A Novel mHealth App for Smokers Living With HIV Who Are Ambivalent About Quitting Smoking: Formative Research and Randomized Feasibility Study
Notice bibliographique
Résumé
BACKGROUND: More people who smoke and are living with HIV now die from tobacco-related diseases than HIV itself. Most people are ambivalent about quitting smoking and want to quit someday but not yet. Scalable, effective interventions are needed to motivate and support smoking cessation among people ambivalent about quitting smoking (PAQS) who are living with HIV. OBJECTIVE: This study aims to develop an app-based intervention for PAQS who are living with HIV and assess its feasibility, acceptability, and potential impact. Results of this study will inform plans for future research and development. METHODS: In phase 1, PAQS living with HIV (n=8) participated in user-centered design interviews to inform the final intervention app design and recruitment plan for a subsequent randomized pilot study. In phase 2, PAQS living with HIV were randomized to either a standard care control app or a similar experimental app with additional content tailored for PAQS and those with HIV. Participants were followed for 3 months. Feasibility focused on recruitment, retention, and participants' willingness to install the app. The study was not powered for statistical significance. Indices of acceptability (satisfaction and use) and impact (smoking behavior change and treatment uptake) were assessed via automated data and self-report among those who installed and used the app (n=19). RESULTS: Recruitment for both study phases was a challenge, particularly via web-based and social media platforms. Enrollment success was greater among people living with HIV recruited from a health care provider and research registry. Once enrolled, retention for the phase 2 randomized study was good; 74% (14/19) of the participants completed the 3-month follow-up. Phase 1 findings suggested that PAQS living with HIV were receptive to using an app-based intervention to help them decide whether, when, and how to stop smoking, despite not being ready to quit smoking. Phase 2 findings further supported this conclusion based on feedback from people who agreed to use an app, but group differences were observed. Indices of acceptability favored the experimental arm, including a descriptively higher mean number of sessions and utilization badges. Similarly, indices of potential impact were descriptively higher in the experimental arm (proportion reducing smoking, making a quit attempt, or calling free tobacco quitline). No participants in either arm quit smoking at the 3-month follow-up. CONCLUSIONS: On the basis of this formative work, PAQS living with HIV may be receptive to using a mobile health-based app intervention to help them decide whether, when, or how to stop using tobacco. Indices of acceptability and impact indicate that additional research and development are warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT05339659; https://clinicaltrials.gov/study/NCT05339659.
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 | 0,020 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 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 ».