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Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach

The world is witnessing an increasing number of senior adult residents who experience health issues. Healthcare innovation facilitates monitoring the health conditions of senior adults and reducing the burden on healthcare institutions. The study explored the effect of health improvement expectancy,...

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Autores principales: Xinyan, Zou, Mamun, Abdullah Al, Ali, Mohd Helmi, Siyu, Long, Yang, Qing, Hayat, Naeem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9650156/
https://www.ncbi.nlm.nih.gov/pubmed/36388276
http://dx.doi.org/10.3389/fpubh.2022.1016065
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author Xinyan, Zou
Mamun, Abdullah Al
Ali, Mohd Helmi
Siyu, Long
Yang, Qing
Hayat, Naeem
author_facet Xinyan, Zou
Mamun, Abdullah Al
Ali, Mohd Helmi
Siyu, Long
Yang, Qing
Hayat, Naeem
author_sort Xinyan, Zou
collection PubMed
description The world is witnessing an increasing number of senior adult residents who experience health issues. Healthcare innovation facilitates monitoring the health conditions of senior adults and reducing the burden on healthcare institutions. The study explored the effect of health improvement expectancy, effort expectancy, price value, perceived vulnerability, health consciousness, and perceived reliability on the intention and adoption of medical wearable devices (MWD) among senior adults in China. Furthermore, a cross-sectional design was adopted, while quantitative data was collected from 304 senior adults through an online survey. A hybrid approach of partial least square structural equational modeling and artificial neural network-based analysis technique was adopted. The findings demonstrated that health improvement expectancy, perceived vulnerability, price value, and perceived reliability significantly affected the intention to adopt MWDs. Moreover, the intention to adopt MWDs significantly positively affected the actual adoption of MWDs among senior adults. Although the moderating effect of the pre-existing conditions and income between the intention to use MWDs and actual adoption of MWDs was positive, it was not statistically significant. The artificial neural network analysis has proven that perceived reliability, price value, and vulnerability are the most critical factors contributing to the intention to use MWDs. The current study offered valuable insights into the factors affecting the intention and adoption of MWDs among senior adults. Following that, theoretical and practical contributions were documented to improve the ease of use and price value for the prospective users of MWDs. The correct healthcare policies could curtail the influx of senior adults into the hospital and empower these adults to track and manage their health issues at home.
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spelling pubmed-96501562022-11-15 Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach Xinyan, Zou Mamun, Abdullah Al Ali, Mohd Helmi Siyu, Long Yang, Qing Hayat, Naeem Front Public Health Public Health The world is witnessing an increasing number of senior adult residents who experience health issues. Healthcare innovation facilitates monitoring the health conditions of senior adults and reducing the burden on healthcare institutions. The study explored the effect of health improvement expectancy, effort expectancy, price value, perceived vulnerability, health consciousness, and perceived reliability on the intention and adoption of medical wearable devices (MWD) among senior adults in China. Furthermore, a cross-sectional design was adopted, while quantitative data was collected from 304 senior adults through an online survey. A hybrid approach of partial least square structural equational modeling and artificial neural network-based analysis technique was adopted. The findings demonstrated that health improvement expectancy, perceived vulnerability, price value, and perceived reliability significantly affected the intention to adopt MWDs. Moreover, the intention to adopt MWDs significantly positively affected the actual adoption of MWDs among senior adults. Although the moderating effect of the pre-existing conditions and income between the intention to use MWDs and actual adoption of MWDs was positive, it was not statistically significant. The artificial neural network analysis has proven that perceived reliability, price value, and vulnerability are the most critical factors contributing to the intention to use MWDs. The current study offered valuable insights into the factors affecting the intention and adoption of MWDs among senior adults. Following that, theoretical and practical contributions were documented to improve the ease of use and price value for the prospective users of MWDs. The correct healthcare policies could curtail the influx of senior adults into the hospital and empower these adults to track and manage their health issues at home. Frontiers Media S.A. 2022-10-28 /pmc/articles/PMC9650156/ /pubmed/36388276 http://dx.doi.org/10.3389/fpubh.2022.1016065 Text en Copyright © 2022 Xinyan, Mamun, Ali, Siyu, Yang and Hayat. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Xinyan, Zou
Mamun, Abdullah Al
Ali, Mohd Helmi
Siyu, Long
Yang, Qing
Hayat, Naeem
Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach
title Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach
title_full Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach
title_fullStr Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach
title_full_unstemmed Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach
title_short Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach
title_sort modeling the adoption of medical wearable devices among the senior adults: using hybrid sem-neural network approach
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9650156/
https://www.ncbi.nlm.nih.gov/pubmed/36388276
http://dx.doi.org/10.3389/fpubh.2022.1016065
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