College of Nursing and Rehabilitation, North China University of Science and Technology, Tangshan, China.
North China University of Science and Technology Affiliated Hospital, Tangshan, China.
J Nurs Manag. 2021 Jul;29(5):1207-1219. doi: 10.1111/jonm.13259. Epub 2021 Feb 21.
To develop a model illustrating the factors that can influence care needs in daily living (CNDL) of older adults and the pathways between these.
The care needs in community-dwelling older adults have increased sharply. A better understanding of the elderly's CNDL would thus help policymakers define which types of support and services should be given.
A multicentre study with structural equation modelling was conducted in this study. We recruited 3,448 community-dwelling older adults in China by using a stratified random cluster sampling technique.
Physical and mental health was the strongest predictor of CNDL. Both age and living situation had positive effects on CNDL, while economic factors, social support and family support were the major risk factors for CNDL.
The presented model provides a better understanding of how to address CNDL in the targeted population. The older adults who are the oldest, low-income, non-empty nesters, and with poor self-rated health or the signs of loneliness should be firstly targeted for daily assistance.
Using this model could provide health authorities and managers with the information of distinguishing between the priority group and the strategies for easing the caregiving burden in older adults care, and thus improving resource utilization.
构建一个模型，展示影响老年人日常生活护理需求（CNDL）的因素及其之间的关系。
社区居住的老年人的护理需求急剧增加。因此，更好地了解老年人的 CNDL 将有助于政策制定者确定应提供哪些类型的支持和服务。
本研究采用多中心研究和结构方程模型。我们通过分层随机聚类抽样技术在中国招募了 3448 名社区居住的老年人。
身心健康是影响 CNDL 的最强预测因素。年龄和居住状况对 CNDL 有积极影响，而经济因素、社会支持和家庭支持是 CNDL 的主要危险因素。
提出的模型提供了更好地了解如何针对目标人群解决 CNDL 的方法。对于年龄最大、收入较低、非与子女同住、自我评估健康状况较差或有孤独感迹象的老年人，应首先提供日常帮助。
使用该模型可以为卫生当局和管理人员提供区分优先群体的信息以及减轻老年人护理负担的策略，从而提高资源利用效率。
