{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T11:44:54Z","timestamp":1783079094529,"version":"3.54.6"},"reference-count":46,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T00:00:00Z","timestamp":1747785600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Job burnout is particularly prevalent within the healthcare sector, with public health practitioners (PHPs) being especially vulnerable. The global impact of the coronavirus disease 2019 (COVID-19) pandemic has been profound, yet the prevalent level of job burnout among PHPs following the crisis has been largely overlooked. This study aims to assess the prevalence and determinants of job burnout among PHPs in the post-COVID-19 era, thereby providing a theoretical foundation for the development of targeted interventions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This cross-sectional survey was conducted from July to October 2023, targeting members of the Center for Disease Control and Prevention and the Public Health Service Center in Baoan District, Shenzhen. A non-random convenience sampling was employed to recruit 222 participants. Demographic and work-related information was compiled. Job burnout was assessed with Chinese revised version of the Maslach Burnout Inventory-General Survey. Binary logistic regression analysis was employed to identify factors influencing job burnout among participants. The mediation effect was tested using the bias-corrected percentile Bootstrap method with 5,000 resamples.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The prevalence of job burnout among the PHPs was found to be 50.90%, with rates of mild, moderate, and severe burnout at 27.03, 15.32, and 8.56%, respectively. Multivariable analysis indicated that self-rated mental health (<jats:italic>OR<\/jats:italic>\u202f=\u202f0.436, 95% <jats:italic>CI<\/jats:italic>: 0.230, 0.827), workload intensity (<jats:italic>OR<\/jats:italic>\u202f=\u202f5.183, 95% <jats:italic>CI<\/jats:italic>: 1.751, 15.340), and the family support for work (<jats:italic>OR<\/jats:italic>\u202f=\u202f3.313, 95% <jats:italic>CI<\/jats:italic>: 1.335, 8.222) were significantly associated with burnout (<jats:italic>p<\/jats:italic>\u202f&amp;lt;\u202f0.05). The PHPs exhibiting poorer self-rated mental health, higher workload, and lower family support for work were at greater risk of job burnout. The mediation analysis revealed that elevated workload indirectly increased the likelihood of burnout (indirect effect\u202f=\u202f2.931, 95% <jats:italic>CI<\/jats:italic>: 1.111, 4.750), exhaustion dimension (indirect effect\u202f=\u202f2.801, 95% <jats:italic>CI<\/jats:italic>: 1.115, 4.486) and cynicism dimension (indirect effect\u202f=\u202f2.977, 95% <jats:italic>CI<\/jats:italic>: 1.127, 4.826) by exacerbating mental health deterioration.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Job burnout has emerged as a common concern among the PHPs in the aftermath of the COVID-19 pandemic. To effectively address burnout, it is crucial to develop effective intervention measures aimed at mitigating risk factors, ultimately enhancing the well-being of the PHPs.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2025.1518114","type":"journal-article","created":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T05:23:07Z","timestamp":1747804987000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Job burnout among public health practitioners in urban China: insights from the post-COVID-19 pandemic 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