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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.
Afiliación
  • Zhao Y; The School of Smart Health and Wellness (Health Medical College), Zhejiang Dongfang Polytechnic, Wenzhou, Zhejiang Province, China.
  • Sazlina SG; Department of Family Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, 43400, Malaysia.
  • Rokhani FZ; Malaysian Research Institute on Ageing (MyAgeing TM ), Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
  • Chinna K; Faculty of Engineering, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
  • Su J; Malaysian Research Institute on Ageing (MyAgeing TM ), Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
  • Chew BH; Faculty of Business and Management, UCSI University, Kulala Lumpur, Selangor, Malaysia.
BMC Nurs ; 23(1): 40, 2024 Jan 13.
Article en En | MEDLINE | ID: mdl-38218894
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 (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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: BMC Nurs Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: BMC Nurs Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido