Objective: The present study aimed to compare the effect of ABM (attention bias modification) with and without tDCS (transcranial direct current stimulation) on attention bias, pain intensity, and disability due to pain and pain-related psychological consequences, such as depression, anxiety, and stress. Method: Using convenience sampling, 60 individuals who met the criteria for chronic low back pain (LBP) were selected and randomly assigned in to 2 experimental groups and 2 control and sham-tDCS groups. The experimental ABM group received 5 sessions of the dot-probe task, while the second experimental group received 5 sessions of dot-probe task combined with tDCS. Results: The findings indicated that ABM and ABM+tDCS could reduce attention bias and pain-related psychological consequences significantly, compared to the control and sham groups. Also, attention bias and pain outcomes (depression, anxiety, disability due to pain and pain intensity) remained in ABM+tDCS group than in ABM group in a 1-month follow-up. Conclusion: It was found that tDCS + ABM had no additional effects at the end of intervention, but led to more long-lasting effects in 1-month follow-up. Randomized clinical trial registry number: IRCT20171107037306N1.
Objective: Road traffic injuries are leading cause of death and economic losses, particularly in developing countries such as Iran. Thus, increased understanding of the causes of traffic accidents can help solve this problem. The primary goal of this study was to examine attentional bias, decision-making styles, and impulsiveness in drivers with safe or risky driving behaviors. The secondary purpose was to determine the variance of each variable among 2 groups of drivers. Method: This was a cross sectional design study, in which 120 male drivers aged 20-30 years (60 males with risky driving behaviors and 60 with safe driving behaviors) were recruited from Tehran using sampling technique. Barratt Impulsiveness Scale (BIS), Decision-Making Style Scale (DMSQ), Manchester Driver Behavior Questionnaire (MDBQ), Self-Assessment Manikin Scale (SAM), and Dot Probe Task were used. The analyses were performed using IBM SPSS version 22. Results: The mean age of participants was 26 years. Significant differences were found between impulsiveness (attentional, motor, and non planning impulsiveness) and decision-making styles (spontaneous and avoidant) between the 2 groups. Also, based on the results of discriminant function analysis (DFS), the subscales of impulsiveness and 2 decision-making styles explained 25% of the variance in the 2 groups of risky and safe drivers. Conclusion: Findings of this study indicated that impulsiveness and 2 decision-making styles were predominant factors. Therefore, not only is there a need for research to reduce traffic accidents, but studies can also be helpful in issuing driving licenses to individuals.
Background: Emotion regulation is an important meta-diagnosis construct and one of the common core and underlying dimensions of emotional disorders. Emotion regulation models are divided into two general categories of interpersonal and interpersonal models. Purpose: This study aimed to compare interpersonal and intrapersonal models of emotion regulation in predicting depression and anxiety syndromes in Tehran universities students. Method and material: The method of this study was cross-sectional. The statistical population of this study was all students of public universities in Tehran. Sampling was done using multi-stage cluster and the subjects were evaluated using Emotion Regulation Strategies Questionnaire, Interpersonal Emotion Regulation Questionnaire, Short Difficulty in Emotion Regulation Questionnaire and SCL-25 Questionnaire. Results: Findings showed that intrapersonal and interpersonal emotion regulation strategies have a significant role in explaining depression and anxiety syndrome. Between the two interpersonal and interpersonal emotion regulation models, the interpersonal emotion regulation model had a stronger and more significant effect on prediction of depression and anxiety syndrome (P <0.01). Conclusion: Both intrapersonal and interpersonal emotion regulation models have role in explanation of depression and anxiety syndromes and can be effective in predicting and treating emotional disorders.
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