Date of Award
Master of Science in Clinical Psychology (MSCP)
Susan Tinsley Li, Ph.D.
The aim of this study was to investigate the value of a measure of children’s attention to predict ADHD diagnoses. Theoretical and empirical literature on ADHD, children’s attention, assessment of children’s attention, and the TEA-Ch (Thames Valley Test Company, 1999), an objective measure of the attention, were reviewed. The TEA-Ch was designed without cutoff or overall scores from which to make inferences on performance. In an attempt to demonstrate the clinical utility of the measure, this study empirically investigated the strength of children’s performance on the TEA-Ch to accurately predict the presence or absence of an ADHD diagnosis, as well as relations between age, gender, and diagnosis. Additionally, cut points were established to investigate another method for identifying diagnoses with the TEA-Ch. Participants included 166 clinic-referred children whom received psychoeducational evaluations. Three subtests of the TEA-Ch were used as predictors of diagnosis. Results indicated that none of the subtests served as significant predictors of the presence or absence of an ADHD diagnosis. Contrary to expectation, the sustained attention component of the TEA-Ch did not serve as a better predictor than the selective and switching attention components. Similarly, the cut point findings were also contrary to expectation in that typical performance as opposed to low performance served as a better identifier of diagnosis for all three attention components. Consistent with expectations, the 2 standard deviation cut points yielded higher percentages of correctly identified cases. There were no significant differences in performance on the TEA-Ch between the children with and without ADHD diagnoses. As expected, there were significant relations between both age and gender and diagnosis the sample. Future research should include all subtests of the TEA-Ch as predictors of ADHD.
Pagenstecher, Laura (2010). Assessment of Children's Attention: Predicting Attention-Deficit/Hyperactivity Disorder Diagnoses (Master's thesis, Pacific University). Retrieved from: