Strengthening Social Capital to Address Isolation and Loneliness in Long-Term Care Facilities During the COVID-19 Pandemic: Systematic Review of Research on Information and Communication Technologies
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic has disproportionately and severely affected older adults, namely those living in long-term care facilities (LTCFs). Aside from experiencing high mortality rates, survivors were critically concerned by social isolation and loneliness (SIL). To address this serious public health concern and stay connected with LTCF residents, information and communication technology (ICT) platforms (eg, video calls) were used as an alternative to maintaining social interactions amid the visiting restriction policy. OBJECTIVE: This paper aimed to synthesize the effects of ICT-related communication interventions using SMS text messaging or chat, video, voice mail, or photo to address SIL in LTCF residents during the COVID-19 pandemic. METHODS: In total, 2793 references published in English and French in 2019 and onward were obtained from 10 relevant databases: PsycINFO-Ovid, Ovid-MEDLINE, CINAHL-EBSCO, Cochrane Library, Web of Science, Scopus, DirectScience, Communication & Mass Media Complete, IEEE Xplore, and ACM Digital Library. A 2-person screening approach was used, and the studies were screened independently and blindly. A narrative synthesis was performed to interpret the results of the included studies, and their quality was appraised. RESULTS: In total, 4 studies were included in the review. ICT-related applications were used to ensure connectedness to address SIL. ICT interventions consisted mainly of videoconferencing, intergroup video call sessions between residents, and chatting (SMS text messages and phone calls). Roughly 3 classes of mediating ICT tools were used: video calls using software applications (eg, Skype); robot systems embedding video telephones; and ordinary telecommunication such as telephone, internet, social media platforms, and videoconferencing. This review has included the role of humanoid robots in LTCFs as an innovation avenue because of their multipurpose use (eg, communication tools and remotely operable). CONCLUSIONS: Remote social capitalization through ICT applications has become an avenue to reduce SIL among LTCF residents. This review examined a social connection approach that will remain relevant and even be fostered after the COVID-19 pandemic. As families remain the main stakeholders of LTCFs, this study's findings could inform policy makers and frontline managers to better shape programs and initiatives to prevent or reduce SIL in LTCFs. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/36269.
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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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 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 ».