Evidence map›Paper›PMID 41238940›Full record

ArticleNaunyn-Schmiedeberg's archives of pharmacology2026

Pharmacological topics of interest for young people: misinformation on TikTok is common.

Alexa Ayana Haß, Roland Seifert

Abstract read
In one paragraph

Article in Naunyn-Schmiedeberg's archives of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Alexa Ayana HaßInstitute of Pharmacology, Hannover Medical School, Carl-Neuberg-Str. 1, D-30655, Hannover, Germany.
Roland SeifertInstitute of Pharmacology, Hannover Medical School, Carl-Neuberg-Str. 1, D-30655, Hannover, Germany. seifert.roland@mh-hannover.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

TikTok is a popular social media platform for young people. This paper aims to investigate the quality of pharmacological content of interest to young people on TikTok. 121 TikTok posts were analysed. The main parameters chosen were presence of misinformation, number of likes/views/comments, advertisement, occupational group, and source of reference. Sex hormones, opioids, and illicit drugs were the most popular topics. Eleven (9%) of 121 posts contained an advertisement. There was significantly more misinformation present in these videos than in posts without advertising. Most posts displayed no source of reference for the given claims (76%). The largest occupational group were influencers with 53 of 121 created videos. Pharmacological education was scarce among content generators. Thirty-two percent of posts contained misinformation, with influencers contributing overproportionally to misinformation. TikTok covers many pharmacological topics of interest to young people. Unfortunately, poor or no referencing of sources and misinformation are common. Content generators often lack proper pharmacological qualification. There is a need for a closer analysis of other social media regarding pharmacological topics. Especially children are estimated to be highly influenced by the portrayal of pharmacological content on social media platforms resulting in possible danger for their health. Protective guidelines for using TikTok and global awareness must be established. Conversely, TikTok must be actively used by official institutions to disseminate correct pharmacological information.

Indexed as

CommunicationPharmacologySocial MediaAdolescentHumansBirth controlDrugsInfluencersPublic healthSex hormonesSocial mediaTikTok

Identifiers

PMID41238940
PMCPMC13046701

What Socratic holds

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Registered trials

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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 Socratic graph.