Evidence map›Paper›PMID 42755655›Full record

ArticleFrontiers in public health2026

Future care preparation profiles and self-support ability among rural Chinese older adults: a cross-sectional study.

Fangyuan Wang, Xianhong Li, Jiajia Han, Yinghui Guan, Jiaqi Tian, Le Xu, Bing Huang, Jianhui Xie

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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Fangyuan WangXiangya School of Nursing, Central South University, Changsha, China.
Xianhong LiXiangya School of Nursing, Central South University, Changsha, China.
Jiajia HanDepartment of Orthopedics, The Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, Hunan, China.
Yinghui GuanDepartment of Orthopedics, The Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, Hunan, China.
Jiaqi TianDepartment of Orthopedics, The Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, Hunan, China.
Le XuDepartment of Orthopedics, The Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, Hunan, China.
Bing HuangDepartment of Orthopedics, The Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, Hunan, China.
Jianhui XieHospital Administration Office, The Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Population aging is accelerating worldwide, and rural older adults may face particular challenges because of limited access to formal care resources. Preparation for future care (PFC) is a multidimensional process involving awareness, avoidance, decision-making, and concrete planning. This study identified latent PFC profiles among rural older adults in China and examined their association with self-support ability. Methods: A cross-sectional survey was conducted among 851 older adults from 16 rural villages in Hebei Province, China. Data were obtained using a general information questionnaire, the 14-item Preparation for Future Care Needs Scale, the Self-supporting Ability Rating Scale for the Elderly, and the Generalized Self-Efficacy Scale. Latent profile analysis used the four PFC dimension mean scores as continuous indicators. Independent-samples Results: Three PFC profiles were identified: scarce-preparation (23.97%), moderate-preparation (47.00%), and high-avoidance/high-action (29.03%). In the adjusted model, marital status, family members' health status, self-efficacy, and PFC profile membership were significantly associated with self-support ability. Compared with the high-avoidance/high-action profile, the scarce-preparation profile ( Conclusion: PFC among rural older adults is heterogeneous, and high avoidance can coexist with active care preparation. The action-oriented components of preparation may be particularly relevant to later-life autonomy. Profile-informed, family-sensitive, and community-based approaches warrant further evaluation in longitudinal and intervention studies.

Indexed as

Rural PopulationSelf EfficacySocial SupportAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHumansMaleSurveys and Questionnaireslatent profile analysispreparation for future carerural older adultsself-efficacyself-support ability

Identifiers

PMID42755655
PMCPMC13581699

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.