2f:I[703058,["/_next/static/immutable/chunks/3bhq_5eh1d760.js","/_next/static/immutable/chunks/1855-ogyi8eh4.js","/_next/static/immutable/chunks/2pfsjpn6k6zlg.js","/_next/static/immutable/chunks/26c7v3_3uwnwu.js","/_next/static/immutable/chunks/25a3ozcrvi1ff.js","/_next/static/immutable/chunks/2r4wx50nvjh_4.js","/_next/static/immutable/chunks/23fsw06hsi5b1.js","/_next/static/immutable/chunks/06_yt270h41rg.js","/_next/static/immutable/chunks/3ezsiz-7shkna.js","/_next/static/immutable/chunks/20x2y96ldu5wx.js","/_next/static/immutable/chunks/2lxntcm3pd1_h.js","/_next/static/immutable/chunks/00dgco8irq3jw.js","/_next/static/immutable/chunks/00nwe-kq0rboc.js","/_next/static/immutable/chunks/2051ffx3xzio9.js"],"PaperListPageClient"] 30:T663,A total of 153 studies (115 cohorts, 1072 effect sizes) with 18 933 participants met criteria for quantitative synthesis. Study participant ages ranged from 2 to 19 (mean [SD], 12.81 [2.79]) years, with 53.8% female and 46.2% male. Most studies were conducted in Europe (62 [40.5%]) and North America (60 [39.2%]), followed by Asia (22 [14.4%]), Australia (5 [3.3%]), and Latin America (1 [0.7%]). Social media use was associated with higher depression, externalizing and internalizing behaviors, self-injurious thoughts, problematic internet use, and substance use (r = 0.09; 95% CI, 0.06-0.12 to r = 0.21; 95% CI, 0.13-0.29) and also with lower academic achievement, poorer self-perception, and less positive development (r = -0.14; 95% CI, -0.26 to -0.01 to r = -0.07; 95% CI, -0.11 to -0.02). Video gaming was associated with higher aggression and externalizing behaviors (r = 0.16; 95% CI, 0.09-0.23 and r = 0.17; 95% CI, 0.07-0.26, respectively) and higher attention/executive functioning (r = 0.10; 95% CI, 0.03-0.16). Other digital media use, including digital device use and messaging/communication media, was associated with depression (r = 0.05; 95% CI, 0.00-0.09 to r = 0.12; 95% CI, 0.02-0.22). Associations between social media and depression were stronger in early adolescence (β = 0.09) and with self or parent-reported outcomes (β = 0.09); associations between social media and positive development were stronger with objective exposure measurement (β = 0.08). More recent social media exposure years showed stronger associations with substance use (β = 0.10).31:Tcca,This systematic review and meta-analysis synthesized global longitudinal studies to estimate associations between social media, video games, and other digital media use with health and developmental outcomes in children and adolescents. To provide a meta-analytic synthesis of evidence on digital media use and health and developmental outcomes among individuals aged 0 to 18 years. This review was preregistered with PROSPERO, MEDLINE, PsycINFO, EMBASE, and ERIC databases and gray literature were searched from 2000 to 2024. Inclusion criteria were English-language longitudinal studies of participants aged 0 to 18 years reporting quantitative associations between digital media use and health or developmental outcomes. Following PRISMA guidelines, 153 studies (115 cohorts, 1072 effect sizes) from 18 933 articles met criteria for quantitative synthesis. Random-effects meta-analyses estimated pooled correlations (r) with 95% CIs. Heterogeneity and moderators (age, sex, measurement method, follow-up duration, year of exposure) were examined. Study quality was assessed using the National Institutes of Health's Quality Assessment Tool. These data were analyzed from February 2025 to August 2025. Primary outcomes were socialemotional, cognitive, physical and motor health, and development associations. A total of 153 studies (115 cohorts, 1072 effect sizes) with 18 933 participants met criteria for quantitative synthesis. Study participant ages ranged from 2 to 19 (mean [SD], 12.81 [2.79]) years, with 53.8% female and 46.2% male. Most studies were conducted in Europe (62 [40.5%]) and North America (60 [39.2%]), followed by Asia (22 [14.4%]), Australia (5 [3.3%]), and Latin America (1 [0.7%]). Social media use was associated with higher depression, externalizing and internalizing behaviors, self-injurious thoughts, problematic internet use, and substance use (r = 0.09; 95% CI, 0.06-0.12 to r = 0.21; 95% CI, 0.13-0.29) and also with lower academic achievement, poorer self-perception, and less positive development (r = -0.14; 95% CI, -0.26 to -0.01 to r = -0.07; 95% CI, -0.11 to -0.02). Video gaming was associated with higher aggression and externalizing behaviors (r = 0.16; 95% CI, 0.09-0.23 and r = 0.17; 95% CI, 0.07-0.26, respectively) and higher attention/executive functioning (r = 0.10; 95% CI, 0.03-0.16). Other digital media use, including digital device use and messaging/communication media, was associated with depression (r = 0.05; 95% CI, 0.00-0.09 to r = 0.12; 95% CI, 0.02-0.22). Associations between social media and depression were stronger in early adolescence (β = 0.09) and with self or parent-reported outcomes (β = 0.09); associations between social media and positive development were stronger with objective exposure measurement (β = 0.08). More recent social media exposure years showed stronger associations with substance use (β = 0.10). In this systematic review and meta-analysis, digital media use was consistently associated with risks to child and adolescent health and development, particularly for social media. These findings highlight the need for targeted, multifaceted policies and interventions to mitigate potential harms from digital media exposure.32:T158b, Importance This systematic review and meta-analysis synthesized global longitudinal studies to estimate associations between social media, video games, and other digital media use with health and developmental outcomes in children and adolescents. Objective To provide a meta-analytic synthesis of evidence on digital media use and health and developmental outcomes among individuals aged 0 to 18 years. Data Sources This review was preregistered with PROSPERO, MEDLINE, PsycINFO, EMBASE, and ERIC databases and gray literature were searched from 2000 to 2024. Study Selection Inclusion criteria were English-language longitudinal studies of participants aged 0 to 18 years reporting quantitative associations between digital media use and health or developmental outcomes. Data Extraction and Synthesis Following PRISMA guidelines, 153 studies (115 cohorts, 1072 effect sizes) from 18 933 articles met criteria for quantitative synthesis. Random-effects meta-analyses estimated pooled correlations (r) with 95% CIs. Heterogeneity and moderators (age, sex, measurement method, follow-up duration, year of exposure) were examined. Study quality was assessed using the National Institutes of Health’s Quality Assessment Tool. These data were analyzed from February 2025 to August 2025. Main Outcomes and Measures Primary outcomes were socialemotional, cognitive, physical and motor health, and development associations. Results A total of 153 studies (115 cohorts, 1072 effect sizes) with 18 933 participants met criteria for quantitative synthesis. Study participant ages ranged from 2 to 19 (mean [SD], 12.81 [2.79]) years, with 53.8% female and 46.2% male. Most studies were conducted in Europe (62 [40.5%]) and North America (60 [39.2%]), followed by Asia (22 [14.4%]), Australia (5 [3.3%]), and Latin America (1 [0.7%]). Social media use was associated with higher depression, externalizing and internalizing behaviors, self-injurious thoughts, problematic internet use, and substance use ( r = 0.09; 95% CI, 0.06-0.12 to r = 0.21; 95% CI, 0.13-0.29) and also with lower academic achievement, poorer self-perception, and less positive development ( r = −0.14; 95% CI, −0.26 to −0.01 to r = −0.07; 95% CI, −0.11 to −0.02). Video gaming was associated with higher aggression and externalizing behaviors ( r = 0.16; 95% CI, 0.09-0.23 and r = 0.17; 95% CI, 0.07-0.26, respectively) and higher attention/executive functioning ( r = 0.10; 95% CI, 0.03-0.16). Other digital media use, including digital device use and messaging/communication media, was associated with depression ( r = 0.05; 95% CI, 0.00-0.09 to r = 0.12; 95% CI, 0.02-0.22). Associations between social media and depression were stronger in early adolescence (β = 0.09) and with self or parent-reported outcomes (β = 0.09); associations between social media and positive development were stronger with objective exposure measurement (β = 0.08). More recent social media exposure years showed stronger associations with substance use (β = 0.10). Conclusions and Relevance In this systematic review and meta-analysis, digital media use was consistently associated with risks to child and adolescent health and development, particularly for social media. These findings highlight the need for targeted, multifaceted policies and interventions to mitigate potential harms from digital media exposure. 25:[[["$","script","0",{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"CollectionPage\",\"name\":\"Substance Use: condition Research & Clinical Takeaways\",\"description\":\"Explore peer-reviewed papers on Substance Use (condition). Clinician-written summaries and actionable practice insights. 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Beverage products and brands like Mood (64.4%) and Delta Extrax (60.1%) most frequently used youth-oriented content; Cycling Frog led in product (93.4%) and recreational (83.7%) themes.","limitations":"Only nine brands and one platform (Instagram) were studied, limiting generalizability. The one-year snapshot may not reflect current or evolving marketing tactics. Content analysis cannot establish a causal link between marketing exposure and consumer behavior or harm.","practice_takeaway":"DICP brands heavily use youth-appealing and recreational content on Instagram with minimal health or age warnings — clinicians should ask adolescent and young adult patients about exposure to this marketing and use of these products. Advocacy for stricter social media marketing regulations for DICPs is warranted given the known harms (poisonings, ED visits, psychotic episodes)."}},{"doi":"10.1176/appi.ajp.20251292","pmid":"42265596","title":"Social Media Use Trajectories and Substance Use Experimentation: A Prospective Cohort Study","journal_title":"American Journal of Psychiatry","journal_issn":"0002-953X","published_at":"2026-06-10T00:00:00.000Z","url":"https://doi.org/10.1176/appi.ajp.20251292","source_score":154,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-18T13:24:30.247Z","updated_at":"2026-06-18T13:24:30.247Z","tags":[{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"age_group","value":"adolescent","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"age_group","value":"child","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"category","value":"Psychiatry","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"condition","value":"Alcohol Use","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"condition","value":"Cannabis Use","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"condition","value":"Nicotine Use","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"condition","value":"Substance Use","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"impact_flag","value":"practice_changing","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"level_of_evidence","value":"2","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"sample_size","value":"n=7166","value_numeric":7166},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"study_design","value":"Prospective Cohort Study","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"warning","value":"Social media use measurement details (e.g., specific instruments, reporter — child vs. parent) are not fully described in the abstract, which may affect interpretation of trajectory accuracy.","value_numeric":null},{"paper_doi":"10.1176/appi.ajp.20251292","tag_type":"warning","value":"The impact_flag 'practice_changing' is assigned cautiously — while the effect sizes are large, the study is observational and cannot establish causation between social media use and substance experimentation.","value_numeric":null}],"summaries":{"what_studied":"This prospective cohort study examined whether trajectories of daily social media use (baseline to year 4) were associated with alcohol, cannabis, and nicotine experimentation at year 5 in 7,166 adolescents (mean age 10 years at baseline) from the Adolescent Brain Cognitive Development (ABCD) Study, followed from 2016–2023.","key_result":"Four social media use trajectories were identified; all increasing trajectories were associated with higher odds of substance use experimentation compared to no/very low use. The early-onset, rapid increasing trajectory showed the strongest association — e.g., aOR=16.86 (95% CI: 10.28–27.65) for cannabis experimentation.","limitations":"- Substance use was measured only at year 5, limiting insight into timing of initiation relative to social media exposure.\n- Social media use was self- or parent-reported, which may introduce recall bias.\n- Findings reflect experimentation (not regular use), so generalizability to heavier substance use patterns is unclear.","practice_takeaway":"Clinicians should screen for early and rapidly escalating social media use in pre-teens, as it is a strong prospective marker for substance use experimentation by mid-adolescence. Counseling families on healthier digital habits before ages 9–11 may be a meaningful prevention opportunity."}},{"doi":"10.1080/10903127.2026.2678432","pmid":"42240286","title":"Identification and Documentation of Patient Social Risk Factors in the Prehospital Setting: A Pilot Implementation","journal_title":"Prehospital Emergency Care","journal_issn":"1090-3127","published_at":"2026-06-04T00:00:00.000Z","url":"https://doi.org/10.1080/10903127.2026.2678432","source_score":2,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-11T13:43:00.692Z","updated_at":"2026-06-11T13:43:00.692Z","tags":[{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"age_group","value":"adult","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"category","value":"Emergency Medicine","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"condition","value":"Housing Instability","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"condition","value":"Social Determinants of Health","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"condition","value":"Substance Use","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"level_of_evidence","value":"4","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"modality","value":"Prehospital Screening Tool","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"sample_size","value":"n=57899","value_numeric":57899},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"sex","value":"mixed","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"study_design","value":"Retrospective Cohort Study","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"warning","value":"Single-agency pilot study conducted over 6 months; findings may not be generalizable to other EMS systems or geographic regions.","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"warning","value":"The 4% SRF documentation rate almost certainly reflects under-reporting rather than true prevalence; the study design cannot distinguish the two.","value_numeric":null},{"paper_doi":"10.1080/10903127.2026.2678432","tag_type":"warning","value":"The p-values reported for age and sex comparisons are listed as '>0.05' in the abstract, suggesting these demographic differences were not statistically significant — this appears counterintuitive given the described directional differences and should be interpreted cautiously.","value_numeric":null}],"summaries":{"what_studied":"A 14-item prehospital social risk factor (SRF) documentation tool — derived from WHO social determinants of health categories — was integrated as a required field into an EMS agency's charting platform; all adult emergency and non-emergency calls over 6 months (July 11, 2024–January 11, 2025) were reviewed retrospectively to assess SRF identification rates and prevalence.","key_result":"Of 57,899 encounters, only 4.0% (n=2,326) had at least one SRF documented; the most common SRFs were substance use (31.3%), housing instability (25.7%), and disability (25.4%), with 30.8% of the SRF-positive group having more than one SRF identified.","limitations":"Single EMS agency limits generalizability; low SRF documentation rate (4%) likely reflects under-reporting rather than true prevalence, and barriers to recognition were not formally assessed; the study cannot distinguish true absence of SRFs from clinician failure to document them.","practice_takeaway":"Making SRF screening a required chart field captured a meaningful subgroup, but a 4% rate signals major under-reporting — EMS systems should identify and address barriers preventing clinicians from recognizing and documenting social risk factors before ED handoff."}},{"doi":"10.1111/add.70485","pmid":"42204061","title":"Will social media bans reduce the amount of substance use‐related content to which young people are exposed?","journal_title":"Addiction","journal_issn":"0965-2140","published_at":"2026-05-27T00:00:00.000Z","url":"https://doi.org/10.1111/add.70485","source_score":8,"is_retracted":false,"is_open_access":false,"raw_metadata":{"pubmed":true,"crossref":true,"unpaywall":true},"created_at":"2026-06-07T13:26:40.106Z","updated_at":"2026-06-07T13:26:40.106Z","tags":[{"paper_doi":"10.1111/add.70485","tag_type":"age_group","value":"adolescent","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"category","value":"Psychiatry","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"condition","value":"Alcohol Use","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"condition","value":"Substance Use","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"condition","value":"Vaping","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"impact_flag","value":"limited_evidence","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"level_of_evidence","value":"7","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"modality","value":"Public Health Policy","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"study_design","value":"Editorial","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"warning","value":"Sex of population not reported or relevant to this policy discussion; sex tag omitted.","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"warning","value":"Study design is ambiguous between 'Editorial' and 'Policy Analysis' — tagged as Editorial per journal labeling.","value_numeric":null},{"paper_doi":"10.1111/add.70485","tag_type":"warning","value":"This is an expert editorial with no original data; all conclusions are hypothesis-driven and based on cited reviews. The Australia ban was very recently implemented (as of publication), so no outcome data are yet available.","value_numeric":null}],"summaries":{"what_studied":"This editorial examines whether Australia's social media ban (prohibiting those under 16 from accounts on platforms like Instagram and TikTok) will reduce young people's exposure to substance-related content (alcohol, vaping, other drugs), and what additional policy measures could complement the ban.","key_result":"The ban's impact on exposure is uncertain and depends on circumvention rates, displacement to other platforms, and industry marketing pivots. Young people who bypass the ban by registering as adults may lose 'teen account' content protections, potentially *increasing* their exposure to vaping, smoking, and other drug content. User-generated alcohol content and influencer marketing remain visible even under existing teen account filters.","limitations":"This is an opinion/editorial with no primary data; all conclusions are speculative or based on cited secondary literature. The ban's real-world effects have not yet been empirically evaluated. The discussion is largely Australia-specific, limiting direct generalizability.","practice_takeaway":"Clinicians working with adolescents should be aware that a social media ban alone may not reduce—and could inadvertently increase—exposure to substance-related content for teens who circumvent age gates. Advocating for school-based media literacy programs and safety-by-design platform regulations offers complementary harm-reduction strategies."}},{"doi":"10.1016/s2352-4642(26)00099-4","pmid":"42114544","title":"Responding to injectable synthetic peptide use among young people: priorities for clinicians and public health","journal_title":"The Lancet Child & Adolescent Health","journal_issn":"2352-4642","published_at":"2026-05-12T00:00:00.000Z","url":"https://doi.org/10.1016/s2352-4642(26)00099-4","source_score":22,"is_retracted":false,"is_open_access":false,"raw_metadata":{"ooir":{"day":"2026-05-11","doi":"10.1016/s2352-4642(26)00099-4","days":"7","issn":"2352-4642","rank":"7","field":"Clinical Medicine","score":"22","category":"Pediatrics","categories":["Pediatrics"],"_categories":["Pediatrics"]},"pubmed":{"doi":"10.1016/S2352-4642(26)00099-4","title":"Responding to injectable synthetic peptide use among young people: priorities for clinicians and public health.","journal":"The Lancet. 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Video gaming was associated with higher aggression (r=0.16) and better attention/executive functioning (r=0.10). Social media–depression links were strongest in early adolescence.","limitations":"- Most studies were from Europe (40.5%) and North America (39.2%), limiting generalizability to other regions.\n- Effect sizes are small-to-modest correlations from observational longitudinal data; causality cannot be established.\n- Self- and parent-reported outcomes inflated some associations (β=0.09 moderator effect), suggesting measurement bias.","practice_takeaway":"Counsel families that social media use carries consistent, small-but-real risks for depression, self-harm ideation, and substance use—especially in early adolescence. Support multifaceted policies and screen-time guidance rather than a single intervention."}}],"initialOffset":6,"fetchConfig":{"kind":"tags","tags":[{"tag_type":"condition","value":"Substance Use"}]},"breadcrumbItems":[{"name":"Home","href":"/"},{"name":"Research Hub","href":"/hub"},{"name":"Conditions","href":"/hub/tag/condition"},{"name":"Substance Use"}],"hrefConfig":{"basePath":"/hub/papers","webViewQueryParams":{"hub_ctx":"tag","hub_tag_type":"condition","hub_tag_value":"Substance Use"}}}]]

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