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

Formative Evaluation of Digital Health Interventions (3229) Artificial Intelligence (2129) Clinical Information and Decision Making (1915) E-Health / Health Services Research and New Models of Care (718) Development and Evaluation of Research Methods, Instruments and Tools (744) User Needs and Competencies (456) Health Literacy, Health Numeracy, and Numeracy (42) Decision Support for Health Professionals (1539)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57204, first published .
Allied Health Professionals’ Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey

Allied Health Professionals’ Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey

Allied Health Professionals’ Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey

Authors of this article:

Jane Hoffman1, 2 Author Orcid Image ;   Laetitia Hattingh1, 2, 3 Author Orcid Image ;   Lucy Shinners4 Author Orcid Image ;   Rebecca L Angus1 Author Orcid Image ;   Brent Richards1, 5 Author Orcid Image ;   Ian Hughes1, 6 Author Orcid Image ;   Rachel Wenke1 Author Orcid Image
Article Authors Cited by (9) Tweetations Metrics

Journals

  1. Hoffman J, Wenke R, Angus R, Shinners L, Richards B, Hattingh L. Overcoming barriers and enabling artificial intelligence adoption in allied health clinical practice: A qualitative study. DIGITAL HEALTH 2025;11 View
  2. Evans K, Papinniemi A, Ploderer B, Nicholson V, Hindhaugh T, Vuvan V, Cowley N, Tariq A, Thomson H. Impact of using an AI scribe on clinical documentation and clinician-patient interactions in allied health private practice: perspectives of clinicians and patients. Musculoskeletal Science and Practice 2025;78:103333 View
  3. Lederman O, Llana A, Murray J, Stanton R, Chugh R, Haywood D, Burdett A, Warman G, Walker J, Hart N. Promises and perils of generative artificial intelligence: a narrative review informing its ethical and practical applications in clinical exercise physiology. BMC Sports Science, Medicine and Rehabilitation 2025;17(1) View
  4. Ayed A, Batran A, Aqtam I, Malak M, Ejheisheh M, Farajallah M, Farraj L, Alkhatib S. Perceived worries in the adoption of artificial intelligence among nurses in neonatal intensive care units. BMC Nursing 2025;24(1) View
  5. Attiqe M, Arif F, Perveen W, Shahzad S, Sajjad Y, Ilyas U. Knowledge, Attitude, and Practices of Artificial Intelligence in Undergraduate and Postgraduate Physical Therapy Students. The Healer Journal of Physiotherapy and Rehabilitation Sciences 2025;5(3):9 View
  6. Dolezel D, Elize , Watzlaf V, Morton M, Lalani K, Sand J, Fenton S. Assessing Artificial Intelligence Literacy: What do Health Information Professionals Know about AI?. Advances in Health Information Science and Practice 2025 View
  7. Khalid Al-Kahtani N, Subbarayalu A, Raman V, Jamjoom M, Faiz Saleem Al-Ansary N, Alakrawi Z, Jawad AL-Ibrahim R, Al-Zaki W. Healthcare professionals' and students' perspectives on artificial intelligence in clinical documentation in eastern Saudi Arabia: Factors influencing adoption and utilization. Informatics in Medicine Unlocked 2025;59:101710 View
  8. Oliveira D, Rego F, Nunes R. Artificial Intelligence in Exercise Prescription in Palliative Care: Perceptions and Ethical Issues. Healthcare 2025;13(22):2987 View
  9. Asmi A, Ihsan Kamaruddin M, Ode Novi Angraeni W, Hardi W, Andre Mangaya Takke J. Basic medical record education and training to prepare professional health human resources. Abdimas Polsaka 2025;4(2):229 View