210 DEMEROUTI, MOSTERT, AND BAKKERa hierarchical property that is, that can be ordered by (Richardsen & Martinussen, 2004; Schutte, Toppi-degree of difﬁculty. However, none of the instru- nen, Kalimo, & Schaufeli, 2000).ments used in this study are known for including Unfortunately, the MBI-GS has one important psy-hierarchical structured items. chometric shortcoming, namely that the items within Second, in addition to the Maslach Burnout Inven- each subscale are all framed in the same direction.tory-General Survey (MBI-GS; Maslach, Jackson, & Accordingly, all exhaustion and cynicism items areLeiter, 1996) and the Utrecht Work Engagement phrased negatively, whereas all professional efﬁcacyScale (UWES; Schaufeli et al., 2002) we will use the items are phrased positively. From a psychometricOLBI, which is a valid instrument that can be used to point of view, such one-sided scales are inferior tomeasure the energy and identiﬁcation dimensions of scales that include both positively and negativelyburnout and work engagement simultaneously as bi- worded items (Price & Mueller, 1986) because theypolar constructs. We focused on these instruments can lead to artiﬁcial factor solutions in which posi-because they include both core dimensions of burn- tively and negatively worded items are likely to clus-out and work engagement, namely a vigor/exhaustion ter (Demerouti & Nachreiner, 1996; cf. Doty &dimension and an identiﬁcation/distancing dimen- Glick, 1998) or may show artiﬁcial relationships withsion, while instruments like the Shirom-Melamed other constructs (Lee & Ashforth, 1990).Burnout Scale (Shirom, 2003) or the Copenhagen The UWES (Schaufeli & Bakker, 2003, 2010;Burnout Inventory (Kristensen, Borritz, Villadsen & Schaufeli et al., 2002) has been developed to measureChristensen, 2005) focus solely on vigor/exhaustion. work engagement deﬁned as a positive, fulﬁlling, Third, next to the factor structure we will also exam- work-related state of mind that is characterized byine the pattern of relationships of the (bipolar and/or vigor, dedication, and absorption. Vigor refers tounipolar) dimensions of burnout and work engagement high levels of energy and mental resilience whilewith relevant job characteristics (work pressure and job working. Dedication refers to a sense of signiﬁcance,autonomy) and organizational outcomes (organizational enthusiasm, inspiration, and pride. Vigor and dedica-commitment and mental health). We focus on these tion are the direct positive opposites of exhaustionconstructs because they have been studied most often as and cynicism, respectively. Absorption is excludedbeing related to the energy or identiﬁcation dimensions from the present study because burnout does notof burnout or engagement. contain any parallel dimension to this dimension. The UWES has been validated in several countries (e.g., Schaufeli et al., 2002; Schaufeli & Bakker, 2004; Measurement of Burnout and Storm & Rothmann, 2003; Yi-Wen & Yi-Qun, Work Engagement 2005). However, some studies found a one- instead of a three-factor structure of work engagement (e.g., The most commonly used instrument for the mea- Sonnentag, 2003).surement of burnout is the MBI-GS (Schaufeli, Leiter, We propose an alternative measure of burnout andMaslach, & Jackson, 1996). Based on the notion that work engagement: The OLdenburg Burnout Inven-emotional exhaustion, depersonalization and per- tory (OLBI; Demerouti, 1999; Demerouti & Nachre-sonal accomplishment (representing symptoms of iner, 1998). It includes positively and negativelyburnout speciﬁc for human services) can be broad- framed items to assess the two core dimensions ofened beyond the interpersonal domain that is charac- burnout: exhaustion and disengagement from work.teristic for the human services, they distinguished Exhaustion is deﬁned as a consequence of intensivethree generic burnout dimensions that were labeled physical, affective and cognitive strain, that is, as aexhaustion, cynicism and professional efﬁcacy, re- long-term consequence of prolonged exposure to cer-spectively. Many empirical ﬁndings point to the cen- tain job demands. Contrary to exhaustion as opera-tral role of exhaustion and cynicism as the “core” tionalized in the MBI-GS, the OLBI covers affectivedimensions of burnout, as opposed to the third com- but also physical and cognitive aspects of exhaustion.ponent—lack of professional efﬁcacy (Lee & Ash- Such an operationalization of exhaustion/vigor cov-forth, 1996). As a result, the third dimension mea- ers more thoroughly peoples’ intrinsic energetic re-sured with the MBI-GS was excluded from this sources, that is, emotional robustness, cognitive live-study. Several studies have supported the invariance liness and physical vigor (Shirom, 2003) and enablesof the MBI-GS factor structure across various occu- the application of the instrument to those workerspational groups (Bakker, Demerouti & Schaufeli, with physical and cognitive work. Disengagement2002; Leiter & Schaufeli, 1996), and across nations refers to distancing oneself from one’s work in gen-
BURNOUT AND WORK ENGAGEMENT 211eral, work object, and work content. Moreover, the consequently the measurement of both concepts isdisengagement-items concern the relationship be- different. As the MBI-GS includes only negativelytween employees and their jobs, particularly with worded items, it is difﬁcult to conclude that individ-respect to identiﬁcation with work and willingness to uals who reject a negatively worded statement wouldcontinue in the same occupation. Depersonalization automatically agree with a positively worded one.is consequently only one form of disengagement Thus, Schaufeli and Bakker (2003) proposed thatwhich is directed toward customers. burnout and work engagement should be conceived The factorial validity of the OLBI has been con- as two opposite concepts that should be measuredﬁrmed in studies conducted in different countries independently with different instruments.(Demerouti & Bakker, 2008; Demerouti, Bakker, Nach- A direct test of the dimensionality of burnout andreiner, & Ebbinghaus, 2002; Halbesleben & Demerouti, work engagement has been conducted by Gonzalez- ´2005; Demerouti et al., 2003). Following a multitrait Roma et al. (2006). They used the MBI-GS and the ´multimethod approach, Demerouti et al. (2003) and UWES to test the hypothesis that items reﬂectingHalbesleben and Demerouti (2005) conﬁrmed the con- exhaustion-vigor and cynicism-dedication are scal-vergent validity of the OLBI and MBI-GS. able on two distinct underlying bipolar dimensions (labeled energy and identiﬁcation, respectively). Us- ing a nonparametric scaling technique, they showed The Dimensionality of Burnout and that these core burnout and engagement dimensions Work Engagement can indeed be seen as opposites of each other along two distinct bipolar dimensions (energy vs. identiﬁ- There are different views regarding the dimension- cation). However, a closer look at their ﬁndings re-ality of burnout and work engagement. Demerouti veals that the exhaustion—vigor items constitute aand colleagues (2001, 2003) assume that the dimen- weak to moderate energy dimension, and that thesions of burnout and work engagement are bipolar cynicism— dedication items constitute a strong iden-dimensions. This is reﬂected in the OLBI which tiﬁcation dimension. Nevertheless, it can be con-includes both negatively and positively worded items cluded from this study that negatively and positivelyso that both ends of the continuum are measured. In framed items can be used to assess the core dimen-other words, the exhaustion and disengagement sub- sions of burnout and work engagement. Speciﬁcally:scales include items that refer to their opposites,namely vigor and dedication, respectively. Positively Hypothesis 1: Disengagement/cynicism andframed items should be reverse-coded if one wants to dedication are opposite ends of one dimension.assess burnout. Alternatively, to assess work engage-ment the negatively framed items should be recoded Hypothesis 2: Exhaustion and vigor are opposite(Demerouti & Bakker, 2008). ends of one dimension. Maslach and Leiter (1997) agree with this stand-point. They rephrased burnout as an erosion of en- Work pressure and autonomy are two job character-gagement with the job, whereby energy turns into istics that have been related to burnout and to workexhaustion, involvement turns into cynicism, and ef- engagement. Speciﬁcally, work pressure has the stron-ﬁcacy turns into ineffectiveness. In their view, work gest positive relationship with exhaustion (Demerouti,engagement is characterized by energy, involvement Bakker, & Bulters, 2004; Lewig, Xanthopoulou, Bak-and professional efﬁcacy, which are the direct (per- ker, Dollard, & Metzer, 2007; Hakanen, Bakker, &fectly inversely related) opposites of the three burn- Schaufeli, 2006; Rothmann & Pieterse, 2007); and aout dimensions. However, it should be noted that less strong but negative relationship with vigortheir MBI-GS includes negative items only. There- (Hakanen et al., 2006; Rothmann & Pieterse, 2007).fore, low scores on exhaustion and cynicism cannot However, some authors found a nonsigniﬁcant rela-be taken as being representative of vigor and dedica- tionship between work/time pressure and exhaustiontion, since employees who indicate that they are not or vigor (Mauno, Kinnunen, & Ruokolainen, 2007).fatigued are not necessarily full of energy. The relationship between work pressure and the iden- Schaufeli and Bakker (2003, 2010; Schaufeli et al., tiﬁcation components of burnout and work engage-2002) argue that work engagement cannot be mea- ment is, however, weak (e.g., Bakker, Demerouti, &sured by the opposite proﬁle of the MBI-GS, be- Verbeke, 2004; Hakanen et al., 2006; Rothmann &cause, even though in conceptual terms engagement Pieterse, 2007). Autonomy seems to be related to theis the positive antithesis of burnout, the content and identiﬁcation dimensions and the energy dimensions
212 DEMEROUTI, MOSTERT, AND BAKKER(Bakker et al., 2004; Demerouti et al., 2001; The response rate was 53%. After permission wasSchaufeli & Bakker, 2004). It shows a negative re- obtained from executive management, the managers,lationship with exhaustion and cynicism (Bakker et Human Resources department, and employee/al., 2004; Hakanen et al., 2006; Koekemoer & Mos- employer committees were informed of the studytert, 2006; Schaufeli & Bakker, 2004), and a positive during management meetings. Thereafter, all em-relationship with vigor and dedication (Hakanen et ployees received paper-and-pencil questionnaires andal., 2006; Mauno et al., 2007). envelopes at their work that could be returned to the Organizational commitment is an outcome that is researchers involved. A letter explaining the purposeparticularly related to the identiﬁcation components of of the research accompanied the questionnaire. Theburnout and work engagement (Schaufeli & Bakker, employees were kindly requested to ﬁll in the ques-2004) and weakly related/unrelated to the energy com- tionnaire in private and send it to the Human Re-ponents, speciﬁcally exhaustion (Hakanen et al., 2006; sources department, where the researchers collectedLlorens, Bakker, Schaufeli, & Salonova, 2006). Finally, all the completed questionnaires. Participation wasmental health shows a stronger relationship with the voluntary, and the conﬁdentiality and anonymity ofenergy dimensions and in particular with exhaustion the answers was emphasized.(Hakanen et al., 2006; Jackson & Rothmann, 2005; The majority of the participants worked in theLewig et al., 2007; Schaufeli & Bakker, 2004). Construction (40.2%) and Mining (24.2%) units, What is of interest for our research question is while the rest worked in the Shared Services (12.3%),whether the two ends of the energy and identiﬁcation Handling (8.3%), Energy (5.1%), Rental (5.1%), anddimensions show the same pattern of relationships Agriculture (4.8%) departments. The participantswith these constructs. Similar relationships would be were predominantly male (71.5%), while 62.7% wereevidence for bipolar constructs, while differential White, 20.4% were African, 11.2% were Colored,relations would substantiate the argument for inde- and 3.1% were Indian. The mean age was 39.61pendent (unipolar) dimensions. For instance, if ex- (SD 11.02). A total of 58.5% of the participantshaustion and vigor are equally strong related to work had a high school qualiﬁcation (Grade 10-Grade 12),pressure (but in the opposite direction) this would while 39.2% possessed a (technical college) diplomasuggest that they represent opposite poles of one or university degree. Most participants were married/dimension. If, however, one of them is substantially living with a partner, with children living at homestronger related to work pressure this would mean (50.6%).that they represent different and thus independentdimensions. Because there is no clear evidence fordifferential relationships between these constructs Instruments2and the two ends of the energy and identiﬁcationdimensions we formulated the following hypotheses: MBI-GS. We used the MBI-GS (Schaufeli et al., 1996) to assess the core burnout dimensions with two Hypothesis 3: Cynicism/disengagement and subscales, namely Exhaustion and Cynicism. Ex- dedication/engagement will be equally strong haustion was measured with ﬁve items (e.g., “I feel related to other constructs (work pressure, au- emotionally drained from my work”). Cynicism was tonomy, organizational commitment, mental assessed with ﬁve items (e.g., “I have become less health), but in the opposite direction. enthusiastic about my work”). All items are scored on a seven-point scale, ranging from (0) “never” to (6) Hypothesis 4: Exhaustion and vigor will be “every day.” High scores on exhaustion and cynicism equally strong related to other constructs (work indicate burnout. pressure, autonomy, organizational commitment, OLBI. The OLBI originally distinguishes an ex- mental health), but in the opposite direction. haustion and disengagement dimension. However, both subscales include four items that are positively worded and four items that are negatively worded. Method This means that both ends of the energy and identi- ﬁcation dimensions are included in the OLBI. TheParticipants and Procedure A cross-sectional survey was conducted using a 2 Le Roux (2005) and Rost (2007) have conﬁrmed theconvenience sample of employees of a company in construct equivalence of the instruments used in the presentthe South African construction industry (N 528). study for different language and educational groups.
BURNOUT AND WORK ENGAGEMENT 213answering categories are (1) “strongly agree” to (4) icism for the MBI-GS, exhaustion and disengage-“strongly disagree.” The OLBI items are displayed in ment for the OLBI, vigor and dedication for thethe Appendix. UWES) ﬁtted responses to all instruments substan- UWES. The UWES (Schaufeli & Bakker, 2003; tially better than did one-factor solutions. All itemsSchaufeli et al., 2002) was used to assess the two core had signiﬁcant loadings on the expected factors ex-dimensions of work engagement, namely vigor and cept for the third item of the cynicism scale (i.e., “Idedication. Vigor was assessed with six items (e.g., just want to do my work and not be bothered”). This“At my work, I feel bursting with energy”). Dedica- is consistent with earlier studies (Schutte et al., 2000;tion was assessed with ﬁve items (e.g., “I ﬁnd the Storm & Rothmann, 2003). Consequently, we de-work that I do full of purpose and meaning”). All cided not to include this item in further analyses.items are scored on a seven-point rating scale, rang- We ﬁtted the responses to all three instruments si-ing from (0) “never” to (6) “every day.” High scores multaneously to the data. However, the energy dimen-indicate work engagement. sions (OLBI-exhaustion, OLBI-vigor, MBI-exhaustion, Work pressure was measured with six items that and UWES-vigor) were analyzed separately from thewere adapted from the Job Content Questionnaire identiﬁcation dimensions (OLBI-disengagement,(Karasek, 1985). The original statements were re- OLBI-dedication, MBI-cynicism, and UWES-dedica-phrased as questions (e.g., “Are you asked to do an tion). This was done in order to avoid building largeexcessive amount of work?”). Items were scored on a models (in this case including 36 manifest variables)scale ranging from (1) “almost never” to (4) “always,” that generally show a poor ﬁt to the data. Bentler andwith higher scores indicating higher job pressure. Chou (1987) suggest that models should not exceed the Autonomy was measured with six items from the total of 20 manifest variables because in large modelsvalidated questionnaire of Van Veldhoven, Meijman, with large sample sizes ‘the sample size multiplier thatBroersen and Fortuin (1997) (e.g., “Can you decide transforms the ﬁt function into a 2-variate will multiplyfor yourself how to carry out your work?”). Items a small lack of ﬁt into a large statistic’ (p. 97). Buildingwere scored on a four-point rating scale: (1) “almost smaller models still allows testing our hypotheses. Wenever” to (4) “always”. Higher scores signify a higher followed the same way of modeling to test the relation-level of autonomy. ships between the energy and identiﬁcation dimensions Mental health was measured with the General Health with other variables (work pressure, autonomy, mentalQuestionnaire (GHQ-28, Goldberg & Williams, 1988). health, and commitment) save one difference: we in-The GHQ-28 is a 28 item questionnaire generally used cluded age and gender as control variables. Speciﬁcally,for the screening of mental illness. The GHQ-28 asks age and gender had a path to all manifest variables ofparticipants to report if they have had any medical the models. CFAs were conducted with AMOS 7complaints and how their general health had been over (Arbuckle, 2006). Next to the inspection of the good-the past few weeks, rating them on a 4-point scale ness-of-ﬁt indices we performed chi-square differenceranging from (1) “better than usual” to 4 “much worse tests in order to compare alternative, nested models.than usual.” The scale taps four factors: somatic symp-toms, anxiety and insomnia, social dysfunction anddepression. Scores were coded such that higher overall Resultsscores indicate better mental health. Cronbach’s alpha and bivariate correlations between Organizational commitment was measured with the study variables are displayed in Table 1. Note thatﬁve items of the affective organizational commitment while all (sub-)scales had sufﬁcient reliability, for OLBIscale developed by Meyer, Allen, and Smith (1993). vigor this was .63. However, we had to keep thisAn example item is “This organization has a great subscale in order to retain a minimum of two indicatorsdeal of personal meaning for me.” Items were rated for each end of the continua.on a 5-point scale ranging from (1) “totally agree” to(5) “totally disagree.” Inferring Identiﬁcation andStatistical Analysis Energy Dimensions In preliminary, unreported CFAs, one- and two- The dimensionality of the identiﬁcation dimensionfactor models were ﬁtted to responses to each of the was tested with alternative models (see Figure 1). Wethree instruments separately. The results indicated tested whether considering separate identiﬁcationthat two-factor model solutions (exhaustion and cyn- factors that is, MBI-cynicism, UWES-dedication,
214 DEMEROUTI, MOSTERT, AND BAKKERTable 1Means, Standard Deviations, and Bivariate Correlations of the Study Variables Mean SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1. MBI exhaustion 2.51 1.40 .82 2. MBI cynicism 2.20 1.26 .44 .73 3. UWES vigor 4.48 1.10 .35 .42 .69 4. UWES dedication 4.95 1.19 .42 .48 .71 .85 5. OLBI exhaustion total1 2.17 .57 .62 .45 .53 .50 .74 6. OLBI exhaustion 2.47 .74 .60 .41 .44 .42 .90 .78 7. OLBI vigor 1.87 .57 .45 .37 .48 .45 .82 .49 .63 8. OLBI disengagement total1 2.07 .55 .52 .54 .55 .68 .67 .62 .53 .79 9. OLBI disengagement 1.97 .62 .38 .37 .48 .65 .50 .37 .51 .82 .6910. OLBI dedication 2.85 .69 .49 .54 .45 .49 .62 .65 .39 .85 .41 .7111. Mental health .68 .45 .54 .39 .37 .41 .61 .56 .49 .49 .39 .43 .9412. Work pressure 2.26 .55 .27 .08 .09 .02 .13 .17 .04 .04 .04 .11 .16 .7713. Autonomy 2.30 .63 .28 .18 .32 .36 .34 .28 .31 .36 .33 .28 .31 .09 .7814. Organizational commitment 2.04 .79 .31 .37 .36 .50 .30 .26 .27 .48 .49 .32 .19 .04 .22 .87Note. Cronbach’s alpha on the diagonal, N 528.1 OLBI exhaustion total and OLBI disengagement total refer to the average score of all positively and negatively wordeditems of the original exhaustion and disengagement OLBI dimensions, respectively.All correlations r |.13| are signiﬁcant at p .01, while correlations |.09| r |.13| are signiﬁcant at p .05.OLBI-disengagement, and OLBI-dedication (Model higher-order factors. Three different second-order1), was better compared to two second-order factors models were tested. In Model 2, the four ﬁrst-orderof distancing and dedication (Model 3) or compared factors of the identiﬁcation dimensions were used toto only one second-order factor of identiﬁcation deﬁne an overall identiﬁcation factor (assuming a(Model 2). Note that OLBI-disengagement included bipolar dimension). In Model 3, MBI-cynicism andthe four negatively formulated items and OLBI- OLBI-disengagement loaded on a distancing second-dedication the four positively formulated items of the order factor, while UWES-dedication and OLBI-disengagement scale. In this way, we had two indi- dedication loaded on a dedication second-order factorcators for each end of the continuum (i.e., two scales (assuming a unipolar dimension). The second-orderfor distancing and two for dedication), which is use- factors were allowed to correlate. In Model 4 weful for building second-order latent factors. The same tested the discriminant validity of the two second-procedure was followed for the energy dimensions in order latent factors (of Model 3) by constraining theira separate series of analyses including MBI- correlation to be 1 (implying identical constructs, cf.exhaustion, UWES-vigor, OLBI-exhaustion and Bagozzi, 1993). Following the same logic we testedOLBI-vigor, OLBI-exhaustion, and OLBI-vigor as parallel models for the energy dimensions using theﬁrst-order factors. respective four ﬁrst-order factors. All models were Model 1 explains responses to the items in terms of nested in Model 1 so that none can ﬁt the data betterfour ﬁrst-order factors. This ﬁrst-order model is impor- than the ﬁrst-order factors model but they were moretant because its ﬁt establishes an upper limit for the parsimonious in that they included fewer parameters.higher-order models (cf. Marsh, Antill, & Cunningham, First, we discuss results regarding the identiﬁca-1989). As can be seen in Table 2, the ﬁt of Model 1 is tion dimensions. Model 2, including a single higher-reasonable for both the identiﬁcation and the energy order factor, ﬁtted the data signiﬁcantly worse thandimensions. For both dimensions, the factor structure is Model 1. This means that much of the variationwell-deﬁned in that all factor loadings were statistically among the ﬁrst-order factors is unexplained by asigniﬁcant and each of the four factors accounts for a global identiﬁcation factor. Model 3 (positing twosigniﬁcant portion of the variance. higher-order factors) provides a better ﬁt to the data The aim of the higher-order models is to describe than the one-factor model (Model 2) and is not sig-correlations among ﬁrst-order factors in terms of niﬁcantly worse than the ﬁrst-order factors model
216 DEMEROUTI, MOSTERT, AND BAKKERTable 2Goodness-of-Fit Indices (Maximum-Likelihood Estimates) for the Conﬁrmatory Factor Analyses 2 Model df p AGFI RMSEA TLI CFI Identiﬁcation dimensions1. First-order factors 332.90 113 .001 .90 .06 .92 .932. One second-order factor 368.88 115 .001 .89 .07 .91 .923. Two second-order factors 334.01 114 .001 .90 .06 .92 .934. Two second-order factors constrained 336.60 115 .001 .90 .06 .92 .93Null 3331.26 136 — .26 .21 — — Energy dimensions1. First-order factors 496.51 146 .001 .87 .07 .87 .892. One second-order factor 521.18 148 .001 .87 .07 .86 .883. Two second-order factors 497.52 147 .001 .87 .07 .87 .894. Two second-order factors constrained 507.35 148 .001 .87 .07 .87 .88Null 3242.47 171 — .32 .20 — —Note. N 528. 2 chi square; df degrees of freedom; AGFI adjusted goodness of ﬁt index; RMSEA root meansquare error of approximation; TLI Tucker Lewis index; CFI comparative ﬁt index.(Model 1). This would suggest that distancing and Relations of Burnout and Workdedication are distinguishable (i.e., not representing Engagement With Other Constructstwo ends of a bipolar construct). However, the esti-mated correlation between the second-order factors If burnout and work engagement are each other’swas high (-.83). Indeed, the model (Model 4) that opposite, they should be equally strong related toassumed no discriminant validity between the sec- other constructs but in the opposite direction. Weond-order factors, distancing and dedication, was not focused on work pressure, autonomy, organizationalsigniﬁcantly worse than Model 3, which included 2 commitment, and mental health. The examination istwo correlated second-order factors, (1) 2.59, accomplished by adding each construct (as latentns, or Model 1, the ﬁrst-order factor model ( 2 factors with manifest variables) separately to Model(2) 3.70, ns). This suggests that distancing and 2 (including one second-order factor) and Model 3dedication are opposite ends of one dimension sup- (including two second-order factors) considered inporting Hypothesis 1. the previous section and by allowing them to corre- The results for the energy dimension were some- late with the second-order factors. Additionally, agewhat different. Again Model 2, positing a single and gender were included as control variables withsecond-order factor showed a worse ﬁt to the datathan Model 1. Model 3, positing two higher-order paths to each manifest variable. Table 3 displays thefactors of exhaustion and vigor, did not ﬁt worse to estimated standardized correlations.the data than Model 1 ( 2(1) 1.01, ns). This Work pressure. The work pressure latent factorindicates that exhaustion and vigor are distinguish- was inferred from three item parcels (each represent-able. The estimated correlation was high ( .81), ing the average of two items) as manifest variables.which implies that exhaustion and vigor overlap When work pressure was added to Model 2, it wassubstantially. Constraining the correlation between unrelated to the identiﬁcation second-order latent fac-the higher order factors, exhaustion and vigor, to tor but was signiﬁcantly related to the second-orderbe equal to one resulted in a slightly worse ﬁt of latent factor of vigor/exhaustion. When two second-the model—that is, Model 4 was signiﬁcantly order latent factors were posited, work pressure wasworse than both Model 3 ( 2(1) 9.83, p .01), positively related to the exhaustion factor and unre-including two distinguishable higher order factors, lated to the vigor factor. Again, it was unrelated toand Model 1, the ﬁrst-order factor model the distancing and engagement factors. Thus, Hy-( 2(2) 10.84, p .01). Thus, the energy com- pothesis 3 is conﬁrmed for work pressure since it isponents seem to form two distinguishable yet unrelated to both distancing and dedication. On thehighly related dimensions. contrary, Hypothesis 4 should be rejected for work
BURNOUT AND WORK ENGAGEMENT 217Table 3Relations (Estimated Correlations) of Higher Order Energy and Identiﬁcation Factors to Work Pressure,Autonomy, Organizational Commitment, and Mental Health After Controlling for Gender and Age Models containing one higher order factor Models containing two higher order factors Energy1 Identiﬁcation1 Exhaustion Vigor Distancing Dedication # a #b #Work pressure .20 .01 .28 .02 .10 .05#Autonomy .44 .41 .38a .46b .36a .40bOrganizational commitment .48 .67 .41a .55b .59a .65bMental health .79 .56 .77a .68b .62a .47bNote. All correlations were signiﬁcant at p .001 except for the correlations marked with the # symbol.1 High scores indicate high work engagement (i.e. high energy and high identiﬁcation level).a,b Means with different superscripts differ signiﬁcantly at the p .05 level (as calculated through AMOS by means ofcritical ratios for differences).pressure because it shows differential relationships related to the second-order factors of attitudes andwith the exhaustion and vigor factors. energy. However, the correlation was stronger for the Autonomy. The autonomy latent factor was in- energy factor. The model including separate exhaus-ferred from three item parcels (each representing the tion and vigor second-order factors showed that theaverage of two items) as manifest variables. Auton- correlation between exhaustion and mental healthomy was related to both the identiﬁcation and the was stronger than the correlation between vigor andenergy second-order latent factors. When two higher mental health. Similarly, mental health was strongerorder factors of attitudes were posited (i.e., Model 2), related to disengagement than to dedication. Contrarythe dedication-autonomy correlation was similar to to Hypotheses 3 and 4, mental health is strongerthe distancing-autonomy correlation. However, the related to the negatively worded dimensions.vigor-autonomy correlation was signiﬁcantly higherthan the exhaustion-autonomy correlation. Thus, au- Common Method Variancetonomy showed the same pattern of relationshipswith both identiﬁcation components, substantiating As with all self-report data, there is the potentialHypothesis 3, but a more differentiated pattern for the for the occurrence of method variance. Two teststwo energy components, rejecting Hypothesis 4. were conducted to determine the extent of method Organizational commitment. Using the ﬁve variance in the current data. First, a Harmon one-items we built three parcels to operationalize the factor test was conducted (Podsakoff & Organ, 1986)latent factor of commitment. Organizational commit- in two series of analysis: (a) all energy items and thement had a stronger correlation with the identiﬁcation items of each of the other constructs separately andfactor than with the energy factor. When two higher- (b) all identiﬁcation items and the items of each oforder identiﬁcation factors were posited they showed the other constructs. Results from these tests sug-a similar relationship with commitment. When two gested the presence of at least ﬁve factors in eachhigher-order energy factors were included, the vigor- analysis, indicating that common method effectscommitment correlation was signiﬁcantly stronger were not a likely contaminant of the results observedthan the exhaustion-commitment correlation. Thus, in our study. To conﬁrm these results, additionalsimilar to the ﬁndings regarding autonomy, organi- analyses were performed to test for common methodzational commitment showed the same pattern of variance following the procedure used by Williams,relationships with both identiﬁcation components, Cote, and Buckley (1989). We compared Model 3,substantiating Hypothesis 3, and a differentiated pat- including the additional constructs and the controltern for the two energy components, rejecting Hy- variables, with a model including additionally a sin-pothesis 4. gle method factor. Results indicated that while the Mental health. The mental health factor was method factor did improve model ﬁt in four of theinferred from four item parcels (each representing the seven cases (the model with energy items and workaverage of seven items belonging to one dimension) pressure could not be estimated), it accounted for aas manifest variables. Mental health was signiﬁcantly small portion (10%) of the total variance, which is
218 DEMEROUTI, MOSTERT, AND BAKKERless than half the amount of method variance (25%) Findings regarding the relationships between theobserved by Williams et al. (1989). Both tests sug- burnout and work engagement dimensions and hypo-gest that common method variance is not a pervasive thetical predictors and outcomes showed a similarproblem in this study. picture. Expanding Gonzalez-Roma et al.’s (2006) ´ ´ ﬁndings, results showed that work pressure, auton- Discussion omy, and organizational commitment have equally strong relationships with distancing and dedication, The aim of this study was to examine whether the but in an opposite fashion. Only mental health turneddimensions of burnout and work engagement are out to be somewhat stronger related to distancingbipolar constructs representing each other’s opposite. than to dedication. This does not seem to be anIn order to investigate this we used the MBI-GS artifact of the item formulation because the GHQ-28(measuring burnout using negatively formulated includes both positively and negatively wordeditems only), the UWES (measuring work engagement items. These ﬁndings largely support the idea thatusing positively formulated items only), and the distancing and dedication represent a bipolar con-OLBI (measuring both burnout and work engage- struct (“identiﬁcation”) since they show no substan-ment as bipolar constructs using positively and neg- tial differences in the pattern of relationships withatively formulated items). Practically, these scales other relevant constructs. In contrast, vigor and ex-measure parallel dimensions using items with over- haustion show a different pattern of relationshipslapping content. In addition, we examined the rela- with work pressure, autonomy, organizational com-tionships of the derived dimensions to work pressure, mitment, and mental health. Autonomy and commit-autonomy, organizational commitment, and mental ment are stronger related to vigor than to exhaustion,health. whereas work pressure and mental health are stronger Taken together, the results inhibit us from provid- related to exhaustion than to vigor. These ﬁndingsing a simple answer to the question whether burnout further substantiate the argument that vigor and ex-and work engagement are bipolar constructs. Our haustion represent independent dimensions.ﬁndings indicate that we should answer this question The logical question now is how can we makefor each dimension separately. While the identiﬁca- sense of these ﬁndings? The ﬁnding that the distanc-tion dimensions of burnout (cynicism/disengage- ing and dedication factors represent two ends of onement) and work engagement (dedication) seem to be construct is not very surprising because people caneach other’s opposite, the energy dimensions (ex- either hold negative or positive attitudes toward theirhaustion vs. vigor) seem to represent two separate but work. It seems unlikely that they endorse both simul-highly related constructs. This conclusion can be taneously. This is also justiﬁed by the distribution ofjustiﬁed both on the basis of the CFA ﬁndings, and the scores across the identiﬁcation dimensions. Thus,the pattern of relationships with other constructs. responses to the identiﬁcation items of burnout and According to the CFA ﬁndings, constraining the work engagement constructs seem to follow thecorrelation between the second-order latent factors of structure of the circumplex of emotions as suggestedthe identiﬁcation dimensions to be one did not make by Watson and Tellegen (1985) where distancing andthe model inferior to a model without this restriction. dedication are considered as two opposites of oneThis means that their correlation was so high that we continuum. In addition, Cacioppo and Berntsoncan assume that the constructs practically overlap. (1994) have argued that the evaluative space in whichThis ﬁnding agrees with Gonzalez-Roma et al.’s ´ ´ attitudes exist is two-dimensional, corresponding to(2006) ﬁndings who used nonparametric methods to the dimensions of the Watson and Tellegen model.assess the dimensionality of two of the three instru- On the contrary, the energy dimensions as opera-ments included in our study (MBI-GS and UWES). tionalized by the various instruments seem to containFor the energy dimensions, however, constraining the different aspects. This applies particularly to the op-correlation of the two second-order latent factors to erationalizations of vigor. While OLBI-vigor is mea-one resulted in a signiﬁcantly worse model ﬁt. Al- sured with items like “After working, I have enoughthough the bivariate and estimated correlation be- energy for my leisure activities” or “When I work, Itween exhaustion and vigor was high, they do not usually feel energized,” a typical item of UWES-seem to form quite two opposites of one continuum. vigor is “At my work, I feel bursting with energy.”This ﬁnding also agrees with Gonzalez-Roma et al. ´ ´ The difference between these items is that OLBI(2006) who found that the exhaustion and vigor items conceives vigor as having sufﬁcient energy reservesconstitute a weak to moderate energy dimension. during and after work while UWES views vigor as
BURNOUT AND WORK ENGAGEMENT 219having a surplus of energy reserves while being at in South Africa (e.g., Black, Colored, and Indian)work. Moreover, vigor, as deﬁned by Schaufeli and from all age groups and in different sectors. How-Bakker (2003, 2004), in addition to the core meaning ever, the ﬁndings seem generally consistent withof high energy levels, seems to include a motivational Gonzalez-Roma et al. (2006) who conducted their ´ ´element as well (i.e., the willingness to invest effort). research in The Netherlands with Dutch languageThus, conceptually and psychometrically, at least instruments.UWES-vigor is not exactly the opposite of exhaus- Another possible drawback of this study is that thetion as measured with the MBI-GS because it also use of the English language for the questionnairescontains motivational aspects. could also have a detrimental inﬂuence on the results In light of these ﬁndings we could suggest that of the study because of the possibility of misunder-reporting different scores for the identiﬁcation com- standing and misinterpretation of items from thoseponents of burnout and work engagement does not participants for whom English is not their ﬁrst lan-seem necessary since they more likely represent the guage. In order to minimize the inﬂuence of thissame construct. Our ﬁndings suggest using two dif- possible drawback, we explained the meaning offerent scores for MBI-exhaustion and UWES-vigor, words that could have possible been misunderstoodbecause these scales measure two different but highly in footnotes. In order to reject the possibility that our(negatively) related constructs. Alternatively, the ﬁndings are inﬂuenced by the instruments that weOLBI instrument could be used, which has been utilized, testing dimensionality issues with otherproven to contain two factors of exhaustion and dis- scales would put our hypotheses to an even moreengagement (or, positively framed, vigor and engage- robust test. However, the existing alternatives—thatment) (Demerouti et al., 2003; Demerouti & Bakker, is, the instruments of Shirom (2003) and Kristensen2008) operationalized by positively and negatively et al. (2005) —focus only on the exhaustion dimen-worded items, thus capturing both ends of the con- sion. A related drawback concerns the low reliabilitytinuum. Note that it is necessary to use the total ( .70) of the UWES-vigor scale and OLBI-vigorscores for the exhaustion/vigor and for the engage- subscale. This might be due to the previous limita-ment/ disengagement dimensions and not to split tions, sampling error and misunderstanding of thethem as was done in the present study (cf. low reli- items. Note, however, that the OLBI-vigor subscaleability of OLBI vigor). is not supposed to be analyzed separately from OLBI-exhaustion. Together, the items form a reliableLimitations and Future Research scale. A ﬁnal potential drawback concerns the way of The ﬁrst limitation of the study is its reliance on analysis. First, as we conducted analysis for the en-self-report, cross-sectional data. While it provides a ergy and the identiﬁcation dimensions separately,useful consideration of the factor structure of the this has implications for establishing construct valid-different instruments, it cannot address the validity ity as for example, the relationships between theissues requiring a diversity of measurement formats. dimensions could not be controlled for. Second,By conducting two different tests we found that re- when we conducted linearity tests of means compar-sponses to the items were not seriously inﬂuenced by ison we found that of the 162 comparisons, 41 pairsan artiﬁcial common method factor. However, future showed a signiﬁcant deviation from linearity at pstudies aiming to examine dimensionality issues need .003 (applying Bonferroni correction). In 21 of allto integrate data from other sources of information signiﬁcant deviations from linearity, three items ofsuch as objective absenteeism in order to minimize UWES-vigor were involved. Strictly speaking, wecommon method artifacts. would have to eliminate UWES-vigor from the anal- Several aspects of the study raise concerns regard- ysis or conduct nonparametric analyses. However,ing the generalizability of our results. Speciﬁcally, because only one of the six scales seems to showalthough the sample of participants represented a nonlinear relationships with items of the other scales,diverse number of jobs (e.g., employees in different we decided to keep this scale in the analysis and tobusiness units and departments), our sample is re- continue with CFA instead of nonparametric tests.stricted to employees of the construction industry and The practical importance of uncovering whetherhas not been randomly selected from the full range of burnout and work engagement are each other’s op-possible occupations. Moreover, our sample was posite concerns mainly psychometric issues withinoverrepresented by White, middle-aged men. Future organizational studies. Organizations need to havestudies might focus more exclusively on other groups short and valid screening instruments to evaluate the
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222 DEMEROUTI, MOSTERT, AND BAKKER Appendix Oldenburg Burnout InventoryInstruction: Below you ﬁnd a series of statements with which you may agree or disagree. Using the scale,please indicate the degree of your agreement by selecting the number that corresponds with each statement Strongly Strongly agree Agree Disagree disagree 1. I always ﬁnd new and interesting aspects in my work. 1 2 3 4 2. There are days when I feel tired before I arrive at work. 1 2 3 4 3. It happens more and more often that I talk about my work in a negative way. 1 2 3 4 4. After work, I tend to need more time than in the past in order to relax and feel better. 1 2 3 4 5. I can tolerate the pressure of my work very well. 1 2 3 4 6. Lately, I tend to think less at work and do my job almost mechanically. 1 2 3 4 7. I ﬁnd my work to be a positive challenge. 1 2 3 4 8. During my work, I often feel emotionally drained. 1 2 3 4 9. Over time, one can become disconnected from this type of work. 1 2 3 410. After working, I have enough energy for my leisure activities. 1 2 3 411. Sometimes I feel sickened by my work tasks. 1 2 3 412. After my work, I usually feel worn out and weary. 1 2 3 413. This is the only type of work that I can imagine myself doing. 1 2 3 414. Usually, I can manage the amount of my work well. 1 2 3 415. I feel more and more engaged in my work. 1 2 3 416. When I work, I usually feel energized. 1 2 3 4Note. Disengagement items are 1, 3(R), 6(R), 7, 9(R), 11(R), 13, 15. Exhaustion items are 2(R), 4(R), 5, 8(R), 10, 12(R),14, 16. (R) means reversed item when the scores should be such that higher scores indicate more burnout. Received July 15, 2008 Revision received October 3, 2009 Accepted October 12, 2009 y E-Mail Notiﬁcation of Your Latest Issue Online! Would you like to know when the next issue of your favorite APA journal will be available online? This service is now available to you. Sign up at http://notify.apa.org/ and you will be notiﬁed by e-mail when issues of interest to you become available!