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 imp...