ORIGINAL ARTICLESVisual-Motor Integration Skills Accuracy of Predicting ReadingSanti, Kristi L.*; Francis, David J.*; Currie, Debra†; Wang, Qianqian Author Information *PhD †OD, MS, FAAO College of Education (KLS, QW), Department of Psychology (DJF), and College of Optometry (DC), University of Houston, Houston, Texas. Kristi L. Santi 491 Farish Hall College of Education University of Houston Houston, TX 77204-5027 e-mail: [email protected] Optometry and Vision Science: February 2015 - Volume 92 - Issue 2 - p 217-226 doi: 10.1097/OPX.0000000000000473 Buy Metrics Abstract Purpose This article investigated the contribution of visual-motor integration (VMI) to reading ability when known predictors of later reading outcomes were also present in the data analysis. Methods Participants included 778 first and second grade students from a large diverse urban district in Texas. The data were analyzed using multiple regression models with a forced entry of predictors for each regression model, and each model was run separately for each outcome. Results The results indicate that VMI drops out of the prediction models once more reading- and language-specific skills are introduced. Conclusions Although VMI skills make a statistically significant contribution in some aspects of the regression model, the reduction in contribution reduces the predictive validity of VMI skills. Therefore, a VMI skill measure will not sufficiently determine if a child has a reading disability. © 2015 American Academy of Optometry
