ArticleFrontiers in psychology2024
A network approach to understanding occupational psychological distress: linking depression, anxiety, and burnout among Chinese healthcare professionals.
Article in Frontiers in psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Bouncing back from stress: objective markers of expressive flexibility and resilience in emergency healthcare workers using computer vision.NPP - digital psychiatry and neuroscience · 2026Article
- From Occupational Hazard to Public Health Concern: A Bibliometric and Knowledge-Mapping Analysis of Sleep Disorders Among Nurses Worldwide (1985-2025).Journal of nursing management · 2026Review
- Occupational stress and psychological wellbeing among critical care nurses in private hospitals in Somalia: a national cross-sectional study.Frontiers in public health · 2026Article
- Qualitative phenomenological exploration of lived experiences and perspectives of Chinese hospital administrators engaged in medical dispute management.Scientific reports · 2025Article
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7 authors.
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Abstract
Objectives: As a population at high risk for psychological distress, healthcare workers typically experience varying degrees of anxiety, depression, and burnout. Studies have found that depression and anxiety have a negative impact on the mental health domain of burnout in healthcare workers. However, little is known about the symptom-to-symptom interactions between these psychological outcomes. This study aims to elucidate the characteristics of depression, anxiety, and burnout networks among healthcare workers. Methods: We recruited 846 healthcare workers from March to April 2023 from three hospitals. A total of 826 healthcare workers completed the General Information Scale, the 16-item Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR16), the Self-rating Anxiety Scale (SAS), and the Burnout Clinical Subtype Questionnaire (BCSQ)-36. The network models were constructed using network analysis. The expected influence and the bridge expected influence of nodes were calculated. The stability and accuracy of the network was assessed. Results: The results showed that the core symptoms in the symptom network mainly included QIDS8 (Energy/Fatigability), SAS3 (Easily upset or frightened), SAS11 (Dizzy), SAS8 (Tiredness), SAS10 (Tachycardia) and BCSQ3 (Worn-out), and the key nodes connecting these symptoms were QIDS2 (Sad mood), SAS20 (Have nightmares), BCSQ3 (Worn-out), SAS8 (Tiredness), QIDS8 (Energy/Fatigability), QIDS4 (Concentration/decision-making) and SAS4 (Madness). Conclusion: Unique pathways of association between burnout, depression, and anxiety were found to exist. Interventions targeting core symptoms can maximize the improvement of depression, anxiety, and burnout, provide a deeper understanding of the relationship between the three conditions, and provide a target and basis for psychological interventions to improve the emotional wellbeing of healthcare workers and enhance their mental health.
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