Quality and Perception of Attention-Deficit/Hyperactivity Disorder Content on TikTok: Cross-Sectional Study
Bibliographic record
Abstract
Background: Social media platforms are increasingly used for both sharing and seeking health-related information online. TikTok has become one of the most widely used social networking platforms. One health-related topic trending on TikTok recently is attention-deficit/hyperactivity disorder (ADHD). However, the accuracy of health-related information on TikTok remains a significant concern. Misleading information about ADHD on TikTok can increase stigmatization and lead to false "self-diagnosis," pathologizing of normal behavior, and overuse of care. Objective: This study aims to investigate the quality and usefulness of popular TikTok videos about ADHD and to explore how this content is perceived by the viewers based on an in-depth analysis of the video comments. Methods: We scraped data from the 125 most liked ADHD-related TikTok videos uploaded between July 2021 and November 2023 using a commercial scraping software. We categorized videos based on the usefulness of their content as "misleading," "personal experience," or "useful" and used the Patient Education Materials Assessment Tool for Audiovisual Materials to evaluate the video quality regarding understandability and actionability. By purposive sampling, we selected 6 videos and analyzed the content of 100 randomly selected user comments per video to understand the extent of self-identification with ADHD behavior among the viewers. All qualitative analyses were carried out independently by at least 2 authors; the disagreement was resolved by discussion. Using SPSS (version 27; IBM Corp), we calculated the interrater reliability between the raters and the descriptive statistics for video and creator characteristics. We used one-way ANOVA to compare the usefulness of the videos. Results: We assessed 50.4% (63/125) of the videos as misleading, 30.4% (38/125) as personal experience, and 19.2% (24/125) as useful. The Patient Education Materials Assessment Tool for Audiovisual Materials scores for all videos for understandability and actionability are 79.5% and 5.1%, respectively. With a score of 92.3%, useful videos scored significantly higher for understandability than misleading and personal experience videos (P<.001). For actionability, there was no statistically significant difference depending on the videos' usefulness (P=.415). Viewers resonated with the ADHD-related behaviors depicted in the videos in 220 out of 600 (36.7%) of the comments and with ADHD in 32 out of 600 (5.3%) of the comments. Self-attribution of behavioral patterns varied significantly, depending on the usefulness of the videos, with personal experience videos showing the most comments on self-attribution of behavioral patterns (102/600, 17% of comments; P<.001). For self-attribution of ADHD, we found no significant difference depending on the usefulness of the videos (P=.359). Conclusions: The high number of misleading videos on ADHD on TikTok and the high percentage of users who self-identify with the symptoms and behaviors presented in these videos can potentially increase misdiagnosis. This highlights the need to critically evaluate health information on social media and for health care professionals to address misconceptions arising from these platforms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".