Behavioral Emotion Regulation and resilience in students: The mediating role of cognitive flexibility

Behavioral Emotion Regulation and resilience in students: The mediating role of cognitive flexibility | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Behavioral Emotion Regulation and resilience in students: The mediating role of cognitive flexibility Mehdi Arabzadeh, Arshia Ansari Esfahani, Soroush Asoodeh, Atiyeh Fouladvand, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8373134/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The aim of the present study was to investigate the mediating role of cognitive flexibility in the relationship between Behavioral Emotion Regulation and students' resilience. The research method was descriptive-correlational and structural equation modeling. The statistical population included all undergraduate students at Kharazmi University in the academic year 2022–2023, from which 301 people were selected as samples using multi-stage cluster sampling. In order to collect data, the Academic Resilience Questionnaire (Connor and Davidson, 2003), Cognitive Flexibility (CFI, Dennis and Vander Wal, 2010), and Behavioral Emotion Regulation Questionnaire (BERQ, Garnefski and Kraaij, 2019) were used. The results showed that the proposed model had a good fit. Also, the direct effect of behavioral emotion regulation on resilience and cognitive flexibility was significant (p < 0.01), and the direct effect of cognitive flexibility on resilience was also significant (p < 0.01). Other results also showed that cognitive flexibility had a mediating role between behavioral emotion regulation and resilience (p < 0.01). In summary, it can be concluded that behavioral emotion regulation directly and indirectly affects students' resilience through the mediating role of cognitive flexibility. Psychology Behavioral emotion regulation resilience cognitive flexibility students Figures Figure 1 Figure 2 Introduction Academic life is full of challenges, personal, social and educational issues, because the student must adapt to them not only to achieve academic success, but also to ensure a good state of physical and mental health throughout the academic period. Otherwise, adverse consequences will be likely Restrepo-Widney et al., 2025; Martin and Marsh, 2006). Studies show that the lack of skills and preparation necessary to deal with the stressors of the student period leads to burnout and frustration (Mc Allister and MC Kinnon, 2009). Therefore, effectively dealing with these stressors will play an effective role in improving the physical and mental health of students. One of the factors that plays a decisive role in critical academic situations for students is resilience (Martin & Marsh, 2006). Resilience is the ability to overcome difficult situations that occur in life, by recognizing them, accepting them, and emerging stronger than them (Rutter, 1999). Resilience is an individual's confidence in their abilities to overcome stress, having coping skills, self-respect, emotional stability, and personal characteristics that increase social support from others ((Solgi and Shafiei, 2022). This construct is one of the factors that prevents the occurrence of psychological problems among individuals and protects them from the psychological effects of problematic events Waugh et al. (2008)). In other words, resilience is positive adaptation in response to adverse circumstances (Masten et al., 2001). Of course, resilience is not just stability against harm or threatening conditions, nor is it a passive state in the face of dangerous conditions, but rather an active and constructive company in one's surrounding environment and the ability of an individual to establish a biological-psychological balance in dangerous conditions (Conz & Magnani, 2020). In fact, academic resilience is defined as a protective behavior that students use to effectively face problems and achieve appropriate academic results. This means that students who have reached a high threshold of resilience continue to achieve high success even when faced with fewer educational resources (Aydin and Micho, 2020). In educational settings, students who demonstrate resilience in their education and in the face of tasks of varying degrees of difficulty are also resilient to obstacles in everyday life. Resilience capacity is generalized to other aspects of individuals' lives, helping them overcome difficulties academically and personally (Reeve et al. (2020). Many factors appear to be associated with and influence resilience. One of the important and effective factors of resilience is emotional self-regulation (Malashahi and Azarian, 2023). Emotion regulation is the ability to employ adaptive psychosocial functions through the regulation of emotional responses, which is a dynamic developmental process that emerges during childhood and adulthood (Allen and Nelson, 2018). Emotion regulation has two cognitive and behavioral dimensions that indicate the way an individual copes with stressful events and should not be considered the same because thinking and action are separate processes (Garnefski et al., 2001). One of the most common types of emotion regulation that has received much credible research is cognitive emotion regulation. Garnefski et al. (2009) define cognitive emotion regulation as the conscious mental strategies that an individual uses to cope with and cope with the receipt of emotionally arousing information. In other words, cognitive emotion regulation means cognitively changing the information that arouses emotion (Ochner-Gross, 2005). Cognitive therapy based on emotion regulation is effective in reducing impulsivity and aggression in children with behavioral problems(Gholamzadeh Nikjoo et al. 2022). Cognitive emotion regulation includes the components of self-blame, blaming others, rumination, catastrophizing, perspective-expanding, positive refocusing, positive appraisal, acceptance of the situation, and planning, which focus on the mental and abstract dimension of the emotion regulation process (Garnefski and Kraaij, 2006; Schroevers et al., 2007). However, a newer type of emotion regulation that has received less research to date is behavioral emotion regulation. Behavioral emotion regulation is a set of behavioral strategies that individuals often use to adapt to and cope with stressful events, and focuses on the behavioral and objective dimensions of the emotion regulation process with the components of distraction seeking (distracting oneself from emotions by doing something else, with the aim of coping with the stressful event), withdrawal (withdrawing from situations and social interactions with the aim of coping with the stressful event), active coping (behaving actively in dealing with the stressful event), social support seeking (actively sharing emotions and asking for advice and support from others with the aim of coping with the stressful event), and denial (ignoring and behaving as if nothing had happened to cope with the stressful event) (Kraaij & Garnevsky, 2019). It seems that distraction-seeking, active coping, and seeking social support are considered positive and adaptive strategies, and withdrawal and ignoring are considered negative and maladaptive strategies, to manage stressful situations (Joorman & Stanton, 2016; Kraaij & Garnefski, 2019). Gross (1999) states that individuals use different emotion regulation strategies depending on their individual differences with others; For example, people who score high on the extraversion scale are more likely to be drawn to situations where there is social conflict. Thus, it is possible that some people, depending on their unique personality traits, prefer to use behavioral emotion regulation strategies over cognitive emotion regulation strategies, or vice versa. Therefore, given individual differences in the use of different emotion regulation strategies, more attention should be paid to the distinction between behavioral and cognitive types. According to a meta-analytic study by Aldao et al. (2010), using maladaptive behavioral emotion regulation strategies is more harmful than not using adaptive strategies. Also, using these maladaptive strategies leads to the individual avoiding effective confrontation with stressful situations and, as a result, reduces his/her resilience (Lovian et al., 2023). Recent findings indicate that emotional dysregulation causes various physical and psychological disorders and makes the individual more vulnerable to stressful events, therefore, researchers have paid special attention to this variable in recent years (Hassani et al., 2008; Garnefski and Kraaij, 2006). Among the psychological disorders that can be caused by disorders in behavioral emotion regulation is substance abuse (Basharpoor, Ahmadi, & Heidari, 2021). One of the academic disorders that can be affected by an individual's emotion regulation strategies is test anxiety (Rasam et al., 2021). Hassani, Sohrabi, & Mohammadkhani (2023) concluded that difficulty in emotion regulation plays a role in students' academic failure. Also, according to the research of Rafiee Rad, Basharpoor, Sadatrasol and Alizadehfard (2021)), behavioral regulation of emotion plays an effective role in increasing and improving the quality of life. A review of the research background shows that the behavioral dimension of emotion regulation has received less attention in previous studies. While it seems that behavioral regulation of emotion plays an important role in adopting adaptive strategies in stressful situations. A relatively large amount of research has been conducted on the relationship between emotion regulation and resilience. For example, Jalali et al. (2022) in their study on the effect of emotion regulation skills training on soldiers' resilience based on the self-efficacy model concluded that emotion regulation skills training using self-efficacy theory has a significant and meaningful effect on soldiers' resilience. Nironamnd, et al. (2019) also found that training in emotion regulation skills and techniques has a positive effect on individuals' resilience and increases it. However, a review of the research background shows that the relationship between the behavioral dimension of emotion regulation and resilience has not been given much attention and study. While it seems that measures aimed at behavioral emotion regulation, such as active coping, are related to individual resilience. On the other hand, the role of mediating factors in the relationship between emotion regulation and resilience has been largely ignored in previous studies. A review of the literature shows that one of the constructs that could possibly be decisive in the relationship between behavioral emotion regulation and resilience is cognitive flexibility. Cognitive flexibility is defined as an individual's readiness to selectively change among mental processes to produce appropriate behavioral responses to stressful situations and refers to the ability to change cognitive dispositions and effectively adapt to the ever-changing environment in which one lives (Dajani & Odin, 2015; Dickstein et al., 2007).According to Guilford (1967), cognitive flexibility is defined as the ability to break old cognitive patterns and thus overcome the stability of performance to create novel and creative connections between concepts. In fact, cognitive flexibility helps individuals to adapt to new and unpredictable events in the environment through learning processes based on previous experiences and processing new cognitive strategies (Canas et al., 2006). The results indicated that cooperative learning markedly improves students' social abilities. Furthermore, both emotional regulation (ER) and cognitive exibility (CF) were identi ed as mediators of this connection, with partial mediation evident in many pathways. Cooperative learning favorably impacted emotional sensitivity and ER, while also in uencing social sensitivity and expressiveness through CF( Ma, et al. 2025) Finally, with the help of cognitive flexibility, an individual can create desirable and adaptive changes in her/his environment and overcome new problems that arise around her/his by changing her/his previous cognitive patterns and employing new cognitive processes that can only be achieved by having flexibility in the thinking process (Canas et al., 2003) People who are flexible in their thinking and behavior seek alternative behaviors and thoughts when faced with problems so that they can flexibly adapt to the new situation by considering other options (Arici-Ozcan et al., 2019)..When faced with new issues, people with cognitive flexibility are ready at any moment to abandon the actions they took in the past when facing previous problems and turn to solutions that deal with the new problem effectively and adapt to the emerging situation and situation with the help of alternative methods (Kloo et al., 2008).These individuals have the ability to quickly reconstruct their cognition; hence, they adapt their responses to the constantly changing demands of their situation and effectively and efficiently deal with unpredictable events (Spiro and Jehng, 2012).Past studies suggest that people with impaired flexibility also have impaired learning and resilience in the face of psychological stress, which ultimately leads to lower creativity, performance, and quality of life (Dajani & Odin, 2015; Feng et al., 2020). Phillips (2011) also states that individuals' weakness in cognitive flexibility can lead to impaired resilience and ultimately cause them to perform poorly in the face of life's difficulties, because they are unable to carry out the cognitive restructuring process efficiently and adapt appropriately to the problem at hand by changing their cognitive strategies and choosing other options as an alternative. In contrast, people who are highly resilient and demonstrate good cognitive flexibility in various situations are able to reconsider their approach to a problem and are able to avoid perceiving that situation as stressful by employing several different behavioral and cognitive methods to solve a problem (Phillips, 2011; Southwick et al., 2005). Findings showed that cognitive-behavioral therapy affects self-control, difficulty in emotion regulation, resilience and psychological flexibility in clients with practical obsession( Ghafari Cherati et al. 2022). People who are able to think about problems flexibly, use alternative interpretations, reframe positively when necessary, and be receptive to challenging situations and upsetting events have greater psychological resilience than those who are not flexible in their thinking; instead of seeing problems as permanent and pervasive, they perceive them as temporary and limited, which is one of the characteristics of resilient people (Haglund et al., 2007).For this reason, people with cognitive flexibility cope more effectively with stressful environmental stimuli and adapt and adapt to their environment more patiently; as a result, they show greater resilience (Boon et al., 2012; Gan et al., 2006). Hajipour and Eynypour (2021) concluded that teaching resilience to individuals increases their level of flexibility due to the development of real experiences, empirical examination of thoughts, and modification of thoughts. Research also shows that there is a significant relationship between cognitive flexibility and emotion regulation. For example, Lee and Orsillo (2014) found that as cognitive flexibility increases, the regulation of negative emotions such as anxiety decreases. Ghosh and Halder (2020) also found a significant relationship between emotion regulation and cognitive flexibility in most adults; such that people with high cognitive flexibility regulated their emotions using cognitive reappraisal of emotion. Raeisi Sarteshneizy et al. (2020) also found that there is a significant relationship between self-efficacy in emotion regulation and cognitive flexibility, and stated that people with high flexibility are better able to cope with emotional turmoil. By reviewing the studies conducted in the field of coping strategies, it seems that paying attention to the three factors of behavioral emotion regulation, resilience, and cognitive flexibility is very important, especially in the academic context. University life is often accompanied by unforeseen events that highlight the need to be equipped with coping strategies and emotion regulation. Whether in situations that require communicating with professors and peers or when facing sometimes difficult and complex assignments, emotion regulation is one of the coping methods that helps relieve tension in stressful situations and can increase students' resilience in difficult and unforeseen situations. Although numerous studies indicate a relationship between emotion regulation and resilience, the behavioral dimension of emotion regulation and its relationship with resilience have not been addressed, and the nature of this relationship and the role of cognitive factors such as cognitive flexibility in the relationship between emotion regulation and resilience are not clear. It seems that people who use adaptive behavioral strategies to regulate their emotions change their perspective on the problem and face it with more flexibility, and therefore show greater resilience in facing problems. Therefore, the aim of the present study is to investigate the mediating role of cognitive flexibility in the relationship between behavioral emotion regulation and resilience. The conceptual model of the research is shown in Fig. 1 . In this study, we intend to test the hypothesis that behavioral emotion regulation through cognitive flexibility is a significant predictor of resilience in students. Method The present study is descriptive in terms of its fundamental purpose and the method of data collection, and is of the correlation type. The analysis method of this study is path analysis, which was used to examine the causal relationships of the research variables. The data were also analyzed with SPSS 25 and AMOS 24 software. The statistical population of the present study consisted of all undergraduate students of Kharazmi University in the academic year 2022–2023. The sample was collected using a multi-stage cluster method and in person (pencil-paper). Regarding the appropriate sample size for structural equation analysis, Kline (2005) suggested that a small sample of 100 numbers, a medium sample of 100 to 200 numbers, and a large sample of more than 200 numbers are considered. In this way, 301 students were selected as the sample. Informed consent to participate in the research and undergraduate students were considered as the entry criterion for the research; failure to respond to the questionnaire questions was considered as the exit criterion. Also, the principle of confidentiality and the principle of informed consent have been considered. Measurement tool: Resilience Questionnaire : This questionnaire was designed by Connor and Davidson in 2003. To create it, research sources on resilience obtained between 1979 and 1991 were reviewed and evaluated. The creators believe that this scale has a good ability to distinguish resilient from fragile individuals. This questionnaire has 25 questions and is a self-report tool. Its scoring is based on a Likert scale between 0 and 4 and the range of scores obtained is between 25 and 100. Mohammadi et al. (2006) adapted it for use in Iran. Besharat (2009) found its reliability based on Cronbach's alpha coefficient of 0.86, which is an acceptable score. To determine the validity of this scale, the correlation of each item with the total score of the category was first calculated and then factor analysis was used. Calculating the correlation of each score with the total score, except for item 3, showed coefficients between 0.41 and 0.64. Then, the scale items were factor analyzed using the principal components method. Before extracting factors based on the item correlation matrix, two KMO indices and Bartlett's sphericity test were calculated. The KMO value was 0.87 and the Bartlett chi-square value was 5556.28, both of which indicated the adequacy of evidence for factor analysis. In a study conducted among students by Samani, Jokar, and Sahragerd (2007), their reliability was reported to be 0.93, and the validity (using factor analysis and convergent and divergent validity) was verified by the test creators in different normal and at-risk groups (Samani et al., 2007). In the present study, the Cronbach's alpha of this questionnaire was 0.79. Cognitive Flexibility Inventory (CFI): This questionnaire was used by Dennis and Vander Wal (2010) to measure a type of cognitive flexibility that is necessary for an individual to successfully challenge and replace dysfunctional thoughts with more functional thoughts. This instrument is a valid two-factor construct; in other words, the final version of this scale consists of 20 questions, 13 questions for the alternatives subscale and 7 questions for the control subscale. In the Iranian version of this scale, developed by Shareh et al. (2014), three factors of control, alternatives, and substitutes for human behavior have been identified. The questions in this questionnaire are scored on a 7-point Likert scale from strongly disagree (1) to strongly agree (7). Questions 2, 4, 9, 7, 11, and 17 are reverse scored. The highest score a person can get is 140 and the lowest score is 20. A higher score indicates more cognitive flexibility and a lower score indicates less cognitive flexibility. Dennis and Vander Wal (2010) showed in a study that the present questionnaire has a good factor structure, convergent validity and concurrent validity. Its convergent validity with the Resilience Questionnaire was 0.67 and its concurrent validity with the Beck Questionnaire was − 0.50. These researchers obtained the reliability of the questionnaire using Cronbach's alpha for the entire questionnaire, control, and replacement as 0.81, 0.77, and 0.75, respectively. Reliability using the internal consistency method by calculating Cronbach's alpha coefficient in 227 students of Shiraz University and reliability using the test-retest method with an interval of 20 days in 35 students of Shiraz University were 0.90 and 0.71, respectively (Shareh et al., 2014). In the present study, Cronbach's alpha was 0.87. Behavioral Emotion Regulation Questionnaire (BERQ): The Behavioral Emotion Regulation Questionnaire (BERQ) was designed by Garnefski and Kraaij in 2019 and assesses how people respond and behave when faced with difficult and stressful life situations. It has 20 questions and 5 subscales, which are: distraction seeking, withdrawal, active engagement, social support seeking, and denial. It is scored on a 5-point Likert scale ranging from 1 to 5. The lowest score in each subscale is 4 and the highest score is 20.In this questionnaire, the higher the score of the subject in the subscales of doing other things, active coping, and seeking social support, and the lower the score in the subscales of withdrawal and ignoring, the better his/her state is in terms of behavioral regulation of emotion. In the study by Kraaij and Garnefski (2019), the reliability of this questionnaire using Cronbach's alpha was reported as 0.86 for doing other things, 0.93 for withdrawal, 0.91 for active coping, 0.91 for seeking support, and 0.89 for ignoring, and the test-retest coefficients for the above subscales were 0.47, 0.70, 0.62, 0.75, and 0.56, respectively. In the study by Rafiee Rad et al. 2022, the reliability of this questionnaire using Cronbach's alpha was reported as 0.732 for the total scale, 0.888 for the distraction subscale, 0.702 for the withdrawal subscale, 0.791 for the active coping subscale, 0.786 for the social support subscale, and 0.844 for the ignoring subscale. Using the test-retest method, the total value was 0.823, the distraction subscale was 0.831, the withdrawal subscale was 0.769, the active coping subscale was 0.930, the social support subscale was 0.874, and the ignoring subscale was 0.791. In the study by Ashori, Ghasemzadeh, and Safarpour in 2020, the opinions of 9 experts were used to determine the face and content validity. The content validity index was obtained by the Lavashe method and the Waltz and Bassel method, and the construct validity index was calculated by factor analysis. The results of exploratory and confirmatory factor analysis, respectively, showed that the five-factor model had a good fit and confirmed the construct validity of the instrument. The face and content validity (total content validity index − 0.84) were confirmed. The content validity index for each of the subscales of doing other things, withdrawal, active coping, seeking social support, and ignoring was 0.82, 0.87, 0.86, 0.78, and 0.83, respectively. The results of the convergent and divergent validity of the behavioral emotion regulation questionnaire were examined and confirmed by administering it simultaneously with the cognitive emotion regulation questionnaire and the depression, anxiety, and stress scale. In the present study, Cronbach's alpha was 0.95 for the entire questionnaire and 0.86, 0.85, 0.79, 0.88, and 0.82 for each of the subscales of doing other things, withdrawal, active coping, seeking social support, and ignoring, respectively. Findings The present study included 301 undergraduate students from Kharazmi University. In order to examine the data collected at the descriptive level, the mean, standard deviation, and correlation matrix between the research variables were calculated using SPSS 25 software. According to Kline (2011), when the sample size is more than 100 people, the skewness and kurtosis index are used to examine normality. If the absolute value of the skewness and kurtosis of the variables is less than 3 and 10, respectively, it can be concluded that the distribution of the variables is normal. Table 1 shows the mean, standard deviation, correlation matrix, and skewness and kurtosis of the research variables. Table 1 Mean, standard deviation, correlation matrix, and skewness and kurtosis of research variables Variable mean standard deviation kurtosis skewness 1 2 3 Resilience 84.98 9.05 -0.02 -0.09 1 Behavioral emotion regulation 65.20 7.02 1.14 1.02 0.16** 1 Cognitive flexibility 96.25 10.29 0.19 0.25 0,11* 0.17** 1 **P < 0,01 As can be seen in Table 1 , the data distribution is normal and the results of Table 2 showed that there is a positive and significant correlation between the research variables. To test the research hypotheses, the structural model fit indices as well as the direct and indirect effect coefficients were estimated using Amos 24 software, and these results are presented below. In order to examine the fit of the model, relative fit indices (RFI, normalized fit (NFI), incremental fit (IFI), Tucker-Lewis (TLI), comparative fit (CFI), and root mean square error of estimation (RMSEA) were estimated, the results of which are given in Table 3 . Table 3 Fit indices of the research structural model Indicators NFI RFI IFI TLI CFI RMSEA Obtained values 0.97 0.95 0.95 0.96 0.99 0.05 Acceptable range > 0.90 > 0.90 > 0.90 > 0.90 > 0.90 < 0.06 As can be seen in Table 3 , all indicators were desirable and within the acceptable range. The standardized regression coefficients are shown in Fig. 2 . Table 4 shows the standardized coefficients of the direct effects of the variables. Table 4 Direct path coefficients and significance of the research conceptual model constructs From variable to variable direct effect Standard coefficient Standard error Lower 95% range Upper 95% range Significance level Percentage of variance explained behavioral emotion regulation Cognitive flexibility 0.26 0.21 0.04 0.25 0.42 0.001 0.35 Cognitive flexibility Resilience 0.17 0.15 0.02 0.09 0.13 0.001 0.28 behavioral emotion regulation Resilience 0.38 0.08 0.02 0.08 0.11 0.001 0.41 As can be seen in Table 4 , the direct effect of behavioral emotion regulation on cognitive flexibility is significant and equal to 0.26. The direct effect of cognitive flexibility on resilience is also equal to 0.17, and the direct effect of behavioral emotion regulation on resilience is equal to 0.38. The results of the mediation analysis are presented in Table 5 . Table 5 Mediating effect of cognitive flexibility in the relationship between behavioral emotion regulation and resilience Pathway Range below 95 Range above 95 Significance level Behavioral regulation of emotion-flexibility-resilience 0.42 0.34 0.01 As can be seen in Table 5 , the upper and lower limits of the bootstrap are both positive and have the same sign, and the obtained value is not zero, which indicates that the indirect path is significant. Therefore, the conceptual model under study has a good fit. Discussion and Conclusions The present study aimed to investigate the mediating role of cognitive flexibility in the relationship between behavioral emotion regulation and resilience. The results of data analysis confirmed the suitability of the proposed model and showed that behavioral emotion regulation has a significant direct effect on students' resilience. These findings were consistent with the results of Jalali et al. (2022), Rassam et al. (2021), Nironamnd et al. (2019).In explaining this finding, according to Nazargarnevsky et al. (2001), it can be said that emotion regulation can be considered as a style of managing emotionally arousing information that encompasses a wide range of cognitive, behavioral, emotional, and physiological responses, helps manage and regulate emotions and makes the individual more adaptable to the environment. It has also been shown that emotion regulation techniques help reduce negative emotional responses and, as a result, increase the individual's resilience in adverse situations (Rubin Falcone, 2018).In behavioral emotion regulation, attempts at distraction, active coping, and attempts to gain social support help individuals regulate their emotions in a desirable manner, gain more self-control, and provide them with greater reassurance about having social support. Meanwhile, withdrawal and ignoring cause individuals to avoid experiencing and coping with stressful situations, which leads to a decrease in individual resilience and even an increase in distress and depression ((Lovian et al.2019). Other research results showed that behavioral emotion regulation has a positive direct effect on cognitive flexibility. These findings were consistent with the results of Sosa and Lagana (2019), Fu and Zhang (2017), and Ashori and Rashidi (2019). In explaining this finding, it can be said that emotion regulation training helps an individual gain more knowledge and awareness of their emotions, and as a result, have better control over their emotions and increase their tolerance for negative emotions. When a person is less negatively affected by their emotions and learns to modulate positive and negative emotions with positive strategies, it will have positive consequences and lead to higher mental and cognitive flexibility in the individual (Kitazawa et al., 2019). The emotion regulation strategies program emphasizes logical thinking and the correct expression of psychological and emotional reactions, and in this program, awareness of feelings and emotions and skills for understanding emotions and choosing situations are taught, which will have a significant impact on cognitive flexibility (Adigun, 2017). Other results showed that cognitive flexibility has a positive and significant direct effect on resilience. These results were in line with the findings of Sayed Mirzaei et al. (2022), Arici-Ozcan et al. (2019), Gloster et al. (2017). In explaining this finding, it can be said that according to Dennis and Vander Wal (2010), the ability to change cognitive dispositions in order to adapt to changing environmental stimuli is the main element in the operational definition of cognitive flexibility. People who have flexible thinking positively restructure their thought framework and are more tolerant and tolerant in challenging and stressful situations (Gloster et al., 2017). In other words, since cognitive flexibility changes people's perspective on life's problems and stresses, it can also have a positive impact on their resilience. There are different emotions, including anger, fear, hope, despair, worry, inferiority complex, pride, sadness, happiness, etc., and they are used to express all positive and negative emotional and psychological states and their accompanying physical symptoms( Sheikhlarabadi et al. 2025). In fact, people with greater cognitive flexibility, due to experiencing more positive emotions, show greater self-flexibility when faced with cognitive tasks and seek new strategies (Arici-Ozcan et al., 2019). The final finding of the study showed that cognitive flexibility plays a mediating role between behavioral emotion regulation and resilience. These findings were consistent with the results of Arici-Ozcan et al. (2019), Moeini et al. (2022), and Ghavami et al. (2022). Emotion regulation training, by making the individual aware of his/her emotions in different situations, helps the individual to have greater control over his/her emotions and to demonstrate a higher level of cognitive flexibility in stressful and tense situations with a higher perception of different problem-solving options and multiple evaluation (Ghavami et al., 2022). The more flexible a person is and the more they view difficult situations as controllable, and the more they have the ability to think of alternative explanations when faced with life events and people's behavior, and the more they can think of alternative solutions in difficult situations, the higher their capacity to cope, adapt, and recover from stress and life difficulties, and they are more psychologically resilient than people who are not flexible (Burton et al., 2010). Therefore, according to what has been said, behavioral emotion regulation through cognitive flexibility affects resilience. Overall, the present study attempted to address the research gap regarding the relationship between behavioral emotion regulation and resilience by reviewing the background and examining the possible impact of cognitive flexibility. One limitation of the present study is the use of questionnaires, which are self-report instruments. Second, the participants in this study were students, so caution should be exercised in generalizing the findings to other age groups. Also, due to the use of the structural equation method, which is based on correlation, the researcher faces limitations in explaining the causal relationships between variables; therefore, conducting research with an experimental design that examines the intervention effect of behavioral emotion regulation by increasing cognitive flexibility on resilience will help confirm and complete the results of the present study. It is suggested that training sessions be held to regulate behavior emotion and improve students' cognitive flexibility, and that the intervention for regulating behavior emotion and cognitive flexibility be taught to counselors and psychologists in university counseling and psychological service centers through a specialized workshop so that they can take a practical step towards improving their resilience by applying this intervention to students with low resilience. Declarations Conflict of interest statement On behalf of all authors, the corresponding author states that there is no conflict of interest. References Adigun OT. (2017). Depression and individuals with hearing loss: A systematic review. Journal of Psychology& Psychotherapy. 7(5):1-6. Aldao A, Nolen-Hoeksema S, Schweizer S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical psychology review . 30(2):217-37. https://doi.org/10.1016/j.cpr.2009.11.004 Allen N, Nelson BW. (2018). 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2","display":"","copyAsset":false,"role":"figure","size":52515,"visible":true,"origin":"","legend":"\u003cp\u003eStandardized regression coefficients in the present research model\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8373134/v1/37d73d5bc98e2619c8825cd2.png"},{"id":98632095,"identity":"8878c3b5-2127-4fc8-b0bb-875e931b4058","added_by":"auto","created_at":"2025-12-19 17:21:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":745482,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8373134/v1/295c5e00-dec2-4aa0-8d1b-87f5f8c44192.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eBehavioral Emotion Regulation and resilience in students: The mediating role of cognitive flexibility\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcademic life is full of challenges, personal, social and educational issues, because the student must adapt to them not only to achieve academic success, but also to ensure a good state of physical and mental health throughout the academic period. Otherwise, adverse consequences will be likely Restrepo-Widney et al., 2025; Martin and Marsh, 2006). Studies show that the lack of skills and preparation necessary to deal with the stressors of the student period leads to burnout and frustration (Mc Allister and MC Kinnon, 2009). Therefore, effectively dealing with these stressors will play an effective role in improving the physical and mental health of students.\u003c/p\u003e \u003cp\u003eOne of the factors that plays a decisive role in critical academic situations for students is resilience (Martin \u0026amp; Marsh, 2006). Resilience is the ability to overcome difficult situations that occur in life, by recognizing them, accepting them, and emerging stronger than them (Rutter, 1999). Resilience is an individual's confidence in their abilities to overcome stress, having coping skills, self-respect, emotional stability, and personal characteristics that increase social support from others ((Solgi and Shafiei, 2022). This construct is one of the factors that prevents the occurrence of psychological problems among individuals and protects them from the psychological effects of problematic events Waugh et al. (2008)). In other words, resilience is positive adaptation in response to adverse circumstances (Masten et al., 2001). Of course, resilience is not just stability against harm or threatening conditions, nor is it a passive state in the face of dangerous conditions, but rather an active and constructive company in one's surrounding environment and the ability of an individual to establish a biological-psychological balance in dangerous conditions (Conz \u0026amp; Magnani, 2020). In fact, academic resilience is defined as a protective behavior that students use to effectively face problems and achieve appropriate academic results. This means that students who have reached a high threshold of resilience continue to achieve high success even when faced with fewer educational resources (Aydin and Micho, 2020). In educational settings, students who demonstrate resilience in their education and in the face of tasks of varying degrees of difficulty are also resilient to obstacles in everyday life. Resilience capacity is generalized to other aspects of individuals' lives, helping them overcome difficulties academically and personally (Reeve et al. (2020). Many factors appear to be associated with and influence resilience.\u003c/p\u003e \u003cp\u003eOne of the important and effective factors of resilience is emotional self-regulation (Malashahi and Azarian, 2023). Emotion regulation is the ability to employ adaptive psychosocial functions through the regulation of emotional responses, which is a dynamic developmental process that emerges during childhood and adulthood (Allen and Nelson, 2018). Emotion regulation has two cognitive and behavioral dimensions that indicate the way an individual copes with stressful events and should not be considered the same because thinking and action are separate processes (Garnefski et al., 2001).\u003c/p\u003e \u003cp\u003eOne of the most common types of emotion regulation that has received much credible research is cognitive emotion regulation. Garnefski et al. (2009) define cognitive emotion regulation as the conscious mental strategies that an individual uses to cope with and cope with the receipt of emotionally arousing information. In other words, cognitive emotion regulation means cognitively changing the information that arouses emotion (Ochner-Gross, 2005). Cognitive therapy based on emotion regulation is effective in reducing impulsivity and aggression in children with behavioral problems(Gholamzadeh Nikjoo et al. 2022).\u003c/p\u003e \u003cp\u003eCognitive emotion regulation includes the components of self-blame, blaming others, rumination, catastrophizing, perspective-expanding, positive refocusing, positive appraisal, acceptance of the situation, and planning, which focus on the mental and abstract dimension of the emotion regulation process (Garnefski and Kraaij, 2006; Schroevers et al., 2007).\u003c/p\u003e \u003cp\u003eHowever, a newer type of emotion regulation that has received less research to date is behavioral emotion regulation. Behavioral emotion regulation is a set of behavioral strategies that individuals often use to adapt to and cope with stressful events, and focuses on the behavioral and objective dimensions of the emotion regulation process with the components of distraction seeking (distracting oneself from emotions by doing something else, with the aim of coping with the stressful event), withdrawal (withdrawing from situations and social interactions with the aim of coping with the stressful event), active coping (behaving actively in dealing with the stressful event), social support seeking (actively sharing emotions and asking for advice and support from others with the aim of coping with the stressful event), and denial (ignoring and behaving as if nothing had happened to cope with the stressful event) (Kraaij \u0026amp; Garnevsky, 2019).\u003c/p\u003e \u003cp\u003eIt seems that distraction-seeking, active coping, and seeking social support are considered positive and adaptive strategies, and withdrawal and ignoring are considered negative and maladaptive strategies, to manage stressful situations (Joorman \u0026amp; Stanton, 2016; Kraaij \u0026amp; Garnefski, 2019). Gross (1999) states that individuals use different emotion regulation strategies depending on their individual differences with others; For example, people who score high on the extraversion scale are more likely to be drawn to situations where there is social conflict. Thus, it is possible that some people, depending on their unique personality traits, prefer to use behavioral emotion regulation strategies over cognitive emotion regulation strategies, or vice versa. Therefore, given individual differences in the use of different emotion regulation strategies, more attention should be paid to the distinction between behavioral and cognitive types.\u003c/p\u003e \u003cp\u003eAccording to a meta-analytic study by Aldao et al. (2010), using maladaptive behavioral emotion regulation strategies is more harmful than not using adaptive strategies. Also, using these maladaptive strategies leads to the individual avoiding effective confrontation with stressful situations and, as a result, reduces his/her resilience (Lovian et al., 2023). Recent findings indicate that emotional dysregulation causes various physical and psychological disorders and makes the individual more vulnerable to stressful events, therefore, researchers have paid special attention to this variable in recent years (Hassani et al., 2008; Garnefski and Kraaij, 2006). Among the psychological disorders that can be caused by disorders in behavioral emotion regulation is substance abuse (Basharpoor, Ahmadi, \u0026amp; Heidari, 2021). One of the academic disorders that can be affected by an individual's emotion regulation strategies is test anxiety (Rasam et al., 2021). Hassani, Sohrabi, \u0026amp; Mohammadkhani (2023) concluded that difficulty in emotion regulation plays a role in students' academic failure. Also, according to the research of Rafiee Rad, Basharpoor, Sadatrasol and Alizadehfard (2021)), behavioral regulation of emotion plays an effective role in increasing and improving the quality of life. A review of the research background shows that the behavioral dimension of emotion regulation has received less attention in previous studies. While it seems that behavioral regulation of emotion plays an important role in adopting adaptive strategies in stressful situations.\u003c/p\u003e \u003cp\u003eA relatively large amount of research has been conducted on the relationship between emotion regulation and resilience. For example, Jalali et al. (2022) in their study on the effect of emotion regulation skills training on soldiers' resilience based on the self-efficacy model concluded that emotion regulation skills training using self-efficacy theory has a significant and meaningful effect on soldiers' resilience. Nironamnd, et al. (2019) also found that training in emotion regulation skills and techniques has a positive effect on individuals' resilience and increases it. However, a review of the research background shows that the relationship between the behavioral dimension of emotion regulation and resilience has not been given much attention and study. While it seems that measures aimed at behavioral emotion regulation, such as active coping, are related to individual resilience. On the other hand, the role of mediating factors in the relationship between emotion regulation and resilience has been largely ignored in previous studies. A review of the literature shows that one of the constructs that could possibly be decisive in the relationship between behavioral emotion regulation and resilience is cognitive flexibility.\u003c/p\u003e \u003cp\u003eCognitive flexibility is defined as an individual's readiness to selectively change among mental processes to produce appropriate behavioral responses to stressful situations and refers to the ability to change cognitive dispositions and effectively adapt to the ever-changing environment in which one lives (Dajani \u0026amp; Odin, 2015; Dickstein et al., 2007).According to Guilford (1967), cognitive flexibility is defined as the ability to break old cognitive patterns and thus overcome the stability of performance to create novel and creative connections between concepts. In fact, cognitive flexibility helps individuals to adapt to new and unpredictable events in the environment through learning processes based on previous experiences and processing new cognitive strategies (Canas et al., 2006).\u003c/p\u003e \u003cp\u003eThe results indicated that cooperative learning markedly improves students' social abilities. Furthermore, both emotional regulation (ER) and cognitive exibility (CF) were identi ed as mediators of this connection, with partial mediation evident in many pathways. Cooperative learning favorably impacted emotional sensitivity and ER, while also in uencing social sensitivity and expressiveness through CF( Ma, et al. 2025) Finally, with the help of cognitive flexibility, an individual can create desirable and adaptive changes in her/his environment and overcome new problems that arise around her/his by changing her/his previous cognitive patterns and employing new cognitive processes that can only be achieved by having flexibility in the thinking process (Canas et al., 2003)\u003c/p\u003e \u003cp\u003ePeople who are flexible in their thinking and behavior seek alternative behaviors and thoughts when faced with problems so that they can flexibly adapt to the new situation by considering other options (Arici-Ozcan et al., 2019)..When faced with new issues, people with cognitive flexibility are ready at any moment to abandon the actions they took in the past when facing previous problems and turn to solutions that deal with the new problem effectively and adapt to the emerging situation and situation with the help of alternative methods (Kloo et al., 2008).These individuals have the ability to quickly reconstruct their cognition; hence, they adapt their responses to the constantly changing demands of their situation and effectively and efficiently deal with unpredictable events (Spiro and Jehng, 2012).Past studies suggest that people with impaired flexibility also have impaired learning and resilience in the face of psychological stress, which ultimately leads to lower creativity, performance, and quality of life (Dajani \u0026amp; Odin, 2015; Feng et al., 2020). Phillips (2011) also states that individuals' weakness in cognitive flexibility can lead to impaired resilience and ultimately cause them to perform poorly in the face of life's difficulties, because they are unable to carry out the cognitive restructuring process efficiently and adapt appropriately to the problem at hand by changing their cognitive strategies and choosing other options as an alternative. In contrast, people who are highly resilient and demonstrate good cognitive flexibility in various situations are able to reconsider their approach to a problem and are able to avoid perceiving that situation as stressful by employing several different behavioral and cognitive methods to solve a problem (Phillips, 2011; Southwick et al., 2005).\u003c/p\u003e \u003cp\u003eFindings showed that cognitive-behavioral therapy affects self-control, difficulty in emotion regulation, resilience and psychological flexibility in clients with practical obsession( Ghafari Cherati et al. 2022). People who are able to think about problems flexibly, use alternative interpretations, reframe positively when necessary, and be receptive to challenging situations and upsetting events have greater psychological resilience than those who are not flexible in their thinking; instead of seeing problems as permanent and pervasive, they perceive them as temporary and limited, which is one of the characteristics of resilient people (Haglund et al., 2007).For this reason, people with cognitive flexibility cope more effectively with stressful environmental stimuli and adapt and adapt to their environment more patiently; as a result, they show greater resilience (Boon et al., 2012; Gan et al., 2006). Hajipour and Eynypour (2021) concluded that teaching resilience to individuals increases their level of flexibility due to the development of real experiences, empirical examination of thoughts, and modification of thoughts.\u003c/p\u003e \u003cp\u003eResearch also shows that there is a significant relationship between cognitive flexibility and emotion regulation. For example, Lee and Orsillo (2014) found that as cognitive flexibility increases, the regulation of negative emotions such as anxiety decreases. Ghosh and Halder (2020) also found a significant relationship between emotion regulation and cognitive flexibility in most adults; such that people with high cognitive flexibility regulated their emotions using cognitive reappraisal of emotion. Raeisi Sarteshneizy et al. (2020) also found that there is a significant relationship between self-efficacy in emotion regulation and cognitive flexibility, and stated that people with high flexibility are better able to cope with emotional turmoil.\u003c/p\u003e \u003cp\u003eBy reviewing the studies conducted in the field of coping strategies, it seems that paying attention to the three factors of behavioral emotion regulation, resilience, and cognitive flexibility is very important, especially in the academic context. University life is often accompanied by unforeseen events that highlight the need to be equipped with coping strategies and emotion regulation. Whether in situations that require communicating with professors and peers or when facing sometimes difficult and complex assignments, emotion regulation is one of the coping methods that helps relieve tension in stressful situations and can increase students' resilience in difficult and unforeseen situations. Although numerous studies indicate a relationship between emotion regulation and resilience, the behavioral dimension of emotion regulation and its relationship with resilience have not been addressed, and the nature of this relationship and the role of cognitive factors such as cognitive flexibility in the relationship between emotion regulation and resilience are not clear. It seems that people who use adaptive behavioral strategies to regulate their emotions change their perspective on the problem and face it with more flexibility, and therefore show greater resilience in facing problems.\u003c/p\u003e \u003cp\u003eTherefore, the aim of the present study is to investigate the mediating role of cognitive flexibility in the relationship between behavioral emotion regulation and resilience. The conceptual model of the research is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In this study, we intend to test the hypothesis that behavioral emotion regulation through cognitive flexibility is a significant predictor of resilience in students.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003eThe present study is descriptive in terms of its fundamental purpose and the method of data collection, and is of the correlation type. The analysis method of this study is path analysis, which was used to examine the causal relationships of the research variables. The data were also analyzed with SPSS 25 and AMOS 24 software. The statistical population of the present study consisted of all undergraduate students of Kharazmi University in the academic year 2022\u0026ndash;2023. The sample was collected using a multi-stage cluster method and in person (pencil-paper). Regarding the appropriate sample size for structural equation analysis, Kline (2005) suggested that a small sample of 100 numbers, a medium sample of 100 to 200 numbers, and a large sample of more than 200 numbers are considered. In this way, 301 students were selected as the sample. Informed consent to participate in the research and undergraduate students were considered as the entry criterion for the research; failure to respond to the questionnaire questions was considered as the exit criterion. Also, the principle of confidentiality and the principle of informed consent have been considered.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement tool:\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e\u003cb\u003eResilience Questionnaire\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eThis questionnaire was designed by Connor and Davidson in 2003. To create it, research sources on resilience obtained between 1979 and 1991 were reviewed and evaluated. The creators believe that this scale has a good ability to distinguish resilient from fragile individuals. This questionnaire has 25 questions and is a self-report tool. Its scoring is based on a Likert scale between 0 and 4 and the range of scores obtained is between 25 and 100.\u003c/p\u003e \u003cp\u003eMohammadi et al. (2006) adapted it for use in Iran. Besharat (2009) found its reliability based on Cronbach's alpha coefficient of 0.86, which is an acceptable score. To determine the validity of this scale, the correlation of each item with the total score of the category was first calculated and then factor analysis was used. Calculating the correlation of each score with the total score, except for item 3, showed coefficients between 0.41 and 0.64. Then, the scale items were factor analyzed using the principal components method. Before extracting factors based on the item correlation matrix, two KMO indices and Bartlett's sphericity test were calculated. The KMO value was 0.87 and the Bartlett chi-square value was 5556.28, both of which indicated the adequacy of evidence for factor analysis. In a study conducted among students by Samani, Jokar, and Sahragerd (2007), their reliability was reported to be 0.93, and the validity (using factor analysis and convergent and divergent validity) was verified by the test creators in different normal and at-risk groups (Samani et al., 2007). In the present study, the Cronbach's alpha of this questionnaire was 0.79.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eCognitive Flexibility Inventory (CFI):\u003c/h3\u003e\n\u003cp\u003eThis questionnaire was used by Dennis and Vander Wal (2010) to measure a type of cognitive flexibility that is necessary for an individual to successfully challenge and replace dysfunctional thoughts with more functional thoughts. This instrument is a valid two-factor construct; in other words, the final version of this scale consists of 20 questions, 13 questions for the alternatives subscale and 7 questions for the control subscale. In the Iranian version of this scale, developed by Shareh et al. (2014), three factors of control, alternatives, and substitutes for human behavior have been identified. The questions in this questionnaire are scored on a 7-point Likert scale from strongly disagree (1) to strongly agree (7). Questions 2, 4, 9, 7, 11, and 17 are reverse scored. The highest score a person can get is 140 and the lowest score is 20. A higher score indicates more cognitive flexibility and a lower score indicates less cognitive flexibility. Dennis and Vander Wal (2010) showed in a study that the present questionnaire has a good factor structure, convergent validity and concurrent validity. Its convergent validity with the Resilience Questionnaire was 0.67 and its concurrent validity with the Beck Questionnaire was \u0026minus;\u0026thinsp;0.50. These researchers obtained the reliability of the questionnaire using Cronbach's alpha for the entire questionnaire, control, and replacement as 0.81, 0.77, and 0.75, respectively. Reliability using the internal consistency method by calculating Cronbach's alpha coefficient in 227 students of Shiraz University and reliability using the test-retest method with an interval of 20 days in 35 students of Shiraz University were 0.90 and 0.71, respectively (Shareh et al., 2014). In the present study, Cronbach's alpha was 0.87.\u003c/p\u003e\n\u003ch3\u003eBehavioral Emotion Regulation Questionnaire (BERQ):\u003c/h3\u003e\n\u003cp\u003eThe Behavioral Emotion Regulation Questionnaire (BERQ) was designed by Garnefski and Kraaij in 2019 and assesses how people respond and behave when faced with difficult and stressful life situations. It has 20 questions and 5 subscales, which are: distraction seeking, withdrawal, active engagement, social support seeking, and denial. It is scored on a 5-point Likert scale ranging from 1 to 5. The lowest score in each subscale is 4 and the highest score is 20.In this questionnaire, the higher the score of the subject in the subscales of doing other things, active coping, and seeking social support, and the lower the score in the subscales of withdrawal and ignoring, the better his/her state is in terms of behavioral regulation of emotion. In the study by Kraaij and Garnefski (2019), the reliability of this questionnaire using Cronbach's alpha was reported as 0.86 for doing other things, 0.93 for withdrawal, 0.91 for active coping, 0.91 for seeking support, and 0.89 for ignoring, and the test-retest coefficients for the above subscales were 0.47, 0.70, 0.62, 0.75, and 0.56, respectively. In the study by Rafiee Rad et al. 2022, the reliability of this questionnaire using Cronbach's alpha was reported as 0.732 for the total scale, 0.888 for the distraction subscale, 0.702 for the withdrawal subscale, 0.791 for the active coping subscale, 0.786 for the social support subscale, and 0.844 for the ignoring subscale. Using the test-retest method, the total value was 0.823, the distraction subscale was 0.831, the withdrawal subscale was 0.769, the active coping subscale was 0.930, the social support subscale was 0.874, and the ignoring subscale was 0.791.\u003c/p\u003e \u003cp\u003eIn the study by Ashori, Ghasemzadeh, and Safarpour in 2020, the opinions of 9 experts were used to determine the face and content validity. The content validity index was obtained by the Lavashe method and the Waltz and Bassel method, and the construct validity index was calculated by factor analysis. The results of exploratory and confirmatory factor analysis, respectively, showed that the five-factor model had a good fit and confirmed the construct validity of the instrument. The face and content validity (total content validity index \u0026minus;\u0026thinsp;0.84) were confirmed. The content validity index for each of the subscales of doing other things, withdrawal, active coping, seeking social support, and ignoring was 0.82, 0.87, 0.86, 0.78, and 0.83, respectively. The results of the convergent and divergent validity of the behavioral emotion regulation questionnaire were examined and confirmed by administering it simultaneously with the cognitive emotion regulation questionnaire and the depression, anxiety, and stress scale.\u003c/p\u003e \u003cp\u003eIn the present study, Cronbach's alpha was 0.95 for the entire questionnaire and 0.86, 0.85, 0.79, 0.88, and 0.82 for each of the subscales of doing other things, withdrawal, active coping, seeking social support, and ignoring, respectively.\u003c/p\u003e"},{"header":"Findings","content":"\u003cp\u003eThe present study included 301 undergraduate students from Kharazmi University. In order to examine the data collected at the descriptive level, the mean, standard deviation, and correlation matrix between the research variables were calculated using SPSS 25 software. According to Kline (2011), when the sample size is more than 100 people, the skewness and kurtosis index are used to examine normality. If the absolute value of the skewness and kurtosis of the variables is less than 3 and 10, respectively, it can be concluded that the distribution of the variables is normal. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the mean, standard deviation, correlation matrix, and skewness and kurtosis of the research variables.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean, standard deviation, correlation matrix, and skewness and kurtosis of research variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003emean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ekurtosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eskewness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResilience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBehavioral emotion regulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive flexibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,11*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e**P\u0026thinsp;\u0026lt;\u0026thinsp;0,01\u003c/h2\u003e \u003cp\u003eAs can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the data distribution is normal and the results of Table\u0026nbsp;2 showed that there is a positive and significant correlation between the research variables. To test the research hypotheses, the structural model fit indices as well as the direct and indirect effect coefficients were estimated using Amos 24 software, and these results are presented below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn order to examine the fit of the model, relative fit indices (RFI, normalized fit (NFI), incremental fit (IFI), Tucker-Lewis (TLI), comparative fit (CFI), and root mean square error of estimation (RMSEA) were estimated, the results of which are given in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFit indices of the research structural model\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTLI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObtained values\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcceptable range\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e, all indicators were desirable and within the acceptable range. The standardized regression coefficients are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the standardized coefficients of the direct effects of the variables.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDirect path coefficients and significance of the research conceptual model constructs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrom variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eto variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edirect effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandard coefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLower 95% range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUpper 95% range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSignificance level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePercentage of variance explained\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebehavioral emotion regulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCognitive flexibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive flexibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResilience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebehavioral emotion regulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResilience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the direct effect of behavioral emotion regulation on cognitive flexibility is significant and equal to 0.26. The direct effect of cognitive flexibility on resilience is also equal to 0.17, and the direct effect of behavioral emotion regulation on resilience is equal to 0.38. The results of the mediation analysis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMediating effect of cognitive flexibility in the relationship between behavioral emotion regulation and resilience\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathway\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange below 95\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRange above 95\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificance level\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBehavioral regulation of emotion-flexibility-resilience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the upper and lower limits of the bootstrap are both positive and have the same sign, and the obtained value is not zero, which indicates that the indirect path is significant. Therefore, the conceptual model under study has a good fit.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion and Conclusions","content":"\u003cp\u003eThe present study aimed to investigate the mediating role of cognitive flexibility in the relationship between behavioral emotion regulation and resilience. The results of data analysis confirmed the suitability of the proposed model and showed that behavioral emotion regulation has a significant direct effect on students' resilience. These findings were consistent with the results of Jalali et al. (2022), Rassam et al. (2021), Nironamnd et al. (2019).In explaining this finding, according to Nazargarnevsky et al. (2001), it can be said that emotion regulation can be considered as a style of managing emotionally arousing information that encompasses a wide range of cognitive, behavioral, emotional, and physiological responses, helps manage and regulate emotions and makes the individual more adaptable to the environment. It has also been shown that emotion regulation techniques help reduce negative emotional responses and, as a result, increase the individual's resilience in adverse situations (Rubin Falcone, 2018).In behavioral emotion regulation, attempts at distraction, active coping, and attempts to gain social support help individuals regulate their emotions in a desirable manner, gain more self-control, and provide them with greater reassurance about having social support. Meanwhile, withdrawal and ignoring cause individuals to avoid experiencing and coping with stressful situations, which leads to a decrease in individual resilience and even an increase in distress and depression ((Lovian et al.2019).\u003c/p\u003e \u003cp\u003eOther research results showed that behavioral emotion regulation has a positive direct effect on cognitive flexibility. These findings were consistent with the results of Sosa and Lagana (2019), Fu and Zhang (2017), and Ashori and Rashidi (2019). In explaining this finding, it can be said that emotion regulation training helps an individual gain more knowledge and awareness of their emotions, and as a result, have better control over their emotions and increase their tolerance for negative emotions. When a person is less negatively affected by their emotions and learns to modulate positive and negative emotions with positive strategies, it will have positive consequences and lead to higher mental and cognitive flexibility in the individual (Kitazawa et al., 2019). The emotion regulation strategies program emphasizes logical thinking and the correct expression of psychological and emotional reactions, and in this program, awareness of feelings and emotions and skills for understanding emotions and choosing situations are taught, which will have a significant impact on cognitive flexibility (Adigun, 2017).\u003c/p\u003e \u003cp\u003eOther results showed that cognitive flexibility has a positive and significant direct effect on resilience. These results were in line with the findings of Sayed Mirzaei et al. (2022), Arici-Ozcan et al. (2019), Gloster et al. (2017). In explaining this finding, it can be said that according to Dennis and Vander Wal (2010), the ability to change cognitive dispositions in order to adapt to changing environmental stimuli is the main element in the operational definition of cognitive flexibility. People who have flexible thinking positively restructure their thought framework and are more tolerant and tolerant in challenging and stressful situations (Gloster et al., 2017). In other words, since cognitive flexibility changes people's perspective on life's problems and stresses, it can also have a positive impact on their resilience. There are different emotions, including anger, fear, hope, despair, worry, inferiority complex, pride, sadness, happiness, etc., and they are used to express all positive and negative emotional and psychological states and their accompanying physical symptoms( Sheikhlarabadi et al. 2025). In fact, people with greater cognitive flexibility, due to experiencing more positive emotions, show greater self-flexibility when faced with cognitive tasks and seek new strategies (Arici-Ozcan et al., 2019).\u003c/p\u003e \u003cp\u003eThe final finding of the study showed that cognitive flexibility plays a mediating role between behavioral emotion regulation and resilience. These findings were consistent with the results of Arici-Ozcan et al. (2019), Moeini et al. (2022), and Ghavami et al. (2022). Emotion regulation training, by making the individual aware of his/her emotions in different situations, helps the individual to have greater control over his/her emotions and to demonstrate a higher level of cognitive flexibility in stressful and tense situations with a higher perception of different problem-solving options and multiple evaluation (Ghavami et al., 2022). The more flexible a person is and the more they view difficult situations as controllable, and the more they have the ability to think of alternative explanations when faced with life events and people's behavior, and the more they can think of alternative solutions in difficult situations, the higher their capacity to cope, adapt, and recover from stress and life difficulties, and they are more psychologically resilient than people who are not flexible (Burton et al., 2010). Therefore, according to what has been said, behavioral emotion regulation through cognitive flexibility affects resilience.\u003c/p\u003e \u003cp\u003eOverall, the present study attempted to address the research gap regarding the relationship between behavioral emotion regulation and resilience by reviewing the background and examining the possible impact of cognitive flexibility. One limitation of the present study is the use of questionnaires, which are self-report instruments. Second, the participants in this study were students, so caution should be exercised in generalizing the findings to other age groups. Also, due to the use of the structural equation method, which is based on correlation, the researcher faces limitations in explaining the causal relationships between variables; therefore, conducting research with an experimental design that examines the intervention effect of behavioral emotion regulation by increasing cognitive flexibility on resilience will help confirm and complete the results of the present study.\u003c/p\u003e \u003cp\u003eIt is suggested that training sessions be held to regulate behavior emotion and improve students' cognitive flexibility, and that the intervention for regulating behavior emotion and cognitive flexibility be taught to counselors and psychologists in university counseling and psychological service centers through a specialized workshop so that they can take a practical step towards improving their resilience by applying this intervention to students with low resilience.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of interest statement\u003c/h2\u003e \u003cp\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e "},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAdigun OT. 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The effects of video game training on the cognitive functioning of older adults: A community-based randomized controlled trial. \u003cem\u003eArchives of Gerontology and Geriatrics\u003c/em\u003e. 80:20-30. https://doi.org/10.1016/j.archger.2018.04.012\u003c/li\u003e\n \u003cli\u003eSouthwick, S.M., Vythilingam, M., Charney, D.S. (2005). The psychobiology of depression and resilience to stress: implications for prevention and treatment. Annu. Rev. Clin. Psychol. 1(1):255-91. https://doi.org/10.1146/annurev.clinpsy.1.102803.143948\u003c/li\u003e\n \u003cli\u003eSpiro, R.J., Jehng, J.C. (2012). Cognitive flexibility and hypertext: Theory and technology for the nonlinear and multidimensional traversal of complex subject matter. In Cognition, education, and multimedia .(pp. 163-205). \u003cem\u003eRoutledge\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eWaugh, C.E., Fredrickson, B.L., Taylor, S.F. (2008). Adapting to life\u0026rsquo;s slings and arrows: Individual differences in resilience when recovering from an anticipated threat. \u003cem\u003eJournal of research in personality\u003c/em\u003e. 42(4):1031-46. https://doi.org/10.1016/j.jrp.2008.02.005\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 2","content":"\u003cp\u003eTable 2 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Kharazmi University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Behavioral emotion regulation, resilience, cognitive flexibility, students","lastPublishedDoi":"10.21203/rs.3.rs-8373134/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8373134/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe aim of the present study was to investigate the mediating role of cognitive flexibility in the relationship between Behavioral Emotion Regulation and students' resilience. The research method was descriptive-correlational and structural equation modeling. The statistical population included all undergraduate students at Kharazmi University in the academic year 2022\u0026ndash;2023, from which 301 people were selected as samples using multi-stage cluster sampling. In order to collect data, the Academic Resilience Questionnaire (Connor and Davidson, 2003), Cognitive Flexibility (CFI, Dennis and Vander Wal, 2010), and Behavioral Emotion Regulation Questionnaire (BERQ, Garnefski and Kraaij, 2019) were used. The results showed that the proposed model had a good fit. Also, the direct effect of behavioral emotion regulation on resilience and cognitive flexibility was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and the direct effect of cognitive flexibility on resilience was also significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Other results also showed that cognitive flexibility had a mediating role between behavioral emotion regulation and resilience (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In summary, it can be concluded that behavioral emotion regulation directly and indirectly affects students' resilience through the mediating role of cognitive flexibility.\u003c/p\u003e","manuscriptTitle":"Behavioral Emotion Regulation and resilience in students: The mediating role of cognitive flexibility","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-19 02:24:13","doi":"10.21203/rs.3.rs-8373134/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"279b110b-81fb-4a69-a308-3c460129866d","owner":[],"postedDate":"December 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59728201,"name":"Psychology"}],"tags":[],"updatedAt":"2025-12-19T02:24:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-19 02:24:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8373134","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8373134","identity":"rs-8373134","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}