Adapting and Evaluating a Brief Advice Tobacco Cessation Intervention in High-reach, Low-resource Settings in India: Protocol for a Cluster Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: About 1.35 million deaths annually are attributed to tobacco use in India. The main challenge, given the magnitude of tobacco use and limited resources, is delivering cessation support at scale, low cost, and through a coordinated cross-system effort; one such example being brief advice interventions. However, highly credentialed staff to identify and counsel tobacco users are scarce. Task-shifting is an important opportunity for scaling these interventions. OBJECTIVE: The LifeFirst SWASTH (Supporting Wellbeing among Adults by Stopping Tobacco Habit) program-adapted from the LifeFirst program (developed by the Narotam Sekhsaria Foundation, Mumbai, India)-is a tobacco cessation program focusing on lower-socioeconomic status patients in Mumbai receiving private health care. This parallel-arm, cluster randomized controlled trial investigates whether the LifeFirst SWASTH program increases tobacco cessation rates in low-resource, high-reach health care settings in Mumbai. METHODS: This study will target tuberculosis-specific nongovernmental organizations (NGOs), dental clinics, and NGOs implementing general health programs serving lower-socioeconomic status patients. Intervention arm patients will receive a pamphlet explaining tobacco's harmful effects. Practitioners will be trained to deliver brief cessation advice, and interested patients will be referred to a Narotam Sekhsaria Foundation counselor for free telephone counseling for 6 months. Control arm patients will receive the same pamphlet but not brief advice or counseling. Practitioners will have a customized mobile app to facilitate intervention delivery. Practitioners will also have access to a peer network through WhatsApp. The primary outcome is a 30-day point prevalence abstinence from tobacco. Secondary outcomes for patients and practitioners relate to intervention implementation. RESULTS: The study was funded in June 2020. Due to the COVID-19 pandemic, the study experienced some delays, and practitioner recruitment commenced in November 2023. As of July 2024, all practitioners have been recruited, and practitioner recruitment and training are complete. Furthermore, 36% (1687/4688) of patients have been recruited. CONCLUSIONS: It is hypothesized that those patients who participated in the LifeFirst SWASTH program will be more likely to have been abstinent from tobacco for 30 consecutive days by the end of 6 months or at least decreased their tobacco use. LifeFirst SWASTH, if found to be effective in terms of cessation outcomes and implementation, has the potential to be scaled to other settings in India and other low- and middle-income countries. The study will be conducted in low-resource settings and will reach many patients, which will increase the impact if scaled. It will use task-shifting and an app that can be tailored to different settings, also enabling scalability. Findings will build the literature for translating evidence-based interventions from high-income countries to low- and middle-income countries and from high- to low-resource settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT05234983; https://clinicaltrials.gov/study/NCT05234983. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57236.
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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 | 0.038 | 0.033 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.009 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.078 | 0.012 |
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.
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".