Evidence map›Paper›PMID 42110400›Full record

ArticleGlobal mental health (Cambridge, England)2026

Prevalence and predictors of psychological distress among Chinese male adults: A cross-sectional study in a large general population.

Tianya Hou, Chunyan Ni, Xiaofei Mao, Jianguo Zhang, Wenxi Deng, Wei Li, Ruike Zhang

Erratum issuedAbstract read
In one paragraph

Article in Global mental health (Cambridge, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Tianya HouFaculty of Psychology, Naval Medical University, China.ORCID https://orcid.org/0000-0001-7361-1935
Chunyan NiSuzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, China.
Xiaofei MaoFaculty of Psychology, Naval Medical University, China.
Jianguo ZhangFaculty of Psychology, Naval Medical University, China.
Wenxi DengNaval Medical University, China.
Wei LiNanjing University Medical School Affiliated Nanjing Drum Tower Hospital Department, China.
Ruike ZhangNaval Medical University, China.ORCID https://orcid.org/0000-0003-1232-390X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since little is known about the mental health status of Chinese male adults, the present study aimed to explore the prevalence and predictors of psychological distress among Chinese male adults. This cross-sectional study recruited 6,140 men by convenience sampling in Liaoning and Shanghai. Psychological distress and perceived social support were measured by the Depression, Anxiety, and Stress Scale-21 and the Perceived Social Support Scale. Multivariable logistic regression analysis was employed to investigate the factors associated with psychological distress. The prevalence of depression, anxiety and stress among Chinese male adults were 14.2%, 26.4% and 12.9%, respectively. Male adults with low perceived social support reported symptoms on all measurements. Being middle-aged, college or above and residing in urban areas were associated with depression, while living in urban areas was the independent risk factor of anxiety. Stress was significantly associated with being middle-aged, married status and college or above. Our results revealed a high prevalence of psychological distress among Chinese male adults in this sample. Results suggest more attention needs to be paid to the mental health of male adults in the studied population, especially those who are middle-aged, college or above, married status and reside in urban areas.

Indexed as

anxietydepressionmale adultsperceived social supportstress

Identifiers

PMID42110400
PMCPMC13150779

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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.