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Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey

BACKGROUND: Digital health has become a heated topic today and smart homes have received much attention as an important area of digital health. Smart home is a device that enables automation and remote control in a home environment via the internet. However, most of the existing studies have focused...

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Autores principales: He, Feiying, Wu, Yibo, Yang, Jiao, Chen, Keer, Xie, Jingyu, Tuersun, Yusupujiang, Li, Lehuan, Wu, Fangjing, Kan, Yifan, Deng, Yuqian, Zhao, Liping, Chen, Jingxi, Sun, Xinying, Liao, Shengwu, Chen, JiangYun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9184334/
https://www.ncbi.nlm.nih.gov/pubmed/35689205
http://dx.doi.org/10.1186/s12913-022-08126-8
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author He, Feiying
Wu, Yibo
Yang, Jiao
Chen, Keer
Xie, Jingyu
Tuersun, Yusupujiang
Li, Lehuan
Wu, Fangjing
Kan, Yifan
Deng, Yuqian
Zhao, Liping
Chen, Jingxi
Sun, Xinying
Liao, Shengwu
Chen, JiangYun
author_facet He, Feiying
Wu, Yibo
Yang, Jiao
Chen, Keer
Xie, Jingyu
Tuersun, Yusupujiang
Li, Lehuan
Wu, Fangjing
Kan, Yifan
Deng, Yuqian
Zhao, Liping
Chen, Jingxi
Sun, Xinying
Liao, Shengwu
Chen, JiangYun
author_sort He, Feiying
collection PubMed
description BACKGROUND: Digital health has become a heated topic today and smart homes have received much attention as an important area of digital health. Smart home is a device that enables automation and remote control in a home environment via the internet. However, most of the existing studies have focused on discussing the impact of smart home on people. Only few studies have focused on relationship between health skills and use of smart home. AIMS: To analyze the health skills of Chinese adults and segment them to compare and analyze the use of smart home for each group. METHODS: We used data from 11,031 participants aged 18 and above. The population was clustered based on five health skills factors: perceived social support, family health, health literacy, media use, and chronic diseases self-behavioral management. A total of 23 smart homes were categorized into three sub-categories based on their functions: entertainment smart home, functional smart home, and health smart home. We analyzed demographic characteristics and utilization rate of smart home across different cluster. Each groups’ features and the differences in their needs for smart home functions were compared and analyzed. RESULTS: As a result of the survey on health skills, three groups with different characteristics were clustered: good health skills, middle health skills, and poor health skills. The utilization rate of smart home was the highest was good health skills group (total smart home: 92.7%; entertainment smart home: 61.1%, functional smart home: 77.4%, and health smart home: 75.3%; P < 0.001). For entertainment smart home, smart TV had the highest utilization rate (good health skills: 45.7%; middle health skills: 43.5%, poor health skills: 33.4%, P < 0.001). For functional smart home, smart washing machine (good health skills: 37.7%, middle health skills: 35.11%, poor health skills: 26.5%; P < 0.001) and smart air conditioner (good health skills: 36.0%, middle health skills: 29.1%, poor health skills: 24.6%) were higher than other of this category. For health smart home, sports bracelet has the highest utilization rate (good health skills: 37.3%, middle health skills: 24.5%, poor health skills: 22.8%). CONCLUSION: People can be divided into different categories based on health skill profiles, those with good health skills had a better utilization rate of smart home. The government and smart home companies need to focus on people with poor smart home use in various ways to promote their use of smart homes for personal health management. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08126-8.
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spelling pubmed-91843342022-06-10 Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey He, Feiying Wu, Yibo Yang, Jiao Chen, Keer Xie, Jingyu Tuersun, Yusupujiang Li, Lehuan Wu, Fangjing Kan, Yifan Deng, Yuqian Zhao, Liping Chen, Jingxi Sun, Xinying Liao, Shengwu Chen, JiangYun BMC Health Serv Res Research BACKGROUND: Digital health has become a heated topic today and smart homes have received much attention as an important area of digital health. Smart home is a device that enables automation and remote control in a home environment via the internet. However, most of the existing studies have focused on discussing the impact of smart home on people. Only few studies have focused on relationship between health skills and use of smart home. AIMS: To analyze the health skills of Chinese adults and segment them to compare and analyze the use of smart home for each group. METHODS: We used data from 11,031 participants aged 18 and above. The population was clustered based on five health skills factors: perceived social support, family health, health literacy, media use, and chronic diseases self-behavioral management. A total of 23 smart homes were categorized into three sub-categories based on their functions: entertainment smart home, functional smart home, and health smart home. We analyzed demographic characteristics and utilization rate of smart home across different cluster. Each groups’ features and the differences in their needs for smart home functions were compared and analyzed. RESULTS: As a result of the survey on health skills, three groups with different characteristics were clustered: good health skills, middle health skills, and poor health skills. The utilization rate of smart home was the highest was good health skills group (total smart home: 92.7%; entertainment smart home: 61.1%, functional smart home: 77.4%, and health smart home: 75.3%; P < 0.001). For entertainment smart home, smart TV had the highest utilization rate (good health skills: 45.7%; middle health skills: 43.5%, poor health skills: 33.4%, P < 0.001). For functional smart home, smart washing machine (good health skills: 37.7%, middle health skills: 35.11%, poor health skills: 26.5%; P < 0.001) and smart air conditioner (good health skills: 36.0%, middle health skills: 29.1%, poor health skills: 24.6%) were higher than other of this category. For health smart home, sports bracelet has the highest utilization rate (good health skills: 37.3%, middle health skills: 24.5%, poor health skills: 22.8%). CONCLUSION: People can be divided into different categories based on health skill profiles, those with good health skills had a better utilization rate of smart home. The government and smart home companies need to focus on people with poor smart home use in various ways to promote their use of smart homes for personal health management. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08126-8. BioMed Central 2022-06-10 /pmc/articles/PMC9184334/ /pubmed/35689205 http://dx.doi.org/10.1186/s12913-022-08126-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
He, Feiying
Wu, Yibo
Yang, Jiao
Chen, Keer
Xie, Jingyu
Tuersun, Yusupujiang
Li, Lehuan
Wu, Fangjing
Kan, Yifan
Deng, Yuqian
Zhao, Liping
Chen, Jingxi
Sun, Xinying
Liao, Shengwu
Chen, JiangYun
Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey
title Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey
title_full Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey
title_fullStr Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey
title_full_unstemmed Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey
title_short Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey
title_sort chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9184334/
https://www.ncbi.nlm.nih.gov/pubmed/35689205
http://dx.doi.org/10.1186/s12913-022-08126-8
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