ArticleQualitative health research2026
Patient Perspectives on Trust in Artificial Intelligence-Powered Tools in Prostate Cancer Diagnostics.
Article in Qualitative health research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline 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
- 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
- The Use of Artificial Intelligence Chatbots by Newly Diagnosed Cancer Patients: A Descriptive Phenomenological Study.Current oncology (Toronto, Ont.) · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing prevalence of prostate cancer cases calls for new ways to improve diagnostic pathways and patient care. Artificial intelligence (AI)-powered tools offer potential to streamline prostate cancer diagnostics, yet little is known about how patients perceive and experience these technologies. This study investigates how patients diagnosed through an AI-powered prostate cancer diagnostic tool express trust in AI. Based on 18 semi-structured qualitative interviews with men who underwent AI-supported diagnostics, data were analyzed using reflexive thematic analysis. Three dimensions of trust were developed. First, participants described a foundational trust in the healthcare system and professionals, shaped by previous positive encounters. Second, this interpersonal trust was central to their acceptance of AI, as participants relied on healthcare professionals and their expertise to explain, justify, and endorse AI technology. Third, participants recognized AI's potential to enhance diagnostics but emphasized the demand for human oversight and second opinion, due to concerns about accountability and AI's lack of intuition and holistic clinical oversight. Participants were more forgiving of human errors than those made by AI, highlighting the relational and moral dimensions of trust in healthcare. These findings underscore the importance of human relationships in shaping how patients engage with AI technologies and how trust in healthcare professionals remains a critical mediator for acceptance of AI in clinical settings. Understanding patients' trust in AI requires attention to the sociotechnical context in which care is delivered. In conclusion, trust in healthcare professionals remains paramount and is crucial for the acceptance of AI in prostate cancer diagnostics.
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Registered trials
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