mature enough to endorse any firm conclusions. We focus our review primarily on three facets of cognition that are clearly implicated in public discourse regarding the impacts of mobile technology – attention, memory, and delay of gratification – and then consider evidence regarding the broader relationships between smartphone habits and everyday cognitive functioning. Along the way, we highlight compelling findings, discuss limitations with respect to empirical methodology and interpretation, and offer suggestions for how the field might progress toward a more coherent and robust area of scientific inquiry.
The Impact of Internet and Social Media Use on Well-Being: A Longitudinal Analysis of Adolescents Across Nine Years
Abstract The present research examines the longitudinal average impact of frequency of use of Internet and social networking sites (SNS) on subjective well-being of adolescents in Germany. Based on five-wave panel data that cover a period of nine years, we disentangle between-person and within-person effects of media use on depressive symptomatology and life satisfaction as indicators of subjective well-being. Additionally, we control for confounders such as TV use, self-esteem, and satisfaction with friends. We found that frequency of Internet use in general and use of SNS in particular is not substantially related subjective well-being. The explanatory power of general Internet use or SNS use to predict between-person differences or within-person change in subjective well-being is close to zero. TV use, a potentially confounding variable, is negatively related to satisfaction with life, but it does not affect depressive symptomatology. However, this effect is too small to be of practical relevance.
Reciprocal Relationships between Trajectories of Loneliness and Screen Media Use during Adolescence
Adolescence is the peak period for loneliness. Now a ubiquitous part of the adolescent landscape, electronic screens may provide avenues for ameliorating feelings of loneliness. Conversely, they may act as risk factors for the development of such feelings. Although cross-sectional studies to date have investigated the relationship between screen use and loneliness, longitudinal studies are needed if causal and directional associations are to be investigated. Utilising an accelerated longitudinal design and online survey we collected four waves of data from 1919 secondary school adolescents aged 10–15 years over two years. Random intercept cross-lagged panel models tested whether changes in five types of screen use (i.e., total screen time, social media use, gaming, passive screen use, and web use) are associated with changes in loneliness in the subsequent time-point, or changes in loneliness are associated with changes in screen use in the subsequent time-point. We found significant reciprocal associations between screen use and loneliness, with the strongest associations between social networking and electronic gaming and quality of friendships. These findings highlight that any significant increase in an adolescent’s screen use may be a potential indicator of changes in quality of friendships or feelings of isolation.
Ten Myths About the Effect of Social Media Use on Well-Being
This viewpoint reviews the empirical evidence regarding the association between social media use and well-being, including life satisfaction and affective well-being, and the association between social media use and ill-being, including loneliness, anxiety, and depressive symptomology. To frame this discussion, this viewpoint will present 10 widely believed myths about social media, each drawn from popular discourse on the topic. In rebuttal, this viewpoint will offer a warranted claim supported by the research. The goal is to bring popular beliefs into dialogue with state-of-the-art quantitative social scientific evidence. It is the intention of this viewpoint to provide a more accurate and nuanced claim to challenge each myth. This viewpoint will bring attention to the importance of using rigorous scientific evidence to inform public debates about social media use and well-being, especially among adolescents and young adults.
The Impact of Social Media on Adolescent Mental Health: A Meta-Analysis
Introduction: The proliferation of social media has raised significant concerns about its potential effects on the mental health of adolescents. This meta-analysis aims to provide a comprehensive assessment of the existing research on the relationship between social media use and various mental health outcomes in adolescents. Methods: A systematic search of electronic databases (PubMed, PsycINFO, Scopus, Web of Science) from January 2018 to June 2024 was conducted to identify relevant studies. Studies were included if they examined the association between social media use and mental health outcomes in adolescents (aged 10-19) and reported quantitative data. Effect sizes were calculated and pooled using random-effects models. Results: A total of 45 studies (N = 153,285 adolescents) met the inclusion criteria. The meta-analysis revealed small but significant associations between increased social media use and increased depressive symptoms (r = 0.12), anxiety (r = 0.10), and loneliness (r = 0.15). Furthermore, a significant negative association was found between social media use and self-esteem (r = -0.08). The analysis also identified several moderators of these effects, including gender, age, and type of social media platform. Conclusion: The findings of this meta-analysis suggest that increased social media use is associated with a range of negative mental health outcomes in adolescents. However, the effects are small, and the relationship is complex, with several moderating factors. Further research is needed to understand the mechanisms underlying these associations and to develop effective interventions to mitigate the potential negative effects of social media on adolescent mental health.
Reflective smartphone disengagement: Conceptualization, measurement, and validation
The present paper develops a new concept, called Reflective Smartphone Disengagement (RSD), defined as individuals’ deliberate efforts to control and restrict smartphone use. Based on the reflective-impulsive model, we examined the RSD concept in four studies, using cross-sectional data of adolescents (Study 1, N = 453, Study 3, N = 760) and adults (Study 4, N = 672), as well as panel data of adults (Study 2, N = 461). In Study 1, findings from exploratory and confirmatory factor analyses supported the one-dimensionality of the RSD scale. In Study 2, we found evidence for high test–retest reliability as well as discriminant validity, and in terms of predictive validity, RSD negatively predicted excessive smartphone use, information overload, and the social availability norm over time. Study 3 demonstrated convergent validity with a negative relationship with trait nomophobia and a positive one with trait self-reflection. Study 4 confirms the structural validity of a shorter version of the scale. We discuss avenues for future research and broader implications of the RSD concept for the field.
Is smartphone addiction really an addiction?
Aims In light of the rise in research on technological addictions and smartphone addiction in particular, the aim of this paper was to review the relevant literature on the topic of smartphone addiction and determine whether this disorder exists or if it does not adequately satisfy the criteria for addiction. Methods We reviewed quantitative and qualitative studies on smartphone addiction and analyzed their methods and conclusions to make a determination on the suitability of the diagnosis “addiction” to excessive and problematic smartphone use. Results Although the majority of research in the field declares that smartphones are addictive or takes the existence of smartphone addiction as granted, we did not find sufficient support from the addiction perspective to confirm the existence of smartphone addiction at this time. The behaviors observed in the research could be better labeled as problematic or maladaptive smartphone use and their consequences do not meet the severity levels of those caused by addiction. Discussion and conclusions Addiction is a disorder with severe effects on physical and psychological health. A behavior may have a similar presentation as addiction in terms of excessive use, impulse control problems, and negative consequences, but that does not mean that it should be considered an addiction. We propose moving away from the addiction framework when studying technological behaviors and using other terms such as “problematic use” to describe them. We recommend that problematic technology use is to be studied in its sociocultural context with an increased focus on its compensatory functions, motivations, and gratifications.