Profiles and Networks: A Person-Centered Analysis of Emotional Labor, Burnout, and Change Fatigue Among Chinese Oncology Nurses.
To identify distinct subtypes of emotional labor among Chinese oncology nurses; explore the heterogeneous network structures linking emotional labor, change fatigue, and burnout across subgroups; and explore potential intervention targets via computer simulation.
Oncology nurses face three key occupational challenges: inherent emotional labor demands, frequent organizational changes inducing change fatigue, and subsequent burnout risk. Although emotional labor is essential for quality care, its misregulation-especially the resource-intensive deep acting-depletes psychological resources per conservation of resources theory. Yet, existing research often overlooks heterogeneity in nurses' emotional labor strategy use.
This study enrolled 924 nurses from a tertiary-level specialized cancer hospital in Zhejiang Province, assessing them using scales for emotional labor, burnout, and change fatigue. First, latent profile analysis identified distinct subgroups based on emotional labor indicators. Subsequently, network analysis constructed symptom networks for the overall cohort and subgroups. Finally, computer simulation technology compared the effects of activating or inhibiting network nodes on overall symptom burden.
LPA revealed three profiles: "Efficient Type-Proactive Regulation" (C1), "Stressed Type-Natural Expression" (C2), and "Exhausted Type-Dysregulated Regulation" (C3). In the total sample network, deep acting (E14) emerged as the most central and influential bridge symptom. Significant interprofile differences in network structure and global strength were observed, with unique core symptoms for each profile: professional efficacy (M10) for C1, overwhelming change (F1) for C2, and morning exhaustion (M3) for C3. Computer simulation identified potential core risk targets (M14, F1) and mitigation targets (E4, E8), with E8 showing cross-profile robustness.
Oncology nurses exhibit distinct emotional labor subtypes, and their burnout and change fatigue display significant, profile-specific associative patterns. Simulation analysis highlights potential intervention targets: managing excessive work engagement and organizational evaluation pressure, while simultaneously promoting adaptive emotional regulation. This suggests that customized, systemic intervention strategies should be adopted, integrating individual skill development with organizational policy adjustments.
The findings of this study advocate for nursing managers to adopt evidence-based, typology-specific management strategies. For C1, professional recognition should be leveraged to enhance their sense of professional efficacy, while optimizing performance evaluations to reinforce adaptive regulation patterns. For C2, management should focus on buffering organizational change stress and leveraging the protective role of equitable evaluation through measures such as establishing flexible feedback mechanisms. For C3, immediate psychological support and short-term leave resources are needed to alleviate physical and mental exhaustion and curb excessive work engagement. At the organizational level, systematically revising performance evaluation systems to reduce instrumental stress and embedding psychological resource support modules into change management processes is recommended. Concurrently, establishing a dynamic monitoring mechanism focused on core bridging symptom E14 facilitates early identification of high-risk individuals.
Oncology nurses face three key occupational challenges: inherent emotional labor demands, frequent organizational changes inducing change fatigue, and subsequent burnout risk. Although emotional labor is essential for quality care, its misregulation-especially the resource-intensive deep acting-depletes psychological resources per conservation of resources theory. Yet, existing research often overlooks heterogeneity in nurses' emotional labor strategy use.
This study enrolled 924 nurses from a tertiary-level specialized cancer hospital in Zhejiang Province, assessing them using scales for emotional labor, burnout, and change fatigue. First, latent profile analysis identified distinct subgroups based on emotional labor indicators. Subsequently, network analysis constructed symptom networks for the overall cohort and subgroups. Finally, computer simulation technology compared the effects of activating or inhibiting network nodes on overall symptom burden.
LPA revealed three profiles: "Efficient Type-Proactive Regulation" (C1), "Stressed Type-Natural Expression" (C2), and "Exhausted Type-Dysregulated Regulation" (C3). In the total sample network, deep acting (E14) emerged as the most central and influential bridge symptom. Significant interprofile differences in network structure and global strength were observed, with unique core symptoms for each profile: professional efficacy (M10) for C1, overwhelming change (F1) for C2, and morning exhaustion (M3) for C3. Computer simulation identified potential core risk targets (M14, F1) and mitigation targets (E4, E8), with E8 showing cross-profile robustness.
Oncology nurses exhibit distinct emotional labor subtypes, and their burnout and change fatigue display significant, profile-specific associative patterns. Simulation analysis highlights potential intervention targets: managing excessive work engagement and organizational evaluation pressure, while simultaneously promoting adaptive emotional regulation. This suggests that customized, systemic intervention strategies should be adopted, integrating individual skill development with organizational policy adjustments.
The findings of this study advocate for nursing managers to adopt evidence-based, typology-specific management strategies. For C1, professional recognition should be leveraged to enhance their sense of professional efficacy, while optimizing performance evaluations to reinforce adaptive regulation patterns. For C2, management should focus on buffering organizational change stress and leveraging the protective role of equitable evaluation through measures such as establishing flexible feedback mechanisms. For C3, immediate psychological support and short-term leave resources are needed to alleviate physical and mental exhaustion and curb excessive work engagement. At the organizational level, systematically revising performance evaluation systems to reduce instrumental stress and embedding psychological resource support modules into change management processes is recommended. Concurrently, establishing a dynamic monitoring mechanism focused on core bridging symptom E14 facilitates early identification of high-risk individuals.