Exclusion of females in autism research: Empirical evidence for a "leaky" recruitment-to-research pipeline.

Autism spectrum disorder (ASD) is characterized by challenges in social communication and the presence of repetitive behaviors or restricted interests. Notably, males are four times as likely as females to be diagnosed with autism. Despite efforts to increase representation and characterization of autistic females, research studies consistently enroll small samples of females, or exclude females altogether. Importantly, researchers often rely on standardized measures to confirm diagnosis prior to enrollment in research studies. We retrospectively analyzed the effects of one such measure (Autism Diagnostic Observation Schedule, ADOS) on research inclusion/exclusion rates by sex in autistic adults, all of whom had a preexisting community diagnosis of autism (n = 145, 95 male, 50 female). Using the ADOS as a confirmatory diagnostic measure resulted in the exclusion of autistic females at a rate over 2.5 times higher than that of autistic males. We compared sex ratios in our sample to those in other large, publically available datasets that rely either on community diagnosis (6 datasets, total n = 42,209) or standardized assessments (2 datasets, total n = 214) to determine eligibility of participants for research. Reliance on community diagnosis rather than confirmatory diagnostic assessments resulted in significantly more equal sex ratios. These results provide evidence for a "leaky" recruitment-to-research pipeline for females in autism research. LAY SUMMARY: Despite efforts to increase the representation of autistic females in research, studies consistently enroll small samples of females or exclude females altogether. We find that despite making up almost 50% of the initially recruited sample based upon self-report of community diagnosis, autistic females are disproportonately excluded from research participation as a result of commonly used autism diagnostic measures. In our sample, and several other publically available datasets, reliance on community diagnosis resulted in significantly more equal sex ratios.

Autism as a disorder of prediction.

A rich collection of empirical findings accumulated over the past three decades attests to the diversity of traits that constitute the autism phenotypes. It is unclear whether subsets of these traits share any underlying causality. This lack of a cohesive conceptualization of the disorder has complicated the search for broadly effective therapies, diagnostic markers, and neural/genetic correlates. In this paper, we describe how theoretical considerations and a review of empirical data lead to the hypothesis that some salient aspects of the autism phenotype may be manifestations of an underlying impairment in predictive abilities. With compromised prediction skills, an individual with autism inhabits a seemingly "magical" world wherein events occur unexpectedly and without cause. Immersion in such a capricious environment can prove overwhelming and compromise one's ability to effectively interact with it. If validated, this hypothesis has the potential of providing unifying insights into multiple aspects of autism, with attendant benefits for improving diagnosis and therapy.