Algorithmic management and stress at work. Beyond control, the importance of work intensification
Abstract
The impact of algorithmic management on work-related stress has been studied, comparing it with other predictors. The relationship between this use of algorithms or artificial intelligence for work organization and other psychosocial risk factors that may affect mental health has also been examined. The analysis is integrated into the Demand-Control-Social Support (DCS) theoretical model. Data from a representative survey of the Spanish working population, AMPWork 2023 (n=1930 cases), is used to empirically test a comprehensive explanatory model of stress. The results found that the main predictor is the workload (long hours), followed by job status. These are followed, in terms of importance, by the intensity of algorithmic management and performing complex tasks. Then the moderating factors appear (taking breaks and communicating with the boss). Those who work more with algorithmic management tend to experience high job demands and do not benefit from moderating factors.
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