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Dying in Darkness: Deviations From Data Sharing Ethics in the US Public Health System and the Data Genocide of American Indian and Alaska Native Communities

In this paper we explore how these barriers perpetuate health inequities, examine the ethical dimensions of data sharing, and argue for a “share by default” model that aligns with public health ethics, respects Tribal sovereignty, and ensures the provision of timely, actionable information for American Indian and Alaska Native communities.

Cason D Schmit, Meghan Curry O’Connell, Sarah Shewbrooks, Charles Abourezk, Fallon J Cochlin, Megan Doerr, Hye-Chung Kum

J Med Internet Res 2025;27:e70983

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Ethical Use of Social Media and Sharing of Patient Information by Medical Students at a University Hospital in Saudi Arabia: Cross-Sectional Survey

We obtained institutional review board approval to conduct the study from KAU’s Ethics Committee (reference #414-‐22). The online survey began with an informed consent statement that explained the purpose of the questionnaire and assured participants that all information would be kept confidential with no names or contact details recorded in the survey. Participation was entirely voluntary, with no reward for completing the survey and no penalty for choosing not to participate.

Sara Farsi, Alaa Sabbahi, Deyala Sait, Raghad Kabli, Ghaliah Abduljabar

JMIR Med Educ 2025;11:e57812

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Studying the Potential Effects of Artificial Intelligence on Physician Autonomy: Scoping Review

Reference 1: Medical artificial intelligence ethics: a systematic review of empirical studiesethics ai ethics ethics of artificial intelligence

John Grosser, Juliane Düvel, Lena Hasemann, Emilia Schneider, Wolfgang Greiner

JMIR AI 2025;4:e59295

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Exploring the Ethical Challenges of Conversational AI in Mental Health Care: Scoping Review

The search combined variations of 3 elements: embodied AI, ethics, and mental health, separated by AND commands. See Multimedia Appendix 2 for detailed information on the search strategy. We included articles discussing the ethical challenges of AI-driven conversational agents functioning in the role of therapists, for persons coping with mental health issues, whether in clinical or nonclinical (eg, commercial) settings.

Mehrdad Rahsepar Meadi, Tomas Sillekens, Suzanne Metselaar, Anton van Balkom, Justin Bernstein, Neeltje Batelaan

JMIR Ment Health 2025;12:e60432

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Physician Perspectives on the Potential Benefits and Risks of Applying Artificial Intelligence in Psychiatric Medicine: Qualitative Study

Reference 12: Evidence, ethics and the promise of artificial intelligence in psychiatryethics

Austin M Stroud, Susan H Curtis, Isabel B Weir, Jeremiah J Stout, Barbara A Barry, William V Bobo, Arjun P Athreya, Richard R Sharp

JMIR Ment Health 2025;12:e64414

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Ethical Considerations for Wastewater Surveillance Conducted by the US Department of Defense

Further, there is a public health ethics principle, which argues that a public health program should use the least invasive or minimally burdensome (to the population being targeted by the program) methods to accomplish its goals [16,34]. Service members already forgo significant autonomy afforded to civilians; therefore, any public health program that might additionally strip away their autonomy must be seriously deliberated before implementation.

Hunter Jackson Smith, Richard T Agans, William J Kowallis

JMIR Public Health Surveill 2025;11:e67145

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Assessing Familiarity, Usage Patterns, and Attitudes of Medical Students Toward ChatGPT and Other Chat-Based AI Apps in Medical Education: Cross-Sectional Questionnaire Study

The current survey was modified based on earlier published research [5,6]; the published surveys were chosen in accordance with the IDEE (Identify, Discern, Ethics, Engage) framework, which evaluates how students utilize chat-based AI to achieve specific educational goals, assesses the perceived level of AI integration, examines the effectiveness of AI tools, and explores the ethical considerations involved.

Safia Elwaleed Elhassan, Muhammad Raihan Sajid, Amina Mariam Syed, Sidrah Afreen Fathima, Bushra Shehroz Khan, Hala Tamim

JMIR Med Educ 2025;11:e63065

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Authors' Reply: Commentary on “Protecting User Privacy and Rights in Academic Data-Sharing Partnerships: Principles From a Pilot Program at Crisis Text Line”

We published this paper to share with the field our experiences, ethical process, judgment calls, and lessons from a 2016-2017 data-sharing pilot, understanding that science and ethics advance through publication, critique, and refinement. Our article explicitly pertains to “noncommercial use of data” for the purposes of research and evaluation. The article neither addresses nor endorses use of Crisis Text Line data for commercial purposes.

Anthony R Pisani, Carlos Gallo, Madelyn S Gould, Nitya Kanuri, John E Marcotte, Brian Pascal, David Rousseau, Megan L Ranney, Bob Filbin, Shairi Turner

J Med Internet Res 2025;27:e59734

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Evaluating and Enhancing Japanese Large Language Models for Genetic Counseling Support: Comparative Study of Domain Adaptation and the Development of an Expert-Evaluated Dataset

Aligned with consensus No consensus Opposed to consensus This research was approved by Kobe City Medical Center General Hospital, after ethics approval, including the Nara Institute of Science and Technology (review ezn240501). The evaluation results of the JGCLLM by the 2 certified genetic counselors and 1 ophthalmologist (SK, YU, and AY) are shown in Figure 2 comprising 120 questions with 4 types of responses, for a total of 480 responses divided among 3 persons.

Takuya Fukushima, Masae Manabe, Shuntaro Yada, Shoko Wakamiya, Akiko Yoshida, Yusaku Urakawa, Akiko Maeda, Shigeyuki Kan, Masayo Takahashi, Eiji Aramaki