CoChat
Sign Up
Cited by 97Impact of Technology on AdolescentsChild and Adolescent Psychosocial and Emotional DevelopmentMental Health via Writing

Social Media Use and Depressive Symptoms Among United States Adolescents

Open access
Kreski, Noah, Platt, Jonathan, Rutherford, Caroline, Olfson, Mark, Odgers, Candice, Schulenberg, John, Keyes, Katherine M.·2021·Journal of Adolescent Health
DOI 10.1016/j.jadohealth.2020.07.006PMC PMC7876159
Open this paper in CoChat — free account

Abstract

Purpose Depression is increasingly common among US adolescents; the extent to which social media exposure contributes to this increase remains controversial. Methods We used Monitoring the Future data from 8th and 10th grade students (n=74,472), 2009–2017, to assess the relationship between daily social media use and depressive symptoms. Self-reported depressive symptom score (range: 4–20) was assessed continuously using a log-transformed outcome and at varying cutscores with logistic regression analyses. First, these outcomes were examined overall, comparing adolescents using social media daily to adolescents who were not. We then estimated predicted depressive symptom scores using 26 predictors in order to establish underlying depression risk. We partitioned students into depression risk quintiles to control for confounding due to underlying depression risk and examine heterogeneity in the association between social media use and depressive symptoms. Sensitivity analyses were used to test the robustness of results with different configurations of the predicted score model, and overall associations were examined in two-year groups to identify differences in effects. Results For girls, in adjusted risk-stratified analysis, daily social media use was not associated with high (vs low) depressive symptoms. For boys, results were inconsistent, suggesting a protective effect of daily social media use at some cutscores. Results were consistent across sensitivity analyses, and any potential harmful effects appear to be limited to 2009–2010, limiting the evidence supporting social media as a current risk factor for depressive symptoms. Conclusions Among US adolescents, daily social media use is not a strong or consistent risk factor for depressive symptoms.

Integrity signals

Registry

Crossref · 10.1016/j.jadohealth.2020.07.006

Cites

37 of 37 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 13 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    For girls, tests of interaction between predicted depression risk and daily social media use were null at all cut scores.

    “Tests of interaction between predicted risk score and daily social media were null for all cutscores.”
    Quote in the paperNot a substantial claim
  • Findingown data

    For girls in that sensitivity analysis, a rise in continuous depressive symptoms was linked to daily social media use only in the lowest predicted risk group (β=0.019, 95% CI 0.006-0.031).

    “Among girls, when depressive symptom score was considered continuously within predicted risk categories, daily social media use was associated with increased depressive symptoms among girls in the lowest predicted risk category only (β=0.019, 95% CI: 0.006, 0.031)”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.
  • Findingown data

    For boys with moderate depression risk, daily social media use was associated with higher risk of depressive symptoms above a score of 12 (OR=1.42, 95% CI 1.13-1.78).

    “Similarly, boys with moderate depression risk were at an increased risk of depressive symptoms >12 (OR=1.42, 95% CI: 1.13, 1.78).”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.
  • Findingown data

    Among US 8th and 10th grade students, the prevalence of daily social media use rose between 2009 and 2017, from 61.0% to 89.0% for girls and from 45.8% to 75.3% for boys.

    “The prevalence of daily social media use increased from 61.0% to 89.0% among girls, and from 45.8% to 75.3% among boys.”
    Quote in the paperNot a substantial claim
  • Findingown data

    For boys in the lowest depression risk category, daily social media use was associated with lower risk of depressive symptoms above a score of 12 (OR=0.77, 95% CI 0.62-0.96).

    “Boys in the lowest depression risk category, however, were at decreased risk for depressive symptoms >12 (OR=0.77, 95% CI: 0.62, 0.96)”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.
  • May combine two claims. 21
  • The quote only partly states this claim. 1
  • Classified as probably not a substantial claim. 8

  • May combine two claims.

    Findingown data

    For girls, a continuous depressive symptom increase was linked to daily social media use in 2009-2010, but not in later years (β=0.027, 95% CI 0.009-0.045).

    “Among girls, when depressive symptom score was considered continuously, daily social media use was associated with increased depressive symptoms in 2009–2010 (β=0.027, 95% CI: 0.009, 0.045), but not in other years.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.

  • The quote only partly states this claim.

    Findingown data

    For boys in the second lowest depression risk stratum, daily social media use was associated with higher risk of depressive symptoms above a score of 9 (OR=1.23, 95% CI 1.02-1.49).

    “Boys in the second lowest depression risk stratum were at increased risk for depressive symptoms >9 (OR=1.23, 95% CI: 1.02, 1.49)”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.

  • May combine two claims.

    Findingown data

    In a sensitivity analysis using a predicted depression risk score at the 90th percentile, many models did not converge because few adolescents had high depressive symptoms at that cut score; at lower predicted risk, estimates were in the same direction and general magnitude as those at the 75th percentile.

    “Given the small number of adolescents at high levels of depressive symptoms at this cutscore, models did not converge for many estimates.”
    • Also stated in: § Results · plain
      “However, at lower levels of predicted depression risk, model estimates were in the same direction and general magnitude of model estimates when predicted depression risk was at the 75th percentile.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.

  • May combine two claims.

    Findingown data

    For boys, tests of whether daily social media use varied by depression risk were mostly null, except at the cut score above 12 (chi-square=13.01, p<0.01).

    “Tests for interaction between daily social media use and depression risk were largely null, and the exception was variation in odds ratios at a cutscore score of >12 (chi-square for interaction: 13.01, p<0.01).”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.

  • May combine two claims.

    Findingown data

    The risk model separated underlying depression risk groups; at the >9 cut score, high symptoms occurred in 10.8% of lowest-risk girls and 9.0% of lowest-risk boys, compared with 97.7% of highest-risk girls and 98.1% of highest-risk boys.

    “For instance, when self-reported depressive symptom score is dichotomized at the lowest cutscore used (>9 symptom score), 10.8% of girls and 9.0% of boys with the lowest depression risk exhibit high depressive symptoms, and 97.7% of girls and 98.1% of boys with the highest depression risk exhibit high depressive symptoms.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.

  • May combine two claims.

    Interpretationown data

    Across the main and sensitivity analyses, the most consistent pattern was a rise in depressive symptoms linked to daily social media use among girls with the lowest depression risk, seen only in the continuous log-transformed outcome and not in binary outcomes.

    “The most consistent association observed across main and sensitivity analyses indicated that girls who had the lowest risk for depression had increased depressive symptoms with daily social media use, though this was only seen in the log-transformed continuous depressive symptom score outcome, not the binary outcomes.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.

  • May combine two claims.

    Interpretationown data

    For US adolescents, daily social media use is neither a strong nor a consistent risk factor for depressive symptoms.

    “Among US adolescents, daily social media use is not a strong or consistent risk factor for depressive symptoms.”
    • Also stated in: § Discussion · plain
      “We found that among adolescents in the United States, daily social media use is not a consistent risk factor for depressive symptoms.”
    • Also stated in: § Conclusion · hedged
      “At present, there is not compelling evidence to suggest that social media use meaningfully increases adolescents’ risk of depressive symptoms.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: There is no empirically validated clinical cut score for depressive symptoms.
    • Rests on an assumption: The subforms containing both social media and depressive symptom items are representative of the full Monitoring the Future sample.

  • May combine two claims.

    Premisecitation

    Online, girls may face more negative emotions than boys due to gender-based harassment and bullying, and because social networks can deepen isolation during conflicts with friends.

    “Girls online appear to be more likely than boys to experience negative emotions, given gender-based harassment and bullying [35], as well as greater salience of social networks that online engagement can facilitate, creating further isolation during periods of conflict with friends [36].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [35] Kowalski, 2014, Bullying in the digital age: A critical review and meta-analysis of cyberbullying research among youth, Psychol Bull source

      Not checked in the free run.

    • cites [36] Ging, 2016, Cyberbullying, conflict management or just messing? Teenage girls’ understandings and experiences of gender, friendship, and conflict on Facebook in an Irish second-level school, Fem Media Stud source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    No data were available on whether adolescents had received mental health treatment.

    “We also lacked information on whether adolescents had received treatment for mental health problems.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Few people with depression receive treatment, so treatment probably did not greatly affect the symptom scores in this sample.

    “Further, a minority of individuals with depression receive treatment [40], suggesting that treatment is unlikely to have a large impact on the symptom scores in our sample.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [40] Hasin, 2005, Epidemiology of major depressive disorder: Results from the national Epidemiologic survey on Alcoholism and related Conditions, Arch Gen Psychiatry source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductcitation

    The depressive symptom trends matched those from other national data sources on depressive episodes and suicide-related behavior, suggesting the measures track meaningful adolescent mental health indicators.

    “However, trends in depressive symptoms were consistent with other national sources with information on depressive episodes and suicide-related behavior [2,4], underscoring that these measures correlate with other meaningful indicators of adolescent mental health.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [2] Mojtabai, 2016, National trends in the prevalence and treatment of depression in adolescents and young Adults, Pediatrics source

      Not checked in the free run.

    • cites [4] 2017, Trends in the prevalence of suicide-related behaviors national YRBS: 1991-2017.

      Not checked in the free run.

    • Rests on an assumption: The subforms containing both social media and depressive symptom items are representative of the full Monitoring the Future sample.

  • May combine two claims.

    Premisecitation

    Sex differences in response styles may appear in adolescence; girls more often use ruminative coping, such as repetitive negative thinking and internal rather than external attribution of negative events, which can raise depressive symptom risk.

    “Gender differences in response styles may become evident during adolescence and girls are more likely to use ruminative coping and response styles [37], that include repetitive or frequent negative thinking, and internal versus external attribution of negative experiences [38], which can increase the risk of depressive symptoms.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [37] Nolen-Hoeksema, 1991, Responses to depression and their effects on the duration of depressive episodes, J AbnormPsychol

      Not checked in the free run.

    • cites [38] Weiner, 1985, An attributional theory of achievement motivation and emotion, Psychol Rev source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductown data

    Using nationally representative US data is a strength of this study and improves how broadly the findings can be generalized.

    “The present study is strengthened by the use of US nationally-representative data, which increases generalizability of the findings.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The subforms containing both social media and depressive symptom items are representative of the full Monitoring the Future sample.

  • May combine two claims.

    Study design and conductown data

    The model predicting high depressive symptoms had adequate fit (McFadden's adjusted pseudo-R2=0.55) and excellent discrimination (AUC=0.95).

    “which demonstrated adequate prediction (McFadden’s adjusted pseudo-R2=0.55)[30] and excellent accuracy in predicting observed high-depressive symptom status (AUC=0.95).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The depressive symptom questions kept the same wording and placement in every survey year, which is a strength.

    “A strength of our depressive symptom measure is the identical wording and placement of questions across the years of data collection.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    The symptom measure is not diagnostic, so its clinical significance is uncertain.

    “Depressive symptoms are not diagnostic and therefore of uncertain clinical importance.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductcitation

    A daily-use measure misses the varied ways adolescents engage with social media, which can be positive or negative depending on context.

    “Daily social media use does not capture the diverse ways in which adolescents use social media, which may be both positive [11,13,15] and negative [5,6,9] depending on the social context.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductcitation

    The four symptom items come from the Bentler Medical and Psychological Functioning Inventory depression scale, reported to have strong reliability (.72) in adolescents.

    “These items are derived from the Bentler Medical and Psychological Functioning Inventory’s depression scale [26] which exhibits strong reliability (.72) in adolescent samples [27].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [26] Newcomb, 1981, A multidimensional assessment of stressful life events among adolescents: Derivation and correlates, J Health Soc Behav source

      Not checked in the free run.

    • cites [27] Newcomb, 1986, Life change events among adolescents: An empirical consideration of some methodological issues, J Nerv Ment Dis source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Risk stratification can control observed confounders more efficiently than regression and may outperform propensity scores when covariates are weakly correlated with exposure.

    “These methods constitute a broader strategy of risk stratification, allowing for more efficient control of observed confounders than regression-based approaches [31,32], and are a better alternative to propensity score estimation when covariates are not highly correlated with the exposure [33].”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [31] Cepeda, 2003, Comparison of logistic regression versus propensity score when the number of events is low and there are multiple confounders, Am J Epidemiol source

      Not checked in the free run.

    • cites [32] Glynn, 2006, Indications for propensity scores and review of their use in pharmacoepidemiology, Basic Clin Pharmacol Toxicol source

      Not checked in the free run.

    • cites [33] Arbogast, 2011, Performance of disease risk scores, propensity scores, and traditional multivariable outcome regression in the presence of multiple confounders, Am J Epidemiol source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    For 2.3% of respondents missing one symptom item, the mean of the other three was imputed; 11.7% missing two or more items were dropped.

    “Respondents missing data on one of the four items (2.3%) were imputed with the mean value of the other three; respondents missing data on two or more of the four items (11.7 %) were excluded from the analysis.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    All analyses adjusted for survey year because question wording changed over time.

    “We controlled for survey year in all analyses, accounting for changes in question wording.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The sample was limited to 8th and 10th graders, so findings might not hold for older or younger youth or those outside school.

    “We only were able to assess 8th and 10th grade students, and results may vary among older or younger respondents or youth who are not in school.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The subforms containing both social media and depressive symptom items are representative of the full Monitoring the Future sample.

  • Classified as probably not a substantial claim.

    Study design and conductown data

    Covariates in the risk models included race/ethnicity, grade, parental education, urbanicity, academic performance, survey year, and MTF subform.

    “We included a range of covariates in the depression risk stratification models, adjusting for central sources of confounding including race/ethnicity, grade, parental educational attainment, urbanicity, academic performance, year, and subform of the MTF questionnaire assigned to the student”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductreasoning

    The cross-sectional design prevents establishing time order, so reverse causation cannot be ruled out and incident symptoms cannot be estimated.

    “Given the cross-sectional nature of these data, we were unable to establish temporality needed to rule out reverse causation, and estimate incident depression symptoms.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Non-response came almost entirely from absenteeism; under 1% of students declined.

    “Almost all non-response was due to absenteeism; less than 1% of students refused to participate.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    School participation was 91%-99%; student response was 85.0%-87.3% (mean 86.5%) without a systematic trend.

    “The overall school participation rates (including replacements of schools that decline to participate) ranged from 91% to 99% for all study years.”
    • Also stated in: § Methods · plain
      “Student response rates have ranged from 85.0% to 87.3%, and averaged 86.5%, with no systematic trend.”
    Quote in the paperNot a substantial claim
26 of 26

  • The paper relies on this without support.

    There is no empirically validated clinical cut score for depressive symptoms.

    “Given that there is no empirically validated clinical cutscore, we used a range of potential cutscores”

  • The paper relies on this without support.

    The subforms containing both social media and depressive symptom items are representative of the full Monitoring the Future sample.

    “We restricted analysis to the subforms in which key study variables overlapped.”
2 of 2

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • There are conflicting findings regarding the association between duration of digital media use and teen depressive symptoms, with some studies finding weak associations and others finding null associations, likely reflecting heterogeneity between different teens.

    “There are conflicting findings regarding the association between duration of digital media use and teen depressive symptoms, with some studies finding weak associations and others finding null associations,141-143 likely reflecting heterogeneity between different teens.”

    From Digital Ecosystems, Children, and Adolescents: Technical Report (2026) · cites this paper as [141]

    Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • Research has highlighted differences between males and females in the links between social media use and well-being in adolescence in a small subset of the analyzed data or other datasets.

    “Research has highlighted differences between males and females in the links between social media use and well-being in adolescence in a small subset of the analyzed data28, or other datasets10,29–33.”

    From Windows of developmental sensitivity to social media (2022) · cites this paper as [29]

Cites

Flagged first, then by citations

1 of the 38 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. 2017, Trends in the prevalence of suicide-related behaviors national YRBS: 1991-2017.

Cited by

Sorted by citations

Related

Authors
Kreski, N., Platt, J., Rutherford, C., Olfson, M., Odgers, C., Schulenberg, J., & Keyes, K. M.
Affiliations
  • Columbia University (US)
  • Columbia University Irving Medical Center (US)
  • University of California, Irvine (US)
  • University of Michigan (US)
Corresponding author
Keyes, Katherine M.
ORCID
Venue
Journal of Adolescent Health
Publisher
Elsevier BV
Published
2021-03
Volume
68
Issue
3
Pages
572-579
ISSN
1054-139X (ISSN-L)
DOI
10.1016/j.jadohealth.2020.07.006
PMC
PMC7876159
OpenAlex
W3048566403
Semantic Scholar
cfc1c151f1b9ce4611d21d5e8425340edad8d709
Cited by
97
References
38
Citations by year
2026: 12 · 2025: 14 · 2024: 22 · 2023: 20 · 2022: 17 · 2021: 11 · 2020: 1
FWCI
16.39
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Adolescent Health (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
National Institute on Drug Abuse
Topics
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Psychology › Clinical Psychology › Child and Adolescent Psychosocial and Emotional Development
  • Social Sciences › Psychology › Social Psychology › Mental Health via Writing
Keywords
social media use, depressive symptoms, adolescents, risk factors for depression, sex differences, adolescent mental health, Monitoring the Future
MeSH terms
Adolescent, Depression, Female, Humans, Male, Risk Factors, Students, United States, Self Report, Social Media

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-04.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-04.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review