Does TikTok contribute to eating disorders? A comparison of the TikTok algorithms belonging to individuals with eating disorders versus healthy controls

Abstract

TikTok employs sophisticated algorithms to deliver users increasingly personalised content over time. We investigated the potential for these algorithms to exacerbate eating disorder symptoms by analysing 1.03 million TikTok videos delivered to 42 individuals with eating disorders (76 % anorexia nervosa) and 49 healthy controls over one month. Within this video corpus, we identified four video categories relevant to eating disorder psychopathology: appearance-oriented videos, dieting videos, exercise videos, and toxic eating disorder (akin to "pro-anorexia") videos. Multi-level models predicted the likelihood of users' algorithms delivering these videos and the likelihood of users "liking" (i.e., volitionally engaging with) these videos. Algorithms belonging to users with eating disorders delivered more appearance-oriented (+146 %), dieting (+335 %), exercise (+142 %), and toxic eating disorder videos (+4343 %). Stronger biases in users' algorithms toward these videos were associated with more severe eating disorder symptoms. Whilst users with eating disorders were slightly more likely to "like" these problematic video categories (e.g., dieting videos: +23 % versus controls), their algorithms were far more likely to deliver these videos in the first place (dieting videos: +335 % versus controls). Our results provide preliminary evidence that the TikTok algorithm might exacerbate eating disorder symptoms via content personalisation processes that are desensitised to volitional user actions (i.e., "liking" videos).

Keywords: Algorithms; Big data; Body image; Eating disorders; Social media; TikTok.