ArticleDigital health
Exploring healthcare professionals' perceptions of artificial intelligence: Validating a questionnaire using the e-Delphi method.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Informational and structural barriers to exercise oncology care in Spain: development of the MOVE-Onco questionnaire and preliminary findings.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Medical students' knowledge and attitude towards using artificial intelligence in medical education and practice: a pre-post study.BMC medical education · 2026Article
- Digital Skills and Readiness of Greek Nurses for Artificial Intelligence Adoption in Clinical Nursing Practice.Nursing reports (Pavia, Italy) · 2026Article
- How does AI perform compared to human expert panels in medical Delphi studies? A pilot study through the lens of pathology.Journal of pathology informatics · 2026Article
- Dental students' knowledge, perceptions, and educational needs regarding artificial intelligence: a multinational cross-sectional survey.BMC medical education · 2026Article
- Hearing health professionals' attitudes and perceived skills toward artificial intelligence.BMC medical education · 2026Article
- AI-Savvy leadership for enhancing AI utilization and employee engagement among digital natives in the EdTech sector.Scientific reports · 2025Article
- A quality improvement project of patient perception of AI-generated discharge summaries: a comparison with doctor-written summaries.Annals of the Royal College of Surgeons of England · 2025Article
- Developing a Patient Experience Questionnaire for the Man Van Mobile Clinical Unit.Health expectations : an international journal of public participation in health care and health policy · 2025Article
- Artificial Intelligence in Healthcare: University Students' Perceptions and Level of Confidence.Healthcare (Basel, Switzerland) · 2025Article
- The acceptance of ophthalmic artificial intelligence for eye diseases: a literature review and qualitative analysis.Eye (London, England) · 2025Review
- Technology adoption in healthcare: Delphi consensus for the early exploration and agile adoption of emerging healthcare technology conceptual framework.BMJ health & care informatics · 2025Article
- The impact of an artificial intelligence enhancement program on healthcare providers' knowledge, attitudes, and workplace flourishing.Frontiers in public health · 2025Article
- Allied Health Professionals' Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey.JMIR formative research · 2024Article
- How do medical professionals make sense (or not) of AI? A social-media-based computational grounded theory study and an online survey.Computational and structural biotechnology journal · 2024Article
- Forecasting the future of smart hospitals: findings from a real-time delphi study.BMC health services research · 2024Article
- Article
- Knowledge, attitude, and practice of artificial intelligence among medical students in Sudan: a cross-sectional study.Annals of medicine and surgery (2012) · 2024Article
- Potential of Large Language Models in Health Care: Delphi Study.Journal of medical Internet research · 2024Article
- Developing knowledge, attitude and practice questionnaire in desmoid tumours (KAPID study): applying e-Delphi to rare diseases.Ecancermedicalscience · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim of this study was to draw upon the collective knowledge of experts in the fields of health and technology to develop a questionnaire that measured healthcare professionals' perceptions of Artificial Intelligence (AI).
methodsThe panel for this study were carefully selected participants who demonstrated an interest and/or involvement in AI from the fields of health or information technology. Recruitment was accomplished via email which invited the panel member to participate and included study and consent information. Data were collected from three rounds in the form of an online survey, an online group meeting and email communication. A 75% median threshold was used to define consensus.
resultsBetween January and March 2019, five healthcare professionals and three IT experts participated in three rounds of study to reach consensus on the structure and content of the questionnaire. In Round 1 panel members identified issues about general understanding of AI and achieved consensus on nine draft questionnaire items. In Round 2 the panel achieved consensus on demographic questions and comprehensive group discussion resulted in the development of two further questionnaire items for inclusion. In a final e-Delphi round, a draft of the final questionnaire was distributed via email to the panel members for comment. No further amendments were put forward and 100% consensus was achieved.
conclusionA modified e-Delphi method was used to validate and develop a questionnaire to explore healthcare professionals' perceptions of AI. The e-Delphi method was successful in achieving consensus from an interdisciplinary panel of experts from health and IT. Further research is recommended to test the reliability of this questionnaire.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.