ArticleBMJ open2023
Public perceptions on the application of artificial intelligence in healthcare: a qualitative meta-synthesis.
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Patient Concerns Regarding Artificial Intelligence Applications in Health Care: Systematic Review and Meta-Synthesis Based on Social Ecological Theory.Journal of medical Internet research · 2026Pooled it
- Perceptions of, Barriers to, and Facilitators of the Use of AI in Primary Care: Systematic Review of Qualitative Studies.Journal of medical Internet research · 2025Pooled it
- The evolving literature on the ethics of artificial intelligence for healthcare: a PRISMA scoping review.Frontiers in digital health · 2025Pooled it
- Health Care Professionals' Experience of Using AI: Systematic Review With Narrative Synthesis.Journal of medical Internet research · 2024Pooled it
- Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment.The patient · 2025Trial
- Do Androids Dream of Lived Experience? Navigating Risks, Uncertainty, and Best Practices Around Generative AI in Patient and Public Involvement and Engagement.Journal of medical Internet research · 2026Article
- AI in Neurological Health Care: Qualitative Study of Patient and Public Perceptions.Journal of medical Internet research · 2026Article
- Effects of Type and Timing of Clinician-Facing AI Support on Patient Trust in Medical Consultations: 2 Vignette Experiments.Journal of medical Internet research · 2026Article
- Consumer Perspectives on Trust in and Benefits of Artificial Intelligence in Health Care.JAMA network open · 2026Article
- Acceptability of digital health solutions and AI: qualitative interviews with perimenopausal women experiencing health inequalities.BMJ innovations · 2026Article
- Public Expectations for Food and Drug Administration Approval of AI-Based Clinical Decision Support Tools: Quantitative Study.JMIR AI · 2026Article
- A qualitative interview study investigating patient, health professional, and developer perspectives on real-world implementation of patient-centered AI systems.NPJ digital medicine · 2026Article
- Global Sentiment Toward Health AI at the Dawn of the ChatGPT Era: Empirical Analysis of Twitter (X) Discourse.Journal of medical Internet research · 2026Article
- Attitudes, Needs, and Expectations Regarding the Application of AI in Occupational Healthcare: A Multiple Stakeholder Perspective.Journal of occupational and environmental medicine · 2026Article
- Review
- Attitudes Towards the Use of Artificial Intelligence in Healthcare: A Conjoint Analysis Survey in Singapore.Asian bioethics review · 2026Article
- Artificial Intelligence in Public Health Education: A Scoping Review of Workforce Competency Development.Health science reports · 2026Article
- Acceptability of Using Artificial Intelligence in the National Health Service Breast Screening Program: A Randomized Online Survey of Screening-Eligible Women in England.Mayo Clinic proceedings. Digital health · 2026Article
- Public perceptions of AI in healthcare: a large-scale BERTopic and sentiment analysis of Reddit discussions.Frontiers in public health · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesMedical artificial intelligence (AI) has been used widely applied in clinical field due to its convenience and innovation. However, several policy and regulatory issues such as credibility, sharing of responsibility and ethics have raised concerns in the use of AI. It is therefore necessary to understand the general public's views on medical AI. Here, a meta-synthesis was conducted to analyse and summarise the public's understanding of the application of AI in the healthcare field, to provide recommendations for future use and management of AI in medical practice.
designThis was a meta-synthesis of qualitative studies.
methodA search was performed on the following databases to identify studies published in English and Chinese: MEDLINE, CINAHL, Web of science, Cochrane library, Embase, PsycINFO, CNKI, Wanfang and VIP. The search was conducted from database inception to 25 December 2021. The meta-aggregation approach of JBI was used to summarise findings from qualitative studies, focusing on the public's perception of the application of AI in healthcare.
resultsOf the 5128 studies screened, 12 met the inclusion criteria, hence were incorporated into analysis. Three synthesised findings were used as the basis of our conclusions, including advantages of medical AI from the public's perspective, ethical and legal concerns about medical AI from the public's perspective, and public suggestions on the application of AI in medical field.
conclusionResults showed that the public acknowledges the unique advantages and convenience of medical AI. Meanwhile, several concerns about the application of medical AI were observed, most of which involve ethical and legal issues. The standard application and reasonable supervision of medical AI is key to ensuring its effective utilisation. Based on the public's perspective, this analysis provides insights and suggestions for health managers on how to implement and apply medical AI smoothly, while ensuring safety in healthcare practice. PROSPERO REGISTRATION NUMBER: CRD42022315033.
Indexed as
Identifiers
36599634What OpenQuestion holds
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.