Conceptualizing Dysstreamia: A Systematic Integrative Review of Algorithmic Exposure, Mood, and Minoritized Mental Health

Abstract

This review introduces and defines Dysstreamia, a chronic, platform-linked depressive-anxious mood state sustained by algorithmically reinforced exposure to distressing or identity-relevant content. Framed within behavioral psychology and Self-Determination Theory (SDT), the study examines how algorithmic design, attentional capture, and social comparison processes contribute to mood regulation and psychological need frustration in digital contexts. An integrative review with embedded qualitative meta-synthesis was conducted across peer-reviewed studies published between 2015 and 2025. Eligible studies investigated social media or digital platform use and depressive or anxious outcomes among racial and ethnic minoritized populations. Databases searched included PsycINFO, PubMed, Scopus, Web of Science, and Google Scholar. Methodological quality was appraised using CASP, JBI, and MMAT tools. Data were extracted and synthesized thematically to identify recurring behavioral and cognitive-affective mechanisms. Fourteen studies met the inclusion criteria. Five consistent behavioral processes emerged: (1) algorithmic exposure to distressing or racialized content, (2) attentional capture and rumination, (3) social comparison and competence threat, (4) perceived loss of control over feeds, and (4) sleep disruption and vigilance. These mechanisms collectively reflect reinforcement loops that sustain low-to-moderate dysphoric affect. Dysstreamia explains how behavioral reinforcement, cognitive bias, and algorithmic design interact to produce persistent mood disturbance. The framework provides a foundation for developing culturally responsive screening tools, boundary-setting interventions, and digital-wellbeing education targeting behavioral regulation in online environments.