the reciprocal relationship between work characteristics and employee burnout and engagement: a...

RESEARCH ARTICLE

The Reciprocal Relationship BetweenWork Characteristicsand Employee Burnout and Engagement:A Longitudinal Study of FirefightersR. P. Ângelo & M. J. Chambel*†

Faculdade de Psicologia, University of Lisbon, Lisbon, Portugal

Abstract

The paradigm of this study is positive occupational psychology, with the job demands-resources model as theresearch model and the Conservation of Resources theory as the general stress theory. The research design analysesthe job demands-resources model’s dynamic nature with normal and reversed causation effects between workcharacteristics and psychological well-being among Portuguese firefighters. In addition, we analyse a positive(engagement) dimension and a negative (burnout) dimension in the firefighters’ well-being, because previously,studies have merely focused on the strain or stress of these professionals. The research questionnaire was distributedto a sample of 651 firefighters, and a two-wave full panel design was used. Cross-lagged panel analyses indicated thatthe causal direction of the relationship between organizational demands and burnout is reciprocal. Also, we foundthat the reciprocal model, including cross-lagged reciprocal relationships between organizational demands/supervisorysupport and burnout/engagement, respectively, is what fits the data best. Practical implications to developorganizational change programmes and suggestions for future research regarding the promotion of occupational healthare discussed. Copyright © 2013 John Wiley & Sons, Ltd.

Received 19 November 2012; Revised 16 August 2013; Accepted 26 August 2013

Keywords

engagement; burnout; traumatic stress/disaster relief operations; stress management

*Correspondence

Maria José Chambel, Faculdade de Psicologia, University of Lisbon, Alameda da Universidade, Lisboa 1649–013, Portugal.†E-mail: [email protected]

Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smi.2532

IntroductionIn the field of occupational health psychology, one ofthe most pressing issues concerns the testing of recip-rocal relationships between job characteristics andpsychological well-being (Meier & Spector, 2013). Lon-gitudinal studies are necessary to explore the strengthand direction of the cross-lagged relations (i.e. relationsacross time) between these variables. These analyses areexceptionally valuable not only to enhance our under-standing of the causal relationship between job charac-teristics and employee well-being but also as practicalinterventions to promote well-being at work.

This study uses the job demands-resources (JD-R)model (Bakker & Demerouti, 2007) as a guiding frame-work. Following recent recommendations (Hakanen,Schaufeli & Aholaa, 2008; Schaufeli, Bakker & Rhenen,2009; Xanthopoulou, Bakker, Demerouti & Schaufeli,2009), we conducted a longitudinal test of the JD-Rmodel, to test bidirectional relationship between workand mental health.

Stress Health (2013) © 2013 John Wiley & Sons, Ltd.

This study has two merits. Firstly, it contributes tothe empirical testing of the JD-R model through theexamination of its dynamic nature with reciprocalcausation effects between job demands/resourcesand burnout/engagement, respectively. Secondly, itdevelops knowledge that will contribute to future appliedimplications for firefighters’ occupational health, whichplays a vital role in society. Nonetheless, to our knowledge,this is the first study of firefighters that simultaneouslytakes into account both positive and negative dimensionsof well-being, namely, burnout and engagement. Previousstudies with this population focused only on the analy-sis of adverse conditions and their repercussions interms of strain.

The job-demands resources model

The JD–R model offers a balanced approach to explainnegative (burnout) as well as positive (engagement)aspects of well-being. Burnout is a psychologicalsyndrome that is associated with a prolonged response

Reciprocal Relationship Among Work Characteristics and Employee Well-Being R. P. Ângelo and M. J. Chambel

to stressors in the workplace (Maslach, 2003). Workengagement may be viewed as a motivational constructcharacterized by a positive feeling in relation to work(Schaufeli, Salanova, Gonzalez-Roma, & Bakker, 2002).

The central proposition of the JD–R model is thatjob demands and job resources evoke two psychologi-cal processes (Schaufeli & Bakker, 2004). The first isreferred to as ‘health impairment’, which begins withchronic job demands (e.g. work overload and organiza-tional demands) and may deplete employees’ mentaland physical resources, possibly leading to burnoutand health deterioration. The ‘motivational process’begins with the presence of suitable job resources (e.g.social support and instrumental support) that increaseemployees’ motivation and may lead to work engage-ment and positive work outcomes.

Although most previous studies of the JD-R modelhave used a cross-sectional approach (Schaufeli, Bakker,& Rhenen, 2009), some more recent studies have used alongitudinal design to test the causal direction of somepathways included in the JD-R model (e.g. Hakanen,Schaufeli, & Aholaa, 2008) or to test not only causaleffects but also reversed effects (e.g. Boyd et al., 2011).The Conservation of Resources theory (COR, Hobfoll,1989) assumes a proposition of ‘loss spirals’ that con-siders a reciprocal causal relationship between jobdemands and burnout. This reciprocal relationship isempirically supported by previous studies (Hall, Dollard,Tuckey, Winefield, & Thompson, 2010).

On the other hand, resources and engagement arealso likely to have a bidirectional relationship overtime, which is consistent with the COR theory preposi-tion of ‘gain spirals’ (Hobfoll, 2002) and has empiricalsupport from previous studies (Schaufeli, Bakker, &Rhenen, 2009; Salanova, Schaufeli, Xanthopoulou &Bakker, 2010).

Thus, further developed JD-R model studies with alongitudinal panel design are important in order tounderstand these global longitudinal dynamics onwell-being (e.g. burnout and engagement) and to con-tribute to the application of this model across a rangeof occupations. Therefore, on the basis of the JD-Rmodel processes and COR theory principles, this paperproposes that a reciprocal causation model between jobdemands/resources and burnout/engagement, respec-tively and simultaneously, should fit better than regularor reverse causation models.

The present study

Study participants: rescue missionfirefighters

Research concerning firefighters’ psychological occupa-tional health has been dominated by the negative effectof their work characteristics (Varvel et al., 2007).Firefighters are considered to have a high-strain occu-pation, since physical danger and psychological stressare part of their daily lives. However, according to

Ben, Scotti, Chen and Fortson (2006), the ways thatthese conditions and events affect firefighters have notbeen sufficiently investigated. Despite the little knowl-edge we have about the positive well-being of theseprofessionals, Rich, Lepine and Crawford (2010)verified that firefighters showed high levels of workengagement. However, the process or conditions thatexplain this positive psychological state have not beensufficiently investigated.

Study Demands and Resource Selection

Since the JD-R model considers that each occupationhas its own specific risk factors, we selected rescue mis-sion professionals, since they are the core elements ofthe organization. Traditional demands of theseprofessionals are related to operations scenarios likemedical emergencies, road accidents, hazardous mate-rial spills, forest and urban fires (Varvel et al., 2007).Regarding firefighters’ professional resources, the liter-ature highlights resources at the unit level (Bacharach,Bamberger, & Doveh, 2008). In order to identify thecultural specificities of Portuguese firefighters, inter-views and focus group methodology (Vogt, King &King, 2004) were conducted. The demands identifiedwere of an organizational nature (situations stemmingfrom the organizational aspects of emergencies),whereas resources were represented by supervisorysupport (perceived by each firefighter).

Organizational demands are highlighted in interna-tional literature on rescue-mission firefighters becauseof the psychological and emotional risks experiencedby these professionals as a result of the typical organiza-tional structure of fire departments (Haslam & Mallon,2003). These demands are particularly important inthis work domain since they can be modified as ameans to improve well-being, unlike its mission, whichconsists of intrinsic demands of an acute nature and isassociated with victims and rescue tasks. Empiricalresults also demonstrated that social support fromsupervisors is particularly important for emergencyprofessionals (Bacharach, Bamberger, & Doveh, 2008).Additionally, according to theCOR theory (Xanthopoulou,Bakker, Demerouti, & Schaufeli, 2009), supervisorysupport contributes to fostering such positive workoutcomes as work engagement. Both in resources and inorganizations demands selected exists the workingpossibility to intervene on them and change their levelsthrough training and organizational development. Thispossibility allows the study results to perform a theoreticaland applied contribution.

Study hypotheses

The theoretical model used in the present study isshown in Figure 1. We tested a model that hypothesizedreciprocal causal relationships in health impairment andmotivational processes. Firstly, we formulated the follow-ing hypotheses concerning regular causality, according tothe JD-R Model assumptions:


Figure 1. The final model (standardized path coefficients) *p< 0.05; ** p< 0.01; *** p< 0.001

R. P. Ângelo and M. J. Chambel Reciprocal Relationship Among Work Characteristics and Employee Well-Being

Hypothesis 1: Organizational demands have a positivecross-lagged effect on burnout.

Hypothesis 2: Supervisory support has a positive cross-lagged effect on work engagement.

Secondly, considering that burnout is not only a conse-quence but also a cause of job demands (Bakker, VanEmmerik, & Van Riet, 2008), because stressed employeestend to assess their job more negatively (Zapf, Dormann,& Frese, 1996), and people with high burnout might getfunctions with higher job demands (Demerouti, Bakker& Bulters, 2004), we hypothesized that

Hypothesis 3: Burnout has a positive cross-lagged effecton organizational demands.

Thirdly, in view of the fact that people with positiveemotions (e.g. engagement) share the ability to broadensocial and psychological resources (Fredrickson, 2001)and that when employees experience work engagementthey tend to easily recognize, activate or create future re-sources (Xanthopoulou, Bakker, Demerouti, & Schaufeli,2009), we hypothesized that

Hypothesis 4: Work engagement has a positive cross-lagged effect on supervisory support.

We hypothesized that we would find reciprocalpaths in health impairment (demands to burnout)and in the motivational relationship (resources to


engagement); we also tested potential reciprocalcross-lagged relationships between demands engage-ment and resources burnout. Although these relation-ships are not specified in the JD-R model (Bakker &Demerouti, 2007), they are consistent with the jobdemands-control model (Karasek, 1979) assumptions,which consider that strain situations at work are char-acterized by high demands and low resources, whereasthose that result in higher learning have low demandsand high resources. Moreover, some empirical studiesbased on the JD-R model verified these reciprocalrelationships (Schaufeli & Bakker, 2004).

Method

Design and procedure

In order to test our hypotheses, we conducted apanel design with two waves and used self-reportquestionnaires to measure the study variables. A 1-yearfollow-up was chosen since both burnout and workengagement are defined as rather persistent psycholog-ical states that do not change very much in the shortrun (Schaufeli, Bakker, & Rhenen, 2009). Accordingto De Lange, Taris, Kompier, Houtman and Bongers(2005), the 1-year time lag also represents the bestmodel fit to examine regular, reversed and reciprocalrelationships between work characteristics and mentalhealth. Furthermore, this interval ensures that seasonalinfluence is stable (Zapf, Dormann, & Frese, 1996),


which is particularly important in professions with crit-ical periods associated with the summer months.

Participants

The participants were professional rescue mission fire-fighters in Portugal, and the study sample was collectedusing a protocol between the University of Lisbon’s Or-ganizational Psychology Department and the PortugueseNational Authority of Civil Protection. Each professionalfirefighter received a questionnaire, instructions on itscompletion and return envelopes. In total, 2025professional firefighters from the 18 districts of Portugalwere invited to participate in the study. Participation inthe study was voluntary and confidential. The total of1610 firefighters participated in the study (80% responserate) at Time 1. Out of all the returned questionnaires,1487 (92%) were complete and usable for subsequentanalyses. At Time 2, the firefighters who had respondedat Time 1 received the second questionnaire. In total,651 (44%) were returned and usable for subsequentanalyses, corresponding to those participants who filledout both questionnaires (32% of the initial group).With regard to the demographics, a comparison ofthe sample characteristics with those of the population(in accordance with government agency files) revealedno differences between our sample and the firefighterspopulation concerning age, gender or experience [Mage =34.8 years old, standard deviation (SD)=8.8 years; 90%male; the yearly mean of firefighting experience was13.4 years, SD = 8.1 years]. As recommended byArmstrong and Overton (1977), we tested for non-response bias by comparing whether firefightersfrom the panel group (N= 651) differed from thedropouts (N= 836) with respect to their baselinelevels on the study variables. Results of a Mann–Whitney U-test only revealed significant differencesregarding gender (p< 0.01), since the male percentageat T1 was 98%.

Measures

Organizational demands scale

This scale, constructed by the authors, stems fromthe firefighter focus groups and the different degreesof experience and geographical bases of the partici-pants, thus representing the Portuguese context. Thefocus groups enabled an identification of professionaldemands and resources specific to the Portuguesefirefighters’ context and were organized with thecollaboration of the Portuguese National FirefightersSchool. The scale reflects organizational demands andincluded four items, namely, ‘Older colleagues do notaccept orders from you, even if you are more qualified;The supervisors do not respect and appreciate thespecialized training that a firefighter has; Poorcoordination with health services at the emergencyscene; Your values and ideals conflict with your FireDepartment and colleagues values’. Items were scored

on a five-point scale (1 = rarely to 5 = very often). Inter-nal consistency (Cronbach’s α) was 0.70 (Time 1) and0.67 (Time 2). Although Nunally (1978) suggested 0.70as a threshold level for alpha, Robinson, Shaver andWrightsman (1991) considered that levels above 0.60were appropriate for exploratory work, particularly whenthe scale had been developed for the study.

Social support of supervisors

The social support of supervisors was validatedthrough the focus group and initial interviews. Supervisorysocial support was measured with four items (e.g. ‘Mysupervisor is concerned about the welfare of those underhim’) from the Job Content Questionnaire (Karasek,1985). Participants were asked to indicate the extent towhich they agreed with each statement on a four-pointscale (1= strongly disagree to 4= strongly agree). Internalconsistency (Cronbach’s α) in the present study was 0.83(Time 1) and 0.84 (Time 2).

Burnout

Burnout was measured using the two core dimen-sions, the emotional exhaustion and cynicism subscalesof the Maslach Burnout Inventory - general version(Schaufeli, Leiter, Maslach, & Jackson, 1996). Emo-tional exhaustion was measured with five items (e.g. ‘Iam emotionally exhausted by my work’), and Cynicismwas measured with five items (e.g. ‘I doubt the valueand usefulness of my work’). However, the inspectionof factor loadings in the confirmatory factor analysisresults pointed to the elimination of two items fromthe cynicism scale, because of low factor loadings (i.e.‘When I am working, I do not like to be bothered byother things’ and ‘I have become more cynical aboutwhether my work contributes anything’). The first itemhad previously been referred to in the literature as anitem that tends not to load in the intended factor,creating problems with factor validity and leading tothe suggestion of its elimination from the original scale(Bakker, Van Emmerik, & Van Riet, 2008). Participantswere asked to rate the frequency of each statement ona seven-point scale (0 = never to 6 = every day).Cronbach’s α in the present study was, for emotionalexhaustion, 0.89 (Time 1) and 0.90 (Time 2), andfor cynicism, 0.75 (Time 1) and 0.78 (Time 2).

Engagement

Engagement was measured using the two coredimensions: the vigour and the dedication subscalesof the Utrecht Work Engagement Scale - generalversion (Schaufeli, Salanova, Gonzalez-Roma, & Bakker,2002). Vigour was measured with five items (e.g. ‘At myjob, I feel strong and vigorous’), and dedication wasmeasured with five items (e.g. ‘I am enthusiastic aboutmy job’). Participants were asked to rate the frequencyof each statement on a seven-point scale (0 = never to6 = every day). Cronbach’s α was, for vigour, 0.74



(Time 1) and 0.77 (Time 2), and for dedication, 0.78(Time 1) and 0.82 (Time 2).

Results

Descriptive analysis

Table I presents means, SDs and correlations amongthe study variables. All correlations were in the expecteddirection and significant.

Measurement model

Before testing the structural model that is displayed inFigure 1, we conducted confirmatory factor analysisto test two competing models to examine whether jobdemands (organizational demands) and job resources(supervisory support) are represented by a two-factormodel or one-factor model that assumes that demandsand resources load on one general factor, representingjob characteristics. Additionally, we also tested if burn-out and engagement are represented by a two-factormodel or one-factor model that represents well-being.The job characteristics one-factor model did not fitthe data well [χ2(245) = 1340.24, p< 0.001; standard-ized root mean square residual (SRMR)= 0.12;Tucker–Lewis index (TLI) = 0.79; comparative fit index(CFI) = 0.81; Akaike information criterion (AIC) =1450.24; root mean square error of approximation(RMSEA) = 0.08]. Concerning the well-being one-factor model, it also did not fit the data well[χ2(245) = 10610.63, p< 0.001; SRMR= 0.11; TLI =0.84; CFI = 0.86; AIC = 1171.63; RMSEA= 0.07]. Incontrast, the four-factor model (job demands andresources, burnout and engagement) fitted the datawell [χ2(242) = 720.97, p< 0.001; SRMR= 0.08;TLI = 0.91; CFI = 0.92; AIC = 836.97; RMSEA = 0.06)and significantly better than both the job characteristicssingle-factor model [Δχ2(3) = 619.27, p< 0.001] andwell-being one-factor model [Δχ2(3) = 340.66,p< 0.001]. Hence, it was concluded that the four-factormodel suitably represented the observed data.

Structural model

Firstly, we tested the fit of the theoretical model, i.e.the reciprocal model, to the data. The fit indicesresults indicated that this model fitted the data well[χ2(238)= 705.54, p< 0.001; SRMR=0.08; TLI = 0.91;CFI = 0.92; AIC=829.54; RMSEA=0.06]. RegardingHypothesis 1, Table II displays the fit indices of thecompeting models, as well as the model comparisons.Although all models indicate an acceptable fit, thechi-squared difference tests were favourable to our theo-retical model, better than the stability model [Δχ2(4) =15.43**, p< 0.01], the causality model [Δχ2(2) = 9.21**,p< 0.01] and the reversed model [Δχ2(2) = 5.29 non-significant (ns)]. Thus, the reciprocal model was thestructural model that best fitted the data.

Figure 1 presents the standardized coefficients foreach of the significant paths in the theoretical model.


Our results support Hypothesis 1, since organizationaldemands had a positive cross-lagged effect on burnout(β= 0.10, p< 0.05). On the other hand, supervisorysupport did not add a significant cross-lagged effecton engagement (β= 0.06, ns) and Hypothesis 2 isrejected. Hypothesis 3 is supported given that burnouthas a positive cross-lagged effect on organizationaldemands (β= 0.13, p< 0.01). Hypothesis 4 is rejectedsince engagement did not add a significant cross-laggedeffect on supervisory support (β= 0.07, ns).

Although not expressed in the hypotheses, the analysesalso revealed that the relationships between organizationaldemands–engagement and supervisory support–burnoutdid not add a significant cross-lagged effect.

DiscussionThe main purpose of the present longitudinal study onrescue mission firefighters was twofold: (1) to providelongitudinal evidence for the JD-R model; and (2) tosimultaneously take into account both positive (engage-ment) and negative (burnout) dimensions of well-beingamong firefighters, a population for whom previouslystudies have concentrated on the analysis of strain.

Longitudinal evidence for the JD-R modelhealth impairment process

We found that burnout in firefighters increases as aconsequence of working in the rescue mission context.Apparently, as a result of job demands, they feel morefatigue during the missions and treat their victims ina more impersonal manner when they are experiencingstress that arises from the organizational aspect ofemergency. This effect is supported by a low standardizedregression coefficient. However, small standardizedeffects are normal in longitudinal research (Semmer,Zapf & Greif, 1996), since a large part of the strainvariance measured in Time 2 will be explained by thesame variable measured at the baseline or Time 1 (i.e.both indicators of burnout share 63% of their variancein the present study).

Longitudinal evidence for the JD-R modelmotivational process

Results of the present study confirm the conclusions ofMauno, Kinnunen and Ruokolainen (2007) that longi-tudinal support for the motivational process is stillscant. Indeed, in our data, no empirical support isfound that supervisory support has a positive cross-lagged effect on engagement. One issue to consider isthe relatively high stability of work engagement(Seppälä et al., 2009), since we controlled for theautoregressive effect of each latent variable at T1 onthe same variable at T2. Therefore, it is difficult for apredictor to account for any additional variance withsuch psychosocial concepts as outcome variables(Hakanen, Schaufeli, & Aholaa, 2008). On the otherhand, our focus groups identified social supervisorysupport as an important job resource. Nonetheless,

Table

I.Descriptivestatisticsan

dzero-order

correlations

forallvariables

(N=65

1)

Variables

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(1)T1organizationaldemands

1—

——

——

——

——

——

(2)T1supervisors’socialsupp

ort

�0.40***

1—

——

——

——

——

—

(3)T1bu

rnou

t–exhaustion

0.26***

�0.10*

1—

——

——

——

——

(4)T1bu

rnou

t–cynicism

0.28***

�0.17***

0.48***

1—

——

——

——

—

(5)T1engagement–vigour

�0.21***

0.19***

�0.29***

�0.30***

1—

——

——

——

(6)T1engagement–dedication

�0.19***

0.25***

�0.27***

�0.37***

0.72***

1—

——

——

—

(7)T2organizationaldemands

0.52***

�0.27***

0.18***

0.24***

�0.15***

�0.16***

1—

——

——

(8)T2supervisors’socialsupp

ort

�0.27***

0.43***

�0.11**

�0.13***

0.11**

0.17***

�0.38***

1—

——

—

(9)T2bu

rnou

t–exhaustion

0.21***

�0.03

0.48***

0.25***

�0.22***

�0.18***

0.28***

�0.18***

1—

——

(10)

T2bu

rnou

t–cynicism

0.17***

�0.02

0.26***

0.30***

�0.19***

�0.20***

0.26***

�0.19***

0.52***

1—

—

(11)

T2engagement–vigour

�0.15**

0.10**

�0.20***

v0.16***

0.46***

0.34***

�0.27***

0.23***

�0.33***

� 0.32***

1—

(12)

T2engagement–dedication

�0.17***

0.10*

�0.20***

�0.20***

0.36***

0.33***

�0.30***

0.23***

�0.33***

�0.42***

0.79***

1

Mean

2.22

2.90

2.25

0.90

4.97

5.37

2.17

2.85

2.34

1.05

4.86

5.29

SD0.81

0.54

1.52

1.28

0.87

0.73

0.75

0.55

1.53

1.40

0.93

0.81

SD:standard

deviation.

***p

<0.001.

**p<0.01.*p

<0.05.



Table II. Goodness-of-fit indices of the competing models, N=651

Model χ2 DF SRMR TLI CFI AIC RMSEA Comparison Δχ2

M1. Reciprocal model 705.54 238 0.08 0.91 0.92 829.54 0.06 — —

M2. Stability model 720.97 242 0.08 0.91 0.92 836.97 0.06 M1–M2 15.43**

M3. Causality model 714.75 240 0.08 0.91 0.92 834.75 0.06 M1–M3 9.21**

M4. Reversed model 710.83 240 0.08 0.91 0.92 830.83 0.06 M1–M4 5.29 ns

DF: degree of freedom; SRMR: standardized root mean square residual; TLI: Tucker–Lewis index; CFI: comparative fit index; AIC: Akaike

information criterion; RMSEA: root mean square error of approximation.

**p< 0.01. *p< 0.05, ns (non-significant).


firefighters work in a highly militarized organiza-tional culture in which the supervisors rely more onan attitude of inspection and correction, and lesson being perceived as a social resource for stressmanagement, thus diminishing the positive impacton their subordinates’ well-being. Furthermore, inorganizations with higher levels of teamwork, as isthe case of the firefighters, supervisory support willbe a weaker source of job well-being (Griffin,Patterson & West, 2001).

Reciprocal causation evidence for theJD-R Model

The model including reciprocal relationships receivedthe strongest empirical support. This result suggeststhat, even though the reciprocal path between supervi-sory support and engagement is non-significant, thedynamic nature of the JD-R model is more evidentwhen all potential effects are simultaneously taken intoaccount, both regular and reverse causation models. Ifthe regular causality effects represent the longitudinalevidence for the JD-R model processes, then as far asthe reversed effects are concerned, the possible theoret-ical explanations for the underlying mechanisms arestill limited. However, De Lange, Taris, Kompier,Houtman and Bongers (2005) presented a conceptualframework to analyse the effects of Time 1 mentalhealth on Time 2 work characteristics on the basis oftwo possible mechanisms. According to these authors,positive re-evaluations of work characteristics can beexplained by assuming that workers with betterpsychological well-being colour their perceptions ofthe work characteristics in a rosier light (the rosyperception mechanism), which corresponds to ourHypothesis 4. Moreover, unhealthy (i.e. ‘burned out’)employees can also evaluate their environment morenegatively and thus report poorer work characteristics,perceiving the same job as gloomier across time (thegloomy perception mechanism), which representsHypothesis 3. Hence, the gloomy perception mecha-nism seems to be the most appropriate to explain ourreciprocal findings, since there is a significant reversedeffect of burnout, which is consistent with the alreadymentioned COR theory assumptions.


Reversed causal effect of burnout

Our results also reveal that burnout has a positive cross-lagged effect on organizational demands. This reverse effectof the health impairment process involves two separateanalyses. Firstly, firefighters with high levels of burnoutperceive higher job demands, either because of a negativelybiased perception or as a result of actual changes in thework environment. However, the organizational demandsscale items reflect conditions that are likely to be alteredby organizational change (particularly of a cultural nature)but are not under the firefighters’ control and are unlikelyto involve widespread changes in the various units over aperiod of one year. Thus, these results suggest that thefirefighters’ perception of the same working conditionschanges as a result of their mental health status, whichmatches the conclusions of other studies (Schaufeli,Bakker, & Rhenen, 2009). The second analysis focuseson the long-term reciprocal relations between jobdemands and burnout, which are consistent with the ap-plicability of COR theory to the firefighters’ work domainand strengthen its person–environment fit approach,which states that well-being is determined by both envi-ronmental and individual factors (Hobfoll, 1989, 2002).

Reversed causal effect of engagement

The results of the present study reveal no empirical sup-port that engagement has a positive cross-lagged effecton supervisory support. Apparently, there is no relation-ship between firefighter’s psychological well-being in rela-tion to their professional mission and supervisory supportover the following year. Regarding two possible mecha-nisms that could explain this effect, presented byXanthopoulou, Bakker, Demerouti and Schaufeli (2009),engaged firefighters could start to recognize supervisorysupport that was previously available to them but, becauseof motivational factors, they were not aware of its exis-tence in the organizational environment (at the time). Al-ternatively, they could start to use the supervisory supportwhose existence was previously recognized but with amore proactive attitude in order to overcome the supervi-sor’s passive leadership patterns. The Portuguese fire-fighters’ organizational culture follows the principle thatthe leader only intervenes after a need for correction hasbecome apparent. Therefore, if a subordinate does not


show performance failures, even if he or she is experiencingdifficulties in managing their professional stress, the leaderwill not approach the subordinate, but he is available toprovide support if the contact is initiated by the firefighter.Thus, these results suggest that since the firefighter has nocontrol over the ability of the organization to provide moresupervisory support, the increase of engagement levels doesnot contribute for optimizing this job resource.

Regarding the long-term reciprocal relations betweenjob resources and engagement, these results are in linewith the first principle and second corollary of theCOR theory, which state that resource loss ismore salientthan resource gain, as loss is more potent than gain(Hobfoll, 2002). Therefore, these resultsmirror the conclu-sions of Hobfoll, Johnson, Ennis and Jackson (2003), whichreinforce the notion that positive occupational health psy-chology cannot focus exclusively on the study of positivework characteristics and flourishing psychological statesbut should also incorporate the study of resources loss inorder to develop methods for changing this scenario.

Limitations and future studies

This study has several limitations. Firstly, the data werecollected through self-reported questionnaires, whichincreases the possibility that the relationships amongthe variables are due to common method variance. How-ever, the longitudinal design overcomes some of the prob-lems of common method variance and unmeasured thirdvariables, since previous levels of the variables are some-what controlled. Furthermore, Harman’s single-factor test(Podsakoff, MacKenzie, Lee & Podsakoff, 2003) was used,and the results revealed that common method variancecannot be considered a serious deficiency in this data set.Additionally, in order to have a more rigorous interpreta-tion of causality and reciprocity, the absence of a three-wave panel study constitutes a second limitation, whichwould have allowed us to investigate the COR theory spi-ral effects onwell-being. Still, according to Zapf, Dormannand Frese (1996), a two-wave study enables an examina-tion of both regular and reversed causal relationships, thusovercoming the major shortage of cross-sectional studies.Finally, a third limitation is the fact that JD-R model(Bakker & Demerouti, 2007) considers not only the directeffect of demands on burnout or the direct effect ofresources on engagement but also moderator effects: asresources moderate the effects of demands on burnoutas well as demands moderate the effects of resources onengagement. Future studies, especially with this popula-tion of firefighters, should be conducted to test thesemoderated relationships.

Conclusions and implications

In the present study, we found evidence of both regularand reverse causal relationships between work charac-teristics and mental health. Although burnout andengagement are traditionally seen as an outcome, ourtwo-wave longitudinal study also suggests that theycan be considered as both consequences and causes inthe JD-R model. Moreover, regarding the simultaneousexistence of two psychological processes, namely,health impairment and motivational process, the firsthas empirical support in this study. The non-significantpath between supervisory support and engagementchallenges the universality of benefits from supervisorysupport. Is supervisor support in highly militarizedorganizational culture, in which supervisors emphasizean attitude of inspection and correction, considered asocial resource? It is important to replicate this studywith other security and relief professionals.

At a theoretical level, this study found that the recipro-cal model is the one that better fits the data, whichcontributes to the development of a reference model inoccupational health psychology, such as the JD-R model,enhancing the perspective that workers’ psychologicalwell-being and environment influence each other recip-rocally. Secondly, these results are encouraging insofaras they pose a challenge to positive occupational psy-chology to adopt a comprehensive perspective, in linewith the JD-R model conceptualization, to understandmechanisms that allow both the inversion of negativeeffects and the promotion of positive effects. Thirdly,the reversed causal effect of burnout reinforces theassumption of Hobfoll (1989, 2002) that well-being isdetermined by both environmental and individual fac-tors, in the specific professional context of firefighters.

In terms of practical implications, since our resultsindicate that changes in organizational demands pre-dict future burnout, which in turn triggers a higherperception of job demands, it is crucial to developorganizational change programmes. We also believethat these results should encourage future longitudinalresearch that includes a systematic intervention for thepromotion of supervisory social support and engage-ment (e.g. a leadership stress management workshop)after Time 1 and thus promoting resources gain. Theabsence of a causal effect of supervisory support onengagement highlights the need for a customized inter-vention that focuses on the specific reality of rescuemission firefighters, in particular the organizationalculture regarding stress management and the activerole of the leader in this process.

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