Proactive and Ongoing Analysis and Management of Ethical Concerns in the Development, Evaluation, and Implementation of Smart Homes for Older Adults With Frailty
Notice bibliographique
Résumé
Successful adoption and sustained use of smart home technology can support the aging in place of older adults with frailty. However, the expansion of this technology has been limited, particularly by a lack of ethical considerations surrounding its application. This can ultimately prevent older adults and members of their support ecosystems from benefiting from the technology. This paper has 2 aims in the effort to facilitate adoption and sustained use: to assert that proactive and ongoing analysis and management of ethical concerns are crucial to the successful development, evaluation, and implementation of smart homes for older adults with frailty and to present recommendations to create a framework, resources, and tools to manage ethical concerns with the collaboration of older adults; members of their support ecosystems; and the research, technical development, clinical, and industry communities. To support our assertion, we reviewed intersecting concepts from bioethics, specifically principlism and ethics of care, and from technology ethics that are salient to smart homes in the management of frailty in older adults. We focused on 6 conceptual domains that can lead to ethical tensions and of which proper analysis is essential: privacy and security, individual and relational autonomy, informed consent and supported decision-making, social inclusion and isolation, stigma and discrimination, and equity of access. To facilitate the proactive and ongoing analysis and management of ethical concerns, we recommended collaboration to develop a framework with 4 proposed elements: a set of conceptual domains as discussed in this paper, along with a tool consisting of reflective questions to guide ethical deliberation throughout the project phases; resources comprising strategies and guidance for the planning and reporting of ethical analysis throughout the project phases; training resources to support leadership, literacy, and competency in project teams for the analysis and management of ethical concerns; and training resources for older adults with frailty, their support ecosystems, and the public to support their awareness and participation in teams and ethical analysis processes. Older adults with frailty require nuanced consideration when incorporating technology into their care because of their complex health and social status and vulnerability. Smart homes may have a greater likelihood of accommodating users and their contexts with committed and comprehensive analysis, anticipation, and management of ethical concerns that reflect the unique circumstances of these users. Smart home technology may then achieve its desired individual, societal, and economic outcomes and serve as a solution to support health; well-being; and responsible, high-quality care.
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 | 0,442 | 0,378 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,018 | 0,028 |
| Communication savante | 0,029 | 0,026 |
| Science ouverte | 0,005 | 0,028 |
| Intégrité de la recherche | 0,010 | 0,019 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».