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USE OF SENSOR TECHNOLOGY TO MAP THE SOCIAL NETWORKS OF PEOPLE LIVING WITH DEMENTIA: A FEASIBILITY STUDY
For older adults living with dementia, social network quality influences health outcomes. However, current social network measurement methods are time consuming and mentally draining for people living with dementia. This study aimed to accurately measure social networks using sensor technology. Blue...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6845563/ http://dx.doi.org/10.1093/geroni/igz038.281 |
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author | Wright-Freeman, Kayla Wei, Sijia McConnell, Eleanor Caves, Kevin Davis, Leighanne Hawkes, Adrienne Moninger, Sarah Corazzini, Kirsten N |
author_facet | Wright-Freeman, Kayla Wei, Sijia McConnell, Eleanor Caves, Kevin Davis, Leighanne Hawkes, Adrienne Moninger, Sarah Corazzini, Kirsten N |
author_sort | Wright-Freeman, Kayla |
collection | PubMed |
description | For older adults living with dementia, social network quality influences health outcomes. However, current social network measurement methods are time consuming and mentally draining for people living with dementia. This study aimed to accurately measure social networks using sensor technology. Bluetooth and radio-frequency identification (RFID) sensors were used to collect social network data in a simulation of a falling nursing home resident living with dementia. Participants wore sensors on their clothing, and video recordings were compared to sensor data. Bluetooth data reflected general direction of movement and instances of idling but were neither precise or accurate. RFID data was accurate after applying data filters. Both systems detected multiple sensors simultaneously. The Bluetooth system is not feasible for clinical use, but the RFID system shows potential for clinical application and accurate measurement of social network factors as interaction frequency and duration. |
format | Online Article Text |
id | pubmed-6845563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-68455632019-11-15 USE OF SENSOR TECHNOLOGY TO MAP THE SOCIAL NETWORKS OF PEOPLE LIVING WITH DEMENTIA: A FEASIBILITY STUDY Wright-Freeman, Kayla Wei, Sijia McConnell, Eleanor Caves, Kevin Davis, Leighanne Hawkes, Adrienne Moninger, Sarah Corazzini, Kirsten N Innov Aging Session 780 (Symposium) For older adults living with dementia, social network quality influences health outcomes. However, current social network measurement methods are time consuming and mentally draining for people living with dementia. This study aimed to accurately measure social networks using sensor technology. Bluetooth and radio-frequency identification (RFID) sensors were used to collect social network data in a simulation of a falling nursing home resident living with dementia. Participants wore sensors on their clothing, and video recordings were compared to sensor data. Bluetooth data reflected general direction of movement and instances of idling but were neither precise or accurate. RFID data was accurate after applying data filters. Both systems detected multiple sensors simultaneously. The Bluetooth system is not feasible for clinical use, but the RFID system shows potential for clinical application and accurate measurement of social network factors as interaction frequency and duration. Oxford University Press 2019-11-08 /pmc/articles/PMC6845563/ http://dx.doi.org/10.1093/geroni/igz038.281 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Session 780 (Symposium) Wright-Freeman, Kayla Wei, Sijia McConnell, Eleanor Caves, Kevin Davis, Leighanne Hawkes, Adrienne Moninger, Sarah Corazzini, Kirsten N USE OF SENSOR TECHNOLOGY TO MAP THE SOCIAL NETWORKS OF PEOPLE LIVING WITH DEMENTIA: A FEASIBILITY STUDY |
title | USE OF SENSOR TECHNOLOGY TO MAP THE SOCIAL NETWORKS OF PEOPLE LIVING WITH DEMENTIA: A FEASIBILITY STUDY |
title_full | USE OF SENSOR TECHNOLOGY TO MAP THE SOCIAL NETWORKS OF PEOPLE LIVING WITH DEMENTIA: A FEASIBILITY STUDY |
title_fullStr | USE OF SENSOR TECHNOLOGY TO MAP THE SOCIAL NETWORKS OF PEOPLE LIVING WITH DEMENTIA: A FEASIBILITY STUDY |
title_full_unstemmed | USE OF SENSOR TECHNOLOGY TO MAP THE SOCIAL NETWORKS OF PEOPLE LIVING WITH DEMENTIA: A FEASIBILITY STUDY |
title_short | USE OF SENSOR TECHNOLOGY TO MAP THE SOCIAL NETWORKS OF PEOPLE LIVING WITH DEMENTIA: A FEASIBILITY STUDY |
title_sort | use of sensor technology to map the social networks of people living with dementia: a feasibility study |
topic | Session 780 (Symposium) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6845563/ http://dx.doi.org/10.1093/geroni/igz038.281 |
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