The expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study
Background Smart nursing homes (SNHs) integrate advanced technologies, including IoT, digital health, big data, AI, and cloud computing to optimise remote clinical services, monitor abnormal events, enhance decision-making, and support daily activities for older residents, ensuring overall well-bei...
| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
BMC
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/108938/ |
| _version_ | 1848865241402703872 |
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| author | Zhao, Yuanyuan Sazlina, Shariff-Ghazali Rokhani, Fakhrul Zaman Chinna, Karuthan Su, Jing Chew, Boon-How |
| author_facet | Zhao, Yuanyuan Sazlina, Shariff-Ghazali Rokhani, Fakhrul Zaman Chinna, Karuthan Su, Jing Chew, Boon-How |
| author_sort | Zhao, Yuanyuan |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Background
Smart nursing homes (SNHs) integrate advanced technologies, including IoT, digital health, big data, AI, and cloud computing to optimise remote clinical services, monitor abnormal events, enhance decision-making, and support daily activities for older residents, ensuring overall well-being in a safe and cost-effective environment. This study developed and validated a 24-item Expectation and Acceptability of Smart Nursing Homes Questionnaire (EASNH-Q), and examined the levels of expectations and acceptability of SNHs and associated factors among older adults in China.
Methods
This was an exploratory sequential mixed methods study, where the qualitative case study was conducted in Hainan and Dalian, while the survey was conducted in Xi’an, Nanjing, Shenyang, and Xiamen. The validation of EASNH-Q also included exploratory and confirmatory factor analyses. Multinomial logistic regression analysis was used to estimate the determinants of expectations and acceptability of SNHs.
Results
The newly developed EASNH-Q uses a Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree), and underwent validation and refinement from 49 items to the final 24 items. The content validity indices for relevance, comprehensibility, and comprehensiveness were all above 0.95. The expectations and acceptability of SNHs exhibited a strong correlation (r = 0.85, p < 0.01), and good test-retest reliability for expectation (0.90) and acceptability (0.81). The highest tertile of expectations (X2=28.89, p < 0.001) and acceptability (X2=25.64, p < 0.001) towards SNHs were significantly associated with the willingness to relocate to such facilities. Older adults with self-efficacy in applying smart technologies (OR: 28.0) and those expressing a willingness to move to a nursing home (OR: 3.0) were more likely to have the highest tertile of expectations compared to those in the lowest tertile. Similarly, older adults with self-efficacy in applying smart technologies were more likely to be in the highest tertile of acceptability of SNHs (OR: 13.8).
Conclusions
EASNH-Q demonstrated commendable validity, reliability, and stability. The majority of Chinese older adults have high expectations for and accept SNHs. Self-efficacy in applying smart technologies and willingness to relocate to a nursing home associated with high expectations and acceptability of SNHs. |
| first_indexed | 2025-11-15T14:01:35Z |
| format | Article |
| id | upm-108938 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T14:01:35Z |
| publishDate | 2024 |
| publisher | BMC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1089382024-05-16T09:51:45Z http://psasir.upm.edu.my/id/eprint/108938/ The expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study Zhao, Yuanyuan Sazlina, Shariff-Ghazali Rokhani, Fakhrul Zaman Chinna, Karuthan Su, Jing Chew, Boon-How Background Smart nursing homes (SNHs) integrate advanced technologies, including IoT, digital health, big data, AI, and cloud computing to optimise remote clinical services, monitor abnormal events, enhance decision-making, and support daily activities for older residents, ensuring overall well-being in a safe and cost-effective environment. This study developed and validated a 24-item Expectation and Acceptability of Smart Nursing Homes Questionnaire (EASNH-Q), and examined the levels of expectations and acceptability of SNHs and associated factors among older adults in China. Methods This was an exploratory sequential mixed methods study, where the qualitative case study was conducted in Hainan and Dalian, while the survey was conducted in Xi’an, Nanjing, Shenyang, and Xiamen. The validation of EASNH-Q also included exploratory and confirmatory factor analyses. Multinomial logistic regression analysis was used to estimate the determinants of expectations and acceptability of SNHs. Results The newly developed EASNH-Q uses a Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree), and underwent validation and refinement from 49 items to the final 24 items. The content validity indices for relevance, comprehensibility, and comprehensiveness were all above 0.95. The expectations and acceptability of SNHs exhibited a strong correlation (r = 0.85, p < 0.01), and good test-retest reliability for expectation (0.90) and acceptability (0.81). The highest tertile of expectations (X2=28.89, p < 0.001) and acceptability (X2=25.64, p < 0.001) towards SNHs were significantly associated with the willingness to relocate to such facilities. Older adults with self-efficacy in applying smart technologies (OR: 28.0) and those expressing a willingness to move to a nursing home (OR: 3.0) were more likely to have the highest tertile of expectations compared to those in the lowest tertile. Similarly, older adults with self-efficacy in applying smart technologies were more likely to be in the highest tertile of acceptability of SNHs (OR: 13.8). Conclusions EASNH-Q demonstrated commendable validity, reliability, and stability. The majority of Chinese older adults have high expectations for and accept SNHs. Self-efficacy in applying smart technologies and willingness to relocate to a nursing home associated with high expectations and acceptability of SNHs. BMC 2024 Article PeerReviewed Zhao, Yuanyuan and Sazlina, Shariff-Ghazali and Rokhani, Fakhrul Zaman and Chinna, Karuthan and Su, Jing and Chew, Boon-How (2024) The expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study. BMC Nursing, 23 (1). pp. 2-19. ISSN 1472-6955 https://bmcnurs.biomedcentral.com/articles/10.1186/s12912-023-01676-0 10.1186/s12912-023-01676-0 |
| spellingShingle | Zhao, Yuanyuan Sazlina, Shariff-Ghazali Rokhani, Fakhrul Zaman Chinna, Karuthan Su, Jing Chew, Boon-How The expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study |
| title | The expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study |
| title_full | The expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study |
| title_fullStr | The expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study |
| title_full_unstemmed | The expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study |
| title_short | The expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study |
| title_sort | expectations and acceptability of a smart nursing home model among chinese older adults: a mixed methods study |
| url | http://psasir.upm.edu.my/id/eprint/108938/ http://psasir.upm.edu.my/id/eprint/108938/ http://psasir.upm.edu.my/id/eprint/108938/ |