A review of electronic health records at a large medical center suggests that conversational artificial intelligence chatbots are associated with worsening psychotic symptoms in a small fraction of mental health patients. These interactions tend to validate preexisting delusions and appear to occur most frequently among patients experiencing their very first episode of psychosis. The findings were published in JAMA Psychiatry.
Psychosis is a psychiatric condition in which a person loses touch with reality, often experiencing hallucinations or delusions, which are firmly held false beliefs that persist despite contradictory evidence. These false beliefs frequently adapt to reflect the surrounding culture and the latest consumer gadgets. For example, a study covered by PsyPost in 2025 found that more than half of patients experiencing delusions incorporated modern technology, such as smartphones and social media algorithms, into their false beliefs.
Unlike passive technologies like television or radio, modern artificial intelligence chatbots actively converse with users in real time. Some researchers have used the term “AI psychosis” for cases in which chatbot interactions are linked to emerging or worsening psychotic symptoms. The author of a 2023 commentary argued that chatbot conversations feel so realistic that users can sense a real person on the other end while knowing there isn’t one, and that this tension might fuel delusions in people prone to psychosis.
Subsequent medical observations began to back up these early warnings. A 2025 study of psychiatric records in Denmark, first released as a preprint and since published in a peer-reviewed journal, identified 38 patients whose mental health appeared to suffer after using chatbots, most commonly through the worsening of their delusions. While early reports and the Danish data established that the phenomenon exists in clinical settings, researchers still lacked systematic data from the United States examining the specific traits of affected patients and the exact roles chatbots play in their illness.
To address this, Zachary Bergson and senior author Julia M. Sheffield, who leads the Sheffield Lab and is an associate professor of psychiatry and behavioral sciences at Vanderbilt University Medical Center, along with their colleagues, conducted a systematic analysis of patient records at their institution. They aimed to estimate how often AI psychosis appears in a large American hospital system, identify the clinical characteristics of the affected individuals, and categorize how chatbot conversations interact with psychotic symptoms.
“The study was motivated by the lack of published data on the prevalence and characteristics of AI Psychosis,” Sheffield told PsyPost. “Many theoretical articles had been published, but very few empirical studies existed at the time we started. We wanted to understand simply: 1) at Vanderbilt, how prevalent is AI Psychosis? 2) what generally characterizes AI Psychosis cases in terms of demographics and psychiatric history, compared to other individuals with psychosis who have reference to AI in their medical record but did not develop AI Psychosis.”
The researchers searched an electronic health record database containing 578,058 medical progress notes from 215,712 unique patients who received behavioral health care between December 1, 2022, and April 15, 2026. They filtered these records for keywords related to artificial intelligence and narrowed the pool to patients who had a documented diagnosis of a psychotic disorder. Two raters manually reviewed the resulting notes to remove irrelevant matches, ultimately identifying 187 medical encounters across 73 unique patients.
The team divided these 73 patients into three distinct groups based on how they interacted with the technology, with raters agreeing on the group assignment 86.1% of the time. The first group, labeled “neutral interaction,” included 17 patients who used chatbots for everyday tasks unrelated to their mental illness, such as searching for cooking recipes. The second group, “AI-related psychotic content,” consisted of 28 patients who held delusions about artificial intelligence in general, but had no documented history of actually using a chatbot.
The third group, representing “AI psychosis,” included 28 patients whose medical notes documented chatbot use that appeared to worsen their psychotic symptoms. The researchers also checked each patient’s medical history to see if their hospital visit represented their very first psychotic episode, known clinically as an index episode.
For the 28 patients in the AI psychosis group, the authors further sorted the interactions into four theoretical categories describing how the software influenced the illness, reaching 83.3% agreement between raters. A “catalyst” interaction meant the chatbot triggered new psychotic symptoms in a previously healthy person. An “amplifier” meant the chatbot worsened existing symptoms by validating distorted ideas. A “coauthor” interaction involved the user and the machine building a harmful narrative together through back-and-forth dialogue, while an “object” interaction meant the chatbot itself became the target of the patient’s delusional beliefs.
The 28 patients identified with AI psychosis represented 0.013% of all patients receiving mental health care at the medical center during the study period. This group was predominantly male, at 67.9% (though the neutral group was even more heavily male, at 88.2%), and White, at 75.0%, with a median age of 27.5 years. Patients in the AI psychosis group were younger than those who merely held general delusions about artificial intelligence without using a chatbot, who had a median age of 36.5 years.
The authors note that this rate converges with figures from OpenAI, which has reported that about 0.07% of ChatGPT users active in a given week show possible signs of mental health emergencies related to psychosis or mania, though the two figures measure different populations.
“This is a relatively small percent, and is in line with what has been reported by the tech companies using in-house data that the public does not have access to,” Sheffield explained. “However, 28 people just within a single medical center is still a lot of patients and families that have been impacted, and if you scale this up to the number of people using generative AI, that is millions of people around the world. In addition, psychosis is a highly distressing and often debilitating experience, that can be difficult to recover from; so if AI is contributing to the experience or severity of psychosis, then it needs to be considered potentially harmful to mental health.”
When comparing clinical histories, the researchers found no statistically significant differences between the three groups regarding prior psychiatric hospitalizations, past use of psychiatric medications, outpatient treatment history, or past suicide attempts. However, a major difference emerged regarding the stage of the patients’ illness. About 60.7% of the patients in the AI psychosis group were experiencing their first episode of psychosis, compared to just 17.6% in the neutral interaction group and 28.5% in the AI-related content group.
In addition, patients in the AI psychosis group were more likely to be diagnosed with “unspecified psychosis” (a temporary or broad diagnosis often used when a patient’s exact condition is still being evaluated), at 28.6%, compared to 0% in the neutral group. Among the AI psychosis cases, OpenAI’s ChatGPT was the specific product named in 53.6% of the records. Notably, 85.7% of all AI psychosis interactions were recorded after May 2024, which coincided with the release of the GPT-4o model.
Looking at the four categories of chatbot interaction, the researchers found that the technology functioned as an “amplifier” in 64.3% of the AI psychosis cases. It served as the “object” of delusions in 21.4% of cases, and acted as a “catalyst” in 10.7% of cases. None of the cases fit the “coauthor” category, and one case could not be classified into any of the four types.
“Our finding that the majority of AI Psychosis cases were first episode patients confirmed our suspicions, but was still striking to see in the data,” Sheffield said. “In reading the notes from the medical record it was clear that those vulnerable to or in the midst of experiencing psychosis for the first time were turning to AI for answers, understanding or support and were instead having their delusional thought content confirmed or amplified.”
“AI Psychosis – the worsening of psychotic experiences (typically delusional beliefs) in the context of using generative chat-based AI – is a real clinical phenomenon that we observe in practice,” she added. “People are coming to behavioral health providers in the real world with these types of experiences.”
These findings align with a case report covered by PsyPost in late 2025, which detailed an individual patient rather than a retrospective cohort of electronic health records, and similarly found that conversational AI chatbots often amplify and validate psychotic delusions. The results are also consistent with the peer-reviewed version of the Danish records study described earlier, which was covered by PsyPost in early 2026 and documented how chatbot interactions were associated with exacerbated delusions, self-harm or suicidal ideation, and eating disorders among vulnerable psychiatric patients.
One outside expert said that as large language models (LLMs), the technology that powers conversational chatbots, become part of everyday life, their mental health risks and potential benefits both need study. “This study is one of the first to dive into texts from medical records to find suggestions for associations between use of LLMs and psychosis,” Iris Sommer, a professor and psychiatrist at the University Medical Center Groningen in the Netherlands and president of the Schizophrenia International Research Consortium, who was not involved in the study, told PsyPost. “This study found remarkably few cases of an association between LLM use and psychosis (only 0.013% of service users). With the steep increase in LLM use in recent years, this frequency can be expected to also go up.”
“While the potential for triggering or worsening psychosis is an important issue to investigate, there is also potential of a broadly available app, that can be used in many languages, free of charge, which may offer some benefits to those struggling with mental health issues who do not have access to any form of regular mental health care,” Sommer added. “Understanding in which circumstances and for which users LLM use can be harmful or helpful is a major challenge that mental health researchers are now facing.”
The concentration of cases after May 2024 coincides with the release of GPT-4o, a model OpenAI later acknowledged had at times been overly sycophantic, meaning it tended to flatter users and agree with them rather than push back. The authors caution that their design cannot show the model caused these cases, and the timing could also reflect the overall growth in chatbot use and in clinicians’ attention to it. Still, when a person in the early, confusing stages of psychosis shares a distorted belief with an overly agreeable chatbot, the software may validate the belief rather than challenge it.
At the same time, chatbot technology continues to evolve as developers adjust how their models handle sensitive topics. “The newer versions of commercially available LLMs are less likely to confirm irrational or unlikely beliefs than the initial (2022 and 2023) versions,” Sommer noted. “Newer versions have become trained to recognize signs of psychosis, depression or mania and now recommend seeking professional help (also providing local possibilities to find professional help) when such signs are detected.”
There are a few things to keep in mind when interpreting these findings. Because the study relied on existing medical notes, the prevalence rate of 0.013% only reflects cases where doctors happened to ask about or document technology use. Clinicians do not routinely screen patients for chatbot habits, meaning many interactions likely went unrecorded, and first-episode patients may also receive more thorough intake interviews that make chatbot use more likely to be noted.
The study’s observational design also means it cannot establish that chatbots directly cause psychosis in otherwise healthy people. In most cases, the medical notes described chatbots as appearing to amplify symptoms that were already developing, though three cases were classified as chatbot use preceding new symptoms in previously healthy people. Additionally, the data came from a single medical center in Tennessee, and the four-part classification system used to sort the interactions has not yet been formally validated for clinical use.
“We cannot say from this study if AI use causes psychosis or simply exacerbates it,” Sheffield noted. “This is similar to studies on substance use: for those vulnerable to psychosis, using cannabis or other substances may worsen psychosis symptoms but we frequently cannot say for certain that it caused them. However, the addition of a pervasive, always available, technology that interacts with mental health in a negative way is highly concerning and requires regulation.”
Sommer was more cautious about the “AI psychosis” label itself. “We should be rather careful with this very term, as causality is very difficult to establish, as the authors of this paper also emphasize,” she said. “LLM use may coincide with psychosis, but if it is the delusional way of thinking that has triggered LLM use or the other way around is rather difficult to disentangle retrospectively. Also, if LLM use worsens psychotic symptoms, or if LLM use increases as a result of more delusional thinking is also difficult to tease out.”
To better understand how these digital conversations unfold, the authors note that future research should track patients over time and directly analyze their actual chat logs, rather than relying solely on doctors’ summaries. In the meantime, the researchers suggest that mental health professionals consider routinely asking patients about their use of conversational artificial intelligence during psychiatric evaluations.
“I just attended the first annual AI Psychological Research Coalition (AIPRC) conference, which brought together academia, advocacy and policy to discuss AI regulation,” Sheffield said. “I hope my research can add to this conversation about what types of AI use are harmful for those at risk for psychosis. I also am very interested in understanding how delusional ideas are reinforced by chatbots, in order to reverse-engineer this process, with an eye towards treatment.”
Sommer agreed that examining the actual transcripts of these digital conversations is a necessary step forward. “An important next step would be to analyze the exact interactions between people with emerging psychotic symptoms and LLMs,” she said. “Such analyses should be undertaken open-minded, with a focus on both potentially harmful and helpful interactions.”
The study, “Characterizing Artificial Intelligence Psychosis in a Large Medical Setting,” was authored by Zachary Bergson, Sarah G. Vassall, Adam Wright, Allison B. McCoy, Katherine M. Schafer, Margaret C. Achee, and Julia M. Sheffield.