Home-Based Digital Technologies to Support Aging-in-Place for Rural African American People With Alzheimer Disease and Their Care Partners: Protocol for a Mixed Methods Feasibility Study
Notice bibliographique
Résumé
BACKGROUND: Rural, low-income African American people have the highest Alzheimer disease and related dementia (ADRD) incidence and prevalence rates but have the least access to formal dementia care. To support individuals living with ADRD, growing evidence suggests that remote monitoring technologies can augment existing care by facilitating the completion of activities of daily living (ADLs) and maintaining communication between individuals living with ADRD and their care partners. Despite the success of remote technologies, no studies have investigated the usability, acceptability, and feasibility of these technologies among rural, lower-income African American people living with ADRD and their care partners. Understanding the potential impact of remote monitoring technology on this population can guide the development of tailored aging-in-place interventions. OBJECTIVE: Among rural, low-income African American people living with ADRD and their care partners, our study, "Revolutionizing Empowerment of African Americans' Cognitive Health Through Innovative Technology," aims (1) to identify barriers to aging-in-place, current technology use behaviors, and attitudes toward remote monitoring technologies and (2) to examine the usability, acceptability, and feasibility of deploying a remote monitoring system in the homes of this population for supporting ADLs. METHODS: In total, 10 low-income African American people living with ADRD and their care partners will be recruited from rural cities in South Carolina. Participants will complete a short web-based survey to collect demographics and their knowledge, experience, and comfort with using internet-connected devices, followed by 45- to 60-minute in-depth interviews (objective 1). In phase 2 (ie, objective 2), 10 additional pairs of participants will be recruited to use a remote monitoring system for 18 months. "Weekly Health Update" surveys will measure changes in health and time spent at home. In-depth interviews will be used at 18 months to examine the usability and acceptability of the system. Feasibility will be determined by the percentage of days data are collected across all sensors. RESULTS: This study was approved by the institutional review board in June 2024. Recruitment for objective 1 began in January 2025. To date, 5 persons living with ADRD and their care partners have been recruited, surveyed, and interviewed about their challenges to aging with ADRD or caring for someone with the disease, technology use, and openness to remote monitoring technology. Recruitment for objective 2 is anticipated to begin in fall 2025, and data collection will conclude by May 2027. Results for objectives 1 and 2 are expected to be published in fall 2026 and winter 2027, respectively. CONCLUSIONS: Findings from the Revolutionizing Empowerment of African Americans' Cognitive Health Through Innovative Technology study will contribute to the refinement of the Collaborative Aging Research Using Technology platform, a multisensor remote monitoring system to support the ADLs for low-income, rural-dwelling African American people living with ADRD. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/78623.
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 | 0,038 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,003 | 0,004 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,007 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,058 | 0,011 |
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 ».