This study examines how cancer patients, the general public, and healthcare professionals use and perceive large language models (such as ChatGPT) for health-related shared decision-making in oncology. A cross-sectional survey was conducted among 7,151 participants across 30 countries using a questionnaire developed and validated through a two-round Delphi process involving 44 experts. The study assessed current patterns of large language model use for health information, barriers to adoption including concerns about reliability and privacy, future expectations regarding these tools in shared decision-making, and demographic predictors of adoption. Participants were recruited through the Prolific platform between March and May 2025, with stratified sampling across three groups: cancer patients diagnosed within the past five years, general population members from the United States and United Kingdom, and licensed healthcare professionals with active patient contact.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Healthcare-specific large language model usage rate
Timeframe: At time of survey completion (single assessment, March-May 2025)
Future belief in large language model improvement of shared decision-making
Timeframe: At time of survey completion (single assessment, March-May 2025)
Barriers to large language model adoption
Timeframe: At time of survey completion (single assessment, March-May 2025)