Date of Award
Open Access Dissertation
Scott L. Decker
Previous research has demonstrated a strong relationship between symptoms of ADHD and academic underachievement. Interventions specific to academic deficits in children with ADHD are available, which are most effective if implemented before secondary concerns arise. Performance based screening is one method for determining the need for early intervention, yet extant measures of attention have limitations for the purposes of large-scale screening. The current study evaluated the psychometric properties and guiding conceptual model of a novel instrument of executive functioning—the GNG Screen— which measures response inhibition via a go/no-go paradigm. Results from Rasch modeling and exploratory factor analysis provide preliminary psychometric support for dimensionality and reliability and suggest further revisions to future versions of the instrument. Importantly, dimensionality findings from the current study align with previous evidence indicating EFs are difficult to measure in isolation. Replicating analyses using a more targeted sample of participants, as well as eliminating redundant and/or outfitting blocks should improve dimensionality findings. Further, item difficulty gleaned from Rasch analyses generally support the guiding conceptual model; however, examination of differences in difficulty suggests a reduction in length may be sufficient for capturing the same range of difficulty. Suggestions for future test development and the establishment of expectations for performance are discussed, in addition to directions for future research and clinical implications.
Bridges, R.(2021). The Development and Validation of an Automated Screener of Attention. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/6537