The expectations and acceptability of a smart nursing home model among Chinese older adults: a mixed methods study
Abstract 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...
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| Format: | Article |
| Language: | English |
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BMC
2024-01-01
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| Series: | BMC Nursing |
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| Online Access: | https://doi.org/10.1186/s12912-023-01676-0 |
| _version_ | 1827382366608293888 |
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| author | Yuanyuan Zhao Shariff-Ghazali Sazlina Fakhrul Zaman Rokhani Karuthan Chinna Jing Su Boon-How Chew |
| author_facet | Yuanyuan Zhao Shariff-Ghazali Sazlina Fakhrul Zaman Rokhani Karuthan Chinna Jing Su Boon-How Chew |
| author_sort | Yuanyuan Zhao |
| collection | DOAJ |
| description | Abstract 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 (X 2 =28.89, p < 0.001) and acceptability (X 2 =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 | 2024-03-08T14:18:32Z |
| format | Article |
| id | doaj.art-cb565e46e05243928a7bc55d368ed58d |
| institution | Directory Open Access Journal |
| issn | 1472-6955 |
| language | English |
| last_indexed | 2024-03-08T14:18:32Z |
| publishDate | 2024-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Nursing |
| spelling | doaj.art-cb565e46e05243928a7bc55d368ed58d2024-01-14T12:17:43ZengBMCBMC Nursing1472-69552024-01-0123111910.1186/s12912-023-01676-0The expectations and acceptability of a smart nursing home model among Chinese older adults: a mixed methods studyYuanyuan Zhao0Shariff-Ghazali Sazlina1Fakhrul Zaman Rokhani2Karuthan Chinna3Jing Su4Boon-How Chew5The School of Smart Health and Wellness (Health Medical College), Zhejiang Dongfang PolytechnicDepartment of Family Medicine, Faculty of Medicine and Health Sciences, Universiti Putra MalaysiaFaculty of Engineering, Universiti Putra MalaysiaFaculty of Business and Management, UCSI UniversityInternational School of Public Health and One Health, Hainan Medical UniversityDepartment of Family Medicine, Faculty of Medicine and Health Sciences, Universiti Putra MalaysiaAbstract 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 (X 2 =28.89, p < 0.001) and acceptability (X 2 =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.https://doi.org/10.1186/s12912-023-01676-0Smart nursing homesQuality of careExpectationsAcceptabilityChinese older adults |
| spellingShingle | Yuanyuan Zhao Shariff-Ghazali Sazlina Fakhrul Zaman Rokhani Karuthan Chinna Jing Su Boon-How Chew The expectations and acceptability of a smart nursing home model among Chinese older adults: a mixed methods study BMC Nursing Smart nursing homes Quality of care Expectations Acceptability Chinese older adults |
| 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 |
| topic | Smart nursing homes Quality of care Expectations Acceptability Chinese older adults |
| url | https://doi.org/10.1186/s12912-023-01676-0 |
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