Burnout, depression, anxiety, and stress negatively impact the well-being and retention of healthcare professionals. The interplay of these symptoms is understudied. Utilizing network analysis, this study examined the interrelationships among these symptom clusters in clinical therapists in China. An anonymous survey was conducted among clinical therapists from 41 tertiary psychiatric hospitals in China. Burnout was assessed using the Maslach Burnout Inventory-Human Service Survey (MBI-HSS), while symptoms of depression, anxiety, and stress were assessed via the Depression, Anxiety, and Stress Scale-21 (DASS-21). Analyses were performed to identify central symptoms and bridge symptoms of this network. A total of 419 participants were included in this survey. The prevalence rate for burnout, depression, anxiety, and stress was 19.8%, 22.2%, 17.9%, and 8.6%, respectively. Network analysis indicated that stress symptoms had the highest expected influence values, closely followed by emotional exhaustion from MBI-HSS. Notably, emotional exhaustion emerged as the strongest bridge of expected influence. The stability of the expected influence and bridge expected influence was robust, with coefficients at 0.75. The study’s findings underscore the importance of recognizing the central symptoms and bridge symptoms, which could lead to more effective early detection and intervention for burnout, depression, anxiety, and stress among clinical therapists.
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