Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 367

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Anxiety and depression among general population in China at the peak of the COVID‐19 epidemic

Open access
Li, Junfeng, Yang, Zhiyun, Qiu, Hui, Wang, Yu, Jian, Lingyu, Ji, Junjun, Li, Kefeng·2020·World Psychiatry

Abstract

An epidemic of coronavirus pneumonia (COVID-19) throughout China has been occurring between 2019 and 2020. To combat the contagion, the Chinese government has implemented community-wide containment strategies such as home quarantine, business and public transportation shutdown, and class suspension for all schools. Psychological assistance has been offered to patients with COVID-19 infection and health professionals in Wuhan1. The effects of the COVID-19 epidemic and state-imposed massive quarantine on public mental health at the general population level have not been evaluated systematically. Our study aimed to examine the prevalence of anxiety and depression among China's adult population at the peak of the COVID-19 epidemic and identify the stressors associated with these disorders. We performed a nationally representative online survey of Chinese residents aged ≥18 years through Wenjuanxing, a web-based survey company. A stratified sampling method was used, and the sample population was randomly distributed in all Chi­na's provinces and municipalities. Subjects with pre-existing psy­chiatric disorders were excluded. A standardized questionnaire collected information on socio-demographic characteristics, time spent on news related to COVID-19 per day, and perceived sources of stress. The severity of anxiety and depression was assessed using the Generalized Anxiety Disorder-7 (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9), respectively. A cut-off total score of 8 was used for both GAD-7 and PHQ-9 to obtain the optimal sensitivity and specificity2, 3. The protocols were approved by the Ethical Committee of Changzhi Medical College. The sample size was calculated by assuming that the prevalence of anxiety and depression would be 4% in China4. This would require the sample size to be roughly 4,100 to achieve the margin of error of 15%. The survey was conducted between February 9 and February 16, 2020. We used descriptive statistics and Mann-Whitney tests or χ2 tests for bivariate analysis. The associations between the above-mentioned variables and the occurrence of anxiety and depression were determined by multinomial logistic regression. All analyses were performed in Prism 8.3. A total of 5,033 individuals (1,676 men and 3,357 women; 40.9% living in provinces with at least 220 coronavirus cases) completed the questionnaire (response rate: 78.1%). The prevalence of anxiety or depression or both was 20.4% (1,029 of 5,033). The median total score on GAD-7 was 10 (interquartile range, IQR: 9-14). The median total score on PHQ-9 was 9 (IQR: 8-13). The occurrence of anxiety and/or depression was significantly associated with time spent on COVID-19 related news per day (odds ratio, OR=1.61, 95% CI: 1.42-1.84, p<0.001). The prevalence of depression and/or anxiety was 17.8% among those spending less than 5 min per day on COVID-19 related news, and 27.9% among those who spent more than one hour. Three psychosocial stressors were significantly associated with the development of both anxiety and depression: "I worry about myself and my loved ones being infected by COVID-19" (OR=1.95, 95% CI: 1.54-2.49 for anxiety; OR=1.24, 95% CI: 1.04-1.50 for depression), "I worry about my income, job, study or ability to pay the loan being affected" (OR=1.38, 95% CI: 1.13-1.68 for anxiety; OR=1.58, 95% CI: 1.35-1.86 for depression), and "Home quarantine causes great inconvenience to my daily life" (OR=1.31, 95% CI: 1.04-1.64 for anxiety; OR=1.42, 95% CI: 1.18-1.70 for depression). In summary, our study revealed that the COVID-19 epidemic caused a sharp increase in the prevalence of anxiety and depression among the general adult population in China, compared to the prevalence of 4% in 20194. The amount of time spent on news related to COVID-19 was significantly associated with the occurrence of these mental health problems, which is likely explained by excessive media coverage5. The financial burden caused by massive quarantine was one of the primary stressors related to both anxiety and depression. Besides psychological interventions, financial aid such as wage subsidy, tax exemption, and extended loan repayment may help reduce the anxiety and depression in the general population. Our study was conducted around the peak of the COVID-19 epidemic6. A longitudinal follow-up would be helpful to track the changes in anxiety and depression levels at different stages of the epidemic.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/wps.20758

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 5 references

Cited by

See all 367

Metadata

Authors
Li, J., Yang, Z., Qiu, H., Wang, Y., Jian, L., Ji, J., & Li, K.
Venue
World Psychiatry
Publisher
Wiley
Published
2020-05-11
Volume
19
Issue
2
Pages
249-250
ISSN
  • 1723-8617 (ISSN-L)
  • 2051-5545
OpenAlex
W3025085020
Cited by
367
References
5
FWCI
30.39
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Anxiety and depression among general population in China at the peak of the COVID‐19 epidemic. https://app.cochat.ai/papers/10.1002/wps.20758
The paper
Li, J., Yang, Z., Qiu, H., Wang, Y., Jian, L., Ji, J., & Li, K. (2020). Anxiety and depression among general population in China at the peak of the COVID‐19 epidemic. World Psychiatry. https://doi.org/10.1002/wps.20758

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.