درخت حوزه‌های تخصصی

Objective: Marital conflict is one of the serious problems in couples' interactions, which is considered as the cause of marital infidelity or divorce in many cases. This research was conducted with the aim of comparing the effectiveness of schema therapy and emotion focused therapy on the attitude towards marital infidelity of people with marital conflict. Methods: The research method was quasi-experimental with a pre-test-post-test design with two experimental groups and a control group along with a follow-up test period. From the statistical population of women referring to the clinics of the 1st district of Tehran, 45 people were selected using the available method and replaced in three groups using a random method. Whatley's marital infidelity questionnaire (2006) was used. First, the pre-test of the attitude towards extrapolation was implemented for all three groups, then schema therapy (Yang, 2003) and emotion focused therapy (Greenberg, 2004) were implemented for the experimental groups, but no intervention was applied for the control group; Finally, the post-test and the follow-up test were performed for all three groups. Findings: The results of the repeated measurement test showed that both schema therapy and emotion focused groups are effective in reducing attitudes towards marital infidelity (f=8.447 and p=0.001). Bonferroni's post hoc test showed that there is no significant difference in the effectiveness of the two schema therapy and emotion focused approaches. Conclusion: To improve the attitude towards marital infidelity of people with marital conflict, it is suggested to use both schema therapy and emotion focused interventions.

Objective: The purpose of the present study is to analyze the challenges faced by the families of veterans suffering from post-traumatic stress disorder (PTSD). Methods: This research was conducted using a qualitative approach and grounded theory methodology. The statistical population consisted of 1,500 individuals, and participants were selected through purposive sampling based on the inclusion criteria. Data collection continued until theoretical saturation was achieved, resulting in the study of 42 families, including spouses and children of veterans with PTSD in Kermanshah province. Additionally, a literature review and semi-structured interviews with 10 experts and social work professionals in the field of family studies were conducted over a 12-month period in 2022. Data were analyzed using Strauss and Corbin’s method. Findings: The results were obtained through three stages of open coding, axial coding, and selective coding. Data analysis yielded 138 subcategories, 15 main categories, and 1 core category. The 15 main categories included: "quality of life issues, financial problems, internal family environment challenges, family functioning issues, psychological problems, parent-child relationship problems, challenges from surrounding individuals and social support networks, marital relationship issues, coping strategy problems, personality trait issues, life cycle challenges, organizational and cultural action problems, family outcome challenges, social outcome challenges, and individual outcome challenges." These were presented as causal, intervening, contextual factors, strategies, and outcomes in the final model. Conclusion: This study, in connection with the research literature, provided a new understanding of the experiences of families of veterans with PTSD by describing their challenges. The findings revealed that these families face significant issues in various aspects of their lives, and reducing these challenges requires greater attention from responsible organizations and mental health centers.

Objective: The aim of this study was to investigate the relationship between rumination and coping strategies with marital self-disclosure. Method: This research is fundamental in terms of its objective and descriptive-correlational in terms of data collection. The statistical population of this study consisted of all married women at the Faculty of Psychology and Educational Sciences, Islamic Azad University, Central Tehran Branch, during the academic year 2022-2023. To this end, 385 women were selected using Cochran’s formula and convenience sampling method. Participants responded to the Marital Self-Disclosure Questionnaire by Waring et al. (1998), the Ruminative Response Scale by Nolen-Hoeksema et al. (1993), and the Brief COPE Inventory by Endler and Parker (2008). After collecting the questionnaires, the data were analyzed using Pearson’s correlation coefficient and simultaneous multiple regression analysis. Findings: The results indicated a significant negative correlation between rumination, avoidance-oriented coping strategies, and emotion-focused coping strategies with marital self-disclosure (p < .01). There was a significant positive correlation between problem-focused coping strategies and marital self-disclosure (p < .01). Conclusion: The results of the multiple regression analysis also revealed that 71.6% of the variance in marital self-disclosure is explained by rumination and coping strategies. Therefore, it can be concluded that rumination and coping strategies can predict marital self-disclosure among married women.

Objective: The present research aimed to examine the effectiveness of neurofeedback therapy on emotional processing, irrational beliefs, and aggression in patients with generalized anxiety disorder. Method: This study was a quasi-experimental pre-test, post-test, and follow-up design with a control group. The research population comprised all women with generalized anxiety disorder visiting psychiatric treatment centers in Golpayegan in the first half of 2019, from which 30 female patients were purposefully selected based on inclusion criteria and randomly assigned to either the experimental or control groups. The experimental group received eight 30-minute sessions of neurofeedback therapy. Meanwhile, the control group did not receive this intervention during the research process. The questionnaires used in this research included the Spitzer Generalized Anxiety Scale (2006), the Baker Emotional Processing Scale (2007), the Jones Irrational Beliefs Questionnaire (1968), and the Buss and Perry Aggression Questionnaire (1992). Data were analyzed using repeated measures analysis of variance with SPSS-24 software. Findings: The results of the data analysis indicated that neurofeedback therapy significantly affected emotional processing (F=10.89, P<0.001), irrational beliefs (F=10.83, P<0.001), and aggression (F=8.16, P<0.008). Conclusion: Given the confirmed effectiveness of neurofeedback therapy on emotional processing, irrational beliefs, and aggression in patients with generalized anxiety disorder, it is recommended that workshops be organized to familiarize counselors and therapists more thoroughly with the principles and techniques of this treatment in the field of this disorder.

The primary issue of this research was to investigate the relationship between artificial intelligence (AI) and user behavior patterns on social networks, the impact of AI on voting behavior, and the connection between the use of online data analysis and students' decision-making in presidential elections. This question arises while considering the influence of AI on user behavior patterns and decision-making in presidential elections. The objective of this study was to evaluate the impact of AI variables and online data on user behavior and decision-making in various contexts. This re-search examined the study hypothesis to better understand how behavior and decision-making are shaped in the digital age and the role of modern technologies in these processes. To conduct this research, a survey method and available library resources were utilized. The study used existing sources and collected necessary data from the target population, namely students at universities in Tehran, and employed descriptive and inferential statistics for data analysis. The findings of this research indicate that demographic variables and AI play a significant role in user behavior and de-cision-making, and the use of online data analysis can influence students' decision-making in presi-dential elections. Additionally, AI can be effective in detecting user behavior patterns on social networks and influencing voting behavior. These results can be useful for policymakers, election officials, and social activists in designing effective strategies to monitor user behavior and decision-making in the digital age, contributing to a better understanding of AI's role in shaping behavior and decision-making in society.