Related Experiment Video
Updated: Jul 23, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Eliciting preferences for cancer screening tests: Comparison of a discrete choice experiment and the threshold
K D Valentine1, Victoria A Shaffer2, Brett Hauber3
1Massachusetts General Hospital, 100 Cambridge St, 16th Floor, Boston, MA 02114, USA; Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA.
Objective:
To compare results of three preference elicitation methods for a cancer screening test.
Methods:
Participants (undergraduate students) completed a discrete choice experiment (DCE) and a threshold technique (TT) task. Accuracy (false positives, false negatives), benefits (lives saved), and cost for a cancer screening test were used as attributes in the DCE and branching logic for the TT. Participants were also asked a direct elicitation question regarding a hypothetical screening test for breast (women) or prostate (men) cancer without mortality benefit. Correlations assessed the relationship between DCE and TT thresholds. Thresholds were standardized and ranked for both methods to compare. A logistic regression used the thresholds to predict results of the direct elicitation.
Results:
DCE and TT estimates were not meaningfully correlated (max ρ = 0.17). Participant rankings of attributes matched only 20% of the time (58/292). Neither method predicted preference for being screened (ps > 0.21).
Conclusions:
The DCE and TT yielded different preference estimates (and rank orderings) for the same participant. Neither method predicted patients' desires for a screening test.
Practice Implications:
Clinicians, patients, policy makers, and researchers should be aware that patient preference results may be sensitive to the method of eliciting preferences.
More Related Videos
Related Concept Videos
Cochran's Q Test
Comparing the Survival Analysis of Two or More Groups
Multiple Comparison Tests
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Fisher's Exact Test
Receiver Operating Characteristic Plot
Crossover Experiments
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.

