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Meta-Analysis
. 2021 Feb;1486(1):90-111.
doi: 10.1111/nyas.14506. Epub 2020 Oct 2.

The prevalence of depression, anxiety, and sleep disturbances in COVID-19 patients: a meta-analysis

Affiliations
Meta-Analysis

The prevalence of depression, anxiety, and sleep disturbances in COVID-19 patients: a meta-analysis

Jiawen Deng et al. Ann N Y Acad Sci. 2021 Feb.

Abstract

Evidence from previous coronavirus outbreaks has shown that infected patients are at risk for developing psychiatric and mental health disorders, such as depression, anxiety, and sleep disturbances. To construct a comprehensive picture of the mental health status in COVID-19 patients, we conducted a systematic review and random-effects meta-analysis to assess the prevalence of depression, anxiety, and sleep disturbances in this population. We searched MEDLINE, EMBASE, PubMed, Web of Science, CINAHL, Wanfang Data, Wangfang Med Online, CNKI, and CQVIP for relevant articles, and we included 31 studies (n = 5153) in our analyses. We found that the pooled prevalence of depression was 45% (95% CI: 37-54%, I2 = 96%), the pooled prevalence of anxiety was 47% (95% CI: 37-57%, I2 = 97%), and the pooled prevalence of sleeping disturbances was 34% (95% CI: 19-50%, I2 = 98%). We did not find any significant differences in the prevalence estimates between different genders; however, the depression and anxiety prevalence estimates varied based on different screening tools. More observational studies assessing the mental wellness of COVID-19 outpatients and COVID-19 patients from countries other than China are needed to further examine the psychological implications of COVID-19 infections.

Keywords: anxiety; coronavirus; depression; meta-analysis; pandemic; sleep disturbance.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
PRISMA flowchart for the identification and selection of observational trials. CINAHL, Cumulative Index to Nursing and Allied Health Literature; CNKI, Chinese National Knowledge Infrastructure; CQVIP, Chongqing VIP Information.
Figure 2
Figure 2
Quality ratings of included studies using the modified Newcastle−Ottawa Scale.
Figure 3
Figure 3
Forest plot for the pooling of depression prevalence. Studies were separated into subgroups based on the screening tool and cutoff values used for evaluating depression. The prevalence values are in percentages. Prevalence was not pooled for the interview subgroup as only one study was included. The differences between subgroups were statistically significant (P < 0.01). CI, confidence interval; PHQ‐9, Patient Health Questionnaire Depression Module‐9; HADS‐D, Hospital Anxiety and Depression Scale (Depression Subscale); SCL‐90, Symptom Checklist‐90; SDS, Self‐Rating Depression Scale.
Figure 4
Figure 4
Forest plot for the pooling of anxiety prevalence. Studies were separated into subgroups based on the screening tool and cutoff values used for evaluating anxiety. The prevalence values are in percentages. Prevalence was not pooled for the interview subgroup as only one study was included. The differences between subgroups were statistically significant (P < 0.01). CI, confidence interval; GAD‐7, General Anxiety Disorder‐7; HADS‐A, Hospital Anxiety and Depression Scale (Anxiety Subscale); SAS, Self‐Rating Anxiety Scale; SCL‐90, Symptom Checklist‐90.
Figure 5
Figure 5
Forest plot for the pooling of sleep disturbance prevalence. Studies were separated into subgroups based on the screening tool and cutoff values used for evaluating sleep disturbances. The prevalence values are in percentages. The differences between subgroups were not statistically significant (P = 0.21). CI, confidence interval; ISI, Insomnia Severity Index; PSQI, Pittsburgh Sleep Quality Index.

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