Comparison of a User-Centered Design, Self-Management App to Existing mHealth Apps for Persons Living With HIV
Notice bibliographique
Résumé
BACKGROUND: There is preliminary evidence that mobile health (mHealth) apps are feasible, attractive, and an effective platform for the creation of self-management tools for persons living with HIV (PLWH). As a foundation for the current study, we conducted formative research using focus groups, participatory design sessions, and usability evaluation methods to inform the development of a health management app for PLWH. The formative research resulted in identification of the following functional requirements of a mHealth app for self-management: (1) communication between providers and peers, (2) medication reminders, (3) medication log, (4) lab reports, (5) pharmacy information, (6) nutrition and fitness, (7) resources (eg, social services, substance use, video testimonials), (8) settings, and (9) search function. OBJECTIVE: The purpose of this study was to conduct an ecological review of the existing apps for PLWH and to compare the functionality of existing apps with the app specifications identified in our formative work. METHODS: We searched two mobile app stores (Google Play and iTunes) and found a total of 5606 apps. We reviewed the apps, narrowed our search terms, and found a total of 112 apps. Of these, we excluded 97 (86.6%) apps that were either not in English (10/112, 8.9%), not HIV focused (32/112, 28.9%), or focused only on HIV prevention (2/112, 7.8%); targeted health care providers (26/112, 23.2%); provided information only on conference schedules and events (7/112, 6.3%), fundraisers (7/112, 6.3%), specific clinics (7/112, 6.3%), international or narrow local resources (3/112, 2.7%); or were identified in the first search but were no longer on the market at the next review (4/112, 3.6%). The 15 apps meeting inclusion criteria were then evaluated for inclusion of the nine functionalities identified in our earlier work. RESULTS: Of the 15 apps that we included in our final review, none had all of the functionalities that were identified in our formative work. The apps that we identified included the following functionalities: communication with providers and/or peers (4/15, 27%), medication reminders (6/15, 40%), medication logs (7/15, 47%), lab reports (5/15, 33%), pharmacy information (4/15, 27%), resources (7/15, 47%), settings (11/15, 73%), and search function (6/15, 40%). No apps included nutrition or fitness information. CONCLUSIONS: Currently, there are only a small number of apps that have been designed for PLWH to manage their health. Of the apps that are currently available, none have all of the desired functionalities identified by PLWH and experts in our formative research. Findings from this work elucidate the need to develop and evaluate mobile apps that meet PLWH's desired functional specifications.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».