Testing the Acceptability and Feasibility of a Gender-Informed Smoking Cessation mHealth App for Women: Mixed Methods Approach
Notice bibliographique
Résumé
Background: Cigarette smoking is a leading cause of preventable morbidity and mortality worldwide. Women who smoke face greater health risks than men, including higher rates of cardiovascular disease and more pronounced declines in lung function. Despite this, women experience lower success rates with conventional smoking cessation treatments, due in part to unique sex- and gender-related factors influencing smoking behavior and barriers to quitting. Digital health tools, such as mobile health apps, offer a promising avenue for delivering accessible, tailored smoking cessation support to women. Objective: This study evaluated the acceptability and feasibility of the "My Change Plan-Women" (MCP-W) app, a gender-specific smoking cessation mobile health intervention co-designed with women who smoke, clinicians, and researchers, to address women's unique needs in smoking cessation. Methods: We conducted a single-group, prospective, sequential mixed methods study with 30 women who smoke in Ontario, Canada. Participants used the MCP-W app for 28 days. Acceptability was defined as ≥50% of participants endorsing "agree" or "strongly agree" to the statement "using the app is likely to help me make changes to my smoking habits." Feasibility was defined as ≥50% of participants using the app for 7 or more days during the trial period. Quantitative data on acceptability, smoking behavior, and motivation to quit were collected at baseline and follow-up via REDCap (Research Electronic Data Capture) surveys. App usage metrics were captured through Google Analytics. Semistructured interviews explored participants' experiences using the app and were thematically analyzed using the theoretical framework of acceptability. Results: At follow-up, 37% (11/30; 95% CI 21%-56%) of participants rated the MCP-W app as acceptable, falling below the predefined threshold (≥50%) and indicating that the intervention "needs further work." Feasibility criteria were met, with 60% (18/30) of participants using the app for 7 or more days. Notably, acceptability was higher among those who used the app for more than 14 days (7/11, 64%) compared with those with lower usage (4/19, 21%). Average daily cigarette consumption decreased from 16.4 to 14.6 cigarettes, and the number of participants reporting at least 1 smoke-free day in the previous week increased from 7% (2/27) to 22% (6/27). Qualitative findings revealed that women with higher motivation to quit found the app more helpful, particularly its behavior change tools (eg, cigarette tracking and identifying triggers) and gender-specific content. However, women facing stress, mental health challenges, or low readiness found it harder to engage. Participants suggested enhancements including customizable reminders, more interactive content, and live or artificial intelligence-based emotional support. Conclusions: The MCP-W app is a feasible intervention for delivering gender-specific smoking cessation support. However, its acceptability was limited to a third of users with high levels of motivation. Improvements to interactivity and support features may enhance its relevance and uptake among women with complex barriers to quitting.
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 | 0,043 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 ».