ArticleJournal of affective disorders2023
Prevalence of depressive symptoms and associated factors during the COVID-19 pandemic: A national-based study.
Article in Journal of affective disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 17 citations in OpenAlex.
- Associations of Iron Indicators with Cognitive Impairment Risk in Postmenopausal Women: Evidence from a Matched Case-Control Study and Back Propagation Neural Network Model.Molecular neurobiology · 2026Article
- Analysis of frailty status and its influencing factors in maintenance hemodialysis patients based on the health ecological model.BMC nephrology · 2025Article
- Prevalence of depression and anxiety and related influencing factors in the Chinese population with noncommunicable chronic diseases: A network perspective.World journal of psychiatry · 2025Article
- Could social support mediate the relationship between personality trait patterns and mental health in Chinese older adults: a nationwide cross-sectional study conducted in 2022.BMC public health · 2025Article
- Analysis of sub-health status and related factors in medical students in the Chinese Mainland from the perspective of health ecology.BMC public health · 2025Article
- Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study.Psychiatry investigation · 2025Article
- The impact of physical exercise on adolescent psychological resilience: an empirical analysis based on deep neural networks.Frontiers in psychology · 2025Article
- Association of habitual physical activity with depression and anxiety: a multicentre cross-sectional study.BMJ open · 2024Article
- The relationship between physical exercise and depressive symptoms in college students: the mediating role of rumination.Frontiers in psychiatry · 2024Article
- Correlations among nicotine dependence, health-related quality of life, and depression in current smokers: a cross-sectional study with a mediation model.Frontiers in psychiatry · 2024Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundPrevious studies have reported that the prevalence of depression and depressive symptoms was significantly higher than that before the COVID-19 pandemic. This study aimed to explore the prevalence of depressive symptoms and evaluate the importance of influencing factors through Back Propagation Neural Network (BPNN).
methodsData were sourced from the psychology and behavior investigation of Chinese residents (PBICR). A total of 21,916 individuals in China were included in the current study. Multiple logistic regression was applied to preliminarily identify potential risk factors for depressive symptoms. BPNN was used to explore the order of contributing factors of depressive symptoms.
resultsThe prevalence of depressive symptoms among the general population during the COVID-19 pandemic was 57.57 %. The top five important variables were determined based on the BPNN rank of importance: subjective sleep quality (100.00 %), loneliness (77.30 %), subjective well-being (67.90 %), stress (65.00 %), problematic internet use (51.20 %).
conclusionsThe prevalence of depressive symptoms in the general population was high during the COVID-19 pandemic. The BPNN model established has significant preventive and clinical meaning to identify depressive symptoms lay theoretical foundation for individualized and targeted psychological intervention in the future.
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