Evidence map›Paper›PMID 39440171›Full record

ArticleFrontiers in public health2024

Social isolation, loneliness, and subjective wellbeing among Chinese older adults during the COVID-19 pandemic.

Haijun Hao, Mengqi Du, Junyue Yue

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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.

Haijun Hao *Department of Social Welfare, Jeonbuk National University, Jeonju, Republic of Korea.
Mengqi Du *Department of Media and Communication Studies, Jeonbuk National University, Jeonju, Republic of Korea.
Junyue YueDepartment of Social Welfare, Jeonbuk National University, Jeonju, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has brought unprecedented challenges to the wellbeing of the older adults worldwide. Both social isolation and loneliness are associated with decreased subjective wellbeing, but it is uncertain whether their effects are independent or if loneliness represents the affective pathway through which social isolation impairs subjective wellbeing. We therefore assessed the extent to which the association between social isolation and subjective wellbeing is mediated by loneliness. We utilized data from the 2020 China Family Panel Studies (CFPS) and focused on a sample of 3,821 individuals aged 60 and above as the participants for our study. The results revealed a significant negative association between social isolation and subjective wellbeing among the older adults during the COVID-19 pandemic. Furthermore, loneliness was found to mediate this relationship, indicating that social isolation led to increased feelings of loneliness, which in turn negatively impacted subjective wellbeing. These findings highlight the detrimental effects of social isolation and loneliness on the wellbeing of the older adults in China during the pandemic. The implications of these results emphasize the need for interventions and support systems that address social isolation and loneliness among the older adults, promoting their wellbeing and overall mental health during challenging times such as the COVID-19 pandemic.

Indexed as

COVID-19LonelinessMental HealthSocial IsolationAgedAged, 80 and overChinaEast Asian PeopleFemaleHumansMaleMiddle AgedPandemicsSurveys and QuestionnairesChinese older adultsCOVID-19 pandemiclonelinesssocial isolationsubjective wellbeing

Identifiers

PMID39440171
PMCPMC11493606

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.