Involving Older People With Frailty or Impairment in the Design Process of Digital Health Technologies to Enable Aging in Place: Scoping Review
Notice bibliographique
Résumé
BACKGROUND: With an increase in life expectancy globally, the focus on digital health technologies that can enhance physical and mental health among older people with frailty and impairment has increased. Similarly, research interest in how digital health technology can promote well-being and self-management of health in older age has increased, including an increased focus on methods for designing digital health technologies that meet the various medical, psychological, and social needs of older population. Despite the increased focus, there remains a necessity to further understand the needs of this population group to ensure uptake and to avoid introduction of additional challenges when introducing technologies, for example, because of poor technological design. The scope is limited to digital health technologies meant to enable older people with frailty and impairment to age in place. OBJECTIVE: In this study, we aimed to explore how older people with frailty and impairment are involved in various parts of the design processes of digital health technologies and identify gaps or neglected steps in a user-involving design process. This included a focus on recruitment strategies, contributions, and methods used to address the perspectives, needs, and desires of older people with frailty and impairment in the development of digital health technologies. METHODS: A scoping review was conducted in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) reporting from February 2021 to April 2021. Literature searches were conducted in PubMed, Scopus, Embase, and IEEE using a search string covering the concepts of health technology, older people, frailty and impairment, user-centered design, and self-management. RESULTS: In total, 1891 studies were imported for screening from the initial search. A total of 22 studies were included in this review after full-text screening and manual search. Invitation through partners was the most reported recruitment strategy to involve older people with frailty and impairment in the design process of digital health technologies. Furthermore, they were commonly involved in the final evaluation of the development process. Three main gaps identified were the use of outreach approaches to recruit older people with frailty and impairment in the design process of digital health technologies, description of the value of involvement and outcome of the contribution of participants, and knowledge regarding involvement in all parts of the design process. CONCLUSIONS: Although there is literature on methods for involving older people with frailty and impairment in the design of digital health technology, there is little methodological dialogue on the nuances of how different methods for involvement relate to and shape the outcome of the development process.
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 | 0,035 | 0,138 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,007 |
| Bibliométrie | 0,016 | 0,014 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,005 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».