ArticleBMJ health & care informatics2020
Clinician and computer: a study on patient perceptions of artificial intelligence in skeletal radiography.
Article in BMJ health & care informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 citations in OpenAlex.
- Artificial intelligence in headache medicine: between automation and the doctor-patient relationship. A systematic review.The journal of headache and pain · 2025Pooled it
- Patient Reactions to Artificial Intelligence-Clinician Discrepancies: Web-Based Randomized Experiment.Journal of medical Internet research · 2025Trial
- Out with AI, in with the psychiatrist: a preference for human-derived clinical decision support in depression care.Translational psychiatry · 2023Trial
- A large-scale vision foundation model for musculoskeletal radiographs.NPJ digital medicine · 2026Article
- Constructs Influencing Patient Perceptions of Use of AI in Medical Imaging Analysis: Systematic Review.Interactive journal of medical research · 2026Review
- Patient Perceptions of Artificial Intelligence in Orthopaedic Surgery: Identifying Potential Barriers to Acceptance and Disparities With Implementation.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026Article
- Is accuracy enough? trust and barriers to AI-based clinical decision support in clinical neurophysiology.Clinical neurophysiology practice · 2026Article
- Public trust of AI in healthcare in South Africa: results of a survey.BMC medical ethics · 2025Article
- Patient Perspectives on Artificial Intelligence in Medical Imaging.Journal of participatory medicine · 2025Article
- Quantifying Healthcare Provider Perceptions of a Novel Deep Learning Algorithm to Predict Sepsis: Electronic Survey.Critical care explorations · 2025Article
- Artificial intelligence for diagnostics in radiology practice: a rapid systematic scoping review.EClinicalMedicine · 2025Article
- The perception of artificial intelligence and infertility care among patients undergoing fertility treatment.Journal of assisted reproduction and genetics · 2025Article
- Just another tool in their repertoire: uncovering insights into public and patient perspectives on clinicians' use of machine learning in perioperative care.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists.Oral radiology · 2025Article
- Assessing Yemeni university students' public perceptions toward the use of artificial intelligence in healthcare.Scientific reports · 2024Article
- A survey of patient acceptability of the use of artificial intelligence in the diagnosis of paediatric fractures: an observational study.Annals of the Royal College of Surgeons of England · 2024Observational
- Artificial Intelligence and Virtual Reality in Headache Disorder Diagnosis, Classification, and Management.Current pain and headache reports · 2024Review
- Autonomous artificial intelligence for diabetic eye disease increases access and health equity in underserved populations.NPJ digital medicine · 2024Article
- Patient Perspectives on the Use of Artificial Intelligence in Health Care: A Scoping Review.Journal of patient-centered research and reviews · 2024Article
- Patient Perspectives on Artificial Intelligence in Healthcare Decision Making: A Multi-Center Comparative Study.Indian journal of orthopaedics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUp to half of all musculoskeletal injuries are investigated with plain radiographs. However, high rates of image interpretation error mean that novel solutions such as artificial intelligence (AI) are being explored.
objectivesTo determine patient confidence in clinician-led radiograph interpretation, the perception of AI-assisted interpretation and management, and to identify factors which might influence these views.
methodsA novel questionnaire was distributed to patients attending fracture clinic in a large inner-city teaching hospital. Categorical and Likert scale questions were used to assess participant demographics, daily electronics use, pain score and perceptions towards AI used to assist in interpretation of their radiographs, and guide management.
results216 questionnaires were included (M=126, F=90). Significantly higher confidence in clinician rather than AI-assisted interpretation was observed (clinician=9.20, SD=1.27 vs AI=7.06, SD=2.13), 95.4% reported favouring clinician over AI-performed interpretation in the event of disagreement.Small positive correlations were observed between younger age/educational achievement and confidence in AI-assistance. Students demonstrated similarly increased confidence (8.43, SD 1.80), and were over-represented in the minority who indicated a preference for AI-assessment over their clinicians (50%).
conclusionsParticipant's held the clinician's assessment in the highest regard and expressed a clear preference for it over the hypothetical AI assessment. However, robust confidence scores for the role of AI-assistance in interpreting skeletal imaging suggest patients view the technology favourably.Findings indicate that younger, more educated patients are potentially more comfortable with a role for AI-assistance however further research is needed to overcome the small number of responses on which these observations are based.
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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.