Perspectives of people affected by cancer toward generative AI in oncology: A scoping review of applications, evidence gaps, and future priorities.

Authors

Bradley D Menz, Nicholas L Scarfo, Erik Cornelisse, Adel Shahnam, Benjamin Chin-Yee, Ceara Rickard, Mark Haseloff, Annie Y S Lau, Anna Ugalde, Catherine Paterson, Michael J Sorich, Raymond J Chan, Andrew Rowland, Ashley M Hopkins

Published in

European journal of cancer (Oxford, England : 1990). Volume 246. Pages 116990. Aug 14, 2026. Epub Aug 14, 2026.

Abstract

Generative AI is increasingly being explored in cancer care, yet little is known about whether these tools align with the priorities and concerns of the people they are intended to support. We conducted a scoping review to identify studies that examined the perspectives of people affected by cancer towards generative AI.
PubMed, Embase, Web of Science, and MEDLINE were searched to July 2026. Two independent reviewers screened identified records for peer-reviewed studies reporting primary empirical data on the perspectives of people affected by cancer regarding generative AI in cancer care contexts. Study characteristics, applications evaluated, and perspectives assessed were extracted and synthesised descriptively and narratively.
Of 2441 records identified, 32 studies comprising 4919 participants were included. Of these, 29 assessed specific applications: 21 Patient Communication and Education, 6 Clinical Note Generation involving lay summaries, 2 Clinical Decision Support; and 3 assessed general perspectives on AI without a defined task. Where perspectives were assessed, studies predominantly measured usefulness (21/32), comprehension (20/32), and trust (14/32). People affected by cancer were generally favourable when generative AI improved the accessibility and readability of health information; however, trust was conditional on personalisation, emotional appropriateness, human oversight, and perceived accuracy. These perspectives may help inform the design and implementation of generative AI, including interface design, patient education, consent processes, workflow integration, governance, monitoring, and feedback mechanisms.
Perspectives towards generative AI involving people affected by cancer remain concentrated in a narrow subset of applications. Considerations for responsible AI deployment, including safety, transparency, equity, and autonomy, have not been assessed from the perspectives of people affected by cancer.

PMID:
42628140
Bibliographic data and abstract were imported from PubMed on 22 Aug 2026.

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