Evidence map›Paper›PMID 40863701›Full record

ArticlePharmacy (Basel, Switzerland)2025

Accuracy and Safety of ChatGPT-3.5 in Assessing Over-the-Counter Medication Use During Pregnancy: A Descriptive Comparative Study.

Bernadette Cornelison, David R Axon, Bryan Abbott, Carter Bishop, Cindy Jebara, Anjali Kumar, Kristen A Root

Abstract read
In one paragraph

Article in Pharmacy (Basel, Switzerland), 2025. 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. Article
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

7 authors.

Bernadette CornelisonR. Ken Coit College of Pharmacy, University of Arizona, 1295 N. Martin Ave., Tucson, AZ 85721, USA.ORCID 0000-0002-4970-571X
David R AxonR. Ken Coit College of Pharmacy, University of Arizona, 1295 N. Martin Ave., Tucson, AZ 85721, USA.ORCID 0000-0002-9903-5996
Bryan AbbottR. Ken Coit College of Pharmacy, University of Arizona, 1295 N. Martin Ave., Tucson, AZ 85721, USA.
Carter BishopR. Ken Coit College of Pharmacy, University of Arizona, 1295 N. Martin Ave., Tucson, AZ 85721, USA.
Cindy JebaraR. Ken Coit College of Pharmacy, University of Arizona, 1295 N. Martin Ave., Tucson, AZ 85721, USA.
Anjali KumarR. Ken Coit College of Pharmacy, University of Arizona, 1295 N. Martin Ave., Tucson, AZ 85721, USA.
Kristen A RootR. Ken Coit College of Pharmacy, University of Arizona, 1295 N. Martin Ave., Tucson, AZ 85721, USA.ORCID 0009-0001-7457-8601

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As artificial intelligence (AI) becomes increasingly utilized to perform tasks requiring human intelligence, patients who are pregnant may turn to AI for advice on over-the-counter (OTC) medications. However, medications used in pregnancy may pose profound safety concerns limited by data availability. This study focuses on a chatbot's ability to accurately provide information regarding OTC medications as it relates to patients that are pregnant. A prospective, descriptive design was used to compare the responses generated by the Chat Generative Pre-Trained Transformer 3.5 (ChatGPT-3.5) to the information provided by UpToDate

Indexed as

artificial intelligenceChatGPTover-the-counter drugspatient safetypregnancy

Identifiers

PMID40863701
PMCPMC12389367

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.