Impact of the COVID-19 Pandemic on Gender Differences in Depression Based on National Representative Data-Reference-Cited by-同舟云学术

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Impact of the COVID-19 Pandemic on Gender Differences in Depression Based on National Representative Data

Published:2023 Issue:6 Volume:38 Page:
ISSN:1011-8934
Container-title:Journal of Korean Medical Science
language:en
Short-container-title:J Korean Med Sci

Author:

Jeong Hyunsuk¹^ORCID,Yim Hyeon Woo¹^ORCID,Lee Seung-Yup²^ORCID,Jung Da Young³^ORCID

Affiliation:

1. Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.

2. Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Korea.

3. Clinical Research Coordinating Center, Catholic Medical Center, Seoul, Korea.

Funder

National Research Foundation of Korea

Publisher

XMLink

Subject

General Medicine

Link

https://jkms.org/pdf/10.3346/jkms.2023.38.e36

Reference37 articles.

1. Prevalence of depression during the COVID-19 outbreak: A meta-analysis of community-based studies

2. The pathoplasticity of dysphoric episodes: differential impact of stressful life events on the pattern of depressive symptom inter-correlations

3. Sex Differences and the Epidemiology of Depression

4. Perceived job insecurity, unemployment and depressive symptoms: a systematic review and meta-analysis of prospective observational studies

5. Men’s Work-Related Stress and Mental Health: Illustrating the Workings of Masculine Role Norms

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1. Predictors of university staff distress during the COVID-19 pandemic. Part II. Risk and protection factors in women and men;Psychiatria i Psychologia Kliniczna;2024-07-24

2. Characteristics of drug overdose suicide attempts presenting to the psychiatric emergency department of Beijing Anding Hospital;BMC Public Health;2024-06-14

3. Non-binary gender, vulnerable populations and mental health during the COVID-19 pandemic: Data from the COVID-19 MEntal health inTernational for the general population (COMET-G) study;Journal of Affective Disorders;2024-05

4. Deep autoencoders and multivariate analysis for enhanced hypertension detection during the COVID-19 era;Electronic Research Archive;2024

5. Deep Autoencoder-based Multivariate Outlier Detection for the Classification of Hypertension: Case study COVID-19;2023-05-08

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