The association between core functions of algorithmic management and work-related health problems: indications for effects beyond well-known psychosocial stressors.

INTRODUCTION: Algorithmic management (AM) marks a transformation in work organization as managerial decisions increasingly rely on data-driven algorithms. While research suggests that AM may affect employee health, empirical evidence remains fragmented. This study examines whether associations between AM and work-related health impairments generalize across occupations. METHODS: Data from the cross-sectional Flash Eurobarometer "OSH Pulse" (N = 27,242 workers) were analyzed using cross-classified mixed-effects logistic regression. Exposure to AM-algorithmic monitoring, task allocation, and performance evaluation-was examined in relation to self-reported health problems (stress, depression or anxiety; musculoskeletal problems; headaches or eyestrain; accidents or injuries; overall fatigue), controlling for demographic variables and psychosocial work stressors. RESULTS: Findings show that with each additional AM function the likelihood of reported health problems increased modestly but constantly (OR = 1.06-1.11). Among the single AM functions examined, monitoring appeared to have most consistent associations with workers health problems. DISCUSSION: Findings suggest that AM may represent an additional risk factor for worker health accross different occupations. However, results should be interpreted cautiously due to non-established screening measures and an overrepresentation of tertiary-educated workers.