Siqi Chen, Jing Cao, Lei Ye, Dong Wei
Introduction: As algorithmic recommendation technology increasingly dominates the circulation of health information, young people's exposure frequency to relevant content has significantly increased. However, the psychological mechanisms through which this exposure affects sleep quality remain insufficiently understood. Methods: Based on Social Cognitive Theory and Cognitive Arousal Theory, this study constructs a serial mediation model to investigate how the frequency of health information exposure under algorithmic recommendation influences youth sleep quality through information anxiety and self-efficacy. A questionnaire survey was conducted among individuals aged 18 to 35. Results: The results show that: (1) the frequency of health information exposure not only directly and negatively predicts sleep quality, but also exerts multiple indirect effects; (2) information anxiety and self-efficacy each serve as independent mediators between information exposure and sleep quality; and (3) information anxiety and self-efficacy form an "emotional-cognitive" serial mediation pathway, whereby greater exposure intensifies information anxiety, undermines self-efficacy, and ultimately impairs sleep quality. Discussion: By revealing the psychological processes through which the algorithmic information environment affects youth sleep, this study offers theoretical support and practical implications for enhancing digital health literacy, improving platform algorithm governance, and strengthening public health interventions.