Assessing medication effects in the MTA study using neuropsychological outcomes
Article first published online: 29 APR 2005
Journal of Child Psychology and Psychiatry
Volume 47, Issue 5, pages 446–456, May 2006
How to Cite
Epstein, J. N., Keith Conners, C., Hervey, A. S., Tonev, S. T., Eugene Arnold, L., Abikoff, H. B., Elliott, G., Greenhill, L. L., Hechtman, L., Hoagwood, K., Hinshaw, S. P., Hoza, B., Jensen, P. S., March, J. S., Newcorn, J. H., Pelham, W. E., Severe, J. B., Swanson, J. M., Wells, K., Vitiello, B., Wigal, T. and the MTA Cooperative Study Group (2006), Assessing medication effects in the MTA study using neuropsychological outcomes. Journal of Child Psychology and Psychiatry, 47: 446–456. doi: 10.1111/j.1469-7610.2005.01469.x
- Issue published online: 9 JUN 2005
- Article first published online: 29 APR 2005
- Manuscript accepted 18 January 2005
- go/no-go test;
- reaction time;
Background: While studies have increasingly investigated deficits in reaction time (RT) and RT variability in children with attention deficit/hyperactivity disorder (ADHD), few studies have examined the effects of stimulant medication on these important neuropsychological outcome measures.
Methods: 316 children who participated in the Multimodal Treatment Study of Children with ADHD (MTA) completed the Conners’ Continuous Performance Test (CPT) at the 24-month assessment point. Outcome measures included standard CPT outcomes (e.g., errors of commission, mean hit reaction time (RT)) and RT indicators derived from an Ex-Gaussian distributional model (i.e., mu, sigma, and tau).
Results: Analyses revealed significant effects of medication across all neuropsychological outcome measures. Results on the Ex-Gaussian outcome measures revealed that stimulant medication slows RT and reduces RT variability.
Conclusions: This demonstrates the importance of including analytic strategies that can accurately model the actual distributional pattern, including the positive skew. Further, the results of the study relate to several theoretical models of ADHD.