Evidence map›Paper›PMID 36091526›Full record

ArticleFrontiers in public health2022

Prevalence and risk factors of depressive symptoms among 140,259 college students during the COVID-19 epidemic normalization in China: A cross-sectional survey.

Xiaoyu Luo, Qingqing Xu, Keliang Fan, Juan Wang, Dandan Wei, Xian Wang, Xiaomin Lou, Hualiang Lin, Chongjian Wang, Cuiping Wu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

4 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

11 authors at 2 institutions in 1 country.

Xiaoyu LuoDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Qingqing XuDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Keliang FanDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Juan WangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Dandan WeiDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Xian WangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Xiaomin LouDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Hualiang LinDepartment of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Chongjian WangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Cuiping WuDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Zhenxing MaoDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
Zhengzhou University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: College students are one of the most vulnerable populations to the COVID-19 pandemic's mental health effects. During the coronavirus disease 2019 (COVID-19) outbreak, we wanted to see how common depressive symptoms were among college students and what factors contributed to that. Methods: Between 21 and 27 May 2021, 140,259 college students from three cities in Henan Province, China, were involved. The Patient Health Questionnaire-9 was used to determine depressive symptoms (PHQ-9). Multiple logistic regression analysis was used to calculate odds ratios (ORs) and 95% CIs for potential depressive symptom factors. Results: Mild depressive symptoms and above are present in 21.12% of college students. Women had a higher prevalence of mild depressive symptoms than men (61.38 vs. 59.75%), and depressive symptoms were most prevalent among rural students and least prevalent among city students (21.44 vs. 20.29%). Participants with depressive symptoms are also more likely to have a poor-behavioral status. From none-to-severe depressive symptoms, 78.88, 15.78, 2.80, 1.67, and 0.88% had them. Gender, residential location, and behavioral status were found to be associated with depressive symptoms after adjusting for potential confounders. Conclusion: This cross-sectional study identified the factors that influence the prevalence of depression in college students. It found that the government should pay more attention to mental health issues affecting college students in combating the COVID-19 epidemic normalization.

Indexed as

COVID-19DepressionChinaCross-Sectional StudiesFemaleHumansMalePandemicsPrevalenceRisk FactorsStudentsChinacollege studentsCOVID-19depressive symptomsfactors

Identifiers

PMID36091526
PMCPMC9449522
OpenAlexW4293216118

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.