Parent Ratings of Impulsivity and Inhibition Predict State Testing Scores

Abstract

One principle of cognitive development is that earlier intervention for educational difficulties tends to improve outcomes such as future educational and career success. One possible way to help students who struggle is to determine if they process information differently. Such determination might lead to clues for interventions. For example, early information processing requires attention before the information can be identified, encoded, and stored. The aim of the present study was to investigate whether parent ratings of inattention, inhibition, and impulsivity, and whether error rate on a reflexive attention task could be used to predict child scores on state standardized tests. Finding such an association could provide assistance to educators in identifying academically struggling children who might require targeted educational interventions. Children (N = 203) were invited to complete a peripheral cueing task (which measures the automatic reorienting of the brain’s attentional resources from one location to another). While the children completed the task, their parents completed a questionnaire. The questionnaire gathered information on broad indicators of child functioning, including observable behaviors of impulsivity, inattention, and inhibition, as well as state academic scores (which the parent retrieved online from their school). We used sequential regression to analyze contributions of error rate and parent-rated behaviors in predicting six academic scores. In one of the six analyses (for science), we found that the improvement was significant from the simplified model (with only family income, child age, and sex as predictors) to the full model (adding error rate and three parent-rated behaviors). Two additional analyses (reading and social studies) showed near significant improvement from simplified to full models. Parent-rated behaviors were significant predictors in all three of these analyses. In the reading score analysis, error rate showed a trend for significance as a predictor. In the analyses for math, language arts, and the overall academic score (created using principal component analysis), the simplified model best predicted academic outcomes