Acceptability of the LetSync App Wireframes for an mHealth Intervention to Improve HIV Care Engagement and Treatment Among Black Partnered Sexual Minority Men: Findings from In-Depth Qualitative Interviews
Notice bibliographique
Résumé
BACKGROUND: HIV disparities continue to be a significant challenge affecting Black sexual minority men in the United States. Inadequate engagement and retention of patients in HIV care has been associated with poor health outcomes. Interventions to improve sustained commitment to HIV care are needed. Mobile health interventions can help facilitate access to and use of HIV health services, particularly among individuals at risk for disengaging with care. OBJECTIVE: We designed the LetSync app wireframes for a mobile health intervention using a couple-centered design approach to improve HIV engagement and treatment among Black sexual minority men and their partners. The objective of this study was to gauge future app user interest and elicit feedback to improve the design, development, and usability of the LetSync app. METHODS: We conducted in-depth interviews with 24 Black sexual minority men to assess the acceptability of the LetSync app wireframes between May 2020 and January 2021. Participants reviewed the LetSync app wireframes and provided feedback regarding perceived usefulness and interest in future app use and suggestions for improvement. RESULTS: Participants indicated interest in the future LetSync app and noted that the wireframes' features were acceptable and usable. In our study, the future LetSync app was frequently referred to as a potential resource that could help facilitate users' engagement in HIV care through the following mechanisms: enable scheduling of appointments and timely reminders for clinic visits; help improve HIV medication adherence; encourage and motivate participants to ask questions to their health care provider and stay engaged in conversations during clinic visits; facilitate effective communication by assisting couples with planning, coordination, and management of daily routines; help participants understand their partner's health needs, including access to and use of health care services; and facilitate participants' ability to improve their relationship skills, partner support, and self-efficacy in managing conflict. In addition to near-universal interest in potential daily app use, study participants indicted that they would recommend the LetSync app to other family members, friends, and people in their social networks who are living with HIV. CONCLUSIONS: Our findings revealed considerable interest in future app use for HIV care management, which could possibly increase the chance of the LetSync app being successfully adopted by Black sexual minority men in couples. Owing to its interactive and couple-centered approach, the LetSync app could help improve communication between Black sexual minority men and their partners and health providers. In addition, the LetSync app could provide an acceptable modality for these men to receive support in accessing HIV care services.
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 | 0,012 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».