preparing pattern for anticipating emotional-behavioral patterns of children based on social skills and anxiety of mothers with self-concept mediation of children

Subject Areas : Tectonostratigraphy

salva shamseddini lory ¹ (conseling)
Farideh Dokanehi Fard ² (Department of Counseling, Faculty of Educational Sciences and Counseling, Islamic Azad University, Roudehen Branch, Tehran, Iran)
AbdolAllah Shafi Abadi ³ (Professor, Department of Counseling, Faculty of Psychology and Educational Sciences, Allameh Tabatabaei University, Tehran, Iran.)

Received: 2017-12-05 Accepted : 2018-11-19 Published : 2018-08-23

Keywords: self-concept, anxiety, Emotional and Behavioral Disorders, Social Disorders,

Abstract :

The purpose of this study was to develop a model for predicting children's emotional-behavioral disorders based on social skills and anxiety of their mothers through mediation of children's self-concept. The research was applied in terms of purpose and in terms of correlation, exploratory, and directed and multivariate type. The statistical population includes all 8-12 year old male students in 4 public schools in district 6 of Tehran along with their mothers. The number of students was requested according to the list of education in the region, of which 2345 were. Multi-stage sampling. The sample size was considered according to the type of research and to prevent the depression of 450 students. The research tool was social skills, behavioral disorders and self-concept. After completing the questionnaires, their mothers were asked to respond to their anxiety questionnaire. Then, the mothers who had high scores in anxiety questionnaire were analyzed by questionnaires for their child and low anxiety scores were excluded from the research process. Then these students were examined with Woodworth’s questionnaire of behavioral-emotional disorders, social skills of Gresham and Elliott, March multi-aspect anxiety questionnaire, self-concept questionnaire of Pierz and Harris and results showed that it was benefit from correlation coefficient, multi-variable regression and path analysis and in case of necessity, it is benefit from statistical methods for analyzing data including: Pearson correlation coefficient, SPSS software and method for analyzing structural equations and Amos software for examining research hypothesis. Results showed that the recommended model has suitable level of goodness of fit.

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