Evidence map›Paper›PMID 35127620›Full record

ArticleFrontiers in public health2021

Negative Life Events, Social Ties, and Depressive Symptoms for Older Adults in China.

Hangqing Ruan, Ke Shen, Feinian Chen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 11% of its field
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

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  6. Adult Friendship and Suicidality: A Scoping Review.Journal of social and personal relationships · 2025
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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 at 2 institutions in 2 countries.

Hangqing RuanDepartment of Sociology, University of Maryland, College Park, MD, United States.
Ke ShenSchool of Social Development and Public Policy, Fudan University, Shanghai, China.
Feinian ChenDepartment of Sociology, University of Maryland, College Park, MD, United States.
Fudan University · CNUniversity of Maryland, College Park · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although it is widely acknowledged that older adults who have gone through negative life events are more likely to develop depression, there is limited evidence on whether and which type of social ties moderate this perceived relationship. Based on 2016 and 2018 waves of Chinese Longitudinal Aging Social Survey (4,466 individuals, 8,932 observations), we apply linear fixed effects models and confirm that negative life events are associated with depressive symptoms for older adults (Coef. = 0.35; 95% CIs 0.11-0.61), and social ties are negatively associated with depression (Coef. = -0.08; 95% CIs -0.10 to -0.07). Our study further suggests that the association between negative life events and depressive symptoms is significantly moderated by friendship ties (Coef. = -0.18, 95% CIs -0.30 to -0.07), rather than family ties (Coef. = -0.03, 95% CIs -0.09 to 0.15). Moreover, the buffering effects of friendship ties are more prominent for the less resilient and less privileged groups, namely male, rural, and less educated older adults. Our findings point to the importance of expanding and strengthening social networks for Chinese older adults in promoting their psychological health.

Indexed as

DepressionSocial NetworkingAgedChinaHumansMaleMental HealthRural PopulationChinadepressive symptomsnegative life eventsolder adultssocial ties

Identifiers

PMID35127620
PMCPMC8810507
OpenAlexW4225820090

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.