Anxiety-depression symptom networks across emotion regulation profiles in Chinese nurses: a latent profile and...

Depression and anxiety are highly prevalent among clinical nurses. This study employed a person-centered analytical approach to identify distinct emotion regulation (ER) profiles among Chinese clinical nurses and examined the structure of depressive and anxiety symptoms within each profile using latent profile analysis (LPA) complemented by network analysis (NA).

A cross-sectional survey was conducted among clinical nurses in China. A total of 1,436 eligible nurses (mean age = 34.16, SD = 7.49; 93.5% female) participated. Participants completed the 10-item Emotion Regulation Questionnaire (ERQ), the 9-item Patient Health Questionnaire (PHQ-9), and the 7-item Generalized Anxiety Disorder scale (GAD-7). LPA was conducted using the two ERQ subscales, cognitive reappraisal and expressive suppression, to identify distinct ER profiles. NA was then applied to model the relationships among depressive and anxiety symptoms for the total sample and within each ER profile. Centrality (Expected Influence) and bridge centrality (Bridge Expected Influence) indices were calculated to identify core and bridging symptoms. Network accuracy and stability were assessed via bootstrap methods, and network structures were compared across profiles using the Network Comparison Test (NCT).

LPA identified five distinct ER profiles: Low Regulation (7.2%), Below-Average Regulation (44.9%), Flexible Regulation (8.6%), Above-Average Regulation (32.0%), and High Regulation (7.2%). The Flexible Regulation group, characterized by high cognitive reappraisal and low expressive suppression, exhibited the lowest levels of depression and anxiety, whereas the Below-Average and Above-Average groups reported the highest symptom severity. NA revealed "Uncontrollable worry" (GAD6) and "Restlessness" (GAD5) as core and bridge symptoms across multiple profiles, while "Sad mood" (PHQ2), "Motor disturbance" (PHQ8), and "Suicidal ideation" (PHQ9) emerged as profile-specific central and bridge symptoms in the Low and Flexible Regulation groups. NCT indicated significant differences in global network structure across several profiles, yet global strength did not differ.

This study reveals heterogeneous ER patterns among clinical nurses and demonstrates that the Flexible Regulation group is the most adaptive configuration. Key central and bridge symptoms differ across profiles, offering empirically grounded targets for profile-informed interventions. Regular mental health screening with attention to profile-specific symptom patterns is recommended to support tailored prevention strategies and improve overall well-being among clinical nurses.

Not applicable.