ArticleFrontiers in public health2026
Analysis of the spatial distribution of occupational burnout among mental health professionals at the city, county, and township levels in Guangxi and related influencing factors.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: This study aims to examine occupational burnout among mental health workers at the municipal, county, and township levels in Guangxi in 2024, as well as its influencing factors, from the perspective of ensuring workforce stability, thereby providing a theoretical basis for the development of targeted intervention measures. Methods: This study employed cluster sampling to conduct a cross-sectional survey of 1,520 mental health workers from different regions of Guangxi, China. The Chinese version of the Maslach Burnout Inventory-General Scale (MBI-GS) was used to assess burnout levels. To ensure the stability of the mental health workforce, we conducted univariate and binary logistic regression analyses using SPSS 27.0 (IBM Corp., Armonk, New York, USA) software across three dimensions: demographic information, institutional level, and work recommendations. Additionally, we utilized ArcMap 10.2 (Esri (Environmental Systems Research Institute, Inc.), Redlands, California, USA.) software to visualize occupational burnout levels across cities in Guangxi using hierarchical maps, thereby identifying the key factors influencing occupational burnout among mental health workers in the region. Results: The prevalence of occupational burnout among mental health workers in Guangxi was 65.46%. Workers in county-level (OR = 2.977, 95% CI: 1.480-5.988) and township-level (OR = 2.312, 95% CI: 1.210-4.416) mental health institutions were more likely to experience occupational burnout. In contrast, mental health workers in municipal institutions exhibited a lower risk of occupational burnout. Based on the recommendations made by mental health professionals, those who suggested "reducing the workload" (OR = 3.449, 95% CI: 2.142-5.554), increasing staff (OR = 2.714, 95% CI: 1.527-4.822), and lowering the difficulty of tasks (OR = 2.745, 95% CI: 1.406-5.359) showed a significantly increased risk of occupational burnout. Among the 14 cities in Guangxi, mental health workers in Laibin, Yulin, Hezhou, and Nanning exhibited higher burnout level than those in other cities. Conclusion: The prevalence of occupational burnout among mental health workers in Guangxi was relatively high. To ensure the stability of this workforce and reduce staff turnover, the competent authorities overseeing mental health services should prioritize monitoring burnout levels among workers at the county and township levels, and in key urban areas. Additionally, measures such as reducing workloads, increasing staffing, and simplifying tasks can help alleviate and symptoms of occupational burnout.
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