ArticleCognitive neuropsychiatry2025
Identifying overlapping and distinctive traits of autism and schizophrenia using machine learning classification.
Article in Cognitive neuropsychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Atypical integration of temporal evidence and priors in causality judgment along the autism-schizotypy continuum.iScience · 2026Article
- Response Inhibition in Autistic Children Predicts Positive Psychotic Symptoms in Young Adulthood-Results from an 8-Year Follow-up Study.Journal of autism and developmental disorders · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
introductionAutism spectrum disorder (ASD) and schizophrenia spectrum disorder (SSD) share some symptoms. We conducted machine learning classification to determine if common screeners used for research in non-clinical and subclinical populations, the Autism-Spectrum Quotient (AQ) and Schizotypal Personality Questionnaire - Brief Revised (SPQ-BR), could identify
methods1,397 undergraduates completed the SPQ-BR and AQ. Random forest classification modelled whether SPQ-BR item scores predicted AQ scores and factors, and vice versa. The models first used all item scores and then the least/most important features.
resultsRobust trait overlap allows for the prediction of AQ from SPQ-BR and vice versa. Results showed that AQ
conclusionsOverall, the SPQ-BR and AQ measure overlapping symptoms that can be isolated to some factors. Importantly, where we observe model failures, we capture distinctive factors. We provide guidance for leveraging existing screeners to avert misdiagnosis and advancing specific/selective biomarker identification.
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