Evidence map›Paper›PMID 30106203›Full record

ArticleHealth & social care in the community2019

Whom should I rely on for my future care? Patterns of care expectations and intergenerational correlates among ageing Chinese adults in Hong Kong.

Xue Bai

Abstract read
In one paragraph

Article in Health & social care in the community, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

1 author.

Xue BaiDepartment of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China.ORCID 0000-0002-0502-7291

Funding

General Research Fund-Early Career Scheme sponsored by the Research Grant Council of Hong Kong 25608915
6 · The paper itself

Abstract

This study examined ageing parents' care expectations across multiple care domains (financial and material, emotional, personal and informational) towards filial and formal sources and identified intergenerational correlates of care expectation patterns using a proposed care expectation model. Data of 780 eligible ageing parents were drawn from a representative household survey of ageing adults (≥50 years) conducted in 2016-2017. Latent class analysis was used to examine the typological structure underlying ageing parents' care expectations. Four patterns of care expectations were discovered: mixed-maximal, filial-modest, formal-modest and neither-minimal. Multinomial logistic regression analysis was conducted to validate the newly proposed care expectation model. In addition to certain predisposing factors (participants' age, sex and education), parental enabling resources (economic status), health characteristics (physical, mental and functional health status), children-related enabling characteristics (number of sons and marital status of children), and intergenerational enabling circumstances (intergenerational relationships and caregiving to their own parents) were introduced into the model and found to be associated with ageing parents' care expectations. The findings can inform policy and programmes that effectively respond to ageing adults' diverse care expectations in Hong Kong and have implications for other Asian societies facing rapid population ageing and increasing care demands.

Indexed as

Intergenerational RelationsAgedAged, 80 and overAge FactorsAgingFemaleHealth StatusHome Care ServicesHong KongHumansMaleMental HealthMiddle AgedParentsSex FactorsSocioeconomic Factorscare expectationsChineselatent class analysisold age and social careolder people

Identifiers

PMID30106203
PMCPMC7379681

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.