درخت حوزه‌های تخصصی

Objective: Psychological factors play a decisive role in the occurrence and experience of pain disorders. This study aimed to compare the effectiveness of emotion-focused therapy and cognitive behavioral therapy on alexithymia and difficulty in emotion regulation in patients with pain disorder. Method : The method of the present study was quasi-experimental with a pretest-posttest design and control group and a two-month follow-up. The statistical population of the study included all women who were referred to Manoushan and Behsa counseling centers in Tehran with psychosomatic problems and pain. Sixty people from this population were selected and randomly divided into three groups (20 people in each group). Research instruments included the Toronto Emotional Dysfunction Scale (Bugby et al., 1994) and the Difficulty in Emotion Regulation Scale (DERS) (Gertz & Roemer, 2004). One group received 12 one-hour sessions of emotion-focused therapy, and another group received 10 one-hour sessions of cognitive behavioral therapy. However, the control group did not receive any intervention during the study. In addition to descriptive statistics, mixed variance analysis and Ben Foroni post hoc test were used to analyze the research data.   Results : The results for alexithymia showed that the emotionally focused therapy group had a significantly lower mean than the cognitive behavioral group (P= 0.02) and the control group (P 0.001), and the cognitive-behavioral group had a significantly higher mean compared to the control group (P = 0.001). Also, the results for the difficulty in emotion regulation showed that the emotionally focused group and the cognitive-behavioral group have significantly lower means compared to the control group (P = 0.001). Conclusions : The results of the present study, in addition to confirming the effectiveness of cognitive-behavioral therapy, indicated that emotion-focused therapy is a more effective treatment for alexithymia. As a result, emotion-focused therapy can be considered an effective treatment that can be used by health professionals to treat pain disorders.

The purpose of this research is to investigate the prediction of corporate social responsibility reporting using financial ratios. To answer the research question, four prediction models of linear regression, K Nearest Neighbor, decision tree, and deep learning were investigated. Also, 61 financial ratios were used according to previous research using data related to listed and non-listed companies of Iran from the years 2012 to 2018. According to the re-sults obtained from the estimation of each of the proposed prediction mod-els, it can be stated that the k-nearest neighbor model has the lowest RMSE value, and in fact, this model predicts the amount of social responsibility with less error than other models. The linear regression model with the high-est RMSE value has a weaker performance than other models. LSTM model and decision tree respectively had the lowest RMSE value after the k-nearest neighbor model. As a result, since the LSTM model requires a large number of test sam-ples for deeper learning, it could not achieve high performance in the evaluated data set. Based on the investigations, it can be stated that the current research does not have a similar example inside or outside of Iran.