Clinical trial · Interventional
Ovarian Cancer Screening and AI
AI on Ovarian Cancer Screening Attitudes in Gynecologists
NCT07503054CI-TRIAL-00106885AI-OCS-Gynnot yet recruitingN/AClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Gynecologists frequently overestimate the benefits and safety of ovarian cancer screening. AI-supported discussions may help correct these misperceptions. This study tests whether an AI-guided conversation about the evidence on ovarian cancer screening can improve gynecologists' knowledge and reduce non-evidence-based screening recommendations, compared with a control AI discussion on ovarian cancer prevalence.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Ovarian Cancer Screening Recommendations by Gynecologists | — | UNRESOLVED | — |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| ChatGPT - Control | Behavioral | — | UNRESOLVED |
| ChatGPT - Evidence-Based Screening Discussion | Behavioral | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- OTHER
- label
- Control (ChatGPT Control Condition)
- description
- Participants in this arm engage in a three-turn conversation with ChatGPT. The AI's role is to: * Discuss the participant's perception of how dangerous ovarian cancer is. * Provide factual information on prevalence, lifetime risk, mortality rates, and general epidemiology. * Avoid any mention of screening tests, guideline recommendations, or screening benefits/harms. * Keep responses concise (5-8 sentences per turn). * Begin by reacting to the participant's opening question: "In your mind, how dangerous is ovarian cancer?"
- interventionNames
- Behavioral: ChatGPT - Control
- type
- EXPERIMENTAL
- label
- Experimental (ChatGPT Evidence-Based Screening Discussion)
- description
- Participants in this arm engage in a three-turn conversation with ChatGPT. The AI's role is to: * Ask participants to elaborate on their reasons for recommending ovarian cancer screening. * Provide clear, evidence-based information about benefits and harms of ovarian cancer screening in average-risk women. * Refer to key findings from large trials (e.g., PLCO, UKCTOCS) with absolute numbers (false-positive rates, unnecessary surgeries, complication rates, lack of mortality benefit). * Summarize positions of major U.S. guidelines (e.g., USPSTF, ACOG), including recommendation against routine screening in asymptomatic, average-risk women. * Evaluate the evidence and state whether routine screening is supported based on current data. * Maintain a respectful, non-judgmental tone; critique evidence, not the participant. * Keep responses concise (5-8 sentences per turn). * Begin by responding to the participant's opening question: "Why do you recommend ovarian cancer screening?"
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 24 Years
Show eligibility criteria text
Inclusion Criteria: * gynecologists in outpatient care who provide ovarian cancer screening to asymptomatic, average-risk women (not guideline consistent) Exclusion Criteria: * gynecologists in inpatient care * gynecologist in outpatient care who do NOT provide ovarian cancer screening to asymptomatic, average-risk women (guideline consistent)
References
Publications (3)
- BACKGROUNDWegwarth O, Gigerenzer G. US gynecologists' estimates and beliefs regarding ovarian cancer screening's effectiveness 5 years after release of the PLCO evidence. Sci Rep. 2018 Nov 21;8(1):17181. doi: 10.1038/s41598-018-35585-z. PMID 30464251
- BACKGROUNDWegwarth O, Pashayan N. When evidence says no: gynaecologists' reasons for (not) recommending ineffective ovarian cancer screening. BMJ Qual Saf. 2020 Jun;29(6):521-524. doi: 10.1136/bmjqs-2019-009854. Epub 2019 Nov 8. No abstract available. PMID 31704891
- BACKGROUNDUS Preventive Services Task Force; Grossman DC, Curry SJ, Owens DK, Barry MJ, Davidson KW, Doubeni CA, Epling JW Jr, Kemper AR, Krist AH, Kurth AE, Landefeld CS, Mangione CM, Phipps MG, Silverstein M, Simon MA, Tseng CW. Screening for Ovarian Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2018 Feb 13;319(6):588-594. doi: 10.1001/jama.2017.21926. PMID 29450531