ArticleJournal of medical Internet research2025
Patients' Perceptions of Artificial Intelligence Acceptance, Challenges, and Use in Medical Care: Qualitative Study.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
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Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Barriers and Facilitators to Patient Acceptance of Artificial Intelligence in Health Care: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Ethical concerns and strategies for implementing artificial intelligence in healthcare: a review of empirical studies.BMC medical ethics · 2026Pooled it
- The OR black box in urology: A survey on patient acceptance and confidence in AI-assisted surgery.BJUI compass · 2026Article
- Patients' and Physicians' Perceptions of AI Integration in Prostate Cancer Diagnosis: Mixed Methods Study of Challenges to the Patient-Physician Relationship.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 attitudes and acceptance of artificial intelligence in multiple sclerosis from the patient perspective.PLOS digital health · 2026Article
- Article
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- Quality of artificial intelligence-generated responses on pediatric celiac disease: Comparative assessment of Open AI ChatGPT and Google Gemini.JPGN reports · 2026Article
- Exploring Patient Perspectives on the Use of Artificial Intelligence to Inform Joint Decision-Making for Patients With Multiple Conditions in Primary Care in the United Kingdom: Qualitative Study.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
- "Black box" artificial intelligence for mortality prediction: a mixed-methods study of palliative care team, patient, and caregiver perspectives.Annals of palliative medicine · 2026Article
- Expectations and concerns of primary healthcare patients in rural areas and small towns in Poland regarding artificial intelligence.Scientific reports · 2026Article
- Transforming Relational Care Values in AI-Mediated Healthcare: A Text Mining Analysis of Patient Narrative.Healthcare (Basel, Switzerland) · 2026Article
- Implementing computer‑aided detection for TB active case finding: A qualitative study of feasibility and acceptability in Tondo, Manila.PLOS global public health · 2026Article
- Public perspectives on artificial intelligence in healthcare in the USA: a cross-sectional survey.BMJ digital health & AI · 2026Article
- Patient and dental practitioner acceptance of artificial intelligence in dental care: a cross-sectional study in Saudi Arabia's eastern province.Frontiers in oral health · 2026Article
- Parents' Perspectives on Artificial Intelligence-Supported Pediatric Healthcare Services: A Descriptive and Correlational Study.Journal of nursing management · 2026Article
- A review for navigating the trade-offs: evaluating open-source and proprietary large language models for clinical and biomedical information extraction.Frontiers in digital health · 2026Review
- Implementing AI innovation in radiology departments in the English NHS: a qualitative study on the experiences of professionals, patient groups and innovators.Frontiers in digital health · 2026Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) is increasingly used in medical care, particularly in the areas of image recognition and processing. While its practical use in other areas is still limited, an understanding of patients' needs is essential for the practical and sustainable implementation of AI, which could further acceptance of new innovations.
objectiveThe objective of this study was to explore patients' perceptions toward acceptance, challenges of implementation, and potential applications of AI in medical care.
methodsThe study used a qualitative research design. To capture a broad range of patient perspectives, we conducted semistructured focus groups (FGs). As a stimulus for the FGs and as an introduction to the topic, we presented a video defining AI and showing 3 potential AI applications in health care. Participants were recruited from different locations in the regions of Halle (Saale) and Erlangen, Germany; all but one group were from outpatient settings. We analyzed the data using a content analysis approach.
resultsA total of 35 patients (13 female and 22 male; age: range 23-92, median 50 years) participated in 6 focus groups. They highlighted that AI acceptance in medical care could be improved through user-friendly applications, clear instructions, feedback mechanisms, and a patient-centered approach. Perceived key barriers included data protection concerns, lack of human oversight, and profit-driven motives. Perceived challenges and requirements for AI implementation involved compatibility, training of end users, environmental sustainability, and adherence to quality standards. Potential AI application areas identified were diagnostics, image and data processing, and administrative tasks, though participants stressed that AI should remain a support tool, not an autonomous system. Psychology was an area where its use was opposed due to the need for human interaction.
conclusionsPatients were generally open to the use of AI in medical care as a support tool rather than as an independent decision-making system. Acceptance and successful use of AI in medical care could be achieved if it is easy to use, adapted to individual characteristics of the users, and accessible to everyone, with the primary aim of enhancing patient well-being. AI in health care requires a regulatory framework, quality standards, and monitoring to ensure socially fair and environmentally sustainable development. However, the successful implementation of AI in medical practice depends on overcoming the mentioned challenges and addressing user needs.
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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.