ArticlePloS one2025
Understanding emotional and health indicators underlying the burnout risk of healthcare workers.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Occupational burnout among healthcare professionals in China: departmental differences, modifiable correlates, and public health intervention strategies.BMC public health · 2026Article
- Lack of treatment options for endemic helminth infections in Chile affects patient care and public health.Lancet regional health. Americas · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
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Abstract
Burnout of healthcare workers is of increasing concern as workload pressures mount. Burnout is usually conceptualised as resulting from external pressures rather than internal resilience and although is not a diagnosable condition, it is related to help seeking for its psychological sequelae. To understand how staff support services can intervene with staff heading for burnout, it is important to understand what other intrapsychic factors are related to it. A diary tool was used by staff in a region of England to self-monitor their wellbeing over time. The tool explores many areas of mental health and wellbeing and enabled regression analysis to predict which of the various factors provided the strongest indicators of burnout. Using a multiple linear regression model, burnout was found to be most associated with depression, receptiveness, mental wellbeing, and connectedness (p<0.05). It was also shown that 71% of the variance present in the response variable, i.e. burnout, explained by independent variables. Both the Spearman Rank Correlation and the Variance Inflation Factor methods found no evidence for multicollinearity in our regression models. We showed how burnout can be explained using a handful of factors including emotional and mental health indicators. The findings suggest a simple set of indicators can predict burnout and could be used for screening. The data suggests attention to four factors around social safeness, grounding and care in the self, hope and meaning, and having sufficient energy could form the basis of wellbeing programs.
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Registered trials
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