Mental Health in the Age of Algorithms: Examining the Behavioral Consequences of Human Interaction with Intelligent Digital Platforms

Abstract

This study aimed to explain users’ lived experiences of the behavioral and psychological consequences of continuous interaction with intelligent digital platforms and to identify the mechanisms through which algorithmic personalization influences attention, emotion, identity, social relationships, and digital self-regulation. This qualitative study employed an inductive thematic analysis. The participants were 24 adult users residing in Tehran who were selected through purposive maximum-variation sampling and had used platforms incorporating recommendation systems on a daily basis for at least two years. Data were collected exclusively through individual semi-structured interviews. Interviews continued until theoretical saturation was achieved; preliminary saturation occurred during the twenty-first interview, and three additional interviews were conducted to confirm the stability and comprehensiveness of the categories. The interviews were transcribed verbatim and analyzed with the assistance of NVivo software. Analysis involved familiarization with the data, generation of initial codes, development and review of themes, and definition and naming of the final themes. Member checking, peer review, maintenance of an audit trail, maximum-variation sampling, and reflexive documentation were used to enhance credibility and dependability. Five main categories were identified: “algorithmic capture of attention and the development of compulsive use,” “emotional fluctuation, social comparison, and psychological fatigue,” “identity reconstruction in the algorithmic mirror,” “the duality of social connectedness and perceived loneliness,” and “algorithmic awareness, resistance, and restoration of agency.” Participants did not experience themselves as merely passive recipients of technology. Instead, they described a reciprocal feedback cycle in which user behavior trained the algorithm, while algorithmically selected outputs subsequently influenced users’ moods, preferences, decisions, and future behaviors. Intelligent platforms may simultaneously facilitate belonging, learning, identity expression, and access to social or psychological support while threatening mental health through engagement-oriented design, repeated exposure to emotionally arousing content, social comparison, sleep disruption, and reduced perceived control. Therefore, the quality and context of interaction, the nature of recommended content, and users’ degree of transparency and control may be more informative than screen time alone. Algorithmic literacy, well-being-oriented platform design, meaningful user control over recommendations, and digital self-regulation interventions are required to reduce harm while preserving the psychosocial benefits of digital participation.