Navigating the Algorithmic Turn in Health Communication: A Systematic Review and Bibliometric Analysis of Short-Form Video Platforms

Abstract

The digital transformation of health communication has entered a new epoch characterized by the dominance of algorithmic short-form video platforms such as TikTok and Douyin. This transition from the “search-and-retrieve” logic of Web 1.0 to the “feed-based” passive consumption of Web 3.0 presents a complex paradox: while these platforms democratize access to medical knowledge, they simultaneously amplify misinformation and foster algorithmic echo chambers. This systematic review synthesizes the current state of research based on a dataset of 763 publications retrieved from the Web of Science Core Collection. Utilizing VOSviewer for bibliometric analysis, we identified five distinct keyword clusters that map the field's intellectual structure: the information ecology of content quality (Green and Blue clusters), the pedagogical potential for empowerment (Yellow and Purple clusters), and the psychological impact on vulnerable audiences (Red cluster).
This article provides an in-depth critique of the “double-edged sword” nature of short videos. It critically evaluates the applicability of traditional quality assessment tools (e.g., DISCERN) to multimodal content, analyzes the mechanisms of algorithmic misinformation propagation, and documents the efficacy of “nano-learning” in medical education. Furthermore, it highlights the profound behavioral impacts on adolescents, ranging from “TikTok Tourette’s” to body dysmorphia, with a specific focus on cross-cultural variances between Western and Chinese contexts. The review concludes that while short videos offer unprecedented opportunities for public health intervention, realizing this potential requires a shift from mere content analysis to algorithmic governance and ethical AI integration. Future research must address the critical gaps in longitudinal behavioral studies and the development of native evaluation metrics for vertical video formats.