How perceived algorithmic control shapes psychological distress among gig workers

In platform labor, algorithmic management monitors the performance of gig workers, and structures how they receive tasks and understand their role. In this study we examined the psychological consequences of perceived algorithmic control for gig workers' well-being. We proposed that perceived algorithmic control would increase psychological distress by reducing workers' sense of work meaning and by weakening their trust in public institutions. Using data obtained in a two-wave survey of 463 gig workers in five Chinese cities, we tested a moderated chain mediation model. The results indicated that work meaninglessness and institutional distrust sequentially mediated the relationship between perceived algorithmic control and psychological distress. Furthermore, regulatory unresponsiveness intensified the effect of institutional distrust on distress. These findings highlight how meaning making and perceived institutional support shape emotional strain in platform work, suggesting that responsive governance and improving transparency are essential to sustaining gig workers' well-being.