Tell me who you are, and I will tell you how you feel?

European Journal of Personality

Eur. J. Pers. 24: 291–308 (2010)

Published online 21 October 2009 in Wiley InterScience

(www.interscience.wiley.com) DOI: 10.1002/per.743

*H

C

Tell Me Who You Are, And I Will Tell You How You Feel?

NICOLE KAMPFE1* and KRISTIN MITTE2

1Department of Differential and Personality Psychology, FSU Jena, Jena, Germany2Institute of Psychology, University of Jena, Jena, Germany

Abstract

Surprisingly little is known about the suggested mediator role of emotional intelligence and

mood-regulation regarding the relationship between personality and subjective well-being.

Three independent samples were administered to investigate whether EI and mood-

regulation served as mediators for subjective well-being beyond personality. Using

structural equation modelling, the authors demonstrated the superior role of extraversion

and neuroticism in explaining satisfaction with life, happiness, positive and negative affect.

Consistent mediation effects were found for the trait meta-mood of repair. Contrary to

expectations, the remaining variables (attention, clarity, self-efficacy of affect regulation)

did not mediate the relationship between personality and well-being; neither did they show

substantial incremental validity in explaining variance in SWB. Results are discussed with

regard to methodological issues and practical implications. Copyright# 2009 John Wiley

& Sons, Ltd.

Key words: personality; mood regulation; subjective well-being; mediation; emotional

intelligence

INTRODUCTION

Subjective well-being (SWB) is one of the most relevant concepts in fundamental and

applied (positive) psychology. The large body of literature dealing with the

conceptualization and prediction of SWB is hardly manageable, and there are numerous

terms being used synonymously; terms such as happiness, satisfaction, psychological well-

being, emotional well-being and positive functioning, for example. A keyword search in

PsychInfo (January, 2009) resulted in 65 633 hits for ‘satisfaction’, 28 312 hits for ‘well-

being’ (subjective: 2004, psychological: 5357; emotional: 1521) and 6817 hits for

‘happiness’. This variety of synonymous key words is also reflected in different conceptual

approaches of SWB. Some authors define SWB merely as the frequent experiences of

pleasant rather than unpleasant affects, which is known as the hedonistic approach (e.g.

Correspondence to: Nicole Kampfe, FSU Jena, Department of Differential and Personality Psychology,umboldtstr. 11, Jena 07743, Germany. E-mail: [email protected]

opyright # 2009 John Wiley & Sons, Ltd.

Received 14 April 2009

Revised 10 August 2009

Accepted 20 August 2009

292 N. Kampfe and K. Mitte

Bradburn, 1969). Others emphasize on a eudaimonic perspective of individual self-

actualization and personal growth (Ryan & Deci, 2001; Ryff & Keyes, 1995). Again, others

conceptualize SWB as being a composite of two broad components, an affective and a

cognitive, with the affective aspect of SWB capturing the balance of positive relative to

negative affects, and the cognitive components reflecting the evaluation of one’s life, also

called life satisfaction (Diener, 1984; Schimmack, Schupp, & Wagner, 2008). We will

apply the latter conceptualization for the present research since it is comprehensive in

considering both, affect and cognition.

One of the most striking questions, pursued by well-being research, is how people reach

or maintain happiness and satisfaction and who those people are. In other words, positive

psychology aims to deduce the various reasons why some people seem to be happier or

more satisfied than others. As a result of intensive research from all psychological fields,

many relevant predictors of SWB have been introduced. Ryan and Deci (2001) for instance

list the following groups of antecedents of SWB: Socioeconomic factors, social factors

(e.g. relatedness) and concepts of goal pursuit (e.g. self-efficacy). However, by far the

strongest predictors of SWB are relatively stable individual features, the first and foremost

being certain aspects of personality as well as aspects of mood regulation.

PERSONALITY AND SWB

The best-confirmed and most relevant predictors of SWB are certain personality

characteristics, in particular extraversion and neuroticism. According to numerous

empirical studies, substantial positive associations were observed between extraversion

and the frequent experience of positive affects and well-being, whereas neuroticism was

repeatedly shown to be a stable negative predictor of indicators of SWB holding positive

relationships with the frequency of experiencing negative affect and clinically relevant

phenomena like depression and anxiety (Costa & McCrae, 1980; Lucas & Fujita, 2000, for

summaries see Lucas, 2008, or Watson & Clark, 1997). The results of a very recent meta-

analysis strengthened the meaning of especially extraversion and neuroticism for SWB

(Steel, Schmidt, & Shultz, 2008). Based on their meta-analytical results, Steel et al. (2008)

showed extraversion and neuroticism to be the over all strongest predictors for SWB

criteria explaining for instance 19% (29% disattenuated) and 29% (41% disattenuated) of

the variance of positive affect.

How can these relationships between personality and SWB be explained? Which are the

dynamic processes inter-linking both concepts? McCrae and Costa (1991) distinguish two

classes of theories: Instrumental and temperamental theories. According to the first,

personality has an indirect impact on SWB, for instance through the selection of certain

situations over other situations (e.g. high-risk sports amongst sensation seekers).

Temperamental explanations, on the other hand, suggest a direct linkage between

personality and SWB, e.g. due to differences in affective reactivity, reward or punishment

sensitivity and chronic level of affect (mood). Whereas, little evidence is available to

support the instrumental explanations, empirical tests of the temperamental explanation

(e.g. affective reactivity of neurotics or extraverts) seem promising, yet, approaches and

results quite mixed (Lucas & Baird, 2004). Although neither of the explanations have yet

been fully confirmed or ruled out, many studies on affective reactivity have shown

relationships between extraversion and reactivity towards positive affects on the one side

Copyright # 2009 John Wiley & Sons, Ltd. Eur. J. Pers. 24: 291–308 (2010)

DOI: 10.1002/per

Towards a process model of SWB 293

and between neuroticism and reactivity towards negative affects on the other side (e.g.

Canli, Sievers, Whitfield, Gotlib, & Gabrieli, 2002; Larsen & Ketelaar, 1989).

In line with the cited research, personality can be seen as a concept explaining individual

differences in how (affective) environmental stimuli are attended to and processed, which

itself is assumed to contribute to variance in SWB.

MOOD REGULATION AND SWB

A concept that is often mentioned together with SWB is mood or emotion regulation. It

refers to ‘all the extrinsic and intrinsic processes responsible for monitoring, evaluating and

modifying emotional reactions, especially their intensive and temporal features, to

accomplish one’s goals’ (Thompson, 1994, p. 27) or as ‘the ability to identify, understand,

express and respond effectively to the full range of human emotions’ (Rudd, Joiner, &

Rajab, 2001, p. 37). On that basis, an association between efficient mood regulation and

higher levels of well-being, especially regarding the affective components, is very evident.

People who are able to effectively maintain positive affects and/or to change negative

moods, should especially meet the affective SWB criteria compared to people less able in

regulating their moods and emotions. In fact, there is an immense amount of research

showing substantial relationships between mood regulation and indicators of SWB or the

lack of SWB (e.g. Catanzaro, Wasch, Kirsch, & Mearns, 2000; Garnefski, Kraaij, &

Spinhoven, 2001; Gross & John, 2003; Kokkonen & Kinnunen, 2006; Larsen & Prizmic,

2008; Phillips, Henry, Hosie, & Milne, 2006). In addition, there is also evidence regarding

the meaning of mood regulation for the cognitive components of SWB, for example life

satisfaction (e.g. Schimmack, Diener, & Oishi, 2002).

A widely known concept that comprises aspects of mood regulation is emotional

intelligence, which was introduced as the ability of individuals to perceive, understand,

assimilate and regulate their emotions (Salovey & Mayer, 1990). It is usually assessed with

tests measuring maximum performance rather than typical characteristics of a person.

However, besides the ability concept, a great number of studies conceptualize and measure

EI as trait rather than ability. Trait EI is defined as ‘a constellation of emotion-related self-

perceptions and dispositions, assessed through self-report’ (Petrides & Furnham, 2003, p.

40). Hence, the distinction between ability and trait EI basically points out to different

assessment approaches. Because the focus of the current research is on self-perceived

mood regulation, we apply the trait approach of EI. Since the introduction of the construct,

a number of different EI self-report measures have been developed (see Palmer,

Donaldson, & Stough, 2002 for an overview). One of the most widely used questionnaires

is the Trait Meta-Mood Scale (TMMS, Salovey, Mayer, Goldman, Turvey, & Palfai, 1995),

which assesses attention, clarity and repair—three reflexive processes accompanying

emotions and central aspects of emotional intelligence. Attention refers to perceived ability

to attend to affective states, whereas clarity describes the perceived ability to understand

and discriminate between different affective qualities. Repair, finally, reflects the perceived

ability to maintain positive and up-regulate negative moods (Salovey et al., 1995) and

hence particularly closely mirrors aspects of mood regulation.

As was shown for concepts of mood regulation, various studies have found significant

relationships between self-reported EI and indicators of SWB, for instance life satisfaction

(Ciarrochi, Chan, & Caputi, 2000; Gignac, 2006; Palmer et al., 2002), affect (Dawda &

Hart, 2000; Schutte, Malouff, Simunek, McKenley, & Hollander, 2002), health aspects


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(Austin, Saklofske, & Egan, 2005; Dawda & Hart, 2000; Salovey, Stroud, Woolery, & Epel,

2002) and stress reaction (Ramos, Fernandez-Berrocal, & Extremera, 2007; Slaski &

Cartwright, 2002), not only in adults but also in adolescents (e.g. Ciarrochi, Chan, &

Bajgar, 2001).

PERSONALITY, MOOD REGULATION AND SWB—A PROCESS MODEL

Mood regulation and emotional intelligence are themselves related to personality,

especially to extraversion and neuroticism (Ciarrochi et al., 2000; Davies, Stanov, &

Roberts, 1998; Dawda & Hart, 2000; Newsome, Day, & Catano, 2000; Warwick &

Nettlebeck, 2004; Wood, Heimpel, & Michela, 2003). Extraversion was shown to be

positively associated with understanding, perception and regulation of emotions (Ciarrochi

et al., 2000; Davies et al., 1998). For neuroticism on the other hand, positive relationships

have been found with dysfunctional mood regulation (Bolger, 1990; Gunthert, Cohen, &

Armeli, 1999; McCrae & Costa, 1986) as well as negative relationships with various

measures of EI (Dawda & Hart, 2000; Singh & Woods, 2008). The size of the correlations

between EI and personality varies considerably from study to study, and is usually slightly

higher for neuroticism compared to extraversion. Chamorro-Premuzic, Bennett and

Furnham (2007) observed correlations of .25 and .30 between EI extraversion and

neuroticism, respectively, whereas Dawda and Hart (2000) report correlations for the total

EI score from .52 (extraversion) to .72 (neuroticism). This variation might partly be

attributable to the measures used, since the studies clearly differ with regard to the

questionnaires applied to assess EI and personality. In fact, there are hardly two studies that

have utilized the same measures for both concepts.

Several studies have provided evidence for the utility of EI constructs by showing that EI

measures were incrementally valid in explaining SWB criteria over and above personality

traits such as extraversion and neuroticism (Chamorro-Premuzic, Bennett, & Furnham,

2007; Day, Therrien, & Carroll, 2005; Extremera & Fernandez-Berrocal, 2005; Petrides &

Furnham, 2001, 2003; Saklofske, Austin, & Minski, 2003; Shulman & Hemenover, 2006;

Singh & Woods, 2008). It can be assumed that EI is capable of explaining between 3 and

7% of the variance in the criteria after personality has been controlled for. Austin et al.

(2005), however, did not find trait EI to be incrementally valid over the Big Five in

explaining life satisfaction and other evaluative criteria of SWB. Obviously, there is

variation in the amount of variance in SWB criteria that can be additionally explained.

However, because all studies varied in the SWB criteria as well as in the chosen measures

of EI and mood regulation, the source of variation remains unclear. Given the larger

number of studies that showed EI to explain a small but significant amount of variance in

SWB beyond personality compared to those that could not show it, we conclude that EI is

incrementally valid for SWB over personality.

Although several studies have shown the link between personality, EI and SWB, a

mediational model was only seldom tested. It is however, important to understand, how

the personality–SWB relationship arises. The above-mentioned studies suggested that one

possible mechanism that produces this association is mood regulation. From a conceptual

point of view, the observed linkages between personality, mood regulation/EI and

SWB point therefore towards a process model of SWB with direct and indirect prediction

paths. Because personality reflects relatively stable individual characteristics, it can be

assumed to be the starting point of the model that predict the personal capacities to regulate


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one’s moods, which in turn should affect individual SWB. Nolen-Hoeksema, Larson, and

Grayson (1999, p. 1070) for instance discuss the possibility that regulatory variables ‘may

be the underlying cause of the relationship between personality variables and emotional

disorders such as depression and anxiety’. Unfortunately, only a small number of studies

have directly addressed the processes that interlink personality and SWB variables, among

which even less examined were mood regulation or EI as mediators. Abbott, Croudace,

Ploubidis, Kuh, Richards, and Huppert (2008), for example, showed that the negative

relationships between early neuroticism (age 26) and psychological well-being (age 52)

were significantly mediated by emotional adjustment, whereas for extraversion mainly

direct effects were observed. Testing constructive thinking as the mediating variable,

Harris and Lightsey (2005) revealed a small mediation effect for the relationship between

neuroticism and negative affect; no mediation of the relationship between extraversion and

positive affect, and generally no mediation for life satisfaction as criteria, due to a lack of

correlation with personality in the first step. Strong evidence for mediation effects of

happiness-increasing strategies (e.g. social affiliation or mental control) on the relationship

between the Big Five and happiness were observed by Tkach and Lyubormirsky (2007).

The authors conducted single structural equation models for each personality–strategy

combination, and found in most cases significant mediation effects. On average, the largest

proportions of variance in happiness was explained by the mediated neuroticism- (average

R2¼ .48) and extraversion models (average R2¼ .39). The authors however, did not

conduct a simultaneous mediation model that would (a) minimize the accumulation of a

error, and (b) allow for the investigation of mediation effects that were purified from

overlapping variance between variables. This seems highly interesting, since the regulation

strategies were positively correlated and yielded different relationships to the big five.

PRESENT RESEARCH

To summarize, a vast amount of research deals with the prediction of different indicators of

SWB. One of the best-established predictors is personality, particularly, neuroticism and

extraversion. However, rather little is known about the mechanisms that interlink

personality and SWB. There is preliminary evidence for a mediating role of concepts of

mood regulation or EI for the personality–SWB relationship. However, the available

studies have either examined only single concepts as mediators (e.g. constructive thinking,

Harris & Lightsey, 2005) or have not investigated the different concepts in simultaneous

models, (Tkach & Lyubormirsky, 2007). Moreover, they revealed quite mixed results: of

the three available studies that directly investigated the linkage between personality and EI,

two found evidence for mediation effect whereas the third found both, evidence for and

against mediation effects. Since all three studies used different SWB criteria (Ryff-

dimensions of SWB, satisfaction with life and happiness) as well as different mediators

(emotional adjustment, constructive thinking and happiness increasing strategies) in a

single sample, it is hard to say what the differences in their results are due to. As such, the

available research does also not provide information that would allow a comparison of

mediation models for the distinct definitory aspects of SWB, basically affective and

cognitive components. The present study aims at filling this gap by testing a process model

approach to SWB. Using three different samples, we collected data on neuroticism and

extraversion, different criteria for SWB (life satisfaction in Sample I; happiness in Sample

II, life satisfaction and positive and negative affect in Sample III) as well as different


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mediating variables (perceived EI and self-efficacy in affect regulation in Sample I and

Sample II, l self-efficacy in affect regulation in Sample III).

We utilized structural equation modelling to investigate the mediation models

simultaneously for the chosen variables within a sample. However, we calculated

separate models for perceived EI as mediators and self-efficacy in affect regulation as

mediators. This was done because of the conceptual differences of these constructs.

Whereas, perceived EI comprises the three trait meta-moods attention, clarity and repair,

self-efficacy in affect regulation particularly captures a person’s believe in how well in

general he or she is able to achieve the subjectively optimal mood state through regulation

(Larsen, 2000). Insofar, high regulatory self-efficacy could even be a result of high levels of

attention, clarity and repair, which would suggest a double mediation model. However,

high self-efficacy could also lead to higher levels in the trait meta-moods. Hence, treating

these four variables as mediating concepts of one and the same level does not seem

appropriate. Thus, in Sample I and II, two different mediation models are calculated, one

with the three trait meta-moods as mediators and one with self-efficacy as single mediator.

METHOD

Participants

Sample I

In the first sample were 467 participants (N¼ 248, 56.4% females) with a mean age of 26.4

years (SD¼ 10.4).

Sample II

The second sample comprised 348 participants (N¼ 186, 53.4% females) with a mean age

of 25.6 years (SD¼ 8.9).

Sample III

The last sample consisted of 679 individuals (students and non-students), of which 480

(68.9%) were female. Participants were on average 27.5 years old (SD¼ 10.3).

Measures

Sample I

Neuroticism and extraversion were assessed with the 12 items-subscales of the German

version of the NEO-FFI (Borkenau & Ostendorf, 1993). Perceived EI was assessed using

the German version of the Trait Meta-Mood Scale (TMMS, Otto, Doring-Seipel, Grebe, &

Lantermann, 2001). The TMMS consists of three subscales attention to moods (13 items),

clarity of moods (9 items) and repair (8 items). As a global measure of mood regulation, we

included the Self-Efficacy in Affect-regulation Scale (SEA, Mitte & Kampfe, 2007), which

comprises of 10-items (5 pro- and 5 con-traits, e.g ‘I know what I need to do to achieve my

desired mood in a situation’, ‘I have no idea how to influence my mood’). Finally, we

assessed Satisfaction with life as indicator for SWB using the German version of the

Satisfaction with Life Scale (SWLS, Diener, Emmons, Larsen, & Griffin, 1985), in which

five items are rated on a seven-point Likert scale.


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Figure 1. Example for Mediation Model (sample I). SWLS, satisfaction with life scale; a, direct effect ofpredictor on mediator; b, direct effect of mediator on criteria; c, direct effect of predictor on criteria; a�b, indirecteffect on criteria.


Sample II

Neuroticism, extraversion, perceived EI and self-efficacy in affect regulation were

measured as in sample I. To assess happiness, we utilized the four-item Subjective

Happiness Scale (SHS, Lyubomirsky & Lepper, 1999). Items are answered using a seven-

point scale.

Sample III

Again, neuroticism, extraversion, perceived EI, self-efficacy in affect regulation and life

satisfaction were assessed as in sample 1. As second SWB measure, we utilized the

Positive Affect Negative Affect Schedule (PANAS; Krohne, Egloff, Kohlmann, & Tausch,

1996) to obtain measures for general positive (10 items) and negative affect (10 items). On

a five-point scale ranging from 1 (‘never’) to 5 (‘very often’) participants indicate how

frequently they experienced each affect in general.

Structural equation modelling

To examine comprehensive mediation effects under the control of measurement error, we

conducted mediation models with all possible direct and indirect effects between the two

personality traits, the mediator(s) and the criterion/criteria. Each variable was estimated by

two parallel item parcels.1 Hence, we investigated latent variables and relationships that

were unconfounded by unsystematic variance. A graphic example for one of the mediation

models is given in Figure 1. For evaluation of the global model fit, we utilized the

x2- statistics, the ratio of x2 and degrees of freedom (df), the Root Mean Square of Error

1Whether one should use item-parcels or just items is a controversy issue in SEM methodology (Little,Cunningham, Shahar, & Widaman, 2002). Each procedure has its own advantages and disadvantages. In ourcase, the advantages of parcelling clearly weighted out its disadvantages. For a discussion see Little, et al. (2002).


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Approximation (RMSEA) and the Comparative Fit Index (CFI). For good model fit, the x2/

df ratio should be less than 2, the RMSEA should not exceed .05 and the CFI should be

larger than .95 (Schermelleh-Engel, Moosbrugger, & Muller, 2003). The relevance of

mediation is reflected by the size of the respective indirect effect, which is the product of

the direct effect between predictor (e.g. neuroticism) and mediator (e.g. clarity) as well as

between mediator and criteria (e.g. happiness). Whether the indirect effects and the total

effects reach significance or not is tested according to Kline (1998).

Structural equation modelling was conducted using AMOS 6.0.

RESULTS

Descriptive statistics and internal consistency of the measures in the three samples are

given in Table 1.

As a first step of the mediation analyses, the Pearson correlations between personality,

the mediator variables and the criteria are observed (Table 2). With only three exceptions,

the requirements for mediation are fulfilled. No mediation can be expected from TMMS

attention for the neuroticism–SWLS relationship in Sample I and Sample II because

attention is unrelated to neuroticism in both samples. Finally, the relationship between

extraversion and negative affect is not significant; hence no mediation effects are to be

examined here.

Next, we conducted the five different mediation models. Whereas, in the first two

samples, there is just one SWB criteria (life satisfaction in Sample I; happiness in Sample

II), Sample III comprises three criteria that are all investigated simultaneously. All models

reached acceptable to good fit with the data (see notes to Tables 3 and 4). The results of the

mediation analyses for meta-moods as mediators are reported in Table 3; Table 4 displays

the results for all three samples using self-efficacy in affect regulation as the mediator. The

dependent variables are depicted in columns; the predicting variables are depicted in rows.

Thus, by reading the tables by rows one follows the direction of paths in the SEM models

(whereas the indirect paths result from combining the two direct paths to the criteria).

Table 1. Descriptive statistics and internal consistency for the three samples

Sample I (SWLS) Sample II (SHS)Sample III (PA/NA

and SWLS)

M SD Rel. M SD Rel. M SD Rel.

Neuroticism 2.79 0.72 0.83 2.77 0.68 0.82 2.61 0.73 0.85Extraversion 3.25 0.62 0.77 3.29 0.64 0.83 3.41 0.57 0.77TMMS attention 4.33 0.65 0.86 3.85 0.61 0.96TMMS clarity 3.87 0.78 0.87 3.57 0.75 0.89TMMS repair 3.71 0.77 0.78 3.46 0.66 0.80SEA 3.92 1.13 0.87 4.24 1.13 0.90 4.31 1.07 0.85SWLS 3.82 1.16 0.90 5.22 1.04 0.84SHS 4.65 1.37 0.92Positive affect 3.31 0.60 0.81Negative affect 2.20 0.63 0.84

Note: TMMS, Trait-Meta-Mood Scale; SEA, self-efficacy in affect regulation; SWLS, satisfaction with life scale;

SHS, subjective happiness scale.


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Table 2. Latent correlations between the variables for the three samples

1 2 3 4 5 6

Sample I1 Neuroticism2 Extraversion �.35��

3 TMMS attention �.01 .36��

4 TMMS clarity �.35�� .29�� .46��

5 TMMS repair �.59�� .64�� .39�� .42��

6 SEA �.51�� .42�� .10 .34�� .52��

7 SWLS �.48�� .39�� .13� .18�� .54�� .30��

Sample II1 Neuroticism2 Extraversion �.52��

3 TMMS attention �.10 .33��

4 TMMS clarity �.38�� .33�� .42��

5 TMMS repair �.57�� .72�� .42�� .39��

6 SEA �.58�� .45�� .12� .50�� .59��

7 SHS �.67�� .74�� .24�� .42�� .75�� .59��

Sample III1 Neuroticism2 Extraversion �.26��

3 SEA �.51�� .31��

4 SWLS �.55 .32�� .33��

5 Positive affect �.24 .33�� .10� .35��

6 Negative affect .55�� .04 �.32�� .33�� .10�

Note: Model fit sample I: x2¼ 125.02, df¼ 56; p< .001; RMSEA¼ 0.051; NFI¼ 0.967; CFI¼ 0.981.

Sample II: x2¼ 128.66, df¼ 56; p< .001; RMSEA¼ 0.061; NFI¼ 0.958; CFI¼ 0.975.

Sample III: x2¼ 155.70, df¼ 39; p< .01; RMSEA¼ 0.066; NFI¼ 0.960; CFI¼ 0.969.

*p< .05, **p< .01.

Table 3. Results of mediation analyses for TMMS (samples I and II)

Attention Clarity Repair SWB criteriay

NeuroticismDirect effects .12�/.08 �.28��/�.29�� .42��/�.28�� .25��/�.25��

Indirect effects .00/�.01 .02/�.03 �.16�/�.10 �.14/�.14Total effect �.39��/�.38��

ExtraversionDirect effects .41��/.37�� .19��/.18� .49��/.57�� .10/.36��

Indirect effects �.01/�.03 �.02/.02 .18�/.19� .16/.19Total effect .26��/.54��

AttentionDirect effects �.02/.09ClarityDirect effects �.08/.10�

RepairDirect effects .37��/.38��

R2 .15/.11 .15/.17 .56/.56 .34/.71

ySample I: AV, satisfaction with life/Sample II: Subjective happiness. Model fit sample I: x2¼ 79.79, df¼ 39;

p< .001; RMSEA¼ 0.048; NFI¼ 0.974; CFI¼ 0.986. Sample II: x2¼ 91.59, df¼ 39; p< .001;

RMSEA¼ 0.062; NFI¼ 0.962; CFI¼ 0.977.

*p< .05, **p< .01.


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Table 4. Results of mediation analyses for SEA (all three samples)

Sample I/Sample II Sample III

SEA SWB criteriay SEA SWLS PA NA

NeuroticismDirect effects �.41��/�.48�� .40��/�.30�� .46 �.49�� .21�� .52��

Indirect effects .00/�.09 �.01 .05 .06Total effect �.39��/�.40�� .50�� .17�� .58��

ExtraversionDirect effects .29��/.19�� .25��/.50�� .19 .18�� .31�� .13��

Indirect effects .00/.04 .00 �.02 �.02Total effect .25��/.54�� .19�� .29�� .11�

SEADirect effects �.01/.19� .02 �.10� �.12�

R2 .33/.36 .28/.69 .30 .34�� .14�� .32��

ySample I: AV, satisfaction with life/Sample II: Subjective happiness.

Note: SWLS, satisfaction with life scale; PA, positive affect; NA, negative affect.

Model fit sample I: x2¼ 33.45, df¼ 14; p< .01; RMSEA¼ 0.063; NFI¼ 0.981; CFI¼ 0.989.

Sample II: x2¼ 37.39, df¼ 14; p< .01; RMSEA¼ 0.060; NFI¼ 0.981; CFI¼ 0.988.

Sample III: x2¼ 155.70, df¼ 39; p< .01; RMSEA¼ 0.066; NFI¼ 0.960; CFI¼ 0.969.

*p< .05, **p< .01.


Results of sample I showed that neuroticism was a significant positive predictor of

attention, while it negatively predicted clarity, repair and life satisfaction. Extraversion

positively predicted all three meta-mood variables but failed to directly contribute to the

criteria. The relationship of extraversion with SWLS was partially mediated by repair (b of

indirect effect¼ .18, p< .05). Repair also mediated the relationships between neuroticism

and SWLS (b¼�.16, p< .05). Attention and clarity did not function as mediators. Taken

together 34 per cent of the variance of SWLS could be explained by all the direct and

indirect effects. The latent correlations between the residuals of the TMMS were .46

(attention–clarity), .33 (attention–repair) and .23 (clarity–repair); they reached signifi-

cance at the .001-level. Without the mediators, neuroticism and extraversion still explained

28 per cent of the variance in SWLS. Thus, the TMMS accounted for 6 per cent incremental

validity.

Very similar results were obtained in Sample II where happiness was used as SWB

criteria. Again, neuroticism negatively predicted clarity, repair and happiness, while the

positive relationship with attention did not reach significance. Extraversion again directly

contributed to all three meta-moods and, in contrast to sample I, also to the SWB criteria.

Here, it even exceeded the effect of neuroticism. Moreover, repair was again found to

mediate the relationship between extraversion and happiness to a significant degree

(b¼ .19, p< .05). In sum, a total of 71 per cent of the variance of happiness could be

explained by the direct and indirect effects in the model. Neuroticism and extraversion

alone explained 66 per cent of the variance in happiness, indicating an increment of 5 per

cent due to the TMMS. Compared to life satisfaction (Sample I), personality and trait-meta

mood contributed considerably more to happiness. Mediation was only observed from the

trait meta-mood of repair. The residuals of attention and clarity correlated significantly

(r¼ .38, p< .001), such as the residuals of attention and repair (r¼ .30, p< .001). In

contrast to sample I, the latent correlation between the residuals of clarity and repair did not

reach significance.


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Self-efficacy of affect regulation was investigated in separate models for each of the

three samples. In none of them did it function as a mediator. It was directly predicted by

neuroticism (negatively) and extraversion (positively) and contributed significantly to

happiness (Sample II) as well as positive and negative affect (Sample III). The incremental

validity of the SEA was highest for happiness (3 percent, Sample II) and comparatively

lower for the remaining criteria (no increment was found for satisfaction with life in

Sample I and III; for positive as well as negative affect in Sample III, 1 per cent incremental

validity was observed. Moreover, the path loadings in Sample III suggest that individuals

higher in regulatory self-efficacy not only experienced less negative affect but also less

positive affect. The latter result is quite puzzling, and shows that the relationships amongst

the constructs are complex (the bi-variate correlation between SEA and PA was

significantly positive, r¼ .10, p< .05). However, the size of the effect is rather small. To

summarize results for the third sample, positive affect was best explained by the variables

in the model (R2¼ .34), followed closely by SWLS (R2¼ .32). For negative affect, only 14

per cent of variance could be explained. The residuals of positive and negative affect were

uncorrelated (r¼�.01, p> .05), such as those of negative affect and SWLS (r¼�.06,

p> .05). Finally, the correlation between the residuals of positive affect and SWLS was

significantly positive (r¼ .23, p< .001).

DISCUSSION

The present study was conducted to investigate a process approach to subjective well-being

using perceived emotional intelligence and self-efficacy in affect-regulation as mediators

between neuroticism, extraversion and different indicators for SWB. Using the data of

three different samples, we calculated five SEM models, in which latent predictor, mediator

and criterion variables were considered simultaneously. Our mediation analyses revealed

highly comparable results across samples.

First, we found generally small indirect effects that were mostly exceeded by the direct

effects. This was especially true for personality which showed substantial main effects on

SWB even after controlling for the mediators. Second, we consistently found a mediation

effect for the trait meta-mood of repair. When life satisfaction was considered as criteria,

repair mediated the relationships of neuroticism (negatively) and extraversion (positively)

with SWLS. For happiness, only the relationship with extraversion was mediated through

repair (positively). Thus, extraverted people seem to be happier and more satisfied with

their life because they more often repair their negative moods and regulate their feelings

into a positive direction. These highly important findings point out that mood repair is a

linkage between personality and SWB, as such they provide some evidence against pure

temperament theories of SWB. The results are most consistent with theories that postulate

temperamental and instrumental effects of personality on SWB. Hence, they offer a

possible starting point for change, because one could assume repair to be trainable, given

the high similarity between repair and classical techniques like positive cognitive

restructuring. Third, the trait meta-moods of attention and clarity had only small direct

effects on SWB: This was found when SWLS was used as the criterion as well as when

happiness served as SWB indicator. Nevertheless, the trait meta-moods together explained

between 5 and 6 per cent of the variance in happiness and satisfaction with life. These

results replicate earlier findings regarding the incremental validity of EI over and above

personality (Chamorro-Premuzic, Bennett & Furnham, 2007; Day et al., 2005; Extremera


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& Fern ndez-Berrocal, 2005; Petrides & Furnham, 2001, 2003; Saklofske, Austin &

Minski, 2003; Shulman & Hemenover, 2006; Singh & Woods, 2008). Given the fact that

similar mediation effects of repair were observed for cognitive aspects of SWB (SWLS)

and affective aspects (happiness), the heterogeneous findings of the available mediation

research might be attributable to the different mediators chosen rather than the criteria

(Abbott et al., 2008; Harris & Lightsey, 2005; Tkach & Lyubormirsky, 2007).

When self-efficacy in affect regulation was considered as mediator, we did not find

mediation effects for the personality–SWB relationship in any of the samples. In fact, for

SWLS it did not even reveal direct effects. For happiness however, it showed small

incremental validity. The results for the predicting of positive and negative affect were

quite surprising (Sample III). Contrary to the theoretical consideration and the observed bi-

variate relationship, the SEA was negatively associated with negative and positive affect in

the comprehensive model. Accordingly, when extraversion and neuroticism were

controlled for, higher levels of regulatory self-efficacy were weakly related to lower

levels of affect, regardless of its valence. Although the effect size was very small

suggesting a rather spurious finding, this result points out to a complex relationship pattern

amongst the variables in the model.

Why, however, is there a significant effect of repair of moods but no effect of the self-

efficacy in regulation one’s moods? One reason might be that repair particularly focuses on

restoring positive moods whereas the SEA scale assessed regulation towards the desired

mood, which might not always be explicitly positive (Kampfe & Mitte, 2009). Secondly,

while repair assesses mood regulation on a very concrete level (e.g. ‘When I become upset,

I remind myself of all the pleasures in life’), the SEA is a more abstract measure of

generalized regulatory self-efficacy (item examples can be found in the method section).

As such, it might share its SWB-relevant variance with broader concepts of personality and

hence, cannot contribute much more to the explanation of SWB over and above FFM

personality measures.

Taken together, the present results supported the overwhelming role that personality

plays for well-being whereby happiness could be explained far better than SWLS. A total

of 66 per cent of variance in happiness was attributable to personality alone. Hence,

particularly happiness is indeed ‘a personal(ity) thing’ (Weiss, Bates, & Luciano, 2008),

whereas SWLS, obviously, depends on other variables than those we have considered

herein. However, because only self-report measures were used, part of the explained

variance might be due to shared method effects. Multitrait–multimethod approaches using

peer-reports could be utilized to disentangle trait from method variance.

We must also not overlook the high possibility of other constructs or processes that

function as mediators between personality and SWB, for instance cognitive processes such

as memory or selective attention. Research examining whether personality is linked to the

processing of affective information has revealed rather inconsistent findings across

different cognitive tasks (Rusting, 1998; for meta-analytic findings for selective

information processing in anxiety, which is part of neuroticism and is one of the most

frequently investigated personality traits regarding this aspect, see Bar-Haim, Lamy,

Pergamin, Bakermans-Kranenburg, & van IJzendoorn, 2007; Mitte, 2008). This may

partially be due to the low reliability of these measures (e.g. regarding the emotional

stroop: Mauer & Borkenau, 2007; regarding the dot probe: Schmukle, 2005). Moreover,

Rusting (1998) reports more consistent results regarding the interaction of personality with

mood states on information processing as well as for an indirect link between personality

and information processing mediated through mood states. On the other hand, Robinson


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and Compton (2008) review a number of promising paradigms for investigating the

relationships between well-being and aspects of information processing, especially

selective attention, and priming. Moreover, motivational aspects seem highly relevant.

Latest research has shown that motives and their degree of realization in an individual

systematically mediated the personality–SWB relationships (Mitte & Kampfe, 2009).

In addition to the results of the mediation analyses, some direct relationships between

the concepts might be of interest as well, for example the relative independence between

neuroticism and attention. While clarity and repair are substantially related to personality

and SWB criteria, attention does neither relate substantially to neuroticism nor to the SEA.

It also shows only weak associations with the SWB criteria of satisfaction and happiness.

This might be surprising given the findings of significant relationships between neuroticism

and mood monitoring (positive) as well as mood awareness (negative, Swinkels &

Giuliano, 1995). However, the current results replicate the findings of other studies (Coffey,

Berenbaum, & Kerns, 2003; Wong, Oei, Ang, Lee, Ng, & Leng, 2007). One reason for the

lack of a relationship might be the fact that attention is assessed without referring to either

positive or negative mood states. However, from a well-being perspective it makes a clear

difference, whether one attends to positive or negative moods. In fact, being able to shift

one’s attention from negative to positive mood states is a functional way of coping (see

Connor-Smith & Flachsbart, 2007).

What do the present results tell us? There is a substantial relationship between

neuroticism, extraversion and indicators of well-being. Moreover, repair particularly

reveals a link to SWB and significantly mediates the personality–SWB relationship. Hence,

especially practical aspects of how a person can successfully regulate his moods at least

partially explain the association between certain personality characteristics and SWB.

Such practical strategies might be constructive thinking (Harris & Lightsey, 2005) or

mental control, direct attempts, affiliation, religion, partying and active leisure (Tkach &

Lyubomirsky, 2007). Hence, although the evidence supports a strong relationship between

personality and SWB, one should not assume SWB to be an unchangeable aspect of one’s

personality, because personality might merely facilitate concrete aspects of self-regulation,

which in turn results in different levels of SWB.

Limitations and future prospects

It became obvious through the present research that concepts like perceived emotional

intelligence or self-efficacy in affect regulation can—if at all—only explain a small

proportion of the linkage between personality and SWB. The lion’s share of the

relationship remained unmediated and the utilized—rather abstract concepts—reflect

only little unique variance apart from personality. However, rather than investigating single

mediation effects, future research should particularly focus on comprehensive approaches.

There are a few limitations of the present study. First, we only assessed neuroticism and

extraversion as the two most relevant traits for predicting affective outcomes. Although, we

would not expect substantially different results from the remaining three of the Big Five

(openness to experience, agreeableness, conscientiousness), they might play an important

role for aspects of SWB as well. Second, by utilizing the NEO-FFI we were not able to

measure personality at the facet level (NEO-PI-R). However, this would have allowed the

disentangling of the effects that different aspects of neuroticism and extraversion have on

SWB. Steel et al. (2008) discuss the fact that some of the NEO items of neuroticism and

extraversion reveal a strong conceptually overlap with SWB (e.g. items from the


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extraversion facet of positive emotions), which in our case could have lead to a strong

content correlations between neuroticism and negative affect and extraversion and positive

affect. Considering the five factors of personality at the facet level, Schimmack, Oishi,

Furr, and Funder (2004) for instance found that the two extraversion facets positive

emotions and cheerfulness as well as the neuroticism facet depression were the strongest

predictors of life satisfaction. Investigating the facets rather than the broad domain scores

not only provides more information on which aspects of the factors are most relevant for

SWB components but also probably, for which aspects changes in a person’s mood or

emotion regulation might have strongest effects.

Third, the current study considered global scores of positive and negative affect as SWB

criteria (Sample III) rather than different qualities of positive and negative affects. This

might be important, since research has found unique patterns of personality correlations for

e.g. different positive affects (e.g. joy, love, contentment) (Mitte & Kampfe, 2008). It might

well be that the predictive power to detect mediation effects could be raised by taking the

different dimensions of positive and negative affects into account. This, however, would

lead the focus away from global SWB.

Fourth, the present study relied on cross-sectional rather than longitudinal designs,

which are especially interesting when mediation is focused. In the current case, the order of

constructs, e.g. personality as predictor, SWB as criteria, is highly established by

theoretical means (e.g. McCrae & Costa, 2003). Nevertheless, for specific domains of SWB

(e.g. job satisfaction), evidence for effects from satisfaction to personality have been found

(Scollon & Diener, 2006). It might also be possible that aspects of mood regulation (e.g. the

ability to repair one’s mood) affect SWB through certain features of personality (e.g. the

tendency to worry, which is part of neuroticism).2 These possibilities deserve further

investigation. Further to this, although our mediation effects were rather small, shared

situational variance could still have lead to an overestimation of the mediation effects. Out

of the cited research on mediation of the personality–SWB relationship, only Abbott et al.

(2008) used a longitudinal design and still found significant mediator effects. Hence,

mediation effects can be assumed relatively stable. Nevertheless, more studies using

longitudinal designs are required to better understand the inter-relation between

personality, mediating concepts and SWB.

To summarize, the question of why some people are more happy or satisfied than others

can partially be answered thus: Because they take concrete action to pursue positive states

and well-being. Hence, we should focus more on the specific strategies that promote SWB

and how they might be taught to people.

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