SynthesisJournal of medical Internet research2023
Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review.
Synthesis in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 2 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
59 citing papers in PubMed, 2 syntheses or guidelines pooled it, 121 citations in OpenAlex.
- Healthcare Professionals' Perceptions of Artificial Intelligence in Healthcare-A Systematic Review of Qualitative Studies.Journal of advanced nursing · 2026Pooled it
- Facilitators and Barriers to Implementing AI in Routine Medical Imaging: Systematic Review and Qualitative Analysis.Journal of medical Internet research · 2025Pooled it
- Preferences for the Use of Artificial Intelligence for Breast Cancer Screening in Australia: A Discrete Choice Experiment.The patient · 2025Trial
- Impact of AI-Assisted Diagnosis on American Patients' Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey Experiment.Journal of medical Internet research · 2025Trial
- AI in Neurological Health Care: Qualitative Study of Patient and Public Perceptions.Journal of medical Internet research · 2026Article
- From Assistance to Autonomy: Acceptability of Progressive Artificial Intelligence Integration in Facial Reconstructive Surgery-Protocol for Within-Subjects Vignette Experiment Among Romanian Adults.Healthcare (Basel, Switzerland) · 2026Article
- Exploring Women's Perspectives on Receiving AI-Enabled Digital Support for Infant Feeding: Multimethods Cross-Sectional Study.JMIR formative research · 2026Article
- Exploring Informal Caregivers' Perception of the Olera Digital Caregiving Assistance Platform for Dementia Care: Mixed Methods Evaluation Study.JMIR formative research · 2026Article
- Attitudes and Needs of Health Care Providers Toward Artificial Intelligence-Assisted Pediatric Palliative Care: Mixed Methods Study.Journal of medical Internet research · 2026Article
- Patient attitudes toward artificial intelligence in Jordanian Healthcare: A cross-sectional survey study.PLOS digital health · 2026Article
- Development and validation of the Oxford Attitudes to Artificial Intelligence in Medicine Scale.JAAD international · 2026Article
- Cognitive differences and ethical concerns in artificial intelligence in healthcare: a comparative text mining study of public and healthcare professional discussions.BMC medical ethics · 2026Article
- Public Expectations for Food and Drug Administration Approval of AI-Based Clinical Decision Support Tools: Quantitative Study.JMIR AI · 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
- Public Perceptions of AI in Medicine and Implications for Future Medical Education: Cross-Sectional Survey.JMIR formative research · 2026Article
- Expectations and concerns of primary healthcare patients in rural areas and small towns in Poland regarding artificial intelligence.Scientific reports · 2026Article
- Health sciences students' attitudes toward artificial intelligence: predictors of ethical awareness, clinical decision-making, and public health perceptions-a cross-sectional study.BMC medical education · 2026Article
- Online survey assessing US primary care physicians' attitudes toward AI use in clinical administrative tasks.BMJ health & care informatics · 2026Article
- Public perspectives on artificial intelligence in healthcare in the USA: a cross-sectional survey.BMJ digital health & AI · 2026Article
- Is accuracy enough? trust and barriers to AI-based clinical decision support in clinical neurophysiology.Clinical neurophysiology practice · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis paper reviews nationally representative public opinion surveys on artificial intelligence (AI) in the United States, with a focus on areas related to health care. The potential health applications of AI continue to gain attention owing to their promise as well as challenges. For AI to fulfill its potential, it must not only be adopted by physicians and health providers but also by patients and other members of the public.
objectiveThis study reviews the existing survey research on the United States' public attitudes toward AI in health care and reveals the challenges and opportunities for more effective and inclusive engagement on the use of AI in health settings.
methodsWe conducted a systematic review of public opinion surveys, reports, and peer-reviewed journal articles published on Web of Science, PubMed, and Roper iPoll between January 2010 and January 2022. We include studies that are nationally representative US public opinion surveys and include at least one or more questions about attitudes toward AI in health care contexts. Two members of the research team independently screened the included studies. The reviewers screened study titles, abstracts, and methods for Web of Science and PubMed search results. For the Roper iPoll search results, individual survey items were assessed for relevance to the AI health focus, and survey details were screened to determine a nationally representative US sample. We reported the descriptive statistics available for the relevant survey questions. In addition, we performed secondary analyses on 4 data sets to further explore the findings on attitudes across different demographic groups.
resultsThis review includes 11 nationally representative surveys. The search identified 175 records, 39 of which were assessed for inclusion. Surveys include questions related to familiarity and experience with AI; applications, benefits, and risks of AI in health care settings; the use of AI in disease diagnosis, treatment, and robotic caregiving; and related issues of data privacy and surveillance. Although most Americans have heard of AI, they are less aware of its specific health applications. Americans anticipate that medicine is likely to benefit from advances in AI; however, the anticipated benefits vary depending on the type of application. Specific application goals, such as disease prediction, diagnosis, and treatment, matter for the attitudes toward AI in health care among Americans. Most Americans reported wanting control over their personal health data. The willingness to share personal health information largely depends on the institutional actor collecting the data and the intended use.
conclusionsAmericans in general report seeing health care as an area in which AI applications could be particularly beneficial. However, they have substantial levels of concern regarding specific applications, especially those in which AI is involved in decision-making and regarding the privacy of health information.
Indexed as
Identifiers
What 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.