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The factors of adaptation to nursing homes in mainland China: a cross-sectional study

BACKGROUND: China is one of the most rapidly ageing countries and has the largest ageing population in the world. The demand for long-term care is increasing. Nursing home placement is one of the most stressful events in a person’s life. Although research on relocation adjustment has been conducted...

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Autores principales: Sun, Changxian, Yu, Yiting, Li, Xuxu, Cui, Yan, Ding, Yaping, Zhu, Shuqin, Li, Xianwen, Chen, Shen, Zhou, Rong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708906/
https://www.ncbi.nlm.nih.gov/pubmed/33256628
http://dx.doi.org/10.1186/s12877-020-01916-x
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author Sun, Changxian
Yu, Yiting
Li, Xuxu
Cui, Yan
Ding, Yaping
Zhu, Shuqin
Li, Xianwen
Chen, Shen
Zhou, Rong
author_facet Sun, Changxian
Yu, Yiting
Li, Xuxu
Cui, Yan
Ding, Yaping
Zhu, Shuqin
Li, Xianwen
Chen, Shen
Zhou, Rong
author_sort Sun, Changxian
collection PubMed
description BACKGROUND: China is one of the most rapidly ageing countries and has the largest ageing population in the world. The demand for long-term care is increasing. Nursing home placement is one of the most stressful events in a person’s life. Although research on relocation adjustment has been conducted in many countries, few studies have been related to the predictors of nursing home adjustment in mainland China. This study aimed to identify the predictors of nursing home adjustment in the context of filial piety in mainland China. METHODS: This was a descriptive study that employed a cross-sectional survey. A total of 303 residents from 22 nursing homes in Nanjing, China, were recruited. A structured questionnaire about residents’ characteristics, activities of daily living, social support, resilience, and nursing home adjustment was administered. Multiple linear regression was used to identify the predictors of adaptation to nursing homes. RESULTS: The predictors of nursing home adjustment were the satisfaction with services(β = .158, P < .01), number of diseases(β = −.091, P < .05), length of stay(β = .088, P < .05), knowledge of the purpose of admission (β = .092, P < .05), resilience(β = .483, P < .001) and social support(β = .186, P < .001). The total explained variance for this model was 61.6%. CONCLUSION: Nursing staff members should assess the characteristics of residents to promote their better adjustment. Resilience had the most significant influence on the level of adaptation, which has been the primary focus of interventions to improve adjustment. The management of disease comorbidities in nursing homes should be standardized and supervised by the government. More volunteers from universities and communities should be encouraged to provide social support to residents. Moreover, a caring culture needs to be emphasized, and the value of filial piety should be advocated in nursing homes of East Asian countries. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-020-01916-x.
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spelling pubmed-77089062020-12-02 The factors of adaptation to nursing homes in mainland China: a cross-sectional study Sun, Changxian Yu, Yiting Li, Xuxu Cui, Yan Ding, Yaping Zhu, Shuqin Li, Xianwen Chen, Shen Zhou, Rong BMC Geriatr Research Article BACKGROUND: China is one of the most rapidly ageing countries and has the largest ageing population in the world. The demand for long-term care is increasing. Nursing home placement is one of the most stressful events in a person’s life. Although research on relocation adjustment has been conducted in many countries, few studies have been related to the predictors of nursing home adjustment in mainland China. This study aimed to identify the predictors of nursing home adjustment in the context of filial piety in mainland China. METHODS: This was a descriptive study that employed a cross-sectional survey. A total of 303 residents from 22 nursing homes in Nanjing, China, were recruited. A structured questionnaire about residents’ characteristics, activities of daily living, social support, resilience, and nursing home adjustment was administered. Multiple linear regression was used to identify the predictors of adaptation to nursing homes. RESULTS: The predictors of nursing home adjustment were the satisfaction with services(β = .158, P < .01), number of diseases(β = −.091, P < .05), length of stay(β = .088, P < .05), knowledge of the purpose of admission (β = .092, P < .05), resilience(β = .483, P < .001) and social support(β = .186, P < .001). The total explained variance for this model was 61.6%. CONCLUSION: Nursing staff members should assess the characteristics of residents to promote their better adjustment. Resilience had the most significant influence on the level of adaptation, which has been the primary focus of interventions to improve adjustment. The management of disease comorbidities in nursing homes should be standardized and supervised by the government. More volunteers from universities and communities should be encouraged to provide social support to residents. Moreover, a caring culture needs to be emphasized, and the value of filial piety should be advocated in nursing homes of East Asian countries. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-020-01916-x. BioMed Central 2020-11-30 /pmc/articles/PMC7708906/ /pubmed/33256628 http://dx.doi.org/10.1186/s12877-020-01916-x Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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 Article
Sun, Changxian
Yu, Yiting
Li, Xuxu
Cui, Yan
Ding, Yaping
Zhu, Shuqin
Li, Xianwen
Chen, Shen
Zhou, Rong
The factors of adaptation to nursing homes in mainland China: a cross-sectional study
title The factors of adaptation to nursing homes in mainland China: a cross-sectional study
title_full The factors of adaptation to nursing homes in mainland China: a cross-sectional study
title_fullStr The factors of adaptation to nursing homes in mainland China: a cross-sectional study
title_full_unstemmed The factors of adaptation to nursing homes in mainland China: a cross-sectional study
title_short The factors of adaptation to nursing homes in mainland China: a cross-sectional study
title_sort factors of adaptation to nursing homes in mainland china: a cross-sectional study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708906/
https://www.ncbi.nlm.nih.gov/pubmed/33256628
http://dx.doi.org/10.1186/s12877-020-01916-x
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