Evidence map›Paper›PMID 41447394›Full record

ArticleEuropean journal of ageing2025

Patterns of multiple caregiving and the influence on depressive symptoms among middle-aged and older adults in China.

Xinyi Zhao, Quan Zhang, Vivian W Q Lou, Siqing Tao

Abstract read
In one paragraph

Article in European journal of ageing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Article
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.

Xinyi ZhaoSchool of Health Humanities, Peking University, Beijing, China.
Quan ZhangDepartment of Economics, University of California Los Angeles, Los Angeles, CA, USA.
Vivian W Q LouDepartment of Social Work and Social Administration, The University of Hong Kong, Pokfulam, Hong Kong, China. wlou@hku.hk.
Siqing TaoSchool of Health Humanities, Peking University, Beijing, China.

Funding

Humanities and Social Science Fund of Ministry of Education of China 23JYC840043
6 · The paper itself

Abstract

With extended life expectancy, middle-aged and older adults have become more involved in multiple types of caregiving. This study aimed to investigate the patterns of multiple caregiving on the basis of the level of participation in parent care, spouse care, and grandchild care and to determine whether these patterns predict follow-up depressive symptoms. Data were obtained from the 2011-2018 waves of the China Health and Retirement Longitudinal Study. A total of 11,775 participants aged 50 years and older in 2011 were included in the latent class analysis to identify the patterns of multiple caregiving. A regression model was used to analyse the associations between baseline caregiving patterns and subsequent depressive symptoms. The results revealed four caregiving patterns: "part-time care for all," "full-time parent care and grandchild care," "part-time spouse care," and "full-time spouse care." Compared with the "part-time care for all" group, the "full-time spouse care" group and the "part-time spouse care" group reported significantly greater depressive symptoms seven years later, whereas the "full-time parent care and grandchild care" group did not significantly differ. The use of categorising multiple caregiving could vividly describe middle-aged and older adults' engagement in caregiving activities and provide a comprehensive prediction of mental health outcomes. Social services should be tailored to sandwiched caregivers in certain caregiving patterns.

Indexed as

Caregiving patternsDepressive symptomsMiddle-aged and older adultsMultiple caregivingSandwich generation

Identifiers

PMID41447394
PMCPMC12775249

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.