Quality of an Assistive Technology Web Application for Primary Care Physicians Serving Older Adults: Concurrent Mixed Methods Study
Notice bibliographique
Résumé
BACKGROUND: Older Latinos living in Puerto Rico experience significantly higher rates of functional disabilities (FDs; 1093/87,300, 27.8%) compared to older adults in the continental United States (755,685/57,913,200, 13.3%). While assistive technologies (ATs) can improve daily function and support aging in place, primary care physicians (PCPs), who are essential in addressing FDs resulting from chronic diseases, often lack knowledge about AT devices and services. The Mi Guía de Asistencia Tecnológica (MGAT; My Assistive Technology Guide) web application was empirically developed to address this gap by providing comprehensive information and videos about AT devices for older adults with functional difficulties in daily living activities. OBJECTIVE: This study aimed to assess the quality of MGAT among PCPs and describe their experiences using the app to increase access to AT for older Latinos. METHODS: A total of 10 PCPs participated in this usability project, receiving MGAT training before a 30-day implementation period. A concurrent mixed methods design was used, combining quantitative data from the User Version of the Mobile User Application Rating Scale (uMARS) and qualitative insights from semistructured individual interviews. The analysis included descriptive statistics and a directed content analysis. RESULTS: The MGAT received high overall objective quality ratings on uMARS (mean 4.06, SD 1.05). Among subdomains, information scored highest (mean 4.60, SD 0.51), followed by functionality (mean 4.20, SD 0.63), aesthetics (mean 4.00, SD 0.82), and engagement, which scored lowest (mean 3.34, SD 1.51). Subjective quality ratings were also favorable, with a mean score of 3.93 (SD 1.19), with recommending the app to others scoring the highest (mean 4.70, SD 0.48) and willingness to pay for the app the lowest (mean 3.11, SD 1.90). Perceived impact received the highest score across all domains (mean 4.82, SD 0.39), with behavior change scoring the highest (mean 5.82, SD 0) and awareness scoring the lowest (mean 4.60, SD 0.52). Qualitative findings revealed that PCPs found MGAT entertaining and interesting, but wanted more customization and interactive features to boost engagement. They appreciated its ease of use and navigation, but noted the need for a stable internet connection. While the design was visually appealing, improvements to the color scheme and element sizes were suggested. Participants valued the high-quality information relevant to older adults but desired more specialized content for medical professionals. They were likely to recommend MGAT, though cost opinions varied. Most importantly, MGAT increased awareness of patient needs, expanded AT knowledge, and positively influenced intentions to recommend AT, ultimately facilitating patient access to AT. CONCLUSIONS: The high-quality and usefulness ratings suggest MGAT could be an effective tool for PCPs in managing older adults' FDs. Future research should evaluate the effectiveness of MGAT in managing FDs among older adults.
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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 | 0,019 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».