Use of and Attitudes Towards Large Language Models for Health Information Among People With Cancer, the Public, and Health-care Professionals

This cross-sectional survey examined how people with cancer, the general public and health-care professionals use large language models (LLMs) such as ChatGPT for health information, what they expect from them, how comfortable people with cancer are with clinicians using them, and which conditions they set for their use. Three English-language questionnaires were deployed through the Prolific research panel between December 24, 2024, and March 30, 2025. The public sample used US and UK recruitment quotas, whereas recruitment of people with cancer and professionals also included other countries. After exclusion of blank, duplicate and repeat records and of main-survey responses from pilot participants, the analysed sample comprised 2142 people with cancer, 1957 public respondents and 2714 professionals (6632 distinct participants). Six principal comparisons of people with cancer with the public on items with identical wording were tested at a Bonferroni-adjusted alpha of 0.0083. All other analyses were exploratory. The study was registered retrospectively after data collection.

Inclusion Criteria: * Age 18 years or older * English language proficiency * Internet access * Registered on the Prolific research platform * For the cancer group: self-reported cancer diagnosis within the past five years * For the professional group: professional practice with patient contact * For the public group: resident of the United States or the United Kingdom Exclusion Criteria: * Failure on embedded attention check questions (4 checks) * Survey completion time less than 5 minutes or greater than 60 minutes * Straight-line responding pattern detected by consistency validation algorithms * Failure of cohort verification procedures