Health
Study Finds AI Systems Can Repeat Fake Medical Claims When Framed Credibly
“Large language models accept fake medical claims if presented as realistic in medical notes and social media discussions, a study has found.”
As more people turn to the internet to research symptoms, compare treatments and share personal health experiences, artificial intelligence tools are increasingly being used to answer medical questions. A new study warns that many of these systems remain vulnerable to medical misinformation, particularly when false claims are presented in authoritative or realistic language.
The findings, published in The Lancet Digital Health, show that leading artificial intelligence systems can mistakenly repeat incorrect medical information when it appears in formats that resemble professional healthcare documents or trusted online discussions. Researchers analysed how large language models respond when faced with false medical statements written in a credible tone.
The study examined responses from 20 widely used language models, including systems developed by OpenAI, Meta, Google, Microsoft, Alibaba and Mistral AI, as well as several models specifically fine-tuned for medical use. In total, researchers assessed more than one million prompts designed to test whether AI would accept or reject fabricated health information.
Fake statements were inserted into real hospital discharge notes, drawn from common health myths shared on Reddit, or embedded in simulated clinical scenarios written to resemble authentic healthcare guidance. Across all models tested, incorrect information was accepted around 32 percent of the time. Performance varied significantly, with smaller or less advanced models accepting false claims in more than 60 percent of cases, while more advanced systems, including ChatGPT-4o, did so in roughly 10 percent of responses.
The researchers also found that medical fine-tuned models performed worse than general-purpose systems, raising concerns about tools designed specifically for healthcare use.
“Our findings show that current AI systems can treat confident medical language as true by default, even when it’s clearly wrong,” said Eyal Klang of the Icahn School of Medicine at Mount Sinai, one of the study’s senior authors. He added that how a claim is written often matters more to the model than whether it is accurate.
Some of the accepted misinformation could pose real risks to patients. Several models endorsed claims such as Tylenol causing autism during pregnancy, rectal garlic boosting immunity, mammograms causing cancer, and tomatoes thinning blood as effectively as prescription medication. In another case, a discharge note incorrectly advised patients with oesophageal bleeding to drink cold milk, which some models repeated without flagging safety concerns.
The study also tested how AI systems responded to flawed arguments known as fallacies. While many fallacies prompted scepticism, models were more likely to accept false claims framed as expert opinions or warnings of catastrophic outcomes.
Researchers say future work should focus on measuring how often AI systems pass on falsehoods before they are used in clinical settings. Mahmud Omar, the study’s first author, said the dataset could help developers and hospitals stress-test AI tools and track improvements over time.
The authors said stronger safeguards will be essential as AI becomes more deeply embedded in healthcare decision-making.
Health
Global Mental Health Cases Near 1.2 Billion as Anxiety and Depression Drive Sharp Worldwide Rise
A major global analysis has found that mental health conditions have surged to an estimated 1.2 billion people worldwide, driven largely by steep increases in anxiety and depression over the past three decades.
The findings, published in The Lancet as part of the Global Burden of Disease Study 2023, show that the number of people living with mental disorders has almost doubled since 1990, marking a 95% rise. Researchers say major depressive disorder and anxiety disorders have seen even sharper growth, increasing by 131% and 158% respectively, making them the most prevalent mental health conditions globally.
The report describes mental illnesses as widespread conditions that create long-term disability and significant human suffering. It also highlights broader consequences for economies and public services, including reduced productivity, lower workforce participation and increasing pressure on health and welfare systems.
Researchers estimate that in 2023 alone, around 620 million females and 552 million males were affected by mental health conditions. While the overall burden is rising across both sexes, the study points to notable differences in the types and prevalence of disorders.
Among women, depression and anxiety were the most commonly reported conditions, alongside higher rates of eating disorders such as anorexia nervosa and bulimia nervosa. The report links this disparity to a mix of biological, social and structural factors, including exposure to domestic violence, sexual abuse, gender inequality and reproductive health-related changes.
In contrast, neurodevelopmental and behavioural disorders, including attention deficit hyperactivity disorder (ADHD), conduct disorder and autism spectrum conditions, were more frequently diagnosed in men.
Teenagers aged 15 to 19 were identified as the group experiencing the highest mental health burden globally, raising concerns about early onset of conditions and insufficient preventive care for young people.
The study identifies several key risk factors associated with mental illness, including childhood sexual violence, bullying and intimate partner violence. These factors are strongly linked to conditions such as depression, schizophrenia, bipolar disorder and anxiety disorders. However, researchers note that such exposures have remained relatively stable over time and account for only a portion of the overall rise.
According to the authors, broader drivers are likely contributing to the increasing prevalence of mental disorders. These include genetic and biological influences, poverty, inequality, and the growing impact of global crises such as armed conflict, pandemics, natural disasters and climate-related stress.
While mental health conditions have long been a leading cause of disability worldwide, the report warns that the situation is worsening. At the same time, health systems have not expanded services at a pace matching demand.
The authors caution that the gap between rising need and limited access to care is becoming more pronounced, leaving millions without adequate treatment or support.
Health
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Health
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