Long-term care home residents’ experiences with socially assistive technologies and the effectiveness of these technologies: a mixed methods systematic review
Notice bibliographique
Résumé
OBJECTIVE: The objectives of this review were to determine the effectiveness of socially assistive technologies for improving depression, loneliness, and social interaction among residents of long-term care (LTC) homes, and to explore the experiences of residents of LTC homes with socially assistive technologies. INTRODUCTION: Globally, the number of older adults (≥ 65 years) and the demand for LTC services are expected to increase over the next 30 years. Individuals within this population are at increased risk of experiencing depression, loneliness, and social isolation. The exploration of the extent to which socially assistive technologies may aid in improving loneliness and depression while supporting social interactions is essential to supporting a sustainable LTC sector. INCLUSION CRITERIA: This mixed methods systematic review included studies on the experiences of older adults in LTC homes using socially assistive technologies, as well as studies on the effectiveness of these technologies for improving depression, loneliness, and social interaction. Older adults were defined as people 65 years of age and older. We considered studies examining socially assistive technologies, such as computers, smart phones, tablets, and associated applications. METHODS: A JBI mixed methods convergent, segregated approach was used. CINAHL (EBSCOhost), MEDLINE (Ovid), Embase, APA PsycINFO (EBSCOhost), and Scopus databases were searched on January 18, 2022, to identify published studies. The search for unpublished studies and gray literature included ProQuest Dissertations and Theses Global, Open Access Theses and Dissertations, Google, and the websites of professional organizations associated with LTC. No language or geographical restrictions were placed on the search. Titles, abstracts, and full texts of included studies were screened by 2 reviewers independently. Included studies underwent quality appraisal and data extraction. Quantitative and qualitative data findings were analyzed separately and then integrated. Where possible, quantitative data were synthesized using comparative meta-analyses with a fixed-effects model. RESULTS: From 12,536 records identified through the search, 14 studies were included. Quantitative (n=8), mixed methods (n=3), and qualitative (n=3) approaches were used in the included studies, with half (n=7) using quasi-experimental designs. All studies received moderate to high-quality appraisal scores. Comparative meta-analyses for depression and loneliness scores did not find any significant differences, and narrative findings were mixed. Qualitative meta-aggregation identified 1 synthesized finding (Matching technology functionality to user for enhanced well-being) derived from 2 categories (Enhanced sense of well-being, and Mismatch between technology and resident ability). CONCLUSIONS: Residents' experiences with socially assistive technologies, such as videoconferencing, encourage a sense of well-being, although quantitative findings related to depression and loneliness reported mixed impact. Residents experienced physical and cognitive challenges in learning to use the technology and required assistance. Future work should consider the unique needs of older adults and LTC home residents in the design and use of socially assistive technologies. REVIEW REGISTRATION: PROSPERO CRD42021279015.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,013 | 0,064 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,009 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,004 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».