Older Adults’ Engagement and Mood During Robot-Assisted Group Activities in Nursing Homes: Development and Observational Pilot Study
Notice bibliographique
Résumé
BACKGROUND: Promoting the well-being of older adults in an aging society requires new solutions. One resource might be the use of social robots for group activities that promote physical and cognitive stimulation. Engaging in a robot-assisted group activity may help in the slowdown of physical and cognitive decline in older adults. Currently, our knowledge is limited on whether older adults engage in group activities with humanlike social robots and whether they experience a positive affect while doing so. Both are necessary preconditions to achieve the intended effects of a group activity. OBJECTIVE: Our pilot study has 2 aims. First, we aimed to develop and pilot an observational coding scheme for robot-assisted group activities because self-report data on engagement and mood of nursing home residents are often difficult to obtain, and the existing observation instruments do have limitations. Second, we aimed to investigate older adults' engagement and mood during robot-assisted group activities in 4 different nursing care homes in the German-speaking part of Switzerland. METHODS: We developed an observation system, inspired by existing tools, for a structured observation of engagement and mood of older adults during a robot-assisted group activity. In this study, 85 older adult residents from 4 different care homes in Switzerland participated in 5 robot-assisted group activity sessions, and they were observed using our developed system. The data were collected in the form of video clips that were assessed by 2 raters regarding engagement (direction of gaze, posture as well as body expression, and activity) and mood (positive and negative affects). Both variables were rated on a 5-point rating scale. RESULTS: Our pilot study findings show that the engagement and mood of older adults can be assessed reliably by using the proposed observational coding scheme. Most participants actively engaged in robot-assisted group activities (mean 4.19, SD 0.47; median 4.0). The variables used to measure engagement were direction of gaze (mean 4.65, SD 0.49; median 5.0), posture and body expression (mean 4.03, SD 0.71; median 4.0), and activity (mean 3.90, SD 0.65; median 4.0). Further, we observed mainly positive affects in this group. Almost no negative affect was observed (mean 1.13, SD 0.20; median 1.0), while the positive affect (mean 3.22, SD 0.55; median 3.2) was high. CONCLUSIONS: The developed observational coding system can be used and further developed in future studies on robot-assisted group activities in the nursing home context and potentially in other settings. Additionally, our pilot study indicates that cognitive and physical stimulation of older adults can be promoted by social robots in a group setting. This finding encourages future technological development and improvement of social robots and points to the potential of observational research to systematically evaluate such developments.
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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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».