Evidence map›Paper›PMID 41063952›Full record

ArticleFrontiers in public health2025

Assessment of mutual aid older care needs for older adults with multimorbidity in urban China: a Kano model-based study.

Zhe Zhang, Yongqian Chen, Marcos C Ochoa

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. 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

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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Zhe Zhang *School of Nursing, Bengbu Medical University, Bengbu, Anhui Province, China.
Yongqian Chen *Department of Human Resources, The Third Affiliated Hospital of Anhui Medical University, Hefei First People's Hospital, Hefei, Anhui Province, China.
Marcos C OchoaThe School of Nursing, The Philippine Women's University Manila, Manila, Philippines.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: China faces escalating challenges in older care because of rapid population ageing and the high prevalence of multimorbidity among urban older adults. Traditional family-based and institutional care models are increasingly inadequate, necessitating innovative solutions like mutual aid older care. However, research gaps persist in understanding the prioritised needs of urban older with multimorbidity within mutual aid older care frameworks. This study evaluates and prioritises mutual aid older care needs for older adults with multimorbidity in urban Chinese communities, by integrating Maslow's Hierarchy of Needs with the Kano Model. Methods: A cross-sectional survey was conducted among 240 older adults (aged ≥65, with ≥2 chronic conditions) across 25 urban communities in Hefei, China. Using a validated questionnaire, 43 service items across safety/health, daily life, learning/socialisation, spiritual, and entertainment domains were assessed. Kano Model categorisation and better-worse coefficient analysis were applied to classify needs (must-be, one-dimensional, attractive, indifferent) and rank priorities via sensitivity calculations. Results: Key must-be needs included cooking, washing hair, and psychological counselling, while one-dimensional priorities emphasised exercise and travelling. Attractive needs featured telemedicine and cultural activities (e.g., Red Song Club). Indifferent items, such as pest control, had minimal impact on satisfaction. The analysis highlighted the centrality of physical health services, mental health support, and social engagement in enhancing quality of life. Discussion: Urban older adults with multimorbidity prioritise integrated care models addressing both basic survival needs and higher-order psychosocial well-being. Mutual aid older care frameworks must therefore balance healthcare accessibility with opportunities for social participation and emotional fulfilment. Future policies should adopt evidence-based, culturally tailored strategies to optimise resource allocation and foster sustainable ageing-in-place solutions. Limitations include geographic specificity and cross-sectional design, warranting broader longitudinal and mixed-method research.

Indexed as

Health Services Needs and DemandMultimorbidityNeeds AssessmentUrban PopulationAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHumansMaleSurveys and QuestionnairesKano modelmultimorbiditymutual aidolder care needspopulation ageing

Identifiers

PMID41063952
PMCPMC12500635

What OpenQuestion holds

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LicenceCC BY
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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.