학술논문
Quality in care homes: How wearable devices and social network analysis might help.
Document Type
Academic Journal
Author
Thompson C; School of Healthcare, University of Leeds, Leeds, West Yorkshire, United Kingdom.; Gordon A; Division of Medical Sciences and Graduate Entry Medicine, University of Nottingham, Derby, Derbyshire, United Kingdom.; Khaliq K; School of Civil Engineering, University of Leeds, Leeds, West Yorkshire, United Kingdom.; Daffu-O'Reilly A; School of Healthcare, University of Leeds, Leeds, West Yorkshire, United Kingdom.; Willis T; Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, West Yorkshire, United Kingdom.; Noakes C; School of Civil Engineering, University of Leeds, Leeds, West Yorkshire, United Kingdom.; Spilsbury K; School of Healthcare, University of Leeds, Leeds, West Yorkshire, United Kingdom.
Source
Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Subject
Language
English
Abstract
Social network analysis can support quality improvement in care homes but traditional approaches to social network analysis are not always feasible in care homes. Recalling contacts and movements in a home is difficult for residents and staff and documentary and other sources of individual contacts can be unreliable. Bluetooth enabled wearable devices are a potential means of generating reliable, trustworthy, social network data in care home communities. In this paper, we explore the empirical, theoretical and real-world potential and difficulties in using Bluetooth enabled wearables with residents and staff in care homes for quality improvement. We demonstrate, for the first time, that a relatively simple system built around the Internet of Things, Bluetooth enabled wearables for residents and staff and passive location devices (the CONTACT intervention) can capture social networks and data in homes, enabling social network analysis, measures, statistics and visualisations. Unexpected variations in social network measures and patterns are surfaced, alongside "uncomfortable" information concerning staff time spent with residents. We show how technology might also help identify those most in need of social contact in a home. The possibilities of technology-enabled social network analysis must be balanced against the implementation-related challenges associated with introducing innovations in complex social systems such as care homes. Behavioural challenges notwithstanding, we argue that armed with social network information, care home staff could better tailor, plan and evaluate the effects of quality improvement with the sub-communities that make up a care home community.
Competing Interests: During the COVID-19 pandemic CN and AG were participants in the UK Scientific Advisory Group for Emergencies (SAGE), co-chaired the SAGE Environment and Modelling Sub-Group and was a member of the SAGE care home working group. CT has previously provided paid scientific advice to Microshare Ltd and has presented to the SAGE care home working group. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
(Copyright: © 2024 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Competing Interests: During the COVID-19 pandemic CN and AG were participants in the UK Scientific Advisory Group for Emergencies (SAGE), co-chaired the SAGE Environment and Modelling Sub-Group and was a member of the SAGE care home working group. CT has previously provided paid scientific advice to Microshare Ltd and has presented to the SAGE care home working group. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
(Copyright: © 2024 Thompson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)