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Ameta-analyticexaminationofthecorrelatesofthethreedimensionsofjobburnout.

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Journal of Applied Psychology1996, Vol. S I . No. 2, 123-133

Copyright 1996 by the American Psychological Association, Inc.002I-90IO/96/S3.00

A Meta-Analytic Examination of the Correlates of theThree Dimensions of Job Burnout

Raymond T. LeeUniversity of Manitoba

Blake E. AshforthConcordia University

This meta-analysis examined how demand and resource correlates and behavioral andattitudinal correlates were related to each of the 3 dimensions of job burnout. Both thedemand and resource correlates were more strongly related to emotional exhaustion thanto either depersonalization or personal accomplishment. Consistent with the conserva-tion of resources theory of stress, emotional exhaustion was more strongly related to thedemand correlates than to the resource correlates, suggesting that workers might havebeen sensitive to the possibility of resource loss. The 3 burnout dimensions were differ-entially related to turnover intentions, organizational commitment, and control coping.Implications for research and the amelioration of burnout arc discussed.

Over the past dozen years, the phenomenon of job

burnout has been investigated in a variety of service oc-

cupations and settings. The construct has been linked to

job stress and is thought to represent a unique response

to frequent and intense client-patient interactions

(Cordes&Dougherty, 1993; Maslach, 1982).

According to Maslach (1982), burnout consists of

three dimensions: emotional exhaustion, depersonaliza-

tion (felt distance from others), and diminished personal

accomplishment. Recent efforts have been made toward

understanding how various correlates are associated with

each of the three dimensions (Burke & Richardsen,

1993; Cordes& Dougherty, 1993;Shirom, 1989).

The conservation of resources theory of stress

(Hobfoll, 1989; Hobfoll & Freedy, 1993) provides a

framework for understanding how such correlates are re-

Raymond T. Lee, Department of Business Administration.University of Manitoba, Winnipeg, Manitoba, Canada; BlakeE. Ashforth, Department of Management, Concordia Univer-sity, Montreal. Quebec, Canada.

Portions of this study were presented at the 13th World Con-gress of Sociology: Sociology of Mental Health Working Group,Bielefeld, Germany, July 1994.

This study was funded in part by a 1993-1994 University ofManitoba, Faculty of Management research support grant.

We are indebted to Monica Filz for assistance with the datacollection and Stephen Hladkyj for assistance with the meta-analysis.

Correspondence concerning this article should be addressedto Raymond T. Lee, Department of Business Administration,Faculty of Management, University of Manitoba, Winnipeg,Manitoba, Canada R3T 2N2. Electronic mail may be sent viaBitnet to [email protected].

lated to burnout. The theory suggests that burnout oc-

curs when certain valued resources are lost, are inade-

quate to meet demands, or do not yield the anticipated

returns. The major demands of work include role ambi-

guity, role conflict, stressful events, heavy workload, and

pressure. The major resources include social support

from various sources; job enhancement opportunities,

such as control, participation in decision making, and au-

tonomy; and reinforcement contingencies (Burke & Ri-

chardsen, 1993; Cordes& Dougherty, 1993). The theory

also states that certain behavioral and attitudinal out-

comes arc likely to occur as a result of resource loss and

burnout. The major outcomes include behavioral coping

responses; turnover intentions; and erosion of organiza-

tional commitment, job involvement, and job satisfac-

tion (Burke & Richardsen, 1993; Kahili, 1988).

Using the conservation of resources framework, recent

studies have investigated how certain demand and re-

source predictors are associated with each of the burnout

dimensions (Lee & Ashforth, 1993a; Leiter, 1993;Leiter

& Maslach, 1988). Leiter and Maslach suggested that

work demands and resources are potential sources of

stress in the stress-strain-coping-self-evaluation process

(Cummings & Cooper, 1979; Lazarus & Folkman,

1984). Emotional exhaustion as a form of strain is di-

rectly affected by these correlates, whereas depersonaliza-

tion as a form of defensive coping and personal accom-

plishment as a form of self-evaluation are indirectly

affected through emotional exhaustion.

Leiter and Maslach's (1988) model has received par-

tial support. Lee and Ashforth (1993a, 1993b) found

several of the correlates to be associated with emotional

exhaustion and depersonalization, but the correlates

123

124 LEE AND ASHFORTH

were only weakly associated with personal accomplish-

ment. Moreover, Golembiewski's (1989) model and Lee

and Ashforth's (1993b) data have raised some doubts re-

garding the sequential ordering among the burnout di-

mensions as posited by Leiter and Maslach.

In light of these findings, Leiter {1993) proposed a re-

vised model in which the demand and resource correlates

are posited to be differentially associated with the three

dimensions. Specifically, the demands are posited to be

more strongly related to emotional exhaustion, whereas

the resources are posited to be more strongly related to

either depersonalization or personal accomplishment. As

Hobfoll and Freedy (1993) stated, demands trigger strain

in the form of physical and emotional exhaustion,

whereas resources help to overcome the need for defen-

sive coping and enhance one's self-efficacy. Leiter (1991 b,

1993) also posited that outcomes reflecting withdrawal

tendencies (e.g., escape coping, low job involvement, and

desire to quit) are more related to either emotional ex-

haustion or depersonalization, whereas outcomes re-

flecting positive self-efficacy (e.g., control coping and fa-

vorable work attitudes) are more related to personal

accomplishment.

Leiter's (1993) revised model also posits how the burn-

out dimensions themselves may be interrelated (cf. Go-

lembiewski, 1989; Leiter, 1989). Specifically, it is now

believed that both emotional exhaustion and personal ac-

complishment develop in parallel with (rather than fol-

lowing from) each other. Hence, both of these dimensions

are posited to be "reactions to different aspects of the

work environment that pose difficulties for human ser-

vice workers" (Leiter, 1993, p. 246).

Although the recent models are based in part on Hob-

foil's (1989) conservation of resources theory, the empir-

ical evidence has been piecemeal and limited in scope.

Thus, our meta-analysis assessed the associations be-

tween various correlates and each of the burnout dimen-

sions. Only studies using the Maslach Burnout Inventory

(MBI; Maslach & Jackson, 1981, 1986) were included

because the scale is the most widely used operationaliza-

tion of burnout. As a multidimensional measure, the

MBI makes it possible to determine whether the symp-

toms of burnout are empirically distinct from each other

and whether they are differentially associated with other

variables. Therefore, our study provides a summary of

the bivariate associations reported in the literature and

has implications for the diagnosis and the amelioration

of burnout.

Method

Literature Search

We undertook both computer and manual searches for pub-lished articles that used the MBI. Using the key phrase "Mas-

lach Burnout Inventory," the computer search scanned the ab-stract databases of clinical psychology, education, management,nursing, psychology, social work, and sociology from 1982 to1994. The manual search scanned the reference lists of Burkeand Richardsen (1993), Cordes and Dougherty (1993), Kahili(1988), and Shirom (1989) for published sources not found inthe aforementioned abstracts.

The search yielded 77 sources, of which 58 provided suffi-cient information to conduct the meta-analysis. Of the remain-ing 19 sources, 11 examined a correlate unique to that study,and 8 did not provide information on reliability estimates, in-tercorrelations among the variables, or both. A letter requestingthe missing information was sent to one of the authors of eachof these 8 articles. This request yielded 3 additional sources, fora total of 61.1 The remaining 5 and the 11 with unique corre-lates were excluded from the analysis.

The 61 studies used in the meta-analysis covered 33 corre-lates based on 56 independent samples. The sample sizes rangedfrom 34 to 906 (M = 198.07, SD = 172.08). Approximately80% of the studies sampled human service providers (e.g.,teachers, nurses, counselors, police officers, and social workers),whereas most of the remaining studies sampled supervisors andmanagers of such service providers. Because the symptoms ofburnout appear to be fundamentally similar across hierarchicallevels (Lee & Ashforth, 1993a, 1993b; Maslach & Jackson,1986), we did not differentiate the results on these bases.

Each study was coded on whether the MBI used the frequencyresponse format, the intensity response format, or both (seeMaslach & Jackson, 1981); the reliability estimates of all mea-sures; and the correlations among the burnout dimensions andcorrelates.

Mela-Analytic Procedure

We followed the procedure given by Hunter and Schmidt(1990). This procedure determines the extent to which corre-lation differences across studies can be attributed to certain sta-tistical artifacts. It is only after such artifacts are taken into ac-count that the corrected correlations between variables, as wellas the variance in correlations across studies, can be estimated.

First, we calculated the uncorrected weighted mean correla-tion (/) by using the zero-order correlations. Second, becausereliability estimates might have varied widely across studies, wecorrected each within-study zero-order correlation for mea-surement unreliability (Hunter & Schmidt, 1990). Where reli-ability estimates were not reported, we substituted the weightedmean reliability (see Table 1) into the correction formula.Then, we calculated the individually corrected weighted meancorrelation (rc). Because so few studies reported scale ranges,means, and standard deviations, it was not possible to correctfor range restrictions.

Third, we computed the variance of the individually cor-rected weighted mean correlation after removing the variances

1 The correlations were provided upon request for the articlesby Constable and Russell (1986); Ross, Altmaier, and Russell(1989); and Russell, Altmaier, and Van Velzen (1987).

META-ANALYSIS OF JOB BURNOUT 125

Table 1Weighted Mean Reliability Estimates oj All Variables

Correlate

Job stressorsRole ambiguityRole clarityRole conflictRole stressStressful eventsWorkloadWork pressurePhysical comfort

SupportSocial supportSupervisor supportCoworker supportWork friendsCommunity bondFamily resourcesPeer cohesionTeam cohesion

Job enhancement opportunitiesAutonomyInnovationParticipationSkill utilizationTask orientation"

k

66

1034

554

6121324252

114664

N

1,518929

2,612703903

1,238681433

1,0103,3773,340

153433244657156

2,177433

1,7631.489

433

xx

.78

.85

.79

.76

.87

.76

.79

.80

.69

.85

.86

.80

.80

.70

.74

.86

.79

.80

.83

.80

.75

Correlate

Reinforcement contingenciesUnmet expectationsContingent rewardsNoncontingent rewardsContingent punishmentsNoncontingent punishments

Frequency response formatEmotional exhaustionDepersonalizationPersonal accomplishment

Intensity response formatEmotional exhaustionDepersonalizationPersonal accomplishment

Behavioral and attitudinal outcomesControl copingPreventive copingTurnover intentionsOrganizational commitmentJob involvementJob satisfactionAttitudes toward workplace climate

k

22222

474747

999

32768

162

N

248496496496496

9,6689,6689,668

1,6371,6371,637

425470

1,2311,8661,0773,788

227

Rxx

.59

.96

.69

.84

.80

.86

.76

.77

.82

.78

.79

.83

.64.78.87.72.79.80

Note, k = number of samples providing reliability information; N = total number of individuals in the k samples; 7?Xx = weighted mean reliability

estimate of each variable across the k samples." Extent to which the work environment emphasizes efficiency and good planning.

due to sampling error and measurement unreliability. We alsocomputed the percentage of variance due to uncorrected arti-facts. Fourth, we computed both the credibility and confidenceintervals (Hunter & Schmidt, 1990). The credibility intervalwas based on the standard deviation of the distribution of effectsizes after correcting for statistical artifacts and provided infor-mation on whether moderators were likely to be present.2 Theconfidence interval was based on the standard error of the meaneffect size and provided information on the accuracy of the in-dividually corrected weighted mean correlation estimate. Last,we conducted a test for the homogeneity of effect sizes acrosssamples by using Hunter and Schmidt's (1990) Q statistic. Be-cause of disagreements over the appropriate ratio of artifacts tosample variance to infer that the effect sizes are homogeneous(cf. Hunter & Schmidt, 1990), we used both the credibility in-terval and the Q statistic to detect moderators (Whitener,1990). Where the Q statistic could not be calculated, we usedonly the credibility interval.

To determine if the effect sizes are homogeneous, Whitener(1990, p. 317) recommended that the credibility interval bechecked to see if it is "sufficiently large" or includes zero. How-ever, it is unclear what qualifies as a sufficiently large interval.Thus, the effect sizes were considered homogeneous if the cred-ibility interval did not include zero and the Q statistic was notsignificant. We computed the confidence interval for homoge-neous effect sizes by using the formula provided by Whitener(1990, p. 316). The effect sizes were considered heterogeneousif the credibility interval did include zero or if the Q statistic was

significant (either case indicated that a moderator was probablyoperating). We computed the confidence interval for heteroge-neous effect sizes by using the formula provided by Whitener(1990, p. 317).

Results

Table 1 reports the number of studies, the total sample

size, and the weighted mean reliability estimate for each

variable. Tables 2-5 report the uncorrected weighted

mean correlation, the individually corrected weighted

mean correlation, the variance, the lower and upper

range of the uncorrected weighted mean correlation

based on the 95% confidence interval, and the results of

the Q test for each correlate.

Mela-Correlations Among the Burnout Dimensions

Of the 61 studies included in the meta-analysis, 33

used the frequency response format, 11 used the intensity

2 A credibility interval that includes zero indicates the prob-ability of a disordinal moderator, where the relationship be-tween two variables is positive in certain samples and negativein others. However, a moderator is still possible even when theinterval does not include zero but is large enough to suggest thatthe effect sizes are heterogeneous (Whitener, 1990).


response format, and the remaining 17 used both, asMaslach and Jackson (1981) did originally. Of the 17studies that used both formats, 9 provided intradimen-

sional correlations between response formats. Across all

three dimensions, the individually corrected weighted

mean correlations were greater than .90, suggesting that

the two formats are largely redundant and that only oneis necessary (Maslach & Jackson, 1986; Schaufeli, Enz-

mann, & Girault, 1993).Table 2 shows the meta-correlations among the three

burnout dimensions. For the frequency response format,

emotional exhaustion was strongly related to depersonal-ization (rc = .64), whereas both dimensions were moder-

ately negatively related to personal accomplishment (rcs= .33 for emotional exhaustion and .36 fordepersonalization). The individually corrected weighted

mean correlations among the three dimensions for the

intensity response format were similar in magnitudes.Given the high correlations between the two response for-

mats and that only a few studies used the intensity re-sponse format, all subsequent meta-analyses examinedthe three dimensions using only the frequency response

format.

Homogeneity of Effect Sizes

Before examining the individually corrected weighted

mean correlations between the correlates and the burn-out dimensions, we determined the number of homoge-

neous effect sizes. For emotional exhaustion, the effect

sizes were homogeneous for 13 of 32 correlates; for de-

personalization, the effect sizes were homogeneous for 16

of 33 correlates; and for personal accomplishment, theeffect sizes were horn ogeneous for 10 of 3 2 correlates. Be-

cause of the small number of studies per variable, it was

not possible to conduct any moderator analysis on corre-

lates with heterogeneous effect sizes. Their individuallycorrected weighted mean correlations should thus be in-

terpreted with caution, especially where both the credi-

bility and confidence intervals include zero (Whitener,

1990).

Mela-Correlations Between the Correlates and the

Burnout Dimensions

For the demand correlates, Table 3 shows that the indi-

vidually corrected weighted mean correlations betweenemotional exhaustion and role conflict, role stress, stress-

ful events, workload, and work pressure were all greater

than or equal to .50. Table 4 shows that the individuallycorrected weighted mean correlations between deperson-alization and role ambiguity, role conflict, role stress,

stressful events, and workload were all greater than orequal to .34. Table 5 shows that the individually correctedweighted mean correlations between personal accom-

plishment and the demand correlates were generally

weak, with the highest being .22.For the resource correlates, Table 3 shows that the in-

dividually corrected weighted mean correlations between

emotional exhaustion and social support, supervisor sup-port, community bond, innovation, participation, unmet

expectations, and noncontingent punishment were all

greater than or equal to | .301. Table 4 shows that the in-dividually corrected weighted mean correlations between

Table 2Mela-Correlations Among the Job Burnout Dimensions

95% CI

Burnout dimension-burnout dimension k N r rc VAR Lower Upper% due toartifacts Q statistic

Frequency response format

Emotional exhaustion-depersonalizationEmotional exhaustion-personal accomplishmentDepersonalization-personal accomplishment

474747

9,6688,9778,977

.52-.27-.29

.64-.33-.36

.029

.024

.053

.54-.46-.52

.75-.21-.26

88.7655.6988.00

36.4010.4449.01*

Intensity response format

Emotional exhaustion-depersonalizationEmotional exhaustion-personal accomplishmentDepersonalization-personal accomplishment

999

1,6371,6371.637

.53-.18-.27

.65-.22-.34

.050

.082

.085

.53-.37-.54

.77-.08-.15

86.6786.6987.48

69.53**67.70**71.92**

Note. The boldface r^s indicate that the 95% credibility interval did not include zero. In cases where the corrected variances were less than zero, theQ statistic could not be calculated. When credibility intervals did not include zero and the Q statistic was not significant, the confidence interval (CI)for homogeneous effect sizes was constructed. Otherwise, the CI for heterogeneous effect sizes was constructed, k = number of studies; N = combinedsample size; r = uncorrccted weighted mean correlation; rc = weighted mean correlation after correcting for within-study measurement unreliability;VAR = variance of after correcting for sampling error and measurement unreliability; % due to artifacts = percentage of variance due to artifactsother than sampling error and measurement unreliability.V :.()]. **/>


Table 3Meta-Correlations With Emotional Exhaustion (Frequency)

95% CI

Correlate

Job stressors (demands)Role ambiguityRole clarityRole conflictRole stressStressful eventsWorkloadWork pressurePhysical comfort

Support (resources)Social supportSupervisor supportCoworker supportWork friendsCommunity bondFamily resourcesPeer cohesionTeam cohesion

Job enhancement opportunities (resources)InnovationAutonomyParticipationSkill utilizationTask orientation'

Reinforcement contingencies (resources)Unmet expectationsContingent rewardsNoncontingent rewardsContingent punishmentsNoncontingent punishments

Behavioral and attitudinal outcomesControl copingTurnover intentionsOrganizational commitmentJob involvementJob satisfactionAttitudes toward workplace climate

k

66

1134

654

613142

425

2

4

11

674

22

222

377

8172

N

1,518929

2,824703903

1,450681433

1,0103,5893,552

153433244

657156

4332,1771,7631,701

433

248496496496496

4251,2312,0781,0774,000

227

r

.16

-.30.42

.50

.45

.52

.41

-.09

-.26-.31-.18

,05-.38-.16-.08-.20

-.24-.13-.26-.20-.20

.38-.24

.12

.09

.27

-.26.37

-.38-.03-.26-.11

rc

.21-.35

.53

.62

.52

.65

.50-.11

-32-.37-.22

.05-.48-.17-.10-.22

-.30-.15

.31-.28-.26

.53-.26

.15

.10

.32

-.30.44

-.43-.04-.31

-.13

VAR

.215

.012

.032

.002

.039

.009

.006


Table 4

Meta-Correlations With Depersonalization (Frequency)

95% Cl

Correlate

Job stressors (demands)Role ambiguityRole clarityRole conflictRole stressStressful eventsWorkloadWork pressurePhysical comfort

Support (resources)Social supportSupervisor supportCoworker supportWork friendsCommunity bondFamily resourcesPeer cohesionTeam cohesion

Job enhancement opportunities (resources)InnovationAutonomyParticipationSkill utilizationTask orientation"


Behavioral and attitudinal outcomesControl copingPreventive copingTurnover intentionsOrganizational commitmentJob involvementJob satisfactionAttitudes toward workplace climate

k

66

1124

554

7121324

25

2

4I I

5

64

222

22

324

76

122

A"

1,518929

2,824286903

1,033681433

1,1763,1723,135

153433244657156

4332,1771,3461,663

433

496496496496496

425470564

2.078749

2,102227

/

.25-.28

.27

.41

.39

.24

.18

.04

-.16-.19-.17-.07-.36-.15-.14-.28

-.22-.10-.14-.29- .23

.13-.10

.18

.08

.20

-.24-.25

.24-.33-.09-.33-.12

re

.34-.27

.37

.54

.50

.34

.22

.06

-.21-.24-.22-.08-.46-.21-.20-.34

-.28-.13-.17-.39-.29

.19-.11

.25

.10

.25

-.28-.37

.31-.42-.11-.44-.15

VAR

.030

.004

.056


Table 5Meta-Correlations With Personal Accomplishment (Frequency)

95% CI

Correlate

Job stressors (demands)Role ambiguityRole clarity

Role conflictRole stressStressful eventsWorkloadWork pressurePhysical comfort

Support (resources)Social supportSupervisor supportCoworker support

Work friendsCommunity bondFamily resourcesPeer cohesionTeam cohesion

Job enhancement opportunities (resources)InnovationAutonomyParticipationSkill utilizationTask orientation8


Behavioral and attitudinal outcomesControl copingTurnover intentionsOrganizational commitmentJob involvementJob satisfaction

Attitudes toward workplace climate

k

66

1034754

7

1315242

52

411664

}

2y

22

32

76

1 ]

2

N

1,131929

2,271703903

1,616681433

1,1763,5893,614

153433244657

156

4332,1771,763

1,663433

496496496496496

425286

2,078749

2,241227

r

.09-.03

-.15.00.18

-.07-.07

-.06

.16

.11

.10

.37-.21-.09-.17

.09

-.21.06.23.13

-.26

-.13.13

-.13.02

-.13

.42-.13-.02-.10

.22

.23

rc

.11-.03-.21

.00

.22-.09-.09-.07

.20

.14

.13

.49-.26

-.12-.22

.12

-.26.07.30.24

-.33

.19

.14-.17

.02-.16

.52-.16-.02-.11

.29

.28

VAR

.374

.066

.105

.040

.160

.068

.007


affected by the stressors. For many service providers, thekey decision is the amount of one or more resources theyneed to invest to meet the demands and to protect them-selves from further resource depletion. Strain occurs whenthe workers feel they no longer have sufficient emotional

resources to handle the interpersonal stressors (cf. Hob-foil, 1989; Maslach, 1982). Instead, many adopt the de-

fensive strategy of withdrawal (rather than engagement)

through depersonalization (Lee & Ashforth, 1993a).

Thus, it is not surprising to find that depersonalization wasalso strongly associated with role stress (rc = .54) and

stressful events (rc = .50).A surprising finding was the weak associations (i.e., rcs

< .30) between personal accomplishment and most ofthe resource correlates. The two exceptions were work

friends (rc = .49) and participation (rc = .30). To theextent that work acquaintances provide individuals witha sense of competence through support, self-efficacy and

self-appraisal may be heightened (Jayaratne & Chess,

1986). Similarly, to the extent that participation leads to

greater felt mastery and control (i.e., empowerment) over

the work environment, self-efficacy and self-appraisal

may also be enhanced.Although gains in resources are viewed by most work-

ers as less salient than the prevention of loss, gains are not

inconsequential (Hobfoll & Freedy, 1993). Resourcesmay directly compensate for certain losses, but they mayalso indirectly help workers cope with work demands. Forexample, with weak social support, interpersonal stres-

sors will likely lead to emotional strain, but with strong

support, their relationship will likely be attenuated

(Jayaratne & Chess, 1986; Russell, Altmaier, & Van Vel-zen, 1987). This proposition is consistent with interac-

tionist accounts of organizational behavior (see Mitchell& James, 1989).

Consistent with Leiter's (1993) model, our findings re-

veal that the three dimensions were differentially associ-

ated with several of the behavioral and atliludinal corre-lates. Emotional exhaustion and depersonalization were

strongly associated with turnover intentions and organi-zational commitment but were weakly associated with

control coping. As a caveat, it is unclear whether the weak

associations reflect the underuse of such a coping behav-ior or its lack of effectiveness and subsequent abandon-

ment. In any case, the lack of an effective coping response

might have served to reinforce subsequent feelings of

helplessness and futility (Lee & Ashforth, 1993a). In

contrast, personal accomplishment was strongly related

to control coping, suggesting that a problem-focused re-sponse and a positive self-appraisal may be mutually re-

inforcing (Lazarus &Folkman, 1984;cf. Leiter, 1991b).

Our findings suggest that outcomes that stem fromemotional exhaustion and reflect the desire to withdraw

may be offset by outcomes that stem from personal ac-complishment and reflect the desire to seek control.Whichever response (either withdrawing or seeking

control) predominates may thus depend on the relativestrengths of emotional exhaustion and personal accom-

plishment as each develops independently over time (Lee

& Ashforth, 1993a; Leiter, 1993).

Study Limitations

One limitation is that the meta-correlations show only

the strength of the relations among the burnout dimen-

sions and by no means deal with the controversy regard-ing their sequential ordering (Golembiewski, 1989;

Leiter, 1989). The arguments over the correct sequence

are based on circumstantial evidence of how stronglyeach dimension is related to certain antecedent and out-

come variables (Cordes & Dougherty, 1993; e.g., see Lee

& Ashforth, 1993b).A second limitation is that the strong association found

between emotional exhaustion and five of the demand

stressors may be partly attributed to a measurement arti-

fact. Three of Maslach and Jackson's (1981, 1986) emo-tional exhaustion scale items (i.e., "I feel emotionally

drained from my work," "Working with people directly

puts too much stress on me," and "Working with peopleall day is really a strain for me") are direct measures of

individual stress reactions. These items correspondclosely to items that tap perceived stress found in fre-

quently used scales of role overload, role conflict, role

ambiguity, stressful events, and work pressure.

A third limitation is that only certain demands and re-sources were examined here. The fact that emotional ex-

haustion was strongly associated with several of the cor-

relates does not necessarily imply the absence of othercorrelates that may be more strongly associated with the

other two dimensions.

Two sets of correlates not examined here are demo-graphic (e.g., sex, age, and education) and dispositional

attributes (e.g., Type A personality, psychological hardi-ness, and locus of control). Although these attributes

have been linked to burnout (Cordes & Dougherty, 1993;

Mclntyre, 1984;Nowack, 1986), their potential as mod-erators requires further clarification and investigation.

Implications for Future Research

Although the demand and resource correlates of jobburnout have been the focus of much attention, their

links to stress-coping and adjustment require further

study. According to the primacy of loss hypothesis, indi-viduals are more sensitive to demands and thus overcom-pensate in the amount of resources expended to preventfurther loss (Hobfoll & Freedy, 1993). To the extent that

META-ANALYS1S OF JOB BURNOUT 131

burnout develops because of this overcompensation, twoquestions are worth investigating: (a) To what extent can

individuals deal with or even overcome burnout by reap-

praising their demands as potential gains (challenges)

rather than certain losses (obstacles; Lazarus & Folkman,

1984; Tversky & Kahneman, 1981) and (b) if demandscan indeed be reframed as potential gains, how can re-

sources be used to change the way stressors are appraised?For example, with the right kind of supervisory support,

workers may come to perceive ambiguous role expecta-

tions as opportunities to carry out their own initiatives

(potential gains) rather than as restrictions on their ac-tions (certain losses).

A broader question that needs to be addressed is the

extent to which the burnout phenomenon is generaliz-able to occupations other than human services (Shirom,

1989). Perhaps the most distinguishing aspect of burn-

out is not so much its psychological and behavioral symp-

toms but rather the demands and the resources perceivedto be the most salient in service settings (cf. Cordes &

Dougherty, 1993). Service providers may work in situa-

tions with demands and resources that are different from

those experienced by, say, production workers in manu-

facturing settings. If true, this suggests that stress re-

searchers should identify and include demands and re-sources perceived by their study participants to be themost relevant for their work context (Maslach, 1982).

Moreover, a comparison of the perceived importance of acommon core of demands and resources between service

and nonservice workers may reveal how and why stressful

situations are dealt with differently between occupations.

Last, longitudinal designs may show that how workershandle burnout is guided by the type and the frequency

of feedback on the usefulness of their initial coping be-

haviors (Leiter, 1991 b). This longitudinal approach sug-

gests several forms of reciprocal relationships involvingburnout and adjustment responses (cf. Cummings &

Cooper, 1979). Multiple data points over time may thushelp determine the kinds of feedback required to amelio-rate or prevent burnout. Such longitudinal data collec-

tion should lead to a better understanding of how burnout

develops and contribute to the broader research on

stress-coping.

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Received December 20, 1994

Revision received August 3, 1995

Accepted October 27, 1995

examination of the correlates of the three dimensions of job burnout

Documents

resource correlates

thedemand correlates

burnout dimensions

possibility of resource

emotional exhaustion

amelioration of burnout

tojob stress

resources theory of