Purpose The purpose of this paper is to present a model for measuring relational capital in banks by using measurement indicators defined in previous studies and according to the conditions of the banking industry and in particular the Ansar bank in Iran. Design/methodology/approach The study identifies measurement indicators of relational capital from the related resources and articles and uses content analysis and factor analysis methods. It also measures the selected indicators through a questionnaire analyzing them using the SPSS software to create a model to measure relational capital in the bank. Findings By using the measurement model created in this research, relational capital in Ansar bank is determined to be comprised of eight principal components. The total score of these components is the starting point of promoting the relational capital in the banking industry. Research limitations/implications This study may not have thoroughly covered the peer- reviewed articles on intellectual capital, but it can be assumed with high confidence that it has made a serious attempt at studying the most important papers on the subject as of date. Moreover, the model presented in this study is valid only when applied in comparing banks. It should further be noted that time limitation, non-availability of relevant experts as well as the required data may have affected the accuracy and reliability of the results. However, the final model has been utilized to try to optimally minimize each limitation according to the existing resources, and through their proper management. Practical implications This study provides a new approach that can significantly help bank managers in comparing their banks in the field of relational capital and reacting to their weaknesses and performance advantages of relational capital over its rivals. Originality/value In addition to creating a new framework for relational capital indicators, this study offers a model for measuring relational capital in the banks.

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A novel coronavirus was first reported in Wuhan, China in December 2109 and was declared a global pandemic by the World Health Organization on 11 March 2020. Identification of the critical factors that predict reduced mobility and human interaction is critical to developing successful transmission mitigation efforts globally. Governments and localities around the world have responded with wide-ranging policies related to containment and closure such as travel restrictions and stay-at-home-orders, as well as economic benefits, expanded testing, and public health education, among others. Anonymized GPSenabled smartphone data is a novel tool to track human mobility and is becoming widely available. This study explores the relationships between containment and closure policies, disease trends, and human mobility patterns in 40 countries in Western, Eastern, Northern, and Southern Europe and North America. The principal component analysis was applied to reduce variable dimensions, followed by multivariate multiple regression. The model parameter estimations indicate that total cases, canceling activities (school, work, events), mask policies and the pandemic declaration all were significant predictors (p<.001) of change in workplace mobility from baseline.

This research aimed to determine the effectiveness of cognitive group therapy on self-efficacy and depression among divorced women. Methods: This was a quasi-experimental study with pretest-posttest design with control group. In this study, all divorced women referring to Hazrate Zeinab Charity Institution in Varamin City, Iran were considered as the statistical population with a sample size of 30 subjects who were selected via purposive sampling and randomly assigned to the experimental (n=15) and control groups (n=15). A weekly cognitive group therapy was applied to the experimental group for 12 sessions, but the control group was placed on the waiting list. Assessment instruments consisted of general self-efficacy scale and Beck depression questionnaire. The obtained data were analyzed using multivariable analysis of covariance. Results: Cognitive group therapy led to significant increase in self-efficacy (df=1, P<0.05, F=66.05) and significant decrease in depression (df=1, P<0.05, F=108.65) among divorced women. Conclusion: According to the results, cognitive group therapy is an effective way of decreasing depression and increasing self-efficiency in divorced women.

Effectiveness of acceptance and commitment therapy on cognitive emotion regulation in men treated with Aims Considering the importance of mental health in veterans' lives, a treatment-based veterans. Therefore, the purpose of this study was to investigate the effectiveness of Acceptance and Commitment Therapy (ACT) training on emotional control of chemical veterans. Materials & Methods This quasi-experimental study with pretest-posttest design with control group was performed among 50 chemical veterans in Arak city in 2017. They were selected by convenient sampling and then randomly assigned into two groups: experimental group (25 people) and control group (25 people). Emotional Control Questionnaire (ECQ) was used to collect data. Acceptance and Commitment Therapy (ACT) training was performed in 10 sessions for the experimental group. Data were analyzed by SPSS 23 software using multivariate analysis of covariance (MANCOVA). Findings the experimental and control groups in the post-test. By controlling the effects of pre-test, ACT Conclusion ACT training is effective on improving emotional control in chemical veterans; in this way that improves emotional inhibition, control of aggression and rumination, but does not affect the benign control.