• Sleep Medicine and Psychophysiology
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• v.20 no.2
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• pp.53-58
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• 2013

Autism Spectrum Disorder (ASD) is characterized by persistent deficits in social communication and restricted, repetitive patterns of behavior and interest. Sleep problems are not uncommon in children with autism spectrum disorders. Symptoms of insomnia are the most frequent sleep problems in individuals with ASD. Sleep problems can cause significant difficulties in the daily life of children with ASD and their families. Genetic factor, deregulations of melatonin synthesis, extraneous environmental stimuli and psychiatric and medical conditions may cause sleep problems. The first line treatment of sleep problems in ASD includes managements for potential contributing factors and parent education about sleep hygiene care for child and behavioral therapy. Supplementation with melatonin may be effective before considering other medications, such as risperidone, clonidine, and mirtazapine.

• Korean Journal of Psychosomatic Medicine
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• v.23 no.2
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• pp.129-135
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• 2015

Objectives : In children and adolescents, the prevalence of overweight has increased in the last 20 years. little research is available on the prevalence of obesity in children with autism spectrum disorders(ASD). The purpose of our study was to determine the prevalence of overweight among a clinical population of children diagnosed with autism spectrum disorders(ASD). Methods : Retrospective chart review of children ages 3-18 years seen between 2012 and 2015 at a Konyang University hospital psychiatric clinic. Diagnostic, medical, and demographic information was extracted from the charts. Body mass index(BMI) was calculated from measures of height and weight recorded in the child's chart. The Center for Disease Control's BMI growth reference was used to determine an age and gender-specific BMI z-score for the children. Results : In our study, children with ASD compared to non ASD group had significantly higher BMI percentiles (p=0.032). The prevalence of overweight($BMI{\geq}85th$ to 95th percentiles) and obesity($BMI{\geq}95th$ percentiles) was 35% and 19% respectively in children with ASD and without ASD. Conclusions : Despite noted limitations, our data suggest that overweight and obesity in children with ASD are more prevalent than without ASD. Longitudinal and further study is needed to examine the factors associated with obesity in this population.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.31 no.3
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• pp.131-145
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• 2020

The microbiota-gut-brain axis, which refers to the bidirectional communication pathway between gut bacteria and the central nervous system, has a profound effect on important brain processes, from the synthesis of neurotransmitters to the modulation of complex behaviors such as sociability and anxiety. Previous studies have revealed that the gut microbiota is potentially related to not only gastrointestinal disturbances, but also social impairment and repetitive behavior-core symptoms of autism spectrum disorder (ASD). Although studies have been conducted to characterize the microbial composition in patients with ASD, the results are heterogeneous. Nevertheless, it is clear that there is a difference in the composition of the gut microbiota between ASD and typically developed individuals, and animal studies have repeatedly suggested that the gut microbiota plays an important role in ASD pathophysiology. This possibility is supported by abnormalities in metabolites produced by the gut microbiota and the association between altered immune responses and the gut microbiota observed in ASD patients. Based on these findings, various attempts have been made to use the microbiota in ASD treatment. The results reported to date suggest that microbiota-based therapies may be effective for ASD, but largescale, well-designed studies are needed to confirm this.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.30 no.4
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• pp.145-152
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• 2019

Objectives: The detection of autism spectrum disorder (ASD) is based on behavioral observations. To build a more objective datadriven 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.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.34 no.1
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• pp.51-56
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• 2023

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.

• Clinical and Experimental Pediatrics
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• v.64 no.6
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• pp.286-292
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• 2021

Background: The effect of exposure to environmental factors on autism spectrum disorders (ASD), especially during pregnancy, is unclear. Purpose: This meta-analysis investigated the association between exposure to pesticides and polychlorinated biphenyls (PCBs) during pregnancy and ASD risk among children. Methods: We searched Scopus, PubMed, Web of Science, and ProQuest for articles published through September 2019. Random-effects models were used to examine the association among studies using pooled odds ratios (ORs) and their 95% confidence intervals (CI). I2 tests were used to measure interstudy heterogeneity. Results: The pooled OR indicated a significant association between PCB and pesticide exposure during pregnancy and ASD risk among children (OR, 1.80; 95% CI, 1.26-2.34; and OR, 1.20; 95% CI, 1.02-1.39), respectively. Conclusion: Findings of the present study indicate that exposure to pesticides and PCBs during pregnancy may affect the risk of ASD among children.

• Phonetics and Speech Sciences
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• v.15 no.2
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• pp.53-59
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• 2023

Detection of children with autism spectrum disorder (ASD) based on speech has relied on predefined feature sets due to their ease of use and the capabilities of speech analysis. However, clinical impressions may not be adequately captured due to the broad range and the large number of features included. This paper demonstrates that the knowledge-driven speech features (KDSFs) specifically tailored to the speech traits of ASD are more effective and efficient for detecting speech of ASD children from that of children with typical development (TD) than a predefined feature set, extended Geneva Minimalistic Acoustic Standard Parameter Set (eGeMAPS). The KDSFs encompass various speech characteristics related to frequency, voice quality, speech rate, and spectral features, that have been identified as corresponding to certain of their distinctive attributes of them. The speech dataset used for the experiments consists of 63 ASD children and 9 TD children. To alleviate the imbalance in the number of training utterances, a data augmentation technique was applied to TD children's utterances. The support vector machine (SVM) classifier trained with the KDSFs achieved an accuracy of 91.25%, surpassing the 88.08% obtained using the predefined set. This result underscores the importance of incorporating domain knowledge in the development of speech technologies for individuals with disorders.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.35 no.1
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• pp.22-28
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• 2024

Interventions for targeted symptoms are important when setting treatment strategies for individuals with autism spectrum disorder (ASD) and developmental disabilities. Especially, the goal should be to achieve individual "niche construction" by allowing them to select and adjust an environment where they can demonstrate their special characteristics and strengths. In addition, these choices should vary depending on the stage of development of each person with ASD and developmental disabilities. It is necessary to establish a detailed and systematic plan for diagnosis and treatment necessary for infants and toddlers, school placement in school age, and employment or self-reliance in adult transition period to establish customized treatment strategies that fit the individual level of people with ASD and developmental disabilities.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.25 no.4
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• pp.187-195
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• 2014

Objectives : The objective of this study was to investigate the relationship between restricted, repetitive behaviors and interests (RRBI) and autistic symptoms in Korean high functioning autism spectrum disorder (ASD) children and to examine the structure of RRBI. Methods : Participants included 147 high functioning ASD subjects and 181 unaffected siblings. ASD subjects were divided into two groups based on the presence of RRBI. The domain scores of the Korean version of Autism Diagnostic Interview-Revised (K-ADI-R), Korean version of Asperger Syndrome Diagnostic Scale and total scores of Korean translated version of Social Responsiveness Scale, Korean version of Social Communication Scale were used for comparison of ASD symptoms between the groups. Eleven items from the RRBI domain of the K-ADI-R were used in principal axis factor analysis (PAF). Results : A statistically lower nonverbal IQ score was observed for ASD with RRBI than for ASD without RRBIs, and more social deficit, communication deficit, and behavioral and emotional problems were observed for ASD with RRBI compared to ASD without RRBI. Using PAF, two distinct factors were identified. 'Resistance to trivial changes in environment', 'Difficulty with minor changes in personal routine & environment', and 'Compulsion/ritual' were included as one factor. Conclusion : Analysis of the data suggests that the presence of RRBI in high functioning ASD is associated with a more severe presentation of autistic disorder. In addition, there appears to be heterogeneity within RRBI in autism except insistence on sameness.

• MALSORI
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• no.65
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• pp.51-65
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• 2008

The aim of this study is to compare ASD (Autism Spectrum Disorder) children with normal children in terms of the prosodic features. Materials are collected by the reading of Korean read sentences. They are composed of 10 declarative sentences, each of which was consisted of 5-6 words. Subjects are consisted of 10 ASD and 10 normal male children with a receptive vocabulary age of 5;0-6;5 years. We found out that both groups showed the differences not only in the tonal patterns at the end of the prosodic phrases, but also in both the degree of rising and falling slope related to pitch contour. While HL% and HLH% were highly emerged in sentence final position in normal group, HL% and HLH% were prominent in ASD group in the same position. LH% and LHL% IP types were observed only in ASD group in sentence medial position. The slope showing the variation in the fundamental frequency at the end of the prosodic phrase was twice as steep in the group of ASD children as in the group of normal children.