- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT07793721
Effects of Risk Presentation Format and Frequently Asked Questions on Breast Cancer Risk Skepticism
August 26, 2026 updated by: University of Colorado, Denver
The purpose of this study is to find out whether the way a breast cancer risk estimate is presented affects how women feel about their risk and whether they believe the estimate is accurate for them.
Women aged 39-74 will complete an online survey in which they receive a personalized breast cancer risk estimate using the Breast Cancer Risk Assessment Tool (BCRAT).
The study includes two experiments.
In the first experiment, women are randomly assigned to receive their estimate in different formats: some will see their risk over 5 years, 10 years, or a lifetime, and some will see their risk expressed out of 100 women or out of 1,000 women.
In the second experiment, women receive their estimate and then have the opportunity to read answers to frequently asked questions about how breast cancer risk is calculated and what the estimate means.
In both experiments, women are asked whether they believe the estimate reflects their true risk.
Both experiments are conducted online through a national survey panel.
Study Overview
Status
Not yet recruiting
Conditions
Intervention / Treatment
Study Type
Interventional
Enrollment (Estimated)
3000
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Laura D Scherer, PhD
- Phone Number: 303-724-3278
- Email: laura.scherer@cuanschutz.edu
Study Contact Backup
- Name: Emily A Vidal, MS
- Phone Number: 303-724-5426
- Email: emily.a.vidal@cuanschutz.edu
Study Locations
-
-
Colorado
-
Aurora, Colorado, United States, 80045
- University of Colorado Anschutz Medical Campus
-
Contact:
- Kate Noonan, MSW
- Phone Number: 303-618-2181
- Email: KATE.NOONAN@CUANSCHUTZ.EDU
-
Contact:
- Laura D Scherer, PhD
- Phone Number: 303-724-3278
- Email: laura.scherer@cuanschutz.edu
-
Principal Investigator:
- Laura D Scherer, PhD
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Yes
Description
Inclusion Criteria:
- Female sex
- Age 39-74 (i.e., people who are eligible for routine breast cancer screening and for whom guidelines recommend an informed, risk-based decision)
- English literacy
Exclusion Criteria:
1. Prior diagnosis of
- breast cancer
- Ductal carcinoma in situ (DCIS)
- Lobular carcinoma in situ (LCIS)
- Known BRCA1/2 gene mutation
- Cowan syndrome
- Li-Fraumeni syndrome
- Having received previous chest radiation for treatment of Hodgkin's lymphoma.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Health Services Research
- Allocation: Randomized
- Interventional Model: Factorial Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Experimental: 5 Year Risk AND N-in-100 Presentation
|
Participants receive a personalized breast cancer risk estimate generated by the Gail Model.
The format of the estimate varies by random assignment across two dimensions: temporal framing (5-year, 10-year, or lifetime risk) and denominator (risk expressed out of 100 women or out of 1,000 women).
All other elements of the risk presentation are held constant across conditions.
Participants receive a personalized breast cancer risk estimate generated by the Gail Model and then view an interactive FAQ document.
The FAQ document was developed from qualitative interviews with women who had previously rejected their risk estimates and addresses common questions about how breast cancer risk is calculated, what factors the model does and does not include, what different risk levels mean, and how to discuss results with a physician.
FAQ items are displayed as expandable questions; participants click to reveal answers.
All participants receive the same FAQ document.
|
|
Experimental: 10 Year Risk AND N-in-100 Presentation
|
Participants receive a personalized breast cancer risk estimate generated by the Gail Model.
The format of the estimate varies by random assignment across two dimensions: temporal framing (5-year, 10-year, or lifetime risk) and denominator (risk expressed out of 100 women or out of 1,000 women).
All other elements of the risk presentation are held constant across conditions.
Participants receive a personalized breast cancer risk estimate generated by the Gail Model and then view an interactive FAQ document.
The FAQ document was developed from qualitative interviews with women who had previously rejected their risk estimates and addresses common questions about how breast cancer risk is calculated, what factors the model does and does not include, what different risk levels mean, and how to discuss results with a physician.
FAQ items are displayed as expandable questions; participants click to reveal answers.
All participants receive the same FAQ document.
|
|
Experimental: Lifetime Risk AND N-in-100 Presentation
|
Participants receive a personalized breast cancer risk estimate generated by the Gail Model.
The format of the estimate varies by random assignment across two dimensions: temporal framing (5-year, 10-year, or lifetime risk) and denominator (risk expressed out of 100 women or out of 1,000 women).
All other elements of the risk presentation are held constant across conditions.
Participants receive a personalized breast cancer risk estimate generated by the Gail Model and then view an interactive FAQ document.
The FAQ document was developed from qualitative interviews with women who had previously rejected their risk estimates and addresses common questions about how breast cancer risk is calculated, what factors the model does and does not include, what different risk levels mean, and how to discuss results with a physician.
FAQ items are displayed as expandable questions; participants click to reveal answers.
All participants receive the same FAQ document.
|
|
Experimental: 5 Year Risk AND N-in-1000 Presentation
|
Participants receive a personalized breast cancer risk estimate generated by the Gail Model.
The format of the estimate varies by random assignment across two dimensions: temporal framing (5-year, 10-year, or lifetime risk) and denominator (risk expressed out of 100 women or out of 1,000 women).
All other elements of the risk presentation are held constant across conditions.
Participants receive a personalized breast cancer risk estimate generated by the Gail Model and then view an interactive FAQ document.
The FAQ document was developed from qualitative interviews with women who had previously rejected their risk estimates and addresses common questions about how breast cancer risk is calculated, what factors the model does and does not include, what different risk levels mean, and how to discuss results with a physician.
FAQ items are displayed as expandable questions; participants click to reveal answers.
All participants receive the same FAQ document.
|
|
Experimental: 10 Year Risk AND N-in-1000 Presentation
|
Participants receive a personalized breast cancer risk estimate generated by the Gail Model.
The format of the estimate varies by random assignment across two dimensions: temporal framing (5-year, 10-year, or lifetime risk) and denominator (risk expressed out of 100 women or out of 1,000 women).
All other elements of the risk presentation are held constant across conditions.
Participants receive a personalized breast cancer risk estimate generated by the Gail Model and then view an interactive FAQ document.
The FAQ document was developed from qualitative interviews with women who had previously rejected their risk estimates and addresses common questions about how breast cancer risk is calculated, what factors the model does and does not include, what different risk levels mean, and how to discuss results with a physician.
FAQ items are displayed as expandable questions; participants click to reveal answers.
All participants receive the same FAQ document.
|
|
Experimental: Lifetime Risk AND N-in-1000 Presentation
|
Participants receive a personalized breast cancer risk estimate generated by the Gail Model.
The format of the estimate varies by random assignment across two dimensions: temporal framing (5-year, 10-year, or lifetime risk) and denominator (risk expressed out of 100 women or out of 1,000 women).
All other elements of the risk presentation are held constant across conditions.
Participants receive a personalized breast cancer risk estimate generated by the Gail Model and then view an interactive FAQ document.
The FAQ document was developed from qualitative interviews with women who had previously rejected their risk estimates and addresses common questions about how breast cancer risk is calculated, what factors the model does and does not include, what different risk levels mean, and how to discuss results with a physician.
FAQ items are displayed as expandable questions; participants click to reveal answers.
All participants receive the same FAQ document.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Risk Skepticism
Time Frame: Day 1
|
Participants' perception of their Gail model risk estimate is trichotomized into three categories: Underestimator (believed risk is lower than estimate), Agreer (believed risk equals estimate), and Overestimator (believed risk is higher than estimate).
|
Day 1
|
|
Risk Perception
Time Frame: Day 1
|
This measure includes two Likert scale questions assessing the perceived likelihood of developing cancer and the level of worry about getting cancer.
|
Day 1
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Investigators
- Principal Investigator: Laura D Scherer, PhD, University of Colorado, Denver
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Estimated)
September 1, 2026
Primary Completion (Estimated)
February 1, 2027
Study Completion (Estimated)
April 1, 2027
Study Registration Dates
First Submitted
August 18, 2026
First Submitted That Met QC Criteria
August 26, 2026
First Posted (Actual)
August 28, 2026
Study Record Updates
Last Update Posted (Actual)
August 28, 2026
Last Update Submitted That Met QC Criteria
August 26, 2026
Last Verified
August 1, 2026
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 26-1163
- R01CA279953 (U.S. NIH Grant/Contract)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
YES
IPD Plan Description
The protocol, code books, and data set associated with this study will be shared on the Open Science Framework after ensuring that it is completely anonymized.
IPD Sharing Time Frame
IPD and supporting information will be made available when the first manuscript is submitted to a journal for review.
IPD Sharing Access Criteria
Anyone will be able to access the IPD and supporting information by downloading it from OSF.
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- SAP
- ANALYTIC_CODE
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.