RESUMO
BACKGROUND: 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. AIM: To analyse the nuanced associations between self-compassion and burnout using network analysis in a large cohort of Chinese nurses. DESIGN: A cross-sectional multi-centre survey design study. METHODS: 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. RESULTS: 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. CONCLUSION: 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. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. IMPACT: 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.
RESUMO
BACKGROUND: Recently developments in the field of positive psychology have provided new perspectives for understanding the connection between individual variation in Quality of life (QoL) and positive aspects of human potential, strengths, and resources, commanding increasing attention. This study aimed to examine self-reported quality of life (QoL) profiles and the association of QoL profiles with positive psychosocial characteristics in Chinese older adults. METHODS: A convenient sample of 354 older adults in nursing homes was recruited from Guangdong Province, China, between November 2020 and January 2021. Latent Profile Analysis (LPA) was conducted to explore QoL profiles using the four WHOQOL-BREF domains as input variables. Multinomial logistic regression was performed to explore the association between latent profiles and predictors. RESULTS: LPA identified three latent QoL profiles: "low QoL with poor psychological health" (18.1%), "moderate QoL" (46.0%) and "high QoL" (35.9%). Frequency of weekly activity, optimism, gratitude, and social support were associated with the increased likelihood of belonging to the moderate-to-high QoL classes. Furthermore, Class 2 (moderate QoL group, reference) was compared with Class3 (high QoL group), higher frequency of weekly physical activity and spending more time on physical activity exhibited higher odds of belonging to high QoL class. CONCLUSION: Using the domains of the WHOQOL-BREF scale, the QoL profiles Chinese older adults can be identified. We found that psychosocial variables and demographic characteristic, including lower level of optimism and gratitude, lack of social support, low frequency of physical activity, and shorter activity duration time, heighten the risk for lower levels of QoL. Identifying classification may help focus on those at elevated risk for poor QoL and for developing tailored QoL improvement programs.