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Record W4407804578 · doi:10.2196/60527

Enhancing Text Message Support With Media Literacy and Financial Incentives for Vaping Cessation in Young Adults: Protocol for a Pilot Randomized Controlled Trial

2025· article· en· W4407804578 on OpenAlexvenueno aff
Tzeyu L. Michaud, Troy B Puga, Rex Archer, Elijah Theye, Cleo Zagurski, Paul A. Estabrooks, Hongying Dai

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Cancer Institute
KeywordsRandomized controlled trialProtocol (science)Financial literacyText messageIncentiveSmoking cessationHealth literacyText messagingMedicineMedical educationPsychologyComputer scienceAlternative medicineFinanceBusinessInternet privacyHealth carePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The persistent high prevalence of e-cigarette use among young adults remains a significant public health concern, with limited evidence and guidance on effective vaping cessation programs targeting this population. OBJECTIVE: This study aims to outline the study design and protocol of a pilot randomized controlled trial aimed at investigating feasibility and assessing whether media literacy education or financial incentives enhance the effectiveness of evidence-based text message support in promoting vaping abstinence among young adult e-cigarette users. METHODS: The pilot study uses a 4-arm (1:1:1:1) randomized controlled trial design to assess the potential impact of different combinations of media literacy education, financial incentives, and text message support on vaping abstinence over a 3-month period. The first month serves as a preparatory phase for quitting, followed by 2 months focused on abstinence. A total of 80 individuals, aged 19-29 years, who have used e-cigarettes within the past 30 days, have internet access, and express interest in quitting vaping within the next 30 days, will be enrolled. Eligible individuals will be randomized into one of the four study groups: (1) Text Message, (2) Media Literacy, (3) Financial Incentive, and (4) Combined. All participants, regardless of group assignment, will receive text message support. Participants will be followed for 12 weeks, with abstinence status assessed at week 12, as well as during remote check-ins at weeks 6, 8, and 10. Feasibility measures include recruitment rate, reach, engagement, and retention. Other outcomes of interest include self-reported 7-day abstinence and changes in nicotine dependence and media literacy scores. Exit interviews will be conducted with those who complete the study to explore facilitators of and barriers to participation and engagement in vaping cessation, which will inform future program refinement and uptake. RESULTS: Recruitment for the study commenced in December 2023 and concluded in August 2024. A total of 40 participants were randomized into these groups: 9 for Text Message, 11 for Media Literacy, 10 for Financial Incentive, and 10 for the Combined group. The final assessment was completed in November 2024, and analyses are currently ongoing. CONCLUSIONS: The findings from this trial could provide valuable insights into the design and uptake of vaping cessation strategies among the young adult population. TRIAL REGISTRATION: ClinicalTrials.gov NCT05586308; https://clinicaltrials.gov/study/NCT05586308. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/60527.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.076
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.035
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0030.003
Science and technology studies0.0040.003
Scholarly communication0.0040.004
Open science0.0040.003
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0760.012

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.

Opus teacher head0.073
GPT teacher head0.495
Teacher spread0.422 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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