In search of better practice in executive functions assessment: Methodological issues and potential solutions

Area of Science:

• Cognitive Psychology
• Neuroscience
• Psychometrics

Background:

• Executive functions (EF) are complex, with ongoing debate regarding their structure and measurement.
• Heterogeneous operationalization of EF task performance complicates structural modeling.

Purpose of the Study:

• To investigate the relationship between EF task operationalization and the resulting structural models derived from confirmatory factor analyses (CFA).
• To identify optimal performance indicators for modeling EF structure.

Main Methods:

• Utilized bootstrapped data from 294 children (8-12 years) across nine EF tasks.
• Employed confirmatory factor analyses (CFA) to compare structural models based on different performance operationalizations (single scores, difference scores, response times, accuracy, drift rate).

Main Results:

• Single task scores demonstrated superior model convergence and acceptance compared to difference scores.
• Drift rate, derived from drift-diffusion models, showed the best balance of convergence and acceptance for EF structural modeling.
• Response times yielded poor model convergence and acceptance.

Conclusions:

• The choice of performance operationalization significantly influences the inferred structure of executive functions.
• Drift rate emerges as a promising indicator for robust EF structural modeling using CFA.