Prevalence of attention deficit hyperactivity disorder in elementary school students in Hamadan

ABSTRACT Background and aims: Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent disorder in children. Due to the importance of the disorder in children and its complications, this study aimed to assess the relation of the disorder with demographic factors in students of schools located in the Hamadan city, west of Iran. Methods: In this study, 1000 students were selected through randomized cluster sampling from Hamadan elementary schools in 2014. Data were gathered using Conners questionnaire. Conners questionnaire completed by teachers and parents. Results were analyzed using SPSS statistical software through Chi-square, Pierson correlation coefficient, and T-test. Results: The overall ADHD prevalence rate in this sample was determined to be 11.3. For boys, this prevalence rate of ADHD was 19.4 and had significant difference with girls (P<0.01). The prevalence of ADHD in families with 1-3 children was 8.7 while it was 15.8 in families with 4 children and more. The difference was statistically significant (P=0.003). There was also higher prevalence among children of parents with lower level of education. Conclusion: ADHD is prevalent in community of Iran. Results indicated that diagnosis must be based on exact and persistent psychological symptoms. It is necessary that schools authorities in region 1 and 2 of Hamadan city take steps to find the cases and manage them

Detecting congestion in DEA by solving one model

The presence of input congestion is one of the key issues that result in lower efficiency and performance in decision-making units (DMUs). So, determination of congestion is of prime importance, and removing it improves the performance of DMUs. One of the most appropriate methods for detecting congestion is Data Envelopment Analysis (DEA). Since the output of inefficient units can be increased by keeping the input constant through projecting on the weak efficiency frontier, it is unnecessary to determine the congested inefficient DMUs. Therefore, in this case, we solely determine congested vertex units. Towards this aim, only one LP model in DEA is proposed and the status of congestion (strong congestion and weak congestion) obtained. In our method, a vertex unit under evaluation is eliminated from the production technology, and then, if there exists an activity that belongs to the production technology with lower inputs and higher outputs compared with the omitted unit, we say vertex unit evidences congestion. One of the features of our model is that by solving only one LP model and with easier and fewer calculations compared to other methods, congested units can be identified. Data set obtained from Japanese chain stores for a period of 27 years is used to demonstrate the applicability of the proposed model and the results are compared with some previous methods