Epistemic validation in Chinese-language cancer-related CAM discourse on YouTube: identifying information frames (Preprint)

BACKGROUND Chinese-language discussions of complementary and alternative medicine (CAM) on social platforms provide an observable record of how commenters negotiate credibility, risk, and treatment integration in high-stakes cancer contexts. OBJECTIVE To identify the dominant information frames through which commenters validate and interpret cancer-related CAM information in Chinese-language YouTube comment discourse. METHODS We analyzed 2,416 publicly available comments from 12 Chinese-language YouTube videos about cancer and CAM (uploaded 2023-2025). After preprocessing, 2,403 comments were modeled using BERTopic with multilingual sentence embeddings (paraphrase-multilingual-MiniLM-L12-v2), UMAP dimensionality reduction, and HDBSCAN clustering. Topics were interpreted through a structured human-in-the-loop protocol, including iterative topic review and intra-coder consistency checks. RESULTS The initial model produced 152 topics; 30.4% (731/2,403) of comments were assigned to an outlier topic. After topic reduction and exclusion of non-substantive topics (eg, platform interaction, off-topic disputes), 30 topics (1,491 comments) were grouped into four frames: (1) cultural authority and access pathways, (2) experiential solidarity and community validation, (3) evidence negotiation through everyday regimens, and (4) negotiating biomedical risk and treatment integration. CONCLUSIONS Credibility work in Chinese-language cancer CAM comment spaces is organized around culturally embedded validation logics beyond biomedical authority. Frame-aware information support (eg, epistemic metadata to distinguish experiential support from clinical guidance) may help commenters navigate mixed-evidence environments more safely without implying clinical endorsement.