Algorithmic Social-Media Reliance for Health Information Under Literacy Constraints
DOI:
https://doi.org/10.66238/fsrma134Keywords:
Health Literacy, Algorithmic Curation, Misinformation, Digital Public Health, Information EnvironmentsAbstract
The rapid proliferation of algorithmically curated social media platforms has fundamentally transformed the dissemination and consumption of health information. This paper investigates the phenomenon of algorithmic reliance for health information among populations constrained by limited health and digital literacy. Through a comprehensive mixed-methods approach, this study explores how algorithmic curation mechanisms exploit cognitive vulnerabilities, thereby exacerbating public health risks such as medical misinformation and vaccine hesitancy. The research investigates the behavioral patterns of users who depend on personalized feeds as their primary source of medical knowledge, analyzing the intersection between health literacy deficits and algorithmic trust. Drawing upon data from a large-scale demographic survey and a simulated platform audit, the analysis reveals a significant negative correlation between health literacy levels and unquestioning reliance on algorithmically recommended content. Furthermore, the findings indicate that users with lower digital literacy are disproportionately channeled into algorithmic echo chambers that reinforce unverified or dangerous health narratives. This study contributes to the broader academic discourse on digital health communication by providing an empirical foundation for understanding systemic algorithmic biases and their impact on vulnerable populations. The paper concludes by proposing actionable policy recommendations for platform regulation and targeted digital health literacy interventions.
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