• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.28 no.4
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• pp.228-234
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• 2017

Objectives: The aim of this study was to investigate the clinical characteristics of aggressive behavior problems in children and adolescents with autism spectrum disorder (ASD). Methods: Children and adolescents with ASD, aged 6-18 years, were included in this study. We divided them into two groups according to the presence or absence of aggressive behavior. They were assessed using three scales, the Korean-Child Behavior Checklist (K-CBCL), Behavior Problem Inventory, and Social Communication Questionnaire, which were completed by their parents, who conducted a continuous performance test to evaluate their attention function. The statistical analysis was done using the Mann-Whitney U-test between the two groups at a p-value of 0.05. Results: A total of 17 children participated in this study. Ten children (7 boys, $12.4{\pm}4.27years$) were included in the group with aggressive behavior problems and 7 children (6 boys, $13.8{\pm}3.53years$) in the group without aggressive behavior problems. There were no significant differences in the age, gender or intelligence quotient of the two groups. The children with aggressive behavior problems showed a trend of higher T-scores in the attention problems and anxiety/depressed subscale of the CBLC (p<0.1). Conclusion: The results suggest that aggressive behavior problems in children with ASD may be related to their attention problems, anxiety and depression.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.721-739
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• 2023

Rating prediction is an important issue in recommender systems, and its accuracy affects the experience of the user and the revenue of the company. Traditional recommender systems use Factorization Machinesfor rating predictions and each feature is selected with the same weight. Thus, there are problems with inaccurate ratings and limited data representation. This study proposes a deep recommendation model based on self-attention Factorization (SAFMR) to solve these problems. This model uses Convolutional Neural Networks to extract features from user and item reviews. The obtained features are fed into self-attention mechanism Factorization Machines, where the self-attention network automatically learns the dependencies of the features and distinguishes the weights of the different features, thereby reducing the prediction error. The model was experimentally evaluated using six classes of dataset. We compared MSE, NDCG and time for several real datasets. The experiment demonstrated that the SAFMR model achieved excellent rating prediction results and recommendation correlations, thereby verifying the effectiveness of the model.

• Human Ecology Research
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• v.51 no.4
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• pp.371-382
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• 2013

The purpose of this study is to investigate children's emotional problems (attention problem, aggression, somatic symptom, social withdrawal, depression) and to examine the relationship between children's emotional problems with family characteristics (parent education, parent job, family income), life-styles (gaming times, TV times, sleep time). The sample was 2,140 collections of second grade children and their parents who participated in Korea Youth Panel Survey on 2011. We analyzed the data which were collected by means of questionnaires and the data were analyzed with t -test, ANOVA, Pearson correlation analysis, and regression analysis with SPSS ver. 19.0. The results were summarized as follows. The level of children's emotional problem was relatively low on average. There is a significant difference in the children's emotional problems according to family characteristics and life-styles. There was a relationship between children's emotional problems (attention problem, aggression, somatic symptom, social withdrawal, depression) and life-styles (gaming times, TV times). The significant factors influencing the children's emotional problems are connected with father's education, mother's job, family income, family characteristics, gaming time and TV time of life style. It is noted that parent education level was an important factor for children's attention problem and aggression. Amongst children's life-styles, gaming time and TV time are negative factors for social withdrawal and depression.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.28 no.2
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• pp.115-122
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• 2017

Objectives: Executive dysfunctions including working memory deficit have been suggested to be one of the major neuropsychological etiologies of attention-deficit hyperactivity disorder (ADHD). The purpose of this study was to investigate the augmentative effects of working memory training on the behavioral problems, quality of life, and parental stress of medicated children with ADHD. Methods: Twenty-five children with ADHD, aged 9 to 19 years, who were being treated with ADHD medication, were included. The participants were trained with a commercially available and computerized working memory program ($Cogmed^{(R)}$) for 5 weeks without any alteration of their medication. The Child Behavior Checklist (CBCL), KIDSCREEN-52 quality of life measure, and Parenting Stress Index-Short Form (PSI-SF) were administered before training, and 4 weeks and 7 months after training, respectively. Results: After completing the training, the anxiety/depression, social problems, thought problems, attention problems, aggressive behavior, and externalizing problems scores in the CBCL were significantly reduced. The score on the Parent-child dysfunctional interaction in the PSI-SF was also decreased. However, the scores related to the quality of life were not changed. These changes were still observed 7 months after the training. Conclusion: Cogmed working memory training can be a promising training option for the additional improvement of behavioral problems and parental stress in medicated children with ADHD.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.30 no.1
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• pp.9-16
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• 2019

Objectives: The purpose of this study was to analyze the discriminant validity and the clinical cut off scores of the Child Behavior Checklist 1.5-5 (CBCL 1.5-5) in the diagnosis of autism spectrum disorder (ASD) and non-ASD. Methods: In total, 104 ASD and 441 non-ASD infants were included in the study. T-test, discriminant analysis, receiver operating characteristic (ROC) curve analysis, and odds ratio analysis were performed on the data. Results: The discriminant validity was confirmed by mean differences and discriminant analysis on the subscales of Emotionally reactive, Somatic complaints, Withdrawn, Sleep problems, Attention problems, Aggressive behavior, Internalizing problems, Externalizing problems, and Total problems, along with the Diagnostic and Statistical Manual of Mental Disorders (DSM)-oriented scales between the two groups. ROC analysis showed that the following subscales significantly separated ASD from normal infants: Emotionally reactive, Somatic complaints, Withdrawn, Sleep problems, Attention problems, Aggressive behavior, Internalizing problems, Externalizing problems, Total problems, and DSM pervasive developmental problems. Moreover, the clinical cut off score criteria adopted in the Korean-CBCL 1.5-5 were shown to be valid for the subscales Withdrawn, Internalizing problems, Externalizing problems, Total problems, and DSM pervasive developmental problems. Conclusion: The subscales of Withdrawn, Internalizing problems, Externalizing problems, Total problems, and DSM pervasive developmental problems significantly discriminated infants with ASD.

• Sleep Medicine and Psychophysiology
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• v.18 no.1
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• pp.10-16
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• 2011

There has been a growing interest in sleep problems associated with attention deficit hyperactivity disorder (ADHD). In this paper, we reviewed the current literature on the underlying sleep problems associated with ADHD. Sleep problems are very common in children with ADHD. Patients with ADHD may have sleep difficulties including difficulty falling asleep, frequent night awakening, increased tiredness upon waking. Children with ADHD are associated to restless legs syndrome, periodic limb movement and sleep-disordered breathing. Screening for other psychiatric comorbidities and the side effects of medications, such as psychostimulants, is also necessary when considering sleep problems in ADHD. Sleep problems can cause a negative impact on the quality of life and emotional well-being both of children with ADHD and their parents. Many evidences suggest that assessment of sleep difficulties should be included in evaluating the patient of ADHD.

• Journal of Korean Academy of Nursing
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• v.40 no.3
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• pp.453-461
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• 2010

Purpose: In this study differences in behavioral problems between children at risk for Attention Deficit Hyperactive Disorder (ADHD) and normally developing children were identified. Further, relationships between parental stress, depression, and child behavioral problems according to ADHD symptoms were explored. Methods: Participants were 222 elementary school children and their parents. The ADHD risk group was determined by the Korean-ADHD Rating Scale. Data were collected using the Korean-ADHD Rating Scale, Korean version of Child Behavior CheckList (K-CBCL), Parenting Stress Index, and Beck Depression Inventory. Data were analyzed using t-test, Pearson correlation coefficients, and regression analysis. Results: 1) The ADHD risk group showed higher levels of behavioral problems, parenting stress, and maternal depression than the normal group. 2) There were significant relationships between ADHD scores and parenting stress (r=.66), maternal depression (r=.35), internal behavioral problems (r=.47), and external problems (r=.55), but, ADHD risk scores were negatively correlated with social competence (r=-.40). 3) The regression analysis revealed that ADHD levels affected the child's internal behavioral problems, mediated by maternal depression ($\beta$=.29, p<.001). Conclusion: The study results show that higher risk scores for ADHD indicate a significant effect for behavioral problems. Also, parenting stress and depression influence child's behavioral problems. These results suggest that identification of children at risk for ADHD and development of parental education programs would contribute to the prevention of behavioral problems and aggravation of the ADHD symptoms.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.20 no.1
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• pp.10-16
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• 2009

Objectives : The purpose of this study was to investigate the characteristics of attention, intellectual functioning and adaptation of girls with attention-deficit hyperactivity disorder (ADHD). Methods : The scores of the ADHD Diagnostic System (ADS), the Korean Wechsler Intelligence Scale for Children-III (K-WISC-III) and the Korean Personality Inventory for Children (KPI-C) were compared between 26 girls with ADHD and 26 boys with ADHD. Results : 1) There was no significant gender difference in the intellectual functioning, except for the picture completion subscale. 2) Compared to the boys, the girls responded more slowly on the ADS visual task. 3) The girls were rated higher by their parents for the depression and social relationship problems of the KPI-C. Conclusion : The results suggest that there are noticeable gender differences for the attention problems and social functioning of children with ADHD.

• Korean Journal of Biological Psychiatry
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• v.26 no.2
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• pp.79-87
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• 2019

Objectives The aim of this study was to investigate the impact of clinical and psychological factors on the quality of life of children and adolescents with epilepsy and their families. Methods Children and adolescents with epilepsy and their families (n = 63, age range = 6-17 years) completed questionnaires on epilepsy-related variables, quality of life, children's depressive symptoms, children's anxiety, children's behavioral problems, children's attention problems, parental stress, and parental anxiety. Stepwise regression analysis was performed to determine the significant predictive variables that affect quality of life. Results In the correlational analysis, children's attention problems (r = 0.363, p = 0.004), parental anxiety (r = 0.377, p = 0.003), parental stress (r = 0.564, p < 0.001), and children's behavioral problems (r = 0.503, p < 0.001) showed a significant correlation with quality of life. Parental stress (β = 0.415, p = 0.001, adjusted R² = 0.345) and children's behavioral problems (β = 0.285, p = 0.02, adjusted R² = 0.345) were significantly related to the quality of life. Conclusions Clinicians should pay attention to parental stress and children's behavioral problems, which affect quality of life in families with pediatric epilepsy.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1231-1242
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• 2019

This paper presents a two-dimensional attention-based long short-memory (2D-ALSTM) model for stock index prediction, incorporating input attention and temporal attention mechanisms for weighting of important stocks and important time steps, respectively. The proposed model is designed to overcome the long-term dependency, stock selection, and stock volatility delay problems that negatively affect existing models. The 2D-ALSTM model is validated in a comparative experiment involving the two attention-based models multi-input LSTM (MI-LSTM) and dual-stage attention-based recurrent neural network (DARNN), with real stock data being used for training and evaluation. The model achieves superior performance compared to MI-LSTM and DARNN for stock index prediction on a KOSPI100 dataset.