ArticleFrontiers in psychiatry2023
Social, lifestyle, and health status characteristics as a proxy for occupational burnout identification: A network approach analysis.
Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
What it found
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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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Lifestyle and Psychosocial Determinants of Type 2 Diabetes Risk Across Adulthood: The Role of Burnout in a Large Occupational Cohort.Medical sciences (Basel, Switzerland) · 2026Article
- Performance evaluation and occupational health safety analysis of university teachers based on time-series feature extraction.Frontiers in public health · 2026Article
- Article
- Machine learning-based early screening of mild cognitive impairment using nutrition-related biomarkers and functional indicators.Frontiers in aging neuroscience · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
10 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Occupational burnout is a type of psychological syndrome. It can lead to serious mental and physical disorders if not treated in time. However, individuals tend to conceal their genuine feelings of occupational burnout because such disclosures may elicit bias from superiors. This study aims to explore a novel method for estimating occupational burnout by elucidating its links with social, lifestyle, and health status factors. Methods: In this study 5,794 participants were included. Associations between occupational burnout and a set of features from a survey was analyzed using Chi-squared test and Wilcoxon rank sum test. Variables that are significantly related to occupational burnout were grouped into four categories: demographic, work-related, health status, and lifestyle. Then, from a network science perspective, we inferred the colleague's social network of all participants based on these variables. In this inferred social network, an exponential random graph model (ERGM) was used to analyze how occupational burnout may affect the edge in the network. Results: For demographic variables, age ( Limitation: The major limitation of this work is that the social network for occupational burnout ERGM analysis was inferred based on associated factors, such as demographics, work-related conditions, health and chronic diseases, and behaviors. Though these factors have been proven to be associated with occupational burnout, the results inferred by this social network cannot be warranted for accuracy. Conclusion: This work demonstrated the feasibility of identifying people at risk of occupational burnout through an inferred colleague's social network. Encouraging staff with lower occupational burnout status to communicate with others may reduce the risk of burnout for other staff in the network.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.