Related Experiment Video
Updated: Mar 21, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
Effects of a risk-based online mammography intervention on accuracy of perceived risk and mammography intentions
Holli H Seitz1, Laura Gibson1, Christine Skubisz1
1Annenberg School for Communication, University of Pennsylvania, 3620 Walnut Street, Philadelphia, PA, 19104, USA.
Objective:
This experiment tested the effects of an individualized risk-based online mammography decision intervention. The intervention employs exemplification theory and the Elaboration Likelihood Model of persuasion to improve the match between breast cancer risk and mammography intentions.
Methods:
2918 women ages 35-49 were stratified into two levels of 10-year breast cancer risk (<1.5%; ≥1.5%) then randomly assigned to one of eight conditions: two comparison conditions and six risk-based intervention conditions that varied according to a 2 (amount of content: brief vs. extended) x 3 (format: expository vs. untailored exemplar [example case] vs. tailored exemplar) design. Outcomes included mammography intentions and accuracy of perceived breast cancer risk.
Results:
Risk-based intervention conditions improved the match between objective risk estimates and perceived risk, especially for high-numeracy women with a 10-year breast cancer risk ≤1.5%. For women with a risk≤1.5%, exemplars improved accuracy of perceived risk and all risk-based interventions increased intentions to wait until age 50 to screen.
Conclusion:
A risk-based mammography intervention improved accuracy of perceived risk and the match between objective risk estimates and mammography intentions.
Practice Implications:
Interventions could be applied in online or clinical settings to help women understand risk and make mammography decisions.
More Related Videos
06:28E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020