Evidence map›Paper›PMID 37462971›Full record

ArticleJAMA network open2023

Assessment of Factors Associated With Mental Well-Being Among Chinese Youths at Individual, School, and Province Levels.

Peng Zhang, Fan Yang, Ning Huang, Wei Yan, Bo Zhang, Cancan Zhang, Kaiping Peng, Jing Guo

Abstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 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

8 authors.

Peng ZhangDepartment of Psychology, Tsinghua University, Beijing, China.
Fan YangDepartment of Health Policy and Management, School of Public Health, Peking University, Beijing, China.
Ning HuangDepartment of Health Policy and Management, School of Public Health, Peking University, Beijing, China.
Wei YanDepartment of Psychology, Tsinghua University, Beijing, China.
Bo ZhangDepartment of Neurology, Boston Children's Hospital, Boston, Massachusetts.
Cancan ZhangDivision of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.
Kaiping PengDepartment of Psychology, Tsinghua University, Beijing, China.
Jing GuoDepartment of Health Policy and Management, School of Public Health, Peking University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Although rapid urbanization in China provided improved economic prosperity and educational opportunities, it was associated with increased internalizing and externalizing problems among youths, with negative outcomes for mental well-being. Previous studies suggested that factors in individual, school, and regional levels were associated with mental well-being, and comprehensively examining these factors may provide evidence for policies for improving youth mental health. Objective: To investigate factors associated with mental well-being at individual, school, and province levels among Chinese youths. Design, Setting, and Participants: This cross-sectional study analyzed nationally representative data collected December 1, 2021, to January 1, 2022, from schools in China. Among 435 schools, 144 institutions had primary school students, 107 institutions had middle school students, 95 institutions had primary and middle school students, and 89 institutions had high school students. A total of 398 520 students were included. Exposures: Characteristics at individual, school, and province levels. Main outcomes and measures: The main outcome was mental well-being, assessed by the Short Warwick-Edinburgh Mental Well-being Scale. Linear mixed-effects models were used to investigate individual, school, and regional disparities in mental well-being among youths. Results: There were 398 520 participants (194 460 females [48.80%]; mean [SD; range] age, 13.78 [2.40; 9-20] years). At the school level, 352 443 students (88.44%) were in public school and 291 354 students (73.11%) were in urban schools. Drinking (coefficient = -1.08; 95% CI, -1.12 to -1.05; P < .001), smoking (coefficient = -0.89; 95% CI, -0.96 to -0.83; P < .001), and increased age (coefficient per 1-year increase in age = -0.02; 95% CI, -0.03 to -0.01; P < .001) were associated with worse mental well-being. Male sex (coefficient = 1.01; 95% CI, 0.98 to 1.04; P < .001), being in a 1-child family (coefficient = 0.17; 95% CI, 0.13 to 0.20; P < .001), being in the Han group (coefficient vs other ethnic groups = 0.20; 95% CI, 0.14 to 0.26; P < .001), a higher frequency and coverage of psychological courses (eg, ≥2/wk for all students vs none: coefficient = 1.02; 95% CI, 0.36 to 1.69; P = .003), and a higher level of self-rated popularity in school (coefficient per 1-unit increase in score = 0.89; 95% CI, 0.88 to 0.89; P < .001) were associated with improved mental well-being. However, age (eg, age and 1 courses/2 wk for all students: coefficient per 1-year increase in age = -0.047; 95% CI, -0.089 to -0.005; P = .03) and sex (eg, female sex and ≥2 courses/wk for some students: coefficient = -0.184; 95% CI, -0.323 to -0.046; P = .009) had interactions with the association between psychological courses and mental well-being. Conclusions and relevance: This study found that social disparities in mental well-being existed and that various factors at different levels were associated with mental well-being among Chinese youths. These findings suggest that public mental health programs may be recommended for associated improvements in regional disparities in mental health resources.

Indexed as

East Asian PeopleMental HealthAdolescentCross-Sectional StudiesEducational StatusFemaleHumansMaleSchools

Identifiers

PMID37462971
PMCPMC10354672

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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.