The Hidden Spectrum Within Eating Disorders: Clustering Neurodivergent Traits and Sensory Sensitivity.

Researchers studied 164 women with eating disorders and found four distinct groups based on autism-like traits, sensory sensitivities, and social skills. These groups had different levels of eating disorder symptoms and challenges. The study suggests that understanding these differences could help doctors provide better, more personalized treatment for each person's specific needs, especially for those who are neurodivergent.

This study examined neurodevelopmental profiles among 164 cisgender females with eating disorders, using cluster analysis to identify distinct subgroups based on autistic traits, sensory sensitivity, and social cognition. Four distinct profiles emerged: a neurodivergent high-risk group, cognitively compensated group, sensory-reactive group, and classically symptomatic group. These clusters differed significantly in autism traits, sensory processing, social cognition, and eating disorder severity. A predictive model achieved 94% accuracy in classifying individuals into these clusters.

The findings suggest that neurodevelopmental dimensions meaningfully differentiate eating disorder presentations and could inform personalized treatment approaches, particularly for individuals with neurodivergent features.

Clinicians should assess autistic traits and sensory processing in eating disorder patients. Different neurodevelopmental profiles may require adapted interventions. Integrating autism screening tools into standard eating disorder assessment could improve treatment personalization and outcomes.

Single study with unclear methodology details. Limited to cisgender females only. Cross-sectional design prevents causal inference. Validation in independent samples needed. Generalizability to other populations uncertain.

Emerging research suggests that autistic traits and sensory sensitivities are prevalent among individuals with eating disorders (EDs), particularly females. Traditional diagnostic approaches may overlook the heterogeneity of neurodevelopmental features within this population. A person-centered approach could uncover meaningful subgroups and guide individualized treatment strategies. This study aimed to identify neurocognitive profiles among cisgender female ED patients, focusing on autistic traits, sensory sensitivity, social cognition, and clinical severity, through a dimensional and person-centered clustering approach.

A total of 164 cisgender female patients were assessed using the Autism Spectrum Quotient (AQ-10), Girls Questionnaire for Autism Spectrum Condition (GQ-ASC), Sensory Perception Quotient (SPQ-10), Story-based Empathy Task (SET), and clinical measures including the Eating Disorder Examination Questionnaire (EDE-Q), Body Uneasiness Test (BUT), and Symptom Checklist-90-Revised (SCL-90-R). Hierarchical cluster analysis (Ward's method) was conducted on standardized scores. Between-cluster comparisons and multinomial logistic regression assessed the robustness and predictive validity of the cluster solution. Four distinct clusters emerged, differing significantly in autistic traits, sensory sensitivity, social cognition, and ED severity (all p < 0.001).

Profiles included a neurodivergent high-risk group, a cognitively compensated group, a sensory-reactive group, and a classically symptomatic group. Multinomial logistic regression predicted cluster membership with 94% accuracy. Neurodevelopmental dimensions meaningfully differentiate ED subgroups and may inform more personalized, stratified care. These findings highlight the importance of integrating autistic traits, sensory processing, and social cognition into ED assessment and treatment planning.

This study identifies four distinct neurodevelopmental and clinical profiles among women with eating disorders, defined by differences in autistic traits, sensory sensitivity, and social cognition. Understanding these profiles can help clinicians recognize the diversity of presentations in eating disorders and adapt interventions to the specific needs of each individual, particularly those with neurodivergent features, ultimately promoting more personalized and effective care.