RESUMEN
The present study assessed the ability of the Dean-Woodcock Sensory-Motor Battery (DWSMB) to distinguish between normal subjects and neurologically impaired individuals. Scores from the subtests of the DWSMB for 250 normal and 250 neurologically impaired individuals were randomly assigned to two equal groups to allow for cross-validation. The DWSMB was able to correctly identify 92.8% of the cases, identifying 94.4% of the normal population and 91.2% of the neurologically impaired subjects. The cross-validation correctly identified 87.2% of the total cases, identifying 91.2% of the normal subjects and 83.2% of the neurologically impaired subjects. An additional discriminant analysis indicated that the DWSMB correctly identified the following cases: 44.9% cardio-vascular accidents, 66.7% multiple sclerosis, 40% seizures, 42% traumatic brain injuries, 62.7% dementia, and 54.5% Parkinson's disease. The results add to the validity of the DWSMB by providing evidence of its ability to differentiate between neurologically impaired and normal individuals.
Asunto(s)
Encefalopatías/diagnóstico , Corteza Cerebral/fisiopatología , Pruebas Neuropsicológicas , Percepción/fisiología , Desempeño Psicomotor/fisiología , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Encefalopatías/fisiopatología , Encefalopatías/psicología , Niño , Preescolar , Análisis Discriminante , Femenino , Humanos , Masculino , Persona de Mediana Edad , Valor Predictivo de las Pruebas , Reproducibilidad de los ResultadosRESUMEN
This study investigated the relationship between reported perinatal complications and autism. The biological mothers of 183 autistic children and 209 normals completed the Maternal Perinatal Scale (MPS), a maternal self-report that surveys complications of pregnancies and medical conditions of the mother. Previous research in this area has been limited, with no definitive conclusions. A discriminant analysis was performed to consider perinatal complications as predictors between the autistic and normal subjects. Using the MPS, 65% of the autistic cases were correctly grouped. The results further indicated significant differences on 3 of the 10 factors of the MPS, in particular, Gestational Age, Maternal Morphology, and Intrauterine Stress. When considered in an item by item fashion, 5 items were found to significantly predict group membership (prescriptions taken during pregnancy, length of labor, viral infection, abnormal presentation at delivery, and low birth weight). Finally, 3 maternal medical conditions were found to be highly significant and contribute to the separation between groups, including urinary infection, high temperatures, and depression.