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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 6, 2024
Date Accepted: Oct 22, 2024

The final, peer-reviewed published version of this preprint can be found here:

Alternative Health and Conventional Medicine Discourse About Cancer on TikTok: Computer Vision Analysis of TikTok Videos

Muenster RM, Gangi K, Margolin D

Alternative Health and Conventional Medicine Discourse About Cancer on TikTok: Computer Vision Analysis of TikTok Videos

J Med Internet Res 2024;26:e60283

DOI: 10.2196/60283

PMID: 39652864

PMCID: 11667741

Alternative health and conventional medicine discourse about cancer on TikTok: A computer vision analysis of TikTok videos

  • Roxana Mika Muenster; 
  • Kai Gangi; 
  • Drew Margolin

ABSTRACT

Background:

Health misinformation is abundant online and becoming an increasingly pressing concern for both oncology practitioners and cancer patients. On social media, including the popular audiovisual app TikTok, the flourishing alternative health industry is further contributing to the spread of misleading and often harmful information, endangering patients’ health and outcomes and sowing distrust in the medical community. The prevalence of non-factual and dangerous false treatments on a platform that is used as a quasi-search engine by young people poses a serious risk to the health of vulnerable cancer patients.

Objective:

This study sought to examine how cancer discourse on TikTok differs between conventional medicine and alternative health videos. It aimed to look beyond mere facts and falsehoods that TikTok users may utter to understand the visual language and format used in support of misleading and truthful narratives, as well as other messages.

Methods:

Using computer vision analysis and subsequent qualitative close reading of 831 TikTok videos, this study examined how alternative health and conventional medicine videos on cancer differ with regards to the visual language they employ. Videos were examined for the prominence and duration of faces, as well as for the background and location of the video and its dominant color scheme.

Results:

The results show that the AltHealth and Health samples made different use of the audiovisual affordances of TikTok. Firstly, users from the alternative health sample were more likely to contain a single face that was prominently featured (12.5% of the image) for a significant period of time (45% of shots), with these testimonial-style videos making up 29% of the sample as compared to 19% of the conventional health sample. Alternative health videos were also more frequently cool tone dominant (P<.001), as well as significantly more likely to be filmed outdoors (P<.001), whereas conventional medicine videos were more likely to take place indoors and feature warm tones such as red, orange, or yellow.

Conclusions:

The findings of this study contribute to an increased understanding of misinformation as not merely a matter of singular falsehoods, but instead a phenomenon whose effects might also be transported through emotive in addition to rational means. They also point to influencer practices and style being an important contributing factor in the declining health of the information environment around cancer and its treatment. The results suggest that public health efforts must extend beyond the correction of false statements by injecting factual information into the cancer discourse online and instead look towards incorporating visual in addition to rational strategies.


 Citation

Please cite as:

Muenster RM, Gangi K, Margolin D

Alternative Health and Conventional Medicine Discourse About Cancer on TikTok: Computer Vision Analysis of TikTok Videos

J Med Internet Res 2024;26:e60283

DOI: 10.2196/60283

PMID: 39652864

PMCID: 11667741

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