Evidence map›Paper›PMID 37215678›Full record

ArticleFrontiers in psychiatry2023

Risk factors and prediction model for mental health in Chinese soldiers.

Mengxue Zhao, Ying He, Quan Tang, Ni Wang, Haoxin Zheng, Zhengzhi Feng

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
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

6 authors at 3 institutions in 1 country.

Mengxue ZhaoDepartment of Military Psychology, Faculty of Medical Psychology, Army Medical University (Third Military Medical University), Chongqing, China.
Ying HeDepartment of Psychiatry, Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Quan TangMedical Psychology Department, No. 984 Hospital of PLA, Beijing, China.
Ni WangGeneral Hospital of Xinjiang Military Region, Wulumuqi, China.
Haoxin ZhengThe 33rd Company of the 11th Battalion, College of Command and Control Engineering, Army Engineering University of PLA, Nanjing, China.
Zhengzhi FengFaculty of Medical Psychology, Army Medical University (Third Military Medical University), Chongqing, China.
Army Medical University · CNPLA 306 Hospital · CNPLA Army Engineering University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study aimed to explore potential risk factors for mental health concerns, and the prediction model for mental health concerns in Chinese soldiers was constructed through combined eligible risk factors. Methods: This cross-sectional study was performed on soldiers under direct command from Gansu, Sichuan, and Chongqing in China, and the soldiers were selected by cluster convenient sampling from 16 October 2018 to 10 December 2018. The Symptom Checklist-90 (SCL-90) and three questionnaires (Military Mental Health Status Questionnaire, Military Mental Health Ability Questionnaire, and Mental Quality Questionnaire for Army Men) were administered, including demographics, military careers, and 18 factors. Results: Of 1,430 Chinese soldiers, 162 soldiers presented mental disorders, with a prevalence of 11.33%. A total of five risk factors were identified, including serving place (Sichuan vs. Gansu: OR, 1.846, 95% CI: 1.028-3.315, Conclusion: The findings of this study demonstrate that mental disorders and onset in Chinese soldiers can be predicted on the basis of these three questionnaires, and the predictive value of the combined model was high.

Indexed as

Chinesemental healthprediction modelrisk factorssoldiers

Identifiers

PMID37215678
PMCPMC10196266
OpenAlexW4377564047

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.