Prediction of treatment outcomes and longitudinal analysis in children with autism undergoing intensive behavioral intervention

摘要

Outcome prediction is an important component of treatment planning and prognosis. However, reliable predictors of intensive behavioral intervention (IBI) have not been clearly established. IBI is an evidence-based approach to the systematic teaching of academic, social, verbal, and daily living skills to individuals with autism spectrum disorder. Incorporating longitudinal analysis to IBI outcome studies may help to identify outcome predictors of clinical value. Twenty-four children with autism underwent on average two years of IBI and completed language, daily living skills, cognitive, and motor assessments (Early Learning Accomplishment Profile and the Learning Accomplishment Profile-Diagnostic, 3rd edition) every six months. We used multilevel analysis to identify potential longitudinal predictors including gender, age, intervention intensity, intervention duration, total intervention time, and pre-intervention functioning. Results indicated that total intervention time, pre-intervention functioning, and age caused the greatest increase in goodness-of-fit of the longitudinal multilevel models. Longitudinal analysis is a promising analytical strategy to identify reliable predictors of the clinical outcome of IBI.