Abstract

In the nursing profession, the concept of self-compassion has been associated with burnout. However, to date, the fine-grained relationships between different dimensions of self-compassion and symptoms of burnout have not been investigated. Network analysis provides a new avenue for exploring the fine-grained correlation paths of two related variables. To analyse the nuanced associations between self-compassion and burnout using network analysis in a large cohort of Chinese nurses. A cross-sectional multi-centre survey design study. Participants were recruited from 30 hospitals in China between April and May 2022. These nurses completed the Chinese Maslach Burnout Inventory-General Survey (C-MBI-GS) and Self-Compassion Scale-Short Form (SCS-SF). Network analysis was performed to illustrate the complex nuanced relationships between self-compassion and burnout. A total of 1467 nurses (age 32.2 [18-56] years; 89.9% were female) participated in the study. Nodes Mindfulness and Isolation had the highest centralities measured by strength. Nodes Mindfulness, reduced personal accomplishment and Isolation were the most negative and positive influential nodes that bridged self-compassion and burnout. There were no differences in terms of gender, age, professional title and job tenure in the structure or connectivity of the self-compassion and burnout network. Different components of self-compassion were specifically associated with different dimensions of burnout in registered nurses. Among these, Mindfulness, Isolation and Reduced personal accomplishment were the three most important components of self-compassion for burnout symptoms. No patient or public contribution. Understanding the intricate connections between self-compassion and burnout will allow hospital administrators to prioritize the elements of Mindfulness and Isolation within self-compassion and the dimension of Reduced personal accomplishment within burnout when designing preventative measures and interventions aimed at reducing nurse burnout.

Full Text
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