Evidence map›Paper›PMID 41232032›Full record

ArticleJMIR infodemiology2025

Quality and Perception of Attention-Deficit/Hyperactivity Disorder Content on TikTok: Cross-Sectional Study.

Katharina Sieferle, Tiziana Guidi, Florence Dorr, Eva Maria Bitzer

Abstract read
In one paragraph

Article in JMIR infodemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Katharina SieferlePublic Health and Health Education, University of Education Freiburg, Kunzenweg 21, Freiburg im Breisgau, 79117, Germany, 49 761 682755.ORCID 0000-0002-4300-8382
Tiziana GuidiPublic Health and Health Education, University of Education Freiburg, Kunzenweg 21, Freiburg im Breisgau, 79117, Germany, 49 761 682755.ORCID 0009-0006-9392-0907
Florence DorrPublic Health and Health Education, University of Education Freiburg, Kunzenweg 21, Freiburg im Breisgau, 79117, Germany, 49 761 682755.ORCID 0000-0003-3674-4696
Eva Maria BitzerPublic Health and Health Education, University of Education Freiburg, Kunzenweg 21, Freiburg im Breisgau, 79117, Germany, 49 761 682755.ORCID 0000-0001-9979-7432

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Attention Deficit Disorder with HyperactivitySocial MediaAdultCross-Sectional StudiesFemaleHumansMaleVideo RecordingADHDattention-deficit/hyperactivity disorderhealth informationmisinformationsocial mediaTikTok

Identifiers

PMID41232032
PMCPMC12614393

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.