Psychometric Validation and Preliminary Clinical Correlation of an Experiential Foraging Task

Measuring the function of decision-making systems reliably is a key goal to assess cognitive functions that underlie psychopathology. However, few metrics are demonstrably reliable, clinically relevant, and able to capture complex overlapping cognitive domains while quantifying heterogeneity across individuals. The WebSurf task is a reverse-translational human experiential foraging paradigm that indexes naturalistic and clinically relevant decision-making. To determine its potential clinical utility, we examined the psychometric properties and clinical correlates of behavioral parameters extracted from WebSurf in an initial exploratory experiment (<i>N</i> = 132) and a preregistered validation experiment (N = 109). Behavior was stable over repeated administrations of the task, as were individual differences. The ability to measure decision-making consistently supports WebSurf's potential utility to predict treatment response, monitor clinical change, and define neurocognitive profiles associated with psychopathology. Moreover, specific WebSurf metrics were predicted by psychiatric symptoms in a replicable manner. Mania and externalizing symptom profiles predicted variability in reward pursuit, while externalizing profiles also predicted reward evaluation. These replicable results suggest that WebSurf and similar paradigms offer promising platforms for computational psychological methods, providing reliable, clinically relevant metrics of decision-making that may enhance psychiatric assessment and personalize treatment approaches.