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 (2181) Decision Support for Health Professionals (1725) Design, Usability, and Evaluation of Research Instruments, Scales, and Measures (105) Clinical Communication, Electronic Consultation and Telehealth (842) Security and Privacy of mHealth and uHealth (171) User Needs and Competencies (522) Artificial Intelligence (2504) Patient Reported Measures and Outcomes in Participatory Medicine (52) Ambient AI Scribes and AI-Driven Documentation Technologies (42)

Published on in Vol 17 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69564, first published .
Diverse group discusses AI in a support group setting, with an AI brain graphic on a display.

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 (18) 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;4(2):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
  8. Maciej Kokoszka , Michalina Chodór , Julia Maria Kuczkowska , Judyta Bordakiewicz , Zuzanna Michalska , Donata Pokorska , Julia Świechowska , Zuzanna Zarzycka , Ingrid Samberger , Magdalena Wiciak . ALGORITHMIC AUTHORITY VS. HUMAN TOUCH: A NARRATIVE REVIEW OF PATIENT TRUST AND CLINICAL AUTONOMY IN AI-ASSISTED DIAGNOSTICS. International Journal of Innovative Technologies in Social Science 2026;3(1(49)) View
  9. Giwa A. Institutional trust and AI-assisted surgery in the US: implications for ethical governance. AI and Ethics 2026;6(3) View
  10. Hou J, Zhang Z, Cheng X, Wang W. Patient Concerns Regarding Artificial Intelligence Applications in Health Care: Systematic Review and Meta-Synthesis Based on Social Ecological Theory. Journal of Medical Internet Research 2026;28:e85663 View
  11. Jakub Sałak , Wiktoria Donocik , Jakub Wrona , Piotr Tryczyński , Piotr Helbin , Aleksandra Gralec , Sebastian Ożga , Aleksandra Spirkowicz . NAVIGATING THE SOCIO-TECHNICAL SHIFT: A SYSTEMATIC REVIEW OF PATIENT TRUST, ANXIETY, AND INFORMED CONSENT IN AI-ENHANCED MAMMOGRAPHY (2022-2026). International Journal of Innovative Technologies in Social Science 2026;4(1(49)) View
  12. . AI Clinical Scribe Limitations: Scoping Review with ☸️SAIMSARA. SAIMSARA Journal 2026;1(3) View
  13. Rabinowitz A, Trauger M, Williams M. Reining in Unbridled AI Enthusiasm: Protecting the Integrity of Rehabilitation Science and Clinical Care. Archives of Physical Medicine and Rehabilitation 2026 View
  14. Sun H, Shi Z, Xia Y, Bai Y, Yu M, Liu R, He P. Patient preferences and willingness-to-pay for AI-enabled blended type 2 diabetes care by digital experience and socioeconomic status: a discrete-choice experiment in China. BMJ Open 2026;16(5):e115755 View
  15. Guo Y, Hu D, Zhou Y, Lyu T, Yang Z, Reynolds T, Zheng K. A scoping review of studies on secure messaging through patient portals: persistent challenges and potential solutions. npj Health Systems 2026;3(1) View
  16. Kuppanda P, Janda M, Caffery L. Constructs Influencing Patient Perceptions of Use of AI in Medical Imaging Analysis: Systematic Review. Interactive Journal of Medical Research 2026;15:e92969 View
  17. Conradi L, Howick J, Bennett-Weston A. Impact of artificial intelligence integrations on empathy in healthcare interactions between patients and practitioners: protocol for a systematic review and thematic synthesis of qualitative studies. BMJ Open 2026;16(6):e118515 View
  18. Hovhannisyan M, Boyd J. Informed Consent in the Age of Clinical AI: Beyond the One-Time Authorization Model. The American Journal of Bioethics 2026:1 View