Loss of Acquired Skills: Regression in Young Children With Autism Spectrum Disorders

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.

Patterns of Restricted and Repetitive Behaviors in Toddlers and Young Children with Autism Spectrum Disorder

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.

Validation of Social Responsiveness Scale for Korean Preschool Children With Autism

Objective@#This cross-cultural study aims to examine the psychometric properties of the Social Responsiveness Scale (SRS) and to determine the best-estimate-cut-off scores for the diagnosis of autism spectrum disorder (ASD) in Korean preschool children. @*Methods@#A total of 563 children was recruited from multiple sources, including Seoul National University Bundang Hospital. Participants were assessed by a multidisciplinary research team using multiple diagnostic tools based on DSM-5 diagnostic criteria. Discriminative validity was tested by comparing the difference in SRS scores between ASD and non-ASD groups. Convergent validity was tested by examining correlations between SRS scores with other diagnostic instruments. A receiver operation characteristic curve analysis was conducted to test the sensitivity and specificity of SRS and to determine the best-estimate-cut-off scores for screening ASD in Korean preschool children. @*Results@#There were significant differences in the total SRS scores between the ASD (n=242) and non-ASD group (n=321) (p<0.01, 95% confidence interval [CI]: 14.08–17.24). The differences were significant even after adjusting for age. SRS scores were significantly correlated with other prescreening diagnostic tools for ASD. The best-estimate cut-off score to screen ASD was 55 (area under curve=0.88, sensitivity 78.1%, specificity 86.6%). @*Conclusion@#The SRS is a valid and reliable instrument to screen and aid in the diagnosis of ASD in Korean preschool children. The adjusted cut-off scores, notably lower than in the original U.S. version, may yield a more accurate diagnosis by reflecting transcultural differences.

Validating the Autism Diagnostic Interview-Revised in the Korean Population

Objective@#This study aimed to examine the validity of the Korean version of the Autism Diagnostic Interview-Revised (K-ADI-R) and determine its efficacy in identifying individuals with autism spectrum disorder (ASD). @*Methods@#Data were pooled from several past and ongoing studies as well as clinical records acquired at Seoul National University Bundang Hospital from 2008 to 2017. The K-ADI-R were administered and scored by trained research reliable examiners. Measurements to investigate the validity of the K-ADI-R was through sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and Cohen’s kappa. @*Results@#A total of 1,271 (age 88.9±62.42 months, male=927) participants were included. The K-ADI-R yielded strong psychometric properties with high sensitivity (86.06–99.27%), specificity (84.75–99.55%), PPV (92.33–99.72%), and NPV (79.43–98.64%). There were significant differences in item scores across the K-ADI-R diagnostic algorithm regardless of age and sex (p<0.001). Agreement between the K-ADI-R and other ASD related measurements ranged between levels of good to excellent. @*Conclusion@#Despite language or cultural boundaries, the K-ADI-R demonstrated high levels of sensitivity, specificity, PPV, and NPV within a wide range of participants; hence, suggesting promising usage as a valuable diagnostic instrument for individuals with ASD.

State and Trait Anxiety of Adolescents with Autism Spectrum Disorders

Objective@#This study examined how state and trait anxiety of adolescents with autism spectrum disorders (ASD) are associated with their demographic characteristics, repetitive and restricted behaviors (RRBs), and internalizing and externalizing problem behaviors. @*Methods@#A total of 96 participants with ASD (mean age=14.30 years; 91 males) completed a battery of tests including the State/Trait Anxiety Inventory (STAI), the Autism Diagnostic Interview-Revised, the Social Responsiveness Scale (SRS), and a cognitive test measuring intelligence quotient (IQ). Participants’ parents completed the Child Behavior Checklist (CBCL). Pearson’s correlations among age, IQ, two subscales of the STAI (i.e., STAIS and STAIT, measuring self-reported state and trait anxiety, respectively), and the Anxiety subscale of CBCL (i.e., CBCL-Anxiety, measuring parent-reported trait anxiety) were computed. Subsequently, Pearson’s correlations were computed among the three anxiety measures, RRBs, and problem behaviors, while controlling for participants’ age and IQ. @*Results@#The STAIS and CBCL-Anxiety were both significantly correlated with higher age, sensory sensitivity, depressive symptoms, somatic complaints, and aggressive behaviors. All three anxiety variables were significantly and positively correlated with total SRS RRB scores. Additionally, the STAIS and STAIT were significantly associated with more severe Compulsion/Adherence behaviors, and the CBCL-Anxiety was also significantly associated with more severe Rule-breaking Behaviors. @*Conclusion@#Self-reported state anxiety showed association patterns similar to those of parent-reported trait anxiety. Future studies investigating the precise operationalization of different anxiety instruments are needed to accurately measure the anxiety of adolescents with ASD.

Validation of Social Responsiveness Scale for Korean Preschool Children With Autism

Objective@#This cross-cultural study aims to examine the psychometric properties of the Social Responsiveness Scale (SRS) and to determine the best-estimate-cut-off scores for the diagnosis of autism spectrum disorder (ASD) in Korean preschool children. @*Methods@#A total of 563 children was recruited from multiple sources, including Seoul National University Bundang Hospital. Participants were assessed by a multidisciplinary research team using multiple diagnostic tools based on DSM-5 diagnostic criteria. Discriminative validity was tested by comparing the difference in SRS scores between ASD and non-ASD groups. Convergent validity was tested by examining correlations between SRS scores with other diagnostic instruments. A receiver operation characteristic curve analysis was conducted to test the sensitivity and specificity of SRS and to determine the best-estimate-cut-off scores for screening ASD in Korean preschool children. @*Results@#There were significant differences in the total SRS scores between the ASD (n=242) and non-ASD group (n=321) (p<0.01, 95% confidence interval [CI]: 14.08–17.24). The differences were significant even after adjusting for age. SRS scores were significantly correlated with other prescreening diagnostic tools for ASD. The best-estimate cut-off score to screen ASD was 55 (area under curve=0.88, sensitivity 78.1%, specificity 86.6%). @*Conclusion@#The SRS is a valid and reliable instrument to screen and aid in the diagnosis of ASD in Korean preschool children. The adjusted cut-off scores, notably lower than in the original U.S. version, may yield a more accurate diagnosis by reflecting transcultural differences.

Validating the Autism Diagnostic Interview-Revised in the Korean Population

Objective@#This study aimed to examine the validity of the Korean version of the Autism Diagnostic Interview-Revised (K-ADI-R) and determine its efficacy in identifying individuals with autism spectrum disorder (ASD). @*Methods@#Data were pooled from several past and ongoing studies as well as clinical records acquired at Seoul National University Bundang Hospital from 2008 to 2017. The K-ADI-R were administered and scored by trained research reliable examiners. Measurements to investigate the validity of the K-ADI-R was through sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and Cohen’s kappa. @*Results@#A total of 1,271 (age 88.9±62.42 months, male=927) participants were included. The K-ADI-R yielded strong psychometric properties with high sensitivity (86.06–99.27%), specificity (84.75–99.55%), PPV (92.33–99.72%), and NPV (79.43–98.64%). There were significant differences in item scores across the K-ADI-R diagnostic algorithm regardless of age and sex (p<0.001). Agreement between the K-ADI-R and other ASD related measurements ranged between levels of good to excellent. @*Conclusion@#Despite language or cultural boundaries, the K-ADI-R demonstrated high levels of sensitivity, specificity, PPV, and NPV within a wide range of participants; hence, suggesting promising usage as a valuable diagnostic instrument for individuals with ASD.

State and Trait Anxiety of Adolescents with Autism Spectrum Disorders

Objective@#This study examined how state and trait anxiety of adolescents with autism spectrum disorders (ASD) are associated with their demographic characteristics, repetitive and restricted behaviors (RRBs), and internalizing and externalizing problem behaviors. @*Methods@#A total of 96 participants with ASD (mean age=14.30 years; 91 males) completed a battery of tests including the State/Trait Anxiety Inventory (STAI), the Autism Diagnostic Interview-Revised, the Social Responsiveness Scale (SRS), and a cognitive test measuring intelligence quotient (IQ). Participants’ parents completed the Child Behavior Checklist (CBCL). Pearson’s correlations among age, IQ, two subscales of the STAI (i.e., STAIS and STAIT, measuring self-reported state and trait anxiety, respectively), and the Anxiety subscale of CBCL (i.e., CBCL-Anxiety, measuring parent-reported trait anxiety) were computed. Subsequently, Pearson’s correlations were computed among the three anxiety measures, RRBs, and problem behaviors, while controlling for participants’ age and IQ. @*Results@#The STAIS and CBCL-Anxiety were both significantly correlated with higher age, sensory sensitivity, depressive symptoms, somatic complaints, and aggressive behaviors. All three anxiety variables were significantly and positively correlated with total SRS RRB scores. Additionally, the STAIS and STAIT were significantly associated with more severe Compulsion/Adherence behaviors, and the CBCL-Anxiety was also significantly associated with more severe Rule-breaking Behaviors. @*Conclusion@#Self-reported state anxiety showed association patterns similar to those of parent-reported trait anxiety. Future studies investigating the precise operationalization of different anxiety instruments are needed to accurately measure the anxiety of adolescents with ASD.

How Do Children with Autism Spectrum Disorder Encode and Reproduce Visuospatial Stimuli?: Investigation into Visuospatial Processing Abilities and Styles

Objective@#The purpose of this study was to examine the visuospatial processing abilities of children with autism spectrum disorder (ASD) using the Rey Osterrieth Complex Figure (ROCF). @*Methods@#One-hundred thirty-four children with ASD [mean age (MA)=113.56 months], 150 siblings of children with ASD (MA= 111.67 months), and 55 typically developing (TD) children (MA=109.02 months) were included in this study. During their one-time visit, participants completed the ROCF, various autism diagnostic assessments, and the Korean-Leiter International Performance ScaleRevised. Repeated-measures Analysis of Covariance (ANCOVA) and post-hoc Tukey-Kramer comparisons were computed to compare the ROCF scores. Partial correlations and multiple regressions were computed to examine the association between ROCF scores and the severity of autistic symptoms, as measured by the Autism Diagnostic Interview-Revised (ADI-R) among children with ASD. @*Results@#There were significant main effects of the analysis group in Structural and Incidental Accuracy, Error, and Style. More siblings than TD children drew in a part-oriented way, but the performance of the sibling group was comparable or superior to that of the TD group in all parameters. Social Interaction scores of children with ASD were significantly associated with Organization scores in Copy condition. Whether or not a child drew in the Part-Oriented style significantly predicted his/her repetitive and restricted behavior scores. @*Conclusion@#The findings add to the evidence for altered visuospatial processing patterns of ASD as a potential inherent and genetic trait and suggest that this particular cognitive style should not be considered as a deficit. Educational and theoretical implications are discussed.

The Use of Artificial Intelligence in Screening and Diagnosis of Autism Spectrum Disorder: A Literature Review

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.