Autism Research最新文献

Autism and borderline personality disorder (BPD) are each associated with increased psychiatric emergency department (PsyED) use, yet the service impact of coexisting autism–BPD remains unclear. We conducted a retrospective chart review of 1027 PsyED visits by 345 autistic adults (2018–2020) at an urban Canadian psychiatric hospital to compare service patterns between those with and without a BPD diagnosis. Sociodemographics, presenting reasons, restraint use, and disposition were analyzed using mixed-effects logistic regression. BPD was documented in 33.5% of visits and in 11.0% of unique autistic individuals, more often in birth-assigned females. Among all autistic individuals' PsyED visits, an autism diagnosis was documented in 60.2% of their text-based charts. Furthermore, autism was documented less frequently when BPD was recorded, suggesting possible diagnostic overshadowing. Suicidality as the primary reason for visit was associated with documented BPD (OR 4.366, 95% CI 2.659–7.169; p < 0.001). No significant differences were observed in disposition (discharge vs. admission) or restraint use between birth-assigned sex, BPD status, or documentation of autism within the visit. Findings underscore the need for sex-sensitive, autism-aware assessments and trauma-informed care in PsyED settings, and caution against diagnostic overshadowing that influences clinical decision-making. Limitations include a single-site sample and lack of autism diagnosis timing data, precluding temporal inferences. Future work should test targeted interventions and clarify mechanisms of suicidality among autistic individuals with coexisting BPD. Integrated autism–BPD care pathways, with specialized outpatient supports, sensory-friendly adaptations, and structured referrals, may improve care and reduce PsyED visits.

This preregistered study examined whether the gender identity phenotype differs between autistic and non-autistic children and adolescents, as well as whether gender identity traits aggregate similarly within their families. Study 1 involved four matched groups of autistic and non-autistic gender diverse youth referred to a UK specialist gender clinic, as well as cisgender autistic and non-autistic youth (n = 45 per group). Participants completed measures of gender typicality, discontentedness, anticipated future identity, and (parent-reported) dysphoria. Despite large and significant differences between cisgender and gender diverse youth across all gender-related measures, there were no significant differences between autistic and non-autistic participants within either gender group. Study 2 assessed recalled childhood gender behaviors and current gender dysphoria in the caregivers of participants from each group (N = 203). Caregivers of gender-referred youth, regardless of autism status, reported higher current dysphoric traits than caregivers of cisgender youth, but no differences were observed in recalled childhood gender-related behavior. Overall, the findings indicate that the gender phenotype of autistic youth is comparable to that of non-autistic youth within the same gender identity group, challenging the assumption that gender diversity in autism arises from different underlying mechanisms. Clinically, these results support equitable access to gender-related care for autistic and non-autistic gender diverse youth.

There is a growing body of evidence suggesting a concurrent association between attentional indices measured via eye tracking and autism symptoms. This meta-analysis examined the utility of eye tracking within longitudinal frameworks for autism interventions, including treatment monitoring and prediction of treatment response. We conducted a multivariate random-effects meta-analysis with a multilevel structure on 25 studies (828 autistic participants; M _age = 3–28 years) to estimate: (a) changes in eye-tracking outcomes from pre- to post-treatment (k = 179); and (b) the correlation between baseline eye-tracking profiles and changes in developmental outcomes following treatment (k = 39). Our analysis revealed a moderate and significant summary effect size for changes in eye-tracking outcomes from pre- to post-treatment (Hedge's g = 0.32, p = 0.010). Additionally, a moderate but non-significant summary effect size was revealed for the correlation between baseline eye-tracking outcomes and changes in developmental outcomes following treatment (Fisher's z = 0.20, p = 0.115), with moderation effects observed based on developmental domain and sex. These findings highlight the potential of eye tracking as a tool for monitoring treatment-induced changes in autistic individuals, while its predictive utility remains less supported. Limitations and implications are discussed.

Evidence indicates that autistic individuals are less susceptible to social influence and cognitive biases than non-autistic individuals. However, no studies have been conducted on the Dunning–Kruger effect (DKE) in autism. The DKE is a cognitive bias in which people with limited expertise in a specific domain overestimate their abilities. The purpose of this study is to compare autistic and non-autistic employees' self-assessments of their performance with their objective performance on a popular performance-based measure of analytic thinking disposition, the CRT (cognitive reflection test). After completing the task, no feedback or clues were provided regarding how well they performed. Participants were then asked to estimate how many questions they answered correctly and compare their performance to other participants by estimating the percentage of peers they outperformed. Results indicated asymmetric calibration of actual versus estimated CRT performance in autistic employees: In the low-performance group, autistic participants overestimated their abilities less than non-autistic participants. However, in the high-performance group, autistic participants underestimated their abilities more than non-autistic participants. Reduced susceptibility to the DKE highlights potential benefits of autistic employees in the workplace. Theoretical and practical implications consider the intersection of metacognitive awareness, autism, and the DKE in an organizational context.

Axon features that underlie the structural and functional organization of cortical pathways have distinct patterns in the brains of neurotypical controls (CTR) compared to individuals with Autism Spectrum Disorder (ASD). However, detailed axon study demands labor-intensive surveys and time-consuming analysis of microscopic sections from postmortem human brain tissue, making it challenging to systematically examine large regions of the brain. To address these challenges, we developed an approach that uses machine learning to automatically classify microscopic sections from ASD and CTR brains, while also considering different white matter regions: superficial white matter (SWM), which contains a majority of axons that connect nearby cortical areas, and deep white matter (DWM), which is comprised exclusively of axons that participate in long-range pathways. The result was a deep neural network that can successfully classify the white matter below the anterior cingulate cortex (ACC) of ASD and CTR groups with 98% accuracy, while also distinguishing between DWM and SWM pathway composition with high average accuracy, up to 80%. Examination of image regions important for network classification and misclassification, through sensitivity maps, along with multidimensional scaling analysis, helped identify key pathological markers of ASD and highlighted the spectrum of ASD heterogeneity and overlaps with neurotypical characteristics. Large datasets that can be used to expand training, validation, and testing of this network have the potential to automate high-resolution microscopic analysis of postmortem brain tissue, so that it can be used to systematically study white matter across brain regions in health and disease.