Choosing Treatments for Children with Autism Spectrum Disorders: The Influence of Parent and Child Factors

Background:  

Countless treatment options exist for children with autism spectrum disorders (ASD), and new therapies are introduced all the time. Choosing which therapeutic program(s) will be best for their children is undoubtedly a difficult task for parents (Green, 2007; Heflin & Simpson, 1998; Marcus, Kunce, & Schopler, 1997). Most often, parents of children with ASD implement several treatments simultaneously (Goin-Kochel, Myers, & Mackintosh, 2007; Stahmer & Aarons, 2009). However, little is known about the factors that influence their selection of various treatments. Parent-specific characteristics, such as education level (Wong & Smith, 2006) and family income (Mandell et al., 2008), as well as child-specific characteristics, such as ASD-symptom severity (Aman, Lam, & Collier-Crespin, 2003) have been reported to have an effect on parent decision-making processes. Yet, more research in this area is necessary in order to help clinicians understand how best to guide parents toward optimal treatment plans for their children with ASD.

Objectives:  

To investigate the relationship between classes of treatments parents choose for their children with ASD and specific parent and child factors.

Methods:  

Participants are children with ASD from the Simons Simplex Collection (SSC; https://sfari.org/simons-simplex-collection), which currently contains 1,887 affected probands between the ages of 4 and 18. All have received best-estimate clinical diagnoses of ASD via research-reliable administrations of the Autism Diagnostic Interview—Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS). Demographic information will include participant sex, age, race/ethnicity, parent education levels, and annual household income. Frequency counts will be generated for the number of children having ever used different classes of treatments, per parent report. Categories of treatments include: speech therapy, occupational therapy, psychotropic medications (e.g., antipsychotics, ADD/ADHD medications, anti-depressants), intensive behavioral therapies (e.g., ABA), biomedical treatments (e.g., chelation, special diets), and other treatments (e.g., social-skills training, picture exchange system). All data for this project have been collected via the SSC.

Results:  

Appropriate correlations will be computed to assess relationships between  each of the aforementioned categories of treatments and (a) the severity of children’s autism symptomatology via the Calibrated Severity Score (CSS; Gotham et al., 2009); (b) children’s verbal and nonverbal IQ scores; (c) parent education level; and (d) annual household income.  For any correlations that are statistically significant, subsequent logistic regression analyses will be computed to determine whether the specific child or parent factor(s) predict use of that type of treatment. Because this investigation is exploratory, there are no hypotheses about directions of potential correlations.

Conclusions:  

Findings from this study may uncover patterns of treatment use that are associated with specific demographic factors. This could have implications for the ways that clinicians or other helping professionals work with families to encourage use of treatments with the best empirical support.