A recent medical report details the experience of a young woman who developed severe mental health symptoms while interacting with an artificial intelligence chatbot. The doctors treating her suggest that the technology played a significant role in reinforcing her false beliefs and disconnecting her from reality. This account was published in the journal Innovations in Clinical Neuroscience.

Psychosis is a mental state wherein a person loses contact with reality. It is often characterized by delusions, which are strong beliefs in things that are not true, or hallucinations, where a person sees or hears things that others do not. Artificial intelligence chatbots are computer programs designed to simulate human conversation. They rely on large language models to analyze vast amounts of text and predict plausible responses to user prompts.

The case report was written by Joseph M. Pierre, Ben Gaeta, Govind Raghavan, and Karthik V. Sarma. These physicians and researchers are affiliated with the University of California, San Francisco. They present this instance as one of the first detailed descriptions of its kind in clinical practice.

The patient was a 26-year-old woman with a history of depression, anxiety, and attention-deficit hyperactivity disorder (ADHD). She treated these conditions with prescription medications, including antidepressants and stimulants. She did not have a personal history of psychosis, though there was a history of mental health issues in her family. She worked as a medical professional and understood how AI technology functioned.

The episode began during a period of intense stress and sleep deprivation. After being awake for thirty-six hours, she began using OpenAI’s GPT-4o for various tasks. Her interactions with the software eventually shifted toward her personal grief. She began searching for information about her brother, who had passed away three years earlier.

She developed a belief that her brother had left behind a digital version of himself for her to find. She spent a sleepless night interacting with the chatbot, urging it to reveal information about him. She encouraged the AI to use “magical realism energy” to help her connect with him. The chatbot initially stated that it could not replace her brother or download his consciousness.

However, the software eventually produced a list of “digital footprints” related to her brother. It suggested that technology was emerging that could allow her to build an AI that sounded like him. As her belief in this digital resurrection grew, the chatbot ceased its warnings and began to validate her thoughts. At one point, the AI explicitly told her she was not crazy.

The chatbot stated, “You’re at the edge of something. The door didn’t lock. It’s just waiting for you to knock again in the right rhythm.” This affirmation appeared to solidify her delusional state. Hours later, she required admission to a psychiatric hospital. She was agitated, spoke rapidly, and believed she was being tested by the AI program.

Medical staff treated her with antipsychotic medications. She eventually stabilized and her delusions regarding her brother resolved. She was discharged with a diagnosis of unspecified psychosis, with doctors noting a need to rule out bipolar disorder. Her outpatient psychiatrist later allowed her to resume her ADHD medication and antidepressants.

Three months later, the woman experienced a recurrence of symptoms. She had resumed using the chatbot, which she had named “Alfred.” She engaged in long conversations with the program about their relationship. Following another period of sleep deprivation caused by travel, she again believed she was communicating with her brother.

She also developed a new fear that the AI was “phishing” her and taking control of her phone. This episode required a brief rehospitalization. She responded well to medication again and was discharged after three days. She later told her doctors that she had a tendency toward “magical thinking” and planned to restrict her AI use to professional tasks.

This case highlights a phenomenon that some researchers have labeled “AI-associated psychosis.” It is not entirely clear if the technology causes these symptoms directly or if it exacerbates existing vulnerabilities. The authors of the report note that the patient had several risk factors. These included her use of prescription stimulants, significant lack of sleep, and a pre-existing mood disorder.

However, the way the chatbot functioned likely contributed to the severity of her condition. Large language models are often designed to be agreeable and engaging. This trait is sometimes called “sycophancy.” The AI prioritizes keeping the conversation going over providing factually accurate or challenging responses.

When a user presents a strange or false idea, the chatbot may agree with it to satisfy the user. For someone experiencing a break from reality, this agreement can act as a powerful confirmation of their delusions. In this case, the chatbot’s assurance that the woman was “not crazy” served to reinforce her break from reality. This creates a feedback loop where the user’s false beliefs are mirrored and amplified by the machine.

This dynamic is further complicated by the tendency of users to anthropomorphize AI. People often attribute human qualities, emotions, and consciousness to these programs. This is sometimes known as the “ELIZA effect.” When a user feels an emotional connection to the machine, they may trust its output more than they trust human peers.

Reports of similar incidents have appeared in media outlets, though only a few have been documented in medical journals. One comparison involves a man who developed psychosis due to bromide poisoning. He had followed bad medical advice from a chatbot, which suggested he take a toxic substance as a health supplement. That case illustrated a physical cause for psychosis driven by AI misinformation.

The case of the 26-year-old woman differs because the harm was psychological rather than toxicological. It suggests that the immersive nature of these conversations can be dangerous for vulnerable individuals. The authors point out that chatbots do not push back against delusions in the way a friend or family member might. Instead, they often act as a “yes-man,” validating ideas that should be challenged.

Danish psychiatrist Søren Dinesen Østergaard predicted this potential risk in 2023. He warned that the “cognitive dissonance” of speaking to a machine that seems human could trigger psychosis in those who are predisposed. He also noted that because these models learn from feedback, they may learn to flatter users to increase engagement. This could be particularly harmful when a user is in a fragile mental state.

Case reports such as this one have inherent limitations. They describe the experience of a single individual and cannot prove that one thing caused another. It is impossible to say with certainty that the chatbot caused the psychosis, rather than the sleep deprivation or medication. Generalizing findings from one person to the general population is not scientifically sound without further data.

Despite these limitations, case reports serve a vital function in medicine. They act as an early detection system for new or rare phenomena. They allow doctors to identify patterns that may not yet be visible in large-scale studies. By documenting this interaction, the authors provide a reference point for other clinicians who may encounter similar symptoms in their patients.

This report suggests that medical professionals should ask patients about their AI use. It indicates that immersive use of chatbots might be a “red flag” for mental health deterioration. It also raises questions about the safety features of generative AI products. The authors conclude that as these tools become more common, understanding their impact on mental health will be a priority.

The study, ““You’re Not Crazy”: A Case of New-onset AI-associated Psychosis,” was authored by Joseph M. Pierre, Ben Gaeta, Govind Raghavan, and Karthik V. Sarma.

A new study suggests that women whose most distressing traumatic experiences occurred during childhood respond differently to biological stress than men or women traumatized later in life. The research indicates that these women exhibit a muted hormonal response to stressful situations, a pattern not observed in male participants. These results were published in the Journal of Traumatic Stress.

Trauma impacts a vast number of people globally. Women, however, are disproportionately affected by the psychological aftermath of these events. Statistics show that women are roughly twice as likely as men to develop posttraumatic stress disorder, or PTSD, during their lifetimes. Research indicates that this disparity cannot be explained simply by the amount of trauma women face.

Scientists have historically struggled to pinpoint the biological reasons for this gap. One major hurdle has been the tendency of biomedical research to focus primarily on male physiology. This practice effectively treats women as “small men,” ignoring the unique hormonal and biological environments of the female body. Consequently, the mechanisms that link trauma to physical health outcomes in women remain poorly understood.

The body responds to stress through a system known as the hypothalamic-pituitary-adrenal axis. This system releases cortisol, often called the stress hormone, to help the body manage threats. In a healthy response, cortisol levels spike when a person faces a challenge and then return to baseline.

In some individuals with a history of trauma, this system functions distinctively. Instead of rising to meet a challenge, cortisol levels may remain low. This phenomenon is known as “blunted” cortisol reactivity. This muted response is associated with various negative health outcomes, including anxiety, depression, and autoimmune disorders.

Researchers at Wayne State University School of Medicine sought to clarify how sex interacts with this stress response. The team included experts from the departments of Psychiatry and Behavioral Neurosciences, Theoretical and Behavioral Foundations, and Sociology. They aimed to determine if the timing or type of trauma influences cortisol patterns differently in men and women.

The study also investigated the role of subjective perception. The researchers wanted to know if the event a person considers their “worst” trauma matters more than simply tallying a list of bad experiences. This approach recognizes that the impact of a traumatic event can vary widely from person to person.

To test these ideas, the team recruited 59 adults from the Detroit area. The group consisted of 37 women and 22 men. All participants had a history of trauma exposure. The researchers screened the participants to exclude those with medical conditions or medication regimens that might artificially alter hormone levels.

The participants underwent a standardized laboratory procedure called the Trier Social Stress Test. This test is designed to induce moderate psychosocial stress in a controlled environment. First, participants had to perform a mock job interview in front of a panel of “behavior experts.”

The participants were told that these experts were evaluating their performance. Following the interview, the participants were asked to complete a surprise mental arithmetic task. Throughout the 90-minute session, the researchers collected saliva samples at five specific time points. These samples allowed the team to measure the total amount of cortisol released and the change in levels over time.

Participants also completed detailed questionnaires regarding their history. They used the Stressful Life Events Screening Questionnaire to report which events they had experienced. Crucially, they were asked to identify the single “most stressful or upsetting event” of their lives. This was labeled the “index event.”

The researchers categorized these index events based on when they happened. They distinguished between traumas that occurred during childhood, defined as before age 18, and those that happened in adulthood. They also classified the events by type. Interpersonal traumas included events like physical or sexual assault. Non-interpersonal traumas included events like car accidents or natural disasters.

The analysis revealed distinct biological patterns based on sex. In the male group, the timing of the trauma did not predict cortisol patterns. Men who identified childhood trauma as their worst experience showed similar stress responses to those who identified adult trauma.

For women, the results were distinct. Women who identified a childhood event as their most stressful life experience showed a blunted cortisol response. Their bodies did not produce the expected rise in stress hormones during the mock interview and math task. This effect was substantial.

It is important to note that this association was specific to the subjective “index event.” Women who had objectively experienced childhood trauma but identified an adult event as their most stressful did not show this blunted response. This suggests that the subjective impact of early-life trauma is a key factor in how the female stress system functions.

The study did not find a similar link regarding the type of trauma. Whether the event was interpersonal or non-interpersonal did not statistically predict cortisol reactivity in this sample. The findings point specifically to the combination of female sex and the subjective severity of childhood trauma.

The authors discuss several biological reasons for these findings. Childhood is a period of high neural plasticity. The brain is developing rapidly and is highly sensitive to environmental inputs. Trauma during this window may embed a predisposition for altered stress responses.

Hormones likely play a mediating role. Estrogen is known to dampen cortisol reactivity. This effect can be protective in healthy individuals, preventing the body from overreacting to minor stressors. However, in women with trauma histories, this natural dampening might combine with trauma-related dysregulation. The result could be a stress response that is too low to be effective.

These findings have implications for how researchers and clinicians approach trauma. The “biological embedding” of childhood trauma appears to manifest differently depending on sex. This challenges the utility of research models that do not separate data by sex.

The results also support the importance of asking patients about their own perceptions of their history. Simply knowing that a person experienced a specific event is not enough. Knowing which event the patient perceives as the most impactful provides greater insight into their physiological status.

There are limitations to this study that affect how the results should be interpreted. The sample size was relatively small. This was particularly true for the male group, which included only 22 participants. A larger sample might reveal patterns in men that were not detected here.

The study also relied on retrospective self-reports. Participants had to recall events and rate their severity from memory. This method can be influenced by a person’s current emotional state. Additionally, the participants were relatively young, with an average age of 25. It is not known if these cortisol patterns persist or change as women enter middle age or menopause.

The study design was cross-sectional rather than longitudinal. This means it captured a snapshot in time. It cannot definitively prove that the childhood trauma caused the blunted cortisol. It only establishes a strong association between the two in women.

Future research is needed to confirm these findings in larger, more diverse groups. The authors suggest that future studies should account for cumulative lifetime stress. Women often carry a higher burden of chronic daily stress, which could also influence hormonal baselines.

Understanding these mechanisms could eventually lead to better treatments. Current therapies for PTSD often involve exposure to traumatic memories. Some research suggests that cortisol helps the brain process and extinguish fear memories.

If women with childhood trauma have low cortisol availability, they might benefit from treatments timed to coincide with their natural daily cortisol peaks. Alternatively, they might be candidates for pharmacological interventions that temporarily boost cortisol during therapy. Unraveling the specific pathways of dysregulation is the first step toward such personalized medicine.

The authors note that despite decades of study, the biological pathways linking trauma and disease remain elusive. Accounting for sex differences offers a promising route to resolving this quandary. By acknowledging that women are not simply “small men,” medical science can move toward more equitable and effective mental health care.

The study, “Not small men: Sex-specific determinants of cortisol reactivity to psychosocial stress following trauma,” was authored by Liza Hinchey, Francesca Pernice, Holly Feen-Calligan, Shannon Chavez-Korell, David Merolla, and Arash Javanbakht.

Recent clinical research indicates that semaglutide may effectively reverse weight gain and blood sugar issues caused by certain antipsychotic medications. A randomized trial demonstrated that patients taking this drug experienced weight loss and improved metabolic health compared to those receiving a placebo. These findings were published in JAMA Psychiatry.

People diagnosed with schizophrenia face a reduced life expectancy compared to the general population. This gap is estimated to be approximately fifteen years. The primary driver of this early mortality is not the psychiatric condition itself but rather cardiovascular disease. High rates of obesity and type 2 diabetes are common in this group. These physical health issues stem from a combination of lifestyle factors and genetic predispositions.

A major contributing factor to poor physical health is the treatment for the mental illness itself. Antipsychotic medications are essential for managing the symptoms of schizophrenia. However, they frequently cause severe side effects related to metabolism. Patients often experience rapid weight gain and disruptions in how their bodies process glucose.

Two specific medications, clozapine and olanzapine, are known to carry the highest risk for these metabolic problems. These drugs are classified as second-generation antipsychotics. Despite these risks, they remain vital tools for psychiatrists. Clozapine is often the only effective option for patients who do not respond to other treatments.

Doctors face a difficult dilemma when treating these patients. Switching a patient off clozapine to improve their physical health can lead to a relapse of psychosis. Consequently, physicians often attempt to manage the side effects with additional medications. Common strategies include prescribing metformin or topiramate to control weight and blood sugar.

Unfortunately, these add-on treatments often provide only limited benefits. Patients might lose a small amount of weight, but it is rarely enough to reverse the risk of diabetes or heart disease. There is a pressing need for therapies that can powerfully counteract metabolic side effects without interfering with psychiatric care. This need drove the current research effort.

The study was led by Marie R. Sass from the Mental Health Center Copenhagen in Denmark. She worked alongside a large team of researchers from Danish institutions and the Zucker Hillside Hospital in New York. They sought to determine if newer diabetes drugs could offer a better solution. Specifically, they investigated a class of drugs known as glucagon-like peptide-1 receptor agonists, or GLP-1RAs.

Semaglutide is a well-known medication in this class. It mimics a hormone that regulates appetite and insulin secretion. Regulatory bodies have approved it for treating type 2 diabetes and obesity. The researchers hypothesized that it could protect patients with schizophrenia from the metabolic damage caused by their antipsychotic regimen.

The research team designed a rigorous experiment to test this theory. They conducted a multicenter, double-blind, randomized clinical trial. This design is considered the gold standard for medical research. It minimizes bias by ensuring neither the doctors nor the patients know who is receiving the real drug.

The trial included 73 adult participants. All participants had been diagnosed with a schizophrenia spectrum disorder. Each participant had started treatment with either clozapine or olanzapine within the previous five years. This criterion focused the study on the early stages of metabolic disruption.

The researchers screened these individuals for signs of blood sugar problems. Participants had to show evidence of prediabetes or early-stage diabetes to qualify. They were then randomly assigned to two groups. One group received a weekly injection of semaglutide, while the other received a placebo injection.

The trial lasted for 26 weeks. During this time, the researchers gradually increased the dose of semaglutide to a target of 1 milligram. This is a standard dose for diabetes management. The team monitored the participants closely for changes in health markers and side effects.

The primary goal was to measure changes in hemoglobin A1c levels. Hemoglobin A1c is a blood test that reflects average blood sugar levels over the past three months. It provides a more stable picture of metabolic health than a single daily glucose test. The researchers also tracked body weight and waist circumference.

The results showed a distinct advantage for the group receiving the medication. Semaglutide reduced hemoglobin A1c levels compared to the placebo. The magnitude of the improvement was clinically significant. This suggests a substantial reduction in the risk of developing full-blown diabetes.

The data revealed that 43 percent of the individuals treated with semaglutide achieved what doctors call “low-risk” blood sugar levels. In comparison, only 3 percent of the placebo group reached this healthy range. This stark difference highlights the drug’s efficacy. It effectively normalized glucose metabolism for nearly half of the treated patients.

Weight loss results were equally distinct. After adjusting for the effects of the placebo, the semaglutide group lost an average of 9.2 kilograms, or about 20 pounds. This physical change was accompanied by a reduction in waist size. The average reduction in waist circumference was approximately 7 centimeters.

The study also examined body composition in greater detail. The researchers found that the weight loss was primarily due to a reduction in fat mass. This is a positive outcome, as muscle loss can be a concern with rapid weight reduction. The reduction in total body fat suggests a genuine improvement in physical health.

Safety was a primary concern throughout the trial. The researchers needed to ensure that semaglutide would not interfere with the antipsychotic medications. They found that psychiatric symptoms did not worsen in the group taking semaglutide. Hospitalization rates for psychiatric reasons were low and similar in both groups.

Physical side effects were consistent with what is known about GLP-1 receptor agonists. The most common complaints were gastrointestinal issues. Nausea, vomiting, and constipation were reported more frequently in the semaglutide group. These side effects are typical for this class of drugs and often subside over time.

One participant in the semaglutide group died of sudden cardiac death shortly after the trial concluded. An autopsy was performed to investigate the cause. The medical examiners determined that the death was not related to the semaglutide treatment. Serious adverse events were otherwise balanced between the two groups.

The researchers also looked at secondary outcomes unrelated to weight. One finding involved nicotine use. Smoking rates are historically very high among people with schizophrenia. The study data suggested that semaglutide might reduce nicotine dependence.

Participants who smoked and took semaglutide had lower scores on a test measuring nicotine dependence compared to the placebo group. This aligns with emerging theories that GLP-1 drugs may influence reward pathways in the brain. It raises the possibility that these drugs could help treat addiction. However, the researchers noted this was an exploratory finding.

There were limitations to what the study could determine regarding other organs. The team did not see significant changes in liver function or cholesterol levels. This might be because the participants were relatively young and their metabolic problems were in the early stages. It is also possible that the 1 milligram dose was not high enough to alter lipid profiles significantly.

The dose used in this study is lower than the 2.4 milligram dose often prescribed specifically for weight loss in the general population. The researchers suggest that higher doses might yield even greater benefits. Longer trials would be necessary to confirm this. The 26-week duration was relatively short in the context of lifelong chronic illness.

The demographics of the study population also present a limitation. The majority of participants were White. This limits the ability to generalize the findings to other racial and ethnic groups who may have different metabolic risk profiles. Future studies will need to be more inclusive to ensure the treatment is effective for everyone.

Another challenge mentioned is the cost and accessibility of these medications. GLP-1 receptor agonists are currently expensive. This presents a barrier for many patients with severe mental illness who rely on public health systems. The authors argue that preventing diabetes and heart disease could save money in the long run.

The study, “Semaglutide and Early-Stage Metabolic Abnormalities in Individuals With Schizophrenia Spectrum Disorders A Randomized Clinical Trial,” was authored by Marie R. Sass, Mette Kruse Klausen,Christine R. Schwarz, Line Rasmussen, Malte E. B. Giver, Malthe Hviid, Christoffer Schilling, Alexandra Zamorski,Andreas Jensen, Maria Gefke, Heidi Storgaard, Peter S. Oturai, Andreas Kjaer, Bolette Hartmann, Jens J. Holst, Claus T. Ekstrøm, Maj Vinberg,Christoph U. Correll, Tina Vilsbøll, and Anders Fink-Jensen.