Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey
Abstract 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...
| Main Authors: | , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2022-06-01
|
| Series: | BMC Health Services Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12913-022-08126-8 |
| _version_ | 1818211701306163200 |
|---|---|
| author | Feiying He Yibo Wu Jiao Yang Keer Chen Jingyu Xie Yusupujiang Tuersun Lehuan Li Fangjing Wu Yifan Kan Yuqian Deng Liping Zhao Jingxi Chen Xinying Sun Shengwu Liao JiangYun Chen |
| author_facet | Feiying He Yibo Wu Jiao Yang Keer Chen Jingyu Xie Yusupujiang Tuersun Lehuan Li Fangjing Wu Yifan Kan Yuqian Deng Liping Zhao Jingxi Chen Xinying Sun Shengwu Liao JiangYun Chen |
| author_sort | Feiying He |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-12T05:36:41Z |
| format | Article |
| id | doaj.art-5f42193ebfa3405c8d1035f725a14c74 |
| institution | Directory Open Access Journal |
| issn | 1472-6963 |
| language | English |
| last_indexed | 2024-12-12T05:36:41Z |
| publishDate | 2022-06-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Health Services Research |
| spelling | doaj.art-5f42193ebfa3405c8d1035f725a14c742022-12-22T00:36:06ZengBMCBMC Health Services Research1472-69632022-06-0122111410.1186/s12913-022-08126-8Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national surveyFeiying He0Yibo Wu1Jiao Yang2Keer Chen3Jingyu Xie4Yusupujiang Tuersun5Lehuan Li6Fangjing Wu7Yifan Kan8Yuqian Deng9Liping Zhao10Jingxi Chen11Xinying Sun12Shengwu Liao13JiangYun Chen14Southern Medical UniversitySchool of Public Health, Peking UniversitySchool of Health Management, Southern Medical UniversitySchool of Public Health, Southern Medical UniversitySchool of Public Health, Southern Medical UniversitySchool of Health Management, Southern Medical UniversitySchool of Health Management, Southern Medical UniversitySchool of Public Health, Southern Medical UniversitySchool of Public Health, Southern Medical UniversityXiangya School of Nursing, Central South UniversityThe Second Xiangya Hospital, Central South UniversitySchool of Languages and Communication Studies of Beijing Jiaotong UniversitySchool of Public Health, Peking UniversityDepartment of Health Management, Southern Hospital of Southern Medical UniversitySchool of Health Management, Southern Medical UniversityAbstract 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.https://doi.org/10.1186/s12913-022-08126-8Smart HomeDigital HealthHealth skillsClusteringChina Family Health Index Survey |
| spellingShingle | Feiying He Yibo Wu Jiao Yang Keer Chen Jingyu Xie Yusupujiang Tuersun Lehuan Li Fangjing Wu Yifan Kan Yuqian Deng Liping Zhao Jingxi Chen Xinying Sun Shengwu Liao JiangYun Chen Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey BMC Health Services Research Smart Home Digital Health Health skills Clustering China Family Health Index 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 | Smart Home Digital Health Health skills Clustering China Family Health Index Survey |
| url | https://doi.org/10.1186/s12913-022-08126-8 |
| work_keys_str_mv | AT feiyinghe chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT yibowu chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT jiaoyang chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT keerchen chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT jingyuxie chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT yusupujiangtuersun chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT lehuanli chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT fangjingwu chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT yifankan chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT yuqiandeng chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT lipingzhao chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT jingxichen chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT xinyingsun chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT shengwuliao chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey AT jiangyunchen chineseadultsegmentationaccordingtohealthskillsandanalysisoftheiruseforsmarthomeacrosssectionalnationalsurvey |