2013panas affect balance score

8/17/2019 2013PANAS Affect Balance Score

1/6

Resilience and affect balance as mediators between trait emotional intelligence

and life satisfaction

Ya Liu, Zhenhong Wang ⇑, Wei Lü

School of Psychology, Shaanxi Normal University, 199 South Chang’an Road, Xi’an 710062, China

a r t i c l e i n f o

Article history:

Received 12 November 2012Received in revised form 17 December 2012Accepted 23 December 2012Available online 27 January 2013

Keywords:

Trait emotional intelligenceSubjective well-beingResilienceAffect balanceLife satisfaction

a b s t r a c t

The current study aimed to analyze the importance of trait emotional intelligence in life satisfaction andto extend the previous literature by investigating the potential mediating effects of resilience and affectbalance in this relationship. To test the study hypotheses, self-report measures of trait emotional intel-ligence, resilience, positive and negative affect, and life satisfaction were administrated to 263 under-graduates. Correlation analysis indicated that trait emotional intelligence was positively correlatedwith life satisfaction. Mediational analyses showed that trait emotional intelligence exerted its indirecteffect on life satisfaction through the simple mediating effect of affect balance and the three-path medi-ating effect of resilience–affect balance. In addition, resilience played as a partial mediator between traitemotional intelligence and affect balance. Furthermore, multi-group analyses showed that the media-tional model was not moderated by gender. Therefore, this study makes a contribution to the complexnature of the association between trait emotional intelligence and subjective well-being.

2012 Elsevier Ltd. All rights reserved.

1. Introduction

Currently, there are two main approaches to conceptualizingand measuring emotional intelligence (EI): trait EI (or trait emo-tional self-efficacy) and ability EI (or cognitive-emotional ability;Mayer, Roberts, & Barsade, 2008; Petrides & Furnham, 2001; Pet-rides, Pita, & Kokkinaki, 2007; Salovey & Mayer, 1990). Trait EI isdefined as a constellation of emotion-related self-perceptions anddispositions located at the lower levels of personality hierarchies(Petrides, Furnham, & Mavroveli, 2007; Petrides, Pita et al., 2007),whereas ability EI is defined as a type of intelligence concerning ac-tual emotion-related cognitive abilities (Mayer et al., 2008). Trait EIis typically assessed via self-report questionnaires (Petrides, Furn-ham et al., 2007; Petrides, Pita et al., 2007), whereas ability EI isbest measured through maximum-performance tests (Mayer

et al., 2008). Although they are two different constructs conceptu-ally, methodologically and empirically, trait and ability EI are twocomplementary rather than oppositional constructs (see Petrides,2011 for a recent review). In the present study, we followed thetrait approach and used a self-report measure to assess EI.

1.1. Trait EI and life satisfaction

Life satisfaction (cognitive well-being) refers to people’s globalcognitive evaluation of the satisfaction with their own lives as a

whole (Diener, Oishi, & Lucas, 2003; Schimmack, 2008). It is an

important indicator of a broad range of positive personal, psycho-logical, social, interpersonal, and intrapersonal outcomes (see Proc-tor, Linley, & Maltby, 2009 for a review). Thus, life satisfaction isoften used to evaluate the quality of people’s lives and is regardedas an important component of subjective well-being (SWB; Dieneret al., 2003; Schimmack, 2008). Various studies have shown mod-erate positive correlations between EI and life satisfaction (Kong &Zhao, 2013; Kong, Zhao, & You, 2012; Palmer, Donaldson, & Stough,2002), even after controlling the Giant Three and (or) Big Five per-sonality dimensions (Gallagher & Vella-Brodrick, 2008; Gannon &Ranzijn, 2005; Law, Wong, & Song, 2004; Petrides, Pita et al.,2007). Recently, Koydemir and Schütz (2012) and Koydemir, Sims-ek, Schütz, and Tipandjan (in press) found that EI is linked to lifesatisfaction in both individualistic and collectivistic cultures. Thus,

the purposes of the current study were to replicate the relation be-tween EI and life satisfaction and to expand previous literature byinvestigating the potential mediational mechanism underlying thisrelationship.

1.2. Resilience and affect balance as mediators

Recently, a large body of research has investigated the potentialmediators between EI and life satisfaction (for a review, see Zeid-ner, Matthews, & Roberts, 2012). Affect balance (affective well-being), for example, was assumed to be a potential mediator inthe relation between EI and life satisfaction in some previous re-search (Kong & Zhao, 2013; Koydemir et al., in press). As a key

0191-8869/$ - see front matter 2012 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.paid.2012.12.010

⇑ Corresponding author. Tel./fax: +86 29 85303312.

E-mail address: [email protected] (Z. Wang).

Personality and Individual Differences 54 (2013) 850–855

Contents lists available at SciVerse ScienceDirect

Personality and Individual Differences

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / p a i d

http://dx.doi.org/10.1016/j.paid.2012.12.010mailto:[email protected]://dx.doi.org/10.1016/j.paid.2012.12.010http://www.sciencedirect.com/science/journal/01918869http://www.elsevier.com/locate/paidhttp://www.elsevier.com/locate/paidhttp://www.sciencedirect.com/science/journal/01918869http://dx.doi.org/10.1016/j.paid.2012.12.010mailto:[email protected]://dx.doi.org/10.1016/j.paid.2012.12.010


2/6

component of SWB, affect balance refers to a balance between po-sitive and negative affect (Schimmack, 2008). Affective well-beinghas been found to be particularly important in forming people’s lifesatisfaction judgments (Kuppens, Realo, & Diener, 2008; Schim-mack, 2008). Considering the robust relation between EI and affec-tive well-being and the role of affective well-being in lifesatisfaction, it is reasonable to assume that affect balance mediatesthe relation between EI and life satisfaction. Consistent with thisline of reasoning, empirical research has supported this assump-tion (Kong & Zhao, 2013; Koydemir et al., in press). Thus, this studyhypothesized that affect balance functioned as a mediator betweenEI and life satisfaction.

Furthermore, resilience was assumed to be another potentialintervening variable between EI and life satisfaction as well as af-fect balance. As an important psychological resource, resiliencegenerally represents the capacity to ‘‘bounce back’’ from stresseffectively, adapt flexibly and even grow positively in response tothe adversity settings (Block & Kremen, 1996; Bonanno, 2004).There is compelling evidence in support of the associations be-tween resilience and both EI (Armstrong, Galligan, & Critchley,2011; Matthews, Zeidner, & Roberts, 2002) and SWB (Liu, Wang,& Li, 2012; Mak, Ng, & Wong, 2011; Yu & Zhang, 2007 ).

With respect to the relation between EI and resilience, Matthewset al. (2002) indicated that EI is antecedent to resilience. Armstronget al. (2011)’s study revealed thatvulnerable individuals have lowerEI scores, whereas resilient individuals have higher EI scores. More-over, theability to effectively regulate one’s ownemotions, a core fa-cet of EI, was found to promote individuals’ resilience (New et al.,2009; Tugade& Fredrickson,2007). Thus, Armstronget al.(2011)ar-gued that EI may well be directly connected to resilience.

As regards the link between resilience and SWB, there is strongevidence that resilience is of considerable benefits to people’s SWB.Specifically, resilience is firmly found to be positively correlatedwith life satisfaction and positive affect, and inversely related tonegative affect (Liu et al., 2012; Mak et al., 2011; Yu & Zhang,2007). In consideration of the associations between EI, resilience

and two components of SWB, this study hypothesized that resil-ience exerted as a mediator between EI and both life satisfactionand affect balance.

1.3. The present study

Based on the preceding rationale and the available literatureshowing that EI is antecedent to resilience (Armstrong et al., 2011;Matthews et al., 2002) and resilience could exert an indirect effecton life satisfaction via affective well-being (Liu et al., 2012), it washypothesized that EI exerts a significant indirect effect on life satis-faction through the three-path mediating effect of resilience and af-fect balance (for more details about the three-path mediationalmodel, see Taylor, MacKinnon, & Tein, 2008). Specifically, individu-alswithhigherEIhavegreaterresilience,which,inturn,servestoen-hance their levels of affective well-being, and thereby increasingtheir life satisfaction. The detailed hypothesized model concerningthe mediator role of resilience and affect balance in the relationshipbetween EI and life satisfaction is presented in Fig. 1.

2. Method

2.1. Participants and procedure

The sample consisted of 263 undergraduates (119 men, 144 wo-men), aged 18–25 years (M = 22.61, SD = 1.41). The majority (over97%) of the participants are the Han nationality.

All participants were briefly instructed as to the purpose of thestudy and then signed a written consent form. Participants were

administered a packet of paper-and-pencil questionnaires measur-ing EI, resilience, affect balance and life satisfaction. The measureswere conducted in the classroom environment by a trained re-search assistant, who was always available to answer any queriesraised by the participants and to ensure their confidential andindependent responding.

2.2. Measures

2.2.1. Trait EI

Trait EI was measured using the widely-used 16-item Wongand Law Emotional Intelligence Scale (WLEIS; Wong & Law,2002). The WLEIS scale contains four dimensions: (a) self emo-tional appraisal (SEA; e.g., ‘‘I really understand what I feel.’’), (b)others’ emotional appraisals (OEA; ‘‘I am a good observer of others’emotions.’’), (c) regulation of emotion in one’s self (ROE; e.g., ‘‘I amable to control my temper and handle difficulties rationally.’’), and(d) use of emotion to facilitate performance (UOE; e.g., ‘‘I alwaysset goals for myself and then try my best to achieve them.’’). Eachof the four dimensions was measured using four items with a se-ven-point Likert-type response format, ranging from 1 (totally dis-agree) t o 7 (totally agree). The WLEIS scale demonstrated clearfactor structure and good internal consistency reliability (Lawet al., 2004; Wong & Law, 2002).

2.2.2. Resilience

The Connor–Davidson Resilience Scale (CD-RISC; Connor &Davidson, 2003) which comprises of 25 statements (e.g., ‘‘able toadapt to change’’, ‘‘best effort no matter what’’, and ‘‘strong senseof purpose’’) was used to assess resilience. For each statement par-ticipants were asked to rate how they generally feel on a five-point

Likert scale that ranges from 0 (not at all) to 4 (true nearly all of thetime). The Chinese version of the CD-RISC, translated by Yu andZhang (2007), was demonstrated to be a reliable and valid mea-surement in assessing resilience for the Chinese population (Yu &Zhang, 2007).

2.2.3. Affect balance

The balance between positive and negative affect was assessedusing the Positive Affect and Negative Affect Schedule (PANAS;Watson, Clark, & Tellegen, 1988). This scale consists of 10 affectiveadjective words for positive affect (e.g., ‘‘active’’, ‘‘alert’’, ‘‘atten-tive’’) and negative affect (e.g., ‘‘afraid’’, ‘‘ashamed’’, ‘‘distressed’’),respectively. Participants were asked to indicate how they gener-ally feel on a five-point Likert scale (1 = ‘‘very slightly’’ to 5 = ‘‘ex-

tremely’’). Both Positive Affect and Negative Affect subscales of the PANAS have demonstrated high reliability, and also excellent

Emotional

Intelligence

Affect

Balance

Resilience

Life

Satisfaction

Fig. 1. The hypothesized model concerning the mediator role of resilience andaffect balance in the relationship of trait emotional intelligence with lifesatisfaction.

Y. Liu et al. / Personality and Individual Differences 54 (2013) 850–855 851


3/6

psychometric properties in college samples (Watson et al., 1988).In the current study, following Koydemir and Schütz (2012) andKoydemir et al. (in press)’s method, the affect balance score, asindicator of affective well-being, was computed by subtractingthe negative affect score from the positive affect score.

2.2.4. Life satisfaction

The Satisfaction with Life Scale (SWLS) developed by Diener,Emmons, Larsen, and Griffin (1985) was used to evaluate individu-als’ global life satisfaction. The SWLS consists of five items (e.g., ‘‘Iam satisfied with my life’’). Each item is responded to by using aseven-point Likert scale ranging from 1 (strongly disagree) to 7(strongly agree). This scale has been shown to have excellent psy-chometric properties (Diener et al., 1985).

3. Results

3.1. Preliminary analyses

Descriptive statistics, reliability estimates (Cronbach’s alphacoefficients), and bivariate zero-order correlations for all the study

variables are presented in Table 1.

3.2. Mediational analyses

We used structural equation modeling (SEM) procedures toexamine the main research hypotheses regarding the mediating ef-fects of resilience and affect balance on the relation between EI andlife satisfaction. The SEM analyses were conducted in Mplus v6using maximum likelihood estimation (Muthén & Muthén, 1998–2010). To evaluate the overall fit of the model to the data, severalindices recommended by Hu and Bentler (1999) and Kline (2011)were calculated in the current study: chi-square statistic (v2),v

2/df ratio, Standardized Root Mean Square Residual (SRMR), RootMean Square Error of Approximation (RMSEA), Comparative Fit In-

dex (CFI) and Tucker-Lewis Index (TLI). According to Hu and Ben-tler (1999) and Kline (2011), goodness-of-fit criteria were used inthe current study that acknowledged the potential for acceptable(v2/df ratio < 3, CFI and TLI > 0.90, SRMR < 0.10, RMSEA < 0.08)and excellent fit (v2/df ratio < 2, CFI and TLI > 0.95, SRMR < 0.08,RMSEA < 0.06).

3.2.1. Measurement model

Following the two-step procedure outlined by Anderson andGerbing (1988), confirmatory factor analysis (CFA) was used to testthe measurement model before testing the structural relationships.The measurement model consisted of four interrelated latent vari-ables including EI, resilience, affect balance, and life satisfaction. EIlatent variable was created by using its four indicators: SEA, OEA,

UOE and ROE. In order to control for inflated measurement errorsand improve the psychometric properties of the variables, we

formed three item parcels for both resilience and affect balanceconstructs. Life satisfaction latent variable was defined using theitems of the SWLS because it consisted of only five items. The re-sults of CFA analysis indicated that the measurement model pro-vided a good fit to the observed data: v2 (84, N = 263) = 154.81(P < 0.001), v2/df ratio = 1.84, SRMR = 0.055, RMSEA = 0.057 (90%CI = 0.042–0.070), P = 0.21; CFI = 0.954, TLI = 0.952.

3.2.2. Structural model

SEM procedure was conducted to test the proposed structuralrelationships among study variables (see Fig. 1). The results indi-cated that the hypothesized mediational model fit the data well,v

2 (84, N = 263) = 154.81 (P < 0.001), v2/df ratio = 1.84,SRMR = 0.055, RMSEA = 0.057 (90% CI = 0.042–0.070), P = 0.21;CFI = 0.954, TLI = 0.952. According to the modification index, theerror terms of SEA and OEA were then allowed to be correlated.The results indicated that the mediational model with the abovetwo correlated error terms fit the data well (v2 (83,N = 263) = 142.82 (P < 0.001), v2/df ratio = 1.72, SRMR = 0.052,RMSEA = 0.052 (90% CI = 0.037–0.067), P = 0.38; CFI = 0.961,TLI = 0.954.) and improved the model fit (4v2 (1,N = 263) = 11.99, P < 0.001). Allowing these two error terms to becorrelated is plausible because SEA and OEA both assess one’s emo-tional appraisal ability, such that there are some content overlapsor similarities between them. Further examination of parameterestimates indicated that all the direct path coefficients were signif-icant in the proposed directions, except for the two paths from EI(b = 0.03, t = 0.25, P = 0.81) and resilience (b = 0.02, t = 0.18,P = 0.85) to life satisfaction. These results suggested that resilienceand affect balance may play a full mediating role in the relation be-tween EI and life satisfaction.

3.2.3. Full versus partial mediation

To test the potential full mediational model, the results of thetwo following mediational models was compared: (a) partial medi-ation model with the direct paths from EI and resilience to life sat-

isfaction not constrained; and (b) full mediational model with thedirect paths from EI and resilience to life satisfaction constrainedto zero. Similar to the partial mediation model, the full mediationmodel fit the data well: v2 (85, N = 263) = 143.02 (P < 0.001), v2/df ratio = 1.68, SRMR = 0.053, RMSEA = 0.051 (90% CI = 0.036–0.065),P = 0.44; CFI = 0.963, TLI = 0.955. Moreover, the partial mediationmodel did not provide a significantly better fit to the data thanthe full mediation model (4v2 (2, N = 263) = 0.20, P = 0.90). Conse-quently, the full mediation model regarding the relation betweenEI and life satisfaction was supported. Standardized path coeffi-cients of the final mediational model, see Fig. 2.

3.2.4. Assessment of mediation

The Bootstrapping procedure in Mplus v6 was used to test the

significance of the mediating effects of resilience and affect bal-ance. Specifically, 1000 bootstrap samples were generated using

Table 1

Means, standard deviations (SD), reliabilities and intercorrelations among study variables (N = 263).

Mean SD a 1 2 3 4 5 6 7

1. Trait EI 82.17 11.81 0.852. SEA 21.37 3.67 0.66 0.78**

3. OEA 20.97 3.77 0.72 0.63** 0.38**

4. ROE 20.69 3.90 0.73 0.75** 0.44** 0.27**

5. UOE 19.14 4.52 0.81 0.80** 0.53** 0.28** 0.51**

6. Resilience 62.27 10.73 0.87 0.42** 0.28** 0.14* 0.51** 0.32**

7. AB 9.49 7.82 0.80 0.40** 0.34** 0.03 0.43** 0.38** 0.41**

8. LS 18.37 6.03 0.77 0.21** 0.21** 0.09 0.12* 0.20** 0.20** 0.33**

Note: AB: affect balance; PA: positive affect; NA: negative affect; LS: life satisfaction. a, Cronbach’s Alpha.*

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

852 Y. Liu et al. / Personality and Individual Differences 54 (2013) 850–855


4/6

random sampling with replacement from the data set ( N = 263).The mediating effects of resilience and affect balance and theirassociated 95% confidence intervals were displayed in Table 2.

According to the results, EI exerted its indirect effect on life sat-isfaction through the simple mediating effect of affect balance andthe three-path mediating effect of resilience–affect balance. EI ex-erted its effect on affect balance through both the direct path andthe indirect path via resilience. In addition, resilience did not havea direct influence on life satisfaction, but exerted an indirect effectvia affect balance.

3.3. Gender differences

Multiple group analyses were conducted to further examinewhether any of the depicted associations in the mediational model(see Fig. 2) differed by gender. The following two models werecompared, one allowing all the paths to be freely estimated in maleand female groups (configurable model) and the other constrainingthem to be equal (constrained model). The results showed that theconstrained model was not significantly different from the config-urable model (4v2 (4, N = 263) = 6.85, P = 0.14), suggesting no sig-nificant gender differences. Inspection of each path coefficient inseparate multiple group analyses further confirmed that all theassociations were similar in magnitude for male and femalegroups, with one exception being the significant difference (4v2

(1, N = 263) = 4.16, P < 0.05) observed for the association between

resilience and affect balance (b = 0.005, P = 0.98, for the malegroup; b = 0.36, P < 0.001, for the female group), suggesting that

the association between resilience and affect balance was strongerfor female than for male students and that resilience did not have asignificant direct effect on affect balance for male students. Themodel with all constrained parameters except the direct path fromresilience to affect balance (freely estimated) suggested only min-imal improvement (4v2 (1, N = 263) = 3.61, P = 0.06). These resultsprovided a preliminary support for the robustness of the finalmediational model.

4. Discussion

The current study analyzed the importance of trait EI in life sat-

isfaction and extended the previous literature by investigating thepotential mediating effects of resilience and affect balance. Inaccordance with previous literature (Gallagher & Vella-Brodrick,2008; Koydemir & Schütz, 2012; Schutte & Malouff, 2011), EIwas found to correlate positively with both life satisfaction and af-fect balance. The promotion role of EI in SWB may be due to a vari-ety of ways. Emotionally intelligent individuals tend to experiencelower levels of distress and negative affect, but to experience posi-tive affect more frequently (Koydemir & Schütz, 2012; Salovey &Mayer, 1990), possess more social support (Law et al., 2004; Wong& Law, 2002), and are better at making use of their emotions bydirecting them towards constructive activities and personal perfor-mance (Law et al., 2004; Wong & Law, 2002). All these advantagespromote emotionally intelligent individuals’ levels of SWB.

Although some research has examined the potential mediatorsbetween EI and life satisfaction (Kong & Zhao, 2013; Kong et al.,

0.24

0.61

0.69

0.65

0.62

0.61

0.730.870.71

0.890.770.66

0.42

0.23

0.45

0.61

0.70

0.77

0.32

0.63

Emotional

Intelligence

SEA

OEA

UOE

ROE

Affect

Balance

Resilience

Life

Satisfaction

R1 R2 R3

AB1 AB2 AB3

LS1

LS2

LS3

LS4

LS5

Fig. 2. The Structural Equation Model regarding the mediating effects of resilience and affect balance on the relation between trait emotional intelligence and life satisfaction.Note: R: resilience; AB: affect balance; LS: life satisfaction. Dashed lines indicated insignificant paths. The path coefficients of final mediational model with eliminating theinsignificant paths are presented in the above model. The path coefficients for the originally hypothesized mediational model are similar to the final mediational model, andthus the detailed results are not reported in the above model.

Table 2

Bootstrapping indirect effects and 95% confidence intervals (CI) for the final mediational model.

Model pathways Point estimate 95% CI

Lower Upper

Trait EI? Resilience? Affect balance 0.141 0.018 0.265Trait EI? Affect balance? Life satisfaction 0.190 0.084 0.296Resilience? Affect balance? Life satisfaction 0.098 0.001 0.194

Trait EI?

Resilience?

Affect balance?

Life satisfaction 0.060 0.004 0.116



5/6

2012; Koydemir et al., in press), there is little research that hasinvestigated the possible mediator between EI and affective well-being. The current study firstly examined resilience as a mediatorbetween EI and life satisfaction as well as affect balance. Consistentwith hypotheses, resilience was revealed to partially mediate therelationship between EI and affect balance. Armstrong et al.(2011) proposed that EI is antecedent to resilience and furtherfound that intrapersonal EI (e.g., Emotional Self-Awareness andEmotional Self-Management) has a significant predictive role inresilience. Concurring with Armstrong et al. (2011)’s research,the current study demonstrated that EI has a significant positiveeffect on resilience. Regarding the relation between resilienceand affective well-being, a growing body of research has demon-strated that individuals with higher levels of resilience have morepositive affect and less negative affect (Liu et al., 2012; Mak et al.,2011). The considerable benefits of resilience on affective well-being may be because resilient individuals have optimistic, zestful,and energetic approaches to life, are curious and open to new expe-riences, and tend to have high positive emotionality (Block & Kre-men, 1996; Bonanno, 2004). Based on these previous findings, it isreasonable to infer that resilience plays a mediating role in therelation between EI and affect balance. This study provided firstsupport for this assumption. However, it is noteworthy to mentionthat the association between resilience and affect balance was sur-prisingly not significant for male students and stronger among fe-male than among male students. This may be because malestudents, regardless of being resilient or vulnerable, are expectedor required to be more rational and less affective than females,especially in the Chinese culture.

In the current study, resilience was found to not simply mediatethe link between EI and life satisfaction. This may be because resil-ience did not have a significant direct influence on life satisfaction,but exerted a significant positive indirect effect via affect balance.This result is in line with Liu et al. (2012)’s research, showing thataffective well-being fully mediated between resilience and life sat-isfaction. Based on the prior literature showing that EI is anteced-

ent to resilience (Armstrong et al., 2011; Matthews et al., 2002),and the association between resilience and affective well-being(Liu et al., 2012) as well as the role of affective well-being in lifesatisfaction (Kuppens et al., 2008; Schimmack, 2008), it is plausibleto hypothesize that EI exerts an indirect influence on life satisfac-tion through the sequential mediating effect of the resilience–af-fect balance. The present study firstly confirmed this hypothesis.In addition, consistent with Koydemir et al. (in press)’s research, af-fect balance was found to simply mediate the relation between EIand life satisfaction. These results highlight the importance of theaffective component of SWB in the relation between EI and lifesatisfaction.

Although we believe that these results contribute to a betterunderstanding of the mediational mechanism in the association

between EI and life satisfaction, we also acknowledge that thereare several limitations of the present study that should be consid-ered. Firstly, the SEA reliability was relatively low (a = 0.66), there-by, we should interpret results with caution although the overall EIscale’s reliability was acceptable to good (a = 0.85). Secondly, itneeds to be pointed out that the present study was a cross-sec-tional design in nature. Thus, the findings reported here reflectassociations and predictions, but not cause–effect relations be-tween the variables in question. Therefore, further studies that uti-lize prospective and longitudinal approaches to determine thecausal relationships between study variables are warranted.Thirdly, the study relied on a college student sample so it remainsto be seen whether the current findings can be generalized to otherage groups, considering the evident differences between student

and adult as well as elderly samples. Finally, the data in this studywere collected only through self-report scales. Future studies

should integrate multiple assessment methods to further strength-en the validity of the findings.

Acknowledgements

This study was funded by Nature Science Foundation of China(30970912).

References

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice. Areview and recommended two-step approach. Psychological Bulletin, 103,411–423.

Armstrong, A. R., Galligan, R. F., & Critchley, C. R. (2011). Emotional intelligence andpsychological resilience to negative life events. Personality and IndividualDifferences, 51, 331–336.

Block, J., & Kremen, A. M. (1996). IQ and ego-resiliency: Conceptual and empiricalconnections and separateness. Journal of Personality and Social Psychology, 70 ,349–361.

Bonanno, G. A. (2004). Loss, trauma, and human resilience. American Psychologist,59, 20–28.

Connor, K. M., & Davidson, J. R. T. (2003). Development of a new resilience scale: TheConnor–Davidson Resilience Scale (CD-RISC). Depression and Anxiety, 18, 76–82.

Diener, E., Emmons, R. S., Larsen, R. J., & Griffin, S. (1985). The satisfaction with lifescale. Journal of Personality Assessment, 49, 71–75.

Diener, E., Oishi, S., & Lucas, R. E. (2003). Personality, culture, and subjective well-being: Emotional and cognitive evaluations of life. Annual Review of Psychology,54, 403–425.

Gallagher, E. N., & Vella-Brodrick, D. A. (2008). Social support and emotionalintelligence as predictors of subjective well-being. Personality and IndividualDifferences, 44, 1551–1561.

Gannon, N., & Ranzijn, R. (2005). Does emotional intelligence predict uniquevariance in life satisfaction beyond IQ and personality? Personality andIndividual Differences, 38, 1353–1364.

Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structureanalysis: Conventional criteria versus new alternatives. Structural EquationModeling, 6 , 1–55.

Kline, R. B. (2011). Principles and practices of structural equation modeling (3rd ed.).New York, NY: Guilford Press.

Kong, F., & Zhao, J. (2013). Affective mediators of the relationship between traitemotional intelligence and life satisfaction in young adults. Personality andIndividual Differences, 54, 197–201.

Kong, F., Zhao, J., & You, X. (2012). Emotional intelligence and life satisfaction inChinese university students: The mediating role of self-esteem and socialsupport. Personality and Individual Differences, 53, 1039–1043.

Koydemir, S., Simsek, Ö. F., Schütz, A., & Tipandjan, A. (in press). Differences in howtrait emotional intelligence predicts life satisfaction: The role of affect balanceversus social support in India and Germany. Journal of Happiness Studies. http://dx.doi.org/10.1007/s10902-011-9315-1.

Koydemir, S., & Schütz, A. (2012). Emotional intelligence predicts components of subjective well-being beyond personality: A two-country study using self- andinformant reports. The Journal of Positive Psychology, 7 , 107–118.

Kuppens, P., Realo, A., & Diener, E. (2008). The role of positive and negativeemotions in life satisfaction judgment across nations. Journal of Personality andSocial Psychology, 95, 66–75.

Law, K. S., Wong, C. S., & Song, L. J. (2004). The construct and criterion validity of emotional intelligence and its potential utility for management studies. Journalof Applied Psychology, 89, 483–496.

Liu, Y., Wang, Z. H., & Li, Z. G. (2012). Affective mediators of the influence of neuroticism and resilience on life satisfaction. Personality and IndividualDifferences, 52, 833–838.

Mak, W. W. S., Ng, I. S. W., & Wong, C. C. Y. (2011). Resilience: Enhancing well-being

through the positive cognitive triad. Journal of Counseling Psychology, 58,610–617.Matthews, G., Zeidner, M., & Roberts, R. D. (2002). Emotional intelligence: Science and

myth. Cambridge: MIT Press.Mayer, J. D., Roberts, R. D., & Barsade, S. G. (2008). Human abilities: Emotional

intelligence. Annual Review of Psychology, 59, 507–536.Muthén, L. K., & Muthén, B. O. (1998–2010). Mplus user’s guide (6th ed.). Los Angeles,

CA: Muthén & Muthén.New, A. S., Fan, J., Murrough, J. W., Liu, X., Liebman, R. E., Guise, K. G., et al. (2009). A

functional magnetic resonance imaging study of deliberate emotion regulationin resilience and posttraumatic stress disorder. Biological Psychiatry, 6 , 656–664.

Palmer, B., Donaldson, C., & Stough, C. (2002). Emotional intelligence and lifesatisfaction. Personality and Individual Differences, 33, 1091–1100.

Petrides, K. V. (2011). Ability and trait emotional intelligence. In T. Chamorro-Premuzic, A. Furnham, & S. von Stumm (Eds.), The Blackwell-Wiley handbook of individual differences. New York: Wiley.

Petrides, K. V., & Furnham, A. (2001). Trait emotional intelligence: Psychometricinvestigation with reference to established trait taxonomies. European Journal of Personality, 15, 425–448.

Petrides, K. V., Furnham, A., & Mavroveli, S. (2007). Trait emotional intelligence:Moving forward in the field of EI. In G. Matthews, M. Zeidner, & R. Roberts

854 Y. Liu et al. / Personality and Individual Differences 54 (2013) 850–855

http://dx.doi.org/10.1007/s10902-011-9315-1http://dx.doi.org/10.1007/s10902-011-9315-1http://dx.doi.org/10.1007/s10902-011-9315-1http://dx.doi.org/10.1007/s10902-011-9315-1


6/6

(Eds.), Emotional intelligence: Knowns and unknowns (Series in Affective Science).Oxford: Oxford University Press.

Petrides, K. V., Pita, R., & Kokkinaki, F. (2007). The location of trait emotionalintelligence in personality factor space. British Journal of Psychology, 98,273–289.

Proctor, C. L., Linley, P. A., & Maltby, J. (2009). Youth life satisfaction: A review of theliterature. Journal of Happiness Studies, 10, 583–630.

Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition, andPersonality, 9, 185–211.

Schimmack, U. (2008). The structure of subjective wellbeing. In M. Eid & R. J. Larsen

(Eds.), The science of subjective well-being (pp. 97–123). New York: Guilford.Schutte, N. S., & Malouff, J. M. (2011). Emotional intelligence mediates the

relationship between mindfulness and subjective well-being. Personality andIndividual Differences, 50, 1116–1119.

Taylor, A. B., MacKinnon, D. P., & Tein, J. Y. (2008). Tests of the three-path mediatedeffect. Organizational Research Methods, 11, 241–269.

Tugade, M. M., & Fredrickson, B. L. (2007). Regulation of positive emotions: Emotionregulation strategies that promote resilience. Journal of Happiness Studies, 8,311–333.

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070.

Wong, C. S., & Law, K. S. (2002). The effects of leader and follower emotionalintelligence on performance and attitude: An exploratory study. The LeadershipQuarterly, 13, 243–274.

Yu, X., & Zhang, J. (2007). Factor analysis and psychometric evaluation of the

Connor–Davidson Resilience Scale (CD-RISC) in Chinese people. Social Behavior and Personality, 35, 19–30.

Zeidner, M., Matthews, G., & Roberts, R. D. (2012). The emotional intelligence,health, and well-being nexus: What have we learned and what have wemissed? Applied Psychology: Health and Well-being, 4, 1–30.


2013panas affect balance score

Documents