Prevalence and profile of treatment non-responders in Autism Early Intervention - Early interventions for preschoolers with Autism Spectrum Disorder (ASD) demonstrate powerful
effects in improving cognitive and language outcomes. However, there is marked individual variability in
intervention response, and a sizeable minority of children remain minimally verbal despite receiving
evidence-supported treatments targeting language. A fine-grained characterization of subgroups of
individuals who do not respond to established treatments has been a critical step to inform development of
new targeted interventions and treatment algorithms across a variety of medical and psychiatric conditions,
such as hypertension, epilepsy, and depression, leading to improvements in treatment outcomes.
In the ASD field, lack of knowledge on the characteristics of children who show minimal treatment
improvements is a critical barrier to the development of targeted interventions for this subgroup, leading to
a profound emotional and economic burden for affected children, their families and the community. The
current project addresses this critical gap by proposing the first large-scale effort to examine the prevalence
and profile of children with ASD who show minimal spoken language progress in response to established
interventions targeting language. This will be achieved through an aggregate dataset from multiple
evidence-supported early intervention programs involving an overall sample of 1326 well-characterized
preschoolers with ASD who received a comprehensive intervention targeting spoken language (among
other domains). This will allow us to (1) determine the prevalence of children who remain minimally verbal
despite receiving evidence-supported intervention, (2) outline an empirically-derived profile of ‘suboptimal
responders’ in the language domain through the analysis of variables that distinguish treated minimally
verbal children who show language improvements versus those who show minimal progress despite
receiving the same amount of intervention, and (3) test predictions derived from different accounts of the
putative mechanisms leading to minimal intervention response in the spoken language domain.
As demonstrated in other areas of health care, understanding characteristics and mechanisms of
‘minimal treatment response’ has the potential to inform the development of treatment algorithms to
address the needs of ‘minimal responders’, such as dose escalation, treatment augmentation, and treating
the constraints that impede progress. The current project will represent an effort of unprecedented
scale to characterize and explain the phenomenon of ‘minimal intervention response’ in ASD early
intervention. This will allow us to move beyond anecdotal accounts of poor treatment response in ASD,
informing theoretical models of treatment response, and generating theoretically and empirically-based
recommendations for future intervention approaches and treatment algorithms to address the unmet needs
of children with ASD who show minimal language improvement in response to current treatment options.
