Child psychiatric disorders are common and treatable, but often go undetected and therefore remain untreated.To assess the Strengths and Difficulties Questionnaire (SDQ) as a potential means for improving the detection of child psychiatric disorders in the community.SDQ predictions and independent psychiatric diagnoses were compared in a community sample of 1959 11- to 17-year-olds from the 2013 Mongolian National Center for Mental HealthMulti-informant (parents, teachers, older children) SDQs identified individuals with a psychiatric diagnosis with a specificity of 66.8% (95% Cl 61.4-73.0%) and a sensitivity of 64.4% (59.9-71.3%). The questionnaires identified over 65% of individuals with conduct, hyperactivity, depressive and some anxiety disorders. Sensitivity was substantially poorer with single-informant rather than multi-informant SDQs.Community screening programmers based on multi-informant SDQs could potentially increase the detection of child psychiatric disorders, thereby improving access to effective treatments

BackgroundIn accordance with WHO investigation, most of the mental disorders onset in childhood and 20 percentof children (1 of fi ve) with mental and behavioral disorder currently. In 2005, by assessment of mentalhealth system in Mongolia (WHO-AIMS) it was concluded that special attention needs to be given todevelop professional competence and services in the area of child and adolescents mental health so itis a reason of the this study.AimTo early identify common emotional and behavioral problems among children and identify risk factorsfor itMethodsThe study was randomly selected 3500 child aged between from 4 to 17 years in 5 districts of Ulaanbaatarcity and 46 soums of 11 aimags of Mongolia.A main tool is Strengths and Diffi culties Questionnaire (SDQ) and included the 25-item child andparent versions were used to record each informant’s perception of four problem domains/subscales.SDQ was differently used child ages such as child aged 6-10 years used by parent version child agedbetween11-17 years used by both child and parent versions.ResultsOf 2920 child who participated in the study, 382 (13%) studied in kindergarten, 2423 (82.9%) school. Anaverage age of participants was 10.9±4.ConclusionThe abnormal emotional reaction was dominantly occurred in urban girls aged between from 6 to 10years and the abnormal behavioral reaction was dominantly occurred in urban boys aged between from6 to 15 years. The family relationship was a risk factor for developing emotional and behavioral problemsin child.

Introduction: In a report from the WHO 2013 it states that, 23% of children between the ages of 13 and 17 had suicidal ideation and 9.3% attempted suicide in the last 12 months. According to the research of Bayarmaa V et al, the prevalence of behavioral and emotional disorder among adolescents is between 8.7% & 9.4%. As a result of these researches, it can be concluded that evaluating the mental health of adolescents and learning the risk factors that can affect it has become an urgent matter in Mongolia. Goal: To establish the prevalence, the factors that influence it and the type of signs and symptoms common to this behavioral and emotional disorder in adolescents of the Gobi-Altai province. Material and Method: No ethical errors were reported during the implementation of this study. We used various versions of the Strengths and Difficulties Questionnaire (SDQ) applicable for children, adolescents, parents and teachers and determined exhibition of emotional and behavioral problems by cross-sectional analysis. 2192 adolescents between the ages of 11-18 years old, 1808 parents and caregivers and 102 teachers from the secondary school in Gobi-Altai province were screened from March to December of 2018. Results: In our study, 50.5% (n=1107) of participants were boys, 49.5% (n=1085) were girls and totally 2192 participants were involved. Regarding the survey results, 58.6% of adolescents in Gobi-Altai province were healthy, 36.1% of them had emotional and behavioral problems and 5.2% of them had emotional and behavioral disorders. For the mental health of adolescent, peer bullying (child 1.4 times higher, parents 6.4 times higher), moving house (child 2 times higher), domestic disputes between parents (child 1.6 times higher), loneliness (child 1.4 times high), hormonal change (teacher 7.7 times high, parents 2 times high), obtaining a qualification for a better life (teacher 6.4 times high) are the factors affecting their mental health negativ ely and creating a mental health problem. Conclusion 58.6% of adolescents in Gobi-Altai province were healthy, 36.1% of them had emotional and behavioral problems and 5.2% of them were with emotional and behavioral disorders. Peer bullying, moving house, domestic disputes between parents, loneliness, hormonal change are the factors affecting the mental health of adolescents negatively.

Introduction. Stigma and discrimination against patients with mental illness is very common amongst the society. Therefore, this study aims to study the knowledge and understanding of mental illness and attitudes to patient with mental illness, among the general population.Goal. To assess the knowledge and understanding of mental illness and attitude to patient with mental illness among population of Ulaanbaatar city and compare its results with a similar research in carried out in 2002.Methods. The study was conducted in Ulaanbaatar city from February to April, 2008 and included 991 people aged over 18 years. The sample was selected from 30 micro districts of Ulaanbaatar city, The method of sampling was using primary dot in first step, sampling households in mid step and selecting people by using method of Sweden key from household in final step. The study used 30 item standardized questionnaires. Also there were 2 extra cards to read for respondents.Result. Among the respondents, 45% were males and 55 % females. Average age was 37 years. In view of identifying negative attitude of patient with schizophrenia, majority of respondents answered as “loony person” (n=136) and “mad person” (n=83). Conclusion. Although there was stigma amongst the study population, 66% of subjects who were involved in study could give right diagnosis in non professional level and were able to identify symptoms of mental illness suggesting that more than half of the sample studied had some knowledge of mental illness.

Background: Globally, an estimated 13% of adolescents aged 10–19 are affected by mental disorders. As of 2020, the number of children under the age of 19 in Mongolia was reported to be 1,289,587, reflecting a 0.9% increase compared to 2015. A 2013 study on adolescents found that 60.5% were categorized as mentally healthy, 30.5% exhibited emotional and behavioral difficulties, and 9% were diagnosed with a mental disorder. A study conducted in Govi-Altai Province between 2018 and 2019 reported that 58.6% of adolescents were classified as healthy, 36.1% experienced psychological difficulties, and 5.2% were diagnosed with a mental disorder. Internationally, adolescent mental health has been widely assessed using the Strengths and Difficulties Questionnaire (SDQ), with an increasing number of studies employing artificial intelligence-based predictive models. However, in Mongolia, research utilizing artificial intelligence and machine learning for analyzing large-scale mental health data remains limited. This gap underscores the need for the present study. Aim: Machine learning models were compared to determine adolescent emotional and behavioral problems using the SDQ. Materials and Methods: Data was collected from teenagers, teachers, and parents in Govi-Altai Province, and the databases were created for each group. The teenager database was divided into 10 folds by cross-validation, and the models were developed using machine learning methods and evaluated using their performance measures. The results were mainly analyzed using the Bayes model. Results: The teenagers have emotional and behavioral problems due to emotional and peer interactions, but they are at risk of developing disorders due to hyperactivity and behavioral changes. Conclusion Comparing the model performance results with previous studies, Bayesian model accuracy decreased by 0.03, sensitivity decreased by 0.08, and specificity increased by 0.01. Also, the difference between the performance evaluation metrics of the C50 and Bayesian models is very small, between 0.01 and 0.02. This shows that the performance of the Bayesian method is good when the number of attributes in the database increases. Compared to the results of the knowledge generated by the research, the participants are more likely to develop emotional and behavioral disorders due to their peer relationship indicators, such as other children generally not liking them, getting on better with adults, and due to emotional symptoms such as being unhappy and depressed.