Differential diagnosis of Hispanic children referred for autism spectrum disorders: complex issues.
Use a step-by-step decision-tree when assessing Hispanic children for autism; half may not have ASD but still need other supports.
01Research in Context
What this study did
Overton et al. (2007) looked at a small group of Hispanic children sent to an autism clinic. They tracked why some kids got an ASD label and others did not.
The team wrote down every extra diagnosis each child had. Then they built a simple decision-tree to help clinicians sort language delays from true autism.
What they found
Half of the Hispanic children did not meet ASD criteria after full testing. Most of those kids still had other problems like language disorder or ADHD.
The decision-tree cut confusion by forcing clinicians to check language, culture, and development in set order.
How this fits with other research
Begeer et al. (2009) showed doctors refer minority kids for autism checks less often. Terry’s tree helps catch the kids who do get referred but sit on the bubble.
Brynskov et al. (2017) found Venezuelan families wait three years from first worry to final diagnosis. Using Terry’s tree at the first visit could shave months off that wait.
Nijs et al. (2016) showed Latino children get fewer services even when autism severity matches White peers. Terry’s clearer diagnosis step may help families qualify for those services sooner.
Why it matters
If you evaluate Hispanic preschoolers, keep Terry’s decision-tree on your clipboard. Expect high rates of language delay and mixed diagnoses. Work through each branch before you decide. A firm, early call helps families skip the long delays shown in later studies and lands kids in therapy faster.
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02At a glance
03Original abstract
This study examines the decision-making process used for differential diagnosis of a sample of Hispanic children referred for autism spectrum disorders (ASDs). Of the sample of 28 children, 18 were diagnosed with ASDs. Of the 10 children who were not diagnosed with ASDs, 80% were found to have multiple diagnostic labels or comorbidities. Mann-Whitney U analyses determined the differences between the children with the most severe social impairment, children with less severe social impairment and the non-autistic children on several domains commonly used to assess ASDs. These analyses indicated significant differences in some characteristics of the children in the sample. Based on these results, a decision-tree for the diagnosis of children with and without ASDs with comorbid disorders was developed.
Journal of autism and developmental disorders, 2007 · doi:10.1007/s10803-006-0349-x