How do you feel right now? Happiness and extraversion in young adults : An experience sampling study

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How Do You Feel Right Now? Happiness and Extraversion in Young Adults: An Experience Sampling Study

Leon Frielingsdorf

Department of Psychology, Health, and Technology, University of Twente Bachelor Thesis

Dr. Matthijs L. Noordzij Drs. Tessa Dekkers

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Abstract

Background. A positive relationship between happiness and extraversion on a trait-level has been frequently reported. But does this account for a state-level and if yes, is the association more prevalent on the trait-level or the state-level? Findings on the state-level can be of practical utility for psychological interventions aiming at an increase of happiness through momentary manipulations of extraversion. Objective. To gain insights into the daily association between happiness and extraversion, an online experience sampling study was conducted over one week with a young adult sample (N = 33; MAge = 21.3). Method. For an assessment of trait scores, the Abridged Five Factor Circumplex Model (AB5C) was used for happiness and the Big Five Aspect Scale (BFAS) for extraversion. For an operationalisation of states, self-made items were used. At the beginning of the study, participants were asked to fill in the trait questionnaires, before being asked to answer the state questions on four occasions per day over one week. For an association of state scores, it was hypothesized that individuals who feel extraverted at the moment also report feeling happier and vice versa. Therefore, a moderate and significant association was expected. With regard to the research question, if the association is more state- like or trait-like, it was hypothesized that the state association would be stronger. Results This was confirmed by utilising a Linear Mixed Model analysis. Thus, if individuals feel extraverted at the moment, they are also prone to feel happier at that moment. Moreover, it was found that the association between happiness and extraversion is more state-like than trait-like, so the association between both constructs is more momentarily. Lastly, it has been shown that state scores for happiness and extraversion show no relation to trait scores for both, indicating that a trait score for happiness and extraversion consists of more than just the average of happy/extraverted situations. Conclusion. Generally spoken, the present paper enabled a shift in perspective regarding the association of happiness and extraversion. Accordingly, it was shown that both concepts are not only associated on a trait-level but also on a state-level.

Moreover, a stronger association was found on the state-level. This can set the starting point for possible innovations in psychotherapeutic interventions with a focus on smaller interventions on several occasions per day focusing on momentary intervention in state extraversion. However, generalisations with the apparent data have to be formulated tentatively.

Thus, state items could not be validated, even though they showed good internal consistency.

Moreover, the data collection has been executed during a global pandemic, so deviations in average trait scores could be observed by comparing them with previous papers.

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Introduction

“Thousands of candles can be lighted from a single candle, and the life of the candle will not be shortened. Happiness never decreases by being shared.” This phrase by Buddha can be linked to recent dynamics in the area of psychology especially caused by innovations in the domain of positive psychology. Here, the link between happiness and the personality trait extraversion has been extensively confirmed by psychological scholars (Furnham, & Cheng, 1997; Pavot, Diener, & Fujita, 1990). Pavot and colleagues (1990) even argue that “the relationship between extraversion and happiness […] is one of the most consistently replicated […] findings in the SWB (subjective well-being) literature”. Accordingly, extraverted individuals share characteristics of assertive behaviour, positive affect, and the need for social attention, whereas happiness defines the degree of satisfaction one has with the quality of his life (Wilt, & Revelle, 2017; Veenhoven, 1991). However, these findings are only limited to relatively stable levels of happiness and extraversion on a trait level, whereas literature lacks insights into the fluctuating component of both concepts, the state level. The latter defines a complementary property to the trait level but does not infer the stability of psychological phenomena (Fleeson, &

Jayawickreme, 2015). Hence, a state captures the situational dynamics of mental processes (Csikszentmihalyi, & Larson, 2014). As the acknowledgement of a state-level allows intervening in the behavioural adaptation of individuals in a smaller time frame, knowledge on both facets is important. To further specify, it has been shown that improvements in certain states can have beneficial effects on an individual’s life quality (Fox, 1999). For instance, research suggests that momentary extraverted behaviour like social support seeking works as a suitable coping mechanism for stressful events (Amirkhan, Risinger, & Swickert, 1995).

Therefore, the present study will aim at an examination of happiness and extraversion on a momentary, state, level.

Happiness

Through the recent emergence of Positive Psychology, happiness has been put in the spotlight of scholarly work. Thus, the field makes extensive efforts to investigate the positive aspects of an individual’s life instead of malfunctioning as in psychopathology (Seligman, &

Csikszentmihalyi, 2014). Furthermore, fulfilment and acting upon one’s talents and goals are in the focus as well as the pursuit of happiness (Gilovich, Kumar, & Jampol, 2015).

Consequently, an increase in one’s life quality through positive interventions defines a core characteristic of this psychological domain (Seligman, Csikszentmihalyi, 2014).

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However, even though a multitude of articles about happiness has been published in the past, there is still no clear consensus about a uniform definition. Here, the issue is that happiness possesses several meanings ranging from the pursuit of mere pleasure to striving for fulfilment (Diener, Scollon, & Lucas, 2009). To avoid this ambiguity, scholars prefer to make use of the term subjective well-being (SWB), which is often used synonymously with happiness (Diener et al., 2009). Generally spoken, SWB includes positive cognitive and affective appraisals an individual has about life (Diener, Lucas, & Oishi, 2002). Therefore, it is defined by overall life satisfaction, the presence of positive affect, and the absence of negative affect (Demır, &

Weitekamp, 2007). This definition of happiness with its properties referring to SWB will be utilised in the present paper.

Findings by Lyubomisky, Sheldon, and Schkade (2005) suggest three factors predicting an individual’s level of happiness, which are namely the happiness set point, circumstances, and intentional activities. Accordingly, the happiness set point refers to genetic preconditions, which are fixed and stable over time. It is the most decisive determinant in the prediction of happiness as it accounts for 50% of its variance (Lyubomisky et al., 2005). The second factor, relating to circumstances, points out demographic (e.g. gender), geographic (e.g. residence), and contextual (e.g. culture) factors that contribute to perceived happiness (Lyubomisky et al., 2005). These factors in total account for about 10% of the variance of happiness (Diener, Suh, Lucas, & Smith, 1999; Lyubomisky et al., 2005). Lastly, intentional activities make up 40% of the variance of happiness (Lyubomisky et al., 2005; Sheldon, & Lyubomirsky, 2006). To elaborate, they refer to voluntary, effortful activities that sustain one’s level of happiness. These include cognitive, behavioural, and volitional aspects of one’s life. Concerning cognitive factors, one can for example stress the positive aspects of one’s life, while behavioural factors relate to actions as for instance acting helpful. Volitional aspects, on the other hand, describe an individual’s striving towards a desirable goal, which in return, if a goal is obtained, positively affects happiness (Lyubomisky et al., 2005).

Happiness has a positive effect on many aspects of daily life. With respect to the effect, happiness has on the lives of individuals, Oswald, Proto, and Sgroi (2015) found that happiness positively affects levels of productivity. Thus, happy individuals are more productive than their unhappier counterparts making them more effective in terms of goal-directed action causing greater levels of fulfilment and overall life satisfaction (Oswald et al., 2015; Seligman, 2004).

Moreover, an investigation with the Authentic Happiness Inventory and the Perceived Stress Scale indicates that high levels of happiness predict lower levels of perceived stress (Schiffrin,

& Nelson, 2010). According to Rim (1993), the reason behind this lies in the more adaptive

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coping styles of happy individuals, which makes them more prone to deal with stress effectively. Furthermore, happy individuals were found to display higher levels of social skills, which is mostly explained by the mediating role of assertiveness (Argyle, & Lu, 1990a). All in all, this relationship between happiness and positive outcomes demonstrates the importance of studying happiness in all its facets.

Here, an important distinction between two ways of viewing happiness has to be made.

As already stated briefly in the introduction, continual, trait happiness and momentary, state happiness differ. For happiness to fulfil the criteria of a trait, it has to possess temporal stability, cross-situational consistency, and inner causation (Veenhoven, 2005). Thus, there are two explanations for happiness on a trait level that refer to certain stability over time. Firstly, happiness can be viewed as a temperamental disposition referring to genetic predispositions, which, as already noted, account for about 50% of the variance of happiness (Csikszentmihalyi,

& Hunter, 2003; Lyubomisky et al., 2005; Veenhoven, 2005). Besides that, it is also argued for trait happiness as an acquired disposition alluding to a positive attitude acquired during the course of life especially in adolescence before the age of 18 (Lieberman, 1970; Veenhoven, 2005). In contrast, state happiness takes situational fluctuations into account. By this, it is meant that positive events in an individual’s life have the effect of increasing happiness momentarily (Csikszentmihalyi, & Hunter, 2003). Schwartz and Strack (1999) for example, pointed out that even seemingly insignificant events like for instance the winning of a favoured football team may have a positive effect on one’s well-being. However, the attributed value certain events have is strongly dependent on the person’s frame of reference. Hence, the personal meaning such events have to a person is a decisive determinant in the appraisal of its value (Csikszentmihalyi, & Hunter, 2003). Findings by Csikszentmihalyi and Hunter (2003) suggest for state happiness that fluctuations depend on the activities one executes. Accordingly, educational activities were found to be associated with below-average scores of happiness.

Recreational and social activities on the other hand predicted an increase of happiness to levels above average (Csikszentmihalyi, & Hunter, 2003). This could be confirmed by more recent findings (Howell, Chenot, Hill, & Howell, 2011). Howell and colleagues (2011) for instance pointed out the role need satisfaction plays in state happiness. Thus, happiness was found to be associated with the satisfied needs for autonomy and relatedness. This is in line with previous findings as autonomy plays a major role in the reduction of stress especially in recreational activities (Chang, & Yu, 2013; Csikszentmihalyi, & Hunter, 2003; Howell et al., 2011).

Concerning the need for relatedness respecting social activities, the relationship is self-evident.

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Extraversion

Closely tied to the need for relatedness and participation in social activities is the personality trait extraversion. Hence, the concept is to be defined by a preference for participation in social events (Argyle, & Lu, 1990b). Moreover, extraverted individuals share high levels of positive affect, confident behaviour, decisive thinking, and need for social attention (Wilt, & Revelle, 2017). This is accompanied by a need for affiliation and a warm, sociable, and interested attitude (Csikszentmihalyi, & Hunter, 2003; Lucas, 2001).

Additionally, extraverts are more sensitive to rewards than their introverted counterparts, who show higher sensitivity to punishment and frustrative non-reward (Canli, 2006; Gray, 1970).

As a consequence, extraverted individuals show lower levels of neuroticism as they shift their view on more positive aspects of life (Canli, 2006). This also manifests itself in more adaptive coping styles like for instance social support seeking (Amirkhan et al., 1995). However, the need for social attention plays a more central role in extraversion than reward sensitivity (Ashton, Lee, & Paunonen, 2002). Following this, extraverted individuals also show more suitable cognitive abilities for social interaction like facial recognition for example (Li et al., 2010).

As part of the Big Five Model, extraversion plays a decisive role in the appraisal of an individual’s personality (Sharpe, Martin, & Roth, 2011). This can be traced back to the early 20^th century when early analytical psychologist Carl Jung started to distinguish between introverted and extraverted personalities (Jung, 1921). Here, he made the differentiation that extraverts are externally focused while introverts are internally focused (Jung, 1921). As stated in a paper by Vukasović and Bratko (2015) is an individual’s level of extraversion is by a slightly larger amount learned than genetically determined. Therefore, extraversion seems to increase over time (Twenge, 2001). For this, findings by Scollon and Diener (2006) indicate, that these changes are to a large extent caused by an increase of social interaction during one’s lifetime caused by occupational as well as romantic relationships. The same paper suggests that these changes are unmediated by age so that the increase of trait extraversion is relatively stable over an individual’s lifetime.

As well as happiness, extraversion also comprises of a state and trait component (McNiel, Lowman, & Fleeson, 2010). Accordingly, state extraversion includes temporary extraverted behaviour, while trait extraversion is more consistent over time (Lischetzke, Pfeifer, Crayen, & Eid, 2012). For this, McNiel and colleagues (2010) found that a temporary manipulation of extraversion results in an increase of positive affect by approximately one

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standard deviation. Yet, this effect does not occur when extraverted individuals are alone (Lucas et al., 2008). However, as state extraversion has not yet been studied extensively, research lacks further findings that would serve the purpose of this study.

Association between Happiness and Extraversion

As happiness or subjective well-being determine by definition an individual’s level of positive affect, there is a tremendous amount of literature supporting the decisive role of extraversion in this relationship (e.g. Allik, & Realo, 1997; Charles, Reynolds, & Gatz, 2001;

Costa, & McCrae, 1988; Furnham, & Cheng, 1997; McNiel et al., 2010; Pavot et al., 1990).

Thus, the association between both traits is suggested to be moderate and significant (Furnham,

& Cheng, 1997). According to Srivastava, Angelo, and Vallereux (2008), this is reasoned by the mediating effect of social interaction on happiness. Thus, as extraverted individuals interact more actively with their environment the effect is, therefore, more apparent than in their introverted counterparts (Srivastava et al., 2008). However, these findings only relate to the trait level of extraversion and happiness. In the context of the present study, previous findings, if applied on a state association, could mean that if an individual displays momentary extraversion, happiness levels would rise too. Accordingly, on social occasions, individual happiness levels would be higher than on occasions in which an individual is alone. However, tangible findings in this domain are only limited to certain facets of extraversion.

Csikszentmihalyi and Wong (1991) for instance found out that momentary positive affect is associated with feeling sociable (Csikszentmihalyi, & Hunter, 2003; McNiel et al., 2010).

Moreover, Howell and colleagues (2011) suggest that need satisfaction plays a decisive role in state happiness. Thus, besides the satisfaction of the need for autonomy, relatedness plays a crucial role as well (Howell et al., 2011; Sulea et al., 2015). Nonetheless, an association between happiness and extraversion on a state level with all its facets has not yet been investigated sufficiently.

Current Study

The present study serves the aim of gaining insights into the relationship between happiness and extraversion on a state level. Therefore, both constructs will be related to each other to investigate the strength of the association on a daily basis. Here, it is hypothesized that a positive association between both constructs will be found. Accordingly, it is assumed that

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when people feel happy at the moment, they also perceive themselves as more extraverted and vice versa, which will assumingly result in a moderate and significant association. Moreover, it will be examined whether the association between happiness and extraversion is best described by a state-like or a trait-like association. For this, it is hypothesized that the association on a state level will be stronger than the trait association.

Methods Participants

The present study was based on a sample of 33 participants. The final dataset included students from the University of Twente and participants that enrolled through an online link that was spread via the messaging app WhatsApp and social media platforms. Initially, the sampling strategy aimed at students as the target group, but it was adapted to a broader range of young adult participants to increase the statistical power of the inferences. The sample consisted of male (N = 8) and female (N = 25) participants with an age ranging from 19 to 25 (M = 21.3; SD = 1.3) and a mainly German cultural background (NGerman = 32; NOther = 1).

Moreover, different occupational backgrounds were covered as well (NStudent = 20;

NStudentAndWorking = 11; NOther = 2). Inclusion criteria incorporated an age of at least 18 years and a sufficient comprehension of English texts. Moreover, participants had to either possess an Apple or Android phone and be able to download and use the Ethica application. Participants who did not fulfil these criteria or displayed suspicious answering patterns were excluded.

Materials

The online survey was created with Ethica, an online survey tool adapted for smartphone use. As the study at hand was part of a bigger research, items not related to the initial aim of this study were incorporated in the test battery as well. The whole test battery included six daily state items and four trait questionnaires. However, as they are only partially relevant for the aim of this study, only the questionnaires associated with the purpose of this study will be described in detail. Therefore, the trait questionnaires consisted of items from the Big Five Aspect Scales (BFAS) (DeYoung, Quilty, & Peterson, 2007) and the AB5C Personality Inventory (Bäckström, Larsson, & Maddux, 2009; Mitchelson, Wicher, LeBreton, & Craig, 2009; Tedone, n.d.). For the state items, three self-made questions were utilised and adapted to the Experience Sampling Method with two items for extraversion and one for happiness.

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Ethica

Ethica v.152 (ethicadata.com) is an online intervention and survey tool that focuses on smartphones as devices for collecting scientific data. Therefore, it is available for Android and Apple phones. The system uses a certain trigger mechanism, which enables data collection on specific occasions making it suitable for Experience Sampling. For the present study, four timeframes per day on seven consecutive days were chosen (see Appendix A). This enabled the collection of a sufficient amount of data and kept the burden on participants due to the possible intrusiveness of the method as low as possible.

Trait Questionnaires

Trait Happiness. To assess the participants’ levels of trait happiness, the subscale named Happiness was taken out of the Abridged Five Factor Circumplex Model (AB5C) (see Appendix B) (Bäckström et al., 2009; Mitchelson et al., 2009; Tedone, n.d.). This included ten items, which were to be answered on a 5-point Likert-scale ranging from one (very inaccurate) to five (very accurate), while five items had to be reversed before scoring (see Appendix B).

Items included for example “I feel comfortable with myself” and “I feel threatened easily”

(Tedone, n.d.). In terms of psychometric properties, the subscale shows good internal consistency (α = .84) and acceptable structural validity (Bäckström et al., 2009; Tedone, n.d.).

Trait Extraversion. For the conceptualisation of trait extraversion, items have been derived from the Big Five Aspect Scales (BFAS) (see Appendix C) (DeYoung et al., 2007).

Here, the subscale for extraversion incorporated measures of enthusiasm and assertiveness with ten items each of which nine items were reversely scored. Thus, the measure consisted of 20 items, which were to be answered on a 5-point Likert scale ranging from one (very inaccurate) to five (very accurate) (see Appendix C). With respect to psychometric properties, the subscale displays good internal consistency for different samples of university students (α = .86 - .88).

Moreover, factor loadings for positively scored items were in a range from .46 to .71 (M = .61) and for reversely scored items between -.62 to -.44 (M = -.56).

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State Questionnaire

To investigate the state components of extraversion and happiness, three items were designed by the researcher. This was done because no questionnaires referring to state happiness and extraversion, initially designed for experience sampling, had been proposed yet.

Therefore, two items have been related to state extraversion while the remaining referred to state happiness. Items for extraversion were “I feel extraverted/sociable at the moment” and “I feel a need to withdraw right now”. For happiness, the item included “I feel happy at the moment”. Each item was to be answered on a 5-point Likert scale with one accounting for “very inaccurate” and five for “very accurate” (see Appendix D). As these items were self-made, there have not yet been investigations concerning the psychometric properties. Thus, data from the trait questionnaires will be used for a validation of the latter, which will be outlined in the data analysis section.

Design and Procedure

To investigate real-time fluctuations of happiness and extraversion, the Experience Sampling Method has been utilised. The longitudinal online survey served the purpose of relating state happiness to state extraversion by also drawing inferences from the assessment of the regarding traits. Ethical approval has been granted by the Behavioural, Management, and Social Sciences (BMS) Ethics Committee of the University of Twente (Request-Nr: 200371).

Participants have been recruited through the internal Test Subject Pool BMS of the University of Twente with a convenience sampling strategy. Additionally, a link leading to the study has been spread through diverse social media platforms like WhatsApp. Participants enrolled through the Test Subject Pool BMS received an incentive of one credit as compensation for their efforts, while for participants outside the University of Twente no compensation could be provided.

The study was conducted over eight days. On the first day, participants enrolled in the study and got all the necessary information for their participation. This included a consent form, contact details of the researchers, and general information about the study. Next, demographics including age, gender, nationality, and occupation were requested, followed by an assessment of the trait domains of happiness and extraversion (see Appendix B and Appendix C for the trait questionnaires). On the consecutive seven days, measurements were made on four occasions per day (9 am – 10 am, 12 am – 1 pm, 4 pm – 5 pm, 8 pm – 9 pm) (see Appendix D

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for the state items relevant to the present study). To remind the participants of answering the surveys, a random trigger in the regarding timeframe plus an additional reminder 30 minutes later were set up before the surveys expired after one hour (see Appendix A). To eliminate possible disturbances during the data collection, a one-week pilot test was conducted. However, as no issues could be found the initial set-up was used for the study.

Data Analysis

For the data analysis, IBM SPSS Statistics 26 has been utilised. Participants being younger than 18 years, having a response rate below 60% were excluded. The reasoning behind the 60% cut-off was on the one hand to collect a sufficient amount of data and on the other hand to exclude participants who were well below the mean response rate (MResponses = 66%) (Conner,

& Lehman, 2012). Moreover, suspicious answering patterns were excluded. To elaborate, there were no fixed criteria for suspicious answering patterns, nonetheless, frequencies of given answers were checked per participant. Next, descriptive statistics were calculated for demographic properties of the sample including age, gender, type of occupation, and nationality. After that, the means and distributions of the state scores were investigated. For state happiness and state extraversion, person mean scores (PM) throughout the study were calculated to account for inter-individual differences between the subjects. Moreover, person mean-centred scores (PM-centred) were computed to examine the daily fluctuations of state happiness and state extraversion by relating the latter to the PM scores, which enabled within- subject analyses. This served the purpose of separating between-subject associations from within-subject associations to allow analyses on different levels on which it will be elaborated later (Smir, & Zohar, 2008; Van den Pol, & Wright, 2009).

Next, the psychometric properties of the measurement tools (AB5C & BFAS) were assessed. Thus, Cronbach’s Alpha has been utilised to compute reliability coefficients of the trait questionnaires. An alpha >.9 is regarded as excellent, >.8 is good, >.7 is acceptable, >.6 is questionable, >.5 is poor and values below .5 are regarded as unacceptable (Gliem, & Gliem, 2003). As the items for the state questionnaire had not yet been psychometrically investigated, Pearson’s correlations have been computed for state happiness and the items from the AB5C as well as for state extraversion and the BFAS. To elaborate, the state PM scores were correlated with the regarding trait scores to validate the measurement tool. Here, coefficients >.9 are regarded as very high, >.7 as high, >.4 as moderate, and values below .4 as low (Csikszentmihalyi, & Larson, 2014; Schober, Boer, & Schwarte, 2018; Taylor, 1990).

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Additionally, reliability coefficients for state measurements were computed. Hence, as the state scores were assessed by one item for happiness and two for extraversion, split-half reliability was investigated by utilising the Spearman-Brown Test (Eisinga, Te Grotenhuis, & Pelzer, 2013). For the interpretation of the coefficients, the previously introduced criteria by Schober and colleagues (2018) and Taylor (1990) were taken. As the association between trait happiness and trait extraversion has been frequently confirmed by diverse scholars, it was also checked if this can be supported by this paper. Here the criterion for significance was the .05 interval.

Lastly, a multigroup Linear Mixed Model (LMM) analysis served the purpose of examining whether the relationship between happiness and extraversion is best described by a trait-like (between-subject) or a state-like (within-subject) association (Smir, & Zohar, 2008;

Van den Pol, & Wright, 2009). Here, standardized z-scores were utilised for state happiness (PM-centred) as the dependent variable (DV) and PM extraversion and PM-centred extraversion as fixed independent variables (IV). The reason behind this methodological choice is that a LMM can handle data with two random components referring to on the one hand the sampling of persons and on the other hand repeated measurements per person (Smir, & Zohar, 2008). The criterion for significance was the .001 interval and for visual representations of the data, Microsoft Excel has been utilised.

Results Participant Flow

In total, 53 participants enrolled in the present study. Three participants have been excluded as they either did not fulfil the inclusion criterion of being at least 18 years old or had an age that deviated too strongly from the sample’s mean (~19 SD above the mean). Even though a high age has not been previously selected as an exclusion criterion the regarding cases were excluded as it is assumed that the participants are in a different stage of life which might impact their emotional perceptions (Twenge, 2001; Veenhoven, 2005). Next, checks for suspicious answering patterns by utilising frequency tables were executed and no unusual responses could not be found. Moreover, 17 participants were excluded as they responded to less than 60% of the state items. By examining the defining properties of the participants excluded due to their response rate, a quite distinct picture was drawn. Thus, the missing data was MNAR (Missing Not At Random), so missing data could especially be observed in participants with comparatively low state scores for both state happiness and state extraversion

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(Donders, Van Der Heijden, Stijnen, & Moons, 2006). This might have had the effect that participants low in state happiness and extraversion are underrepresented as they violated an inclusion criterion. For a visual representation of this observation Figure 2 (high scores), Figure 3 (medium scores), and Figure 4 (low scores) may be taken into account. Finally, a dataset of 33 participants was used for the analysis.

Descriptive Statistics

Table 1 displays descriptive statistics for trait extraversion and trait happiness including minima, maxima, means, and standard deviations. By utilising the Shapiro-Wilk Test it was found out that trait scores for extraversion and happiness are both normally distributed, which was also confirmed by visual analyses (Mudholkar, Srivastava, & Thomas Lin, 1995).

Moreover, the sample appears to incorporate more happy individuals with a score higher than one SD above the mean (21%) than extraverted individuals (18%). However, there are also more individuals with a happiness score lower than one SD below the mean (18%) in comparison to individuals low in extraversion (15%). This shows that the distribution of happiness scores appears to have a larger spread than the extraversion distribution.

Concerning the scales’ psychometric properties, it has been shown that both scales display good internal consistency (αHappiness = .84; αExtraversion = .88). Pearson’s correlational analyses have been utilised between the trait and PM state scores in order to assess the criterion validity of the state measurements. For extraversion, a low non-significant correlation has been found (r = .298, p = .092), which also accounts for happiness (r = .224, p = .211). With regard to split-half reliability according to the Spearman-Brown Test, however, both state measurements showed high coefficients (ρHappiness = .724; ρExtraversion = .712).

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Table 1

Descriptive Statistics for Trait Extraversion (BFAS), Trait Happiness (AB5C) and State PM- Scores

Variable Minimum

(scale minimum)

Maximum (scale maximum)

M SD

BFAS 51

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98 (100)

73.09 10.39

AB5C 24

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45 (50)

34.76 5.47

State Extraversion PM 1.88 (1)

4.81 (5)

3.50 .57

State Happiness PM 2.81 (2)

4.58 (5)

3.77 .45

Association between Trait Scores

The association between the trait scores taken from the BFAS and the AB5C is low but significant (r = .361, p = .039. For visual representation purposes (see Figure 1) standardised z- scores were calculated to simplify the comparison of scores.

Figure 1

Standardised Trait Scores per Participant arranged by Trait Happiness z-scores.

-3 -2 -1 0 1 2 3

25608 26094 26396 25671 26078 26095 26082 26093 26318 26057 26075 26052 26054 26076 26098 26060 26081 26088 26105 26059 26286 26056 26091 26142 26314 26134 26077 26114 26161 26290 26051 26087 26062

Standardised Trait Score

Participant ID

zTrait Happiness zTrait Extraversion

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Inferential Analysis

Lastly, an LMM has been applied to explore whether the relationship between happiness and extraversion is a within-person (state-like) or between-person (trait-like) association. Thus, standardised z-scores have been employed to check if state happiness (PM-centred) is best described by state extraversion PM (trait-like association) or state extraversion PM-centred (state-like association). As analyses have shown, a state-like association is most applicable in this case. Hence, state extraversion (PM-centred) shows a moderate and significant association with state happiness (PM-centred) (β = .523, SE = .031, p<.001), while the association with PM scores is low and non-significant (β = .013, SE = .029, p = .657). To illustrate the association between state scores, Figure 2 depicts raw state scores for happiness and extraversion for a participant (Nr. 25608) with high state scores chronologically sorted per occasion. Figure 3 represents state scores for a participant (Nr. 26077) with medium state scores for both concepts and Figure 4 displays state scores for a low-scoring participant (Nr. 26161). Here, it is observable that the low-scoring participant filled out way fewer surveys than the medium and high-scoring counterparts.

Figure 2

State Happiness and State Extraversion Raw Scores for Participant Nr. 26161

Note. Scores for Day 1: Morning and Day 6: Evening are missing because the surveys have not been filled in by the participant.

0 1 2 3 4 5 6

Day 1: Morning Day 1: Noon Day 1: Afternoon Day 1: Evening Day 2: Morning Day 2: Noon Day 2: Afternoon Day 2: Evening Day 3: Morning Day 3: Noon Day 3: Afternoon Day 3: Evening Day 4: Morning Day 4: Noon Day 4: Afternoon Day 4: Evening Day 5: Morning Day 5: Noon Day 5: Afternoon Day 5: Evening Day 6: Morning Day 6: Noon Day 6: Afternoon Day 6: Evening Day 7: Morning Day 7: Noon Day 7: Afternoon Day 7: Evening

Raw Score

State Happiness State Extraversion

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Figure 3

State Happiness and State Extraversion Raw Scores for Participant Nr.25608.

Note. Scores for Day 2: Afternoon, Day 4: Morning and Day 7: Morning are missing because the surveys have not been filled in by the participant.

Figure 4

State Happiness and State Extraversion Raw Scores for Participant Nr.26077

Note. Scores for Day 1: Afternoon, Day 3: Noon, Day 3: Afternoon, Day 4 Morning – Day 4:

Evening, Day 5: Afternoon, Day 5: Evening and Day 7: Evening are missing because the surveys have not been filled in by the participant.

0 1 2 3 4 5 6

Raw Score

0 1 2 3 4 5 6

Raw Scores

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Discussion

The purpose of the study at hand was to gain a better understanding of the relationship between happiness and extraversion on a daily level. Therefore, it has been investigated how happiness and extraversion states fluctuate over the course of one week by making four measurements per day. Moreover, trait levels of the participating individuals have been assessed as well. This had several purposes ranging from on the one hand a validation of the state items and on the other hand to critically evaluate previous findings by scholars respecting the association of both concepts on a trait level. Concerning the validation of state measurements, low non-significant correlations were found, whereas previous findings regarding the positive association of happiness and extraversion trait scores could be mostly confirmed (Furnham, & Cheng, 1997).

In terms of the association of state scores, the present study found the strongest association between state happiness (PM-centred) and state extraversion (PM-centred). This confirmed the hypothesis that findings for the trait association can be confirmed on a state level (Furnham, &

Cheng, 1997). Nonetheless, when taking the PM-scores into account a different picture is drawn. Thus, a significant association between state PM-scores of happiness and extraversion could not be found.

State Association

As the purpose of the present study was to gain a better understanding of the association between happiness and extraversion on a state level the following section will consist of a critical evaluation of the findings. Generally spoken, the hypothesized association between state scores can be accepted. Thus, a state-like association was found between state happiness (PM- centred) and state extraversion (PM-centred) with a moderate and significant association.

Respecting previous research tackling the association of happy and extraverted states, as in McNiel and Fleeson (2006), the same observation was made. Here, however, extraverted states were manipulated by instructing individuals to act extraverted. Nevertheless, these previous findings can be confirmed by the present observational study in daily life. Moreover, different findings suggest that the relationship between trait extraversion and trait happiness is to a certain extent mediated by extraverted and happy states (Wilt, Noftle, Fleeson, & Spain, 2012). To elaborate, these findings introduced a dynamic mediation model that tries to explain the interaction of happiness and extraversion on a state and a trait level in a unique model (Wilt et al., 2012). Hence, trait extraversion causes extraverted states, which predict happy states

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which impact trait happiness scores. As well as in the present paper, the association between state extraversion and state happiness is the strongest. However, trait extraversion is also associated with trait happiness and state happiness, while state extraversion is also directly related to trait happiness with a low association.

Operationalisation of States

As the present study contained state measurements that have not been validated yet, a psychometrical investigation of the latter was the first step of the data analysis. Here, findings show that the items might display high levels of reliability, whereas the criterion validity of the subscales was below an acceptable threshold (Csikszentmihalyi, Larson, 2014; Gliem, &

Gliem, 2003). This sends an ambiguous message, as the phrasing of the items (“I feel happy at the moment”; “I feel extraverted/sociable at the moment”) specifically refers to the regarding concepts by simultaneously seeming to be internally consistent. However, by correlating the items to the matching trait assessments a different picture is drawn. As the validity coefficients display small values there are two possible ways of interpreting these findings. On the one hand, the items could have been created poorly and on the other hand, trait scores reflect something different than the sum of happy moments in a certain period.

For the first claim, it is hard to test whether the differences in trait and state scores are reasoned by a poor phrasing of the items as this would extend the analytical scope of the present study. Nevertheless, the phrasing of the state items is quite distinct (“I feel happy at the moment”; “I feel extraverted/sociable at the moment”) and shows good face validity when being related to the trait items (“I look at the bright side of life”; “I make friends easily”) (DeYoung et al., 2007; Holden, 2010; Tedone, n.d.). Even though these examples show that the phrasing is not the same they still seem to be linked in a general manner with specifics referring to a state or trait being measured. However, specifically for extraversion, the state items do not refer to the assertiveness component of extraversion as apparent in the following example of a trait item (“I see myself as a good leader”) (DeYoung et al., 2007). This might have had the effect that only a certain extent of extraversion has been captured with the state items, which could have violated their validity.

The second explanation, however, referring to general differences in trait and state scores seems sensible on the background of previous findings. According to Latent State-Trait Theory, a state measurement depends on an individual’s personal characteristics (trait), the

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characteristics of the situation, and the interaction of both (Steyer, Schmitt, & Eid, 1999). As the characteristics of a situation, as well as their estimations, differ it may cause difficulties, as in this case, to relate trait and state scores to each other. Spoken in the words of Gestalt psychologist Kurt Koffka this means “the whole is other than the sum of its parts” (Wong, 2010). Here, the “whole” refers to trait scores while “the sum of its parts” refers to average state scores over the course of one week. So, for the present research, a happiness/extraversion trait score consists of more than just the sum of happy/extraverted situations (Anastasi, 1983; Steyer, Schmitt, & Eid, 1999). This is also reflected in a paper by Schmitt and Steyer (1993) on the Latent State-Trait Model, where the point is made that situation and interaction effects only display a small portion of the variance of a trait score. However, this paper refers to social desirability as construct but remarks that the model as whole can be applied to various psychological phenomena.

An additional remark includes the unclear disaggregation between traits and states (Allen, & Potkay, 1981; Steyer et al., 1999). Therefore, there has not yet been found a psychometric procedure to ensure that a trait measurement does not include a certain state component referring to the situation in which the trait assessment has been executed. To elaborate, while an individual is in a certain state when executing the trait assessment, each state measurement reflects a different state. Nevertheless, the impacted trait assessment is seen as fixed which might lead to discrepancies in the association. For instance, an individual that just experienced trouble at work would have lower trait happiness scores than the same individual would have if it did the same test on another occasion. To account for this, one could refer to the state PM-scores to diminish the situational influence of the occasion in which the trait assessment has been executed. This would solve the previously mentioned issue, but by referring back to the Latent State-Trait Model it is apparent that such a solution does not sufficiently reflect a trait score (Anastasi, 1983; Steyer, Schmitt, & Eid, 1999). Thus, a state does not only consist of the average of happy moments, which is also reflected in the finding that this paper could not associate trait scores with state PM-scores.

Trait Association

As the association between happiness and extraversion on a trait level has been replicated extensively in the past, the present paper also aimed at confirming this relationship.

Findings from the paper at hand indicate a weak but significant correlation. This sufficiently reflects previous findings regarding the association of both concepts. In a paper by Francis

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(1998) for instance, a weak significant correlation was found for an assessment with the Oxford Happiness Inventory and the extraversion dimension derived from the Revised Eysenck Personality Questionnaire. Furthermore, in a paper published by Hills and Argyle (2001) utilising the same measurement tools as in Francis (1998), a moderate association was found.

As expected, data from the sample at hand could mostly replicate previous findings.

Corona Situation

Through the worldwide spread of the SARS-CoV-2 virus in 2019, people all around the world had to adapt their lifestyles to the demands of the pandemic. As governmental regulations included social distancing resulting in a deprivation of social contacts, it was expected that extraversion scores would slightly decrease due to a lack of situations to exert extraverted behaviour. Besides that, it was also estimated that changes in lifestyle and partial restrictions of social activities would also negatively affect happiness scores.

For happiness, the expected decline is mainly based upon a recent paper by Yang and Ma (2020). Here it is stated that in China for instance “the onset of the coronavirus epidemic led to a 74% drop in overall emotional well-being” (Yang, & Ma, 2020). When comparing average trait happiness scores with previous literature, this observation gets verified (Morris, Burns, Periard, & Shoda, 2015; Yang, & Ma, 2020). Hence, the average trait happiness scores in the present paper deviate by 72% from previous findings by Morris and colleagues (2015).

Concerning extraversion, findings by Sutin and colleagues (2020) cannot confirm the previously assumed minor decreases in extraversion trait scores. By taking the present data and previous research by DeYoung and colleagues (2007) on a student sample into account, it is revealed that indeed extraversion trait scores slightly increased (+8%) in the course of the pandemic.

These deviations from the usually found scores in happiness and extraversion and the strong differences in deviations from the norm might have had a strong impact on the inferences drawn from the data at hand. Accordingly, associations of happiness and extraversion with the present data were lower than in comparable papers. This is reflected in a comparison with a paper by Furnham and Cheng (1997). Here, it is observable that the trait association in the present paper deviates by about 8% from earlier findings. For state scores, similar findings were expected. However, due to a lack of data from previous research on state associations, this expectation could not be proven. Moreover, the absent association between the trait and state

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PM-scores might also be at least partially explainable by the current situation through prevalent distressing situations. For instance, an increase in family conflicts, irritation, and anxiety might be responsible for the discrepancies in trait and state PM-scores (Peshave, & Peshave, 2020).

Practical Utility of Findings

As the findings from the present paper introduce a change in perspective regarding the perception of the association of happiness and extraversion, several psychological domains can benefit from the findings at hand. Especially in psychotherapeutic settings, a focus on the creation of extraverted states may have a positive effect on happiness (McNiel et al., 2010).

However, as the findings of this paper do not allow for causal inference, claims about the practical utility have to be formulated tentatively. Thus, no direct recommendations can be made about a suitable procedure in which the findings can be placed. However, especially interventions aiming at an increase of wellbeing through adaptions in social interaction like for instance treatments for social anxiety can benefit from the present findings (Naragon-Gainey, Watson, & Markon, 2009). To elaborate, several small interventions over a day focusing on an increase in state extraversion can positively impact situational happiness, which according to Wilt et al.’s (2012) Dynamic Mediation Model, consequently, affects trait happiness (McNiel et al., 2010). The latter, however, could not be confirmed by the present paper. Therefore, this implication is still cautiously formulated as more research in this domain is necessary. Also, previous research has shown that by instructing individuals to act extraverted, a momentary rise in happiness can be achieved (McNiel et al., 2010). As previously mentioned do these intentional activities account for 40% of an individual’s happiness and especially activities with extraverted properties like acting sociable enhance one’s wellbeing decisively (Csikszentmihalyi, & Hunter, 2003; Lucas, 2001; Lyubomisky et al., 2005; Sheldon, &

Lyubomirsky, 2006).

Strengths and Limitations

In the following, the strengths and limitations of the present paper are going to be evaluated by starting with strengths. Therefore, both hypotheses could be confirmed as well as the association between trait scores. Thus, a moderate association was found between state scores, and the association between the concepts of happiness and extraversion was shown to be mainly state-like. This enables a shift in perspective, as previously both concepts were

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mainly considered on a trait-level (e.g. Furnham, & Cheng, 1997; Pavot, Diener, & Fujita, 1990). As previously mentioned, this shift of perspective can be of practical utility especially for psychological interventions aiming at an increase of happiness by intervening in state extraversion (McNiel et al., 2010).

Even though the present results support the association of happiness and extraversion on a state level, it is appropriate to recognize several potential limitations. Firstly, as the sample mainly consisted of university students in a narrow age range, the generalisability of the findings is limited to young adult university students. Secondly, the current situation plays a crucial role in evaluating the limitations of the present study. As previously mentioned, the data collection has been executed during a global pandemic, which led to decisive differences especially in trait happiness scores. For this, there are two possible perspectives on the findings.

First of all, one has to be tentative to generalise the present findings on times after or before the pandemic, as it has already been stated that there are certain deviations. Secondly, however, the results at hand also shed light on changes in happiness and extraversion during a pandemic.

Although this was not the initial aim of the study, it can be useful in understanding people’s emotional reactions to a global crisis.

Implications for Future Research

Based on the previously noted limitations, there is a set of recommendations for future research. Besides remarks about the generalisability of results, which do not play a decisive role in significantly improving the present paper, the current pandemic situation gives more reason for future research. Hence, a repetition of the present study on another occasion can be a sensible step to on the one hand get results that are not fixed to a crisis, and on the other hand, it would enable a comparison between crisis and post-crisis emotional states and traits.

Additionally, as it has been found that trait scores show no relation to the average state scores (PM) over a week, more investigation on the association of states and traits can be effective.

Moreover, a different phrasing of the state items could be a sensible step as well to account for the low criterion validity in the present study. Additionally, as it was found that low-scoring participants were partly excluded due to their low response rates, it is recommended to repeat the study with different exclusion criteria. Lastly, as the present findings potentially offer a new approach to certain psychotherapeutic procedures, more scientific efforts in the effectiveness of smaller, daily interventions have to be made.

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