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The effect of COVID-19 on the home behaviours of people affected by dementia
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s41746-022-00697-4.pdf | Published version | 794.62 kB | Adobe PDF | View/Open |
Title: | The effect of COVID-19 on the home behaviours of people affected by dementia |
Authors: | Serban, A-I Soreq, E Barnaghi, P Daniels, S Calvo, RA CR&T Group Sharp, DJ |
Item Type: | Journal Article |
Abstract: | The COVID-19 pandemic has dramatically altered the behaviour of most of the world's population, particularly affecting the elderly, including people living with dementia (PLwD). Here we use remote home monitoring technology deployed into 31 homes of PLwD living in the UK to investigate the effects of COVID-19 on behaviour within the home, including social isolation. The home activity was monitored continuously using unobtrusive sensors for 498 days from 1 December 2019 to 12 April 2021. This period included six distinct pandemic phases with differing public health measures, including three periods of home 'lockdown'. Linear mixed-effects modelling is used to examine changes in the home activity of PLwD who lived alone or with others. An algorithm is developed to quantify time spent outside the home. Increased home activity is observed from very early in the pandemic, with a significant decrease in the time spent outside produced by the first lockdown. The study demonstrates the effects of COVID-19 lockdown on home behaviours in PLwD and shows how unobtrusive home monitoring can be used to track behaviours relevant to social isolation. |
Issue Date: | 17-Oct-2022 |
Date of Acceptance: | 29-Sep-2022 |
URI: | http://hdl.handle.net/10044/1/100189 |
DOI: | 10.1038/s41746-022-00697-4 |
ISSN: | 2398-6352 |
Publisher: | Nature Research |
Journal / Book Title: | npj Digital Medicine |
Volume: | 5 |
Issue: | 1 |
Copyright Statement: | © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
Sponsor/Funder: | UKRI Centre for Doctoral Training in AI for Healthcare |
Funder's Grant Number: | EP/S023283/1 |
Keywords: | CR&T Group |
Publication Status: | Published |
Conference Place: | England |
Open Access location: | https://www.nature.com/articles/s41746-022-00697-4 |
Article Number: | ARTN 154 |
Appears in Collections: | Faculty of Medicine Dyson School of Design Engineering Imperial College London COVID-19 Department of Brain Sciences |
This item is licensed under a Creative Commons License