Evidence map›Paper›PMID 37701543›Full record

ArticleWorld journal of psychiatry2023

Investigation of contemporary college students' mental health status and construction of a risk prediction model.

Xiao-Li Mao, Hong-Mei Chen

Open access · diamondAbstract read
In one paragraph

Article in World journal of psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.0field-weighted citation impact, top 14% 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.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Xiao-Li MaoSchool of Health and Nursing, Wuchang University of Technology, Wuhan 430223, Hubei Province, China. maoxiaoli1973@163.com.
Hong-Mei ChenSchool of Health and Nursing, Wuchang University of Technology, Wuhan 430223, Hubei Province, China.
Wuchang University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDue to academic pressure, social relations, and the change of adapting to independent life, college students are under high levels of pressure. Therefore, it is very important to study the mental health problems of college students. Developing a predictive model that can detect early warning signals of college students' mental health risks can help support early intervention and improve overall well-being.

aimTo investigate college students' present psychological well-being, identify the contributing factors to its decline, and construct a predictive nomogram model.

methodsWe analyzed the psychological health status of 40874 university students in selected universities in Hubei Province, China from March 1 to 15, 2022, using online questionnaires and random sampling. Factors influencing their mental health were also analyzed using the logistic regression approach, and R4.2.3 software was employed to develop a nomogram model for risk prediction.

resultsWe randomly selected 918 valid data and found that 11.3% of college students had psychological problems. The results of the general data survey showed that the mental health problems of doctoral students were more prominent than those of junior college students, and the mental health of students from rural areas was more likely to be abnormal than that of urban students. In addition, students who had experienced significant life events and divorced parents were more likely to have an abnormal status. The abnormal group exhibited significantly higher Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 scores than the healthy group, with these differences being statistically significant (

conclusionIn this study, nearly 11.3% of contemporary college students had psychological problems, the risk factors include students from rural areas, divorced parents, non-single children, infrequent exercise, and significant life events.

Indexed as

CollegeInfluencing factorsLogistic regression analysisPredictive modelsPsychological healthRisk factors

Identifiers

PMID37701543
PMCPMC10494769
OpenAlexW4385887390

What OpenQuestion holds

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LicenceCC BY-NC
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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.