Accessibility settings

This paper is in the following e-collection/theme issue:

Theme Issue (2024): Patient and Consumer Use of Artificial Intelligence for Health (10) Clinical Information and Decision Making (2093) Decision Support for Health Professionals (1654) Design, Usability, and Evaluation of Research Instruments, Scales, and Measures (99) Clinical Communication, Electronic Consultation and Telehealth (812) Security and Privacy of mHealth and uHealth (166) User Needs and Competencies (497) Artificial Intelligence (2385) Patient Reported Measures and Outcomes in Participatory Medicine (48) Ambient AI Scribes and AI-Driven Documentation Technologies (27)

Published on in Vol 17 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69564, first published .
Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation

Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation

Patient Perspectives on Artificial Intelligence in Health Care: Focus Group Study for Diagnostic Communication and Tool Implementation

Authors of this article:

Garrett Foresman1 Author Orcid Image ;   Joshua Biro1 Author Orcid Image ;   Alberta Tran2 Author Orcid Image ;   Kate MacRae3 Author Orcid Image ;   Sadaf Kazi1, 3 Author Orcid Image ;   Laura Schubel1 Author Orcid Image ;   Adam Visconti3 Author Orcid Image ;   William Gallagher3, 4 Author Orcid Image ;   Kelly M Smith5, 6 Author Orcid Image ;   Traber Giardina7, 8 Author Orcid Image ;   Helen Haskell9 Author Orcid Image ;   Kristen Miller1, 3, 4 Author Orcid Image
Article Authors Cited by (7) Tweetations Metrics

Journals

  1. Asghar W, Khalid N. Precision nutrition at the crossroads: translational challenges and bottlenecks hampering the promise. Nutrition and Health 2025;31(3):801 View
  2. Haskell H, Giardina T, Dolka I, McDonald K. Ten years on: how far have we come in patient engagement in diagnosis?. Diagnosis 2025;12(4):538 View
  3. Irfan B, Boyd J, Sirvent R. When Protecting Privacy Means Protecting Health: Foreseeable Health Harms of AI Language Translation and Interpretation Technologies for Immigrant Patients. NEJM AI 2025;2(12) View
  4. Wubineh B, Deriba F, Gemeda F. Ethical concerns and strategies for implementing artificial intelligence in healthcare: a review of empirical studies. BMC Medical Ethics 2026;27(1) View
  5. Martini N, Dhaliwal N, Alipour E, Scahill S, Sajtos L. Patient Perceptions of Artificial Intelligence in Diabetes Self-Management: Cross-Sectional Survey Study. JMIR Formative Research 2026;10:e83030 View
  6. Nguyen N, Tran P. The Third Presence in the Clinic Room: How Artificial Intelligence is Reshaping the Clinical Encounter. Mayo Clinic Proceedings: Digital Health 2026:100354 View
  7. Housni A, Shulkin A, Katz A, Giannini G, Roy-Fleming A, Nakhla M, South C, Brazeau A. Designing a Carbohydrate Counting App for Young Adults With Type 1 Diabetes: Usability Testing Interview Study. Journal of Medical Internet Research 2026;28:e86024 View