A proof-of-concept study testing the factor structure of the Stop Signal Task: overlap with substance use and mental health symptoms.

Abstract

Background: Research utilizing experimental tasks usually does not report estimates of internal reliability of measurement. However, modern measurement theories conceptualize reliability as sample dependent indicating that reliability should be empirically demonstrated in the samples used to make inferences.Objectives: Test whether confirmatory factor analytic (CFA) estimates of reliability can be applied to a commonly used task measuring response inhibition (the Stop Signal Task) to predict substance use (alcohol and cannabis) and mental health symptoms.Methods: Thirty-seven participants between the ages of 18-20 (72% female; 16% Asian, 3% Native American, 11% Black or African American, 59% White; 32% Latino/a/x) were recruited via social media advertisement and attended a laboratory visit. The Stop Signal Reaction Time (SSRT) was calculated as the outcome for three experimental blocks and used as indicators in a CFA.Results: CFA suggests the task yields reliable scores; factor loadings were statistically significant (p < .05) and substantial (standardized loadings ranged from .74 to .94). However, reliability increased across experimental blocks and error was non-trivial (ranging from 50% to 12% of the variance). The inhibition factor predicted higher maximum number of drinks consumed (β = .37, p < .05), higher frequency of cannabis use (β = .39, p < .05), and more cannabis use occasions within using days (β = .40, p < .05), as well as facets of mental health (anxious/depression, attention, and anxiety problems; all p's < .05).Conclusion: Results support the utility of CFA to test for reliability of measurement, with the ability to inhibit dominant responses serving as a transdiagnostic correlate of substance use and mental health problems.