Cross-sectional network analysis reveals central symptoms among health care workers, suggesting these may help target interventions.
Discrepancies persist regarding burnout-depression-anxiety relationships in health care workers (HCWs), hindering interventions. This cross-sectional study developed a symptom-level network model to clarify their interconnections. Nine hundred ninety-two HCWs completed online surveys assessing depression, anxiety, and burnout symptoms. A network model was constructed using bridge expected influence (BEI) to identify central symptoms and network comparisons to evaluate work-related stress impacts. The analysis identified "psychomotor problems" (BEI=0.96, 95% CI [0.78, 1.11]), "irritability" (BEI=0.85, 95% CI [0.68, 1.02]), and "collapse" (BEI=0.78, 95% CI [0.58, 0.99]) as central symptoms. Network comparison revealed no significant differences in the structure of symptom networks among varying levels of stress (global strength in high-stress condition: 13.50; moderate-stress condition: 13.06; S=0.44, p=.17). Preliminary evidence indicates interventions targeting "psychomotor problems," "irritability," and "collapse" can be applied across varying stress levels. Targeting these symptoms might disrupt cross-diagnostic activation pathways to mitigate comorbidities in HCWs.
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Ge et al. (2025) studied this question.
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