JMIR Formative Research

Recent advances in AI, particularly large language models, have generated growing interest in their application to medical education and examination preparation. However, the accuracy, reasoning quality, and adherence to clinical guidelines of these tools in postgraduate urology assessments remain unclear.

Breast augmentation is one of the most performed aesthetic surgical procedures worldwide. Given its elective character and potential complications, clear and comprehensible informed consent is essential.

Despite widespread discussion of opportunities and risks about AI in medicine, few health care professionals routinely used AI during this study period. Physicians and men were more likely to report frequent AI use, and frequent AI users more often reported positive sentiments about AI’s future impacts on pay, enjoyment, and productivity at work. The youngest professionals (≤29 years) were less engaged and more skeptical about AI’s future benefits. These findings highlight a gap between AI’s promise and medical practice, as adoption varies by role, experience, and demographics.

AI is increasingly being explored as a tool to enhance efficiency, access, and diagnostic accuracy in mental health care. However, the perspectives of clinicians, who are central to the delivery and oversight of care, on the use of AI remain underexamined.

A multilayered fraud-mitigation approach is essential to ensure data integrity in medical survey research; basic measures alone (eg, CAPTCHA) would permit widespread fraud.

National digital health systems are increasingly recognized as a key tool for strengthening health care systems and improving patient outcomes. Global guidance from the World Health Organization and European Union initiatives emphasizes interoperability, robust data governance, and secure exchange of health information as prerequisites for system-wide benefits. However, translating these principles into operational national digital health infrastructures remains challenging, and empirical evidence on long-term, centralized implementation models is limited. Lithuania is among a small number of European countries that have implemented a fully centralized national digital health platform (DHP), providing a valuable case for examining the development, structure, and performance of such systems.

In the United States and worldwide, chronic pain affects a vast number of people and is one of the leading reasons adults seek medical care. In the United States, 24.3% of adults reported experiencing chronic pain in the prior 3 months in 2023. Chronic pain is defined as pain that lasts ≥3 months, significantly disrupting one’s daily functioning and quality of life. Chronic pain can also be accompanied by other conditions, including anxiety and depression. Health care providers should be aware of several limitations in their current treatment modalities. Although opioid analgesics are used for moderate to severe pain management, they cause many serious adverse effects, including sedation, respiratory depression, constipation, and a high risk of dependence and addiction. Other pain medications, such as nonopioid analgesics, including nonsteroidal anti-inflammatory drugs, adjuvant analgesics, and corticosteroids, also cause a range of side effects and organ toxicity.

AI is increasingly integrated into medical education, offering new ways for students to acquire knowledge and support clinical reasoning. However, the extent, patterns, and implications of AI use among medical students remain incompletely understood. Prior studies have relied on retrospective surveys that are susceptible to recall bias and have not quantified AI use as a proportion of total study time.

Health care professional–generated vignettes are commonly used to illustrate and analyze patient experiences, shaped through clinical reflection to support provider understanding, training, and practice improvement. However, the subjective interpretation of narratives and the time-consuming manual process limit this approach. As an alternative, patients could record video blogs (vlogs) of their experiences, which can then be transformed into vignettes using GenAI and carefully designed prompts.

Popular discourse often frames prescription stimulants Ritalin and Adderall as drugs for teens and emerging adults with greater financial resources (eg, students or young professionals), while illicit stimulants such as crack or methamphetamine are often considered drugs for older adults with lower incomes. Crack and methamphetamine are also frequently used in combination with opioids to offset the sedating effects of adulterants such as fentanyl and xylazine in the unregulated drug supply. This combination of stimulant and opioid use creates additional overdose risks and may require new public health approaches. Our team posited that creating effective messages to protect against overdose in the context of stimulant use entailed first developing a better understanding of which stimulants people are using in combination with opioids.

Respiratory inductance plethysmography (RIP) belts are the standard for measuring thoracoabdominal movements in home sleep apnea testing (HSAT), but are often cumbersome and power-intensive.

Large language models (LLMs) have shown promising performance on medical examinations across specialties. However, comparative evaluations of current-generation LLMs across multiple European anesthesiology examinations, alongside structured assessment of hallucinations vs question-related confusion, remain lacking.