Mohammad Ali Mohammadyfar
Volume 3, Issue 11 , March 2018, , Pages 71-90
Abstract
Introduction: The aim of this study was to evaluate the effectiveness of neurofeedback education in improving the performance of attention and cognitive flexibility in athletic students. Method: To this end, 40 male students of physical education at Kharazmi University were randomly assigned to two groups ...
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Introduction: The aim of this study was to evaluate the effectiveness of neurofeedback education in improving the performance of attention and cognitive flexibility in athletic students. Method: To this end, 40 male students of physical education at Kharazmi University were randomly assigned to two groups of 20. The first group received 16 sessions of neurofeedback training (2 sessions per week) as the experimental group, and the second group (control) received no intervention. The research tools consisted of the Stroop Attention Computer Test and the Wisconsin Cognitive Flexibility Computer Test. The data were analyzed using one-variable and multivariate analysis of covariance and analyzed using SPSS19 software. Findings: The results showed that the experimental group had statistically superiority (p
Shahrokh Makvand hoseini; mahmmod najafi; Reza Khaleghi
Volume 3, Issue 10 , January 2018, , Pages 63-80
Abstract
Aim:The purpose of this study is to investigate the relationship between brain-behavioral systems activity mediated by positive and negative emotions on social anxiety of students. Method: This study is correlational and structural modeling. In this study 409 students (200 males, 194 females and 15 unknown), ...
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Aim:The purpose of this study is to investigate the relationship between brain-behavioral systems activity mediated by positive and negative emotions on social anxiety of students. Method: This study is correlational and structural modeling. In this study 409 students (200 males, 194 females and 15 unknown), from the University of Mashhad were selected by convenience sampling and three questionnaires: Social Anxiety Inventory (SPI) , Positive and Negative Affect Scale Panas (PANAS) and Brain-behavioral systems scale (BAS/BIS) in the form of self-report questionnaires. The raw data using structural modeling to estimate the maximum fit and were analyzed using LISREL software. Findings: The results indicate that the theoretical model is a good fit. Behavioral Inhibition System (BIS) directly associated with social anxiety as well as indirectly through negative emotions associated with social anxiety. As well as behavioral inhibition system associated with positive affect as significant negative relationship. Behavioral Aproach System (BAS) also indirectly through the positive affect, have an impact on social anxiety. The Fight/Flight/Freeze System (FFFS) through negative emotions associated with social anxiety. Positive Affect (PA) and Negative Affect (NA) both are significantly related with social anxiety.The impact of emotions (positive and negative affects) between path of brain-behavior systems and social anxiety, is important. Conclusion: High levels of negative affect in person, or low levels of positive affect, can be a sign to predict social anxiety.
