ArticleBMJ open2020
Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
What it found
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Who cites it
42 citing papers in PubMed.
- Consumer Perspectives on Trust in and Benefits of Artificial Intelligence in Health Care.JAMA network open · 2026Article
- Artificial intelligence for precision oncology from phenotyping and drug discovery to clinical translation.Discover oncology · 2026Review
- Stakeholders' Perceived Benefits and Concerns Regarding Artificial Intelligence in the Care of Older Adults.Journal of the American Geriatrics Society · 2026Article
- Key Information Influencing Patient Decision-Making About AI in Health Care: Survey Experiment Study.Journal of medical Internet research · 2026Article
- Public perceptions of health data sharing for artificial intelligence research: a qualitative focus group study in the UK.BMJ digital health & AI · 2026Article
- Attitudes of the Iranian Public Toward the Clinical Use of Artificial Intelligence in Medicine: A Cross-Sectional Survey.Patient preference and adherence · 2026Article
- Article
- Review
- Patients' Perceptions of Artificial Intelligence Acceptance, Challenges, and Use in Medical Care: Qualitative Study.Journal of medical Internet research · 2025Article
- Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study.Journal of medical Internet research · 2025Article
- Understanding Public Judgements on Artificial Intelligence in Healthcare: Dialogue Group Findings From Australia.Health expectations : an international journal of public participation in health care and health policy · 2025Article
- Artificial Intelligence in Medical Care - Patients' Perceptions on Caregiving Relationships and Ethics: A Qualitative Study.Health expectations : an international journal of public participation in health care and health policy · 2025Article
- Rheumatoid arthritis patients' perspective on the use of prediction models in clinical decision-making.Rheumatology (Oxford, England) · 2025Article
- How public discourse on medical AI shapes governance expectations: a Weibo-based mixed-methods study from China.Frontiers in public health · 2025Article
- Cautious optimism: public voices on medical AI and sociotechnical harm.Frontiers in digital health · 2025Article
- Attitudes toward artificial intelligence and robots in healthcare in the general population: a qualitative study.Frontiers in digital health · 2025Article
- Acceptability of artificial intelligence in breast screening: focus groups with the screening-eligible population in England.BMJ public health · 2024Article
- Analysis of public perceptions on the use of artificial intelligence in genomic medicine.Human genomics · 2024Article
- Trustworthy and ethical AI-enabled cardiovascular care: a rapid review.BMC medical informatics and decision making · 2024Review
- Acceptability of artificial intelligence for cervical cancer screening in Dschang, Cameroon: a qualitative study on patient perspectives.Reproductive health · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesGiven widespread interest in applying artificial intelligence (AI) to health data to improve patient care and health system efficiency, there is a need to understand the perspectives of the general public regarding the use of health data in AI research.
designA qualitative study involving six focus groups with members of the public. Participants discussed their views about AI in general, then were asked to share their thoughts about three realistic health AI research scenarios. Data were analysed using qualitative description thematic analysis. SETTINGS: Two cities in Ontario, Canada: Sudbury (400 km north of Toronto) and Mississauga (part of the Greater Toronto Area).
participantsForty-one purposively sampled members of the public (21M:20F, 25-65 years, median age 40).
resultsParticipants had low levels of prior knowledge of AI and mixed, mostly negative, perceptions of AI in general. Most endorsed using data for health AI research when there is strong potential for public benefit, providing that concerns about privacy, commercial motives and other risks were addressed. Inductive thematic analysis identified AI-specific hopes (eg, potential for faster and more accurate analyses, ability to use more data), fears (eg, loss of human touch, skill depreciation from over-reliance on machines) and conditions (eg, human verification of computer-aided decisions, transparency). There were mixed views about whether data subject consent is required for health AI research, with most participants wanting to know if, how and by whom their data were used. Though it was not an objective of the study, realistic health AI scenarios were found to have an educational effect.
conclusionsNotwithstanding concerns and limited knowledge about AI in general, most members of the general public in six focus groups in Ontario, Canada perceived benefits from health AI and conditionally supported the use of health data for AI research.
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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.