Adolescent Mental Health

Abstract Greater screen time is associated with increased symptoms of autism spectrum disorder (autism), attention-deficit/hyperactivity disorder (ADHD), and lower scores on measures of development in preschool-aged community samples. In the current longitudinal study, we examined screen time differences at 18 months of age based on clinically-defined outcomes (i.e., Autism, ADHD Concerns, Comparison) determined at age 3–5 years in a genetically-enriched sample based on family history, along with prospective associations between toddler screen time and preschool autism/ADHD symptoms and developmental achievement. Participants (n = 82) included children at high and low familial likelihood for autism and ADHD. Children with Autism and ADHD Concerns outcomes experienced significantly more screen exposure at 18 months than children without autism or elevated symptoms of ADHD. Greater screen time at 18 months was also associated with preschool symptoms of autism and ADHD and lower developmental achievement across the sample. Preschoolers with neurodevelopmental challenges experienced more screen exposure earlier in development than same-age peers, increasing potential for negative developmental impacts.

Four-wave longitudinal cohort (Trondheim Early Secure Study, Norway; n=800, ages 10, 12, 14, and 16 years). Measured social media use and symptoms of depression and anxiety through diagnostic interviews with children and parents. Applied random intercept cross-lagged panel models. Found no significant prospective association between social media posting, liking, or commenting and subsequent depression or anxiety symptoms. The reverse direction (mental health predicting social media use) was also not supported. Results were consistent across sex.

Importance Contemporary studies raise concerns regarding the implications of excessive screen time on the development of autism spectrum disorder (ASD). However, the existing literature consists of mixed and unquantified findings. Objective To conduct a systematic review and meta-analyis of the association between screen time and ASD. Data Sources A search was conducted in the PubMed, PsycNET, and ProQuest Dissertation & Theses Global databases for studies published up to May 1, 2023. Study Selection The search was conducted independently by 2 authors. Included studies comprised empirical, peer-reviewed articles or dissertations published in English with statistics from which relevant effect sizes could be calculated. Discrepancies were resolved by consensus. Data Extraction and Synthesis This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline. Two authors independently coded all titles and abstracts, reviewed full-text articles against the inclusion and exclusion criteria, and resolved all discrepancies by consensus. Effect sizes were transformed into log odds ratios (ORs) and analyzed using a random-effects meta-analysis and mixed-effects meta-regression. Study quality was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. Publication bias was tested via the Eggerz test for funnel plot asymmetry. Data analysis was performed in June 2023. Main Outcomes and Measures The 2 main variables of interest in this study were screen time and ASD. Screen time was defined as hours of screen use per day or per week, and ASD was defined as an ASD clinical diagnosis (yes or no) or ASD symptoms. The meta-regression considered screen type (ie, general use of screens, television, video games, computers, smartphones, and social media), age group (children vs adults or heterogenous age groups), and type of ASD measure (clinical diagnosis vs ASD symptoms). Results Of the 4682 records identified, 46 studies with a total of 562 131 participants met the inclusion criteria. The studies were observational (5 were longitudinal and 41 were cross-sectional) and included 66 relevant effect sizes. The meta-analysis resulted in a positive summary effect size (log OR, 0.54 [95% CI, 0.34 to 0.74]). A trim-and-fill correction for a significant publication bias (Eggerz = 2.15;P = .03) resulted in a substantially decreased and nonsignificant effect size (log OR, 0.22 [95% CI, −0.004 to 0.44]). The meta-regression results suggested that the positive summary effect size was only significant in studies targeting general screen use (β [SE] = 0.73 [0.34];t 58 = 2.10;P = .03). This effect size was most dominant in studies of children (log OR, 0.98 [95% CI, 0.66 to 1.29]). Interestingly, a negative summary effect size was observed in studies investigating associations between social media and ASD (log OR, −1.24 [95% CI, −1.51 to −0.96]). Conclusions and Relevance The findings of this systematic review and meta-analysis suggest that the proclaimed association between screen use and ASD is not sufficiently supported in the existing literature. Although excessive screen use may pose developmental risks, the mixed findings, the small effect sizes (especially when considering the observed publication bias), and the correlational nature of the available research require further scientific investigation. These findings also do not rule out the complementary hypothesis that children with ASD may prioritize screen activities to avoid social challenges.

Abstract The relationship between social media use and life satisfaction changes across adolescent development. Our analyses of two UK datasets comprising 84,011 participants (10–80 years old) find that the cross-sectional relationship between self-reported estimates of social media use and life satisfaction ratings is most negative in younger adolescents. Furthermore, sex differences in this relationship are only present during this time. Longitudinal analyses of 17,409 participants (10–21 years old) suggest distinct developmental windows of sensitivity to social media in adolescence, when higher estimated social media use predicts a decrease in life satisfaction ratings one year later (and vice-versa: lower estimated social media use predicts an increase in life satisfaction ratings). These windows occur at different ages for males (14–15 and 19 years old) and females (11–13 and 19 years old). Decreases in life satisfaction ratings also predicted subsequent increases in estimated social media use, however, these were not associated with age or sex.

We provide quasi-experimental estimates of the impact of social media on mental health by leveraging a unique natural experiment: the staggered introduction of Facebook across US colleges. Our analysis couples data on student mental health around the years of Facebook’s expansion with a generalized difference-in-differences empirical strategy. We find that the rollout of Facebook at a college had a negative impact on student mental health. It also increased the likelihood with which students reported experiencing impairments to academic performance due to poor mental health. Additional evidence on mechanisms suggests the results are due to Facebook fostering unfavorable social comparisons. (JEL D91, I12, I23, L82)

Prospective cohort study from the Japan Environment and Children's Study examining whether screen time duration at age 1 predicts ASD diagnosis at age 3. Found a significant association between prolonged screen exposure at 1 year and ASD diagnosis at 3 years in boys, but not in girls. Effect was attenuated but persistent after adjustment for sociodemographic confounders.

Meta-analysis of 57 empirical studies from 17 countries (74 effect sizes; combined n=105,440) examining the association between cyberbullying victimization and depression in adolescents. Pooled correlation: r = 0.291 (95% CI 0.246-0.335). Moderator analyses: females more affected than males; effect strengthens with age; reported effect sizes have increased over time (consistent with growing cyberbullying severity or improved measurement). Country of origin did not significantly moderate the association.

The rise of social media has provoked both optimism about potential societal benefits and concern about harms such as addiction, depression, and political polarization. In a randomized experiment, we find that deactivating Facebook for the four weeks before the 2018 US midterm election (i) reduced online activity, while increasing offline activities such as watching TV alone and socializing with family and friends; (ii) reduced both factual news knowledge and political polarization; (iii) increased subjective well-being; and post-experiment Facebook use. Deactivation reduced post-experiment valuations of Facebook, suggesting that traditional metrics may overstate consumer surplus. (JEL D12, D72, D90, I31, L82, L86, Z13)

Abstract 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.

Cohort study using National Children's Study archive data examining associations between experiential factors (screen viewing, caregiver-child play) in the first 18 months of life and ASD-like symptoms and risk on the Modified Checklist for Autism in Toddlers (M-CHAT) at age 2. Television/video viewing at 12 months was significantly associated with more ASD-like symptoms at 2 years. Daily parent-child play was associated with fewer ASD-like symptoms. Neither factor was significantly associated with ASD clinical diagnosis.

Research by Twenge, Joiner, Rogers, and Martin has indicated that there may be an association between social-media use and depressive symptoms among adolescents. However, because of the cross-sectional nature of this work, the relationship among these variables over time remains unclear. Thus, in this longitudinal study we examined the associations between social-media use and depressive symptoms over time using two samples: 594 adolescents ( M age = 12.21) who were surveyed annually for 2 years, and 1,132 undergraduate students ( M age = 19.06) who were surveyed annually for 6 years. Results indicate that among both samples, social-media use did not predict depressive symptoms over time for males or females. However, greater depressive symptoms predicted more frequent social-media use only among adolescent girls. Thus, while it is often assumed that social-media use may lead to depressive symptoms, our results indicate that this assumption may be unwarranted.

Specification curve analysis (SCA) applied across three large-scale social datasets (YRBS, MTF, MCS; total n=355,358) to examine the association between digital technology use and adolescent psychological well-being. Explored hundreds of thousands of defensible analytical specifications. The association is negative but small across virtually all specifications, explaining at most 0.4% of well-being variation -- comparable in magnitude to associations between well-being and wearing glasses or eating potatoes. Authors conclude the evidence does not support population-level policy interventions.

Secondary analysis of a 4-year randomized clinical trial cohort (n=3,826 Canadian adolescents). Annually measured social media use, television viewing, video gaming, and computer use against depressive symptoms (Brief Symptoms Inventory). Found within-person associations between social media and TV use and depressive symptoms; tested displacement, upward social comparison, and reinforcing spirals as explanatory mechanisms. Video gaming and general computer use were not significantly associated with depression.

Population-based study using UK Millennium Cohort data (n=10,904, age 14). Examined whether social media use is associated with adolescents' depressive symptoms and tested four candidate mediating pathways: online harassment, sleep disruption, self-esteem reduction, and body-image concerns. Found significant associations with all four pathways, with effects substantially stronger in girls. Concluded that interventions to mitigate social media harm should target the specific mediating pathways rather than aggregate exposure.

Longitudinal panel data show heavier daily Instagram use predicting depressive symptom escalation in adolescent girls, controlling for prior symptoms, sleep, and offline social activity.

In two nationally representative surveys of U.S. adolescents in grades 8 through 12 ( N = 506,820) and national statistics on suicide deaths for those ages 13 to 18, adolescents’ depressive symptoms, suicide-related outcomes, and suicide rates increased between 2010 and 2015, especially among females. Adolescents who spent more time on new media (including social media and electronic devices such as smartphones) were more likely to report mental health issues, and adolescents who spent more time on nonscreen activities (in-person social interaction, sports/exercise, homework, print media, and attending religious services) were less likely. Since 2010, iGen adolescents have spent more time on new media screen activities and less time on nonscreen activities, which may account for the increases in depression and suicide. In contrast, cyclical economic factors such as unemployment and the Dow Jones Index were not linked to depressive symptoms or suicide rates when matched by year.

Quasi-experimental cohort comparison replicates the directional effect of Twenge et al. with a tighter effect-size estimate and broader European sample.

Within-person daily-diary design finds no reliable effect of daily smartphone screen time on next-day depressive symptoms once between-person confounds are removed.