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Machine learning analysis of the association between psychosocial risks and burnout syndrome in mining workers
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DOI：10.3389/fpubh.2026.1871339.png)
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Abstract
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IntroductionBurnout syndrome represents a critical issue in occupational health; particularly in high-demand contexts such as mining; where physical; environmental; and psychosocial risks converge and affect workers' wellbeing and job performance. In this context; the study objective is to analyze the association between psychosocial risk factors and burnout syndrome among mining workers in Moquegua; Peru.MethodsA quantitative; analytical cross-sectional study with a non-experimental design was conducted. The study population consisted of 65 workers from a mining unit in Moquegua; Peru. Given the complete accessibility of the target population; a census approach was adopted; and all eligible workers were included in the study (N = 65). Validated instruments were used; including the SUSESO/ISTAS21 questionnaire for psychosocial risks and the Maslach Burnout Inventory. Data analysis involved descriptive and correlational statistics; multiple linear regression; and machine learning techniques.ResultsThe findings revealed significant associations between psychosocial factors particularly social support; leadership; and work–family conflict (double presence) and burnout. All analyzed factors demonstrated significant associations capacity; with double presence emerging as the most influential predictor. Furthermore; machine learning analyses identified relevant burnout-related patterns within the analyzed dataset; highlighting their effectiveness in identifying burnout-related patterns.DiscussionBurnout in mining is a multifactorial phenomenon influenced by organizational and psychosocial conditions. The results support the use of machine learning as an useful tool for identifying psychosocial risk patterns that may support prevention strategies; contributing to improved occupational health strategies in high-risk industrial settings.
Keywords:
artificial intelligence
mining
occupational health
work-related stress
psychosocial risks
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