Exploring Work-Related Stress, Burnout, Poor Sleep Quality and Mindfulness as Predictors for Psychosomatic Symptoms

Psychosomatic symptoms refer to the medically unexplained physical disturbances that are commonly associated with psychological distress and have been observed within occupational settings impacting employee well-being. The current study investigates whether work-related stress, burnout, poor sleep quality, and mindfulness can significantly predict the manifestation of psychosomatic symptoms in a sample of employed Greek adults. A total of 209 individuals with a mean age of M= 33.68 years (SD= 8.68) participated in the survey, completing demographic information followed by five separate validated self-report questionnaires, including the Workplace Stress Scale (WSS), Oldenburg Burnout Inventory (OLBI), Short Pittsburgh Sleep Quality Index (Short-PSQI), Five Facet Mindfulness Questionnaire – 15 (FFMQ-15) and the Psychosomatic Screening Questionnaire - 29 (PSSQ-29). The standard multiple linear regression analysis indicated significance of the model, F (6, 202) = 38.78, p< .001, adjusted R2= .521, indicating a large effect size, thus 52.1% of the variance of psychosomatic symptoms could be explained by the predictors combined. Specifically, work-related stress (B= 1.86, p< .001), burnout (B= 1.86, p= .006), poor sleep quality (B= 4.20, p< .001), and mindfulness (B= 3.04, p< .001), revealed a significant positive association with the outcome, while gender and low income (< €10.000), also contributed significantly to psychosomatic symptoms scores. Contrary to the initial hypothesis and prior research, mindfulness was found to be positively correlated with psychosomatic symptoms, indicating a more complex relationship. These findings contribute to the growing body of research on psychosomatic symptoms in occupational settings and highlight the importance of further investigation. Future research should consider biological, psychological and individual difference factors while adopting longitudinal designs to more accurately assess causality and understand the mechanisms of these associations, ultimately forming strategies to support and improve employee well-being.