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European Journal of Work andOrganizational PsychologyPublication details, including instructions for authorsand subscription information:http://www.tandfonline.com/loi/pewo20

“Take a break?!” Off-jobrecovery, job demands, andjob resources as predictors ofhealth, active learning, andcreativityJan de Jonge a , Ellen Spoor a , Sabine Sonnentag b ,Christian Dormann c & Marieke van den Tooren aa Department of Industrial Engineering and InnovationSciences, Eindhoven University of Technology,Eindhoven, The Netherlandsb Department of Psychology, University of Mannheim,Mannheim, Germanyc Department of Work, Organizational and EconomicPsychology, Johannes Gutenberg University, Mainz,GermanyPublished online: 26 Jul 2011.

To cite this article: Jan de Jonge , Ellen Spoor , Sabine Sonnentag , ChristianDormann & Marieke van den Tooren (2012) “Take a break?!” Off-job recovery, jobdemands, and job resources as predictors of health, active learning, and creativity,European Journal of Work and Organizational Psychology, 21:3, 321-348, DOI:10.1080/1359432X.2011.576009

To link to this article: http://dx.doi.org/10.1080/1359432X.2011.576009

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‘‘Take a break?!’’ Off-job recovery, job demands, and

job resources as predictors of health, active learning,

and creativity

Jan de Jonge1, Ellen Spoor

1, Sabine Sonnentag

2,

Christian Dormann3, and Marieke van den Tooren

1

1Department of Industrial Engineering and Innovation Sciences,Eindhoven University of Technology, Eindhoven, The Netherlands2Department of Psychology, University of Mannheim, Mannheim,Germany3Department of Work, Organizational and Economic Psychology,Johannes Gutenberg University, Mainz, Germany

The aim of this study is to investigate the moderating effect of matchingjob resources as well as matching off-job recovery (i.e., detachment fromwork) on the relation between corresponding job demands andpsychological outcomes. Using the Demand-Induced Strain Compensation(DISC) Model as a theoretical framework, we conducted a cross-sectionalsurvey study with 399 employees from three Dutch organizations. Resultsshowed that (1) cognitive demands, resources, and lack of detachment arepredictors of cognitive outcomes (i.e., active learning and creativity), (2)emotional demands and lack of detachment are predictors of emotionaloutcomes (i.e., emotional exhaustion), and (3) physical demands, lack ofdetachment, and lack of resources are predictors of physical outcomes (i.e.,physical health complaints). Specifically, cognitive detachment from workmight have negative effects on learning and creativity, whereas emotionaland physical detachment from work might have positive effects onemployees’ health, and even on creativity. In conclusion, in order to copewith specific job demands, employees need corresponding job resources anddetachment from work to balance health and performance-relatedoutcomes.

Correspondence should be addressed to Jan de Jonge, Department of Industrial Engineering

and Innovation Sciences, Human Performance Management Group, Eindhoven University of

Technology, P.O. Box 513, Eindhoven, 5600 MB, The Netherlands. E-mail: j.d.jonge@tue.nl

EUROPEAN JOURNAL OF WORK AND

ORGANIZATIONAL PSYCHOLOGY

2012, 21 (3), 321–348

� 2012 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

http://www.psypress.com/ejwop http://dx.doi.org/10.1080/1359432X.2011.576009

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Keywords: Burnout; Creativity; Detachment from work; Job demands; Jobresources; Off-job recovery.

Many employees in today’s working situations have to deal with high levelsof job demands, which could have negative effects on their health and jobperformance (e.g., Parent-Thirion, Fernandez-Macıas, Hurley, & Vermey-len, 2005). In order to cope with these job demands, researchers have tried toidentify job characteristics that buffer against the adverse effects of jobdemands. For instance, it has been proposed that so-called job resources areable to moderate the relation between job demands and employee outcomes,such that high job demands result in poor health or low performance, unlessemployees have sufficient job resources (such as job control and workplacesocial support) to cope with their demanding job (e.g., Demerouti, Bakker,de Jonge, Janssen, & Schaufeli, 2001; Karasek & Theorell, 1990). In thisperspective, job resources can be broadly conceptualized as instrumental,psychosocial, assets at work that can be used as strategic options for action(cf. Hobfoll, 1989, 2002). Because job demands can often not be reduced,the idea to increase job resources instead to combat strain is appealing fortodays working life.

More recently, Sonnentag and Zijlstra (2006) noted that the process ofrecovering from job demands is equally important. Researchers haveincreasingly shown that off-job recovery is important to protect employees’health and to optimize job performance (e.g., Fritz & Sonnentag, 2005;Fritz, Yankelevich, Zarubin, & Barger, 2010; Sonnentag & Niessen, 2008;Westman & Eden, 1997). Recovery refers to the process during which anindividual’s functioning returns to its prestressor level and in which strain isreduced (Craig & Cooper, 1992; Meijman & Mulder, 1998). Thus, recoverycan be regarded as a process opposite to the strain process during which thedetrimental effects of stressful situations are at least alleviated or eveneliminated. Recovery occurs when no further demands are put on thoseaspects of an individual’s functioning on which job demands have beenput during the work process (Meijman & Mulder, 1998). If recovery issuccessful, an individual’s health and performance improves. If off-jobrecovery is not successful, health and performance will be affected and theindividual starts the next working day in a suboptimal state.

This study investigates the relation between off-job recovery, jobdemands, and job resources in the prediction of psychological outcomes.Theoretical models such as Hobfoll’s (1989, 1998) Conservation ofResources (COR) Theory and the Effort–Recovery (E-R) Model (Meijman,1989; Meijman & Mulder, 1998) explain the role of off-job recovery in thejob stress process. More specifically, exposure to job demands implies thatsome sort of effort has to be expended to meet those demands. According to

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Hockey (2000) as well as Zijlstra and Sonnentag (2006), effort expenditureduring work draws on an employee’s internal resources, and may lead toresource depletion (see also Hobfoll, 2002). Enduring resource depletion willlead to fatigue and finally to a state of exhaustion. To avoid this situation,people need to refill their energy reservoirs, for instance by means of off-jobrecovery.

DEMAND-INDUCED STRAINCOMPENSATION MODEL

The assocation between job demands, job resources, and off-job recovery inthe prediction of health, active learning, and creativity will be tested usingthe Demand-Induced Strain Compensation (DISC) Model (de Jonge &Dormann, 2003, 2006). The DISC Model initially proposes that employeeoutcomes can be explained by two different work-related antecedents (i.e.,job demands and job resources) and by two distinct processes. First, as faras these antecedents and outcomes are concerned, de Jonge and Dormann(2003, 2006) emphasize the need to recognize the multidimensionality ofthese concepts. In line with Hockey (2000), they propose that job demands,job resources, and job-related outcomes each contain cognitive, emotional,and physical elements—an assumption that has been empirically justified(e.g., de Jonge & Dormann, 2006; van den Tooren & de Jonge, 2008).

Second, the DISC Model predicts that high job demands may haveadverse effects on health and well-being that can best be counteractedthrough the availability and activation of functional, corresponding, kindsof job resources (also known as matching—cf. Daniels & de Jonge, 2010).For example, when emotional problems with clients arise (e.g., insolentpatients), emotionally supportive colleagues as job resources are likely to behelpful. If emotionally supportive colleagues are unavailable, other jobresources can be useful to some extent, for instance control at work tohandle a particular problematic client. Based on functional, self-regulatoryprocesses, de Jonge and Dormann (2006) propose that job demands arefirstly dealt with using easily available matching job resources. If suchmatching job resources are not available or when they are depleted (cf.Hobfoll, 2002), employees will search for other job resources and will evenuse job resources that do not correspond to the kind of job demands. Asa consequence, de Jonge and Dormann state that matching job resourcesare most often powerful in combating particular job demands, followed byless-matching or even nonmatching job resources.

Recently, Daniels and de Jonge (2010) presented an overview of empiricalevidence for the key assumptions in the DISC Model. Studies conducted totest the matching principle of the DISC Model show that results in generalhave been supportive. Specifically, 15 out of 19 DISC studies (including two

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2-wave panel studies and 16 cross-sectional studies) showed evidence insupport of the model.

BEYOND DISC: INTEGRATION OF DETACHMENTFROM WORK

One of the aims of the present study is to integrate off-job recovery as anadditional explanatory factor into the DISC Model. Until now, the DISCModel mainly focused on processes occurring at work. However, it mightnot only be unfavorable features of the work situation (and a mismatchbetween job demands and job resources) that lead to negative healthoutcomes. Also experiences and events happening off the job may be relatedto health. Specifically, research on recovery has shown that recoveryexperiences during nonwork time interact with job demands (Sonnentag,Binnewies, & Mojza, 2010) and job resources (Siltaloppi, Kinnunen, &Feldt, 2009) in the prediction of poor health and well-being. These studies,however, did not yet systematically test the interaction between jobdemands, job resources, and off-job recovery; nor they did not differentiatebetween the cognitive, emotional, and physical aspects of demands,resources, and recovery. Thus, our extended DISC Model also goes beyondearlier research on recovery by describing specific combinations of jobdemands and resources on the one hand, and off-job recovery on the other.

Gaining knowledge about how job demands, job resources, and off-jobrecovery are related to employee outcomes is highly relevant for both theoryand practice. From a theoretical point of view, matching internal resourcesare most important to buffer stress (cf. Daniels & de Jonge, 2010; de Jonge &Dormann, 2006). The DISC Model proposes that external resources (such asjob resources) are utilized when matching internal resources are unavailableor depleted. The present research, while still acknowledging the usefulness ofexternal resources, adds to the literature by investigating recovery as astrategy by which internal resources are rebuilt. In the present study, we willfocus on the recovery concept of detachment from work. This concept can beseen as the most central diversionary strategy as far as job-related recoveryis concerned (cf. Sonnentag & Fritz, 2007; Sonnentag & Geurts, 2009).Etzion, Eden, and Lapidot (1998) defined detachment from work as an‘‘individual’s sense of being away from the work situation’’ (p. 579). It is anexperience of leaving one’s work behind when returning home from work(i.e., ‘‘switching off’’ through off-job recovery). Low detachment from workimplies that the functional bodily systems (e.g., neuroendocrine andcardiovascular systems) remain in a state of prolonged activation (e.g.,Brosschot, Gerin, & Thayer, 2006). To recover from high job demands, it isimportant that employees engage in off-job activities that appeal to othersystems or do not engage at all in effort-related activities (cf. Geurts &

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Sonnentag, 2006). For instance, a healthcare worker whose job requireshigh emotional effort would be better off avoiding engagement in off-jobactivities that put high demands on the same (i.e., emotional) systems.Similarly, a construction worker with a highly demanding physical jobwould be better off avoiding engagement in activities after work that puthigh demands on the same (i.e., physical) systems. In this context,Sonnentag and Niessen (2008) proposed that a full degree of off-jobrecovery is attained when the employee feels that both cognitive andphysical as well as emotional systems called upon during work have returnedto their baseline levels after work. So, we assume that detachment fromwork should encompass cognitive, emotional, and physical absence fromwork, which is in line with the three DISC dimensions. In line withMeijman’s (1989) E-R Model and subsequent theorizing about the role ofoff-job recovery in the job stress process (Geurts & Sonnentag, 2006),we propose that detachment from work has an additional, moderating,effect in the relation between job demands, job resources, and employeeoutcomes. Furthermore, in line with DISC theory, we assume thatdetachment from work which matches particular demands will be mosteffective (e.g., emotional detachment in relation to emotional demands).However, before delineating our hypotheses, we will first discuss thedifferent functions of detachment from work in processes of health, activelearning, and creativity.

First, in unfavorable work situations (i.e., when job demands are highand job resources are low), detaching from work could have a positive effecton an employee’s health. These situations are high strain jobs in Karasek’s(2008) terms, and phases of switching off through off-job recovery seem tobe very important for employees facing these situations. Put differently,being busy with job-related thoughts after work drains energy that willimpair health. Cross-sectional, longitudinal, and daily-survey studiessupport this view (e.g., Siltaloppi et al., 2009; Sonnentag, Binnewies, &Mojza, 2008, 2010; Sonnentag & Fritz, 2007). For instance, in their panelstudy with a 1-year time lag, Sonnentag, Binnewies, and Mojza (2010) founda significant negative association between Time 1 detachment from workand Time 2 exhaustion. Therefore, detachment could indeed support healthin high strain jobs due to the restoration of internal resources (see alsoSonnentag & Geurts, 2009).

Second, though research on detachment and adverse health clearly seemsto indicate negative assocations, research on detachment and learning andcreativity outcomes is still in its infancy. Active learning and creativityusually do not occur without any cognitive demand placed upon theindividual (e.g., Amabile & Mueller, 2008; Karasek, 2008). So, cognitive jobdemands are in principle useful to ignite active learning and creativebehavior, but there are ramifying conditions that must be met. First,

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learning and creativity at work are likely to occur when there is at least aslight surplus of available cognitive job resources (cf. de Jonge & Dormann,2003). If these resources would be minimal, demands are probably be dealtwith using already available cognitive strategies. Only when surpluses areavailable, is there room to think about existing problems and to develop newand innovative ways of how to handle the cognitive job demands. Thequestion now is how this interplay between demands and resources isconditioned by detachment. At a first glance, detaching from work meansleaving cognitive job demands (and job resources) behind, which couldmitigate active learning and creativity. In addition, due to higher boundariesbetween work and nonwork roles caused by high levels of detachment(cf. Ashforth, Kreiner, & Fugate, 2000), employees may need more time toreturn into their ‘‘working mode’’. This implies that employees will not be ascreative as they could have been when they spent some time prior to workthinking about work problems (cf. Fritz et al., 2010). Put differently, notdetaching from work during leisure time seems to be a prerequisite forcontinuous work-related problem-solving attempts. In cases of highcognitive job demands and resources, low detachment from work mightlead to efficient problem solving and thus to increased learning and creativebehavior. So, when individuals are exposed to active working conditions(i.e., high demands and high resources), detachment from work as acognitive recovery strategy hampers active learning and creativity.

To sum up these two different functions of detachment, we propose thatin high strain jobs, high detachment from work represents an importantsource of off-job recovery, that particularly may foster health (i.e.,rebuilding internal resources). In contrast, in active jobs, high cognitivedetachment from work might be detrimental for processes of learning andcreativity to occur, whereas low detachment could be particularly beneficialto learning and creative behavior (i.e., some sort of prolonged activation ofproblem-solving thoughts).

The following three hypotheses address the extent to which the threekinds of work-related antecedents predict health, active learning, andcreativity. Based on the DISC matching assumption and respectivereasoning about off-job recovery, we hypothesize that both job resourcesand detachment from work are moderators in the relation between jobdemands and psychological outcomes. In addition, we expect that matchingjob resources as well as matching detachment from work are most oftenpowerful in combating particular job demands.

Hypothesis 1: Emotional job resources and emotional detachment fromwork moderate the relation between emotional job demands andemotional exhaustion (three-way moderation). In more detail, thisrelation will be weaker for employees with both high emotional resources

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and high emotional detachment, than for employees lacking thoseresources and detachment.

Hypothesis 2: Physical job resources and physical detachment fromwork moderate the relation between physical job demands and physicalcomplaints (three-way moderation). Similarly, this relation will be weakerfor employees with both high physical resources and high physicaldetachment, than for employees lacking those resources and detachment.

Hypothesis 3: Cognitive job demands are positively related to activelearning and creativity, and this relation is moderated (i.e., strengthened)by cognitive job resources, as well as moderated (i.e., weakened) bycognitive detachment from work (three-way moderation). In more detail,the moderating/strengthening effect of cognitive job resources will bestronger for employees with low rather than high cognitive detachment.

METHOD

Procedure and participants

Cross-sectional surveys were distributed among 873 employees from threeservice organizations in The Netherlands; that is, 150 healthcare workersfrom a general hospital, 123 healthcare workers from an organization forresidential elderly care, and 600 workers employed in a recreation resort.Organizations were selected by convenience sampling, but also because thiskind of work poses cognitive, emotional, and physical demands onemployees. In total 399 out of 873 people returned the questionnaire(46% response rate). Response rates per organization were 57%, 59%,and 40%, respectively. The somewhat lower response rate in the thirdorganization might be caused by the relatively high number of temporaryworkers. Employees were well-informed about the survey, and couldparticipate on a voluntary basis.

A breakdown of the demographics showed that 80% of the employeeswere female (percentages per organization: 72%, 97%, and 78%,respectively). The mean age was 36.7 years (SD¼ 12.6), and ranged from16 to 62 years. Mean age for hospital workers was 41.1 years (SD¼ 10.9),for elderly care workers 42.2 years (SD¼ 9.1), and for recreation resortworkers 33.5 years (SD¼ 13.1). Mean organizational tenure per organiza-tion was 13.3 (SD¼ 9.4), 5.9 (SD¼ 6.8), and 6.5 (SD¼ 6.2) years,respectively. Total mean organizational tenure was 7.9 years (SD¼ 7.6).Fifteen per cent of all participants worked on a full-time basis, which meansat least 36 hours per week (percentages per organization: 45%, 3%, and8%, respectively). Finally, 76% of the participants reached a secondary

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educational level (sometimes associated with additional healthcare educa-tion), whereas the remaining part had a bachelors or masters degree. Thesedemographics do not substantially differ from other Dutch studies in thesetypes of organizations (e.g., de Jonge, le Blanc, Peeters, & Noordam, 2008;Gevers, van Erven, de Jonge, Maas, & de Jong, 2010; van Veldhoven &Sluiter, 2009).

Measures

Variables included in the present study are cognitive, emotional, andphysical job demands, job resources, and detachment from work on theone hand, and psychological outcomes on the other. Table 1 shows thepsychometric properties of these measures (i.e., Cronbach’s alphas or itemintercorrelations on diagonal) as well as their means, standard deviations,and zero-order correlations.

Cognitive, emotional, and physical job demands and job resources. Thesewere measured using a well-validated, shortened version of the DISCQuestionnaire (DISQ-S), which was particularly developed for testing thistheoretical model (e.g., van den Tooren & de Jonge, 2008; van de Ven,Vlerick, & de Jonge, 2008). Cognitive job demands primarily impinge onbrain processes involved in information processing, e.g., ‘‘Employee X willneed to display high levels of concentration and precision at work’’.Emotional job demands can be defined as the effort needed to deal withjob inherent emotions and/or organizationally desired emotions duringinterpersonal transactions, e.g., ‘‘Employee X will have to display emotions(e.g., towards clients, colleagues, or supervisors) that are inconsistent withhis/her current feelings’’. Physical job demands refer to static and dynamicphysical exertion at work, e.g., ‘‘Employee X will have to lift or move heavypersons or objects (more than 10 kg)’’. Cognitive job resources refer to theopportunity to determine a variety of task aspects and to use problemsolving skills, e.g., ‘‘Employee X would have the opportunity to take a breakwhen tasks require a lot of concentration’’. Emotional job resources refer toemotional support from colleagues or supervisors, e.g., ‘‘Other people (e.g.,clients, colleagues, or supervisors) would be a listening ear for Employee Xwhen he/she has faced a threatening situation’’. Finally, physical jobresources refer to instrumental support from colleagues and supervisors, orergonomic aids at work, e.g., ‘‘Employee X would receive help from others(e.g., clients, colleagues, or supervisors) in lifting or moving heavy personsor objects’’. All but one scale of the DISQ-S consist of three items that canbe scored on a 5-point frequency scale, ranging from 1 (‘‘never or veryrarely’’) to 5 (‘‘very often or always’’). Cronbach’s alphas in this study varyfrom .55 to .87 (see Table 1).

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TA

BL

E1

De

scri

pti

ve

sta

tist

ics

an

dP

ea

rso

nco

rre

lati

on

so

fth

em

ea

sure

s

Measure

MSD

12

34

56

78

910

11

12

13

14

15

16

17

18

19

1.Gender

0.80

0.40

2.Age

36.7012.63

.19**

3.Education

4.16

1.517

.18**

.02

4.Employment

status

0.15

0.367

.34**

.06

.39**

5.Recreation

resorta

0.18

0.39

.23**

.21**7

.13*

7.17**

6.General

hospitala

0.22

0.417

.14*

.18**

.60**

.46**7

.25**

7.Cognitive

dem

ands

3.76

0.74

.06

.22**

.24**

.23**7

.08

.29**

.71

8.Emotional

dem

ands

2.67

0.797

.04

.10

.28**

.14**7

.13*

.25**

.53**

.74

9.Physical

dem

ands

3.20

0.96

.09

.04

7.06

7.09

7.12*

.10

.10

.12*

.77

10.Cognitive

resources

3.05

0.787

.04

7.03

.19**

.20**

.21**

.23**

.16**

.19*

7.22**

.55

11.Emotional

resources

3.95

0.86

.18**

.07

7.03

.03

.05

7.01

.05

7.04

.08

.14**

.87

12.Physical

resources

3.26

0.767

.03

7.03

7.09

.05

.26**7

.08

7.03

7.13*

7.12*

.28**

.38**

.63

13.Cognitive

detachment

3.53

0.89

.07

.17**

.05

7.03

.12**

.11*

.04

.00

.04

7.05

7.02

7.03

.76b

14.Emotional

detachment

3.69

0.887

.04

.08

.09

.02

.05

.17**7

.01

.12*

7.01

.07

.06

7.03

.51**

.71b

15.Physical

detachment

3.71

0.80

.04

.01

7.01

7.06

.06

7.05

7.04

7.16**7

.05

7.06

.10

.07

.32**

.39**

.78b

16.Active

learning

2.34

0.677

.04

7.13*

.11

.24**

.02

.11

.20**

.10

7.10

.24**

.22**

.22**7

.19**7

.13*

7.01

.87

17.Creativity

2.94

0.657

.12*

.09

.12*

.17**

.08

7.04

.26**

.23**7

.08

.25**

.10

.09

7.06

7.02

.00

.30**.90

(co

nti

nu

ed

ov

erl

ea

f)

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TA

BL

E1

(Co

nti

nu

ed

)

Measure

MSD

12

34

56

78

910

11

12

13

14

15

16

17

18

19

18.Emotional

exhaustion

2.27

0.827

.04

7.06

.05

7.05

7.09

7.03

.14**

.27**

.13*

7.08

7.13*

7.13*

7.12*

7.25**7

.33**7

.14*

.04.84

19.Physical

complaints

1.70

0.66

.16**

.06

7.07

7.10

7.09

7.04

.06

.04

.24**7

.07

.12*

7.14*

7.08

7.03

7.13*

7.04

.02.31**.73

Cronbach’salphasare

onthediagonal).N¼399.*p5

.05(two-tailed),**p5

.01(two-tailed).

aReference

group:organizationforresidentialelderly

care.bPearsonintercorrelations.

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To test the construct validity of the DISQ-S scales in the present study,we estimated a confirmatory factor analytical (CFA) model using LISREL8.54 (cf. Joreskog & Sorbom, 1996). A six-factor model was estimatedpositing three factors representing cognitive, emotional, and physicaldemands, and three factors representing cognitive, emotional, and physicalresources. Model tests were based upon the covariance matrix and usedmaximum likelihood estimation. Model fit was assessed by a chi-square testwith a nonsignificant test indicating a good fit to the empirical data.However, because nonsignificant chi-square test values are rarely obtainedin this kind of analysis, we also used other fit indices such as the root meansquared error of approximation (RMSEA), the nonnormed fit index(NNFI), and the comparative fit index (CFI) as recommended by Hair,Black, Babin, and Anderson (2010). Though the chi-square was significantindeed, w2(120)¼ 383.65, p5 .001, the remaining fit indices revealed that asix-factor model provided a good fit to the data (RMSEA¼ .07,NNFI¼ .90, CFI¼ .91). All factor loadings were significant and rangedfrom .46 to .88 (completely standardized). Factor correlations ranged from7.22 to .53.

Detachment from work. This was measured using a new developed scaleby the present authors, called DISQ-R, consisting of cognitive, emotional,and physical detachment after work has been done. All dimensions consistof two items each, which can be scored on a 5-point frequency scale, rangingfrom 1 (‘‘never’’) to 5 (‘‘always’’). Item correlations for all three dimensionswere r¼ .76, r¼ .71, and r¼ .78, respectively (all ps5 .001). Items of eachdimension are: ‘‘After work, I mentally distance myself from work’’ and‘‘After work, I put all thoughts of work aside’’ (cognitive); ‘‘After work,I emotionally distance myself from work’’ and ‘‘After work, I keep allemotions from work aside’’ (emotional); ‘‘After work, I physically distancemyself from work’’ and ‘‘After work, I shake off the physical exertion fromwork’’ (physical). To test the construct validity of the DISQ-R, again a CFAwas conducted. Though the chi-square was significant, w2(6)¼ 40.24,p5 .001, the remaining fit indices revealed that a three-factor modelprovided a good fit to the data (RMSEA¼ .09, NNFI¼ .91, CFI¼ .96).Factor loadings were all significant and ranged from .55 to .78 (completelystandardized). Factor correlations ranged from .32 to .51.

Furthermore, to test whether or not our proposed moderators (i.e., jobresources and detachment from work) are conceptually independent, weconducted two additional CFAs. In the first CFA model, we tested a six-factor structure proposing three factors representing cognitive, emotional,and physical resources, as well as three factors representing cognitive,emotional, and physical detachment. The second CFA model assumed threegeneral ‘‘job resource’’ factors on which all resource and detachment items

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were loading on a respective cognitive, emotional, and physical dimension.Then, the two models were compared by means of a chi-square differencetest (Dw2; Bentler & Bonett, 1980), in which a significant deterioration in fitresulted in the rejection of the hypothesis of conceptually dependentconstructs. The corresponding chi-square difference test was significant,Dw2(12)¼ 736.31, p5 .001, indicating that the hypothesis of conceptuallydependent constructs should be rejected. Looking at the first and valid CFAmodel, w2(75)¼ 183.56, p5 .001, fit indices revealed that a six-factor modelof three resource factors and three detachment factors provided a good fitto the data (RMSEA¼ .06, NNFI¼ .93, CFI¼ .95). This result is in linewith the study of van Veldhoven and Sluiter (2009), who also founddiscriminative validity between job resources and recovery.

Emotional exhaustion. Emotional exhaustion was measured by thewell-validated Dutch version (Schaufeli & van Dierendonck, 2000) of theMaslach Burnout Inventory (Maslach & Jackson, 1986). The scalecontained five items with a 7-point response scale ranging from 0(‘‘never’’) to 6 (‘‘always’’, ‘‘daily’’), with a Cronbach’s alpha of .84. Anexample item is: ‘‘I feel emotionally drained from my work’’.

Physical health complaints. Physical health complaints refer to neck,shoulder, and back problems in the last 6 months and were measured withthree items derived from a scale developed by Hildebrandt and Douwes(1991). The possible responses were 1 (‘‘no’’), 2 (‘‘sometimes’’), and 3(‘‘yes’’). Cronbach’s alpha is .73.

Active learning. Active learning refers to the degree employees areenabled and stimulated to acquire new knowledge and skills, and to solveproblems at their job. This scale (cf. Taris, Kompier, de Lange, Schaufeli, &Schreurs, 2003) consists of four items that can be scored on a 4-pointfrequency scale, ranging from 1 (‘‘(almost) never’’) to 4 (‘‘(nearly) always’’).Cronbach’s alpha is .87. For example, ‘‘At work, I learn new things’’.

Employee creativity. Employee creativity can be defined as thegeneration of novel and useful ideas by employees. This work-relatedconstruct was assessed by a 7-item scale originally developed by George andZhou (2001), and translated/backtranslated in a well-validated Dutchversion (e.g., see de Jonge et al., 2008). The scale could be scored on a5-point rating scale ranging from 1 (‘‘never’’) to 5 (‘‘always’’), with aCronbach’s alpha of .90. Example items are: ‘‘Comes up with new andpractical ideas to improve performance’’ and ‘‘Exhibits creativity on the jobwhen given opportunity to’’.

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Demographic characteristics. Finally, demographic characteristics suchas gender (dummy coded: 0¼male and 1¼ female), age (continuousvariable), education (from 1¼ low degree to 6¼ high degree), andemployment status (dummy coded: 0¼ part time and 1¼ full time) wereincluded as control variables as their relation with this kind of variables iswell-established (e.g., de Jonge et al., 2008; Sonnentag & Zijlstra, 2006).Further, we controlled for the three different types of organizations usingtwo dummy variables (the reference group was the organization forresidential elderly care).

Analytical strategy

Relations between demands, resources, and detachment on the one hand,and employee psychological outcomes on the other, were tested in a series ofhierarchical regression analyses. No significant violations of linear regres-sion assumptions were detected. Variables involved in interactions werestandardized in advance to avoid multicollinearity to a large extent (Aiken& West, 1991). In the first step we entered the demographic characteristicsand the dummies for type of organization. Next, the main terms ofdemands, resources, and detachment were included. In the third step, themoderating effects were entered using multiplicative interaction terms(Demands6Resources, Demands6Detachment, Resources6Detach-ment) of demands, resources, and detachment (cf. Aiken & West, 1991).In the fourth and final step, the three-way interaction of demands, resources,and detachment was entered (Demands6Resources6Detachment). Allregression models were stepwise compared to test whether the higher ordermodels contributed significantly in the prediction of the dependentvariables, using an incremental F-test procedure (Finc; Jaccard, Turrisi, &Wan, 1990). It should be noted that all interactions were of cognitive,emotional, or physical kind according to the main assumption of DISCtheory (cf. van de Ven et al., 2008), which implies that we had nine two-wayinteractions and three three-way interactions for each dependent variable.

RESULTS

Emotional exhaustion and physical health complaints

Results of the hierarchical regression analyses with emotional exhaustionand physical complaints as health outcomes are depicted in Table 2. As canbe seen, the work-related antecedents added substantially to the predictionof both types of adverse health indicators when gender, age, education,employment status, and type of organization were controlled for (R2s were.23 and .14, respectively). As regards emotional exhaustion, the table

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indicates that the model with main effects only fit the data best (Model 2),F(15, 325)¼ 6.57, p5 .001. Specifically, higher emotional demands wererelated to stronger feelings of exhaustion. In addition, employees who

TABLE 2Hierarchical regression models of adverse health outcomes with job demands, job

resources, detachment from work, and their matching interactions

Outcomes

Emotional

exhaustion

Physical

complaints

Model 1: Control variables (DR2) .02 .05

Gender 7.05a .11

Age 7.07 .07

Education .07 7.02

Employment status 7.09 7.04

Recreation resortb 7.01 7.09

General hospitalb 7.07 7.07

Model 2: Demands and resources (DR2) .21 .09

Cognitive job demands .08 .05

Cognitive job resources 7.08 .02

Cognitive detachment .04 7.04

Emotional job demands .19** 7.03

Emotional job resources 7.07 .13*

Emotional detachment 7.14* .03

Physical job demands .08 .21***

Physical job resources 7.04 7.15*

Physical detachment 7.24** 7.13*

Model 3: Two-way interactions (DR2)

Cognitive demands6Cognitive resources

Cognitive demands6Cognitive detachment

Cognitive resources6Cognitive detachment

Emotional demands6Emotional resources

Emotional demands6Emotional detachment

Emotional resources6Emotional detachment

Physical demands6Physical resources

Physical demands6Physical detachment

Physical resources6Physical detachment

Model 4: Three-way interactions (DR2)

Cognitive demands6Resources6detachment

Emotional demands6Resources6Detachment

Physical demands6Resources6Detachment

Best-fitting model R2¼ .23

F(15, 325)¼ 6.57

p5 .001 (Model 2)

Adjusted R2¼ .20

R2¼ .14

F(15, 325)¼ 3.52

p5 .001 (Model 2)

Adjusted R2¼ .10

N¼ 399. *p5 .05 (two-tailed), **p5 .01 (two-tailed), ***p5 .001 (two-tailed). aStandar-

dized coefficients are shown. bReference group: organization for residential elderly care.

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experienced low levels of both emotional and physical detachment reportedhigher levels of exhaustion. With regard to physical complaints, Table 2shows also that the best-fitting regression model was the main effects onlymodel (Model 2), F(15, 325)¼ 3.52, p5 .001. In particular, employeesreporting high physical demands, low physical resources, as well as lowlevels of physical detachment reported higher levels of physical complaints.In addition, low emotional job resources were related to more physicalcomplaints.

Active learning

Results of the hierarchical regression analysis with active learning as acognitive outcome are depicted in Table 3. As can be seen, the work-relatedantecedents added substantially to the prediction of active learning whengender, age, education, and type of organization were controlled for(R2¼ .25). In this case, the regression model with three-way interactions(Model 4) was the best-fitting model according to the incremental F-testprocedure, Finc(3, 310)¼ 2.60, p5 .05. More specifically, we found asignificant matching three-way interaction in which both cognitive detach-ment and cognitive resources moderated the relation between cognitivedemands and active learning. This interaction effect was graphicallyrepresented according to the method described by Aiken and West (1991).Values of the predictor variables were chosen one standard deviation belowand above the mean. Four simple regression lines were then generated byentering these values in the equation: two lines in case of low detachment(Figure 1a) and two lines in case of high detachment (Figure 1b). Dawsonand Richter (2006) noted that interaction plots do not allow inferences asregards the significance of an individual slope. Therefore, a precise test ofslope significance of the respective simple regression lines was carried out(cf. Aiken & West, 1991).

As hypothesized, Figure 1a shows that at low cognitive detachment, highcognitive demands were related to more active learning when cognitiveresources were high (þ1SD; simple slope test), t¼ 2.38, p5 .05). Cognitivedemands were not significantly associated with active learning whencognitive resources were low (71SD; simple slope test), t¼ 0.96,p¼ ns. Figure 1b shows that at high cognitive detachment from work,cognitive demands were not significantly related to active learning whencognitive resources were high (þ1SD; simple slope test), t¼70.72, p¼ ns.Cognitive demands were positively related to active learning when cognitiveresources were low (71SD; simple slope test), t¼ 2.14, p5 .05.

In the case of significant three-way interactions, two-way interactionsandmain effectsmay be interpreted in terms of the average effect of a predictoracross values of a moderator. This average effect usually will be a meaningful

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piece of information as well (cf. Jaccard et al., 1990). As far as these lowerorder effects are concerned, findings showed that both cognitive demandsand emotional resources were positively associated with active learning,while cognitive detachment was negatively associated with active learning.

TABLE 3Hierarchical regression models of active learning and creativity with job demands, job

resources, detachment from work, and their matching interactions

Outcomes

Active learning Creativity

Model 1: Control variables (DR2) .09 .07

Gender 7.04a 7.13*

Age 7.15* .13*

Education 7.02 .09

Employment status .16** .10

Recreation resortb .05 .02

General hospitalb .10 7.22**

Model 2: Demands and resources (DR2) .12 .12

Cognitive job demands .14* .19**

Cognitive job resources .11 .19**

Cognitive detachment 7.13* 7.09

Emotional job demands .02 .12

Emotional job resources .12* .11

Emotional detachment 7.09 .02

Physical job demands 7.06 7.03

Physical job resources .12 .00

Physical detachment .07 .07

Model 3: Two-way interactions (DR2) .02 .06

Cognitive demands6Cognitive resources 7.07 .00

Cognitive demands6Cognitive detachment 7.03 .09

Cognitive resources6Cognitive detachment 7.04 7.15**

Emotional demands6Emotional resources .03 .06

Emotional demands6Emotional detachment 7.07 7.09

Emotional resources6Emotional detachment .05 .12*

Physical demands6Physical resources .04 7.01

Physical demands6Physical detachment 7.07 7.08

Physical resources6Physical detachment 7.06 .07

Model 4: Three-way interactions (DR2) .02

Cognitive demands6Resources6Detachment 7.13*

Emotional demands6Resources6Detachment 7.05

Physical demands6Resources6Detachment .05

Best-fitting model R2¼ .25

F(27, 313)¼ 3.89

p5 .001 (Model 4)

Adjusted R2¼ .19

R2¼ .25

F(24, 313)¼ 4.30

p5 .001 (Model 3)

Adjusted R2¼ .19

N¼ 399. *p5 .05 (two-tailed), **p5 .01 (two-tailed). aStandardized coefficients are shown.bReference group: organization for residential elderly care.

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Employee creativity

Table 3 also shows the results of hierarchical regression analysis with regardto our second cognitive outcome; i.e., employee creativity. Again, the work-related antecedents added substantially to the prediction of employeecreativity controlling for demographics and type of organization (R2¼ .25).The regression model with two-way interactions was the best-fitting modelfor this outcome measure (i.e., Model 3), Finc(9, 313)¼ 2.66, p5 .01. Table 3shows that two two-way interaction effects were significant: one forcognitive resources and cognitive detachment, and one for emotionalresources and emotional detachment. As regards the cognitive interactioneffect, Figure 2 shows that at low cognitive detachment from work (71SD),an increase in cognitive resources was related to more employee creativity

Figures 1a–1b. Three-way interaction between cognitive job demands, cognitive job resources,

and cognitive detachment for active learning.

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(simple slope test), t¼ 4.67, p5 .01. Contrarily, cognitive resources were notsignificantly associated with employee creativity when cognitive detachmentwas high (þ1SD; simple slope test), t¼ 0.67, p¼ ns. Figure 3 depicts theemotional interaction effect, and indicates that high emotional resourceswere related to more employee creativity in case of high emotionaldetachment from work (þ1SD; simple slope test), t¼ 4.43, p5 .01. In caseof low emotional detachment (71SD), emotional resources were notassociated with employee creativity (simple slope test), t¼70.01, p¼ ns.As far as main effects are concerned, results indicated that both cognitivedemands and cognitive resources were positively associated with creativity.

DISCUSSION

This study examined the relation between off-job recovery (i.e., detachmentfrom work), job demands, and job resources in the prediction of health,active learning, and creativity. We used the Demand-Induced StrainCompensation (DISC) Model (de Jonge & Dormann, 2003) as a heuristicframework. To our knowledge, this is the first study that tested specificcombinations of job demands and resources on the one hand, and off-jobrecovery on the other in the prediction of employee outcomes. Our studyextends previous job stress and recovery research (e.g., Zijlstra & Sonnentag,2006) by investigating the issue of optimal resourcing and optimal recovery.In other words, are different kinds of job resources and off-job recovery ableto predict corresponding types of psychological outcomes? Based on theDISC matching principle and further reasoning about off-job recovery, weexpected that in high strain jobs, high detachment from work represents animportant source of off-job recovery, that particularly may foster health.In contrast, in active jobs, high cognitive detachment from work might bedetrimental for processes of learning and creativity to occur, whereas low

Figure 2. Two-way interaction between cognitive job resources and cognitive detachment for

employee creativity.

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cognitive detachment could be particularly beneficial to learning andcreative behaviour.

In terms of the types of interactions found, the current study detected oneout of four (or 25%) hypothesized matching three-way interactions—theinteraction between cognitive demands, cognitive resources, and cognitivedetachment on active learning. So, we found some supportive evidence forHypothesis 3. However, we did not find any supportive evidence forHypotheses 1 and 2: Neither emotional job resources/detachment norphysical resources/detachment moderated the relation between theircorresponding dimensions of job demands and adverse health outcomes.Nevertheless, the overall pattern of our findings suggests that matching jobresources and matching detachment from work are indeed relevant foremployees’ outcomes. More specifically, results showed in general that (1)cognitive demands, resources, and lack of detachment are predictors ofcognitive outcomes (i.e., active learning and creativity), (2) emotionaldemands and lack of detachment are predictors of emotional outcomes (i.e.,emotional exhaustion), and (3) physical demands, lack of detachment, andlack of resources are predictors of physical outcomes (i.e., physical healthcomplaints). Next to these within-domain associations, a few cross-domaineffects of emotional resources and emotional detachment in the predictionof cognitive and physical outcomes were detected. The total amount ofvariance explained (ranging from R2¼ .14 to R2¼ .25) was satisfying, givenmethodological considerations as well as the multicausal aetiology of job-related psychological outcomes (cf. Semmer, Zapf, & Greif, 1996).

Predictors of emotional exhaustion and physicalhealth complaints

Emotional job demands, emotional detachment, and physical detachmentfrom work were important predictors for burnout’s key component

Figure 3. Two-way interaction between emotional job resources and emotional detachment for

employee creativity.

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‘‘emotional exhaustion’’. This finding adds to the literature on burnout.More recent research on burnout has shown that emotional job demandsmay lead to emotional exhaustion (cf. de Jonge et al., 2008; Zapf & Holz,2006). Although research on emotional job demands has been proliferat-ing throughout the last decade (cf. de Jonge et al., 2008; Zapf & Holz,2006), the question remains in what way off-job recovery plays asignificant role. Based upon our ‘‘main-effects’’ model findings (Model 2in Table 2), burnout (in terms of emotional exhaustion) seems to be aresponse to emotionally demanding tasks, which will be further amplifiedin case both emotional and physical detachment from work are absent aswell (i.e., depletion of energy). This finding also adds to recent recoveryresearch (e.g., Fritz et al., 2010; Sonnentag, Binnewies, & Mojza, 2010),and suggests that both emotional and physical detachment from work arepowerful off-job recovery experiences (i.e., rebuilding internal resources)in case of professional burnout. This is in line with the matchingprinciple. Finally, with regard to the emotion regulation literature (e.g.,Brotheridge & Grandey, 2002), emotional detachment resembles thecoping strategy of ‘‘surface acting’’, but might also incorporate aspects of‘‘deep acting’’.

Analyses on physical health complaints revealed that physical jobdemands, physical and emotional job resources, and physical detachmentfrom work were important predictors. Although only the main-effects modelwas significant (i.e., Model 2 in Table 2), these findings pointed to thehypothesized direction and were also in line with the matching principle:high physical demands, lack of physical job resources, as well as lack ofphysical detachment from work were all associated with more physicalhealth complaints. So, next to the positive role of physical job resources, ourstudy shows that physical detachment from work is equally important in theprevention of physical health complaints.

A final note should be made on the role of emotional job resources. Ourfindings indicate that this variable is important for physical healthcomplaints. The question is, however, why emotional job resources (whetheror not in combination with emotional job demands) are not important foremotional exhaustion. Empirical results of de Jonge et al. (2008) showedthat emotional job resources were effective only in case of more specificmeasures of emotional job demands, and not in case of more generalmeasures of emotional job demands (as is the case here). Evidence suggeststhat being engaged in several demanding tasks simultaneously may decreasethe chance of success at each of them if an employee is using the same,limited, job resource (Vohs, Baumeister, & Ciarocco, 2005). Given this idea,it could be that employees effectively use (limited) emotional job resources incase of specific emotional job demands rather than in case of more generalemotionally demanding tasks.

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Predictors of active learning and employee creativity

As hypothesized, cognitive job demands, cognitive job resources, andcognitive detachment from work were indeed important for the cognitiveoutcomes; that is, active learning and employee creativity. In more detail, athree-way interaction of these variables in the prediction of active learningwas found in such a way that the proposed moderating/strengthening effectof cognitive job resources on the relation of cognitive job demands andlearning was only present in case of low cognitive detachment from work.An identical effect of cognitive detachment was found in case of employeecreativity: an increase in cognitive job resources was only related to moreemployee creativity in case of low cognitive detachment from work. Theseresults point to some sort of paradoxical situation: cognitive detachmentfrom work seems to have negative effects on these cognitive outcomes.Ashforth and colleagues’ (2000) theorizing with regard to boundariesbetween work and nonwork domains can be helpful in explainingassociations between detachment from work and active learning andcreativity. High levels of segmentation (i.e., high levels of detachment) canhinder performance-related behavior as employees may need longer to getback into ‘‘working mode’’. Indeed, an empirical study by Fritz andassociates (2010) showed lower levels of job performance at very high levelsof detachment from work.

Furthermore, it could be that a lack of cognitive detachment from workis more inclined to positive work reflection (cf. Binnewies, Sonnentag, &Mojza, 2009). Positive work reflection involves a positive reappraisal ofwork experiences and includes thinking about successfully accomplishedtasks and pleasurable events at work. A longitudinal study by Fritz andSonnentag (2005) showed that thinking about one’s job in a positive way(which should be more likely if one has an active job) during the weekendwas positively associated with pursuit of learning after the weekend. Thisis also in line with studies on ruminative thinking (e.g., Cropley, Dijk, &Stanley, 2006; Cropley & Millward, 2009). The ‘‘pondering on a problem’’aspect of rumination may also have a positive impact on people. In otherwords, thinking about one’s work during off-job time fosters being creative(i.e., the development of new ideas and plans, or active problem solving),and also a person’s willingness to actively engage in learning when backat the workplace. A final explanation stems from a recent study by Baas,de Dreu, and Nijstad (2008). They examined whether, when, and whymoods and motivational states influence creativity. Their meta-analysisshowed that conventional ideas about when and how creativity is achievedare not correct. People are not more creative when they are relieved andrelaxed (three studies, N¼ 750, r¼ .01, p¼ ns), which is in line with ourresults.

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In contrast, the effects of emotional detachment from work on our twocognitive outcomes were not completely in line with our predictions: Anincrease in cognitive job resources was associated with more creativity incase of high emotional detachment from work. An explanation could be thatemotional detachment from work has to do with effective recovery (i.e.,restoration of internal resources) from emotionally laden, negative, workreflections. Negative work reflections are assumed to be resource-consumingexperiences (Fritz & Sonnentag, 2006), and might lead to negative sustainedactivation in the human brain (Brosschot et al., 2006). This could blockemployee creativity to a large extent. From a different perspective, one couldalso argue that emotional detachment from work may give way foran increase in positive affect that is known to foster creativity (Amabile,Barsade, Mueller, & Staw, 2005).

Limitations

This first study on the integration of the off-job recovery concept into theDISC Model is not without limitations. A first limitation concerns its cross-sectional design as well as its reliance on only self-report measures.Although we suggested a particular causal order of the variables, othercausal directions or even reciprocal relations could be possible as well. Forinstance, Cropley et al. (2006) mentioned that employees who perceive theirjobs as challenging and stimulating may also find themselves continuouslythinking about work issues during leisure time. In addition, a two-wavelongitudinal panel survey by Binnewies et al. (2009) showed that creativitywas related to a decrease in feeling recovered during leisure time over time.Future multiwave longitudinal studies should investigate this kind ofassociations more profoundly. Added to this, common method variancemight have played a role, although recent studies showed that this influenceis not as high as could be expected (cf. Spector, 2006). For instance, recentstudies (de Jonge & Peeters, 2009; Fritz et al., 2010; Sonnentag, Kuttler, &Fritz, 2010) showed that self-reports and other-reports (i.e., co-workers orspouses) converged significantly on the presumed associations, chippingaway at the assumption that self-report of these types of job characteristicsand outcome measures necessarily results in systematic bias and inflatedrelations.

A second concern is that our study might suffer from power problems dueto the large number of predictors compared to sample size. Related to thisis the modest amount of variance explained by the interaction terms(DR2¼ 4–6%). However, this does neither negate the theoretical importancenor mean that the, interactive, effects have little substantive significance. Theresults are important indeed because the size of any interaction effect isattenuated by measurement error when interaction terms are formed by

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multiplying variables to form cross-product terms as is required inregression analysis (Aiken & West, 1991).

A third concern is the somewhat lower alpha for cognitive resources.However, as the scale showed higher alphas in other studies (alphas4 .70),and could not be improved in the current study by deleting items, we decidedto keep the current scale to make future replication studies possible.

A final limitation is that the present study addressed the matchingprinciple in a subset of conditions only. Though we tested eightnonhypothesized three-way interactions (e.g., Cognitive demands6Cogni-tive resources6Cognitive detachment in the prediction of emotionalexhaustion), we did not explicitly test for nonmatching three-way interac-tions, merely due to power problems as well as the huge amount ofnonmatching interactions to be tested (i.e., 96 nonmatching three-wayinteractions). Future studies should at least check1 all possible conditions toenable full support for the matching hypotheses to be obtained (cf. de Jonge& Dormann, 2006).

Implications for future research and practice

A first avenue for further research is the long-term relation between off-jobrecovery, job demands, and job resources in the prediction of health andperformance-related outcomes. Longitudinal studies covering large andmultiple time intervals are badly needed (cf. Geurts & Sonnentag, 2006;Sonnentag, Kuttler, & Fritz, 2010). Another level of analysis concerns short-term effects, for instance differentiating between acute and enduringsituations where there is some level of match of job resources (e.g., Geverset al., 2010), or day-level research on the issue of short-term matching jobresources and short-term matching off-job recovery (e.g., Spoor, de Jonge, &Hamers, 2010). A final level of analysis stems from vacation research whichshows that detachment from work is also relevant during longer respites(e.g., de Bloom et al., 2009; Fritz & Sonnentag, 2006). Therefore, the rolethat time plays deserves further attention.

A second avenue for future research is concerned with the particular typeof nonwork-time activities in this type of research (i.e., passive or activerecovery—cf. Geurts & Sonnentag, 2006). For instance, physical detach-ment does not imply that a person should abstain from all physicalactivities, such as sports or gardening. In line with DISC theory, it could bethat nonwork-time behaviors that require other types of effort than those at

1Based upon the acting editor’s and reviewers’ suggestions, we did check all remaining

nonmatching three-way interactions. It appeared that four out of 96 (or 4.2%) nonmatching

three-way interactions were significant, which is a lower percentage than the one out of four (or

25%) significant matching three-way interactions.

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work are more significant in maximizing detachment from work than iscommonly recognized (see also Winwood, Bakker, & Winefield, 2007).

A third and final avenue for more research attention could be given tothe specific detachment concepts. For example, with respect to emotionaldetachment it would be interesting to relate emotional detachment to theemotion regulation literature. Possibly, emotional detachment might beachieved by processes similar to surface and deep acting (see alsoBrotheridge & Lee, 2002).

Although causal interpretations of our data are tentative, the studyfindings suggest promising directions for today’s practice. First, organiza-tions should provide those job resources that correspond to particular jobdemands in order to stimulate health, active learning, and creativity.Second, it is important to notice that detachment from work seems to beassociated with health and performance-related outcomes, although indifferent ways. Both supervisors and employees should pay attention todetachment from work as a double-edged sword: Cognitive detachmentfrom work might have negative effects on learning and creativity, whereasemotional and physical detachment from work might have positive effectson employees’ health, and even on creativity. For that very reason,supervisors should be refrained from making the right type of detachmentimpossible to serve both job performance and employee health. They canalso act as role models, showing how detachment can be most effective. Withrespect to performance-related outcomes, organizations and supervisorsshould encourage employees to give themselves sufficient time to changebetween work and nonwork modes (Ashforth et al., 2000). Recent researchshowed that detachment can be learned (Hahn, Binnewies, Sonnentag, &Mojza, 2011), indicating that employees can influence the way and degreethey detach from work. This means that employees should also take careof their own off-job recovery for their personal health by learning andimproving adequate cognitive, emotional, and physical distraction techni-ques. For instance, this can be conducted by attention switching andthought stopping (Cropley & Millard Purvis, 2003), adequately separatingtheir work and nonwork life (cf. Sonnentag et al., 2008), and activeinvolvement in nonwork-time behaviors such as playing sports andgardening, which require other types of effort than those at work (cf.Winwood et al., 2007).

CONCLUSIONS

Modern organizations want healthy and productive employees. In order tocope with specific job demands, employees need corresponding job resourcesand detachment from work to balance health and performance-relatedoutcomes. For organizational and performance purposes, it seems to be

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beneficial for employees to think about one’s work during off-job time (i.e.,effective problem solving, and the development of new ideas and plans), andalso to enhance a person’s willingness to actively engage in learning whenback at the workplace. When working in a highly enjoyable and stimulatingcontext, and the ‘‘pondering on a problem’’ aspect of rumination mayappear effectual, detachment might not be needed. In the long term,however, the continual emphasis on work at the cost of no detachment at allmight lead to health problems (Cropley et al., 2006, Siltaloppi et al., 2009;Sonnentag, Kuttler, & Fritz, 2010). So, the importance of appropriatelydetaching from work (either actively or passively) for an employee’s healthshould not be ignored in this respect.

Therefore, the ultimate benefits for both employees and organizationsseem to lie in a healthy balance between different types of detachment fromwork. An interesting avenue for future research would be to examine theprecise conditions under which detachment from work is most beneficial andwhen it might even have negative effects.

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