Adapting and Evaluating a Brief Advice Tobacco Cessation Intervention in High-reach, Low-resource Settings in India: Protocol for a Cluster Randomized Controlled Trial
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,038 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,007 | 0,004 |
| Méta-épidémiologie (sens large) | 0,016 | 0,009 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,004 | 0,005 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,008 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,078 | 0,012 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».