JMIRx Med

White spot lesions (WSL) are white marks that can form on teeth during orthodontic treatment with fixed appliances (FA) and become apparent once they are removed. About half of people who have FA treatment get WSLs. They are usually caused by poor tooth-brushing around the brace. Although there have been studies that have investigated the prevention and treatment for WSL, there remain uncertainties about what young people and their parents or guardians know or feel about them. A Cochrane review concluded that patient-reported outcomes have been overlooked in WSL prevention studies.

This is a peer review report related to "Challenges in Implementing a Mobile AI Chatbot Intervention for Depression Among Youth on Psychiatric Waiting Lists: A Randomized Control Study Termination Report"

This is a peer review report related to "Challenges in Implementing a Mobile AI Chatbot Intervention for Depression Among Youth on Psychiatric Waiting Lists: A Randomized Control Study Termination Report"

This is the author(s)' response to peer review reports related to [manuscript title "Challenges in Implementing a Mobile AI Chatbot Intervention for Depression Among Youth on Psychiatric Waiting Lists: A Randomized Control Study Termination Report"

The mental health of children and adolescents is a growing public health concern, with increasing rates of depression and anxiety impacting their emotional, social, and academic well-being. In Japan, access to timely psychiatric care is limited, leading to extended waiting periods that can range from three months to a year. AI-driven chatbots, such as emol, which integrate Acceptance and Commitment Therapy (ACT), show potential as digital solutions to support young patients during these waiting times. The AI chatbot emol was selected based on a comprehensive review of Japanese mental health technology applications, including in-person evaluations with company representatives.

This is a peer review report related to "Challenges in Implementing a Mobile AI Chatbot Intervention for Depression Among Youth on Psychiatric Waiting Lists: A Randomized Control Study Termination Report"

This is the author(s)' response to peer review reports related to "Rapidly benchmarking Large Language Models for diagnosing comorbid patients: A comparative study leveraging the LLM-as-a-judge method"

On average, one in ten patients die because of a diagnostic error and medical errors are the third largest cause of death in the US. While LLMs have been proposed to help doctors with diagnoses, no research results have been pub-lished on comparing the diagnostic ability of many popular LLMs on a large, openly accessible real-patient cohort.