The purpose of the present study was to examine whether an autism diagnosis could be predicted by social interaction as measured by the Ghuman-Folstein Screen for Social Interaction in conjunction with selected demographic variables (i.e., sex, age, ethnicity, mother's educational level, and socio-economic status). Univariate and bivariate analyses were conducted to explore each predictor variable and to explore possible relationships between predictor variables and autism. Binary logistic regression was utilized to examine various models' ability to predict autism. The final model was able to correctly identify 74% of the cases. The GF-SSI was the greatest predictor of autism. The selected demographic variables were not significant predictors of autism. These results were discussed in relation to the literature on sex, age, ethnicity, maternal education and socio-economic status. Future directions for research were also discussed.
|Advisor:||Morris, Richard J.|
|Commitee:||Bechtel, Robert, Ghuman, Jaswinder, Johnson, Christopher, Perfect, Michelle|
|School:||The University of Arizona|
|School Location:||United States -- Arizona|
|Source:||DAI-B 72/07, Dissertation Abstracts International|
|Subjects:||Developmental psychology, Psychology|
|Keywords:||Autism, Demographic variables, Prediction, Social interaction, Young children|
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