Patients’ Perceptions of Artificial Intelligence Acceptance, Challenges, and Use in Medical Care: Qualitative Study
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| Publicat a: | Journal of Medical Internet Research vol. 27 (2025), p. e70487 |
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| Autor principal: | |
| Altres autors: | , , , , , , , , |
| Publicat: |
Gunther Eysenbach MD MPH, Associate Professor
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| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 001 | 3222369187 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1438-8871 | ||
| 024 | 7 | |a 10.2196/70487 |2 doi | |
| 035 | |a 3222369187 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Gundlack, Jana | |
| 245 | 1 | |a Patients’ Perceptions of Artificial Intelligence Acceptance, Challenges, and Use in Medical Care: Qualitative Study | |
| 260 | |b Gunther Eysenbach MD MPH, Associate Professor |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Background:Artificial 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.Objective:The objective of this study was to explore patients’ perceptions toward acceptance, challenges of implementation, and potential applications of AI in medical care.Methods:The 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.Results:A 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.Conclusions:Patients 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. | |
| 610 | 4 | |a Food & Drug Administration--FDA | |
| 651 | 4 | |a Germany | |
| 653 | |a Patient-centered care | ||
| 653 | |a Application | ||
| 653 | |a Content analysis | ||
| 653 | |a End users | ||
| 653 | |a Psychology | ||
| 653 | |a Health services | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Qualitative research | ||
| 653 | |a Quality standards | ||
| 653 | |a Challenges | ||
| 653 | |a Sustainability | ||
| 653 | |a Clinical decision making | ||
| 653 | |a Sustainable development | ||
| 653 | |a Focus groups | ||
| 653 | |a Innovations | ||
| 653 | |a Stimulus | ||
| 653 | |a Perceptions | ||
| 653 | |a Implementation | ||
| 653 | |a Medical equipment | ||
| 653 | |a Data processing | ||
| 653 | |a Data integrity | ||
| 653 | |a Acceptance | ||
| 653 | |a Quality of care | ||
| 653 | |a Data quality | ||
| 653 | |a Well being | ||
| 653 | |a Patients | ||
| 653 | |a Research design | ||
| 653 | |a Standards | ||
| 653 | |a Feedback | ||
| 653 | |a Mental health services | ||
| 653 | |a Decision making | ||
| 653 | |a Medical decision making | ||
| 653 | |a Video recordings | ||
| 653 | |a Health care | ||
| 700 | 1 | |a Thiel, Carolin | |
| 700 | 1 | |a Negash, Sarah | |
| 700 | 1 | |a Buch, Charlotte | |
| 700 | 1 | |a Apfelbacher, Timo | |
| 700 | 1 | |a Denny, Kathleen | |
| 700 | 1 | |a Christoph, Jan | |
| 700 | 1 | |a Mikolajczyk, Rafael | |
| 700 | 1 | |a Unverzagt, Susanne | |
| 700 | 1 | |a Frese, Thomas | |
| 773 | 0 | |t Journal of Medical Internet Research |g vol. 27 (2025), p. e70487 | |
| 786 | 0 | |d ProQuest |t Library Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3222369187/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3222369187/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3222369187/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |