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Development and Evaluation of Treatment Adherence Interventions for Older Adults With MCI Using IoT Devices

For older adults with mild cognitive impairment (MCI), treatment adherence is essential to prevent and delay dementia. Older adults with MCI should maintain treatment for chronic diseases, exercise regularly, and adhere to treatment to maintain health status. There is a lack of comprehensive interve...

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Autores principales: Shin, Jinhee, Cho, Eunhee, Kim, Gwang Suk, Kim, Heejung, Ye, Byoung Seok, Pack, Chang-Gi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8681551/
http://dx.doi.org/10.1093/geroni/igab046.2600
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author Shin, Jinhee
Cho, Eunhee
Kim, Gwang Suk
Kim, Heejung
Ye, Byoung Seok
Pack, Chang-Gi
author_facet Shin, Jinhee
Cho, Eunhee
Kim, Gwang Suk
Kim, Heejung
Ye, Byoung Seok
Pack, Chang-Gi
author_sort Shin, Jinhee
collection PubMed
description For older adults with mild cognitive impairment (MCI), treatment adherence is essential to prevent and delay dementia. Older adults with MCI should maintain treatment for chronic diseases, exercise regularly, and adhere to treatment to maintain health status. There is a lack of comprehensive interventions to promote treatment adherence (medication adherence and physical activity) for older adults with MCI. The purpose of this study was to develop an internet of things (IoT)-based real-time treatment adherence for old adults with MCI and examine the effectiveness of the program. This study was a randomized controlled trial. The patients were enrolled from the neurology outpatient department clinic at a hospital in Korea. The subjects were 18 in the experimental group and 20 in the control group. This study intervention was IoT-based medication adherence device and real-time monitoring sever plus wrist wearable device. The study consists of a 10-week intervention period. The intervention program was provided for only the experimental group and the control group with a wearable device and usual care. Assessments were conducted at baseline, 6 weeks, and 10-weeks. A mixed-effects model was used in the analysis to evaluate the program. The IoT-based treatment adherence intervention was effective in improving medication adherence over time (β =11.465, p<.001), physical activity (K-PASE) (β =27.376, p<.001) and average the number of steps per week (β=3202.53, p<.001). Health care providers can use this program to improve treatment adherence for chronic disease management and dementia prevention of older adults with cognitive impairment.
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spelling pubmed-86815512021-12-17 Development and Evaluation of Treatment Adherence Interventions for Older Adults With MCI Using IoT Devices Shin, Jinhee Cho, Eunhee Kim, Gwang Suk Kim, Heejung Ye, Byoung Seok Pack, Chang-Gi Innov Aging Abstracts For older adults with mild cognitive impairment (MCI), treatment adherence is essential to prevent and delay dementia. Older adults with MCI should maintain treatment for chronic diseases, exercise regularly, and adhere to treatment to maintain health status. There is a lack of comprehensive interventions to promote treatment adherence (medication adherence and physical activity) for older adults with MCI. The purpose of this study was to develop an internet of things (IoT)-based real-time treatment adherence for old adults with MCI and examine the effectiveness of the program. This study was a randomized controlled trial. The patients were enrolled from the neurology outpatient department clinic at a hospital in Korea. The subjects were 18 in the experimental group and 20 in the control group. This study intervention was IoT-based medication adherence device and real-time monitoring sever plus wrist wearable device. The study consists of a 10-week intervention period. The intervention program was provided for only the experimental group and the control group with a wearable device and usual care. Assessments were conducted at baseline, 6 weeks, and 10-weeks. A mixed-effects model was used in the analysis to evaluate the program. The IoT-based treatment adherence intervention was effective in improving medication adherence over time (β =11.465, p<.001), physical activity (K-PASE) (β =27.376, p<.001) and average the number of steps per week (β=3202.53, p<.001). Health care providers can use this program to improve treatment adherence for chronic disease management and dementia prevention of older adults with cognitive impairment. Oxford University Press 2021-12-17 /pmc/articles/PMC8681551/ http://dx.doi.org/10.1093/geroni/igab046.2600 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. https://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/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Shin, Jinhee
Cho, Eunhee
Kim, Gwang Suk
Kim, Heejung
Ye, Byoung Seok
Pack, Chang-Gi
Development and Evaluation of Treatment Adherence Interventions for Older Adults With MCI Using IoT Devices
title Development and Evaluation of Treatment Adherence Interventions for Older Adults With MCI Using IoT Devices
title_full Development and Evaluation of Treatment Adherence Interventions for Older Adults With MCI Using IoT Devices
title_fullStr Development and Evaluation of Treatment Adherence Interventions for Older Adults With MCI Using IoT Devices
title_full_unstemmed Development and Evaluation of Treatment Adherence Interventions for Older Adults With MCI Using IoT Devices
title_short Development and Evaluation of Treatment Adherence Interventions for Older Adults With MCI Using IoT Devices
title_sort development and evaluation of treatment adherence interventions for older adults with mci using iot devices
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8681551/
http://dx.doi.org/10.1093/geroni/igab046.2600
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