An Avatar-Led Web-Based and SMS Text Message Smoking Cessation Program for Socioeconomically Disadvantaged Veterans: Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Despite the declining prevalence of cigarette smoking in the United States, socioeconomically disadvantaged veterans receiving care from the Veterans Health Administration have a high prevalence of smoking. Currently, available treatment options for these veterans focus on tobacco users who are ready to quit and have limited reach. Consequently, there is a great need for accessible, effective smoking cessation interventions for veterans at all levels of readiness to quit smoking. OBJECTIVE: To address these needs, we developed Vet Flexiquit, a web-based Acceptance and Commitment Therapy program for veterans, and evaluated its acceptability (primary aim), efficacy, and impact on theory-based change processes relative to the National Cancer Institute's SmokefreeVET program in a pilot randomized controlled trial. METHODS: Participants (N=49) were randomized 1:1 to receive either the Vet Flexiquit (n=25) or SmokefreeVET (n=24) web program. Both groups received SMS text messages as part of the intervention for 6 weeks. Both interventions are fully automated and self-guided. Primary outcome data were collected at 3 months after the randomization. Self-reported smoking abstinence was biochemically verified using saliva cotinine. Multivariable logistic regression, negative binomial regression, and linear regression models were used to evaluate the association between the treatment arm and outcomes of interest. RESULTS: Acceptability, as measured by overall treatment satisfaction, was high and similar across treatment arms: 100% (17/17) for Vet Flexiquit and 95% (18/19) for SmokefreeVET. Acceptability, as measured by utilization, was more modest (log-ins: M=3.7 for Vet Flexiquit and M=3.2 for SmokefreeVET). There were no statistically significant differences between treatment arms for any acceptability measures. Similarly, there were no statistically significant differences between treatment arms in the secondary outcomes of smoking cessation or change in Acceptance and Commitment Therapy's theory-based processes. In open-ended survey responses, some veterans in both treatment arms expressed interest in having support from a professional or peer to enhance their experience, as well as an expanded SMS text messaging program. CONCLUSIONS: Both programs had high ratings of acceptability, limited utilization, and a similar impact on cessation and cessation processes. Taken together with the qualitative data suggesting that additional support may enhance participants' experience of both programs, these preliminary findings suggest that the programs may have similar outcomes among veterans who are looking for a digital cessation treatment option and that integrating provider or peer support and enhancing the SMS text messaging program holds promise as a means of boosting engagement and outcomes for both programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04502524; https://clinicaltrials.gov/ct2/show/NCT04502524.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".