Streamlining Adult Autism Diagnosis: High-yield DSM-5-TR Predictors and Sex-Based Considerations
摘要
This study examined which DSM-5-TR criteria most strongly predict autism diagnosis in adults and whether predictive patterns differ by sex assigned at birth.
MethodsA team of neurodivergent researchers designed and carried out the study with input from autistic psychologists and community members. The participants were English-speaking adults who sought telehealth services from an autism mental health service provider. A convenience sample of 234 adults (mean age 34.25 years, 72.2% assigned female at birth) underwent an autism evaluation through a telehealth organization. Licensed psychologists rated seven DSM-5-TR domains on a 0–2 scale based on structured interviews and standardized measures. Ridge penalized logistic regression was used.
ResultsResults indicated that social-emotional reciprocity (OR = 5.21) and nonverbal communication (OR = 4.82) were the strongest predictors of autism diagnosis, followed by relationship differences (OR = 3.63), need for routines (OR = 2.57), and repetitive behaviors (OR = 2.20). Intense interests and sensory processing differences showed limited predictive utility. Sex assigned at birth did not meaningfully enhance diagnostic prediction beyond core symptom presentation, except for a modest interaction effect with nonverbal communication in individuals assigned female at birth.
ConclusionsThese findings suggest clinicians may benefit from prioritizing assessment of social-emotional reciprocity and nonverbal communication domains when evaluating adults for autism, potentially improving diagnostic efficiency and accuracy.