Autism spectrum disorder involves challenges in social communication and restricted, repetitive behaviors. Historically, males have received autism diagnoses at comparatively high rates, prompting an underrepresentation of females in research and an incomplete understanding of sex-specific symptom presentations and comorbidities. This review examines sex differences in the prevalence of common comorbidities of autism to inform tailored clinical practices. These conditions include attention deficit hyperactivity disorder, anxiety disorders, conduct disorder, depression, epilepsy, intellectual disability, and tic disorders. Attention deficit hyperactivity disorder is prevalent in both sexes; however, females may more frequently exhibit the inattentive subtype. Anxiety disorders display inconsistent sex differences, while conduct disorder more frequently impacts males. Depression becomes more common with age; some studies indicate more pronounced symptoms in adolescent girls, while others suggest greater severity in males. Epilepsy is more prevalent in females, especially those with intellectual disabilities. Despite displaying a male predominance, intellectual disability may exacerbate the severity of autism to a greater degree in females. No clear sex differences have been found regarding tic disorders. Overall, contributors to sex-based differences include biases stemming from male-centric diagnostic tools, compensatory behaviors like camouflaging in females, genetic and neurobiological differences, and the developmental trajectories of comorbidities. Recognizing these factors is crucial for developing sensitive diagnostics and sex-specific interventions. Inconsistencies in the literature highlight the need for longitudinal studies with large, diverse samples to investigate autism comorbidities across the lifespan. Understanding sex differences could facilitate earlier identification, improved care, and personalized interventions, thus enhancing quality of life for individuals with autism.

Autism spectrum disorder involves challenges in social communication and restricted, repetitive behaviors. Historically, males have received autism diagnoses at comparatively high rates, prompting an underrepresentation of females in research and an incomplete understanding of sex-specific symptom presentations and comorbidities. This review examines sex differences in the prevalence of common comorbidities of autism to inform tailored clinical practices. These conditions include attention deficit hyperactivity disorder, anxiety disorders, conduct disorder, depression, epilepsy, intellectual disability, and tic disorders. Attention deficit hyperactivity disorder is prevalent in both sexes; however, females may more frequently exhibit the inattentive subtype. Anxiety disorders display inconsistent sex differences, while conduct disorder more frequently impacts males. Depression becomes more common with age; some studies indicate more pronounced symptoms in adolescent girls, while others suggest greater severity in males. Epilepsy is more prevalent in females, especially those with intellectual disabilities. Despite displaying a male predominance, intellectual disability may exacerbate the severity of autism to a greater degree in females. No clear sex differences have been found regarding tic disorders. Overall, contributors to sex-based differences include biases stemming from male-centric diagnostic tools, compensatory behaviors like camouflaging in females, genetic and neurobiological differences, and the developmental trajectories of comorbidities. Recognizing these factors is crucial for developing sensitive diagnostics and sex-specific interventions. Inconsistencies in the literature highlight the need for longitudinal studies with large, diverse samples to investigate autism comorbidities across the lifespan. Understanding sex differences could facilitate earlier identification, improved care, and personalized interventions, thus enhancing quality of life for individuals with autism.

Autism spectrum disorder involves challenges in social communication and restricted, repetitive behaviors. Historically, males have received autism diagnoses at comparatively high rates, prompting an underrepresentation of females in research and an incomplete understanding of sex-specific symptom presentations and comorbidities. This review examines sex differences in the prevalence of common comorbidities of autism to inform tailored clinical practices. These conditions include attention deficit hyperactivity disorder, anxiety disorders, conduct disorder, depression, epilepsy, intellectual disability, and tic disorders. Attention deficit hyperactivity disorder is prevalent in both sexes; however, females may more frequently exhibit the inattentive subtype. Anxiety disorders display inconsistent sex differences, while conduct disorder more frequently impacts males. Depression becomes more common with age; some studies indicate more pronounced symptoms in adolescent girls, while others suggest greater severity in males. Epilepsy is more prevalent in females, especially those with intellectual disabilities. Despite displaying a male predominance, intellectual disability may exacerbate the severity of autism to a greater degree in females. No clear sex differences have been found regarding tic disorders. Overall, contributors to sex-based differences include biases stemming from male-centric diagnostic tools, compensatory behaviors like camouflaging in females, genetic and neurobiological differences, and the developmental trajectories of comorbidities. Recognizing these factors is crucial for developing sensitive diagnostics and sex-specific interventions. Inconsistencies in the literature highlight the need for longitudinal studies with large, diverse samples to investigate autism comorbidities across the lifespan. Understanding sex differences could facilitate earlier identification, improved care, and personalized interventions, thus enhancing quality of life for individuals with autism.

Autism spectrum disorder involves challenges in social communication and restricted, repetitive behaviors. Historically, males have received autism diagnoses at comparatively high rates, prompting an underrepresentation of females in research and an incomplete understanding of sex-specific symptom presentations and comorbidities. This review examines sex differences in the prevalence of common comorbidities of autism to inform tailored clinical practices. These conditions include attention deficit hyperactivity disorder, anxiety disorders, conduct disorder, depression, epilepsy, intellectual disability, and tic disorders. Attention deficit hyperactivity disorder is prevalent in both sexes; however, females may more frequently exhibit the inattentive subtype. Anxiety disorders display inconsistent sex differences, while conduct disorder more frequently impacts males. Depression becomes more common with age; some studies indicate more pronounced symptoms in adolescent girls, while others suggest greater severity in males. Epilepsy is more prevalent in females, especially those with intellectual disabilities. Despite displaying a male predominance, intellectual disability may exacerbate the severity of autism to a greater degree in females. No clear sex differences have been found regarding tic disorders. Overall, contributors to sex-based differences include biases stemming from male-centric diagnostic tools, compensatory behaviors like camouflaging in females, genetic and neurobiological differences, and the developmental trajectories of comorbidities. Recognizing these factors is crucial for developing sensitive diagnostics and sex-specific interventions. Inconsistencies in the literature highlight the need for longitudinal studies with large, diverse samples to investigate autism comorbidities across the lifespan. Understanding sex differences could facilitate earlier identification, improved care, and personalized interventions, thus enhancing quality of life for individuals with autism.

Autism spectrum disorder involves challenges in social communication and restricted, repetitive behaviors. Historically, males have received autism diagnoses at comparatively high rates, prompting an underrepresentation of females in research and an incomplete understanding of sex-specific symptom presentations and comorbidities. This review examines sex differences in the prevalence of common comorbidities of autism to inform tailored clinical practices. These conditions include attention deficit hyperactivity disorder, anxiety disorders, conduct disorder, depression, epilepsy, intellectual disability, and tic disorders. Attention deficit hyperactivity disorder is prevalent in both sexes; however, females may more frequently exhibit the inattentive subtype. Anxiety disorders display inconsistent sex differences, while conduct disorder more frequently impacts males. Depression becomes more common with age; some studies indicate more pronounced symptoms in adolescent girls, while others suggest greater severity in males. Epilepsy is more prevalent in females, especially those with intellectual disabilities. Despite displaying a male predominance, intellectual disability may exacerbate the severity of autism to a greater degree in females. No clear sex differences have been found regarding tic disorders. Overall, contributors to sex-based differences include biases stemming from male-centric diagnostic tools, compensatory behaviors like camouflaging in females, genetic and neurobiological differences, and the developmental trajectories of comorbidities. Recognizing these factors is crucial for developing sensitive diagnostics and sex-specific interventions. Inconsistencies in the literature highlight the need for longitudinal studies with large, diverse samples to investigate autism comorbidities across the lifespan. Understanding sex differences could facilitate earlier identification, improved care, and personalized interventions, thus enhancing quality of life for individuals with autism.

Objectives: Regression, while not a core symptom of autism spectrum disorder (ASD), has been suggested to be a distinct subtype by previous studies. Therefore, this study aimed to explore the prevalence and clinical differences between those with and without regression in children with ASD. Methods: This study includes data from toddlers and young children aged 2–7 years acquired from other projects at Seoul National University Bundang Hospital. The presence and characteristics of regression were explored using question items #11–28 from the Autism Diagnostic Interview-Revised. Chi-square and independent t-tests were used to compare various clinical measurements such as autistic symptoms, adaptative behavior, intelligence, and perinatal factors. Results: Data from 1438 young children (1020 with ASD) were analyzed. The overall prevalence rate of regression, which was mainly related to language-related skills, was 10.2% in the ASD group, with an onset age of 24 months. Regarding clinical characteristics, patients with ASD and regression experienced ASD symptoms, especially restricted and repetitive interests and behaviors, with greater severity than those without regression. Furthermore, there were significant associations between regression and hypertension/placenta previa. Conclusion In-depth surveillance and proactive interventions targeted at young children with ASD and regression should focus on autistic symptoms and other areas of functioning.

OBJECTIVES: The detection of autism spectrum disorder (ASD) is based on behavioral observations. To build a more objective data-driven method for screening and diagnosing ASD, many studies have attempted to incorporate artificial intelligence (AI) technologies. Therefore, the purpose of this literature review is to summarize the studies that used AI in the assessment process and examine whether other behavioral data could potentially be used to distinguish ASD characteristics. METHODS: Based on our search and exclusion criteria, we reviewed 13 studies. RESULTS: To improve the accuracy of outcomes, AI algorithms have been used to identify items in assessment instruments that are most predictive of ASD. Creating a smaller subset and therefore reducing the lengthy evaluation process, studies have tested the efficiency of identifying individuals with ASD from those without. Other studies have examined the feasibility of using other behavioral observational features as potential supportive data. CONCLUSION: While previous studies have shown high accuracy, sensitivity, and specificity in classifying ASD and non-ASD individuals, there remain many challenges regarding feasibility in the real-world that need to be resolved before AI methods can be fully integrated into the healthcare system as clinical decision support systems.
Artificial Intelligence ; Autism Spectrum Disorder ; Autistic Disorder ; Behavior Observation Techniques ; Decision Support Systems, Clinical ; Delivery of Health Care ; Diagnosis ; Mass Screening ; Methods ; Sensitivity and Specificity

Objectives: Restricted and repetitive behaviors (RRBs) are a core symptom in the diagnosis of autism spectrum disorder (ASD). The complexity of behavioral patterns has called for the creation of phenotypically homogeneous subgroups among individuals with ASD.The purpose of this study was 1) to investigate the different types of RRBs and 2) to explore whether subgroups created by RRBs would show unique levels of functioning in toddlers and young children with ASD. Methods: A total of 313 children with ASD, aged 12–42 months were included in the analysis. The Autism Diagnostic Interview-Revised was used to obtain information on the different types of RRBs by grouping 15 items into six categories. The Vineland Adaptive Behaviors Scale, a parent-reported questionnaire, was used to measure adaptive functioning. A portion of the children were analyzed separately for verbal-related RRBs based on their expressive language level. Two-step cluster analysis using RRB groups as features was used to create subgroups. Analysis of covariance while covarying for age and language was performed to explore the clinical characteristics of each cluster group. Results: Sensory-related RRBs were the most prevalent, followed by circumscribed interests, interest in objects, resistance to change, and repetitive body movements. A subset of the children was analyzed separately to explore verbal-related RRBs. Four cluster groups were created based on reported RRBs, with multiple RRBs demonstrating significant delays in adaptive functioning. Conclusion Heterogeneity of RRBs emerges at a young age. The different patterns of RRBs can be used as valuable information to determine developmental trajectories with better implications for treatment approaches.

Objective: Sibling relationships in early childhood can have a positive impact on children’s social interaction and communication skills. Similarly, autistic children can benefit from interactions with their siblings, who can serve as readily available partners for social interaction. However, there is a lack of research on the effects of siblings based on specific characteristics of the sibling. Therefore, the aim of this study is to compare social interactions and communication skills of autistic children based on sibling status and characteristics. Methods: We conducted a retrospective data review involving 895 autistic children and their siblings at Seoul National University Bundang Hospital. Variety of diagnostic assessments or questionnaires were administered. Based on the characteristics of the data, Quade’s test for nonparametric analysis of covariance was used to compare autism-related symptoms and levels of functioning of the autistic child according to 1) sibling status, 2) birth order, 3) sex, and 4) diagnosis of the sibling. Pearson correlation was used to explore associations between the sibling age gap and different clinical scores. Results: Having siblings was associated with fewer difficulties in restricted and repetitive behaviors. Based on the comparison of the Autism Diagnostic Interview-Revised scores, autistic children with multiple siblings demonstrated better nonverbal behaviors. Autistic children with autistic siblings experienced greater difficulties in social interactions and communications, such as peer relationships, sharing enjoyment, and engaging in social imitative play. Conclusion The study revealed differences in social interactions and communication skills of autistic children based on sibling status, birth order, affected sibling, age gap, and sex.