A Mixed Reality Cognitive Orthosis to Support Older Adults in Achieving Their Daily Living Activities: Focus Group Study With Clinical Experts
Notice bibliographique
Résumé
BACKGROUND: Mixed reality is an emerging technology that allows us to blend virtual objects into the actual user's environment. This can be realized using head-mounted displays. Many recent studies have suggested the possibility of using this technology to support cognition in people with neurodegenerative disorders (NDs). However, most studies have explored improvements in cognition rather than in independence and safety during the accomplishment of daily living activities. Therefore, it is crucial to document the possibility of using mixed reality to support the independence of older adults in their daily lives. OBJECTIVE: This study is part of a larger user-centered study of a cognitive orthosis using pure mixed reality to support the independence of people living with NDs. This study aimed to explore (the difficulties encountered by older adults with NDs in their daily life to ensure that pure mixed reality meets their needs, (the most effective interventions with this population to determine what types of assistance should be provided by pure mixed reality technology, how the pure mixed reality technology should provide assistance to promote aging in place, and the main facilitators of and barriers to the use of this technology. METHODS: We conducted a descriptive, qualitative study. A total of 5 focus groups were completed with occupational therapists who had expertise in the disease and its functional impacts (N=29) to gather information. Each focus group met once for a 1-hour period. All sessions were held over a 3-month period. A semistructured interview guide was used. All group interviews were audiotaped with the consent of each participant to facilitate the data analysis. We conducted inductive qualitative analysis in four stages using a thematic analysis approach: full transcription of the audio recordings, first-order coding of the transcribed data, second-order coding from the first-order code list, and data reduction and matrix development. RESULTS: The results suggested that the main difficulties encountered by this population were in remembering to complete tasks, initiating the tasks, and planning the tasks. Several interventions are used to improve the independence of this population, such as prevention, simplification or facilitation, adaptation, and compensation. The use of pure mixed reality in older adults with NDs to promote independence and safety at home is promising and may respond to several clinical functions identified by the participants. Finally, pure mixed reality has good potential for use in this population and involves certain facilitators and obstacles, such as resources, technical aspects, and social considerations. CONCLUSIONS: The cognitive orthosis that will be developed in light of this study will act as a proof of concept for the possibility of supporting people with NDs using pure mixed reality.
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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 | 0,007 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 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 ».