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Customizing Computerized Adaptive Test Stopping Rules for Clinical Settings Using the Negative Affect Subdomain of

Saki Amagai¹, Aaron J Kaat¹, Rina S Fox²

¹Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.

JMIR Formative Research

|March 21, 2025

Summary

Optimizing computerized adaptive tests (CATs) involves balancing patient burden and measurement reliability. Modified stopping rules, particularly reducing the maximum item count, offer a promising approach for clinical use.

Keywords:

CAT NIH Toolbox clinical setting clinician computerized adaptive testing patient-reported outcome reliability stopping rules test burden

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Area of Science:

Psychometrics
Clinical Psychology
Health Outcomes Research

Background:

Patient-reported outcome measures (PROMs) are vital for clinical decisions and treatment evaluation.
However, PROMs can be burdensome for patients and may lack the reliability needed for clear clinical interpretation.

Purpose of the Study:

To evaluate how alternative stopping rules in computerized adaptive tests (CATs) can enhance reliability for clinical applications.
To minimize the patient burden associated with CATs.

Main Methods:

Computerized adaptive test (CAT) simulations were performed on three adult item banks from the NIH Toolbox Emotion Battery (Anger Affect, Fear Affect, Sadness).
Original NIH Toolbox CAT stopping rules (score SE <0.3 before 12 items) were compared with a SE-change rule, fixed-length CATs (4-12 items), and a reduced maximum item rule (8 items).
Measures included administered items (burden), proportion of assessments achieving reliability cutoffs (0.85, 0.90, 0.95) (precision), and accuracy of score recovery.

Main Results:

Alternative stopping rules generally reduced burden and increased high reliability compared to original rules for adult banks.
The SE-change rule and fixed-length CATs with ≤8 items increased assessments with reliability <0.85.
The reduced maximum stopping rule demonstrated the best balance between precision and parsimony.

Conclusions:

Reducing test burden while maintaining score precision for clinical use presents significant challenges.
Stopping rules for CATs should be adapted based on the specific study population and objectives.