measure engage and burnout

WILMAR B. SCHAUFELI, MARISA SALANOVA,VICENTE GONZ ALEZ-ROM A and ARNOLD B. BAKKER

THE MEASUREMENT OF ENGAGEMENT AND BURNOUT:A TWO SAMPLE CONFIRMATORY FACTOR

ANALYTIC APPROACH

(Received 15 December, 2000; Accepted 5 August, 2001)

ABSTRACT. This study examines the factorial structure of a new instrument tomeasure engagement, the hypothesized opposite of burnout in a sample of univer-sity students (N = 314) and employees (N = 619). In addition, the factorial structureof the Maslach-Burnout Inventory-General Survey (MBI-GS) is assessed and the rela-tionship between engagement and burnout is examined. Simultaneous confirmatoryfactor analyses in both samples confirmed the original three-factor structure of theMBI-GS (exhaustion, cynicism, and professional efficacy) as well as the hypothesizedthree-factor structure of engagement (vigor, dedication, and absorption). Contrary toexpectations, a model with two higher-order factors burnout and engagement did not show a superior fit to the data. Instead, our analyses revealed an alterna-tive model with two latent factors including: (1) exhaustion and cynicism (core ofburnout); (2) all three engagement scales plus efficacy. Both latent factors are neg-atively related and share between 22% and 38% of their variances in both samples.Despite the fact that slightly different versions of the MBI-GS and the engagementquestionnaire had to be used in both samples the results were remarkably similaracross samples, which illustrates the robustness of our findings.

KEY WORDS: burnout, engagement, measurement, students.

Two trends recently emerged in burnout research which both boil downto a broadening of the traditional concept and scope (Maslach et al.,2001). First, the concept of burnout that was initially closely linkedto the human services such as health care, education, and social workwhere employees do people work of some kind, has been expandedtowards all other professions and occupational groups. Second, burnoutresearch seems to shift towards its opposite: job engagement. Instead oflooking exclusively to the negative pole, researchers recently extendedtheir interest to the positive pole of workers well-being. Seen fromthis perspective, burnout is rephrased as an erosion of engagementwith the job. This development reflects an emerging trend towards apositive psychology that focuses on human strengths and optimalfunctioning rather than on weaknesses and malfunctioning (Seligmanand Csikszentmihalyi, 2000).

Journal of Happiness Studies 3: 7192, 2002. 2002 Kluwer Academic Publishers. Printed in the Netherlands.

72 WILMAR B. SCHAUFELI ET AL.

Burnout and its MeasurementOriginally, burnout as measured with the Maslach-Burnout Inventory(MBI Maslach and Jackson, 1981) was defined as a three-dimensionalsyndrome of emotional exhaustion (i.e. the draining of emotionalresources because of demanding interpersonal contacts with others),depersonalization (i.e. a negative, callous, and cynical attitude towardsthe recipients of ones care or services), and lack of personal accom-plishment (i.e. the tendency to evaluate ones work with recipientsnegatively). Typically, burnout was assumed to occur in individualswho work with people in some capacity, for instance in health care,social services, or education. For that very reason, all three originaldimensions of the MBI refer to contacts with other people at the job.However, nearly a quarter of a century of research and practice haslearned that burnout also exists outside the realm of the human ser-vices. Therefore, the concept of burnout and its measurement werebroadened to include all employees and not only those who do peoplework (Maslach and Leiter, 1997). Consequently, the original version ofthe MBI was adapted for use outside the human services; this new ver-sion was called MBI-General Survey (MBI-GS: Schaufeli et al., 1996).The three dimensions of the MBI-GS parallel those of the original MBI,in the sense that they are more generic and do not refer to other peopleone is working with. For instance, the first dimension exhaustion ismeasured by items that tap fatigue but do not make direct reference toother people as the source of ones tiredness. The items that measurecynicism reflect indifference or a distant attitude towards work in gen-eral, not necessarily with other people. Finally, professional efficacyhas a broader focus compared to the parallel MBI-scale encompass-ing both social and non-social aspects of occupational accomplish-ments. Psychometric research with the MBI-GS using confirmatoryfactor analysis demonstrated that the three-factor structure is invariantacross occupations such as clerical and maintenance employees, tech-nical staff, nurses, and managers (Leiter and Schaufeli, 1996), softwareengineers and university staff (Taris et al., 1999), and blue collar andwhite collar workers (Schutte et al., 2000). In addition, in the latterstudy the factor-structure of the MBI-GS proved to be cross-nationallyinvariant across samples from Sweden, Finland, and The Netherlands.

The first objective of the current study is to replicate the invarianceof the three-factor structure of the MBI-GS across a sample of uni-versity students and employees, respectively. Previous studies used aslightly adapted original version of the MBI to measure burnout among

ENGAGEMENT AND BURNOUT 73

university students in which, for instance, instructors was substi-tuted for recipients (Ballogu et al., 1995; Gold et al., 1989; Gold andMichael, 1985; Powers and Gose, 1986). However, a suchlike reword-ing is not unproblematic because the meaning of an item might changedramatically. For instance, the item I treat some instructors as if theywere impersonal objects does not refer to a cynical or indifferent atti-tude towards the main activity of a student (i.e. studying and takingclasses) but to a negative attitude towards another person that is, atleast partly based on personal preferences rather than on study-relatedexperiences. As a matter of fact, this holds for the entire adapted deper-sonalization scale. Since the MBI-GS is a more generic instrumentthat measures burnout without referring to other people, the inher-ent problems of rewording are avoided. The substitution in the currentinvestigation of studies for work/job is unproblematic because theformer refers to the daily activities that are performed by the studentsthat constitute their very role. Burnout in the student sample thereforemeans feeling exhausted because of study demands, having a cynicaland detached attitude towards ones study, and feeling incompetent asa student.

Engagement and its MeasurementTo date, relatively little attention has been paid to concepts that might beconsidered antipodes of burnout. An exception is psychological pres-ence or to be fully there, a concept that emerged from role theory andis defined as an experiential state that accompanies personally engag-ing behaviors that involve the channeling of personal energies intophysical, cognitive, and emotional labors (Kahn, 1992). Although Kahn(1992) presents a comprehensive theoretical model of psychologicalpresence, he does not propose an operationalization of the construct.More recently, Maslach and Leiter (1997) assumed that engagementis characterized by energy, involvement, and efficacy which are con-sidered the direct opposites of the three burnout dimensions exhaus-tion, cynicism, and lack of professional efficacy, respectively. Engagedemployees have a sense of energetic and effective connection withtheir work activities and they see themselves as able to deal com-pletely with the demands of their job. By implication, engagement inthe view of Maslach and Leiter (1997) is assessed by the opposite pat-tern of scores on the three MBI dimensions. That is, according to theseauthors, low scores on exhaustion and cynicism, and high scores on effi-cacy are indicative for engagement. By using the MBI for measuring


engagement, however, it is impossible to study its relationship withburnout empirically since both concepts are considered to be oppositepoles of a continuum that is covered by one single instrument, the MBI.

We take a different perspective by considering burnout and engage-ment to be opposite concepts that should be measured indepen-dently with different instruments. Based on a theoretical analysis(Schaufeli and Bakker, 2001), two underlying dimensions have beenidentified of work-related well-being: (1) activation, ranging fromexhaustion to vigor, and (2) identification, ranging from cynicism todedication. Burnout is characterized by a combination of exhaustion(low activation) and cynicism (low identification), whereas engagementis characterized by vigor (high activation) and dedication (high identi-fication). Furthermore, burnout includes reduced professional efficacy,and engagement includes absorption. In contrast to both the other ele-ments of burnout and engagement that are direct opposites (exhaustionvs. vigor and cynicism vs. dedication), reduced efficacy and absorptionare not each others direct opposites, rather they are conceptually dis-tinct aspects that are not the end points of some underlying continuum.It is noteworthy in this respect that reduced efficacy was added as aconstituting element of burnout on second thoughts after it appearedas a third factor from a factor-analysis of a preliminary version of theMBI (Maslach, 1993). In a similar vein, absorption was found to be arelevant aspect of engagement after some 30 in-depth interviews werecarried out (Schaufeli et al., 2001). Hence, engagement is defined as apositive, fulfilling, work-related state of mind that is characterized byvigor, dedication, and absorption. Rather than a momentary and specificstate, engagement refers to a more persistent and pervasive affective-cognitive state that is not focused on any particular object, event, indi-vidual, or behavior. Vigor is characterized by high levels of energy andmental resilience while working, the willingness to invest effort in oneswork, and persistence even in the face of difficulties. Dedication is char-acterized by a sense of significance, enthusiasm, inspiration, pride, andchallenge. Instead of involvement we prefer to use the term dedication.Although, involvement like dedication (see above) is usually definedin terms of psychological identification with ones work or ones job(Kanungo, 1982; Lawler and Hall, 1970), whereby the latter goes onestep beyond, both quantitatively as well as qualitatively. In a qualitativesense, dedication refers to a particularly strong involvement that goesone step further than the usual level of identification. In a qualitativesense, dedication has a wider scope by not only referring to a particular


cognitive or belief state but including the affective dimension as well.The final dimension of engagement, absorption, is characterized bybeing fully concentrated and deeply engrossed in ones work, wherebytime passes quickly and one has difficulties with detaching oneselffrom work. Being fully absorbed in ones work comes close to whathas been called flow, a state of optimal experience that is character-ized by focused attention, clear mind, mind and body unison, effortlessconcentration, complete control, loss of self-consciousness, distortionof time, and intrinsic enjoyment (Csikszentmihalyi, 1990). However,typically, flow is a more complex concept that includes many aspectsand refers to rather particular, short-term peak experiences insteadof a more pervasive and persistent state of mind, as is the case withengagement.

Thus, contrary to Maslach and Leiter (1997) we do not feel thatengagement is adequately measured by the opposite profile of MBIscores. Although we concur that, conceptually speaking, engagementis the positive antithesis of burnout, we acknowledge that the measure-ment of both concepts, and hence its structure, differs. As a conse-quence, engagement is operationalized in its own right. It is the secondaim of our paper to investigate some psychometric features of our self-constructed engagement inventory that consists of the three dimensionsmentioned above: vigor, dedication, and absorption. More specifically,the internal consistencies of the three scales as well as their factorialvalidity will be studied.

Engagement and BurnoutIn addition to the psychometric qualities of the engagement and burnoutinventories, the relationship between both concepts will be researched.Since engagement is defined as the opposite experience of burnout, it isexpected that all burnout and engagement scales are negatively related(i.e. when efficacy is reversibly scored as reduced efficacy). A negativecorrelation is particularly expected between exhaustion and vigor, andbetween cynicism and dedication since they represent opposite poles ofthe activation and identification dimensions, respectively (see above).

Moreover, since burnout and engagement are both multidimensionalconstructs it is expected that a model that takes this higher-order struc-ture into consideration fits best to the data. In other words, we predictthat the fit of a model that assumes two second-order factors (burnoutand engagement) on which all three burnout scales and all threeengagement scales load, respectively, shows a superior fit compared to


a model that assumes that all six scales refer to one underlying general,undifferentiated dimension (well-being).

METHOD

Samples and ProcedureSample 1 consisted of 314 undergraduate students of the Universityof Castellon, Spain (214 females 68% and 100 males 32%). Theirmean age was 22.3 years (SD = 3.7); 45% was in their first year, 23%in their second year, 14% in their third year, and 18% in their finalyear, respectively. The questionnaire was administered in the spring of1999 to students enrolled in several classes, the majority in psychology(55%), followed by tourism (20%), computer science (18%), and otherstudies (7%).

Sample 2 consisted of 619 employees (291 females 47% and328 males 53%) from 12 Spanish private and public companies1.They were employed in various jobs and occupational fields, such asclerical jobs (33%), technical and support staff (23%), human services(16%), management (9%), sales (7%), laboratory settings (7%), andproduction line operators (5%). The mean age of the sample was 32.8(SD = 8.36). The questionnaire was distributed in 1999 by profes-sionals of the human resources departments of the organizations thatparticipated in the study.

InstrumentBurnout was assessed with the Spanish version (Salanova andSchaufeli, 2000) of the MBI-GS (Schaufeli et al., 1996) that was slightlyadapted for use in the students sample (e.g., instead of I feel emo-tionally drained from my work, I feel emotionally drained from mystudy). The MBI-GS consists of 16 items that are scored on threescales: Exhaustion (EX) (5 items; e.g., the above mentioned item);Cynicism (CY) (5 items: e.g., I have become less enthusiastic aboutmy study/work); Efficacy (EF) (6 items; e.g., I can effectively solvethe problems that arise in my study/work). All items are scored on a7-point frequency rating scale ranging from 0 (never) to 6 (always).High scores on EX and CY and low scores on EF are indicative forburnout (i.e. all EF-items are reversibly scored). Internal consisten-cies (Cronbachs ) for the EX, CY, and EF scales were 0.66, 0.64,


and 0.74 (Sample 1) and 0.85, 0.78, and 0.73 (Sample 2), respectively.After, removing one item (When Im in class or Im studying I dontwant to be bothered) the value of the initial coefficient of CY wassubstantively increased to 0.79 (Sample 1) and 0.84 (Sample 2). Thus,with one notable exception (EX in Sample 1), all -values meet thecriterion of 0.70 (Nunnaly and Bernstein, 1994).

Engagement was assessed with 24 self-constructed items that weresimultaneously formulated in Spanish and English. Subsequently, abilingual psychologist checked the semantic and syntactic equivalenceof both versions. The Spanish version for employees (Salanova et al.,2001) was slightly reworded for use in the students sample.1 Theengagement items are supposed to reflect three underlying dimensions:Vigor (VI) (9 items; e.g., When I get up in the morning, I feel likegoing to class/work); Dedication (DE) (8 items; e.g., Im enthusiasticabout my study/job), and Absorption (AB) (7 items; e.g., WhenIm studying/working, I forget everything around me). The engage-ment items are similarly scored as those of the MBI-GS. In order toavoid answering bias, burnout and engagement items were randomlymerged into a 40-item questionnaire. The psychometric properties ofthe engagement scales are reported in the next section.

AnalysesReliability analysisIn a first step, internal consistencies (Cronbachs ) were computed forthe three engagement scales whereby an iterative process was used toremove those items that either negatively affected values of or thatdid not make a positive contribution to the level of . As a result of thefirst step, three subscales emerged with a minimum number of itemsand maximum internal consistency.

Model testing using structural equation modeling (SEM)SEM methods as implemented by AMOS (Arbuckle, 1997) were usedto test various models simultaneously in both samples the so-calledmultiple-group method. First, the hypothesized correlated three-factormodel of the MBI-GS was tested across both samples and comparedto the fit of a one-factor model that assumes that all items load on onesingle underlying dimension. Second, in a similar vein, the hypoth-esized correlated three-factor model of engagement was tested across


both samples and compared to a one-factor model. Finally, the relation-ship of burnout and engagement was studied by testing two alternativemodels across both samples: (1) a model (M1) that assumes that allburnout and engagement scales refer to one underlying general well-being dimension; that is, M1 consists of one second-order dimensionon which all burnout and engagement scales are supposed to load; (2) amodel (M2) that assumes that burnout and engagement are two differentbut related constructs; that is, M2 consists of two correlated second-order dimensions burnout and engagement on which the burnoutand engagement scales are supposed to load, respectively.

Fit indicesMaximum likelihood estimation methods were used and the input foreach analysis was the covariance matrix of the items. The goodness-of-fit of the models was evaluated using absolute and relative indices.The absolute goodness-of-fit indices calculated were (cf. Joreskog andSorbom, 1986): (1) the 2 goodness-of-fit statistic; (2) the Root MeanSquare Error of Approximation (RMSEA); (3) the Goodness-of-FitIndex (GFI); (4) the Adjusted Goodness-of-Fit Index (AGFI). The2-test is a test of the difference between the observed covariancematrix and the one predicted by the specified model. Non-significantvalues indicate that the hypothesized model fits the data. However,this index is sensitive to sample size, so that the probability of reject-ing a hypothesized model increases as sample size increases. To over-come this problem, the computation of relative goodness-of-fit indicesis strongly recommended (Bentler, 1990). The error of approximationrefers to the lack of fit of the model to the population covariance matrix,and RMSEA is a measure of the discrepancy per degree of freedom forthe model. Values smaller than 0.08 are indicative of an acceptable fit,and values greater than 0.1 should lead to model rejection (Cudeck andBrowne, 1993). The GFI is a measure of the relative amount of vari-ance accounted for by the model, whereas the AGFI also takes modelparsimony into account. Since the distribution of the GFI and the AGFIis unknown, no statistical test or critical value is available (Joreskogand Sorbom, 1986).

The relative goodness-of-fit indices computed were (cf. Marshet al., 1996): (1) Normed Fit Index (NFI); (2) Non-Normed Fit Index(NNFI) also called the Tucker Lewis Index (TLI); (3) ComparativeFit Index (CFI). The NFI represents the point at which the model being


evaluated falls on a scale running from an unconstrained null model toperfect fit of the hypothesized model. This index is normed to fall on a01 continuum. In contrast, the NNFI which in addition takes modelparsimony into account could fall outside this range due to samplingfluctuation. Finally, the CFI is a population measure of model mis-specification that is particularly recommended for model comparisonpurposes (Goffin, 1993). For all three relative fit-indices, as a rule ofthumb, values greater than 0.90 are considered as indicating a good fit(Hoyle, 1995).

RESULTS

In the first step, internal consistencies were computed for the threeengagement scales in each sample. Initial coefficients for the threeengagement scales were: VI (9 items), = 0.68 (Sample 1) and = 0.80 (Sample 2); DE (8 items), = 0.91 (in both samples); AB(7 items), = 0.73 (Sample 1) and = 0.75 (Sample 2). In the stu-dents sample, the value of could be improved for VI when three itemswere eliminated ( = 0.78), whereas the value of remained virtuallythe same for the employees (0.79). For reasons of parsimony three itemscould be excluded from DE without substantially decreasing the scalesinternal consistency; = 0.84 and = 0.89 for the students and theemployees, respectively. For similar reasons, one AB-item was elim-inated without seriously affecting -values: = 0.73 and = 0.72for students and employees, respectively. Appendix includes the result-ing items of the three engagement scales. Table I shows mean values,standard deviations, internal consistencies, and inter-correlations of theburnout and engagement scales in both samples.

As can be seen from Table I as expected all burnout andengagement scales are negatively related, whereas interrelations ofthe burnout and engagement scales are all positive. Furthermore, theengagement scales are stronger interrelated (mean r = 0.63 in Sample 1and mean r = 0.70 in Sample 2) than the burnout scales (meanr = 0.35 in Sample 1 and mean r = 0.40 in Sample 2). Themean r of the burnout and engagement scales is 0.38 in Sample 1and 0.42 in Sample 2. Of the burnout scales, EX is least stronglyrelated to the engagement scales (particularly AB), whereas EF is moststrongly related to these scales. As expected, DE is fairly strongly


TABL

EI

Mea

ns,s

tand

ard

dev

iatio

ns,c

orr

elat

ions

,an

din

tern

alco

nsis

tenc

ies(

Cron

bach

s

fors

tude

nts/e

mpl

oyee

son

thed

iago

nal)o

fthe

burn

ou

t(E

X,CY

,re

duce

dEF

)and

enga

gem

ent(

VI,D

E,A

B)sc

ales

inth

est

uden

tsam

ple

(N=

314)

and

the

empl

oyee

sam

ple

(N=

619)

Stud

ents

Empl

oyee

sCo

rrela

tions

MSD

MSD

FEX

CYrE

FV

ID

EA

BEX

3.61

1.11

2.24

1.23

227.

520.

66/0

.85

0.59

0.21

0.3

4

0.3

0

0.1

6CY

2.45

1.17

1.87

1.21

48.5

00.

46

0.79

/0.8

40.

41

0.4

7

0.5

5

0.3

9

rEF

1.98

1.00

1.65

0.86

29.2

20.

21

0.38

0.74

/0.7

30

.60

0.5

5

0.44

VI

3.30

1.13

3.82

0.86

55.8

90

.20

0.2

7

0.6

4

0.78

/0.7

90.

69

0.69

DE

4.41

1.20

3.74

1.29

60.7

00

.14

0.5

1

0.6

8

0.60

0.84

/0.8

90.

72

AB

3.37

1.12

3.53

1.00

4.51

0.1

20

.22

0.6

0

0.74

0.56

0.73

/0.7

2No

tes:

EX=

Exha

ustio

n,CY

=Cy

nici

sm,r

EF=

redu

ced

Effic

acy,

VI=

Vigo

r;D

E=

Ded

icat

ion;

AB=

Abs

orpt

ion;

Corre

latio

nsfo

rstu

dent

sbel

owth

edi

agon

al;p

measure engage and burnout

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