School Psychologists' and Teachers' Perceptions of Data Used in the Identification of Behaviorally Disordered Students

To assess the availability, quality, and sufficiency of file information for students identified as behaviorally disordered, 60 student files were rated by 60 school psychologists and 60 elementary teachers of the behaviorally disordered. Student files consisted of information available at the time of staffing for students who were subsequently identified as behaviorally disordered. It was found that traditional types of data (academic and intellectual measures) were rated as being available and of highest quality, whereas behaviorally oriented data (e.g., actual behavior data) were available, but of lowest quality. In addition, 87% of the student files were perceived by at least one rater as containing inadequate information for the purpose of identifying students as behaviorally disordered. When asked about their opinions regarding the value of nine types of data for making identification decisions (without referring to specific student files), psychologists' and teachers' mean ratings were quite similar. Implications of these findings are discussed in relation to practices currently used to identify behaviorally disordered students.

Prediction of Brain Damage in a Neurological Population with Cerebrovascular Accidents

A total of 15 intellectual and 12 sensory-motor variables were examined as predictors of brain damage in a neurological population with cerebrovascular accidents. Results obtained via Student's t tests and multiple regression analyses demonstrate that it is possible to predict brain damage significantly in this clinical population. Specific conclusions were: (1) as single predictor variables, sensory-motor measures are superior to intellectual measures; (2) brain damage as measured behaviorally is consistent across patient populations in neurological, psychiatric, and neurological sub-groups with CVA; and, (3) multiple variant prediction holds promise for diagnosis of brain damage in a CVA population.