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Department of Social Psychology

Positive Emotions and Well-being

Master thesis of: Yemanja Göttges

10208976

April 2017

Primary Advisor: Disa Sauters

Secondary Advisor: Suzanne Oosterwijk

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Abstract

The aim of this study was to examine the relationship between positive emotions (PEs) and subjective well-being (SWB). More specifically, this study explored the predictive value of gratitude, awe, compassion, forgiveness and love for SWB as previous studies indicated a correlation between these PEs and well-being. There was no consensus whether all PEs equally accounted for this influence. Through the use of experience sampling method (ESM;

Schimmack, 2003) the current research explored variation in the predictive value of specific types of PEs on SWB. Multiple regression analyses showed that only gratitude and compassion were reliable predictors for SWB. Gratitude seems to be the strongest predictor; gratitude predicted both components of SWB. Furthermore ego resilience was a mediator of the relationship between gratitude and SWB.

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Introduction

Background

For the last six decades much research in the field of psychology focused on the study of mental illnesses and the development of intervention strategies to treat those illnesses.

According to Seligman (2004) and other pioneers on the study of positive psychology (Diener & Seligman, 2002; Seligman & Csikszentmihalyi, 2000) however, due to the focus on developing treatment and intervention programs for abnormal behavior, some significant matters were left out. Diener and Seligman (2002) went beyond traditional psychological research methods by conducting breakthrough research on very happy people. In this study, Seligman approached human behavior from a completely new dimension. Diener and Seligman theorized that integrating effective strategies of very happy people into lives of the unhappy ones might prevent them from becoming ill by improving their well-being. The question that was addressed in their study was what factors contributed to a happy life. A comparison between very unhappy, average- and very happy people was made in order to identify key behavioral factors in which each group differed. Differences in moods and emotions were studied as well. Findings showed a relationship between personality factors, social relationships and happiness. On mood and emotions, findings showed that happy people had a well-balanced emotional climate; overall the very happy people felt happy but they were also well capable to adjust in a functional way to changing circumstances, meaning that they were receptive for unpleasant and extremely pleasant emotions as well. Although the results of Diener and Seligmans’s first study on happy human being behavior were purely correlational, their approach changed the scientific field of

psychological research radically by introducing a new method in studying human behavior. Out of this approach a new domain of research in the field of psychology was born: positive

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Subjective well-being

A theme that gained popularity within this new field of research was the study on SWB, also known as happiness. SWB is a psychological construct that is used to determine one’s psychological health based on people’s own evaluations of their life (Lucas & Diener, 2008). Similar to the construct of physical health, SWB consists out of several facets that interact and influence one another. Facets such as positive memories, feeling a purpose in life, optimism, and the relative amount of positive and negative affect over time. Momentary experiences and moods (affective evaluations) as well as global judgments about one’s life as a whole (cognitive evaluations) both relate to SWB (Kim-pietro et al., 2005). Kim-pietro et al., (2005) introduced a model to illustrate the complex structure of SWB and its facets (events and circumstances, emotional reactions, memory of emotions & global judgments on life satisfaction) to clarify the contribution of each facet to the overall state of SWB. SWB can be affected by each of these facets, though all of the facets are interrelated and influence one another. The consideration of SWB as a multiple-faceted construct takes different types of conceptualizations into account. SWB can be studied from its cognitive core: in this case SWB is measured as an overall judgment on significant life domains (e.g., work and social relationships), or its affective core: studied by collecting multiple emotional experiences. The first approach aims to examine overall

judgments on life satisfaction and quality of life. The second approach uses emotional

experiences to measure people’s judgments on SWB. This approach differs from the cognitive approach because instead of collecting an overall judgment, the aim is to collect specific information about emotional experiences that have occurred in order to identify significant feelings that influence judgments on SWB. SWB seems to be a good indicator for success in multiple life domains as well as the subjective experience of this success. People that score high on SWB are more likely to experience rich and satisfying social relationships, marital

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2002; Lyubomirsky, King & Diener, 2005). Measures on SWB have proven to be stable over time and hence considered to be reliable predictors for studies on human happiness.

Broaden-and-Build theory

The broaden-and-build theory (Frederickson, 2001) provides a theoretical framework of the underlying mechanisms accounting for the physical and psychological health benefits associated with PEs. The broaden-and-build theory states that PEs are functional adaptations that play a key role in building deep-rooted resources and resilience that are needed to be successful in life. The broaden-and-build theory points out that positive- and negative emotions are processed through different mechanisms and hence have a distinct impact on behavior and well-being. Negative emotions activate the sympathetic nervous system in the face of

immediate danger or threat. In contrast, PEs activate the parasympathetic nervous system. As a result, one’s attention, cognition and behavioral repertoire are broadened which facilitates renewed approaches to handle situations due to more flexible goals and mindsets. Over time, these experiences accumulate and provide valuable resources (e.g., having a broader response repertoire) that can benefit a healthy and happy life.

Complementary to the broaden-and-build theory is the undoing hypothesis (Fredrickson, Mancuso, Branigan & Tugade, 2000) that states that due to the broadened cognitive capacity associated with PEs, subsequent negative or stressful experiences can be approached in a more functional manner. According to the undoing hypothesis, a broadened cognitive capacity to handle a negative experience by for example considering multiple options to cope, at the same time reduces the possible negative after-effects (e.g., narrowed attention, thoughts and actions) of negative emotions. PEs seem to have a unique ability of down-regulating the physiological consequences of negative emotions and seem to be more receptive to change than negative emotions (Chow, Ram, Fujita, Boker, & Clore, 2005).

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Positive affect

Multiple studies have found correlations between positive- and negative affect and life satisfaction (e.g., Tugade, Frederickson, & Barrett, 2004; Kuppens, Realo & Diener, 2008). Most of these studies have found a stronger correlation between positive affect and SWB in comparison with the correlation between negative affect and SWB. For example, Suh, Diener, Oishi & Triandis (1998) found a correlation between negative affect and life satisfaction of -.26 versus a correlation between positive affect and SWB of .44. Cohn, Frederickson, Brown, Mikels & Conway (2009) found a significant predictive value on life satisfaction for the presence of PEs, for the presence of negative emotions no correlation was found. Hence, the current study was designed to examine the relationship between PEs and SWB.

Positive Emotions

PEs contribute to feelings of SWB and SWB appears to be a good indicator for success in various life domains including physical well-being, social relationships, romantic relationships and work performance (Cohn et al., 2009; Frederickson, 2001; Lyubomirsky, King & Diener, 2005; Tugade, Frederickson & Feldman Barrett, 2004). Findings also show that PEs play a key role in building ego resilience, that is, the ability to adjust to changing circumstances. Adaptive responses may include identifying opportunities, adapting to constraints and bouncing back from misfortune. This means that PEs enable one to successfully cope with stressful life-events by raising levels of ego resilience over time. Ego resilience also reinforces itself by generating PEs. When life challenges are successfully encountered, both the overall state of global life satisfaction and ego resilience can grow (Cohn, Frederickson, Brown, Mikels & Conway, 2009). Moreover, it has also been found that the frequency of PEs was a better predictor of well-being than the intensity (Kuppens, Realo and Diener, 2008). The following section will further outline specific benefits of different types of PEs.

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Gratitude

Research findings have indicated a correlation between SWB and gratitude (Watkins, 2004). Gratitude turned out to raise consciousness towards acts of help people receive in everyday life. The ability to be aware of certain acts of aid has been associated with SWL over time (McCullough, Kilpatrick, & Emmons, 2001). The experience of gratitude can make it less likely for people to become habituated to positive events happening to them which in turn can contribute to SWL over time (Watkins, 2004). Wood, Maltby, Gillet Linley and Joseph (2008) found that gratitude could predict well-being even when controlling for personality factors. Froh, Seffick and Emmons (2008) conducted a quasi-experimental study in which they manipulated gratitude by examining gratitude in the form of counting one’s blessings. For 2 weeks on a daily basis with a 3-week follow-up, participants reported either blessings or hassles they had

experienced. Results indicated a significant change in enhanced well-being, gratitude and less negative affect following counting blessings. Using a daily self-report system, the current study further examined the impact of the experience of gratitude on SWB.

Awe

Another PE that has been found to benefit feelings of well-being is awe. Awe is an overwhelming feeling of wonder that can arise in response to a complex or sensational

phenomenon one encounters. Awe encourages one to accommodate existing mental schema’s to adjust one’s understanding of the world. Awe has been related to religious practices,

experiencing the birth of a child and observing incredible natural phenomenon’s such as the Grand Canyon (Keltner & Haidt, 2003). Rudd, Vohs and Aaker (2012) found a relationship between awe and well-being that was explained by awe’s characteristic to expand one’s perception of time. Rudd et al., (2012) found that the manipulation of awe, relative to a manipulation of happiness, expanded time perception, reduced impatience and increased

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willingness to volunteer one’s time. Moreover, the perception of having increased time available related to a preference for experiential goods over material ones and greater life satisfaction. The relationship between awe and the cognitive- and affective component of SWB was further

examined in this study.

Compassion

Compassion encompasses the ability to experience empathy towards others and the self. Compassion involves offering kindness and patience and being non-judgmental by

acknowledging the existence of imperfection in the human nature (Neff, 2003). Neff (2003) found a significant positive relationship between compassion and life satisfaction. Mongrain, Chin & Shapira (2011) found that practicing compassion, by interacting with someone in a supportive and caring way, contributed to higher levels of happiness. Having compassion for the self can enhance feelings of well-being through self-nourishing (e.g., preventing oneself of becoming overly stressed by taking time off from work). Self-compassion allows the experience of feeling PEs towards the self through transforming negative self-affect (blaming oneself for failures) into positive self-affect (being kind and understanding towards the self). This study further examined the effects of compassionate feelings on well-being.

Forgiveness

The establishment and maintenance of close social relationships is a fundamental human need (Self-determination theory; Ryan & Delci, 2000) and the maintenance of supportive relationships is essential to physical and psychological health (Baumeister & Leary, 1995). Forgiveness plays a key role in reconciling relational conflict, and apologies are the strongest facilitators of forgiveness (McCullough, Worthington & Rachal, 1997). Bono, McCullough & Root (2008) argued that forgiving a close relationship partner raises feelings of reconnection to a significant source of social support, which in turn benefits feelings of well-being. Results of a

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longitudinal study on forgiveness and well-being (Bono et al., 2008) revealed indeed that forgiveness related to greater well-being and that this relationship could be explained by

renewed feelings of closeness toward the offender. Karremans, van Lange, Ouwerker en Kluwer (2003) examined relationship-specific variables that determine the degree to which forgiveness can enhance psychological well-being. Findings showed that forgiveness was only associated with enhanced life satisfaction and levels of positive affect when commitment was strong (best friend), but not when commitment was weak (casual acquaintance). The effects of reconciling relational conflict on well-being were further addressed in the present study.

Love

Kornfield (2014) poetically described love as the recognition that we are not separate from other human beings, the planet and the universe. Out of this recognition a resonance of deep care for others known as love arises. Love in its different forms has been identified as an important predictor of happiness, satisfaction and positive emotions. Kim and Hatfield (2004) found that the experience of love was related to higher levels of positive affect and judgments on life satisfaction. Moreover, Frederickson, Cohn, Coffey, Pek & Finkel (2008) found that the daily experience of PEs can be increased through the daily practice of loving-kindness

mediation. As a consequence of this loving-kindness meditation, personal resources such as self-acceptance and positive social relations improved levels of life satisfaction. This study further examined the relationship between love and feelings of well-being.

The present study

The question that was addressed in the current research was whether specific types of PEs (specifically, gratitude, awe, compassion, forgiveness and love) contributed to SWB in a unique manner. The frequency of experienced PEs seems to play an important role in the overall

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state of physical and psychological well-being (Diener, Sandvik & Pavot, 2009; Kuppens, Realo & Diener, 2008). Moreover, previous findings indicate a possible mediating role for trait

resilience in the relationship between PEs and SWB. PEs seem to be good predictors of life satisfaction and the affective climate, two main components of SWB. It is likely that ego resilience plays a mediating role in this matter. The current research examined this relationship with specific emphasis on the unique characteristics of specific types of PEs and the way in which they relate to SWB.

Hypothesis

A significant relationship between PEs and SWB has been found. However, it remained unclear whether all PEs equally account for this relationship and whether PEs relate to different components of SWB in the same way. Particular PEs have unique characteristics that may benefit certain aspects of well-being (e.g., promoting feelings of connectedness, the perception of less time pressure), and so it may be that specific types of PEs relate to well-being in a distinct manner. The current research examined these specific relationships through the following hypothesis:

H1: specific PEs (gratefulness, awe, compassion, forgiveness & love) singularly predict SWB H1a: unique variance in the affective component of SWB is explained by gratitude H1b: unique variance in the cognitive component of SWB is explained by gratitude H1c: unique variance in the affective component of SWB is explained by awe H1b: unique variance in the cognitive component of SWB is explained by awe

H1d: unique variance in the affective component of SWB is explained by compassion H1e: unique variance in the cognitive component of SWB is explained by compassion H1f: unique variance in the affective component of SWB is explained by forgiveness H1g: unique variance in the cognitive component of SWB is explained by forgiveness

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H1h: unique variance in the affective component of SWB is explained by love H1i: unique variance in the cognitive component of SWB is explained by love

H2: all of the PEs (gratefulness, awe, compassion, forgiveness & love) taken together predict the cognitive- and the affective components of SWB

H3: unique variance of SWB explained by PEs is mediated by trait ego resilience

Method

Participants

Participants were first grade psychology students from the University of Amsterdam (UvA) who were recruited via the official recruitment website of the UvA (www.lab.uva.nl) and word of mouth. 3 research credits, equals 180 minutes of research participation they need to obtain as part of their curriculum, was offered for participation in a week-long study on PEs and SWB. To determine the number of participants, the sample- (N=89) and effect size (medium to large) of a comparable study on PEs and life satisfaction by Cohn, Frederickson, Brown, Mikels & Conway (2009) were taken into account. Out of the 92 sign-ups 72 participants (N=72), of which 80.6% woman, total mean age = 25.2 years (SD=9.1), started and completed the actual research.

Procedure

All participants were given informed consent prior to participation after signing-up and filling out demographic details. This information contained the aim of the project as well as information regarding the design of the study; one-week daily self-report on PEs and

instructions; hours between each shift, time to complete each shift and consequences of missing out on shifts. Prior and after the daily self-report measurements participants provided judgments on mood, life satisfaction and resilience. Participants were instructed to have access to a cellular

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phone with Internet connection during all shift times. After the final entry participants were automatically linked to a page where information regarding reward, appreciation and instructions for debriefing was presented.

Materials

Daily emotions. Participants used their own cellular phone to submit daily emotion reports. Experienced PEs were assessed using the Experience Sampling Method (ESM;

Schimmick, 2003). Participants were asked whether or not they experienced one or more of the 5 PEs (gratitude, awe, compassion, forgiveness and love) that were examined. Participants were able to respond by choosing a point on a Likert-scale (0-5; 0= very slightly or not at all, 5=a lot) to determine if, and if so, how strongly they experienced the PE. For 7 days, participants

received notifications through their cellular phone 3 times per day (12am, 3-6pm and 9-12pm). At the start of every shift participants received a text message containing a link directing them to the survey. Participants were asked about PEs they experienced during the last 30 minutes (Schimmick, 2003). 30 minutes before closing of the shift participants received a warning notification regarding closing of the shift.

PANAS. EWB was measured using the Positive and Negative Affect Scales (PANAS; Watson, Clark & Tellegen, 1988). The PANAS contains two 10-item mood scales on which participants responded by choosing a point on a Likert-scale (0-5; 0= very slightly or not at all, 5=a lot) answering questions regarding their mood (e.g., you have felt this way during the past week: interested). Both mood scales were found to be highly reliable (PA α=0.86-0.90, NA α=0.84-0.87).

Life Satisfaction. Life satisfaction was measured using the Satisfaction with Life Scale (SWLS; Diener et al.,1985). The SWLS consists out of 5 items (e.g., in most ways my life is close to my ideal) on which participants responded by choosing a point on a Likert-scale (0-7; 0=strongly disagree, 7=strongly agree). The reliability of the SWLS was high (α=0.86).

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Ego Resilience. The Resilience 89 (ER89; Block & Kremen, 1996) was used to examine trait ego resilience that points out to variation in effectiveness of adaptation to ever-changing being and ever-ever-changing circumstances. The ER89 contains 14 items (e.g., I quickly get over and recover from being startled) on which participants responded by choosing a point on a 4-point Likert-scale (0=does not apply at all, 4=applies very strongly). The ER89 was found to be a reliable measurement for trait ego resilience (α=0.69).

Data analyses

The current research used both simple and multiple regression analyses for hypothesis testing. All PEs were treated as separable predictors. Before conducting this regression, correlation analyses were used to examine any possible relation between the PEs that will be assessed. The independent variable (IV) in the current research was all PEs taken together (IV1) as well as separately (IV2). The dependent variables (DV) consisted of measures of life

satisfaction, affect and ego resilience. To test H1, the predictive value of all different PEs on PANAS and SWLS was examined using simple regression. To test H2, the predictive value of all PEs on both measures on SWB was further tested with multiple regressions. It was also tested whether unique variance explained by separate PEs could be explained by trait ego resilience (H3) to test the significance of this relationship with mediation analysis.

Results

To explore variation in the predictive value of specific types of PEs on SWB several hypotheses were tested. PEs were measured as both the intensity of the experienced PE and as the frequency that each PE was reported by each participant. Two questionnaires, the SWLS and the PANAS, were used as measurements to test both components of SWB.

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Before proceeding with the analyses the following assumptions were examined: sample size, normality, multicollinearity, and possible outliers for the predictive variable as well as the outcome variable. Analyses were conducted using SPSS. The minimum requirement for the sample size was met (≥20 per predictor). The Komogoriv Smirnov test was used to check for normality. Except for the SWLS, PEa, PEf, PEc data was normally distributed. Looking at the distribution of values for both the outcome and predictor variables no outliers were found. Outliers were tested with Cook’s distance. There were no influential outliers (>1) in the current data set. The scatter- and probability plots confirmed this finding. This is to be expected as the range of values was limited by the Likert scale.

Hypothesis H1 and H1a to H1i were tested using both simple regressions. Hypothese 2 was tested using multiple regressions. To test the relationship between each single PE and the dependent variables, the standard method for regression (enter) was used. To test the

relationship between all PEs taken together and the dependent variables, a stepwise regression method was used. The stepwise method includes predictive variables in a model when they account for sufficient variance in the model. With this method, predictors are put into the model at the same time. Adding predictors to the model stops whenever there are no more predictors that meet the criteria to account for variance. This method is suitable for explorative research, which is the case since there is no prior research suggesting that PEs do not equally account for feelings of well-being. Multicollinearity could not be ruled out as the correlation between some of the predictors was high (above 0.70). High correlation was observed between the following pairs of variables: gratitude and compassion, gratitude and forgiveness love, awe and

compassion, awe and forgiveness, compassion and forgiveness, and compassion and love. This increased the standard errors for the coefficients in the multiple regression, leading to loss of significance and change in coefficient for some of the PEs that had significant coefficients in the simple regression.

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H1: Specific PEs (gratefulness, awe, compassion, forgiveness & love) singularly predict SWB

Table 1

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SWB -> PANAS SWLS PANAS SWLS PANAS SWLS PANAS SWLS PANAS SWLS

Gratitude 0.373 0.346 (0.010) (0.015) Awe 0.230 0.131 (0.120) (0.368) Compassion 0.155 0.076 (0.297) (0.695) Forgivness 0.147 0.146 (0.325) (0.316) Love 0.269 0.265 (0.068) (0.066) Adjusted R2 0.120 0.101 0.032 0.000 0.002 0.000 0.000 0.001 0.052 0.051 N 47 49 47 49 47 49 47 49 47 49

Tables 1 and 2 report the results for the simple regressions for all PEs, with both the PANAS and the SWLS as dependent variables. Table 1 reports results for the effect of the intensity of PEs and Table 2 shows the results for the frequency that a PE was reported.

Looking in Table 1 at the predictor variable relationship to the outcome, gratitude and love had a significant and positive effect on both the PANAS and the SWLS. This can be seen in columns 1,2,9 and 10 of Table 1. The coefficient on gratitude was positive and significant and was able to explain variance in the PANAS and the SWLS with an adjusted r-squared of 12 and 10 percent respectively. The coefficient on love was weakly significant (p=0.07) and the model was able to explain only 5 percent of the variance in both the PANAS and the SWLS. The coefficients of awe, compassion and forgiveness were all insignificant and the simple

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Table 2

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SWB -> PANAS SWLS PANAS SWLS PANAS SWLS PANAS SWLS PANAS SWLS

Gratitude 0.208 0.308 (0.171) (0.031) Awe 0.115 0.105 (0.297) (0.472) Compassion 0.003 0.078 (0.982) (0.604) Forgivness 0.100 0.128 (0.503) (0.380) Love 0.081 0.203 (0.569) (0.161) Adjusted R2 0.020 0.076 0.002 0.000 0.000 0.000 0.000 0.000 0.000 0.000 N 47 49 47 49 47 49 47 49 47 49

Table 2 looks at the effect of SWB on the frequency that a PE was reported. Results looked less significant than Table 1, with the only significant coefficient being the one of gratitude on the SWLS. This model was able to explain 7% in the variance of the SWLS. The frequency of all other PEs was not significantly related to SWB.

H1 could not be rejected. More specifically H1a, H1b could not be rejected at 95% confidence level and H1h and H1i could not be rejected at the 90% confidence level.

H2: All of the PEs (gratefulness, awe, compassion, forgiveness & love) taken together predict the cognitive- and the affective components of SWB

Table 3 Table 4 (1) (2) (1) (2) SWB -> PANAS SWLS SWB -> PANAS SWLS Gratitude 0.373 0.725 Gratitude . 0.890 (0.01) (0.001) (.) (0.001) Compassion . -0.433 Compassion . -0.681 (.) (0.023) (.) (0.009) Adjusted R2 0.120 0.179 Adjusted R2 0.000 0.185 N 47 49 N 47 49

Tables 3 and 4 report the results for multiple regression models where all the PEs

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multiple regressions were done with the stepwise method and only the results for the included variables are reported in Tables 3 and 4.

Starting from Table 3, results show that all PEs taken together were able to only predict around 12% of outcome scores for the PANAS and around 17% for outcome scores for the SWLS. In column 1, gratitude appeared to be the only significant predictor in the model with p-value lower than 0.01. Because this was the only variable included, size, sign and significance were in line with the results from Table 1. Contrary to what was found in Table 1, love was not

significant in the multiple regression.

In column 2 results also show that all PEs taken together were able to predict 18% of outcome scores on the SWLS. In this case, both gratitude and compassion were significant predictors in the model. Specifically 10% of variance in the model was explained by gratitude and together with compassion these PEs accounted for 18% of variance. Interestingly while gratitude had the expected positive sign, higher levels of intensity of compassion had a negative effect on the SWLS.

In Table 4 the effect of the frequency of all reported PEs on SWB is reported. In the model reported in column 1 no variable was included in the stepwise method as none of the frequencies of PEs had any effect on outcome scores of the PANAS. This result was in line with the output of Table 2. In column 2, the results are showing a situation similar to Table 3 where both gratitude and compassion had a strongly significant effect on the SWLS. Again the results showed that while higher frequency of reported gratitude led to higher SWLS, the opposite was true for compassion. The model of Table 4, column 2 was able to predict more than 18% of the variance in the SWLS scores. H2 could be rejected as only gratitude and compassion were significant predictors of SWB.

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H3: unique variance of SWB explained by PEs is mediated by trait ego resilience

From the previous analysis it can be concluded that gratitude was the only PE that was consistently related to both measures of SWB. In this section the mediation of gratitude by ego resilience of SWB is tested.

The mediation of the relationship between gratitude and SWB via ego resilience was tested using the PROCESS macro for SPSS by Andrew F. Hayes. There was a significant indirect effect of mean reported gratitude on the PANAS through ego resilience, the completely standardized indirect effect was equal to 0.243 with 95% Bootstrapped Confidence Intervals (BCI) between 0.0558 and 0.4392. This was equal to an effect on the total variation (represented by the R-squared of the mediation) of 12.4%, 95% BCI[.00253, 0.2772]. The Sobel test

confirmed the existence of mediation with a p-value of 0.026. It could be concluded that ego resilience was a mediator of the relationship between mean reported gratitude and the PANAS.

Ego resilience was also a mediator for the effect of mean reported gratitude on the SWLS, with a completely standardized indirect effect of 0.1891 and 95% BCI[0.0540,0 .3698]. The mediation effect explained 9.5% of total variation (BCI[0.0054,0 .2661]). The Sobel test confirmed the existence of mediation with a p-value of 0.040. Also for the SWLS it could be concluded that ego resilience was a mediator of mean reported gratitude.

The mediation analysis was repeated for the frequency of experienced gratitude. In this case the indirect effect of the mediation of reported frequency of gratitude via ego resilience was not significantly different from zero for both the PANAS and the SWLS. The lack of mediation was confirmed in both cases by an insignificant Sobel test.

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Discussion

The aim of this study was to examine the relationship between PEs and SWB. More specifically, this study explored the predictive value of gratitude, awe, compassion, forgiveness and love for SWB, as previous studies have indicated a correlation between these individual PEs and well-being. Through the use of the experience sampling method, the current research

explored variation in the predictive value of specific types of PEs on SWB. Findings partly supported the hypotheses regarding differential effects of PEs on well-being.

SWB, also known as happiness, was studied based on its two distinct main facets: cognitive and emotional. Overall judgments on life satisfaction and quality of life represent the cognitive core of SWB. Emotional experiences; emotions, moods and general emotional well-being, represent the affective core. The relationship between all PEs taken together versus separate in relationship with each distinct facet of SWB was explored. Contrary to prior research findings, only two of the PEs, gratitude and compassion, were found to be reliable predictors for feelings of well-being, with gratitude being the strongest predictor. A small effect was found for love. The current study did not find a relationship between awe, forgiveness and SWB, even though previous studies have found such a relationship.

The experience of gratitude related to both life satisfaction and EWB while compassion only was found to relate to life satisfaction. Both, the intensity as well as the frequency of the experienced emotion accounted for these effects. A possible explanation for this might be that gratitude, in comparison with the other emotions, is more flexible in the way it can occur. Gratitude can be experienced in response to both concrete (e.g., being grateful for a gift) and abstract (e.g., being grateful for ones life as a whole) events. Gratitude is also applicable to all of the other emotions; one can experience gratefulness over the experience of love, over

reconciling a friendship, and over the experience of awe. This is in line with the high correlation between gratitude and the other PEs found in this study. This overlapping characteristic

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broadens the field of influence for gratitude, which might explain its greater impact on well-being. As mentioned previously, compassion involves offering kindness and patience and being non-judgmental towards the self and others by acknowledging the existence of imperfection in the human nature (Neff, 2003). Embodying compassion can alter the way in which life is interpreted given any less fortunate circumstance. From an evolutionary viewpoint, compassion also originated for the use of social bonding, which in turn generates PEs. Interestingly, while higher scores for gratitude on intensity and frequency related to an increase of feelings of well-being, higher scores for compassion related to lower scores on life satisfaction. Empathy, a main characteristic of compassion, perhaps explains this finding. One way to empathize is to identify with someone else’s feelings/perspective (Neff, 2003). Given these feelings to be negative, one might feel for the other or with the other. Hence, feel similar to the other and therefore

experience lower SWB. Compassion also has similar overlapping characteristic; it can be applied to all feelings that arise in response to any changing circumstance. Contrary, forgiveness and awe arise in response to one specific circumstance (a conflict or a phenomenon one encounters) and are therefore limited in their field of influence. Frequency reports also support this notion; whereas gratitude, love and compassion were experienced on average 11-13 times, forgiveness and awe 8 times. For gratitude, the strongest predictor in the model, an additional analyses was conducted to explore gratitude’s impact on well-being could be explained by trait ego resilience. It was found that gratitude’s impact on both the affective- and the cognitive component of SWB could be explained by ego resilience. Hence, it was confirmed that gratitude plays a key role in building ego resilience, the ability to adapt to changing circumstances. Gratitude plays part in the process of identification of opportunities, adaptation to constraints and the ability to bounce back from misfortune. In turn, it supports successful coping with stressful life-events by raising levels of ego resilience over time.

The current study confirmed and supported prior findings on PEs and happiness and pointed out to the importance of the experience of PEs in order to live a happy and meaningful

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life. Happy people are more successful in multiple life domains such as health, marriage, friendship, income, and work performance (Diener & Seligman, 2002; Lyubomirsky, King & Diener, 2005). Working- and spending time on activities that make us feel passionate and excited increases our productivity and enhances feelings of well-being. This relationship, between happiness and success, seems to be bi-directional: success makes people feel good and maintaining a positive emotional climate seems to increase chances of success (Lyubomirsky, King & Diener, 2005). Positive emotional experiences support an open-minded and flexible approach to life, which in turn stimulates creativity and personal growth. Constant changing circumstances are the inevitable fundament of human life. Regardless whether these changes are for the better or for the worse, adapting to the flow of life, while developing skills to cope with changing circumstances, seems to be the most beneficial way to go.

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