The instrumental role of forgiving in the relationship between cognitive flexibility and decision-making and happiness in athletes

The instrumental role of forgiving in the relationship between cognitive flexibility and decision-making and happiness in athletes | 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 The instrumental role of forgiving in the relationship between cognitive flexibility and decision-making and happiness in athletes Mehmet KARA, Nuriye Şeyma KARA This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4369738/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract This study intended to reveal the mediating relationship of forgiveness in the relationship between cognitive flexibility, decision-making, and happiness of athletes aged 18 and over through structural equation modeling. A total of 618 licensed athletes participated in the study, and the data were collected from volunteer participants using the "Forgiveness Decision Scale", "Cognitive Flexibility Scale", "Natural Decision-Making Scale" and "Happiness Scale". The results indicated that athletes’ forgiveness was the full mediator in the relationship between decision-making and happiness, and the partial mediator in the relationship between cognitive flexibility and happiness. The mediation study carried out offers clues to identify and eliminate the negativities on the way to the success of the athletes. Forgiveness Decision-Making Happiness Cognitive Flexibility Mediating Role Athlete Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Being happy, which is one of the situations we aim for in our lives, is a situation that everyone can desire. Happiness, one of the interests of positive psychology, is not only a component of an individual's mental health [ 1 ], but also a positive emotional state that contributes to the individual's interpretation of life [ 2 ], meaning it provides benefits in more than one dimension [ 3 ]. Being in a happy state is a situation that can affect the sports life as well as the healthy fulfillment of daily activities. Happiness is defined as the psychological state of health, joy and peace [ 4 ]. Seligman [ 5 ] stated that being happy consists of three dimensions: positive emotion, commitment to life and meaning of life. Positive emotion is based on having positive emotions about the past, present and future, and learning the skills necessary to increase the intensity of these emotions. In the dimension of being connected to life, the individual is expected to do activities that he enjoys in his business life, interpersonal relationships or in his spare time. Finally, in the dimension of the meaning of life, it requires the individual to use his talents and strengths for the benefit of society. In summary, the concept of happiness is based on the ability to control negative emotions and turn them into positive ones. In order for an individual to be happy, he must control his attitudes and reactions to the events he encounters. Therefore, this aspect of happiness is associated with the concept of forgiveness. The more an individual's sense of forgiveness is developed, the more his/her positive approach to life can increase his/her level of happiness. In a way, forgiveness is a concept that contains negative emotions. Edwards [ 6 ] stated that forgiveness begins in pain, anger, insecurity and confusion and sprouts in hatred. In other words, at its core is the ability to control these negative emotions and to look at the glass half full. In this respect, the concept of forgiveness is very important in terms of social relations and health. Fitzgibbons, Enright, and Brien [ 7 ] defined forgiveness as an affective, intellectual and moral reaction to unjust behavior by people. In this respect, it is possible to say that the concept of forgiveness opens a door to happiness. As a matter of fact, being able to control negative emotions in order to establish healthy relationships can positively strengthen our human relationships. In this context, this positive emotional state that emerges in our human relationships can increase the happiness level of individuals. Worthington [ 8 ], in his pyramid model of forgiveness, suggested that individuals' ability to forgive others in mutual relationships may be related to their level of happiness and well-being. Maltby, Day, and Barber [ 9 ] concluded that there is a significant positive relationship between happiness and forgiveness. In another study, Chan [ 10 ] found that there is a significant positive relationship between forgiveness and happiness. Forgiveness is not only a term that includes emotional processes, but also a concept that has cognitive processes [ 11 ]. Karremans, Van Lange, Ouwerkerk and Kluwer [ 12 ] found that happiness and the concept of forgiveness were positively related in their study. Again, Kaya ve Orçan [ 13 ] found that happiness has a mediating role between empathy, life satisfaction and forgiveness. In another study, Adam-Karduz and Sarıcam [ 14 ] found that there were significant relationships between forgiveness and happiness. Forgiveness and happiness are concepts that athletes encounter a lot in the sports environment. Because people who participate in sporting activities can feel better psychologically and physically, get away from stress and worries, improve their human relations, and feel happy by increasing their motivation [ 15 ]. This emotional state obtained in the sports environment can sometimes be experienced intensely by people who play sports professionally or as amateurs. Because athletes who constantly participate in competitions or competitions may be happy or unhappy at the end of the match. This situation may also affect their level of forgiveness. In addition, this situation can positively or negatively affect the performance of athletes in the next competition. As a matter of fact, sport can be expressed as a whole that includes various concepts such as competition, purpose, effort and excitement. The fact that athletes feel these emotions intensely can be quite decisive in their attitude towards the opponent and their performance. In order for athletes to be happy in the situations they face, it may be a result of their cognitive flexibility that they sometimes exhibit different behaviors than they are accustomed to and turn to the more appropriate option among the options they can choose. For this reason, it can be expressed as an expected product that people with high cognitive flexibility are happier as a result of their correct choices. Because people with high cognitive flexibility, which is expressed as the ability to quickly move from one situation to another [ 16 ], can easily change their minds in sudden situations [ 17 ]. Cognitive flexibility, defined by Kara, Kara, and Çetin [ 18 ] as the way of thinking towards the task that the individual has, can be a stepping stone to happiness. Therefore, it can be stated that the decisions made by an athlete with high cognitive flexibility in order to be happy may be more appropriate. As a matter of fact, Asıcı and Ikiz [ 19 ] found that there are significant and positive relationships between cognitive flexibility and happiness levels of individuals in their study. In addition, Yıldız [ 20 ] found that cognitive flexibility has a moderate and significant relationship with subjective well-being and that the predictor variables explain 60% of the total variance in subjective well-being. In another study, Satan [ 21 ] concluded that cognitive flexibility significantly predicted subjective well-being. Demirtaş [ 22 ] concluded that cognitive flexibility is positively related to happiness and cognitive flexibility predicts happiness. Similarly, Asıcı and Sarı [ 23 ] found that cognitive flexibility directly predicts happiness. Although being happy is a state of emotion, it is one's choices that drive happiness. When making choices, athletes also make a judgment among different situations. Decision making is a way of minimizing doubts and uncertainties [ 24 ] by voluntarily choosing one of the possible options [ 25 ]. Dilmaç and Bozgeyikli [ 26 ] found a significant relationship between subjective well-being and decision-making styles in their study. In another similar study, Tekkurşun-Demir, Namlı, Hazar, Turkeli, and Cicioglu [ 27 ] found a significant relationship between decision-making styles and mental well-being. Yıldız and Eldekioglu [ 28 ] concluded in their study that decision-making styles were significantly predicted in terms of happiness variable. Bubic and Erceg [ 29 ] found that the tendency to maximize during decision making is positively correlated with all three orientations towards happiness. Within the scope of this study, it was aimed to examine the effect of forgiveness on the process in the relationship between athletes' decision-making behaviors and happiness levels as well as the effect of forgiveness on the process in the relationship between athletes' cognitive flexibility and happiness levels. When the related studies were examined, the motivation of the study was that there was no study investigating whether the forgiveness variable included in the process had a mediating effect in the relationship between decision-making and cognitive flexibility of athletes and their happiness. Considering the studies, there is no modeling study that focuses on the relationships of these variables, which have a dominant role in sportive activities, within triple combinations. It is also considered important to model these relationships between variables and to visualize and address these models in the context of structural equation modeling (SEM). The motivation for examining the study with structural equation modeling is to examine the terms whose possible relationships are presented and whose conceptual relationships are discussed. The theoretical presentation of the causality relations of the models created reveals the importance of the examination. Before moving on to the models to be investigated within the scope of the study, the dependent, independent and mediating variables that are the subject of the research will be explained in the conceptual framework and the models predicted by the literature will be tested in this direction. The aim of this study is to determine how the relationship between decision making, cognitive flexibility and happiness changes when forgiveness is included in the process. The belief that these factors will contribute to the success of athletes reveals the importance of the study. 1.1. Happiness and Sport The concept of happiness, which is a part of our human emotions, can be shown as one of the determining factors in terms of the level of human life quality. Happiness corresponds to the evaluation of the level of quality of life of the individual in relation to his/her whole life [ 30 ]. Happiness is expressed as a cognitive and affective evaluation of life. Accordingly, an individual's frequent experience of positive emotions such as joy, pride, confidence and excitement; less frequent experience of negative emotions such as anger, fear, anxiety and hatred; and high satisfaction with family, work, career and similar areas of life can be explained as indicators of happiness [ 31 ]. In a sense, it can be inferred that feeling positive emotions frequently increases our daily life quality. Myers and Diener [ 32 ] defined happiness as the quantity and superiority of positive feelings about one's life. Seligman [ 5 ] stated that happiness consists of three dimensions: positive emotion, connectedness to life and meaning of life. Positive emotion refers to having positive emotions about the past, present and future and learning the necessary skills to increase the intensity of these emotions; being connected to life refers to doing and enjoying activities that the individual enjoys in his/her work life, social relationships or leisure time; and living a meaningful life refers to the ability to use one's talents and strengths to serve the society. In this context, it is possible to associate the concept of happiness with sports. Because sport is a concept that allows the discharge of negative emotions and it contains concepts such as success, purpose, winning and perseverance. Therefore, it is possible to say that the gains obtained in these concepts can bring happiness. As a matter of fact, human beings live for a purpose and make an effort to fulfill this purpose. Likewise, the concept of sport, which contains many goals, is related to happiness in this respect. Regarding this issue, according to Farabi, happiness is a goal that every human being desires, it is preferred and desired for the human being himself at any time [ 33 ]. The effort of athletes to be successful can be seen as an important component of happiness in sports. 1.2. Forgiveness and Sport Human beings have a structure that contains many emotions by nature. In this context, it can be said that the thinking power of human beings, who are thinking beings, is affected by a wide variety of emotional functions. These functions can be classified as positive and negative emotions. Therefore, the ability to control these emotions in the right way is an important factor in maintaining a healthy life. Because the emotional control required by social life affects our interpersonal relationships. As a matter of fact, people encounter many negative situations or events while interacting with their environment. In the face of this situation, the individual who is not forgiving towards his/her environment may isolate himself/herself from the society. The concept of forgiveness is seen as an interpersonal process to maintain and improve the quality of human relationships [ 34 ]. It is important to internalize the concept that affects our relationship with our environment so much. Forgiveness is a concept that allows a person to remove negative emotions from his/her life and transform them into an objective or positive emotion [ 35 ]. This concept, which is based on the removal of negative emotions, is related to the fact that sport is a concept that allows the discharge of negative emotions. Interaction in the sports environment provides the discharge and control of emotions. Individuals participating in sportive activities have the opportunity to express their emotions through movements. This enables the discharge and control of negative emotions such as anger, aggression, shyness, jealousy [ 36 ]. The fact that forgiveness sprouts as a result of negative emotions [ 6 ] means that it emerges as a result of the removal of these emotions. Therefore, the concept of forgiveness is seen to be related to sports since the opportunity to get away from negative emotions in a sports environment can enable an individual full of anger to discharge his/her emotions. 1.3. Cognitive Flexibility and Sport The situations we face in daily life push us to think alternatively among different options. The choices we make as a result of thinking determine the course of our lives. Therefore, having the cognitive abilities to make the right choices is important for the positive progress of our lives. At this point, it is possible to talk about the concept of cognitive flexibility. Cognitive flexibility is defined as the ability to assimilate that it is correct not to see the right options in the face of a problem, but to be able to see the options before making a choice [ 37 ]. In other words, cognitive flexibility is a form of fluid intelligence determined by the ability to bring alternative solutions to different situations [ 38 ]. In other words, it can be said to be able to adapt our cognitive processes according to the situations we encounter. In this sense, the concept of sport can be mentioned to support cognitive control. Because the concept of cognitive flexibility, which is at the basis of executive functions, is known to provide conscious control of actions, thoughts and emotions [ 39 ]. Considering the areas where sports interact with the brain, it is possible that our cognitive control is supported by sports. From a neurological point of view, it is known that the release of serotonin and dopamine, neurotransmitters that affect the decision-making mechanism in the brain increases with sports. In this context, these oscillations, which increase with sports, are important in terms of predicting which decision may be correct. Therefore, it can be said that there is a relationship between sports and cognitive flexibility. 1.4. Decision making and Sport The choices we face in our lives often lead us to choose one of these choices. In doing so, it is necessary to make a decision about which choice is the right one and to think about every aspect. Because we can be happy or sad as a result of the decisions we make. Decision making can be expressed as making the most appropriate choice by eliminating doubts and uncertainties in the light of the information obtained by individuals in the face of certain situations [ 40 ]. In other words, decision making is knowing what to do in a given or emerging situation [ 41 ]. Akpınar, Temel, Birol, Akpınar, and Nas [ 42 ] explained decision making as a behavior taken to eliminate the difficulty experienced when there are at least two or more options that will lead to an object, person or situation that is thought to satisfy the need. In this respect, the phenomenon of decision-making is also present in sports, which contains difficulties. Because the decisions made by referees, coaches or athletes in sports are decisive in being successful. In the sports environment where we often have to exhibit decision-making behavior, athletes are obliged to think in many ways and choose the most appropriate option. The decision to apply the wrong technique in a challenge can result in failure. In this respect, it is extra important for athletes to think in multiple ways to make the right decision. In addition, the changes that occur in the brain during sports can improve decision-making. From a neurological perspective, the dorsolateralalprefrontal cortex and ventromedialprefrontal cortex regions, which are the regions responsible for decision-making behavior in our brain, help in thought processes and making choices among various alternatives. In addition, brain imaging systems have concluded that these regions play an active role during activities such as short-term memory, cognitive flexibility and decision-making behavior in the light of various contexts [ 43 ]. When the effects of exercise on the nervous system are examined, it has been found that it improves synaptic structures in the brain, especially in regions related to cognitive functions such as the anterior hippocampus and prefrontal lobe, and accelerates neurogenesis, angioe-nesis, and cerebral blood flow [ 44 ]. Therefore, developments in these regions, which are responsible for the decision-making mechanism in the brain with sports and exercise, are important in terms of making the right decisions. In this context, it can be said that there is a relationship between decision-making and sports. The theoretical models planned based on the existence of the relationships between the variables above are visualized below in accordance with the purpose of the research. The theoretical models created for the concepts explained are presented in Fig. 1 and Fig. 2 and the hypotheses written for these models are indicated below the figures. Within the framework of the hypotheses covering Figure.1 and Figure.2, the main problem statement can be expressed as "What is the mediating role of forgiveness in the relationship between cognitive flexibility, decision making and happiness in athletes?". 2. Method 2.1. Research Model This study was designed within the scope of relational survey models in which possible theoretical causal relationships between athletes' cognitive flexibility, decision making, happiness and forgiveness were examined. Researchers do not intervene in the relationships in relational survey models. The researcher, who can provide clues in relational research, does not look for a relationship related to causes and effects [45]. 2.2. Study Group The study group of the research consists of 623 athletes who are 18 years of age or older and actively engaged in licensed sports as of 2023. As a result of the assumption tests of the Structural Equation Model, which is a multivariate analysis type, it was concluded that the remaining 618 observations were of sufficient size considering the minimum number of observations to be reached [46]. 2.3. Data Collection Tools Forgiveness Decision Scale The Decision to Forgive Scale, adapted to Turkish culture by Ekşi, Parlak, and Demir Celayir [47], consists of 6 items and a single dimension. The scale, which does not have reverse items, is a 5-point Likert-type scale ranging from Strongly Disagree (1) to Strongly Agree (5). A high score indicates a person's high decision to forgive. For the adaptation study of the Forgiveness Decision Scale to Turkish Culture, 297 pre-service teachers over the age of 18 participated. The Cronbach's alpha reliability coefficient calculated to obtain the reliability evidence of the scale was 0.91, and this value revealed that the scale is a highly reliable measurement tool. In addition, the item-total correlations of the items were examined to obtain evidence of the construct validity of the scale and it was found that these values ranged between 0.59 and 0.84. The correlation coefficients were also found to be statistically significant. Cognitive Flexibility Scale The Cognitive Flexibility Scale developed by Bilgin [48] consists of 19 items. The scale items consist of pairs of adjectives (e.g. I can, I cannot, - I am successful, I am unsuccessful). The lowest score that can be obtained from the scale is 21 points and the highest score is 105 points. Reliability and validity were tested using a sample of 637 adolescents. The higher the scores obtained from the scale, the closer the individual is to cognitive flexibility. In the reliability study conducted on the scale, the Cronbach's alpha coefficient for the whole scale was found to be 0.92. The item-total correlations of the items ranged between 0.49 and 0.63. The test-retest correlation coefficient was 0.77 and the halving coefficient was 0.87 over an eight-week interval. Natural Decision Making Scale Developed by Sundu and Yaşar, [49] the Natural Decision Making Scale consists of 6 items and one dimension. The Cronbach's Alpha coefficient calculated for the whole scale is 0.80. There are no reverse coded items in the scale, which has a 5-point Likert structure ranging from Strongly Agree to Disagree. Natural decision making, which is the subject of the research, was preferred in the scale created with 554 participants over the age of eighteen who are working in different professions, since it is seen as the process of focusing on and choosing the most appropriate one among various options. In addition, the factor loadings of the Natural Decision Making scale items ranged from 0.68 to 0.87 and all of them were statistically significant. Happiness Scale The Happiness Scale developed by Demirci and Eksi [50] has a unidimensional structure consisting of 6 items. The scale, which does not contain any reverse-coded items, has a 5-point Likert structure (1: Not at All Suitable for Me, 5: Completely Suitable for Me). Cronbach Alpha internal consistency coefficient of the scale was calculated as 0.83. The Happiness Scale, which was created to investigate the characteristics of a peaceful and happy life, was conducted with 900 participants over the age of 18. In addition, the test-retest reliability coefficient obtained from the reapplication of the scale to 62 participants at three-week intervals was calculated as 0.73. The factor loadings of the items in the scale ranged between 0.59 and 0.78. Confirmatory factor analysis (CFA) was conducted to reveal the psychometric qualities of the data collection tools used in this study. The aim of CFA is to discover the factor or factors based on the relationships between variables by revealing the sources of variance and covariance [51]. In order to obtain evidence for the reliability and convergent validity of the scales used in the study, AVE values were calculated and presented in Table 1. According to the research findings, the values calculated for CR, which is the evidence of construct relability, should be above 0.50 [52], the average variance extracted for convergent validity, i.e. AVE, should be in the range of CR≥AVE≥0.50 [53], but in cases where AVE values are less than 0.5, the CR≥0.7 criterion can be accepted for convergent validity. Since all scales included in the analysis were unidimensional, divergent validity evidence such as maximum shared squared (MSV) and average mean square of shared variance (ASV) were not examined. Table 1. Reliability and Validity Findings of The Scales Used Scales CA CR AVE CA CR Convergent Validity Happiness 0.87 0.84 0.49 ✓ ✓ ✓ Cognitive Flexibility 0.95 0.94 0.44 ✓ ✓ ✓ Natural Decision Making 0.70 0.70 0.40 ✓ ✓ ✓ Forgiveness 0.86 0.86 0.54 ✓ ✓ ✓ Criteria ≥.70 ≥.70 ≥.70>CR ≥.70 ≥.70 AVE<CR When the results of Table.1 are taken into consideration, it is concluded that all measurement tools used within the scope of the research provide reliable and valid measurements. It can be said that the AVE value obtained in Table 1 is low but acceptable. This is because Fornell and Larcker [53] emphasized that in cases where the CR value is higher than 0.60, AVE less than 0.50 is acceptable and construct validity is sufficient [54]. 2.4. Collection of Data The necessary ethical permission was obtained from the relevant committees before the study. Ethics committee approval was obtained from Mersin University. Voluntary participants were informed that the information received would only be used within the scope of the current study and would remain confidential. Scale forms including demographic information were applied to the participant athletes online for approximately 15 minutes and data were collected. 2.5. Data Analysis This study was conducted with structural equation modeling (SEM) in order to reveal the mediating relationships of forgiveness in the relationship between cognitive flexibility, decision making and happiness in active licensed athletes. SEM, which is a statistical method that predicts the causal relationships that observed and latent variables may have, puts forward a theoretical framework [55, 56, 57]. The main purpose of SEM is to reveal the relationship patterns of the data obtained as well as the latent variables [58]. SEM, which is widely used to test observed and latent variables and is based on a theoretical foundation [59, 60], is a method that tests and estimates multivariate models in fields such as economics, medicine and psychology [61, 62], and differs from traditional methods by taking into account the measurement errors of the latent variable [63, 16]. Before performing SEM, which is a multivariate statistical technique, assumptions were examined. Within the scope of the assumptions, since the data were collected online, no missing or missing data were found. Then, single and multiple outliers were examined. In this context, the standardized Z values for single outliers ranged between (-3.54, 1.58), and the 445th observation with a value of -4.37 was excluded from the analysis because it produced a single outlier. In this context, since all observations were within the limits of 4 ≥ z ≥ 4 [51], the analysis continued without any single outlier. As a result of the degrees of freedom comparison [64] for the remaining 621 observations, 3 observations (163rd, 390th and 546th) that produced values above the values of Mahalonobis distances (χ23, 0.001=16.27) were excluded from the analysis and the analyses continued with the remaining 618 observations. The hypothesis analyses continued with testing the multicollinearity problem and Variance Inflation Factor (VIF) and Tolerance values were analyzed. In this context, the tolerance values ranged between (0.922, 0.974) and all values were above 0.20; the VIF values ranged between (1.027, 1.084) and all observation values were below 5, indicating that there was no multicollinearity problem among the items [51]. The Durbin-Watson value, which is an additional test for multicollinearity, was obtained as 1.93, and the fact that this value is close to 2 [65] is an indication that the errors are not related to each other. Testing the measurement model is one of the basic assumptions of SEM analyses. Table.2 presents the goodness of fit and poorness of fit values of the measurement model including all the variables within the scope of the study and the criterion criteria against which these values will be compared. Table 2. Measurement Model Results Variables X 2 /sd RMSEA SRMR CFI NFI NNFI CFA Measurement Model 2555/623 0.08 0.05 0.95 0.93 0.95 Perfect fit ≤ 3 ≤.05 ≤.05 ≥.95 ≥.95 ≥.95 Good fit 3≤ x 2 /sd ≤ 5 .05≤RMSEA≤.08 .05 ≤ SRMR ≤.10 .90≤CFI <.95 90≤NFI<.95 90≤NFI<.95 Considering the goodness of fit statistics found in Table 2 and the literature criteria, it is observed that the tested measurement models match with excellent and good fit criteria. The testing of measurement models is an important assumption of SEM analysis [66], and the model-data fit evaluation is evaluated in Table 2 by considering excellent and acceptable fit values [67, 68, 69, 70]. It is recommended to report RMSEA, x 2 degrees of freedom and significance values, SRMR and CFI values as a minimum in studies based on CFA [70]. The measurement model tested with the dependent, independent and mediator variables in the study matches with excellent fit and good fit indicators. In this study, which was conducted on the basis of SEM by taking into account the mediation model of Baron and Kenny [71], the status of the relationships between the dependent, independent and mediator variables is taken into account in mediation decisions. In the first stage, the relationship between the dependent and independent variable is tested. This relationship should be significant. In the next stage, the fact that the mediating variable added to the model causes the relationship between the independent and dependent variable to be lost reveals that the mediating variable is full mediation, while only a decrease in the relationship between the independent and dependent variable or a slight decrease in the level of the standardized value reveals that it is partial mediation [72]. Before proceeding with the decision analyses regarding mediation studies, all of the binary relationships between the variables to be considered within the scope of the model must be significant. In this context, the analyses of the binary relationships between the dependent, independent and mediator variables hypothesized for Model-1 and Model-2 are evaluated based on the measurement model outputs and presented in Table 3 and Table 4. Table 3. Correlations Between Study Variables Variables Happiness Decision Making Happiness --- Decision Making .11 ** --- Forgiveness .23 ** .30 ** ** p < .01 Table 4. Correlations Between Study Variables Variables Happiness Cognitive Flexibility Happiness --- CognitiveFlexibility .54 ** --- Forgiveness .23 ** .14 ** ** p < .01 Therefore, within the scope of mediation, hypotheses 1,2,3,4,5,6,7 of the theoretical models in Figure 1 and Figure 2 were confirmed and the prerequisites for the mediation study were provided. 3. Findings In this section, mediation analyses were carried out in stages on the two models whose theoretical frameworks were drawn. In the first stage, the direct relationship between the dependent and independent variables and the t values revealing the significance of this relationship, and in the second part; the magnitude (status) of the relationship between the independent variable and the dependent variable obtained by adding the mediating variable to the models and the t values calculated for this relationship are included. 3.1. Model-1 The results of the mediation test conducted for model-1, which investigates whether forgiveness is a mediating variable in the relationship between decision making and happiness, are presented. Figures 3.a and 3.b show the standardized loadings and t values of the structural model between decision making, which is the independent variable in the research, and happiness, which is the dependent variable of the research. Figure 3.b reveals that there is a significant positive relationship between decision making and happiness levels of athletes (t=2.09; p<.01). Figure 3.a also shows that there is a theoretically weak causal relationship between athletes' decision making and their happiness levels (β=0.11; p<.01). Decision-making of athletes predicts their happiness levels by 0.01% (R2). The model data goodness of fit results obtained for this model are summarized in Table 5. Table 5. Model Fit Values for The Relationship Between Decision Making and Happiness Variables X 2 /sd RMSEA SRMR CFI NFI NNFI CFA Measurement Model 186/53 0.066 0.044 0.96 0.95 0.95 Perfect fit ≤ 3 ≤.05 ≤.05 ≥.95 ≥.95 ≥.95 Good fit 3≤ x 2 /sd ≤ 5 .05≤RMSEA ≤.08 .05 ≤ SRMR ≤ .10 .90≤CFI <.95 90≤NFI<.95 90≤NFI<.95 When the goodness of fit criteria in Table 5 are examined, it is concluded that the values of the model between the independent variable decision-making and the dependent variable happiness comply with the criteria of excellent and good fit. In the next stage of the mediation model, the mediator variable "forgiveness" was added to the model and figures 4.a and 4.b were obtained. In the model in which athletes' forgiveness levels assumed the mediating role, it was found that the relationship between decision making and happiness became insignificant (β=0.04 p>.01). On the other hand, the relationship between the independent variable decision-making and the mediating variable forgiveness was found to be positively significant (t=6.00; p<.01) and decision-making explained 9% (R2) of the change in forgiveness. The t-value findings of the relationships between variables are presented in Figure 4.b. Baron and Kenny [71] emphasized that there may be a mediation relationship if the relationship between the dependent variable and the independent variable decreases or disappears completely when the mediator variable is activated. Considering the significance levels of the relationships in the model, it can be said that forgiveness plays a full mediating role in the relationship between decision making and happiness. Table 6 presents the goodness of fit values for the mediation modeling. Table 6 Model Fit Values for The Mediating Role of Forgiveness in The Relationship Between Decision Making and Happiness Variables X 2 /sd RMSEA SRMR CFI NFI NNFI CFA Measurement Model 420/117 0.067 0.047 0.95 0.94 0.95 Perfect fit ≤ 3 ≤.05 ≤.05 ≥.95 ≥.95 ≥.95 Good fit 3≤ x 2 /sd ≤ 5 .05≤RMSEA ≤.08 .05 ≤ SRMR ≤ .10 .90≤CFI <.95 90≤NFI<.95 90≤NFI<.95 When the goodness of fit measures given in Table 6 and SEM values given in Figure 4.a and Figure 4.b are analyzed; it is seen that the relationship between decision making and happiness is explained by forgiveness. When athletes' forgiveness levels are included in the model, the model goodness of fit values have excellent and good fit indicators. 3.2. Model -2 In Model-2 created within the scope of the research, the mediating role of forgiveness in the relationship between athletes' cognitive flexibility levels and happiness levels is questioned. In the model, cognitive flexibility as the independent variable, happiness as the dependent variable and then forgiveness as the mediating variable were included in the process. Figure 5.a and 5.b show the results of the structural model. Figure 5.b shows that there is a significant positive relationship between athletes' cognitive flexibility levels and their happiness levels ( t =12,20; p <.01). Figure 5.a also shows that there is a moderate relationship between athletes' cognitive flexibility and their happiness levels ( β =0.54; p <.01). Athletes' decision-making predicts their happiness levels by 0.29% (R 2 ). The model data goodness of fit indices for the model between the two latent variables, which constitutes the first stage of mediation, are presented in Table 7. Table 7. Model Fit Values for The Relationship Between Cognitive Flexibility and Happiness Variables X 2 /sd RMSEA SRMR CFI NFI NNFI CFA Measurement Model 1858/274 0.011 0.062 0.95 0.94 0.95 Perfect fit ≤ 3 ≤.05 ≤.05 ≥.95 ≥.95 ≥.95 Good fit 3≤ x 2 /sd ≤ 5 .05≤RMSEA ≤.08 .05 ≤ SRMR ≤ .10 .90≤CFI <.95 90≤NFI<.95 90≤NFI<.95 The goodness of fit measures obtained in Table 7 have excellent and good fit indicators. The standardized path coefficients for the model investigating whether forgiveness plays a mediating role in the relationship between cognitive flexibility and happiness and the t-values giving information about the significance of these coefficients are presented in figures 6.a and 6.b. In the model in which athletes' forgiveness levels assumed the mediating role, it was concluded that the relationship between cognitive flexibility and happiness maintained its significance (β= 0.52; p<.01). Baron and Kenny [71] reveal that the relationship between the dependent variable and the independent variable is partial mediation if the relationship between the dependent variable and the independent variable decreases when the mediating variable is activated or a slight decrease in the level of the standardized value is observed [72]. Based on this information, it can be stated that the relationship between the dependent and independent variables decreased compared to the first stage (r=0,52; p <.01), so forgiveness played a partial mediating role between these two variables. The t-value findings of the relationships between the variables are presented in Figure 6.b. Table 8 presents the goodness of fit values for the mediation modeling. Table 8. Model Fit Values for The Mediating Role of Forgiveness in The Relationship Between Cognitive Flexibility and Happiness Variables X 2 /sd RMSEA SRMR CFI NFI NNFI CFA Measurement Model 2141/431 0.087 0.061 0.95 0.94 0.95 Perfect fit ≤ 3 ≤.05 ≤.05 ≥.95 ≥.95 ≥.95 Good fit 3≤ x 2 /sd ≤ 5 .05≤RMSEA ≤.08 .05 ≤ SRMR ≤ .10 .90≤CFI <.95 90≤NFI<.95 90≤NFI<.95 Considering the model goodness and model badness criteria for the model in which forgiveness plays a mediating role in the relationship between cognitive flexibility and happiness, it was concluded that this model also met the criteria of perfect fit and acceptable fit from a multiple evaluation perspective. 4. Discussion, Conclusion and Recommendations The dynamic structure of sport reveals the importance of more than one component in the process leading to success. Therefore, it can reveal the importance of cognitive and affective characteristics of athletes as well as their physical competencies. For this reason, in the present study, when forgiveness comes into play, the relationship between athletes' cognitive flexibility and decision-making and their happiness was tested with structural equation modeling. It was determined that the SEM results were statistically significant and satisfactory and the models constructed in the theoretical framework were confirmed by the data obtained from the athletes. Within the scope of the study, the relevant assumptions were tested and analyzed before the mediation relationship and it was determined that there were significant relationships between decision making, cognitive flexibility, forgiveness and happiness. Depending on these relationships, two different SEM models, Model-1 and Model-2, were constructed. In Model-1, it was tested whether forgiveness has a mediating role in the relationship between decision making and happiness of athletes and according to the results, it was determined that forgiveness is a full mediator. Again, in Model-2, which was constructed to determine whether forgiveness has a mediating role in the relationship between athletes' cognitive flexibility and their happiness, it was found that forgiveness is a partial mediator. According to the results of the research, it was determined that there is a significant and positive relationship between happiness and decision making. When the literature is examined, Dilmaç and Bozgeyikli [ 26 ] concluded that there is a significant relationship between subjective well-being and decision-making styles of prospective teachers. In another study, Bubic and Erceg [ 29 ] found that there was a significant positive relationship between students' decision-making styles and subjective well-being. Another result obtained is that there is a significant and positive relationship between happiness and forgiveness. In the related literature, Yasar [ 73 ] found that subjective well-being is positively related to psychological resilience and forgiveness. Eke [ 74 ] concluded that there is a significant positive relationship between adults' forgiveness scores and their subjective well-being. A significant and positive relationship was also found between decision-making and forgiveness, which is another important finding. Looking at similar studies, Demirtas [ 75 ] concluded that there are significant positive relationships between psychological resilience, forgiveness and cognitive control variables. According to this result, it was interpreted that people with psychological resilience have the ability to control and manage their negative emotions and thoughts and create alternative coping strategies, and thanks to these features, they are more forgiving. Another important result of the study is the significant and positive relationship between happiness and cognitive flexibility. When the literature is examined, Balta [ 76 ] found a significant positive relationship between cognitive flexibility and happiness scores of adult individuals. In a similar study, Sagar [ 77 ] concluded that cognitive flexibility significantly predicted subjective well-being at school. One of the findings of the study is the significant and positive relationship between cognitive flexibility and forgiveness. In his study, Kara [ 78 ] found that there was a significant negative relationship between the recognition sub-dimension of forgiveness flexibility and cognitive flexibility, and a significant positive relationship between the internalization and implementation sub-dimensions and cognitive flexibility. In another study, Akın [ 79 ] found a significant relationship between cognitive flexibility and forgiveness. One of the important results in the study is that forgiveness, which is included in the process in the relationship between decision-making and happiness in Model-1, reduces the level of the relationship and loses its significance, as a result, forgiveness assumes a full mediating role. In this context, decision-making behaviors and happiness of athletes are affected by their forgiveness levels. For this reason, it can be said that as the forgiveness levels of athletes increase, their happiness levels due to decision-making will change. Since forgiving athletes in order to be more successful will increase their happiness levels, it is important to organize non-athlete factors such as coaches within this framework. In Model-2, which we can express as another important factor for the current research, the forgiveness factor included in the process in the relationship between athletes' cognitive flexibility and their happiness affects the degree of the relationship and reveals forgiveness as a partial mediating variable. In other words, the relationship between athletes' cognitive flexibility and their happiness decreased when forgiveness was included in the process and forgiveness assumed a partial mediating role. In addition to the belief that the study will contribute to the field, it may be suggested to the researchers to look at the mediating relationships of athletes in future studies in terms of athletes competing in team sports or individual sports. In addition, examining the distinction of athletes in the categories of contact sports or non-contact sports will also help to increase the contribution of the study to the field. In the current study, convenience sampling was used as a sampling technique, and in order for this technique not to cause problems in terms of generalizability to the population, a sufficient number of athletes (n = 618) were reached. In this context, studies that can be created similar to the current study can also be created using simple random sampling technique. The study can be expanded by analyzing more cognitive factors for the success of athletes and contribute to the field. Trying to contribute to the analysis of the failure factors of athletes who do very good physical training but cannot take a place on the rostrum has revealed the importance of the research. Declarations Authors’ contributions Research Design MK, NŞK; Statistical analysis MK; Preparation of the article, MK, NŞK; Data Collection was carried out by MK, NŞK. Funding The study has no external fundings. Availability of data and materials The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate All procedures performed in this study involving human participants were in accordance with the ethical standards of the Department of Psychology, the University of Hong Kong, and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Mersin University Social and Human Sciences Ethics Committee. Informed consent form was obtained from all participating in the study. Consent for publication Not Applicable. Competing interests The authors declare no competing interests. References Sheldon KM, Lyubomirsky S. Achieving sustainable new happiness: Prospects, practices, and prescriptions. Positive Psychology in Practice, 2004; 127-145. Crossley A, Langdridge D. Perceived sources of happiness: A network analysis. 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Structural Equation Modeling: A Multidisciplinary Journal, 1999; 6(1), 1-55. Hooper C, Killick R, Lovestone S. The GSK3 hypothesis of alzheimer’s disease. Journal of Neurochemistry, 2008; 104(6), 1433-1439. Kline RB. Principles and practice of structural equation modeling (4th Edn.). London: The Guilford Press, 2016. Baron RM, Kenny DA. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 1986; 51(6), 1173. Gurbuz S, Sahin F. Research methods in social sciences. Ankara: Seckin Press, 2018. Yasar K. The relationship between the subjective well-being levels of education faculty students and their psychological resilience and forgiveness levels (PhD Thesis), Bursa Uludag University, Institute of Educational Sciences, Bursa, 2015. Eke A. The effect of family environment perception and forgiveness characteristics on subjective well-being in emerging adults (Published Master's Thesis). Maltepe University, Institute of Social Sciences, Istanbul. 2018. Demirtas AS. Resilience and forgiveness in emerging adulthood: Parallel multiple mediation of cognitive control/resilience. OPUS International Journal of Society Researches, 2021; 17(35), 1968-1989. Balta SN. Investigation of the effects of cognitive flexibility levels of young adults on death anxiety levels and happiness levels (Published Master's Thesis). Istanbul Gelisim University, Institute of Social Sciences. Istanbul, 2020. Sagar ME. Predictors of subjective well-being at school in adolescents: Emotion regulation, coping and cognitive flexibility. Aegean Education Journal, 2022; 23(2), 133-149. Kara NS. Examination of the meaning of life, forgiveness flexibility, cognitive flexibility and psychological symptoms in terms of various variables in individuals who do and do not do sports. Sakarya University of Applied Sciences, Graduate School of Education, Sakarya, 2020. Akın G. Examining the relationship between cognitive flexibility, forgiveness and perfectionism in adolescents (Published Master's Thesis). Istanbul Sabahattin Zaim University, Institute of Educational Sciences, Istanbul, 2021. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4369738","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":320335898,"identity":"9b80c350-664d-4b84-8c8b-2c6f1ffca8ba","order_by":0,"name":"Mehmet KARA","email":"","orcid":"","institution":"Mersin University","correspondingAuthor":false,"prefix":"","firstName":"Mehmet","middleName":"","lastName":"KARA","suffix":""},{"id":320335899,"identity":"c580b4ff-2179-4155-b4ed-775b72741000","order_by":1,"name":"Nuriye Şeyma 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happiness in athletes.\u003c/p\u003e\n\u003cp\u003eHypothesis 3: There is a significant positive relationship between forgiveness and happiness in athletes.\u003c/p\u003e\n\u003cp\u003eHypothesis 4: When forgiveness is activated in athletes, the relationship between decision making and happiness decreases.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4369738/v2/a88b413a9d70e01e473c909a.png"},{"id":81062401,"identity":"ce6cd5a7-db96-4e0d-a7b6-bf665ad83e0d","added_by":"auto","created_at":"2025-04-21 19:38:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":56201,"visible":true,"origin":"","legend":"\u003cp\u003eHypothesis 5: There is a significant positive relationship between cognitive flexibility and happiness in athletes.\u003c/p\u003e\n\u003cp\u003eHypothesis 6: There is a significant positive relationship between cognitive flexibility and forgiveness in athletes.\u003c/p\u003e\n\u003cp\u003eHypothesis 7: When forgiveness is activated in athletes, the relationship between cognitive flexibility and happiness decreases.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4369738/v2/0036f977f9e49f85c3c20e31.png"},{"id":81062399,"identity":"5a764845-2d59-4d34-99a1-39130e718b57","added_by":"auto","created_at":"2025-04-21 19:38:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26202,"visible":true,"origin":"","legend":"\u003cp\u003ea. standard \u0026nbsp;\u0026nbsp;path coefficients for the binary model\u003c/p\u003e\n\u003cp\u003eb. t-values \u0026nbsp;\u0026nbsp;for the binary model\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4369738/v2/bdc6a74b3902c0ca6375e209.png"},{"id":81062402,"identity":"c6282842-356a-4442-808e-ece8e298b93a","added_by":"auto","created_at":"2025-04-21 19:38:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":40195,"visible":true,"origin":"","legend":"\u003cp\u003ea. standard path \u0026nbsp;\u0026nbsp;coefficients for the triplet model\u003c/p\u003e\n\u003cp\u003eb. t-values \u0026nbsp;\u0026nbsp;for the triplet model\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4369738/v2/fab59e39d3808cfe9b29aad2.png"},{"id":81062527,"identity":"11121e14-5252-4f58-810d-9e1884666ce5","added_by":"auto","created_at":"2025-04-21 19:46:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":25948,"visible":true,"origin":"","legend":"\u003cp\u003ea. standard \u0026nbsp;\u0026nbsp;path coefficients for the binary model\u003c/p\u003e\n\u003cp\u003eb. t-values \u0026nbsp;\u0026nbsp;for the binary model\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4369738/v2/c2b7f0333d99cee38750d237.png"},{"id":81062403,"identity":"86b085d5-8795-4717-8b5a-c6aa667de66b","added_by":"auto","created_at":"2025-04-21 19:38:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":43009,"visible":true,"origin":"","legend":"\u003cp\u003ea. standard \u0026nbsp;\u0026nbsp;path coefficients for the triplet model\u003c/p\u003e\n\u003cp\u003eb. t-values \u0026nbsp;\u0026nbsp;for the Tripartite Model\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4369738/v2/59c3d2fe5e9c7a9c053f79ca.png"},{"id":81991336,"identity":"cafd97e6-7982-42f0-83bb-4191f358dd53","added_by":"auto","created_at":"2025-05-05 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Introduction","content":"\u003cdiv class=\"Heading\"\u003eBeing happy, which is one of the situations we aim for in our lives, is a situation that everyone can desire. Happiness, one of the interests of positive psychology, is not only a component of an individual\u0026apos;s mental health [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e], but also a positive emotional state that contributes to the individual\u0026apos;s interpretation of life [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e], meaning it provides benefits in more than one dimension [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e]. Being in a happy state is a situation that can affect the sports life as well as the healthy fulfillment of daily activities. Happiness is defined as the psychological state of health, joy and peace [\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e]. Seligman [\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e] stated that being happy consists of three dimensions: positive emotion, commitment to life and meaning of life. Positive emotion is based on having positive emotions about the past, present and future, and learning the skills necessary to increase the intensity of these emotions. In the dimension of being connected to life, the individual is expected to do activities that he enjoys in his business life, interpersonal relationships or in his spare time. Finally, in the dimension of the meaning of life, it requires the individual to use his talents and strengths for the benefit of society. In summary, the concept of happiness is based on the ability to control negative emotions and turn them into positive ones. In order for an individual to be happy, he must control his attitudes and reactions to the events he encounters. Therefore, this aspect of happiness is associated with the concept of forgiveness.\u003c/div\u003e\n\u003cp\u003eThe more an individual\u0026apos;s sense of forgiveness is developed, the more his/her positive approach to life can increase his/her level of happiness. In a way, forgiveness is a concept that contains negative emotions. Edwards [\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e] stated that forgiveness begins in pain, anger, insecurity and confusion and sprouts in hatred. In other words, at its core is the ability to control these negative emotions and to look at the glass half full. In this respect, the concept of forgiveness is very important in terms of social relations and health. Fitzgibbons, Enright, and Brien [\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e] defined forgiveness as an affective, intellectual and moral reaction to unjust behavior by people. In this respect, it is possible to say that the concept of forgiveness opens a door to happiness. As a matter of fact, being able to control negative emotions in order to establish healthy relationships can positively strengthen our human relationships. In this context, this positive emotional state that emerges in our human relationships can increase the happiness level of individuals. Worthington [\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e], in his pyramid model of forgiveness, suggested that individuals\u0026apos; ability to forgive others in mutual relationships may be related to their level of happiness and well-being. Maltby, Day, and Barber [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e] concluded that there is a significant positive relationship between happiness and forgiveness. In another study, Chan [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e] found that there is a significant positive relationship between forgiveness and happiness. Forgiveness is not only a term that includes emotional processes, but also a concept that has cognitive processes [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. Karremans, Van Lange, Ouwerkerk and Kluwer [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e] found that happiness and the concept of forgiveness were positively related in their study. Again, Kaya ve Or\u0026ccedil;an [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e] found that happiness has a mediating role between empathy, life satisfaction and forgiveness. In another study, Adam-Karduz and Sarıcam [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e] found that there were significant relationships between forgiveness and happiness. Forgiveness and happiness are concepts that athletes encounter a lot in the sports environment. Because people who participate in sporting activities can feel better psychologically and physically, get away from stress and worries, improve their human relations, and feel happy by increasing their motivation [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. This emotional state obtained in the sports environment can sometimes be experienced intensely by people who play sports professionally or as amateurs. Because athletes who constantly participate in competitions or competitions may be happy or unhappy at the end of the match. This situation may also affect their level of forgiveness. In addition, this situation can positively or negatively affect the performance of athletes in the next competition. As a matter of fact, sport can be expressed as a whole that includes various concepts such as competition, purpose, effort and excitement. The fact that athletes feel these emotions intensely can be quite decisive in their attitude towards the opponent and their performance.\u003c/p\u003e\n\u003cp\u003eIn order for athletes to be happy in the situations they face, it may be a result of their cognitive flexibility that they sometimes exhibit different behaviors than they are accustomed to and turn to the more appropriate option among the options they can choose. For this reason, it can be expressed as an expected product that people with high cognitive flexibility are happier as a result of their correct choices. Because people with high cognitive flexibility, which is expressed as the ability to quickly move from one situation to another [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e], can easily change their minds in sudden situations [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]. Cognitive flexibility, defined by Kara, Kara, and \u0026Ccedil;etin [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e] as the way of thinking towards the task that the individual has, can be a stepping stone to happiness. Therefore, it can be stated that the decisions made by an athlete with high cognitive flexibility in order to be happy may be more appropriate. As a matter of fact, Asıcı and Ikiz [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e] found that there are significant and positive relationships between cognitive flexibility and happiness levels of individuals in their study. In addition, Yıldız [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e] found that cognitive flexibility has a moderate and significant relationship with subjective well-being and that the predictor variables explain 60% of the total variance in subjective well-being. In another study, Satan [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e] concluded that cognitive flexibility significantly predicted subjective well-being. Demirtaş [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e] concluded that cognitive flexibility is positively related to happiness and cognitive flexibility predicts happiness. Similarly, Asıcı and Sarı [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e] found that cognitive flexibility directly predicts happiness.\u003c/p\u003e\n\u003cp\u003eAlthough being happy is a state of emotion, it is one\u0026apos;s choices that drive happiness. When making choices, athletes also make a judgment among different situations. Decision making is a way of minimizing doubts and uncertainties [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e] by voluntarily choosing one of the possible options [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. Dilma\u0026ccedil; and Bozgeyikli [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e] found a significant relationship between subjective well-being and decision-making styles in their study. In another similar study, Tekkurşun-Demir, Namlı, Hazar, Turkeli, and Cicioglu [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e] found a significant relationship between decision-making styles and mental well-being. Yıldız and Eldekioglu [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e] concluded in their study that decision-making styles were significantly predicted in terms of happiness variable. Bubic and Erceg [\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e] found that the tendency to maximize during decision making is positively correlated with all three orientations towards happiness.\u003c/p\u003e\n\u003cp\u003eWithin the scope of this study, it was aimed to examine the effect of forgiveness on the process in the relationship between athletes\u0026apos; decision-making behaviors and happiness levels as well as the effect of forgiveness on the process in the relationship between athletes\u0026apos; cognitive flexibility and happiness levels. When the related studies were examined, the motivation of the study was that there was no study investigating whether the forgiveness variable included in the process had a mediating effect in the relationship between decision-making and cognitive flexibility of athletes and their happiness. Considering the studies, there is no modeling study that focuses on the relationships of these variables, which have a dominant role in sportive activities, within triple combinations. It is also considered important to model these relationships between variables and to visualize and address these models in the context of structural equation modeling (SEM). The motivation for examining the study with structural equation modeling is to examine the terms whose possible relationships are presented and whose conceptual relationships are discussed. The theoretical presentation of the causality relations of the models created reveals the importance of the examination. Before moving on to the models to be investigated within the scope of the study, the dependent, independent and mediating variables that are the subject of the research will be explained in the conceptual framework and the models predicted by the literature will be tested in this direction.\u003c/p\u003e\n\u003cp\u003eThe aim of this study is to determine how the relationship between decision making, cognitive flexibility and happiness changes when forgiveness is included in the process. The belief that these factors will contribute to the success of athletes reveals the importance of the study.\u003c/p\u003e\n\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\n \u003ch2\u003e1.1. Happiness and Sport\u003c/h2\u003e\n \u003cp\u003eThe concept of happiness, which is a part of our human emotions, can be shown as one of the determining factors in terms of the level of human life quality. Happiness corresponds to the evaluation of the level of quality of life of the individual in relation to his/her whole life [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. Happiness is expressed as a cognitive and affective evaluation of life. Accordingly, an individual\u0026apos;s frequent experience of positive emotions such as joy, pride, confidence and excitement; less frequent experience of negative emotions such as anger, fear, anxiety and hatred; and high satisfaction with family, work, career and similar areas of life can be explained as indicators of happiness [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. In a sense, it can be inferred that feeling positive emotions frequently increases our daily life quality. Myers and Diener [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e] defined happiness as the quantity and superiority of positive feelings about one\u0026apos;s life.\u003c/p\u003e\n \u003cp\u003eSeligman [\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e] stated that happiness consists of three dimensions: positive emotion, connectedness to life and meaning of life. Positive emotion refers to having positive emotions about the past, present and future and learning the necessary skills to increase the intensity of these emotions; being connected to life refers to doing and enjoying activities that the individual enjoys in his/her work life, social relationships or leisure time; and living a meaningful life refers to the ability to use one\u0026apos;s talents and strengths to serve the society. In this context, it is possible to associate the concept of happiness with sports. Because sport is a concept that allows the discharge of negative emotions and it contains concepts such as success, purpose, winning and perseverance. Therefore, it is possible to say that the gains obtained in these concepts can bring happiness. As a matter of fact, human beings live for a purpose and make an effort to fulfill this purpose. Likewise, the concept of sport, which contains many goals, is related to happiness in this respect. Regarding this issue, according to Farabi, happiness is a goal that every human being desires, it is preferred and desired for the human being himself at any time [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. The effort of athletes to be successful can be seen as an important component of happiness in sports.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e1.2. Forgiveness and Sport\u003c/h2\u003e\n \u003cp\u003eHuman beings have a structure that contains many emotions by nature. In this context, it can be said that the thinking power of human beings, who are thinking beings, is affected by a wide variety of emotional functions. These functions can be classified as positive and negative emotions. Therefore, the ability to control these emotions in the right way is an important factor in maintaining a healthy life. Because the emotional control required by social life affects our interpersonal relationships. As a matter of fact, people encounter many negative situations or events while interacting with their environment. In the face of this situation, the individual who is not forgiving towards his/her environment may isolate himself/herself from the society. The concept of forgiveness is seen as an interpersonal process to maintain and improve the quality of human relationships [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]. It is important to internalize the concept that affects our relationship with our environment so much.\u003c/p\u003e\n \u003cp\u003eForgiveness is a concept that allows a person to remove negative emotions from his/her life and transform them into an objective or positive emotion [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. This concept, which is based on the removal of negative emotions, is related to the fact that sport is a concept that allows the discharge of negative emotions. Interaction in the sports environment provides the discharge and control of emotions. Individuals participating in sportive activities have the opportunity to express their emotions through movements. This enables the discharge and control of negative emotions such as anger, aggression, shyness, jealousy [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]. The fact that forgiveness sprouts as a result of negative emotions [\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e] means that it emerges as a result of the removal of these emotions. Therefore, the concept of forgiveness is seen to be related to sports since the opportunity to get away from negative emotions in a sports environment can enable an individual full of anger to discharge his/her emotions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e1.3. Cognitive Flexibility and Sport\u003c/h2\u003e\n \u003cp\u003eThe situations we face in daily life push us to think alternatively among different options. The choices we make as a result of thinking determine the course of our lives. Therefore, having the cognitive abilities to make the right choices is important for the positive progress of our lives. At this point, it is possible to talk about the concept of cognitive flexibility. Cognitive flexibility is defined as the ability to assimilate that it is correct not to see the right options in the face of a problem, but to be able to see the options before making a choice [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]. In other words, cognitive flexibility is a form of fluid intelligence determined by the ability to bring alternative solutions to different situations [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. In other words, it can be said to be able to adapt our cognitive processes according to the situations we encounter. In this sense, the concept of sport can be mentioned to support cognitive control. Because the concept of cognitive flexibility, which is at the basis of executive functions, is known to provide conscious control of actions, thoughts and emotions [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]. Considering the areas where sports interact with the brain, it is possible that our cognitive control is supported by sports. From a neurological point of view, it is known that the release of serotonin and dopamine, neurotransmitters that affect the decision-making mechanism in the brain increases with sports. In this context, these oscillations, which increase with sports, are important in terms of predicting which decision may be correct. Therefore, it can be said that there is a relationship between sports and cognitive flexibility.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e1.4. Decision making and Sport\u003c/h2\u003e\n \u003cp\u003eThe choices we face in our lives often lead us to choose one of these choices. In doing so, it is necessary to make a decision about which choice is the right one and to think about every aspect. Because we can be happy or sad as a result of the decisions we make. Decision making can be expressed as making the most appropriate choice by eliminating doubts and uncertainties in the light of the information obtained by individuals in the face of certain situations [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]. In other words, decision making is knowing what to do in a given or emerging situation [\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e]. Akpınar, Temel, Birol, Akpınar, and Nas [\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e] explained decision making as a behavior taken to eliminate the difficulty experienced when there are at least two or more options that will lead to an object, person or situation that is thought to satisfy the need. In this respect, the phenomenon of decision-making is also present in sports, which contains difficulties. Because the decisions made by referees, coaches or athletes in sports are decisive in being successful. In the sports environment where we often have to exhibit decision-making behavior, athletes are obliged to think in many ways and choose the most appropriate option. The decision to apply the wrong technique in a challenge can result in failure. In this respect, it is extra important for athletes to think in multiple ways to make the right decision. In addition, the changes that occur in the brain during sports can improve decision-making.\u003c/p\u003e\n \u003cp\u003eFrom a neurological perspective, the dorsolateralalprefrontal cortex and ventromedialprefrontal cortex regions, which are the regions responsible for decision-making behavior in our brain, help in thought processes and making choices among various alternatives. In addition, brain imaging systems have concluded that these regions play an active role during activities such as short-term memory, cognitive flexibility and decision-making behavior in the light of various contexts [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]. When the effects of exercise on the nervous system are examined, it has been found that it improves synaptic structures in the brain, especially in regions related to cognitive functions such as the anterior hippocampus and prefrontal lobe, and accelerates neurogenesis, angioe-nesis, and cerebral blood flow [\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e]. Therefore, developments in these regions, which are responsible for the decision-making mechanism in the brain with sports and exercise, are important in terms of making the right decisions. In this context, it can be said that there is a relationship between decision-making and sports.\u003c/p\u003e\n \u003cp\u003eThe theoretical models planned based on the existence of the relationships between the variables above are visualized below in accordance with the purpose of the research. The theoretical models created for the concepts explained are presented in Fig. 1 and Fig. 2 and the hypotheses written for these models are indicated below the figures.\u003c/p\u003e\n \u003cp\u003eWithin the framework of the hypotheses covering Figure.1 and Figure.2, the main problem statement can be expressed as \u0026quot;What is the mediating role of forgiveness in the relationship between cognitive flexibility, decision making and happiness in athletes?\u0026quot;.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"2. Method","content":"\u003cp\u003e\u003cstrong\u003e2.1. Research Model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was designed within the scope of relational survey models in which possible theoretical causal relationships between athletes\u0026apos; cognitive flexibility, decision making, happiness and forgiveness were examined. Researchers do not intervene in the relationships in relational survey models. The researcher, who can provide clues in relational research, does not look for a relationship related to causes and effects [45].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Study Group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study group of the research consists of 623 athletes who are 18 years of age or older and actively engaged in licensed sports as of 2023. As a result of the assumption tests of the Structural Equation Model, which is a multivariate analysis type, it was concluded that the remaining 618 observations were of sufficient size considering the minimum number of observations to be reached [46].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Data Collection Tools\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eForgiveness Decision Scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Decision to Forgive Scale, adapted to Turkish culture by Ekşi, Parlak, and Demir Celayir [47], consists of 6 items and a single dimension. The scale, which does not have reverse items, is a 5-point Likert-type scale ranging from Strongly Disagree (1) to Strongly Agree (5). A high score indicates a person\u0026apos;s high decision to forgive. For the adaptation study of the Forgiveness Decision Scale to Turkish Culture, 297 pre-service teachers over the age of 18 participated. The Cronbach\u0026apos;s alpha reliability coefficient calculated to obtain the reliability evidence of the scale was 0.91, and this value revealed that the scale is a highly reliable measurement tool. In addition, the item-total correlations of the items were examined to obtain evidence of the construct validity of the scale and it was found that these values ranged between 0.59 and 0.84. The correlation coefficients were also found to be statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCognitive Flexibility Scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Cognitive Flexibility Scale developed by Bilgin [48] consists of 19 items. The scale items consist of pairs of adjectives (e.g. I can, I cannot, - I am successful, I am unsuccessful). The lowest score that can be obtained from the scale is 21 points and the highest score is 105 points. Reliability and validity were tested using a sample of 637 adolescents. The higher the scores obtained from the scale, the closer the individual is to cognitive flexibility. In the reliability study conducted on the scale, the Cronbach\u0026apos;s alpha coefficient for the whole scale was found to be 0.92. The item-total correlations of the items ranged between 0.49 and 0.63. The test-retest correlation coefficient was 0.77 and the halving coefficient was 0.87 over an eight-week interval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNatural Decision Making Scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDeveloped by Sundu and Yaşar, [49] the Natural Decision Making Scale consists of 6 items and one dimension. The Cronbach\u0026apos;s Alpha coefficient calculated for the whole scale is 0.80. There are no reverse coded items in the scale, which has a 5-point Likert structure ranging from Strongly Agree to Disagree. Natural decision making, which is the subject of the research, was preferred in the scale created with 554 participants over the age of eighteen who are working in different professions, since it is seen as the process of focusing on and choosing the most appropriate one among various options. In addition, the factor loadings of the Natural Decision Making scale items ranged from 0.68 to 0.87 and all of them were statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHappiness Scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Happiness Scale developed by Demirci and Eksi [50] has a unidimensional structure consisting of 6 items. The scale, which does not contain any reverse-coded items, has a 5-point Likert structure (1: Not at All Suitable for Me, 5: Completely Suitable for Me). Cronbach Alpha internal consistency coefficient of the scale was calculated as 0.83. The Happiness Scale, which was created to investigate the characteristics of a peaceful and happy life, was conducted with 900 participants over the age of 18. In addition, the test-retest reliability coefficient obtained from the reapplication of the scale to 62 participants at three-week intervals was calculated as 0.73. The factor loadings of the items in the scale ranged between 0.59 and 0.78.\u003c/p\u003e\n\u003cp\u003eConfirmatory factor analysis (CFA) was conducted to reveal the psychometric qualities of the data collection tools used in this study. The aim of CFA is to discover the factor or factors based on the relationships between variables by revealing the sources of variance and covariance [51]. In order to obtain evidence for the reliability and convergent validity of the scales used in the study, AVE values were calculated and presented in Table 1. According to the research findings, the values calculated for CR, which is the evidence of construct relability, should be above 0.50 [52], the average variance extracted for convergent validity, i.e. AVE, should be in the range of CR\u0026ge;AVE\u0026ge;0.50 [53], but in cases where AVE values are less than 0.5, the CR\u0026ge;0.7 criterion can be accepted for convergent validity. Since all scales included in the analysis were unidimensional, divergent validity evidence such as maximum shared squared (MSV) and average mean square of shared variance (ASV) were not examined.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eReliability and Validity Findings of The Scales Used\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.153846153846153%\"\u003e\n \u003cp\u003eScales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003eCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.846153846153847%\"\u003e\n \u003cp\u003eAVE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003eCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.76923076923077%\"\u003e\n \u003cp\u003eConvergent\u003c/p\u003e\n \u003cp\u003eValidity\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.153846153846153%\"\u003e\n \u003cp\u003eHappiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.846153846153847%\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.76923076923077%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.153846153846153%\"\u003e\n \u003cp\u003eCognitive Flexibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.846153846153847%\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.76923076923077%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.153846153846153%\"\u003e\n \u003cp\u003eNatural Decision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.846153846153847%\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.76923076923077%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.153846153846153%\"\u003e\n \u003cp\u003eForgiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.846153846153847%\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.76923076923077%\"\u003e\n \u003cp\u003e✓\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.153846153846153%\"\u003e\n \u003cp\u003eCriteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e\u0026ge;.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e\u0026ge;.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.846153846153847%\"\u003e\n \u003cp\u003e\u0026ge;.70\u0026gt;CR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e\u0026ge;.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.307692307692308%\"\u003e\n \u003cp\u003e\u0026ge;.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.76923076923077%\"\u003e\n \u003cp\u003eAVE\u0026lt;CR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen the results of Table.1 are taken into consideration, it is concluded that all measurement tools used within the scope of the research provide reliable and valid measurements. It can be said that the AVE value obtained in Table 1 is low but acceptable. This is because Fornell and Larcker [53] emphasized that in cases where the CR value is higher than 0.60, AVE less than 0.50 is acceptable and construct validity is sufficient [54].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4. Collection of Data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe necessary ethical permission was obtained from the relevant committees before the study. Ethics committee approval was obtained from Mersin University. Voluntary participants were informed that the information received would only be used within the scope of the current study and would remain confidential. Scale forms including demographic information were applied to the participant athletes online for approximately 15 minutes and data were collected. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5. Data Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted with structural equation modeling (SEM) in order to reveal the mediating relationships of forgiveness in the relationship between cognitive flexibility, decision making and happiness in active licensed athletes. SEM, which is a statistical method that predicts the causal relationships that observed and latent variables may have, puts forward a theoretical framework [55, 56, 57]. The main purpose of SEM is to reveal the relationship patterns of the data obtained as well as the latent variables [58]. SEM, which is widely used to test observed and latent variables and is based on a theoretical foundation [59, 60], is a method that tests and estimates multivariate models in fields such as economics, medicine and psychology [61, 62], and differs from traditional methods by taking into account the measurement errors of the latent variable [63, 16].\u003c/p\u003e\n\u003cp\u003eBefore performing SEM, which is a multivariate statistical technique, assumptions were examined. Within the scope of the assumptions, since the data were collected online, no missing or missing data were found. Then, single and multiple outliers were examined. In this context, the standardized Z values for single outliers ranged between (-3.54, 1.58), and the 445th observation with a value of -4.37 was excluded from the analysis because it produced a single outlier. In this context, since all observations were within the limits of 4 \u0026ge; z \u0026ge; 4 [51], the analysis continued without any single outlier. As a result of the degrees of freedom comparison [64] for the remaining 621 observations, 3 observations (163rd, 390th and 546th) that produced values above the values of Mahalonobis distances (\u0026chi;23, 0.001=16.27) were excluded from the analysis and the analyses continued with the remaining 618 observations. The hypothesis analyses continued with testing the multicollinearity problem and Variance Inflation Factor (VIF) and Tolerance values were analyzed. In this context, the tolerance values ranged between (0.922, 0.974) and all values were above 0.20; the VIF values ranged between (1.027, 1.084) and all observation values were below 5, indicating that there was no multicollinearity problem among the items [51]. The Durbin-Watson value, which is an additional test for multicollinearity, was obtained as 1.93, and the fact that this value is close to 2 [65] is an indication that the errors are not related to each other.\u003c/p\u003e\n\u003cp\u003eTesting the measurement model is one of the basic assumptions of SEM analyses. Table.2 presents the goodness of fit and poorness of fit values of the measurement model including all the variables within the scope of the study and the criterion criteria against which these values will be compared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eMeasurement Model Results\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"590\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.966101694915253%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.745762711864407%\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.423728813559322%\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003eNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003eNNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.966101694915253%\"\u003e\n \u003cp\u003eCFA Measurement Model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.745762711864407%\"\u003e\n \u003cp\u003e2555/623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.423728813559322%\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.966101694915253%\"\u003e\n \u003cp\u003ePerfect fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.745762711864407%\"\u003e\n \u003cp\u003e\u0026le; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.423728813559322%\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.966101694915253%\"\u003e\n \u003cp\u003eGood fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.745762711864407%\"\u003e\n \u003cp\u003e3\u0026le; x\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd \u0026le; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.423728813559322%\"\u003e\n \u003cp\u003e.05\u0026le;RMSEA\u0026le;.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003e.05 \u0026le; SRMR \u0026le;.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e.90\u0026le;CFI \u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eConsidering the goodness of fit statistics found in Table 2 and the literature criteria, it is observed that the tested measurement models match with excellent and good fit criteria. The testing of measurement models is an important assumption of SEM analysis [66], and the model-data fit evaluation is evaluated in Table 2 by considering excellent and acceptable fit values [67, 68, 69, 70]. \u0026nbsp;It is recommended to report RMSEA, x\u003csup\u003e2\u0026nbsp;\u003c/sup\u003edegrees of freedom and significance values, SRMR and CFI values as a minimum in studies based on CFA [70]. The measurement model tested with the dependent, independent and mediator variables in the study matches with excellent fit and good fit indicators.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, which was conducted on the basis of SEM by taking into account the mediation model of Baron and Kenny [71], the status of the relationships between the dependent, independent and mediator variables is taken into account in mediation decisions. In the first stage, the relationship between the dependent and independent variable is tested. This relationship should be significant. In the next stage, the fact that the mediating variable added to the model causes the relationship between the independent and dependent variable to be lost reveals that the mediating variable is full mediation, while only a decrease in the relationship between the independent and dependent variable or a slight decrease in the level of the standardized value reveals that it is partial mediation [72].\u003c/p\u003e\n\u003cp\u003eBefore proceeding with the decision analyses regarding mediation studies, all of the binary relationships between the variables to be considered within the scope of the model must be significant. In this context, the analyses of the binary relationships between the dependent, independent and mediator variables hypothesized for Model-1 and Model-2 are evaluated based on the measurement model outputs and presented in Table 3 and Table 4.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eCorrelations Between Study Variables\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"454\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.72185430463576%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003eHappiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003eDecision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.72185430463576%\"\u003e\n \u003cp\u003eHappiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.72185430463576%\"\u003e\n \u003cp\u003eDecision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e.11\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.72185430463576%\"\u003e\n \u003cp\u003eForgiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e.23\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e.30\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003e** p \u0026lt; .01\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eCorrelations Between Study Variables\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.72185430463576%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003eHappiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003eCognitive Flexibility\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.72185430463576%\"\u003e\n \u003cp\u003eHappiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.72185430463576%\"\u003e\n \u003cp\u003eCognitiveFlexibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e.54\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.72185430463576%\"\u003e\n \u003cp\u003eForgiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e.23\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\"\u003e\n \u003cp\u003e.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003e** p \u0026lt; .01\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTherefore, within the scope of mediation, hypotheses 1,2,3,4,5,6,7 of the theoretical models in Figure 1 and Figure 2 were confirmed and the prerequisites for the mediation study were provided.\u003c/p\u003e"},{"header":"3. Findings","content":"\u003cp\u003eIn this section, mediation analyses were carried out in stages on the two models whose theoretical frameworks were drawn. In the first stage, the direct relationship between the dependent and independent variables and the t values revealing the significance of this relationship, and in the second part; the magnitude (status) of the relationship between the independent variable and the dependent variable obtained by adding the mediating variable to the models and the t values calculated for this relationship are included. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1. Model-1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the mediation test conducted for model-1, which investigates whether forgiveness is a mediating variable in the relationship between decision making and happiness, are presented. Figures 3.a and 3.b show the standardized loadings and t values of the structural model between decision making, which is the independent variable in the research, and happiness, which is the dependent variable of the research.\u003c/p\u003e\n\u003cp\u003eFigure 3.b reveals that there is a significant positive relationship between decision making and happiness levels of athletes (t=2.09; p\u0026lt;.01). Figure 3.a also shows that there is a theoretically weak causal relationship between athletes\u0026apos; decision making and their happiness levels (\u0026beta;=0.11; p\u0026lt;.01). Decision-making of athletes predicts their happiness levels by 0.01% (R2). The model data goodness of fit results obtained for this model are summarized in Table 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eModel Fit Values for The Relationship Between Decision Making and Happiness\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"590\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.6383701188455%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.544991511035654%\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.959252971137522%\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.959252971137522%\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\"\u003e\n \u003cp\u003eNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.091680814940577%\"\u003e\n \u003cp\u003eNNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.6383701188455%\"\u003e\n \u003cp\u003eCFA Measurement Model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.544991511035654%\"\u003e\n \u003cp\u003e186/53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.959252971137522%\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.959252971137522%\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.091680814940577%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.6383701188455%\"\u003e\n \u003cp\u003ePerfect fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.544991511035654%\"\u003e\n \u003cp\u003e\u0026le; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.959252971137522%\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.959252971137522%\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.091680814940577%\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.6383701188455%\"\u003e\n \u003cp\u003eGood fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.544991511035654%\"\u003e\n \u003cp\u003e3\u0026le; x\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd \u0026le; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.959252971137522%\"\u003e\n \u003cp\u003e.05\u0026le;RMSEA \u0026le;.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.959252971137522%\"\u003e\n \u003cp\u003e.05 \u0026le; SRMR \u0026le; .10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\"\u003e\n \u003cp\u003e.90\u0026le;CFI \u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.091680814940577%\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eWhen the goodness of fit criteria in Table 5 are examined, it is concluded that the values of the model between the independent variable decision-making and the dependent variable happiness comply with the criteria of excellent and good fit. In the next stage of the mediation model, the mediator variable \u0026quot;forgiveness\u0026quot; was added to the model and figures 4.a and 4.b were obtained.\u003c/p\u003e\n\u003cp\u003eIn the model in which athletes\u0026apos; forgiveness levels assumed the mediating role, it was found that the relationship between decision making and happiness became insignificant (\u0026beta;=0.04 p\u0026gt;.01). On the other hand, the relationship between the independent variable decision-making and the mediating variable forgiveness was found to be positively significant (t=6.00; p\u0026lt;.01) and decision-making explained 9% (R2) of the change in forgiveness. \u0026nbsp; The t-value findings of the relationships between variables are presented in Figure 4.b. Baron and Kenny [71] emphasized that there may be a mediation relationship if the relationship between the dependent variable and the independent variable decreases or disappears completely when the mediator variable is activated. Considering the significance levels of the relationships in the model, it can be said that forgiveness plays a full mediating role in the relationship between decision making and happiness. Table 6 presents the goodness of fit values for the mediation modeling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u0026nbsp;\u003c/strong\u003eModel Fit Values for The Mediating Role of Forgiveness in The Relationship Between Decision Making and Happiness\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"590\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.966101694915253%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003eNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003eNNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.966101694915253%\"\u003e\n \u003cp\u003eCFA Measurement Model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003e420/117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.966101694915253%\"\u003e\n \u003cp\u003ePerfect fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003e\u0026le; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.966101694915253%\"\u003e\n \u003cp\u003eGood fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.525423728813559%\"\u003e\n \u003cp\u003e3\u0026le; x\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd \u0026le; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003e.05\u0026le;RMSEA \u0026le;.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.932203389830509%\"\u003e\n \u003cp\u003e.05 \u0026le; SRMR \u0026le; .10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e.90\u0026le;CFI \u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.88135593220339%\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen the goodness of fit measures given in Table 6 and SEM values given in Figure 4.a and Figure 4.b are analyzed; it is seen that the relationship between decision making and happiness is explained by forgiveness. When athletes\u0026apos; forgiveness levels are included in the model, the model goodness of fit values have excellent and good fit indicators.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Model -2\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Model-2 created within the scope of the research, the mediating role of forgiveness in the relationship between athletes\u0026apos; cognitive flexibility levels and happiness levels is questioned. In the model, cognitive flexibility as the independent variable, happiness as the dependent variable and then forgiveness as the mediating variable were included in the process. Figure 5.a and 5.b show the results of the structural model.\u003c/p\u003e\n\u003cp\u003eFigure 5.b shows that there is a significant positive relationship between athletes\u0026apos; cognitive flexibility levels and their happiness levels (\u003cem\u003et\u003c/em\u003e=12,20; \u003cem\u003ep\u003c/em\u003e\u0026lt;.01). Figure 5.a also shows that there is a moderate relationship between athletes\u0026apos; cognitive flexibility and their happiness levels (\u003cem\u003e\u0026beta;\u003c/em\u003e=0.54; \u003cem\u003ep\u003c/em\u003e\u0026lt;.01). Athletes\u0026apos; decision-making predicts their happiness levels by 0.29% (R\u003csup\u003e2\u003c/sup\u003e). The model data goodness of fit indices for the model between the two latent variables, which constitutes the first stage of mediation, are presented in Table 7.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7.\u0026nbsp;\u003c/strong\u003eModel Fit Values for The Relationship Between Cognitive Flexibility and Happiness\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"582\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.83848797250859%\" valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.683848797250858%\" valign=\"top\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.151202749140893%\" valign=\"top\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.151202749140893%\" valign=\"top\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003eNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003eNNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.83848797250859%\" valign=\"top\"\u003e\n \u003cp\u003eCFA Measurement Model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.683848797250858%\" valign=\"top\"\u003e\n \u003cp\u003e1858/274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.151202749140893%\" valign=\"top\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.151202749140893%\" valign=\"top\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.83848797250859%\" valign=\"top\"\u003e\n \u003cp\u003ePerfect fit\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.683848797250858%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026le; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.151202749140893%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.151202749140893%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.83848797250859%\" valign=\"top\"\u003e\n \u003cp\u003eGood fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.683848797250858%\" valign=\"top\"\u003e\n \u003cp\u003e3\u0026le; x\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd \u0026le; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.151202749140893%\" valign=\"top\"\u003e\n \u003cp\u003e.05\u0026le;RMSEA \u0026le;.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.151202749140893%\" valign=\"top\"\u003e\n \u003cp\u003e.05 \u0026le; SRMR \u0026le; .10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003e.90\u0026le;CFI \u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.058419243986254%\" valign=\"top\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;The goodness of fit measures obtained in Table 7 have excellent and good fit indicators. The standardized path coefficients for the model investigating whether forgiveness plays a mediating role in the relationship between cognitive flexibility and happiness and the t-values giving information about the significance of these coefficients are presented in figures 6.a and 6.b.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the model in which athletes\u0026apos; forgiveness levels assumed the mediating role, it was concluded that the relationship between cognitive flexibility and happiness maintained its significance (\u0026beta;= 0.52; p\u0026lt;.01). Baron and Kenny [71] reveal that the relationship between the dependent variable and the independent variable is partial mediation if the relationship between the dependent variable and the independent variable decreases when the mediating variable is activated or a slight decrease in the level of the standardized value is observed [72]. Based on this information, it can be stated that the relationship between the dependent and independent variables decreased compared to the first stage (r=0,52; \u003cem\u003ep\u003c/em\u003e\u0026lt;.01), so forgiveness played a partial mediating role between these two variables. The t-value findings of the relationships between the variables are presented in Figure 6.b. Table 8 presents the goodness of fit values for the mediation modeling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8.\u0026nbsp;\u003c/strong\u003eModel Fit Values for The Mediating Role of Forgiveness in The Relationship Between Cognitive Flexibility and Happiness\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"586\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.752136752136753%\" valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.623931623931623%\" valign=\"top\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.068376068376068%\" valign=\"top\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.068376068376068%\" valign=\"top\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.991452991452991%\" valign=\"top\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.504273504273504%\" valign=\"top\"\u003e\n \u003cp\u003eNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.991452991452991%\" valign=\"top\"\u003e\n \u003cp\u003eNNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.752136752136753%\" valign=\"top\"\u003e\n \u003cp\u003eCFA Measurement Model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.623931623931623%\" valign=\"top\"\u003e\n \u003cp\u003e2141/431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.068376068376068%\" valign=\"top\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.068376068376068%\" valign=\"top\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.991452991452991%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.504273504273504%\" valign=\"top\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.991452991452991%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.752136752136753%\" valign=\"top\"\u003e\n \u003cp\u003ePerfect fit\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.623931623931623%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026le; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.068376068376068%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.068376068376068%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026le;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.991452991452991%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.504273504273504%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.991452991452991%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.752136752136753%\" valign=\"top\"\u003e\n \u003cp\u003eGood fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.623931623931623%\" valign=\"top\"\u003e\n \u003cp\u003e3\u0026le; x\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e/sd \u0026le; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.068376068376068%\" valign=\"top\"\u003e\n \u003cp\u003e.05\u0026le;RMSEA \u0026le;.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.068376068376068%\" valign=\"top\"\u003e\n \u003cp\u003e.05 \u0026le; SRMR \u0026le; .10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.991452991452991%\" valign=\"top\"\u003e\n \u003cp\u003e.90\u0026le;CFI \u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.504273504273504%\" valign=\"top\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.991452991452991%\" valign=\"top\"\u003e\n \u003cp\u003e90\u0026le;NFI\u0026lt;.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eConsidering the model goodness and model badness criteria for the model in which forgiveness plays a mediating role in the relationship between cognitive flexibility and happiness, it was concluded that this model also met the criteria of perfect fit and acceptable fit from a multiple evaluation perspective.\u003c/p\u003e"},{"header":"4. Discussion, Conclusion and Recommendations","content":"\u003cp\u003eThe dynamic structure of sport reveals the importance of more than one component in the process leading to success. Therefore, it can reveal the importance of cognitive and affective characteristics of athletes as well as their physical competencies. For this reason, in the present study, when forgiveness comes into play, the relationship between athletes' cognitive flexibility and decision-making and their happiness was tested with structural equation modeling. It was determined that the SEM results were statistically significant and satisfactory and the models constructed in the theoretical framework were confirmed by the data obtained from the athletes.\u003c/p\u003e \u003cp\u003eWithin the scope of the study, the relevant assumptions were tested and analyzed before the mediation relationship and it was determined that there were significant relationships between decision making, cognitive flexibility, forgiveness and happiness. Depending on these relationships, two different SEM models, Model-1 and Model-2, were constructed. In Model-1, it was tested whether forgiveness has a mediating role in the relationship between decision making and happiness of athletes and according to the results, it was determined that forgiveness is a full mediator. Again, in Model-2, which was constructed to determine whether forgiveness has a mediating role in the relationship between athletes' cognitive flexibility and their happiness, it was found that forgiveness is a partial mediator.\u003c/p\u003e \u003cp\u003eAccording to the results of the research, it was determined that there is a significant and positive relationship between happiness and decision making. When the literature is examined, Dilma\u0026ccedil; and Bozgeyikli [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] concluded that there is a significant relationship between subjective well-being and decision-making styles of prospective teachers. In another study, Bubic and Erceg [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] found that there was a significant positive relationship between students' decision-making styles and subjective well-being.\u003c/p\u003e \u003cp\u003eAnother result obtained is that there is a significant and positive relationship between happiness and forgiveness. In the related literature, Yasar [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e] found that subjective well-being is positively related to psychological resilience and forgiveness. Eke [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] concluded that there is a significant positive relationship between adults' forgiveness scores and their subjective well-being.\u003c/p\u003e \u003cp\u003eA significant and positive relationship was also found between decision-making and forgiveness, which is another important finding. Looking at similar studies, Demirtas [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e] concluded that there are significant positive relationships between psychological resilience, forgiveness and cognitive control variables. According to this result, it was interpreted that people with psychological resilience have the ability to control and manage their negative emotions and thoughts and create alternative coping strategies, and thanks to these features, they are more forgiving.\u003c/p\u003e \u003cp\u003eAnother important result of the study is the significant and positive relationship between happiness and cognitive flexibility. When the literature is examined, Balta [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e] found a significant positive relationship between cognitive flexibility and happiness scores of adult individuals. In a similar study, Sagar [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e] concluded that cognitive flexibility significantly predicted subjective well-being at school.\u003c/p\u003e \u003cp\u003eOne of the findings of the study is the significant and positive relationship between cognitive flexibility and forgiveness. In his study, Kara [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e] found that there was a significant negative relationship between the recognition sub-dimension of forgiveness flexibility and cognitive flexibility, and a significant positive relationship between the internalization and implementation sub-dimensions and cognitive flexibility. In another study, Akın [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e] found a significant relationship between cognitive flexibility and forgiveness.\u003c/p\u003e \u003cp\u003eOne of the important results in the study is that forgiveness, which is included in the process in the relationship between decision-making and happiness in Model-1, reduces the level of the relationship and loses its significance, as a result, forgiveness assumes a full mediating role. In this context, decision-making behaviors and happiness of athletes are affected by their forgiveness levels. For this reason, it can be said that as the forgiveness levels of athletes increase, their happiness levels due to decision-making will change. Since forgiving athletes in order to be more successful will increase their happiness levels, it is important to organize non-athlete factors such as coaches within this framework.\u003c/p\u003e \u003cp\u003eIn Model-2, which we can express as another important factor for the current research, the forgiveness factor included in the process in the relationship between athletes' cognitive flexibility and their happiness affects the degree of the relationship and reveals forgiveness as a partial mediating variable. In other words, the relationship between athletes' cognitive flexibility and their happiness decreased when forgiveness was included in the process and forgiveness assumed a partial mediating role.\u003c/p\u003e \u003cp\u003eIn addition to the belief that the study will contribute to the field, it may be suggested to the researchers to look at the mediating relationships of athletes in future studies in terms of athletes competing in team sports or individual sports. In addition, examining the distinction of athletes in the categories of contact sports or non-contact sports will also help to increase the contribution of the study to the field. In the current study, convenience sampling was used as a sampling technique, and in order for this technique not to cause problems in terms of generalizability to the population, a sufficient number of athletes (n\u0026thinsp;=\u0026thinsp;618) were reached. In this context, studies that can be created similar to the current study can also be created using simple random sampling technique. The study can be expanded by analyzing more cognitive factors for the success of athletes and contribute to the field. Trying to contribute to the analysis of the failure factors of athletes who do very good physical training but cannot take a place on the rostrum has revealed the importance of the research.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch Design MK, NŞK; Statistical analysis MK; Preparation of the article, MK, NŞK; Data Collection was carried out by MK, NŞK.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has no external fundings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in this study involving human participants were in accordance with the ethical standards of the Department of Psychology, the University of Hong Kong, and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Mersin University Social and Human Sciences Ethics Committee. Informed consent form was obtained from all participating in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSheldon KM, Lyubomirsky S. Achieving sustainable new happiness: Prospects, practices, and prescriptions. Positive Psychology in Practice, 2004; 127-145.\u003c/li\u003e\n \u003cli\u003eCrossley A, \u0026nbsp;Langdridge D. Perceived sources of happiness: A network analysis. Journal of Happiness Studies, 2005; 6, 107-135.\u003c/li\u003e\n \u003cli\u003eSchiffrin HH, Nelson SK. Stressed and happy? 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Sakarya University of Applied Sciences, Graduate School of Education, Sakarya, 2020.\u003c/li\u003e\n \u003cli\u003eAkın G. Examining the relationship between cognitive flexibility, forgiveness and perfectionism in adolescents (Published Master\u0026apos;s Thesis). Istanbul Sabahattin Zaim University, Institute of Educational Sciences, Istanbul, 2021.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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":"Forgiveness, Decision-Making, Happiness, Cognitive Flexibility, Mediating Role, Athlete","lastPublishedDoi":"10.21203/rs.3.rs-4369738/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4369738/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study intended to reveal the mediating relationship of forgiveness in the relationship between cognitive flexibility, decision-making, and happiness of athletes aged 18 and over through structural equation modeling. A total of 618 licensed athletes participated in the study, and the data were collected from volunteer participants using the \"Forgiveness Decision Scale\", \"Cognitive Flexibility Scale\", \"Natural Decision-Making Scale\" and \"Happiness Scale\". The results indicated that athletes\u0026rsquo; forgiveness was the full mediator in the relationship between decision-making and happiness, and the partial mediator in the relationship between cognitive flexibility and happiness. The mediation study carried out offers clues to identify and eliminate the negativities on the way to the success of the athletes.\u003c/p\u003e","manuscriptTitle":"The instrumental role of forgiving in the relationship between cognitive flexibility and decision-making and happiness in athletes","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2025-04-21 19:38:39","doi":"10.21203/rs.3.rs-4369738/v2","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}},{"code":1,"date":"2024-06-28 15:58:04","doi":"10.21203/rs.3.rs-4369738/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":"195acf94-aa4c-476e-8e62-c034f2f5bcde","owner":[],"postedDate":"April 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-29T04:08:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-21 19:38:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-4369738","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4369738","identity":"rs-4369738","version":["v2"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}