Evidence map›Paper›PMID 42326772›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Characterizing artificial intelligence (AI) psychosis in a large academic medical setting: evidence of the new clinical phenomenon and the vulnerability of those in early phases of psychosis.

Zachary Bergson, Sarah G Vassall, Adam Wright, Allison B McCoy, Katherine M Schafer, Margaret C Achee, Julia M Sheffield

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Zachary BergsonVanderbilt University Medical Center, Department of Psychiatry and Behavioral Sciences.ORCID 0000-0002-2498-1486
Sarah G VassallVanderbilt University Medical Center, Department of Psychiatry and Behavioral Sciences.ORCID 0000-0002-0393-8155
Adam WrightVanderbilt University Medical Center, Department of Biomedical Informatics.ORCID 0000-0001-6844-145X
Allison B McCoyVanderbilt University Medical Center, Department of Biomedical Informatics.ORCID 0000-0003-2292-9147
Katherine M SchaferVanderbilt University Medical Center, Department of Psychiatry and Behavioral Sciences.
Margaret C AcheeVanderbilt University Medical Center, Department of Psychiatry and Behavioral Sciences.ORCID 0009-0004-6137-0547
Julia M SheffieldVanderbilt University Medical Center, Department of Psychiatry and Behavioral Sciences.ORCID 0000-0002-0280-3101

Funding

Testing the role of belief updating in persecutory delusionsR01MH137024 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Julia May Sheffield · 2024 to 2026
$2.3M
NIMH NIH HHS R01 MH137024
6 · The paper itself

Abstract

Background: Concerns about "AI psychosis" have swirled in the media since ChatGPT's release, but few systematic analyses exist. We therefore conducted an electronic health record (EHR) analysis to identify the frequency, clinical characteristics, and quality of AI interactions in patients experiencing psychosis treated in a medical center. Methods: AI keywords (e.g., ChatGPT, AI) were used to search Vanderbilt University Medical Center's EHR from 12/1/2022-4/1/2026. Records were discarded if they were not AI-related or if the primary diagnosis did not include psychosis. Three raters read notes to determine if a patient was experiencing AI psychosis and classified the interactions using 4 a-priori categories (Catalyst, Amplifier, Co-Author, Object) formulated to explain how AI-related negative outcomes emerge. Findings: 73 patients met our criteria. 28 patients were rated as experiencing AI psychosis, 17 had neutral interactions, and 28 expressed delusional content related to AI without documented evidence of conversational AI use. ChatGPT was the matching keyword for 53.6% patients experiencing AI psychosis. The majority of AI psychosis cases were documented after ChatGPT's "4o" model was released in May 2024. Notably, the AI Psychosis group had significantly more patients experiencing a first psychotic episode (60.7%) compared to the other two groups. Amplifier was the most common (64.3%) qualitative rating in the AI Psychosis group. Interpretation: "AI psychosis" is an infrequent but real phenomenon observed in clinical practice. Most affected patients were experiencing their first psychotic episode and presented with AI psychosis following the release of the more sycophantic GPT-4o. Among the affected patients, AI most often exacerbated an existing condition by reinforcing distorted ideas.

Identifiers

PMID42326772
PMCPMC13278220

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.