Related Experiment Video
Updated: Jan 24, 2026

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese
Published on: April 1, 2016
Interactivity in a Decision Aid: Findings From a Decision Aid to Technologically Enhance Shared Decision Making RCT
Masahito Jimbo1, Ananda Sen2, Melissa A Plegue1
1Department of Family Medicine, University of Michigan, Ann Arbor, Michigan.
Introduction:
Colorectal cancer screening (CRCS) remains underutilized. Decision aids (DAs) can increase patient knowledge, intent, and CRCS rates compared with "usual care," but whether interactivity further increases CRCS rate remains unknown.
Study Design:
A two-armed RCT compared the effect of a web-based DA that interactively assessed patient CRC risk and clarified patient preference for specific CRCS test to a web-based DA with the same content but without the interactive tools.
Setting/Participants:
The study sites were 12 community- and three university-based primary care practices (56 physicians) in southeastern Michigan. Participants were men and women aged 50-75 years not current on CRCS.
Intervention:
Random allocation to interactive DA (interactive arm) or non-interactive DA (non-interactive arm).
Main Outcome Measures:
Primary outcome was medical record documentation of CRCS 6 months after the intervention. Secondary outcome was patient decision quality (i.e., knowledge, preference clarification, and intent) measured immediately before and after DA use, and immediately after the office visit. To determine that either DA had a positive effect on CRCS adherence, usual care CRCS rates were determined from the three university-based practices among patients eligible for but not participating in the study.
Results:
Data were collected between 2012 and 2014; analysis began in 2015. At 6 months, CRCS rate was 36.1% (95% CI=30.5%, 42.2%) in the interactive arm (n=284) and 40.5% (95% CI=34.7%, 46.6%) in the non-interactive arm (n=286, p=0.29). Usual care CRCS rate (n=440) was 18.6% (95% CI=15.2%, 22.7%), significantly lower than both arms (p<0.001). Knowledge, attitude, self-efficacy, test preference, and intent increased significantly within each arm versus baseline, but the rate was not significantly different between the two arms.
Conclusions:
The interactive DA did not improve the outcome compared to the non-interactive DA. This suggests that the resources needed to create and maintain the interactive components are not justifiable.
Trial Registration:
This study is registered at www.clinicaltrials.gov NCT01514786.
More Related Videos
Related Concept Videos
Decision Making
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Decision Making: P-value Method
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
Decision Making: Traditional Method
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
Self-Evaluation: Self-Enhancement and Self-Verification
Predator-Prey Interactions
Finding the Center of Gravity

