Psychometric Validation and Preliminary Clinical Correlation of an Experiential Foraging Task.

Area of Science:

• Cognitive neuroscience
• Computational psychiatry
• Clinical psychology

Background:

• Reliable measurement of decision-making is crucial for understanding psychopathology.
• Existing metrics often lack reliability, clinical relevance, or the ability to capture individual differences.
• The WebSurf task offers a naturalistic paradigm for assessing decision-making.

Purpose of the Study:

• To examine the psychometric properties and clinical correlates of the WebSurf task.
• To determine the clinical utility of WebSurf behavioral parameters.
• To assess the reliability and replicability of WebSurf metrics.

Main Methods:

• Two experiments (N=132, N=109) were conducted to evaluate the WebSurf task.
• Behavioral parameters were extracted from the WebSurf task.
• Psychometric properties and correlations with psychiatric symptoms were analyzed.

Main Results:

• WebSurf task behavior and individual differences were stable over repeated administrations.
• Specific WebSurf metrics were reliably predicted by psychiatric symptoms (mania, externalizing profiles).
• Externalizing profiles predicted variability in reward pursuit and evaluation.

Conclusions:

• The WebSurf task provides reliable and clinically relevant metrics of decision-making.
• WebSurf shows promise for predicting treatment response, monitoring clinical change, and defining neurocognitive profiles.
• This paradigm supports computational psychological methods for enhancing psychiatric assessment and treatment personalization.