Using self-reported data to assess the validity of driving simulation data

In this article, we use self-reported driving behaviors from a written questionnaire to assess the measurement validity of data derived from a driving simulation. The issue of validity concerns the extent to which measures from the experimental context map onto constructs of interest. Following a description of the experimental methods and setting, an argument for the face validity of the data is advanced. Convergent validity was assessed by regressing behaviors observed in the driving simulator on self-reported measures of driving behaviors. Significant relationships were found across six measures: accidents, speeding, velocity, passing, weaving between traffic, and behavior at stop signs. Concurrent validity was evaluated with an analysis of simulator accident involvement and attention deficit hyperactivity disorder status. Discrimmant validity was assessed using a multitrait-multimethod matrix of simulator and questionnaire data. We concluded that although the relationship between self-reported behaviors and observed responses in the simulator falls short of perfect correspondence, the data collected from the driving simulator are valid measures of the behaviors of interest.