Abstract

Algorithmic systems are increasingly used for mood and emotion regulation. Moving beyond the notion of passive screen time, this narrative review synthesizes literature from biopsychology, Human–Computer Interaction, learning theory, attachment theory, and psychodynamic perspectives to examine algorithmic co-regulation. Algorithmic co-regulation is conceptualized as a bidirectional process in which digital systems respond to users’ behavioral and emotional cues while simultaneously shaping regulatory styles and identity development. The review clarifies how algorithmic systems function as co-regulators by engaging reward-learning pathways and simulating relational processes. Evidence suggests that although algorithmic co-regulation may offer accessible resources for emotion regulation, it is also associated with psychological distress, emotional dependency, erosion of internal coping strategies, and altered identity development. For psychotherapeutic practice, the review highlights the importance of integrating algorithm awareness into assessment and intervention. The article concludes by identifying critical gaps in the literature and emphasizing the need for longitudinal, qualitative, and controlled research to advance understanding of algorithmic co-regulation in mental health contexts.