Optimized short-forms of the Cognitive Distortions Questionnaire

Area of Science:

• Psychology
• Psychometrics
• Machine Learning

Background:

• The Cognitive Distortions Questionnaire (CD-Quest) is a valuable tool for assessing cognitive distortions.
• Its full length can be a barrier in time-limited settings.

Purpose of the Study:

• To develop brief, hand-scorable short-forms of the CD-Quest.
• To maintain high accuracy in measuring cognitive distortions with fewer items.

Main Methods:

• Utilized the RiskSLIM machine learning method to create short-form scales.
• Optimized item selection and integer weights to maximize concordance with the full CD-Quest score.
• Trained models on US undergraduate data and validated on diverse international samples.

Main Results:

• A 9-item short-form accurately reproduced full CD-Quest scores (R² = 90.4-93.6%) across validation samples.
• A 5-item ultra-short-form demonstrated good accuracy (R² = 78.2-85.5%).

Conclusions:

• Brief, accurate short-forms of the CD-Quest were successfully developed.
• These versions enhance the feasibility of measuring cognitive distortions for users with limited time and resources.