Engaging Aging Individuals in the Design of Technologies and Services to Support Health and Well-Being: Constructivist Grounded Theory Study
Notice bibliographique
Résumé
BACKGROUND: Changes noted within the aging population are physical, cognitive, as well as emotional. Social isolation and loneliness are also serious problems that the aging population may encounter. As technology and apps become more accessible, many basic services, such as those offered by social services, well-being organizations, and health care institutions, have invested in the development of supportive devices, services, and Web-based interactions. Despite the perceived benefits that these devices and services offer, many aging individuals choose not to engage, or engage in a limited manner. To explore this phenomenon, we developed a theory to describe the condition for engagement. OBJECTIVE: The main objective of this study was to understand the perceptions of an aging South African population regarding Web-based services and technologies that could support aging in place (AiP). Although the concept of AiP speaks to a great number of everyday activities, this paper explores aspects of health and well-being as being central to AiP. METHODS: The study used a grounded theory (GT) methodology, relying on an iterative and simultaneous process of data collection, coding, category development, and data comparisons. Data were collected through qualitative methods, including interviews (13 participants aged between 64 and 85 years), 2 participatory workshops (15 participants), and observations. The study focused on Charmaz's approach to constructivist GT, which puts forward the premise that theory or knowledge cannot take shape in a purely objective manner. Instead, theory is constructed through the interaction of the researcher and research participant. Coding and data analysis were supported with ATLAS.ti (ATLAS.ti Scientific Software Development GmbH). RESULTS: The study resulted in a substantive theory exploring the process of interaction and engaging factors through user insights and experiences. The emerging design theory, Ageing User Decision-Driven Engagement (AUDDE), explored the elements that support engagement with technology and supportive apps, which could offer access to required health and wellness services. CONCLUSIONS: In AUDDE, the perceived value of the interaction is a crucial catalyst for engagement. Aging users continuously make meaning of their experiences, which affects their current and future actions.
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 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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».