Co-Designing a Conversational Agent with Frail and Impaired Older People to Enhance Ageing in Place through Self-management and Empowerment
Notice bibliographique
Résumé
Background: SMILE is a collaborative project between Norway, Denmark, The Netherlands, Canada, and Greece. The aim is to enable older people to live an independent and active life, irrespective of frailty, physical and/or cognitive impairments using eHealth solutions developed in co-creation with service users. The aim of the eHealth solution is to enable ageing in place, by combining prevention, prediction, communication, timely care, and assistance to help older people be engaged in their own condition and remain connected with their community. A user requirement specification and co-creation workshops was conducted in 2021 prior to the development of a Digital Care Facilitator (DCF) and a Conversational Agent (CA). Methods: The co-creation process entails initial interviews and observations conducted in Denmark, Norway, and the Netherlands, and 4 phases of co-creation workshops with service users. The initial interviews and observations provided an overview of the service users current practices e.g., daily activities and self-management of own health condition, their use of technology, and insight into requirements and needs for a future eHealth solution. Specifically, nine areas of interest were identified: 1) clinical condition, 2) physical activities, 3) sleep quality, 4) nutrition and hydration, 5) hygiene, 6) mental health, 7) social health, 8) air quality and 9) entertainment. The nine features were presented and discussed among 16 participants with COPD at phase 1 workshops in Denmark and Norway in May 2022. The features were presented to the participants in paper format, where partici-pants could ask questions and share thoughts. Then the participants were given four post-it’s on which they individually could write down the four features they found most valuable and that met their daily needs the most. Results: The phase 1 workshops helped narrow down nine areas of interest, to four specific features to include in the design of a conversational agent (CA), based on direct input from service users. The four features from the phase 1 workshops include: 1) health condition, 2) daily activity 3) social life, and 4) circadian rhythm. Input from the participants suggest that the valuable features of interest can enable an independent lifestyle and wellbeing without being disease or diagnose specific. Conclusion: The four features identified through input from the services user’s, formed the basis for development of a mock-up of the CA. The CA was presented at a phase 2 workshop, where input from user’s will be used to further develop and design the interface and the content of the CA and the DCF. The initial interviews and observations suggest that designing an interface for older frail people to ease information access and communication with care givers should not be specific to one condition but address how to support physiological, psychological, and social parameters that are meaningful for the age group. The results indicate that a focus on the four areas; health condition, daily activity, social life, and circadian rhythm, are relevant to ad-dress in future development of service design for older adults (65+), as they may contribute to increased empowerment, well-being and ageing in place.
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 | 0,005 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».