Organizational predictors and health consequencesof changes in burnout: A 12-year cohort study

MICHAEL P. LEITER1*, JARI J. HAKANEN2, KIRSI AHOLA2,SALLA TOPPINEN-TANNER2, AKI KOSKINEN2 AND ARI VÄÄNÄNEN2

1Acadia University, Wolfville, NS, Canada2Finnish Institute of Occupational Health, Helsinki, Finland

Summary We investigated job burnout and job characteristics, including decision authority, skill discretion, predict-ability, and information flow, among Finnish forestry workers (N = 4356) in a longitudinal study. We linkedthese responses individually with data on the participants’ subsequent prescriptions for psychotropic drugsincluding antidepressants. We aim to study the antecedents of changes in burnout levels over four years timeand their health-related consequences in an eight-year follow-up. The results showed that inconsistencyamong the levels of the Maslach Burnout Inventory subscales (e. g., high scores in exhaustion and lowcynicism or vice versa) at baseline identified patterns that were prone to change in burnout four years later.Information flow predicted the direction of this change for the exhaustion and cynicism aspects of burnout,whereas skill discretion and predictability did so for reduced professional efficacy. Change toward burnoutpredicted future risk of psychotropic drug use. It seems that adverse changes in burnout are influenced bypoor organizational resources, and change toward burnout is likely to elevate the risk of poor mental health.Copyright © 2012 John Wiley & Sons, Ltd.

Keywords: burnout; health; longitudinal; change

Introduction

Job burnout, a syndrome of chronic exhaustion, cynicism, and inefficacy, is an ongoing problem in work life thatdistresses employees and weakens the financial performance of organizations. Losing the capacity to be energeticallyinvolved in work, something that normally strengthens self-efficacy, imposes huge costs on personal fulfillment andorganizational productivity. Extensive research has established clear connections between health outcomes and burnout(Halbesleben & Buckley, 2004; Maslach, Schaufeli, & Leiter, 2001; Shirom &Melamed, 2005). Further understandingof these connections would benefit from focusing on the actual process of burning out and using more objectivemeasures of health. The present study addresses these points.A relevant part of the challenge to decrease burnout and its detrimental consequences concerns the chronic nature

of burnout. Indeed, research on job burnout has found the underlying constructs—energy, involvement, andefficacy—to be remarkably stable over time (Hakanen& Schaufeli, 2012; Hakanen, Schaufeli, & Ahola, 2008;Maslachet al., 2001; Schaufeli, Leiter, & Maslach, 2009). Ironically, despite burnout’s considerable stability, models of thesyndrome emphasize the multidimensional process that evolves over time (Leiter, 1993; Maslach et al., 2001), andlongitudinal, regression-based research designs are an established standard for research on burnout. However, in a largesample, the people who are in flux are easily lost against the backdrop of stability. Thus, examining the sample as awhole does not foster understanding of burnout as a dynamic process. A method for identifying people who are aboutto change would be valuable. In order to gain an insight into the process of burnout, it is essential to have an a priorirationale for separatingmore volatile people from stable ones and to identify the dynamics of change. The process tested

*Correspondence to: Michael P. Leiter, Acadia University, Wolfville, NS Canada B4P 2R6. E-mail: michael.leiter@acadiau.ca

Copyright © 2012 John Wiley & Sons, Ltd.Received 17 November 2011

Revised 19 August 2012, Accepted 24 August 2012

Journal of Organizational Behavior, J. Organiz. Behav. 34, 959–973 (2013)Published online 20 September 2012 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/job.1830 R

esearchArticle

in this study used the inconsistency between three dimensions of burnout, that is, exhaustion, cynicism, and reducedprofessional efficacy, as a means of identifying the people with different change profiles according to burnoutdimensions across time.Our objective was to use longitudinal panel data to analyze changes in burnout. First, we consider the extent to

which inconsistency among the three aspects of burnout indicate a propensity toward change. This expectation fol-lows Maslach and Leiter (2008) who demonstrated that people with inconsistent scores on exhaustion and cynicismtended to change toward greater consistency in these two subscales of the Maslach Burnout Inventory (MBI;Maslach, Jackson, & Leiter, 1996). We build on this analysis to consider inconsistency among all three MBIsubscales.Our second research objective was to identify workplace conditions at Time 1 that predict change in burnout

scores beyond the contribution of inconsistency. The third research objective was to identify the extent to whichinconsistency among the MBI subscales helps to predict severe long-term health consequences. This approachemphasizes burnout as a process that is influenced by organizational conditions and that has an impact upon employees’health. The use of independent data on health supplements the predominant use of self-report measures of health in theexisting burnout literature.

Persistence and antecedents of job burnout over time

Previous longitudinal studies have indicated the chronic and stable nature of burnout (e.g., Hakanen & Schaufeli,2012; Toppinen-Tanner, Kalimo, & Mutanen, 2002). The basis for burnout’s considerable perseverance overtime may arise from vicious cycles of interactions between psychological states and the work environment(De Lange, Taris, Kompier, Houtman, & Bongers, 2004). Constant demands that exceed resources aggravateexhaustion, and inadequate rewards or experiences of injustice contribute to cynicism. Energy is the mostimmediate physical and psychological resource available to employees, and chronic exhaustion diminishes thisenergy. Without the resource of personal energy, employees are less capable of managing a given level ofdemand. A sense of professional efficacy follows from an energetic involvement in one’s work. In contrast, apersistent sense of discouragement has the potential to sap one’s energy or to reduce one’s involvement in workactivities. Consistency among the three dimensions of burnout defines a more balanced, self-reinforcing stateeither on the positive end (a sense of efficacy with no indications of exhaustion or cynicism) or on the negativeend (a lack of efficacy accompanied by exhaustion and cynicism). Inconsistency among these elements has aless stable quality.

Identifying change in burnout and its organizational predictors

The overall stability of burnout over time raises distinct challenges for investigating process models of the syndrome(Leiter, 1993). Maslach and Leiter (2008) developed an innovative approach for identifying individuals who werelikely to experience change in burnout or work engagement (no burnout) in the near future. They proposed thatpeople with inconsistent experiences of exhaustion and cynicism were inclined to resolve the contradiction betweenthese qualities toward a consistency. For example, people experiencing involvement, despite feeling exhausted,would over time either experience an increase in cynicism or a decrease in exhaustion (and increase in energy) tobe more consistent in their experience of burnout.Accordingly, they identified two types of inconsistent patterns at Time 1: the Exhaustion Only group (high scores

in exhaustion but low scores in cynicism) and the Cynicism Only group (high scores in cynicism but low scores inexhaustion). These groups were likely to change toward a more consistent pattern of burnout (high or low in bothdimensions) over the course of one year. Moreover, the direction of the resolution was not inherent solely in thelevels of exhaustion and cynicism but also in the dynamics between the individual and the work environment.

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Specifically, those people with inconsistent scores who felt unfairly treated at work tended to move in the directionof burnout (high exhaustion and high cynicism), whereas their colleagues who felt fairly treated moved toward noburnout (Maslach & Leiter, 2008).In the present study, by including the professional efficacy dimension of burnout, we were able to test the

inconsistency hypothesis with all the three dimensions of burnout. In addition, justice may not be the only qual-ity associated with the direction of change; other areas of work life may also play a part. Employees in othersettings may be more swayed by issues pertaining to workload or reward structures, depending on the corevalues or situational forces affecting the organization. For instance, Boersma and Lindblom (2009) found in astudy among a random sample of the Swedish general population that those who at baseline reported only highexhaustion but then changed in a positive direction experienced a favorable change in their workload comparedwith those who developed toward burnout. In addition, burnout rehabilitation studies have shown that by in-creasing job control (Hätinen et al., 2009), social support (van Dierendonck, Schaufeli, & Buunk, 1998), andopportunities for participation (Le Blanc, Hox, Schaufeli, Taris, & Peeters, 2007), burnout levels may decrease.From this perspective, examining burnout in conjunction with a broad assessment of work life factors offers agood strategy for identifying the possible determinants of change. In the present study, we focused on four workcharacteristics (decision authority, skill discretion, predictability, and information flow) that may play a role inthe development of either burnout or well-being. Several studies have found that decision authority (e.g., Taris,Schreurs, & Schaufeli, 1999), skill discretion (e.g., Rafferty, Friend, & Landsbergis, 2001; Taris et al., 1999),predictability (e.g., Borritz et al., 2005), and information flow (Hakanen, Bakker, & Schaufeli, 2006) are relatedto burnout. The personal control that is inherent in all four of these psychosocial factors allows employees toboth moderate their workload according to their resources and to adjust their work to be more consistent withtheir aims and values. Considering a diverse range of work life qualities will help to identify psychosocialfactors in all kinds of work, which may be relevant to people with a propensity to change their psychologicalconnection with work.In the present study, we approached inconsistency among the MBI subscales as a continuous score rather

than the discrete groupings used in Maslach and Leiter (2008). We calculated the within-subject standard de-viation among the standardized scores of the three MBI subscales at Time 1 (MBI WSSD). To consider thecontribution of inconsistency, we examined the extent to which the MBI WSSD contributed to the predictionof future scores on exhaustion, cynicism, and professional efficacy beyond their respective Time 1 scores.Whereas Leiter (1993) proposed a process model in which exhaustion predicts cynicism that in turn predictsprofessional efficacy, we included these relationships within the analyses to accommodate the establishedassociations among the three MBI subscales. Longitudinal research has confirmed this pattern of relationshipsamong the MBI subscales (e. g., Lee & Ashforth, 1993). These considerations lead to the followinghypotheses:

Hypothesis 1a: The inconsistency among the burnout dimensionswill explain additional variance in Time 2 exhaustionbeyond that explained by Time 1 exhaustion.

Hypothesis 1b: The inconsistency among the burnout dimensions will explain additional variance in Time 2 cynicismbeyond that explained by Time 1 cynicism and Time 1 exhaustion.

Hypothesis 1c: The inconsistency among the burnout dimensions will explain additional variance in Time 2professional efficacy beyond that explained by Time 1 professional efficacy and Time 1 cynicism.

After these analyses, we investigated the role of the four job characteristics as potential predictors of the directionof change in burnout. On the basis of the earlier considerations and investigations mentioned above, we formulatedthe following hypotheses:

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Hypothesis 2a: At least one of the work characteristics (information flow, decision authority, skill discretion, andpredictability) at Time 1 will improve the prediction of Time 2 exhaustion beyond the variance explained by Time1 exhaustion and inconsistency among the burnout dimensions.

Hypothesis 2b: At least one of the work characteristics (information flow, decision authority, skill discretion, andpredictability) at Time 1 will improve the prediction of Time 2 cynicism beyond the variance explained by Time 1cynicism, Time 1 exhaustion, and inconsistency among the burnout dimensions.

Hypothesis 2c: At least one of the work characteristics (information flow, decision authority, skill discretion, andpredictability) at Time 1 will improve the prediction of Time 2 professional efficacy beyond the varianceexplained by Time 1 professional efficacy, Time 1 cynicism, and inconsistency among the burnout dimensions.

Burnout and health outcomes

Research has identified a strong, persistent relationship between burnout and health outcomes (Halbesleben &Buckley, 2004; Shirom, 2009; Shirom, Melamed, Toker, Berliner, & Shapira, 2005). In a population-based Finnishsample, burnout was found to relate to both mental disorders and physical illnesses (Ahola et al., 2005; Honkonenet al., 2006). In addition, in a three-wave seven-year follow-up study among Finnish dentists, burnout predicteddepressive symptoms and life dissatisfaction (Hakanen & Schaufeli, 2012). It has also shown to predict new casesof insomnia (Armon, Shirom, Shapira, & Melamed, 2008), type 2 diabetes (Melamed, Shirom, Toker, & Shapira,2006), gastroenteritis, and common colds (Mohren et al., 2003).Burnout may also lead to severe health problems. In a sample of forest industry workers, burnout predicted

hospitalization due to mental disorders and cardiovascular diseases (Toppinen-Tanner, Ahola, Koskinen, &Väänänen, 2009). It also contributed to mortality among the workers under 45 years of age at baseline during a10-year follow-up (Ahola, Koskinen, Kouvonen, Shirom, & Väänänen, 2010). Regarding organizational costs, burn-out has also been found to precede absenteeism (Bakker, Demerouti, de Boer, & Schaufeli, 2003; Borritz, Rugulies,Christensen, Villadsen, & Kristensen, 2006; Toppinen-Tanner, Ojajärvi, Väänänen, Kalimo, & Jäppinen, 2005) andto predict disability pensions (Ahola et al., 2009).Only a few studies have investigated the health problems related to changes in burnout. However, Boersma and

Lindblom (2009) found a favorable change in the levels of anxiety and depression in their sample of workers, whoexperienced high exhaustion at baseline and had moved toward lower burnout at one-year follow-up, compared withthose employees who had moved toward burnout or remained incongruent in their scores. In addition, Hätinen et al.(2009) found in their rehabilitation study that among employees whose burnout symptoms had decreased,depression had also decreased and job satisfaction increased.In this study, we investigated how changes in burnout predict future psychotropic medication. Prescribed

medication reflects a level of chronic distress sufficient to prompt people to seek help from a medical practitioner, whoevaluates whether the problem warrants pharmaceutical intervention. Psychotropic medications, such as antidepressants,are especially relevant to burnout because of the syndrome’s close relationships with depression (Ahola et al., 2005, 2007;Leiter & Durup, 1994). In Finland, prescriptions for medication are recorded in a national register that provides anindependent source of data concerning severe personal distress.We assumed that a change toward burnout would result in deteriorated health. This assumption goes beyond the

finding of an overall cross-sectional association between burnout and antidepressant use (Ahola et al., 2007) byproposing that the relationship between burnout and medication use not solely rests on the overall level of burnoutbut also reflects the actual process of burning out. Inconsistency provides an indicator for greater dynamism amongthe aspects of burnout. We propose that a negative score on an aspect of burnout that is accompanied by indicators ofchange will be more closely associated with poor health outcomes than will negative scores on an aspect of burnoutalone. The research evidence led us to formulate the following hypotheses:

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Hypothesis 3a: Time 1 inconsistency among the burnout dimensions will improve the prediction of subsequentpsychotropic medication use beyond that provided by Time 2 burnout scores.

Hypothesis 3b: Time 1 inconsistency among the burnout dimensions will improve the prediction of subsequentantidepressant medication use beyond that provided by Time 2 burnout scores.

Method

Study context

We conducted the study in an originally Finnish forest industry corporation, which has over 40 000 employees globally.The company had been a stable traditional employer for several decades in Finland, where this prospective study wasconducted. The majority of its industrial plants was dispersed around Finland and produced different kinds of forestindustry products, such as timber, pulp, and fine paper. It was a major employer in many towns and sparselypopulated areas, and had shaped both industrial and local traditions in many ways. Over the last decades, the workwithin the company had become psychologically more abstract and demanding, whereas the physical demands ofthe blue-collar workers had decreased due to the computerization of production. Despite this, however, the blue-collar jobs still entailed more traditional risk factors, such as physically heavy work, hazards, and shift work.During the period from 1996 to 2000, various organizational development projects were launched using the infor-mation gathered in the 1996 questionnaire. These projects aimed to improve working conditions and well-beingamong several employee groups (Kalimo & Toppinen, 1999).

Participants

We collected the data as part of the “Still Working” cohort study (Väänänen et al., 2008), which uses company-widequestionnaire survey data combined, person by person, with administrative health register data over a period of15 years (register baseline 1/1994–9/2000; register follow-up for eight years between 10/2000 and 12/2008). Thestudy participants were the domestic personnel in Finland of the international forestry company mentioned earlier.Most were men (75 percent). Their mean age was 42.4 years (SD = 8.1) at the beginning of the study. The partici-pants represented all occupational groups such as managers, office personnel, foremen, and technical designers,as well as industrial workers, and maintenance staff. According to the health registers, 5.7 percent of the respondentshad already purchased psychotropic medication for six years prior to the health follow-up. The study excluded theseemployees from the analyses predicting the use of psychotropic medication.

Procedure

We gathered the data in three phases. In 1996 (T1), a company-wide survey on work and well-being was conducted(Kalimo & Toppinen, 1999). Questionnaires were sent to the work units, distributed to all employees and managers,and, once completed, mailed directly to the researchers. These data provided information on burnout and job char-acteristics for the present study. Of the eligible domestic employees (n = 15 466) who returned the questionnaire atbaseline (n = 9705, response rate 63 percent), 8371 were identified from the database of the National PopulationRegister Centre. In 2000 (T2), in a similar way, we conducted a second survey among the employees of the samecompany (n = 12 940), including all of the factors included in the T1 survey. Of the original participants,7850 employees participated in the second phase (response rate 61 percent), and we identified 7230 of them. In

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the third phase (T3), we gathered data on psychotropic drug purchases among the participants from the nationalhealth registers for the period 1 October 2000 to 31 December 2008. The final cohort of this study consisted of4618 employees: 3457 men and 1161 women (59 percent manual employees). All of whom had responded to bothsurveys. We used the total cohort in testing Hypothesis 1, whereas in the analyses of register outcomes (psychotropicmedication and mortality), the number of participants was 4356, owing to the exclusion of employees with previouspsychotropic medication use.

Instruments

BurnoutWe measured burnout using the Maslach Burnout Inventory—General Survey (MBI-GS; Maslach et al., 1996), whichhas been proven to be a reliable and valid instrument of burnout (Schutte, Toppinen, Kalimo, & Schaufeli, 2000; Tariset al., 1999). The Finnish version of the scale (Kalimo, Hakanen, & Toppinen-Tanner, 2006; Kalimo & Toppinen,1997) has been widely used in population studies (Ahola et al., 2005; Kalimo & Toppinen, 1997) and representativesamples of various occupational and organizational groups (Kalimo et al., 2006). Exhaustion refers to feelings ofoverstrain, tiredness, or fatigue attributed to overtaxing work. Cynicism refers to an indifferent or unfeeling attitudetoward work. The present study used only four of the five original cynicism items. Professional efficacy consists offeelings of competence, successful achievement, and accomplishment in one’s work, which diminishes when burnoutdevelops. Participants used a 7-point Likert-type scale ranging from 0 (never) to 6 (every day) to rate the extent towhich they experienced exhaustion and cynicism at work (e.g., “I feel burned out from my work”). We excludedone of the cynicism items because of low internal consistency with the subscale, caused by the Finnish translation(Schutte et al., 2000; Toppinen-Tanner et al., 2002).

Job characteristicsWe assessed job characteristics using questions from the Occupational Stress Questionnaire (Elo, Leppänen,Lindström, &Roponen, 1992).Wemeasured decision authority (T1 a = .81, T2 a = .82) by five items (e.g.“Can you planyour work yourself?”) and skill discretion (T1 a = .80, T2 a = .80) by five items (e.g., “To what extent is your workmonotonous or variable?”), and assessed predictability (T1 a = .72, T2 a = .71) at work by five items (e.g., “Can youanticipate the problems and disturbances that arise in your work?”). The measure of predictability specifically assessesthe clarity of work goals, the ability to foresee work problems, work awareness as a whole, and the significance of workdisturbances in work process andwork outcome.Wemeasured these characteristics on a 5-point scale, all of which wereset to point in the same direction, so that the higher the value, the more negative the evaluation (1 = very little and5= very much). The convergent and construct validity of the scales have proved to be good, and these variables haveshown to predict various types of health-related outcomes such as subjective functional capacity and cardiovasculardiseases (Väänänen et al., 2008, 2005). Information flowwas operationalized by five items (T1 a = .66, T2 a =69) relatedto the amount and quality of information to which respondents had access (e.g., “When changes relating to your worktake place, how well are you informed?”). We used a Likert-type scale as the format for answering, ranging from 1(poorly/never) to 5 (very well/always; Väänänen, Pahkin, Kalimo, & Buunk, 2004).

Psychotropic medicationWe collected data on psychotropic drug prescriptions from the National Prescription Register, managed by theSocial Insurance Institution of Finland (Martikainen & Rajaniemi, 2004). The register provides comprehensive dataon prescribed medication on a national level, as the national sickness insurance scheme covers the entire populationand provides reimbursement for virtually all filled prescriptions. The prescription register of the Social InsuranceInstitution is composed of outpatient prescription data based on the World Health Organization’s AnatomicalTherapeutic Chemical (ATC) classification code (WHO, 2004). In Finland, a physician writes all prescriptions. TheSocial Insurance Institution obtains these data from all pharmacies in Finland as part of the national drug reimbursement

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scheme (Martikainen & Rajaniemi, 2004). We extracted the number of prescriptions for psychotropic drugs such asantidepressants (ATC code N06A), antipsychotics (ATC code N05A), and anxiolytics (ATC code N05B) for eachparticipant between 1 October 2000 and 31 December 2008. We excluded employees who had drug prescriptionsrelated to these medicine categories between 1 January 1994 and 30 September 2000, before the follow-up, from thefinal cohort. We used having at least one prescription between 1 October 2000 and 31 December 2008 as an indicatorof psychotropic medication. We extracted antidepressant prescriptions separately in a similar way.

Other demographic informationWe obtained data on age and sex from the National Population Register Centre, whereas we extracted occupationalstatus (white-collar/blue-collar worker) from employers’ records.

Statistical analyses

We calculated within-subject standard deviations (WSSD) among the standardized scores of the three MBI subscales(with efficacy reversed) at Time 1 for each participant. The MBI WSSD described the level of inconsistency amongthe three MBI subscales: the larger the differences among these three standardized scores, the larger their WSSD,providing a direct indicator of variability for each participant (Campbell, 1990; Smith, Kassin, & Ellsworth,1989). As a continuous variable built upon the distribution of scores from each subject, the WSSD brings a distinctbut compatible perspective on the quality of inconsistency that was defined dichotomously by median splits inMaslach and Leiter (2008).We tested the hypotheses through a series of multiple regressions. The tests examined the extent to which burnout

inconsistency and job characteristics improved the prediction of outcome variables.

Results

Descriptive statistics

Table 1 displays the correlations for the three dimensions of burnout and the four job characteristics as well as theMBI WSSD for Time 1, the three dimensions of burnout for Time 2, and medication use. The correlations among theMBI-GS subscales are consistent with those reported by Leiter and Maslach (2004). The four job characteristicswere significantly and negatively related to exhaustion, cynicism, and professional efficacy. The correlations amongthe job characteristics ranged at Time 1 from r= .21 between predictability and decision authority to r = .55 betweenskill discretion and decision authority. The analysis found strong correlations across time ranging from r= .47 forcynicism to r = .54 for exhaustion.Table 2 displays the means, standard deviations, Cronbach’s alphas, and t-test results contrasting Time 1 with

Time 2 scores for each of the variables. Using a Bonferroni correction to produce a 0.05/7 = 0.007 criterion forsignificance, we found that scores on decision authority, exhaustion, and cynicism decreased over the study interval.It is noteworthy that compared with those of Maslach and Leiter (2008), the scores in the present study were morepositive than has been reported in North American samples on the MBI-GS on exhaustion (M=2.32; t(4582) = 40.57,p< .01), cynicism (M=1.82; t(4582) = 23.60, p< .01), and efficacy (M=1.60; t(4582) = 17.95, p< .01) at Time 1.

Predicting change from inconsistency

Three multiple regression analyses tested Hypotheses 1a, 1b, and 1c regarding the extent to which inconsistenciesamong the three MBI subscales at Time 1 predicted change in each of the three MBI subscales over the study

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Table

1.Correlatio

ns.

12

34

56

78

910

1112

1314

15Tim

e2

1Exhaustion

.50

.22

.65

�.08

�.10

�.25

�.22

.13

.00

.54

.35

.14

.10

.10

2Cynicism

.29

.71

�.31

�.18

�.31

�.32

.05

.07

.33

.47

.23

.06

.05

3Efficacy

(reversed)

.75

�.27

�.19

�.35

�.21

.06

.02

.18

.23

.53

.06

.06

4MBIWSSD

�.28

�.21

�.39

�.31

.10

.04

.41

.42

.42

.10

.09

5Skilldiscretio

n.55

.24

.26

�.14

.09

�.05

�.16

�.24

�.06

�.04

6Decisionauthority

.21

.28

�.02

.06

�.09

�.10

�.17

�.04

�.02

7Predictability

.35

�.21

.03

�.17

�.20

�.23

�.04

�.04

8Inform

ationflow

�.07

.08

�.18

�.21

�.17

�.05

�.05

9Sex

(M=1;

F=2)

.01

.04

�.01

.02

.08

.07

10Age

.04

.04

.04

�.01

�.01

Tim

e2

11Exhaustion

.60

.22

.11

.10

12Cynicism

.28

.10

.09

13Efficacy

(reversed)

.06

.05

Subsequentyears

14Psychotropicdrugs

.87

15Antidepressantdrugs

Note:N=4176

listwise;correlations

greaterthan

.025

aresignificant

(p<.05);correlatio

nsgreaterthan

.048

aresignificant

(p<.01).M

BIWSSD,w

ithin-subjectstandard

deviation

amongthestandardized

scores

ofthethreeMaslach

Burnout

Inventorysubscalesat

Tim

e1.

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interval beyond the contribution of Time1 MBI scores (Table 3). To test Hypotheses 2a, 2b, and 2c regarding theadditional predictive power of Time 1 job characteristics, we entered these predictors in a stepwise fashion in thefollowing step of each multiple regression.We entered the Time 1 score for the corresponding measure in the first step of each of the three multiple regressions.

Following Leiter (1993), we also entered Time 1 exhaustion in the first step for cynicism and Time 1 cynicism in thefirst step for professional efficacy. The second step in the multiple regressions entered the MBI WSSD. The third stepof the regression stepped in any of the workplace characteristics that had a significant coefficient in the context of thepreceding predictors.The multiple regressions confirmed Hypotheses 1a, 1b, and 1c in that inconsistency among the MBI subscales at

Time 1 explained an additional amount of variance in each of the three aspects of burnout beyond the variance accountedfor by each aspect’s autocorrelation plus the other aspect of burnout following the burnout model by Leiter (1993).The MBI WSSD accounted for an increment in R2 for exhaustion (F(1, 4409) = 41.10, p< .01), cynicism

Table 3. Stepwise multiple regressions on exhaustion, cynicism, and efficacy.

T2 exhaustion T2 cynicism T2 efficacy (reversed)

Time 1 predictors b ΔR2 b ΔR2 b ΔR2

Step 1 .285 .235 .276T1 exhaustion .53** .16** NAT1 cynicism NA .39** .08**T1 efficacy (reversed) NA NA .50**Step 2 .006 .005 .001T1 exhaustion .46** .11** .13**T1 cynicism .33** .55**T1 efficacy (reversed)MBI WSSD .17** .11** �.09**Step 3 .002 .002 .008T1 exhaustion .46** .11** NAT1 cynicism NA .32** .09**T1 efficacy (rev) NA NA .52**MBI WSSD .10** .10** �.07**Information flow �.04** �.05** �.02Skill discretion .02 �.01 �.09**Decision authority �.02 .00 �.02Predictability �.01 �.02 �.03**

Note: NA, not applicable; MBI WSSD, within-subject standard deviation among the standardized scores of the three Maslach Burnout Inventorysubscales at Time 1.**p< .01.

Table 2. Means, standard deviations, Cronbach’s alpha, and t-test between Time 1 and Time 2.

Variable M T1 SD T1 a Τ1 M T2 SD T2 a Τ2 t df Sig. Lower Upper

Skill discretion 3.50 0.78 0.80 3.49 0.77 0.80 2.09 4597 .04 .00 .03Decision authority 3.50 0.81 0.81 3.45 0.84 0.82 4.95 4580 .01 .03 .06Predictability 4.19 0.53 0.72 4.21 0.52 0.71 �2.00 4576 .05 �.03 .00Information flow 3.39 0.74 0.66 3.39 0.73 0.69 �0.54 4573 .60 �.03 .02Exhaustion 1.46 1.05 0.87 1.17 1.08 0.81 18.53 4514 .01 .25 .31Cynicism 1.42 1.15 0.84 1.14 1.26 0.82 15.37 4357 .01 .24 .30Efficacy (reversed) 1.28 1.19 0.88 1.54 1.27 0.86 14.68 4357 .01 �.30 �.23

SD, standard deviation; df, degrees of freedom.

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(F(1, 4288) = 26.46, p< .01), and efficacy (F(1, 4402) = 8.86, p< 01). Although statistically significant, the effect sizesfor each of these increments were small, accounting for at most 0.6 percent of the variance in the MBI subscales.The multiple regressions confirmed Hypotheses 2a, 2b, and 2c in that a workplace characteristic explained an

additional amount of variance in each of the three aspects of burnout beyond the variance accounted for by eachaspect’s autocorrelation plus the other aspect of burnout from the Leiter (1993) model plus the MBI WSSD. Forexhaustion, information flow accounted for an increment in R2 (F(1, 4408) = 10.73, p= .01). For cynicism, informationflow accounted for an increment in R2 (F(1, 4287) = 13.06, p< .01). For efficacy, skill discretion accounted for anincrement in R2 (F(1, 4240) = 41.87, p< .01), as did role predictability, (F(1, 4240) = 4.94, p= .03). As with the MBIWSSD analysis, the effect sizes for each of these increments were small, accounting for 0.2 percent of the variancein exhaustion or cynicism and 0.8 percent of the variance in efficacy.The combined predictors explained a significant proportion of the variance in exhaustion (R2 = .29;

F(3, 4408) = 609.20, p< .01), cynicism (R2 = .24; F(4, 4287) = 343.35, p< .01), and efficacy (R2 = . 29;F(5, 4240) = 348.23, p< .01). Table 3 displays the stepwise coefficients for the three multiple regressions.A second set of multiple regressions examined the extent to which inconsistency among the MBI subscales at

Time 1 increased the extent to which the three aspects of burnout at Time 2 predicted the use of psychotropicmedication and of antidepressant medication over the subsequent nine years. As indicated in Table 1, Time 2 exhaustionand cynicism were significant correlates of both forms of medication, but Time 2 efficacy was not a significant predictorof either. After we entered Time 2 exhaustion and cynicism into the multiple regression, Time 1 MBIWSSD accountedfor a significant increment in explained variance for psychotropic medication, increasing R2 from .012 to .014(F(1, 4318) = 10.10, p< .01) and antidepressants R2 from .011 to .013 (F(1, 4318) = 8.91, p< .01).The combined predictors explained a significant proportion of the variance in psychotropic medication (R2 = .014;

F(3, 4318) = 21.66, p< .01) and antidepressants (adjusted R2 = .012; F(3, 4318) = 18.32, p< .01). Table 4 displaysthe coefficients for the two multiple regressions.

Discussion

This study aimed to (i) investigate the change in the consistency of burnout dimensions across a four-year follow-upperiod, (ii) identify the job characteristics predicting the change, and (iii) test whether the direction of change in burnoutpredicted mental health outcomes. Our study results are in line with earlier findings of Maslach and Leiter (2008) byshowing that inconsistency among burnout subscales make a distinct contribution to predicting subsequent change inburnout and that psychosocial factors at work at baseline made an additional contribution to predicting direction ofsubsequent change in burnout. Moreover, our analysis used a much larger sample (4196 vs. 446 persons), used allthe three dimensions of burnout, and extended the previous study by identifying the connections between inconsistencyamong burnout aspects and the subsequent ill health outcomes. These findings make valuable contributions of practicalrelevance to the study of job burnout and occupational health.This study confirms the value of viewing burnout as a process. It focuses on incipient change and tracks the

direction of this change. In Maslach and Leiter’s (2008) study, the significant organizational factor was fairness.

Table 4. Multiple regressions on medication use.

Psychotropic medication Antidepressants

Predictors b t Sig. b t Sig.

T2 exhaustion .058 3.03 .01 .047 2.46 .01T2 cynicism .038 1.99 .002 .041 2.12 .03T2 efficacy .009 0.56 .574 .009 0.21 .57T1 MBI WSSD .054 3.18 .01 .051 2.98 .01

MBI WSSD, within-subject standard deviation among the standardized scores of the three Maslach Burnout Inventory subscales at Time 1.

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In addition, increasing job control (Hätinen et al., 2009) or decreasing workload (Boersma & Lindblom, 2009) haveshown to contribute to lower levels of burnout. Our study found information flow, skill discretion, and predictabilityto be of importance. These results are consistent with the assumption that the importance of different job resourcesand job demands is context-specific (Bakker & Demerouti, 2007; Hakanen & Roodt, 2010).The job characteristic of information flow contributed to predicting subsequent levels of exhaustion and cynicism.

The work characteristics of skill discretion and predictability enhanced the prediction of professional efficacy.Employees experiencing cynicism, despite high energy, are more likely to use their energy to become moreinvolved, moving toward a no burnout condition, if they are confident of being supported by their organizations throughenough relevant work-related information. Without such support, they are more likely to become progressively moreexhausted, eventually resulting in a burnout condition. Similarly, skill discretion and predictability may act as resourcesthat help in carrying out tasks in the most meaningful way, for example, by enabling job crafting, that is, by changing theboundaries and conditions of job tasks and relationships or the meaning of one’s job (Wrzesniewski & Dutton, 2001).Job crafting can further lead to engagement in contrast to burnout.

Health outcomes

We also found support for the association between inconsistency among burnout components and severe healthoutcomes over the following eight-year period. Our finding that burnout predicts psychotropic medication suggeststhat the shift toward burnout means prolonged emotional distress, which may lead to depression (Ahola & Hakanen,2007). This finding extended previous research on the relationship between burnout and the use of psychotropicmedications as an indicator of mental ill health (Ahola et al., 2007) replicating it in a longitudinal design.Our study showed that workers were more likely to use psychotropic medication and especially antidepressants if

they had shifted toward burnout. The presence of this effect well after the actual shift is consistent with a view ofburnout as a long-term psychological process with severe health outcomes. The shift in burnout occurred over fouryears (from 1996 to 2000), and the use of psychotropic medication occurred over an eight-year period after this shift.This pattern reflects the chronic persistence of emotional distress in burnout.The method explored in this analysis supports a central theoretical proposition in burnout research regarding the

close connection of exhaustion, cynicism, and professional efficacy. The findings here are consistent with otherlongitudinal research that has found a complex dynamic between these three aspects (Halbesleben & Buckley, 2004).One does not clearly precede the other; instead, they both tend to move toward consistency. Exhausted but involvedpeople may either become energized through their work or become so discouraged that they become disengaged andcynical. The evidence shows that both types of change occur. Qualities of the work environment, such as informationflow and skill discretion, may play a role in determining the direction of that resolution. Overall, the analysis supportsthe proposition by Leiter (1993) that employees’ energy influences their potential involvement and that their degree ofinvolvement also influences the amount of energy that they bring to their work.

Limitations

This study has certain limitations that need to be addressed. We were only able to include four job characteristics aspossible predictors of the direction of change in burnout. It was, for example, not possible to test whether fairness orworkload would have emerged as early predictors of burnout, similar to that of previous studies (Boersma &Lindblom, 2009; Maslach & Leiter, 2008). In addition, we only included one kind of health outcome that indicatedby psychotropic medication use. However, whereas most burnout studies have used self-reported health indicatorswith a cross-sectional design, our study was based on an eight-year follow-up period on psychotropic medicationuse, and we were able to exclude those who had already used psychotropic medication before the follow-up period.Psychotropic medication use captures such mental health problems that have urged the employee to seek help andthat have been evaluated by a physician to benefit from medical treatment.

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Another limitation was that this study was conducted in only one company. An interesting future option is torepeat the analysis simultaneously in several organizations with the same job demands and resources, and to investigatewhether the salient issues would turn out to be the same or organization-specific work characteristics. The study spannedover a decade during which many events occurred in the lives of participants that go far beyond the few constructsmeasured in this study.

Implications for theory and practice

The results have implications for theory. However, the small effect sizes introduce caution in their practical application.The analysis of eachMBI subscale and of medication use showed that the inconsistency variable accounted for less thanone percent of the variance in outcome variables. Although statistically significant, the effect was modest. The largesample permitted a valuable perspective on the subtle relationships that would not be evident in smaller researchsamples or in initiatives designed to improve the quality of work life. The study confirms that the inherent stability inburnout remains the dominant theme across an organizational sample. However, trends identified in this analysisprovide direction for future research and theory development.The predictive power of the alignment of three aspects of burnout strengthens the argument of a strong interde-

pendency between these qualities. The exhaustion subscale concerns the energy that allows employees to maintainand focus attention on their work. Without this kind of energy, employees are inclined to experience withdrawalfrom work, reflected in the experiences of cynicism. In a complementary way, cynical attitudes toward work coulddiscourage employees from investing their energy in the enterprise or to be inspired by their experiences at work.Additionally, a sense of professional efficacy receives support from energetic involvement in one’s work whileproviding a foundation for engagement with work.The analysis emphasized the importance of information flow, skill discretion, and predictability and identified

these areas as potential targets for enhancing the quality of work life. As found by Maslach and Leiter (2008), thepredictors pertained to the resource side of the demand/resource balance for the employees. The results argue forthe importance of empowering employees with appropriate resources to maintain involvement in their work as wellas their health. These results may also suggest that resources at work are easier to influence and more closely relatedto social relationships at work, whereas job demands may reflect the inherent characteristics of one’s work task,thereby making it more difficult to change (Hakanen et al., 2006). Recent research that demonstrated that improve-ments in burnout arising from an intervention to improve collegiality (Leiter, Laschinger, Day, & Gilin-Oore, 2011)remained in effect at a one-year follow-up provides a hopeful note (Leiter, Laschinger, Day, & Gilin-Oore, 2011).These results suggest that the long-term consistency in the aspects of burnout have a constructive quality wheninterventions move them into a positive range.The results for medication use reemphasize the vital role of psychologically healthy workplaces. The associations

between entirely different types of data—individual questionnaire responses and government health records—createsconfidence in the robustness of their relationships despite the small effect sizes. Despite the burnout scales and theinconsistency score accounting for only one percent of the variance in medication use, it remains noteworthy that theanalysis established a connection across distinct sources of information and across years. These results add anotherelement of evidence to previous longitudinal studies that found the link between burnout and future health, and stressthe importance of preventive actions at workplaces.The findings have implications for considering the process of burnout development. The inconsistent pattern

did not inevitably lead to burnout. The unfortunate progression was more prevalent when a key job characteris-tic—information flow, skill discretion, or predictability—was experienced as negative by employees. Organizationshave several options for preventing burnout (e.g., cognitive behavioral or participatory approaches; Hätinen et al.,2009; LeBlanc, Woodrow, Sidhu, & Dubrowski, 2008) and enhancing contrasting states, that is, work engagement(e.g., increasing individual resources, such as self-efficacy; Vuori, Toppinen-Tanner, & Mutanen, 2012). By

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decreasing burnout and increasing engagement, it seems that it is possible to guarantee more productive work yearsand better health.

Acknowledgement

This study was supported by the Academy of Finland (SA 128089).

Author biographies

Michael P. Leiter, PhD, is Canada Research Chair in Occupational Health and Wellbeing at the Department ofPsychology, Acadia University. His current research addresses the social environments of work units, especiallythe design of interventions to alleviate burnout through improving collegiality. For more details, visit: www.workengagement.comJari J. Hakanen, PhD, is a senior researcher in the Finnish Institute of Occupational Health and an adjunct professorin social psychology at the University of Helsinki. His research interests focus on positive occupational healthpsychology, especially on work engagement, burnout, the JD-R model, and work-family enrichment.Kirsi Ahola, PhD, works as a team leader in the Finnish Institute of Occupational Health. She is also an adjunctprofessor in occupational health psychology at the University of Helsinki. Her research topics cover various adverseconsequences of burnout as well as the associations between work and mental health.Salla Toppinen-Tanner, PhD, is a team leader at the Finnish Institute of Occupational Health in a team dealingwith career changes and diversity management. Her research covers burnout, individual health resources andinterventions.Aki Koskinen, MSc, is a senior specialist in Finnish Institute of Occupational Health His expertise is in statisticalresearch methods, data management and in the data processing of the registry based research.Ari Väänänen, PhD, is Leader of Work Life in Transition Team at the Finnish Institute of Occupational Health,Finland. He is Adjunct Professor in the Department of Social Research, University of Tampere, Finland. His mainareas of interest are historical sociology of work life and health-related consequences of psychosocial factors.

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