Predictors of longitudinal ABA treatment outcomes for children with autism: A growth curve analysis
| Autor: | Jinho Kim, Michael Tiura, Hilary Baldi, Deanne Detmers |
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| Rok vydání: | 2017 |
| Předmět: |
Male
medicine.medical_treatment Affect (psychology) Severity of Illness Index Developmental psychology 03 medical and health sciences Applied Behavior Analysis 0302 clinical medicine Cognition Sex Factors Adaptation Psychological Developmental and Educational Psychology medicine Humans 0501 psychology and cognitive sciences Cognitive skill Longitudinal Studies Autistic Disorder Growth Charts Applied behavior analysis Child Social Behavior Adaptive behavior Communication 05 social sciences Age Factors Growth curve (biology) medicine.disease Developmental disorder Clinical Psychology Treatment Outcome Autism spectrum disorder Child Preschool Autism Educational Status Female Psychology 030217 neurology & neurosurgery 050104 developmental & child psychology Clinical psychology |
| Zdroj: | Research in developmental disabilities. 70 |
| ISSN: | 1873-3379 |
| Popis: | Background Autism spectrum disorder (ASD) is a developmental disorder that causes lifelong disability. Applied Behavior Analysis (ABA) is one of the most empirically studied and validated approaches for treating children diagnosed with ASD. Due to the heterogeneity of ASD, it is important to ascertain who will most benefit from treatment. Methods In this study, 35 participants, with a mean entry age of 3 years, received ABA therapy. Children were assessed at intake and every 6 months thereafter using the Developmental Profile-3 (DP-3) to measure their communication, social-emotional, adaptive behavior, and physical development (2–6 measures per participant). Using a growth curve analysis, we investigated if age, diagnosis severity, cognitive functioning, treatment hours, gender, parent education level, or primary language spoken at home significantly predicted the growth trajectories of ABA treatment outcomes. Results Our findings indicated that higher cognitive functioning significantly predicted faster growth across all four developmental domains, age at entry predicted initial status, and other variables only predicted growth rates in one or two domains. Implications Knowing the predictors of treatment outcome is important information for customizing treatment and this study demonstrated how longitudinal analyses can illuminate how participant characteristics affect the course of ABA therapy. |
| Databáze: | OpenAIRE |
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