Evidence map›Paper›PMID 42482708›Full record

ArticleInnovation in aging2026

From family support to smart health devices: addressing subjective community healthcare gaps in aging China.

Yue-Xuan Mu, Ru Wang, Yi Xiao, Hong-Peng Sun

Abstract read
In one paragraph

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

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Yue-Xuan MuSchool of Public Health, Medical College of Soochow University, Suzhou, China.ORCID https://orcid.org/0000-0003-3225-4569
Ru WangSchool of Public Health, Medical College of Soochow University, Suzhou, China.
Yi XiaoSchool of Public Health, Medical College of Soochow University, Suzhou, China.
Hong-Peng SunSchool of Public Health, Medical College of Soochow University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Population aging is increasing pressure on community health services in China, while family support remains central to later-life care. It remains unclear whether smart health devices can help reduce subjective gaps between older adults' service needs and actual service use, and whether such effects depend on family support. Research Design and Methods: We analyzed pooled person-wave observations from the 2018, 2020, and 2023 waves of the China Longitudinal Aging Social Survey, including 34,482 observations from 18,292 respondents in 1,277 village or urban neighborhood community clusters. Subjective service gaps were measured as a binary indicator of severe unmet need, defined as unmet need for three or more community health services, and as a count of unmet services from 0 to 7. Mixed-effects logistic and negative binomial models examined the associations of intergenerational support, smart health device ownership, and comprehensive community care capacity with these outcomes. Interaction terms, predicted probabilities, and subgroup analyses were used to aid interpretation. Results: Intergenerational support alone did not show a stable gap-reducing association. Smart health devices moderated the association between intergenerational support and subjective service gaps, such that device ownership was more beneficial when family support was stronger. This pattern was more evident among urban residents, women, and adults aged 60-69 years. Discussion and Implications: Smart health devices are unlikely to reduce subjective service gaps on their own. Their value depends on whether older adults can use them within supportive family and community contexts.

Indexed as

Community care servicesIntergenerational supportUnmet healthcare needs

Identifiers

PMID42482708
PMCPMC13385345

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LicenceCC BY-NC-ND
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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.