Evidence map›Paper›PMID 39850986›Full record

ArticleJournal of global health2025

Willingness and determinants of elder care modes among elderly individuals: insights from underdeveloped regions in Western China.

Yunhua Wang, Guorong Chai, Jiancheng Wang

Abstract read
In one paragraph

Article in Journal of global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yunhua WangSchool of Management, Lanzhou University, Gansu, China.
Guorong ChaiSchool of Management, Lanzhou University, Gansu, China.
Jiancheng WangGansu Health Vocational College, Gansu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The aim of the present study was to investigate the willingness of elderly individuals regarding their choice of elderly care modes in underdeveloped regions of Western China and to identify the key factors influencing the willingness. Methods: We distributed a total of 20 000 questionnaires using the multistage stratified cluster random sampling method, and successfully collected 19 460 of them. After conducting quality checks, we deemed 19 040 questionnaires valid for analysis. The survey covered seven cities, 24 counties, and 255 villages in Gansu Province. We conducted statistical analyses, including univariate χ Results: Among the 19 040 valid responses, 88.55% preferred home care, 5.01% opted for community care, 5.01% chose institutional care, 1.08% preferred mutual care, and 0.36% selected smart care. Elderly individuals who have a lower level of education, residence within a 15-minute walking distance to the nearest health care facility, and believe that elder care should rely on themselves or their children, etc. exhibit a higher willingness for choosing the home care mode (P < 0.05). Elderly individuals who believe that elderly care should be reliant on their children, and possess a greater knowledge for the combination of medical and elderly care, etc. exhibit a stronger willingness for choosing the community care (P < 0.05). Elderly individuals with lower educational level and lack endowment insurance, etc. exhibit a higher willingness for choosing the mutual care (P < 0.05). Elderly individuals who are not afflicted with chronic illnesses and reside within a 15-minute distance from the nearest medical centre exhibit a higher willingness for choosing the smart care mode (P < 0.05). Conclusions: In underdeveloped regions in China, home care continues to be the predominant choice among elderly individuals. However, the growing demand for diverse elderly care modes warrants attention. Multiple factors influence the willingness of elderly individuals when selecting care modes. This study offers valuable insights for policymakers, enabling government departments to implement targeted strategies and interventions to meet the diverse service needs of the elderly population effectively.

Indexed as

Choice BehaviorHealth Services for the AgedHome Care ServicesAgedAged, 80 and overChinaFemaleHumansMaleMiddle AgedSurveys and Questionnaires

Identifiers

PMID39850986
PMCPMC11758468

What OpenQuestion holds

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Registered trials

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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.