Journal: JAMA Health Forum, 2026 doi: 10.1001/ jamahealthforum.2026.3014
Authors: Anna H. Grummon, Clayton Ulm, Amanda B. Zeitlin, Marissa G. Hall, Jennifer Falbe, Nathan A. Kline, & Thomas N. Robinson
Abstract:
Importance: Social media use is nearly ubiquitous among US teenagers and young adults and has been associated with increased risk for negative health outcomes such as depression and anxiety. Policymakers in several states have proposed or adopted policies requiring warnings on social media platforms.
Objective: To test whether teenagers and young adults perceive that social media warnings discourage them from wanting to use social media and increase their awareness of the harms of social media.
Design, setting, and participants: This within-participants randomized clinical trial was conducted online in December 2025 among US teenagers and young adults aged 13 to 29 years.
Interventions: Participants viewed 15 messages shown in random order: 13 health warnings about different harms (eg, negative body image, and depression and anxiety), a screen time break warning similar to messages voluntarily displayed on some social media platforms, and a neutral control message. Messages were displayed on a mock social media page.
Main outcomes and measures: Participants rated each message on a 1 to 5 scale for perceived message effectiveness for discouraging social media use (primary outcome) and awareness of the harms of social media (secondary outcome). Linear mixed models were used to estimate differences in outcomes between message topics, expressed as average differential effects (ADEs).
Results: A total of 1012 participants (mean [SD] age, 19.3 [4.5] years; 509 women and girls [50%], 491 men and boys [49%], and 12 individuals who identified as nonbinary or another gender [1%]) completed the study. Participants perceived all health warnings as well as the screen time break warning as more effective than the control message (range of ADEs, 0.32 [95% CI, 0.24 to 0.41] to 0.62 [95% CI, 0.53 to 0.71]). Participants perceived all health warnings as more effective than the screen time break warning (range of ADEs, 0.16 [95% CI, 0.08 to 0.24] to 0.30 [95% CI, 0.22 to 0.37]), except for the health warning about addiction (ADE, 0.07 [95% CI, -0.004 to 0.14]). Similarly, participants perceived all warnings as increasing their awareness of the harms of social media more than the control message (range of ADEs, 0.19 [95% CI, 0.10 to 0.28] to 0.63 [95% CI, 0.54 to 0.72]) and all health warnings as increasing their awareness more than the screen time break warning (range of ADEs, 0.21 [95% CI, 0.13 to 0.28] to 0.44 [95% CI, 0.36 to 0.52]).
Conclusions and relevance: These findings of this randomized clinical trial suggest that requiring warnings on social media platforms could increase awareness of the harms of social media and discourage teenagers and young adults from wanting to use social media.
Trial registration: ClinicalTrials.gov Identifier: NCT07199660.
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Journal: EClinicalMedicine, 2026, doi: 10.1016/j.eclinm.2026.104141
Authors: Seungyeon Lee, Wenyu Song, David W. Bates, Richard D. Urman, & Ping Zhang
Abstract:
Background: Over the last decade, fentanyl use in the U.S. has experienced a dramatic shift, largely driven by a rise in illicit fentanyl and its role in the opioid overdose crisis. Characterizing individual-level illicit fentanyl exposure poses significant challenges, as such use often occurs outside clinical settings and is not directly captured in clinical data, making it difficult to measure its true scale and impact.
Methods: We conducted a retrospective cohort study using Epic Cosmos, a large U.S. electronic health record dataset comprising over 300 million patients across inpatient and outpatient settings nationwide (January 1, 2015, to December 31, 2023). The dataset provides individual-level clinical data, including diagnoses, medication records, and laboratory testing data, enabling longitudinal characterization of fentanyl exposure. To infer sources of fentanyl exposure, we linked urine drug testing (UDT) results to fentanyl medication records using a sequential time window screening method (e.g., UDT positive with pre-fentanyl records or without). Temporal and Cox proportional hazards analyses were used to examine longitudinal patterns and risks of opioid-related harmful outcomes associated with medical-source versus illicit-source fentanyl exposure. Regional variation was explored. Confounding was adjusted using stabilized inverse probability weighting based on demographics, social vulnerability index, and 37 baseline conditions. Subgroup analyses tested effects of underlying clinical burden. Sensitivity analyses evaluated alternative UDT screening windows and follow-up periods to assess sensitivity to exposure and outcome definitions.
Findings: Our study cohort included 295,728 patients, consisting of 85,535 (28.9%) in the medical-source cohort (MSC) and 210,193 (71.1%) in the illicit-source cohort (ISC). From 2015 to 2023, the prevalence of nonfatal opioid overdose was consistently higher in the ISC. Overdose prevalence in the ISC increased markedly over time, reaching 18.6%, whereas only a modest increase was observed in the MSC, reaching 4.3%. For opioid dependence and abuse, the ISC had higher prevalence, and steeper year-over-year increases, versus the MSC until 2020. After 2020, prevalence in the ISC declined, particularly for dependence, but remained consistently higher than in the MSC throughout the study period. Region-stratified temporal patterns followed the overall cohort-level patterns. Illicit-source fentanyl initiation was associated with significantly elevated risk of 30-day opioid-related harmful outcomes, with adjusted hazard ratios of 2.99 (95% CI, 2.71-3.29; P < 0.001) for overdose, 1.96 (95% CI, 1.84-2.10; P < 0.001) for abuse, and 3.05 (95% CI, 2.89-3.22; P < 0.001) for dependence, compared with medical-source initiation, after confounding adjustment. Across subgroups stratified by clinical conditions, illicit-source initiation was consistently associated with increased risk of outcomes.
Interpretation: Illicit-source fentanyl exposure is associated with a markedly higher risk of opioid-related harmful outcomes than medical-source exposure, providing evidence that illicit fentanyl is a driver of adverse patient outcomes. Whilst acknowledging the limitations of this analysis, these findings underscore the substantial contribution of illicit fentanyl to the ongoing opioid epidemic and highlight the need for deeper investigation of how medical and illicit fentanyl use interact over time. Further research is warranted.
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Journal: Digital Health, 2026, doi: 10.1177/20552076261483333
Authors: Jiyoun Song, Sue Hyon Kim, Yoonjae Lee, Mollie Hobensack, Hyunjin Son, & Aviv Y. Landau
Abstract:
Objective: Substance use disorders (SUDs) are a major public health challenge, and stigma remains a key barrier to care. Unprofessional or stigmatizing language can shape clinician perceptions and affect decision-making. Traditional natural language processing (NLP) often misses context-dependent bias, while large language models (LLMs) pose reliability concerns. This study aimed to (1) develop an LLM-enhanced, human-validated NLP model to detect unprofessional language, (2) quantify unprofessional language and behavioral health referrals, and (3) examine their association among patients with SUD.
Methods: In this retrospective cohort study, we analyzed the MIMIC-IV, a large deidentified electronic health record database from a tertiary academic medical center in USA, for adult (≥18 years) with SUD admitted to the emergency department or intensive care unit between 2008 and 2019. A rule-based NLP algorithm detected unprofessional language. Three LLMs (GPT-4, Claude 3, Llama-3) expanded the vocabulary, and expert panel reviewed all generated terms for relevance and clinical realism before integration. Multivariable logistic regression examined the association between unprofessional language and behavioral health referrals.
Results: Of 260,347 patients, 31.5% had SUD. Unprofessional language was more frequent in SUD notes (72% vs. 52%). The LLM-enhanced model improved over baseline (F-score 0.89 to 0.91). Within the SUD cohort, unprofessional language was significantly associated with higher odds of referral (adjusted odds ratio = 1.54) (all p < .001).
Conclusion: Unprofessional language was common in SUD documentation and associated with behavioral health referrals. This human-validated, LLM-enhanced approach highlights how documentation-based stigma may influence care pathways and underscores the need for bias-aware, equitable communication strategies.
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Journal: Substance Use, 2026, doi: 10.1177/29768357261481840
Authors: Meghan A. Costello, Bryn Evohr, Vanessa Iroegbulem, Jason Dufour, Kelly Casottana, Corinne Cather, … A. Eden Evins
Abstract:
Background: Vaped nicotine use is associated with nicotine dependence, mental health symptoms, and physical health problems in adolescents, and peer nicotine use is a robust predictor of nicotine vaping in adolescents and young adults.
Objective: Examine associations between peer nicotine vaping and participant nicotine vaping cessation outcomes or nicotine dependence treatment adherence among adolescents and young adults enrolled in a vaping cessation trial.
Design: Exploratory secondary analysis of a 12-week randomized controlled trial with 3-month follow-up.
Methods: Participants completed a three arm, 12-week trial of varenicline and counseling, placebo and counseling, or enhanced treatment-as-usual. Participants (N=280; ages 16-25) indicated number of close friends in their broad peer network who use nicotine vapes, and a subset reported on frequency of nicotine vaping among their 10 closest friends as well as frequency of vaping by their best friend. Analyses evaluated the effect of peer vaping on biochemically-verified 7-day nicotine abstinence (end-of-treatment and follow-up) and treatment adherence. Multilevel mixed-effects models accounted for treatment condition.
Results: Participants reported a mean of 6.9 (SD=6.8) close peers in their broad peer network used vaped nicotine at baseline; more peers using nicotine vapes was inversely associated with end-of-treatment abstinence (β=-.11, p=.03), and more frequent vaping among participants’ top 10 closest peers and best friend vaping frequency were inversely associated with abstinence at end-of-treatment and follow-up (βs=-.25 to -.32, ps≤.05). For every 1 SD increase in participants’ best friend’s vape frequency, participants were 76% less likely to maintain a vape quit at 3-month follow-up (β=-1.26, p=.044; OR=0.24). Measures of peer vaping were also inversely associated with study medication adherence (βs>=-.52, ps≤.007) and fewer counseling sessions attended (βs=-.49 to -.60, ps≤.008).
Conclusion: Peer vaping behavior may be associated with adolescents’ capacity to quit vaped nicotine. Interventions that directly address peer network influences may enhance vaping cessation outcomes.
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Journal: JMIR Form Research, 2026, doi: 10.2196/99947
Authors: Ian David Aronson, Robert Quiles, Anthony Cramer, Chunki Fong, & Alex S. Bennett
Abstract:
Background: Popular discourse often frames prescription stimulants Ritalin and Adderall as drugs for teens and emerging adults with greater financial resources (eg, students or young professionals), while illicit stimulants such as crack or methamphetamine are often considered drugs for older adults with lower incomes. Crack and methamphetamine are also frequently used in combination with opioids to offset the sedating effects of adulterants such as fentanyl and xylazine in the unregulated drug supply. This combination of stimulant and opioid use creates additional overdose risks and may require new public health approaches. Our team posited that creating effective messages to protect against overdose in the context of stimulant use entailed first developing a better understanding of which stimulants people are using in combination with opioids.
Objective: While conducting formative research to develop a new intervention, our team sought to examine prescription stimulant use among participants, including middle-aged, lower-income, and homeless people. This entailed first ascertaining the prevalence of Ritalin and Adderall use among participants, and then asking people why they used them. We also sought to implement a novel AI-assisted coding methodology and to write up the steps we took as a replicable model that other research teams could readily use to facilitate their own data analysis.
Methods: We collected substance use screenings during 3 waves of data collection in 2025 (N=102 participants). In early 2026, we conducted 16 qualitative interviews with people who reported using Ritalin or Adderall. We then conducted mixed methods analyses to examine reported substance use, including the use of opioids and Ritalin or Adderall in combination, as well as potential relationships between using opioids with prescription stimulants and reporting a desire to stop using drugs. After conducting the interviews, we implemented a new hybrid methodology using AI tools to code interview transcripts and generate detailed reports accompanied by supporting quotes.
Results: Participants described using Ritalin or Adderall to manage negative effects of increasingly powerful opioids, including oversedation and withdrawal symptoms. A subset of participants who reported using both Ritalin or Adderall and opioids were 3.5 times more likely to agree or strongly agree with the statement “I want to stop using drugs but I need help to do that” compared to those who did not report using these substances in combination (19/22, 86.4% vs 18/28, 64.3%; odds ratio 3.52, 95% CI 0.83-14.89; P=.09). Although not statistically significant, this difference may prove practically significant and merits further study.
Conclusions: The use of prescription stimulants appears to be increasingly common among new populations of people who use opioids, including those who report very low incomes and even homelessness. Additional research is warranted to examine how this type of polysubstance use may require different types of prevention strategies.
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