CompletedNot Applicable

Use and Acceptance of Large Language Models for Cancer Shared Decision-Making

Germany7,151 participantsStarted 2025-03-01

Plain-language summary

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.

Who can participate

Age range

18 Years

Sex

ALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: * Age 18 years or older * English language proficiency * Regular internet access * Registered on the Prolific research platform * For cancer patient cohort: self-reported cancer diagnosis within the past five years * For healthcare professional cohort: licensed healthcare practitioner with active patient contact * For general population cohort: resident of the United States or 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

Questions worth asking your doctor

Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.

1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?

Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.

Questions for the trial coordinator

The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.

1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?

A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.

What they're measuring

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)

Trial details

NCT IDNCT07526441

SponsorTechnical University of Munich

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2025-05-01

View on ClinicalTrials.gov More Cancer trials

Plain-language summary

Who can participate

Age range

18 Years

Sex

ALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

What they're measuring

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)