Feasibility and Engagement of a Peer-Driven Mobile Intervention for Adolescent E-Cigarette Cessation: Cluster Randomized Pilot Study
Bibliographic record
Abstract
Background: E-cigarette use remains prevalent among US adolescents, with many reporting daily use and high nicotine dependence. Few evidence-based mobile health interventions focus specifically on adolescents. Objective: This study aimed to evaluate the feasibility, engagement, and preliminary efficacy of vaper-to-vaper (V2V)-a multicomponent, peer-driven texting intervention supporting adolescent e-cigarette cessation. Methods: A cluster randomized pilot study was conducted in 5 Massachusetts high schools, with schools randomized to either the V2V texting intervention (n=3) or a control group (n=2) that received a link to the National Cancer Institute's Smokefree.gov Quit Vaping website. The V2V intervention included four components: (1) peer-written messages provided motivation, tips, and strategies to support adolescents in quitting vaping, sent daily in the first 30 days; (2) peer videos featuring adolescents sharing their experiences with e-cigarettes and motivations to quit, sent regularly as links aligned with related peer message topics; (3) peer coaches-university students aged younger than 22 years who had successfully quit vaping-trained to provide support, encouragement and answers to participants' questions through the texting platform; and (4) a fictional, gamified mystery story integrated into the texting platform to promote engagement. Each gamified message included a short story segment and a question, with the next segment unlocked after a response or automatically after 3 days. The intervention was mainly delivered over 30 days, but adolescents could message the peer coach over the 3 months. Eligible participants (grades 9-12, current e-cigarette users) were followed for 3 months. We assessed the feasibility of recruitment and retention (target: 80 participants, ≥85% retention), engagement with intervention components, and participant satisfaction. The secondary outcomes included improvements from baseline in confidence to quit, self-efficacy to resist vaping in specific high-risk situations, and fewer days vaped. E-cigarette cessation was biochemically verified using the Abbott iScreen cotinine test. Results: Seventy-one adolescents enrolled (intervention: 39/71, 55% ; control: 32/71, 45%), with a 96% follow-up rate at 3 months. Among intervention participants who responded to engagement items (N=37), high engagement-defined as self-reported use always, usually, or about half the time-was highest for peer messaging (n=29, 78%), followed by gamification (n=18, 49%), peer coaching (n=18, 49%), and peer video (n=13, 35%). The intervention group showed nonsignificant improvements in confidence to quit (n=17, 46%, vs n=9, 24%, moved from not at all, somewhat, or moderately confident to very or extremely confident) and in the number of days vaped in the past 30 days (-3.6 vs -2.9), while self-efficacy scores (adapted smoking self-efficacy scale range 12-60) were slightly lower compared to the control group (mean -0.21, SD 1.14, vs mean 0.06, SD 1.39). Cotinine-validated 7-day point prevalence abstinence was similar between groups (intervention: 21.6% vs control: 22.6%). Conclusions: The V2V intervention demonstrated feasibility and acceptability, with strong engagement and high satisfaction. Although differences between groups were not statistically significant, findings suggest that peer-driven mobile interventions are a promising approach to support adolescent e-cigarette cessation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".