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“Digital Clinicians” Performing Obesity Medication Self-Injection Education: Feasibility Randomized Controlled Trial

“Digital Clinicians” Performing Obesity Medication Self-Injection Education: Feasibility Randomized Controlled Trial

Artificial Intelligence (AI) chatbots have the potential to be used for a variety of medical tasks, including note taking [15] and personalized medicine [16]. Anonymized AI chatbots have been judged to provide better, more concise, empathetic answers to general health queries than verified physicians [17]. Chat GPT-3 is known to be accurate with common chief complaints [18] and GPT-4 recently outscored 99.98% of simulated human readers when diagnosing complex clinical cases [19].

Sean Coleman, Caitríona Lynch, Hemendra Worlikar, Emily Kelly, Kate Loveys, Andrew J Simpkin, Jane C Walsh, Elizabeth Broadbent, Francis M Finucane, Derek O' Keeffe

JMIR Diabetes 2025;10:e63503

Generative AI–Powered Mental Wellness Chatbot for College Student Mental Wellness: Open Trial

Generative AI–Powered Mental Wellness Chatbot for College Student Mental Wellness: Open Trial

DMHIs refer to a range of health information technologies (eg, websites, mobile apps, and chatbots) designed to intervene in health conditions by changing behaviors, cognitions, and emotional states [8]. Among these, chatbots stand out as artificial intelligence (AI)–driven tools capable of engaging in human-like conversations.

Jazmin A Reyes-Portillo, Amy So, Kelsey McAlister, Christine Nicodemus, Ashleigh Golden, Colleen Jacobson, Jennifer Huberty

JMIR Form Res 2025;9:e71923

Population-Based Digital Health Interventions to Deliver at-Home COVID-19 Testing: SCALE-UP II Randomized Clinical Trial

Population-Based Digital Health Interventions to Deliver at-Home COVID-19 Testing: SCALE-UP II Randomized Clinical Trial

Population-level interventions using digital health tools, such as SMS text messaging and chatbots, and coupled with a human component, are a promising approach for promoting equitable access to preventive care services. Despite disparities in access to digital technologies, cellphone ownership is now ubiquitous. Even in US households earning less than US $30,000 annually, 97% have a cellphone and 76% have a smartphone [12].

Guilherme Del Fiol, Tatyana V Kuzmenko, Brian Orleans, Jonathan J Chipman, Tom Greene, Ray Meads, Kimberly A Kaphingst, Bryan Gibson, Kensaku Kawamoto, Andy J King, Tracey Siaperas, Shlisa Hughes, Alan Pruhs, Courtney Pariera Dinkins, Cho Y Lam, Joni H Pierce, Ryzen Benson, Emerson P Borsato, Ryan C Cornia, Leticia Stevens, Richard L Bradshaw, Chelsey R Schlechter, David W Wetter

J Med Internet Res 2025;27:e74145

Evaluating the Quality of Psychotherapy Conversational Agents: Framework Development and Cross-Sectional Study

Evaluating the Quality of Psychotherapy Conversational Agents: Framework Development and Cross-Sectional Study

Traditionally, rule-based chatbots, which use scripted responses to user queries to improve mental health, have been the predominant type of chatbot used by the general public [4] and researchers [5]. Recently, generative artificial intelligence–based chatbots have emerged. These chatbots use technological advances such as large language models (LLMs) to provide more personalized and human-like responses, which has further boosted the popularity of chatbots.

Kunmi Sobowale, Daniel Kevin Humphrey

JMIR Form Res 2025;9:e65605

Using Large Language Models to Enhance Exercise Recommendations and Physical Activity in Clinical and Healthy Populations: Scoping Review

Using Large Language Models to Enhance Exercise Recommendations and Physical Activity in Clinical and Healthy Populations: Scoping Review

By using advanced AI tools such as LLMs and chatbots, ERs and PA formulation is becoming increasingly scientific and personalized [21]. This not only has the potential to optimize exercise outcomes but may also enhance safety, ushering in a new era in chronic disease prevention and health management. To our knowledge, this paper represents one of the first scoping reviews of the applications of LLMs in the fields of ERs and PA, with 2 primary objectives.

Xiangxun Lai, Jiacheng Chen, Yue Lai, Shengqi Huang, Yongdong Cai, Zhifeng Sun, Xueding Wang, Kaijiang Pan, Qi Gao, Caihua Huang

JMIR Med Inform 2025;13:e59309

Expert and Interdisciplinary Analysis of AI-Driven Chatbots for Mental Health Support: Mixed Methods Study

Expert and Interdisciplinary Analysis of AI-Driven Chatbots for Mental Health Support: Mixed Methods Study

It is increasingly imperative that we as HCI researchers analyze the diverse ways in which such chatbots, which claim to aid mental health, are promoted, described, and used, particularly given their use by at-risk users who may not fully recognize their intended purpose. This work then investigated the relationship between design and care as manifested in today’s mental health–related chatbots.

Kayley Moylan, Kevin Doherty

J Med Internet Res 2025;27:e67114

Technology-Assisted Interventions in the Delivery of HIV Prevention, Care, and Treatment Services in Sub-Saharan Africa: Scoping Review

Technology-Assisted Interventions in the Delivery of HIV Prevention, Care, and Treatment Services in Sub-Saharan Africa: Scoping Review

The extracted data were grouped into categories based on the type of digital technology used (ie, social media, mobile phone apps, health information systems, mobile SMS or SMS text messaging, chatbots, interactive voice response (IVR), and hotline.

Louis Henry Kamulegeya, Ivan Kagolo, Brenda Kabakaari, Joan Atuhaire, Racheal Nasamula, J M Bwanika

J Med Internet Res 2025;27:e68352

Authors’ Reply: The Importance of Comparing New Technologies (AI) to Existing Tools for Patient Education on Common Dermatologic Conditions: A Commentary

Authors’ Reply: The Importance of Comparing New Technologies (AI) to Existing Tools for Patient Education on Common Dermatologic Conditions: A Commentary

Our pilot study compares AI chatbot responses to potential patient questions, with the primary goal of comparing the utility of three chatbots by assessing their strengths and weaknesses. As suggested by Parker, recommending the usage of AI in place of existing patient education materials would require a larger, more robust investigation that compares AI to existing resources.

Courtney Chau, Hao Feng, Gabriela Cobos, Joyce Park

JMIR Dermatol 2025;8:e72540