Labeling and Disclosure of AI-generated Mental Health Content on TikTok

TikTok has become a significant source of health information, and concern has grown about AI-generated content (henceforth, 'AIGC') as a vehicle for health misinformation. Where AIGC presents realistic-appearing people giving health advice, disclosure labels are the viewer's only reliable cue that what they are watching is synthetic. This research letter compares AI label metadata across 128,016 mental health-related TikTok videos and 4,924 videos from a network of 50 profiles posting exclusively AI-generated mental health content to evaluate how much content reaches audiences undisclosed. In a keywords-based collection, fewer than a percent of TikTok videos about mental health carried an AI label, but in profiles containing purely AI-generated content, just over 9 in 10 videos (90.23%) were neither labelled by the creator nor identified by TikTok's automatic detection. Additionally, in the keyword collection, automatic detection produced the majority of labels, while in confirmed AI-generated content from 50 profiles, it accounted for just three of the 481 labelled videos. These findings highlight the challenging landscape of AI disclosure and labelling and raise questions about where automatic detection is failing.