Journal of Occupational and Organizational Psychology (2001) 74 29ndash46 Printed in Great BritainOacute 2001 The British Psychological Society

Testing reciprocal relationships between jobcharacteristics and psychological well-being

A cross-lagged structural equation model

Jan de JongeDepartment of Social and Organizational Psychology Utrecht University The Netherlands

Department of Work and Organizational Psychology University of Nijmegen The Netherlands

Christian DormannDepartment of Work and Organizational Psychology Johann Wolfgang Goethe University Germany

Peter P M JanssenDepartment of Health Organization Policy and Economics Section Work and Health

Maastricht University The Netherlands

Maureen F DollardSchool of Psychology University of South Australia Whyalla Campus South Australia

Jan A Landeweerd and Frans J N NijhuisDepartment of Health Organization Policy and Economics Section Work and Health

Maastricht University The Netherlands

This article describes a two-wave panel study which was carried out to examinereciprocal relationships between job characteristics and work-related psychologicalwell-being

Hypotheses were tested in a sample of 261 health care professionals usingstructural equation modelling (LISREL 8) Controlling for gender age andnegative aVectivity the results primarily supported the hypothesis that Time 1 jobcharacteristics in uence Time 2 psychological well-being More speci cally Time 2job satisfaction was determined by Time 1 job demands and workplace socialsupport respectively Furthermore there was also some preliminary but weakevidence for reversed cross-lagged eVects since Time 1 emotional exhaustion seemedto be the causal dominant factor with respect to Time 2 (perceived) job demands

In conclusion this study builds on earlier cross-sectional and longitudinal ndings by eliminating confounding factors and diminishing methodologicalde ciencies Empirical support for the in uence of job characteristics onpsychological well-being aYrms what several theoretical models have postulatedto be the causal ordering among job characteristics and work-related psychologicalwell-being

Requests for reprints should be addressed to Jan de Jonge Department of Social and Organizational PsychologyUtrecht University PO Box 80140 3508 TC Utrecht The Netherlands

29

The purpose of this study was to examine the causal relationship between jobcharacteristics and employee psychological well-being While there is some generalagreement that these relationships do exist there is still some disagreement aboutthe speci c nature magnitude and in particular the causal direction of therelationships (eg Semmer Zapf amp Greif 1996 Zapf Dormann amp Frese 1996)For instance do high job demands lead to job-related strain Or is strain primarysuch that high-strained workers are more likely to report their job demands ashigher Good examples of longitudinal panel studies are scarce (less than 10according to Zapf and colleagues) which means that evidence of strong causalrelationships between job characteristics and well-being outcomes has beenpiecemeal and limited in scope Moreover comprehensive empirical tests of allpostulated relationships by means of sophisticated statistical techniques such ascovariance structure models are rather scarce as well (Zapf et al 1996)

Demonstrating causal relationships has become important from a theoreticalpractical and methodological perspective For example prominent job character-istics models like the demandndashcontrolndashsupport (DCS) model (Karasek amp Theorell1990) and the job characteristics (JC) model (Hackman amp Oldham 1980) assumethat the causal ow is unidirectional where job characteristics aVect well-beingoutcomes and not vice versa If this is really the case then there is reason tobelieve that some of the observed problems may have their roots in the propertiesof the job itself Therefore restructuring jobs or workplaces may be a usefulstarting-point for eVective interventions

However current transactional models like Edwardsrsquo cybernetic model of stresscoping and well-being (Edwards 1998) emphasize the reciprocal nature of thestress process in which perceived job characteristics are also aVected by employeewell-being Practically the impact of stress management on employee well-beingmultiplies itself over time as increases in well-being and decreases in job stressorsmutually reinforce each other (Daniels amp Guppy 1997)

There are still methodological pitfalls and de ciencies in longitudinal researchwhich make it very diYcult to detect causal as well as reciprocal relationshipsAccording to Frese and Zapf (1988) as well as Kessler and Greenberg (1981) aplausible causal relationship exists between two variables if there is an associationof some sort between them if there is evidence about the direction of causality andif other explanations can be ruled out In short we cannot demonstrate causalityWe can only make causal relationships plausible by ruling out alternative expla-nations (see also Bollen 1989) In this respect several recommendations can bemade such as performing a full panel design with an adequately planned time lagtaking stabilities of variables into account and using covariance structure modelling(eg Finkel 1995 Frese amp Zapf 1988 Van der Kamp amp Bijleveld 1998 Williamsamp PodsakoV 1989 Zapf et al 1996)

The focus of the present article is on the direction of relationships between jobcharacteristics and work-related psychological well-being in a two-wave panelstudy In this context the DCS model or the JC model are useful vehicles toinvestigate speci c job characteristics and speci c well-being outcomes Bothmodels obviously favour the unidirectional perspective and allow for unambiguouspredictions of the signs of the relationships between job characteristics and

30 Jan d e Jonge et al

employee well-being For example a two-wave panel study involving 180 studentteachers by Parkes Mendham and Von Rabenau (1994) revealed that Time 2somatic symptoms were predicted by a combination of high Time 1 demands lowTime 1 autonomy and low Time 1 social support For this reason we hypothesizethat job characteristics at Measurement 1 in uence employee well-being atMeasurement 2 (H1)

There are methodological and substantive reasons to expect reversed eVects ofemployee well-being on working conditions According to the so-called drifthypothesis (Frese 1982 Kohn amp Schooler 1983 Lorence amp Mortimer 1985Williams amp PodsakoV 1989) one can postulate that highly motivated workers driftto better jobs accompanied with more job autonomy more support and fewerdemands In contrast people with bad health or motivational de cits in particularmay drift to worse jobs due to their bad personal record of sickness absenteeism oreven disability (see also Waldron Herold Dunn amp Staum 1982)

As Daniels and Guppy (1997) have noted lsquoas the individual changes so will hisor her transactions with the environmentrsquo (p 157) For instance unsatised peoplepeople with a low motivation or people who are emotionally exhausted may receiveless social support because people with poor well-being may not be seen as beingable to reciprocate by their supervisors and colleagues (Daniels amp Guppy 1997)Since supervisors may perceive them as also lacking drive they may not be givenautonomy either Added to this one could also argue that occupational burnoutleads to cognitive and behavioural withdrawal reactions which in turn lead to lackof workplace social support (Schaufeli amp Enzmann 1998 see also Firth-Cozens ampHardy 1992)

Even if the actual amount of support autonomy and demands do not changethere may be poorer perceptions of these working conditions It is well known thatnegative moods in particular depression lead to an increased recall of negativeinformation (eg Mathews 1993 Taris Bok amp Calje 1998) Since uncontrollableevents are supposed to be more aversive than controllable ones (Miller 1980)following Daniels and Guppy it can be argued that people with reduced mood mayrecall more uncontrollable events and thus report less autonomy Similarlyindividuals with reduced aVective well-being may recall more demands and fewersituations in which they received support so that they report less support than wasactually available to them and more demands (see also Firth-Cozens 1992)

Nevertheless in their overview of longitudinal studies by Zapf et al (1996) onlysix out of 16 studies on organizational stress which tested for reversed causationyielded evidence for reversed causation Thus when compared to the great numberof theoretically proposed mechanisms the empirical evidence for such eVects is notstrong In conclusion our second hypothesis is that psychological well-being atMeasurement 1 in uences (perceived) job characteristics at Measurement 2 (H2)

Finally as several authors have stated (eg Caldwell amp OrsquoReilly 1982 James ampJones 1980 James amp Tetrick 1986 Williams amp PodsakoV 1989 Zapf et al 1996)there is also reason to believe that reciprocal relationships between (perceived) jobcharacteristics and psychological well-being do exist in that Time 2 well-being isin uenced by Time 1 job characteristics and Time 2 (perceived) job characteristicsare aVected by Time 1 psychological well-being Williams and PodsakoV (1989) for

Job characteristics and psychological well-being reciprocal relationships 31

The purpose of this study was to examine the causal relationship between jobcharacteristics and employee psychological well-being While there is some generalagreement that these relationships do exist there is still some disagreement aboutthe speci c nature magnitude and in particular the causal direction of therelationships (eg Semmer Zapf amp Greif 1996 Zapf Dormann amp Frese 1996)For instance do high job demands lead to job-related strain Or is strain primarysuch that high-strained workers are more likely to report their job demands ashigher Good examples of longitudinal panel studies are scarce (less than 10according to Zapf and colleagues) which means that evidence of strong causalrelationships between job characteristics and well-being outcomes has beenpiecemeal and limited in scope Moreover comprehensive empirical tests of allpostulated relationships by means of sophisticated statistical techniques such ascovariance structure models are rather scarce as well (Zapf et al 1996)

Demonstrating causal relationships has become important from a theoreticalpractical and methodological perspective For example prominent job character-istics models like the demandndashcontrolndashsupport (DCS) model (Karasek amp Theorell1990) and the job characteristics (JC) model (Hackman amp Oldham 1980) assumethat the causal ow is unidirectional where job characteristics aVect well-beingoutcomes and not vice versa If this is really the case then there is reason tobelieve that some of the observed problems may have their roots in the propertiesof the job itself Therefore restructuring jobs or workplaces may be a usefulstarting-point for eVective interventions

However current transactional models like Edwardsrsquo cybernetic model of stresscoping and well-being (Edwards 1998) emphasize the reciprocal nature of thestress process in which perceived job characteristics are also aVected by employeewell-being Practically the impact of stress management on employee well-beingmultiplies itself over time as increases in well-being and decreases in job stressorsmutually reinforce each other (Daniels amp Guppy 1997)

There are still methodological pitfalls and de ciencies in longitudinal researchwhich make it very diYcult to detect causal as well as reciprocal relationshipsAccording to Frese and Zapf (1988) as well as Kessler and Greenberg (1981) aplausible causal relationship exists between two variables if there is an associationof some sort between them if there is evidence about the direction of causality andif other explanations can be ruled out In short we cannot demonstrate causalityWe can only make causal relationships plausible by ruling out alternative expla-nations (see also Bollen 1989) In this respect several recommendations can bemade such as performing a full panel design with an adequately planned time lagtaking stabilities of variables into account and using covariance structure modelling(eg Finkel 1995 Frese amp Zapf 1988 Van der Kamp amp Bijleveld 1998 Williamsamp PodsakoV 1989 Zapf et al 1996)

The focus of the present article is on the direction of relationships between jobcharacteristics and work-related psychological well-being in a two-wave panelstudy In this context the DCS model or the JC model are useful vehicles toinvestigate speci c job characteristics and speci c well-being outcomes Bothmodels obviously favour the unidirectional perspective and allow for unambiguouspredictions of the signs of the relationships between job characteristics and

30 Jan d e Jonge et al

employee well-being For example a two-wave panel study involving 180 studentteachers by Parkes Mendham and Von Rabenau (1994) revealed that Time 2somatic symptoms were predicted by a combination of high Time 1 demands lowTime 1 autonomy and low Time 1 social support For this reason we hypothesizethat job characteristics at Measurement 1 in uence employee well-being atMeasurement 2 (H1)

There are methodological and substantive reasons to expect reversed eVects ofemployee well-being on working conditions According to the so-called drifthypothesis (Frese 1982 Kohn amp Schooler 1983 Lorence amp Mortimer 1985Williams amp PodsakoV 1989) one can postulate that highly motivated workers driftto better jobs accompanied with more job autonomy more support and fewerdemands In contrast people with bad health or motivational de cits in particularmay drift to worse jobs due to their bad personal record of sickness absenteeism oreven disability (see also Waldron Herold Dunn amp Staum 1982)

As Daniels and Guppy (1997) have noted lsquoas the individual changes so will hisor her transactions with the environmentrsquo (p 157) For instance unsatised peoplepeople with a low motivation or people who are emotionally exhausted may receiveless social support because people with poor well-being may not be seen as beingable to reciprocate by their supervisors and colleagues (Daniels amp Guppy 1997)Since supervisors may perceive them as also lacking drive they may not be givenautonomy either Added to this one could also argue that occupational burnoutleads to cognitive and behavioural withdrawal reactions which in turn lead to lackof workplace social support (Schaufeli amp Enzmann 1998 see also Firth-Cozens ampHardy 1992)

Even if the actual amount of support autonomy and demands do not changethere may be poorer perceptions of these working conditions It is well known thatnegative moods in particular depression lead to an increased recall of negativeinformation (eg Mathews 1993 Taris Bok amp Calje 1998) Since uncontrollableevents are supposed to be more aversive than controllable ones (Miller 1980)following Daniels and Guppy it can be argued that people with reduced mood mayrecall more uncontrollable events and thus report less autonomy Similarlyindividuals with reduced aVective well-being may recall more demands and fewersituations in which they received support so that they report less support than wasactually available to them and more demands (see also Firth-Cozens 1992)

Nevertheless in their overview of longitudinal studies by Zapf et al (1996) onlysix out of 16 studies on organizational stress which tested for reversed causationyielded evidence for reversed causation Thus when compared to the great numberof theoretically proposed mechanisms the empirical evidence for such eVects is notstrong In conclusion our second hypothesis is that psychological well-being atMeasurement 1 in uences (perceived) job characteristics at Measurement 2 (H2)

Finally as several authors have stated (eg Caldwell amp OrsquoReilly 1982 James ampJones 1980 James amp Tetrick 1986 Williams amp PodsakoV 1989 Zapf et al 1996)there is also reason to believe that reciprocal relationships between (perceived) jobcharacteristics and psychological well-being do exist in that Time 2 well-being isin uenced by Time 1 job characteristics and Time 2 (perceived) job characteristicsare aVected by Time 1 psychological well-being Williams and PodsakoV (1989) for

Job characteristics and psychological well-being reciprocal relationships 31

employee well-being For example a two-wave panel study involving 180 studentteachers by Parkes Mendham and Von Rabenau (1994) revealed that Time 2somatic symptoms were predicted by a combination of high Time 1 demands lowTime 1 autonomy and low Time 1 social support For this reason we hypothesizethat job characteristics at Measurement 1 in uence employee well-being atMeasurement 2 (H1)

There are methodological and substantive reasons to expect reversed eVects ofemployee well-being on working conditions According to the so-called drifthypothesis (Frese 1982 Kohn amp Schooler 1983 Lorence amp Mortimer 1985Williams amp PodsakoV 1989) one can postulate that highly motivated workers driftto better jobs accompanied with more job autonomy more support and fewerdemands In contrast people with bad health or motivational de cits in particularmay drift to worse jobs due to their bad personal record of sickness absenteeism oreven disability (see also Waldron Herold Dunn amp Staum 1982)

As Daniels and Guppy (1997) have noted lsquoas the individual changes so will hisor her transactions with the environmentrsquo (p 157) For instance unsatised peoplepeople with a low motivation or people who are emotionally exhausted may receiveless social support because people with poor well-being may not be seen as beingable to reciprocate by their supervisors and colleagues (Daniels amp Guppy 1997)Since supervisors may perceive them as also lacking drive they may not be givenautonomy either Added to this one could also argue that occupational burnoutleads to cognitive and behavioural withdrawal reactions which in turn lead to lackof workplace social support (Schaufeli amp Enzmann 1998 see also Firth-Cozens ampHardy 1992)

Even if the actual amount of support autonomy and demands do not changethere may be poorer perceptions of these working conditions It is well known thatnegative moods in particular depression lead to an increased recall of negativeinformation (eg Mathews 1993 Taris Bok amp Calje 1998) Since uncontrollableevents are supposed to be more aversive than controllable ones (Miller 1980)following Daniels and Guppy it can be argued that people with reduced mood mayrecall more uncontrollable events and thus report less autonomy Similarlyindividuals with reduced aVective well-being may recall more demands and fewersituations in which they received support so that they report less support than wasactually available to them and more demands (see also Firth-Cozens 1992)

Nevertheless in their overview of longitudinal studies by Zapf et al (1996) onlysix out of 16 studies on organizational stress which tested for reversed causationyielded evidence for reversed causation Thus when compared to the great numberof theoretically proposed mechanisms the empirical evidence for such eVects is notstrong In conclusion our second hypothesis is that psychological well-being atMeasurement 1 in uences (perceived) job characteristics at Measurement 2 (H2)

Finally as several authors have stated (eg Caldwell amp OrsquoReilly 1982 James ampJones 1980 James amp Tetrick 1986 Williams amp PodsakoV 1989 Zapf et al 1996)there is also reason to believe that reciprocal relationships between (perceived) jobcharacteristics and psychological well-being do exist in that Time 2 well-being isin uenced by Time 1 job characteristics and Time 2 (perceived) job characteristicsare aVected by Time 1 psychological well-being Williams and PodsakoV (1989) for

Job characteristics and psychological well-being reciprocal relationships 31

instance have argued that at a conceptual level such reciprocal relationships areprevalent in organizational behaviour research like job design and job stressresearch Bi-directional in uences which imply some sort of vicious circle do notcorrespond entirely to the nature of most social and psychological systems Hencea few longitudinal studies have demonstrated that simultaneous reciprocal causalitydoes occur (eg Bateman amp Strasser 1983 James amp Jones 1980 James amp Tetrick1986 Kohn amp Schooler 1983 Schwarzer Hahn amp Jerusalem 1993 Taris et al1998) For example Schwarzer et al (1993) found in a three-wave panel study thatpoor mental health leads to lower (perceived) social support which in turn leadsto poorer mental health Taken together we nally hypothesize that in addition toHypotheses 1 and 2 (perceived) job characteristics and psychological well-beingmutually in uence each other (H3)

In addition to all this the present study was designed to address some of theabove-mentioned methodological issues (eg performing a full panel design andusing covariance structure modelling)

Method

Design and participants

We conducted a full panel design with two panel waves participants supplied data at twomeasurement points in time The aim was to have about a one-year interval between the twomeasurements This time appears to be long enough for possible changes in individual scores but nottoo long for too much non-response in our study sample (see also Frese amp Zapf 1988 Vermaat1994) Moreover in this way possible seasonal uctuations in work were controlled for

Self-report questionnaires were administered and could be returned by mail All questionnairescontained an administration number for second round identi cation

As part of an extensive research project (De Jonge 1995) the initial sample consisted of health careworkers of one general hospital and three nursing homes in The Netherlands At Time 1 457 healthcare workers received the questionnaires and 380 respondents returned the questionnaire (83response rate) At Time 2 363 out of 454 health care workers returned the questionnaire giving an80 response rate The nal sample re ects those persons who participated at both times Thenumber of respondents who completed both questionnaires was 261 or 57 of the initial group Thispercentage is not very unusual according to the literature about panel non-response (Hagenaars1990) A breakdown of the demographic characteristics of the sample shows that 89 of the healthcare workers were women The mean age of the group was 3187 years (SD = 8middot52) The mean workexperience was 1068 years (SD = 7middot17) and 45 of the respondents worked full-time

A comparison of continuous participants with drop-outs showed that our data did not appear tosuVer from serious selection problems The panel group was signi cantly older (t = 204 plt 05) andhad signi cantly higher mean work experience (MannndashWhitney Z = 402 plt 001) These results arenot surprising because a substantial number of the drop-outs were (young) student nurses whochange units twice a year

An important question is whether disappearance from the sample is an outcome of a causaldynamic that is diVerent from that of the survivors To nd out whether this was the case or not itis advisable to check for causal homogeneity in the sample (Hagenaars 1990 Kessler amp Greenberg1981) In other words causal relationships should be (nearly) the same for the panel group and thedrop-outs Cross-sectional multi-sample structural equation analyses (Joreskog amp Sorbom 1993)indicated that disappearance from the sample was not likely to be the result of diVerent causaldynamics (group comparison D v 2(12) = 909 p = ns) Therefore both groups were quite comparablein terms of internal consistency as well as in terms of the pattern of relationships between jobcharacteristics and psychological well-being

32 Jan d e Jonge et al

Measures

The questionnaire comprised three main sections demographicpersonal characteristics jobcharacteristics and employee psychological well-being

Demographic and personal characteristics These refer to background factors such as gender age andnegative aVectivity These variables may confound the results (Burke Brief amp George 1993 Karasekamp Theorell 1990 Spector 1997) Therefore we included these variables to control for their possiblein uence Negative aVectivity was measured by trait anxiety as recommended by several authors(Clark Watson amp Mineka 1994 Dollard amp Wine eld 1998 Watson amp Clark 1984) The scale wasderived from the Dutch Organizational Stress Questionnaire (Reiche amp Van Dijkhuizen 1979) andconsists of four items with a response scale ranging from 1 lsquoneverrsquo to 4 lsquoalwaysrsquo An example item islsquoI feel nervousrsquo

The job characteristics demands autonomy and social support included in this study were guidedby Karasekrsquos DCS model (Karasek amp Theorell 1990) In order to minimize bias the subjectiveindictors of the job characteristics contained items with a minimum of cognitive processing In otherwords these items were precisely de ned and were worded as neutrally as possible (cf Frese 1999Frese amp Zapf 1988)

Job d emands These were measured by an eight-item questionnaire (5-point response scale ranging from1 lsquoneverrsquo to 5 lsquoalwaysrsquo) that included a wide range of qualitative and quantitative demanding aspectsof the job such as working under time pressure working hard and job complexity The psychologicaljob demands scale has been well validated in Dutch samples of health care professionals (eg DeJonge Janssen amp Van Breukelen 1996 De Rijk Le Blanc Schaufeli amp De Jonge 1998) An exampleitem is lsquoIn the unit where I work work is carried out under pressure of timersquo

Job autonomy This was assessed by the Maastricht Autonomy Questionnaire (MAQ De JongeLandeweerd amp Van Breukelen 1994 De Jonge 1995) which consisted of ten Likert-items with a5-point response scale ranging from 1 lsquovery littlersquo to 5 lsquovery muchrsquo The MAQ measures the workerrsquosopportunity to determine a variety of task elements like the method of working the pace of work andthe work goals For instance lsquoThe opportunity that the work oVers to determine the method ofworking yourselfrsquo

Workplace social support A ten-item scale of total work-related social support (from the seniornursing oYcer as well as from colleagues) was used to measure workplace social support Thescale was derived from a Dutch questionnaire on organizational stress (VOS-D Bergers Marcelissenamp De WolV 1986) A 4-point response scale was used ranging from 1 lsquoneverrsquo to 4 lsquoalwaysrsquo Forinstance lsquoIf there are problems at work can you talk about them with your senior nursingoYcercolleaguesrsquo

The choice of the three psychological well-being variables (cf Warr 1987) was also guidedby the DCS model (see also Van der Doef amp Maes 1999) That is emotional exhaustion re ectedoutcomes of the job-strain hypothesis of the DCS model whereas job satisfaction and workmotivation re ected outcomes of the active behaviour hypothesis (for more details see Karasek ampTheorell 1990)

Emotional exhaustion We measured emotional exhaustion by means of the Dutch version of theMaslach Burnout Inventory (Schaufeli amp Van Dierendonck 1993) This instrument is particularlysuitable for use in human services professions like nursing Moreover emotional exhaustion is themost characteristic burnout dimension that is closest to more orthodox job-strain variables(Enzmann Schaufeli Janssen amp Rozemann 1998 Maslach 1998) In its original form the scaleconsists of nine items scored on a 7-point scale (ranging from 0 lsquoneverrsquo to 6 lsquoalwaysrsquo) Becauseof insuYcient factorial validity in earlier burnout studies one of the original items (ie lsquoWorkingwith people directly puts too much stress on mersquo) was eliminated in the Dutch version ofthe MBI

Job satisfaction This was assessed by a single item (ie lsquoI am satis ed with my present jobrsquo) that wasscored on a 5-point rating scale ranging from 1 lsquostrongly disagreersquo to 5 lsquofully agreersquo It has been shownthat a global index of overall job satisfaction is a valid measure of general job satisfaction (eg

Job characteristics and psychological well-being reciprocal relationships 33

Scarpello amp Campbell 1983 Wanous Reichers amp Hudy 1997) Wanous et al (1997) assumed areliability of 57 for such a single-item measure

Work motivation This was measured by ve items in which the respondents were asked howstimulating interesting and challenging their work was (De Jonge 1995) The questions wereanswered on a 5-point scale with a response scale ranging from 1 (lsquostrongly disagreersquo to 5 lsquofully agreersquoFor example lsquoMy work stimulates me to perform better all the timersquo

Data analysis

We performed covariance structure modelling (LISREL 8 Joreskog amp Sorbom 1993) in order toanalyse our panel data Because of the large number of items used to operationalize all the variablesin our model simultaneous consideration of all observed variables (ie items) would result inunreliable parameter estimates and insuYcient power (Bentler amp Chou 1987 Jaccard amp Wan 1996)Therefore each of the components in the panel model was included in the structural equationanalyses as a latent variable In other words the covariance structure model was simpli ed byassuming that the observed and latent variables were identical (each construct had only oneoperationalization) Furthermore a two-step approach was followed (cf Anderson amp Gerbing 1988)First we tested the measurement models and secondly we tested the structural equation modelsThe measurement models used showed the variables to be valid and reliable (De Jonge 1995 seealso Table 1)

Using structural equation modelling may lead to a slightly complex variant of the general panelmodel (eg see Finkel 1995 Kessler amp Greenberg 1981) By means of such a cross-lagged structuralequation model (see Fig 1) a number of competing structural equation models were tted to the datain several steps First of all a model without cross-lagged structural paths but with temporal stabilities(model M1) was speci ed Second this stability model was compared with three more complex modelsthat were nearest in likelihood to the hypothesized structural model

(1) a model with cross-lagged structural paths from Time 1 job characteristics to Time 2psychological well-being (model M2 re ecting Hypothesis H1 in arrow 1)

(2) a model with cross-lagged structural paths from Time 1 psychological well-being to Time 2 jobcharacteristics (model M3 re ecting Hypothesis H2 in arrow 2)

(3) a model with both cross-lagged structural patterns (model M4) representing reciprocal eVects(re ecting Hypothesis H3 in arrows 1 and 2)

Full information maximum likelihood (FIML) estimation was used to assess the t of thiscross-lagged structural equation model Note that the model consists of regression coeYcientsrepresenting the diVerential cross-lagged structural paths testndashretest coeYcients between themeasurement scales covariances between the background variables residual covariances between thejob characteristics and errors in equations The latter are allowed to correlate because error causedby mis-speci cation of the model would be re ected in these correlations The existence of anadditional variable that is not included in the model might be responsible for this error-correlation(called occasion-factor by Dwyer 1983) and is necessary in order to explain the outcome variablesmore fully (Long 1983 MacCallum Wegener Uchino amp Fabrigar 1993) Moreover Time 1 gender(dummy variable) Time 1 age and Time 1 negative aVectivity (NA) were introduced into the panelmodel as potential confounders Consequently these variables were labelled as exogenous variables(see Bollen 1989 p 126) and all other variables were labelled as endogenous variables (ie the jobcharacteristics and psychological well-being) Finally we assume that gender age and negativeaVectivity were directly related to the Time 1 variables and only indirectly to the Time 2 variables (ieby way of testndashretest coeYcients from Time 1 variables to Time 2 variables)

ResultsPreliminary results

Prior to the LISREL analyses the means standard deviations coeYcient alphasand Pearson correlations (including testndashretest coeYcients) were computed (see

34 Jan d e Jonge et al

Tab

le1

Mea

nss

tand

ard

devi

atio

ns(S

D)

coe Y

cien

tal

phas

(a)

and

Pea

rson

corr

elat

ions

ofth

est

udy

varia

bles

Mea

sure

sM

SDa

12

34

56

78

910

1112

1314

1G

ende

ra(1

)mdash

mdash2

Age

(1)

318

78

522

11

3A

Vec

tivity

(1)

144

41

75

20

50

14

Dem

ands

(1)

316

68

88

20

80

32

15

Aut

onom

y(1

)2

735

98

12

19

13

20

32

30

6Su

ppor

t(1

)3

343

27

50

82

04

21

92

24

24

7Sa

tisfa

ctio

n(1

)4

028

5mdash

08

20

92

34

23

12

54

68

Mot

ivat

ion

(1)

382

69

86

20

22

16

20

72

26

19

34

52

9E

xhau

stio

n(1

)1

689

28

52

06

20

74

55

22

13

22

52

40

22

710

Dem

ands

(2)

316

71

89

20

22

01

20

72

23

52

21

22

82

21

50

11A

uton

omy

(2)

278

58

84

21

60

42

04

22

76

42

92

22

52

16

24

312

Sup

port

(2)

328

38

82

13

20

02

18

22

12

35

93

63

22

26

23

43

913

Sat

isfa

ctio

n(2

)3

948

3mdash

06

20

32

26

23

42

43

85

54

32

43

24

03

95

314

Mot

ivat

ion

(2)

363

66

86

21

12

06

20

92

20

17

25

40

62

22

52

20

27

42

55

15E

xhau

stio

n(2

)1

618

88

50

12

12

37

33

21

72

24

23

52

25

66

50

23

32

44

25

42

36

p

05

two-

taile

da G

ende

rw

asco

ded

0(m

ales

)an

d1

(fem

ales

)N

ote

N=

261

Key

(1

)=T

ime

1(2

)=T

ime

2

Job characteristics and psychological well-being reciprocal relationships 35

The rst chi-square diVerence test showed that the diVerence between thestability model and the model with cross-lagged eVects from job characteristics towell-being outcomes was signicant (M1 vs M2 D v 2(9) = 1701 p 05) Thismeans that the unconstrained model with lagged eVects (M2) better accounts forthe data than the constrained model with no lagged eVects (M1) In other wordsthere is statistical evidence that Time 1 job characteristics in uence Time 2psychological well-being

Alternatively a second chi-square diVerence test showed that the diVerencebetween the stability model and the model with cross-lagged structural paths fromTime 1 well-being to Time 2 (perceived) job characteristics was not signi cant (M1

vs M3 D v 2(9) = 1191 p = ns) Thus model M3 has no better statistical t thanmodel M1 Generally psychological well-being in Measurement 1 was not able toin uence (perceived) job characteristics in Measurement 2

The chi-square diVerence test between the stability model and the model with allcross-lagged structural paths was signi cant (M1 vs M4 D v 2(18) = 3037 p 05)However model t did not improve if reversed structural paths were added to theconventional paths (M2 vs M4 D v 2(9) = 1336 p = ns) On the contrary therewas a clear improvement in model t if usual structural paths were added to thereversed paths (M3 vs M4 D v 2(9) = 1846 p 05) Generally in terms ofchi-square relative to the degrees of freedom model M2 showed the best t of allcompeting models (see Table 2) Model M2 also had a relatively good t when themost important practical t indices were reviewed (ie GFI = 96 AGFI = 86RMSEA = 07 NNFI = 91 AIC = 24031 PNFI = 35 and CFI = 97) accordingto criteria presented by Hu and Bentler (1998) or by Schumacker and Lomax(1996) For instance in terms of model comparisons model M2 showed the bestcombination of NNFI and CFI In terms of parsimony model M2 showed thelowest AIC compared to the other lagged models (ie models M3 and M4) If onewere to take these t indices as the most important ones it would also lead to thepreference of model M2

Table 2 Goodness-of- t indices and chi-square diVerence tests of nested structuralmodels of psychological well-being

Model v 2 df Comparison D v 2 D df

No cross-lagged (M1) 9886 48Cross JCT1ndashPWT2 (M2) 8185 39 M1 vs M2 1701 9Cross PWT1ndashJCT2 (M3) 8695 39 M1 vs M3 1191 9Both cross (M4) 6849 30 M1 vs M4 3037 18

M2 vs M4 1336 9M3 vs M4 1846 9

p 05 p 001Note N=261Key JC=Job characteristics PW=Psychological well-being T1=Time 1 T2=Time 2

Job characteristics and psychological well-being reciprocal relationships 37

coeYcients of the best tting model (M2) It should be noted that the FIMLestimates have been standardized and that only signicant relationships betweenjob characteristics and psychological well-being and testndashretest stability coeYcientsare shown Regarding the signi cant cross-lagged parameters it appears that Time 1job demands in uence Time 2 job satisfaction Higher levels of Time 1 job demandscause lower levels of Time 2 job satisfaction Furthermore Time 1 workplace socialsupport in uences Time 2 job satisfaction as well that is higher levels of socialsupport lead to higher levels of job satisfaction Taken together both job demandsand social support appeared to be the causal factors

As mentioned before evidence exists that reciprocal relationships are presentsince the unconstrained model with both types of lagged eVects (M4) betteraccounts for the data than the constrained model with no lagged eVects (M1)However we also concluded that the chi-square diVerence test was mainly causedby the eVects of job characteristics on psychological well-being This means that ingeneral the reciprocal model can exist without reversed eVects but it cannot existwithout eVects of job characteristics on psychological well-being Referring toRogosarsquos (1980) statement again we tried to explore those reciprocal cross-laggedpatterns in addition to model M2 by examining the individual pathways Resultsfrom model M4 showed one additional cross-lagged eVect from Time 1 emotionalexhaustion to Time 2 (perceived) job demands (standardized path coeYcient11 p 05) This reversed structural path indicated that higher levels of Time 1emotional exhaustion seemed to in uence higher levels of (perceived) psycho-logical job demands at Time 2

Discussion

The main purpose of the present study was to test and evaluate the direction ofrelationships between job characteristics and employee psychological well-beingWe used a two-wave panel design which allowed more rigorous interpretation ofcausality and reciprocity than cross-sectional designs Additionally we tried toavoid the possible methodological pitfalls of standard statistical techniques bytesting cross-lagged structural equation models

The results primarily supported Hypothesis H1 such that after controlling forgender age and negative aVectivity job characteristics in uenced psychologicalwell-being More speci cally both job demands and workplace social supportappeared to be the causally dominant factors with regard to job satisfactionFurthermore there was also some preliminary but weak evidence for reversedcross-lagged eVects since emotional exhaustion seemed to be the causally dominantfactor with respect to (perceived) job demands

The present ndings are consistent with the scarce longitudinal studies in thisresearch area For instance James and Tetrick (1986) performed a two-stage leastsquares analysis of job characteristics and job satisfaction After comparing threealternative causal models they concluded that job characteristics appeared to be astronger cause of job satisfaction than vice versa

A closer inspection of the lagged relationships indicated additional support forjob characteristicsndashwell-being relationships as far as job demands and workplace

Job characteristics and psychological well-being reciprocal relationships 39

social support were concerned Both variables showed a lagged pattern of relationsimilar to cross-sectional ndings presented in the literature The nding thatpsychological job demands are negatively associated with job satisfaction wasreplicated in the present study (Spector 1997) Interestingly though we found alagged eVect which strengthens earlier cross-sectional ndings in health care work(eg De Jonge et al 1996 Landsbergis 1988 McLaney amp Hurrell 1988) Thelagged relationship between social support and job satisfaction seems to re ect thenature of work of nurses and nursesrsquo aides A key characteristic feature of their jobsis that workplace social support plays an important role in daily work because forthe most part nurses and nursesrsquo aides work closely together in teams (eg ShinnRosario Morch amp Chestnut 1984) This nding also underlines the assumptions ofthe DCS model concerning highly motivated and satis ed employees (Karasek ampTheorell 1990) It is therefore not surprising that this model has been expandedwith workplace social support as a key predictor (Johnson amp Hall 1988) Finallya number of empirical studies indicate that supportive relationships generallyenhance outcomes such as job satisfaction and work motivation (eg see Boumansamp Landeweerd 1992 Parkes et al 1994 Peeters 1994) In all these results provideadditional empirical evidence for these two job characteristics in the prediction ofemployee well-being

Conversely there was weak evidence for only one lagged reversed relationshipwith emotional exhaustion as a predictor for (perceived) psychological jobdemands This contradicts the research that does nd evidence of reversedcausation (eg Zapf et al 1996) Reasons for this can only be speculative Forinstance Daniels and Guppy (1997) found only a weak eVect of poor well-being forthe appraised stressfulness of job demands not their frequency This carries therisk that relationships between demands and well-being are aVected by self-reportor method variance (Wall Jackson Mullarkey amp Parker 1996) We tried to avoidevaluative components like intensity in the measurement of demands and useddescriptive as well as frequency-based measures instead (eg Frese amp Zapf 1988)and this might be a reason for lack of corroboration A similar way of reasoningcould be true for job autonomy to explain lack of reversed causation (eg De Jonge1995 Wall et al 1996)

Previous longitudinal studies that detected reversed eVects on (perceived) socialsupport covered either a very short time lag (eg Daniels amp Guppy 1997 Fisher1985) or longer time lags (Marcelissen Winnubst Buunk amp De WolV 1988)However a panel study by Billings and Moos (1982) which used a similar time lagas our study (ie one year) failed to demonstrate lagged eVects of psychologicalsymptoms on support It might be that in general the eVect of aspects of well-beingon (perceived) social support takes place within a few months rather than aone-year period Another reason might be that reversed eVects of well-being on(perceived) support are speci c rather than global and that the support measureused in our study was not speci c enough to detect reversed eVects For exampleDaniels and Guppy (1997) found a diVerential pattern of associations betweenaspects of well-being and subsequent reported diVerent dimensions of socialsupport More speci cally they found eVects on help support and socialdependability but not on esteem support In a similar vein Marcelissen et al

40 Jan d e Jonge et al

(1988) found that strains aVected only support by co-workers and not by thesupervisor

The reversed association between emotional exhaustion and (perceived) jobdemands was found in earlier burnout studies For instance a two-wave panel studyamong health care professionals (3 monthsrsquo time interval) also showed that Time 1emotional exhaustion predicted Time 2 (perceived) work overload (Leiter amp Durup1996) In addition in a two-wave longitudinal study (10 monthsrsquo time interval)among teachers Shirom and Oliver (1986) found that burnout was a predictorrather than a consequence of (perceived) job demands

There are several reasons why one may expect that emotional exhaustion inparticular aVects (perceived) working conditions rather than job satisfaction andwork motivation First the drift hypothesis which is rather non-speci c insuggesting that any kind of poor health may cause bad working conditions byworkers drifting to a new and worse job does not apply because job changes wereexcluded from the present study Secondly perceived working conditions ratherthan objective ones were considered so that perceptual mechanisms are more likelyto apply than eVects of well-being on actual (objective) working conditionsThirdly the argument that people with poor aVective health recall more unfavour-able working conditions particularly applies to depression (Daniels amp Guppy1997) Among the variables investigated in the present study emotional exhaustionis most closely linked to depression as indicated by items such as lsquofeelingdepressedrsquo lsquofeeling hopelessrsquo and lsquofeeling worthlessrsquo Fourthly emotional exhaus-tion has been conceived as a general and comprehensive dimension of well-being(Enzmann et al 1998) Hence if emotional exhaustion or any other broadwell-being variable is included further health-related variables may have only weakadditional eVects on the perceptions of job conditions Therefore emotionalexhaustion may have stronger eVects on working conditions than job satisfactionand work motivation

Schaufeli and Enzmann (1998) however explained such reversed causal eVectsfrom burnout to (perceived) job characteristics from a methodological point ofview They stated that regression approaches to control statistically for the initialburnout scores may be inappropriate as a method to study predictors of changeespecially if the stability of burnout scores is high (which often seems to be thecase) Therefore they proposed promising alternative methods for the study ofchange such as growth curve modelling We did not apply this technique as morethan two waves are required for this approach

In conclusion the present results underline the importance of studyingreversed causal eVects in this kind of study (see also Zapf et al 1996) We believethat reversed eVects should always be conceived as a plausible alternativeexplanation for relations between (perceived) job characteristics and employeewell-being

The concept of negative aVectivity (NA) as a confounder of the associationbetween (perceived) job characteristics and job-related strain has been widelyinvestigated (for an overview see Spector Zapf Chen amp Frese 2000) There areimportant diverging reasons for assessing NA in job stress research First NA mayspuriously in ate the associations between the variables which have been measured

Job characteristics and psychological well-being reciprocal relationships 41

by self-report methods Secondly controlling for NA may also mean that variancein job-related strain that could be due to the work environment is removed with theNA measure In other words not controlling for NA could lead to an exaggerationof the job-strain association whereas controlling for NA in attempting to re nemethodology could lead to an underestimation of the relative importance of jobcharacteristics (Dollard amp Wine eld 1998)

Except for job autonomy and work motivation the present study showed thatNA was correlated with all job characteristics and psychological well-being In thestructural equation models however controlling for NA had no impact onjob-strain relationships There are at least three plausible interpretations of this nding First although measures used were self-reports job characteristicsmeasures have been operationalized in such a way that a certain degree ofobjectivity would be derived (cf Frese 1999 Frese amp Zapf 1988) Secondly ifperfect stability of NA is assumed NA need not be considered in panel studiesbecause its eVect is automatically partialled out if the structural equation modelis in a state of equilibrium (Spector et al 2000) Finally a number of studieshave found that NA is not (or weakly) associated with job satisfaction (egChen amp Spector 1991 Dormann amp Zapf 1998 Moyle 1995 Williams Gavinamp Williams 1996) Because the signi cant cross-lagged patterns were mainlyfound with regard to job satisfaction this study underlines the use of jobsatisfaction as an index of strain to help overcome the confounding eVectsproduced by NA

At least two remarks regarding the present study can be made First our data arecollected in discrete time samples while the processes to be observed arecontinuous Therefore we cannot obtain valid parameter estimates until themeasurement period matches the causal lag (Engel amp Meyer 1996 Frese amp Zapf1988) Moreover time mis-speci cations may lead to serious problems if the timelag is too short (Kessler amp Greenberg 1981) We have tried to estimate this periodby means of a pilot study (Vermaat 1994) but the only remedy seems to be theestimation of distributed lag models afterwards in multi-wave studies (Engel ampMeyer 1996) In contrast one could argue that discrete time approximations ofsuch continuous processes are in practice quite adequate since in some instanceschanges do not occur continuously but in distinct stages (Van der Kamp ampBijleveld 1998)

A second point involves the study population Studying people in just oneoccupation has advantages as well as disadvantages An advantage of a single-occupation group like health care professionals is that we had virtually no variancein socio-economic status which precludes confounding eVects The challenge ishowever to obtain enough variance on the variables of interest to allow hypothesistests Compared to large multi-occupation studies we might have some restrictionin range in our variables But health care professionals as an occupational grouphave the advantage of providing much natural variance because of diVerent types ofhealth care areas and because diVerent specialties exist within the same generalhospital or nursing home (Fox Dwyer amp Ganster 1993 Ganster amp Fusilier 1989)Nevertheless generalization of the current results to other occupations awaitsfurther empirical examination

42 Jan d e Jonge et al

In conclusion this study builds on earlier cross-sectional and longitudinal ndings by eliminating confounding factors and diminishing several methodologi-cal de ciencies Empirical support for the in uence of job characteristics onwork-related psychological well-being aYrms what several prominent theoreticalmodels have postulated to be the causal ordering among job characteristics andaVective responses to jobs (see Hackman amp Oldham 1980 Karasek amp Theorell1990 Siegrist 1998 Warr 1987) However this study does not invalidate theevidence that supports a reverse causal relationship (ie from psychologicalwell-being to (perceived) job characteristics) although this evidence is lessconclusive It may preliminarily indicate that (perceived) job characteristics andpyschological well-being in uence each other reciprocally rather than unidirection-ally (cf Edwards 1998) So there is a plea for studying more complex models ofthe job stress process including reciprocal relationships

Practically the present study indicated that job characteristics themselves arerelatively important predictors of employee well-being Worksite interventionsmdashdecreasing or stabilizing job demands and increasing social supportmdashare usefulstarting-points which could improve employee well-being

References

Anderson J C amp Gerbing D W (1988) Structural equation modeling in practice A review andrecommended two step approach Psychological Bulletin 103 411ndash423

Bateman T S amp Strasser S (1983) A cross-lagged regression test of the relationships between jobtension and employee satisfaction Journal of Applied Psychology 68 439ndash445

Bentler P M amp Bonett D G (1980) Signi cance tests and goodness of t in the analysis ofcovariance structures Psychological Bulletin 88 588ndash606

Bentler P M amp Chou C P (1987) Practical issues in structural modelling Sociological Methods andResearch 16 78ndash117

Bergers G P A Marcelissen F H G amp WolV Ch J de (1986) VOS-D VragenlijstOrganisatiestress-D handleid ing [VOS-D Work stress questionnaire Doetinchem] NijmegenUniversity of Nijmegen

Billings A G amp Moos R H (1982) Social support and functioning among community and clinicalgroups A panel model Journal of Behavioral Med icine 5 295ndash311

Bollen K A (1989) Structural equations with latent variables New York WileyBoumans N P G amp Landeweerd J A (1992) The role of social support and coping behaviour in

nursing work Main or buVering eVect Work and Stress 6 191ndash202Browne M W amp Cudeck R (1989) Single sample cross-validation indices for covariance structures

Multivariate Behavioral Research 24 445ndash455Browne M W amp Cudeck R (1993) Alternative ways of assessing model t In K A Bollen amp

J S Long (Eds) Testing structural equation models (pp 136ndash162) Newbury Park CA SageBurke M J Brief A P amp George J M (1993) The role of negative aVectivity in understanding

relations between self-reports of stressors and strains A comment on the applied psychologyliterature Journal of Applied Psychology 78 402ndash412

Caldwell D F amp OrsquoReilly C A (1982) Task perceptions and job satisfaction A question ofcausality Journal of Applied Psychology 67 361ndash391

Chen P Y amp Spector P E (1991) Negative aVectivity as the underlying cause of correlationsbetween stressors and strain Journal of Applied Psychology 76 398ndash407

Clark L A Watson D amp Mineka S (1994) Temperament personality and the mood and anxietydisorders Journal of Abnormal Psychology 103 103ndash116

Daniels K amp Guppy A (1997) Stressors locus of control and social support as consequences ofaVective psychological well-being Journal of Occupational Health Psychology 2 156ndash174

Job characteristics and psychological well-being reciprocal relationships 43

The rst chi-square diVerence test showed that the diVerence between thestability model and the model with cross-lagged eVects from job characteristics towell-being outcomes was signicant (M1 vs M2 D v 2(9) = 1701 p 05) Thismeans that the unconstrained model with lagged eVects (M2) better accounts forthe data than the constrained model with no lagged eVects (M1) In other wordsthere is statistical evidence that Time 1 job characteristics in uence Time 2psychological well-being

Alternatively a second chi-square diVerence test showed that the diVerencebetween the stability model and the model with cross-lagged structural paths fromTime 1 well-being to Time 2 (perceived) job characteristics was not signi cant (M1

vs M3 D v 2(9) = 1191 p = ns) Thus model M3 has no better statistical t thanmodel M1 Generally psychological well-being in Measurement 1 was not able toin uence (perceived) job characteristics in Measurement 2

The chi-square diVerence test between the stability model and the model with allcross-lagged structural paths was signi cant (M1 vs M4 D v 2(18) = 3037 p 05)However model t did not improve if reversed structural paths were added to theconventional paths (M2 vs M4 D v 2(9) = 1336 p = ns) On the contrary therewas a clear improvement in model t if usual structural paths were added to thereversed paths (M3 vs M4 D v 2(9) = 1846 p 05) Generally in terms ofchi-square relative to the degrees of freedom model M2 showed the best t of allcompeting models (see Table 2) Model M2 also had a relatively good t when themost important practical t indices were reviewed (ie GFI = 96 AGFI = 86RMSEA = 07 NNFI = 91 AIC = 24031 PNFI = 35 and CFI = 97) accordingto criteria presented by Hu and Bentler (1998) or by Schumacker and Lomax(1996) For instance in terms of model comparisons model M2 showed the bestcombination of NNFI and CFI In terms of parsimony model M2 showed thelowest AIC compared to the other lagged models (ie models M3 and M4) If onewere to take these t indices as the most important ones it would also lead to thepreference of model M2

Table 2 Goodness-of- t indices and chi-square diVerence tests of nested structuralmodels of psychological well-being

Model v 2 df Comparison D v 2 D df

No cross-lagged (M1) 9886 48Cross JCT1ndashPWT2 (M2) 8185 39 M1 vs M2 1701 9Cross PWT1ndashJCT2 (M3) 8695 39 M1 vs M3 1191 9Both cross (M4) 6849 30 M1 vs M4 3037 18

M2 vs M4 1336 9M3 vs M4 1846 9

p 05 p 001Note N=261Key JC=Job characteristics PW=Psychological well-being T1=Time 1 T2=Time 2

Job characteristics and psychological well-being reciprocal relationships 37

coeYcients of the best tting model (M2) It should be noted that the FIMLestimates have been standardized and that only signicant relationships betweenjob characteristics and psychological well-being and testndashretest stability coeYcientsare shown Regarding the signi cant cross-lagged parameters it appears that Time 1job demands in uence Time 2 job satisfaction Higher levels of Time 1 job demandscause lower levels of Time 2 job satisfaction Furthermore Time 1 workplace socialsupport in uences Time 2 job satisfaction as well that is higher levels of socialsupport lead to higher levels of job satisfaction Taken together both job demandsand social support appeared to be the causal factors

As mentioned before evidence exists that reciprocal relationships are presentsince the unconstrained model with both types of lagged eVects (M4) betteraccounts for the data than the constrained model with no lagged eVects (M1)However we also concluded that the chi-square diVerence test was mainly causedby the eVects of job characteristics on psychological well-being This means that ingeneral the reciprocal model can exist without reversed eVects but it cannot existwithout eVects of job characteristics on psychological well-being Referring toRogosarsquos (1980) statement again we tried to explore those reciprocal cross-laggedpatterns in addition to model M2 by examining the individual pathways Resultsfrom model M4 showed one additional cross-lagged eVect from Time 1 emotionalexhaustion to Time 2 (perceived) job demands (standardized path coeYcient11 p 05) This reversed structural path indicated that higher levels of Time 1emotional exhaustion seemed to in uence higher levels of (perceived) psycho-logical job demands at Time 2

Discussion

The main purpose of the present study was to test and evaluate the direction ofrelationships between job characteristics and employee psychological well-beingWe used a two-wave panel design which allowed more rigorous interpretation ofcausality and reciprocity than cross-sectional designs Additionally we tried toavoid the possible methodological pitfalls of standard statistical techniques bytesting cross-lagged structural equation models

The results primarily supported Hypothesis H1 such that after controlling forgender age and negative aVectivity job characteristics in uenced psychologicalwell-being More speci cally both job demands and workplace social supportappeared to be the causally dominant factors with regard to job satisfactionFurthermore there was also some preliminary but weak evidence for reversedcross-lagged eVects since emotional exhaustion seemed to be the causally dominantfactor with respect to (perceived) job demands

The present ndings are consistent with the scarce longitudinal studies in thisresearch area For instance James and Tetrick (1986) performed a two-stage leastsquares analysis of job characteristics and job satisfaction After comparing threealternative causal models they concluded that job characteristics appeared to be astronger cause of job satisfaction than vice versa

A closer inspection of the lagged relationships indicated additional support forjob characteristicsndashwell-being relationships as far as job demands and workplace

Job characteristics and psychological well-being reciprocal relationships 39

social support were concerned Both variables showed a lagged pattern of relationsimilar to cross-sectional ndings presented in the literature The nding thatpsychological job demands are negatively associated with job satisfaction wasreplicated in the present study (Spector 1997) Interestingly though we found alagged eVect which strengthens earlier cross-sectional ndings in health care work(eg De Jonge et al 1996 Landsbergis 1988 McLaney amp Hurrell 1988) Thelagged relationship between social support and job satisfaction seems to re ect thenature of work of nurses and nursesrsquo aides A key characteristic feature of their jobsis that workplace social support plays an important role in daily work because forthe most part nurses and nursesrsquo aides work closely together in teams (eg ShinnRosario Morch amp Chestnut 1984) This nding also underlines the assumptions ofthe DCS model concerning highly motivated and satis ed employees (Karasek ampTheorell 1990) It is therefore not surprising that this model has been expandedwith workplace social support as a key predictor (Johnson amp Hall 1988) Finallya number of empirical studies indicate that supportive relationships generallyenhance outcomes such as job satisfaction and work motivation (eg see Boumansamp Landeweerd 1992 Parkes et al 1994 Peeters 1994) In all these results provideadditional empirical evidence for these two job characteristics in the prediction ofemployee well-being

Conversely there was weak evidence for only one lagged reversed relationshipwith emotional exhaustion as a predictor for (perceived) psychological jobdemands This contradicts the research that does nd evidence of reversedcausation (eg Zapf et al 1996) Reasons for this can only be speculative Forinstance Daniels and Guppy (1997) found only a weak eVect of poor well-being forthe appraised stressfulness of job demands not their frequency This carries therisk that relationships between demands and well-being are aVected by self-reportor method variance (Wall Jackson Mullarkey amp Parker 1996) We tried to avoidevaluative components like intensity in the measurement of demands and useddescriptive as well as frequency-based measures instead (eg Frese amp Zapf 1988)and this might be a reason for lack of corroboration A similar way of reasoningcould be true for job autonomy to explain lack of reversed causation (eg De Jonge1995 Wall et al 1996)

Previous longitudinal studies that detected reversed eVects on (perceived) socialsupport covered either a very short time lag (eg Daniels amp Guppy 1997 Fisher1985) or longer time lags (Marcelissen Winnubst Buunk amp De WolV 1988)However a panel study by Billings and Moos (1982) which used a similar time lagas our study (ie one year) failed to demonstrate lagged eVects of psychologicalsymptoms on support It might be that in general the eVect of aspects of well-beingon (perceived) social support takes place within a few months rather than aone-year period Another reason might be that reversed eVects of well-being on(perceived) support are speci c rather than global and that the support measureused in our study was not speci c enough to detect reversed eVects For exampleDaniels and Guppy (1997) found a diVerential pattern of associations betweenaspects of well-being and subsequent reported diVerent dimensions of socialsupport More speci cally they found eVects on help support and socialdependability but not on esteem support In a similar vein Marcelissen et al

40 Jan d e Jonge et al

(1988) found that strains aVected only support by co-workers and not by thesupervisor

The reversed association between emotional exhaustion and (perceived) jobdemands was found in earlier burnout studies For instance a two-wave panel studyamong health care professionals (3 monthsrsquo time interval) also showed that Time 1emotional exhaustion predicted Time 2 (perceived) work overload (Leiter amp Durup1996) In addition in a two-wave longitudinal study (10 monthsrsquo time interval)among teachers Shirom and Oliver (1986) found that burnout was a predictorrather than a consequence of (perceived) job demands

There are several reasons why one may expect that emotional exhaustion inparticular aVects (perceived) working conditions rather than job satisfaction andwork motivation First the drift hypothesis which is rather non-speci c insuggesting that any kind of poor health may cause bad working conditions byworkers drifting to a new and worse job does not apply because job changes wereexcluded from the present study Secondly perceived working conditions ratherthan objective ones were considered so that perceptual mechanisms are more likelyto apply than eVects of well-being on actual (objective) working conditionsThirdly the argument that people with poor aVective health recall more unfavour-able working conditions particularly applies to depression (Daniels amp Guppy1997) Among the variables investigated in the present study emotional exhaustionis most closely linked to depression as indicated by items such as lsquofeelingdepressedrsquo lsquofeeling hopelessrsquo and lsquofeeling worthlessrsquo Fourthly emotional exhaus-tion has been conceived as a general and comprehensive dimension of well-being(Enzmann et al 1998) Hence if emotional exhaustion or any other broadwell-being variable is included further health-related variables may have only weakadditional eVects on the perceptions of job conditions Therefore emotionalexhaustion may have stronger eVects on working conditions than job satisfactionand work motivation

Schaufeli and Enzmann (1998) however explained such reversed causal eVectsfrom burnout to (perceived) job characteristics from a methodological point ofview They stated that regression approaches to control statistically for the initialburnout scores may be inappropriate as a method to study predictors of changeespecially if the stability of burnout scores is high (which often seems to be thecase) Therefore they proposed promising alternative methods for the study ofchange such as growth curve modelling We did not apply this technique as morethan two waves are required for this approach

In conclusion the present results underline the importance of studyingreversed causal eVects in this kind of study (see also Zapf et al 1996) We believethat reversed eVects should always be conceived as a plausible alternativeexplanation for relations between (perceived) job characteristics and employeewell-being

The concept of negative aVectivity (NA) as a confounder of the associationbetween (perceived) job characteristics and job-related strain has been widelyinvestigated (for an overview see Spector Zapf Chen amp Frese 2000) There areimportant diverging reasons for assessing NA in job stress research First NA mayspuriously in ate the associations between the variables which have been measured

Job characteristics and psychological well-being reciprocal relationships 41

by self-report methods Secondly controlling for NA may also mean that variancein job-related strain that could be due to the work environment is removed with theNA measure In other words not controlling for NA could lead to an exaggerationof the job-strain association whereas controlling for NA in attempting to re nemethodology could lead to an underestimation of the relative importance of jobcharacteristics (Dollard amp Wine eld 1998)

Except for job autonomy and work motivation the present study showed thatNA was correlated with all job characteristics and psychological well-being In thestructural equation models however controlling for NA had no impact onjob-strain relationships There are at least three plausible interpretations of this nding First although measures used were self-reports job characteristicsmeasures have been operationalized in such a way that a certain degree ofobjectivity would be derived (cf Frese 1999 Frese amp Zapf 1988) Secondly ifperfect stability of NA is assumed NA need not be considered in panel studiesbecause its eVect is automatically partialled out if the structural equation modelis in a state of equilibrium (Spector et al 2000) Finally a number of studieshave found that NA is not (or weakly) associated with job satisfaction (egChen amp Spector 1991 Dormann amp Zapf 1998 Moyle 1995 Williams Gavinamp Williams 1996) Because the signi cant cross-lagged patterns were mainlyfound with regard to job satisfaction this study underlines the use of jobsatisfaction as an index of strain to help overcome the confounding eVectsproduced by NA

At least two remarks regarding the present study can be made First our data arecollected in discrete time samples while the processes to be observed arecontinuous Therefore we cannot obtain valid parameter estimates until themeasurement period matches the causal lag (Engel amp Meyer 1996 Frese amp Zapf1988) Moreover time mis-speci cations may lead to serious problems if the timelag is too short (Kessler amp Greenberg 1981) We have tried to estimate this periodby means of a pilot study (Vermaat 1994) but the only remedy seems to be theestimation of distributed lag models afterwards in multi-wave studies (Engel ampMeyer 1996) In contrast one could argue that discrete time approximations ofsuch continuous processes are in practice quite adequate since in some instanceschanges do not occur continuously but in distinct stages (Van der Kamp ampBijleveld 1998)

A second point involves the study population Studying people in just oneoccupation has advantages as well as disadvantages An advantage of a single-occupation group like health care professionals is that we had virtually no variancein socio-economic status which precludes confounding eVects The challenge ishowever to obtain enough variance on the variables of interest to allow hypothesistests Compared to large multi-occupation studies we might have some restrictionin range in our variables But health care professionals as an occupational grouphave the advantage of providing much natural variance because of diVerent types ofhealth care areas and because diVerent specialties exist within the same generalhospital or nursing home (Fox Dwyer amp Ganster 1993 Ganster amp Fusilier 1989)Nevertheless generalization of the current results to other occupations awaitsfurther empirical examination

42 Jan d e Jonge et al

In conclusion this study builds on earlier cross-sectional and longitudinal ndings by eliminating confounding factors and diminishing several methodologi-cal de ciencies Empirical support for the in uence of job characteristics onwork-related psychological well-being aYrms what several prominent theoreticalmodels have postulated to be the causal ordering among job characteristics andaVective responses to jobs (see Hackman amp Oldham 1980 Karasek amp Theorell1990 Siegrist 1998 Warr 1987) However this study does not invalidate theevidence that supports a reverse causal relationship (ie from psychologicalwell-being to (perceived) job characteristics) although this evidence is lessconclusive It may preliminarily indicate that (perceived) job characteristics andpyschological well-being in uence each other reciprocally rather than unidirection-ally (cf Edwards 1998) So there is a plea for studying more complex models ofthe job stress process including reciprocal relationships

Practically the present study indicated that job characteristics themselves arerelatively important predictors of employee well-being Worksite interventionsmdashdecreasing or stabilizing job demands and increasing social supportmdashare usefulstarting-points which could improve employee well-being

References

Anderson J C amp Gerbing D W (1988) Structural equation modeling in practice A review andrecommended two step approach Psychological Bulletin 103 411ndash423

Bateman T S amp Strasser S (1983) A cross-lagged regression test of the relationships between jobtension and employee satisfaction Journal of Applied Psychology 68 439ndash445

Bentler P M amp Bonett D G (1980) Signi cance tests and goodness of t in the analysis ofcovariance structures Psychological Bulletin 88 588ndash606

Bentler P M amp Chou C P (1987) Practical issues in structural modelling Sociological Methods andResearch 16 78ndash117

Bergers G P A Marcelissen F H G amp WolV Ch J de (1986) VOS-D VragenlijstOrganisatiestress-D handleid ing [VOS-D Work stress questionnaire Doetinchem] NijmegenUniversity of Nijmegen

Billings A G amp Moos R H (1982) Social support and functioning among community and clinicalgroups A panel model Journal of Behavioral Med icine 5 295ndash311

Bollen K A (1989) Structural equations with latent variables New York WileyBoumans N P G amp Landeweerd J A (1992) The role of social support and coping behaviour in

nursing work Main or buVering eVect Work and Stress 6 191ndash202Browne M W amp Cudeck R (1989) Single sample cross-validation indices for covariance structures

Multivariate Behavioral Research 24 445ndash455Browne M W amp Cudeck R (1993) Alternative ways of assessing model t In K A Bollen amp

J S Long (Eds) Testing structural equation models (pp 136ndash162) Newbury Park CA SageBurke M J Brief A P amp George J M (1993) The role of negative aVectivity in understanding

relations between self-reports of stressors and strains A comment on the applied psychologyliterature Journal of Applied Psychology 78 402ndash412

Caldwell D F amp OrsquoReilly C A (1982) Task perceptions and job satisfaction A question ofcausality Journal of Applied Psychology 67 361ndash391

Chen P Y amp Spector P E (1991) Negative aVectivity as the underlying cause of correlationsbetween stressors and strain Journal of Applied Psychology 76 398ndash407

Clark L A Watson D amp Mineka S (1994) Temperament personality and the mood and anxietydisorders Journal of Abnormal Psychology 103 103ndash116

Daniels K amp Guppy A (1997) Stressors locus of control and social support as consequences ofaVective psychological well-being Journal of Occupational Health Psychology 2 156ndash174

Job characteristics and psychological well-being reciprocal relationships 43

coeYcients of the best tting model (M2) It should be noted that the FIMLestimates have been standardized and that only signicant relationships betweenjob characteristics and psychological well-being and testndashretest stability coeYcientsare shown Regarding the signi cant cross-lagged parameters it appears that Time 1job demands in uence Time 2 job satisfaction Higher levels of Time 1 job demandscause lower levels of Time 2 job satisfaction Furthermore Time 1 workplace socialsupport in uences Time 2 job satisfaction as well that is higher levels of socialsupport lead to higher levels of job satisfaction Taken together both job demandsand social support appeared to be the causal factors

As mentioned before evidence exists that reciprocal relationships are presentsince the unconstrained model with both types of lagged eVects (M4) betteraccounts for the data than the constrained model with no lagged eVects (M1)However we also concluded that the chi-square diVerence test was mainly causedby the eVects of job characteristics on psychological well-being This means that ingeneral the reciprocal model can exist without reversed eVects but it cannot existwithout eVects of job characteristics on psychological well-being Referring toRogosarsquos (1980) statement again we tried to explore those reciprocal cross-laggedpatterns in addition to model M2 by examining the individual pathways Resultsfrom model M4 showed one additional cross-lagged eVect from Time 1 emotionalexhaustion to Time 2 (perceived) job demands (standardized path coeYcient11 p 05) This reversed structural path indicated that higher levels of Time 1emotional exhaustion seemed to in uence higher levels of (perceived) psycho-logical job demands at Time 2

Discussion

The main purpose of the present study was to test and evaluate the direction ofrelationships between job characteristics and employee psychological well-beingWe used a two-wave panel design which allowed more rigorous interpretation ofcausality and reciprocity than cross-sectional designs Additionally we tried toavoid the possible methodological pitfalls of standard statistical techniques bytesting cross-lagged structural equation models

The results primarily supported Hypothesis H1 such that after controlling forgender age and negative aVectivity job characteristics in uenced psychologicalwell-being More speci cally both job demands and workplace social supportappeared to be the causally dominant factors with regard to job satisfactionFurthermore there was also some preliminary but weak evidence for reversedcross-lagged eVects since emotional exhaustion seemed to be the causally dominantfactor with respect to (perceived) job demands

The present ndings are consistent with the scarce longitudinal studies in thisresearch area For instance James and Tetrick (1986) performed a two-stage leastsquares analysis of job characteristics and job satisfaction After comparing threealternative causal models they concluded that job characteristics appeared to be astronger cause of job satisfaction than vice versa

A closer inspection of the lagged relationships indicated additional support forjob characteristicsndashwell-being relationships as far as job demands and workplace

Job characteristics and psychological well-being reciprocal relationships 39

social support were concerned Both variables showed a lagged pattern of relationsimilar to cross-sectional ndings presented in the literature The nding thatpsychological job demands are negatively associated with job satisfaction wasreplicated in the present study (Spector 1997) Interestingly though we found alagged eVect which strengthens earlier cross-sectional ndings in health care work(eg De Jonge et al 1996 Landsbergis 1988 McLaney amp Hurrell 1988) Thelagged relationship between social support and job satisfaction seems to re ect thenature of work of nurses and nursesrsquo aides A key characteristic feature of their jobsis that workplace social support plays an important role in daily work because forthe most part nurses and nursesrsquo aides work closely together in teams (eg ShinnRosario Morch amp Chestnut 1984) This nding also underlines the assumptions ofthe DCS model concerning highly motivated and satis ed employees (Karasek ampTheorell 1990) It is therefore not surprising that this model has been expandedwith workplace social support as a key predictor (Johnson amp Hall 1988) Finallya number of empirical studies indicate that supportive relationships generallyenhance outcomes such as job satisfaction and work motivation (eg see Boumansamp Landeweerd 1992 Parkes et al 1994 Peeters 1994) In all these results provideadditional empirical evidence for these two job characteristics in the prediction ofemployee well-being

Conversely there was weak evidence for only one lagged reversed relationshipwith emotional exhaustion as a predictor for (perceived) psychological jobdemands This contradicts the research that does nd evidence of reversedcausation (eg Zapf et al 1996) Reasons for this can only be speculative Forinstance Daniels and Guppy (1997) found only a weak eVect of poor well-being forthe appraised stressfulness of job demands not their frequency This carries therisk that relationships between demands and well-being are aVected by self-reportor method variance (Wall Jackson Mullarkey amp Parker 1996) We tried to avoidevaluative components like intensity in the measurement of demands and useddescriptive as well as frequency-based measures instead (eg Frese amp Zapf 1988)and this might be a reason for lack of corroboration A similar way of reasoningcould be true for job autonomy to explain lack of reversed causation (eg De Jonge1995 Wall et al 1996)

Previous longitudinal studies that detected reversed eVects on (perceived) socialsupport covered either a very short time lag (eg Daniels amp Guppy 1997 Fisher1985) or longer time lags (Marcelissen Winnubst Buunk amp De WolV 1988)However a panel study by Billings and Moos (1982) which used a similar time lagas our study (ie one year) failed to demonstrate lagged eVects of psychologicalsymptoms on support It might be that in general the eVect of aspects of well-beingon (perceived) social support takes place within a few months rather than aone-year period Another reason might be that reversed eVects of well-being on(perceived) support are speci c rather than global and that the support measureused in our study was not speci c enough to detect reversed eVects For exampleDaniels and Guppy (1997) found a diVerential pattern of associations betweenaspects of well-being and subsequent reported diVerent dimensions of socialsupport More speci cally they found eVects on help support and socialdependability but not on esteem support In a similar vein Marcelissen et al

40 Jan d e Jonge et al

(1988) found that strains aVected only support by co-workers and not by thesupervisor

The reversed association between emotional exhaustion and (perceived) jobdemands was found in earlier burnout studies For instance a two-wave panel studyamong health care professionals (3 monthsrsquo time interval) also showed that Time 1emotional exhaustion predicted Time 2 (perceived) work overload (Leiter amp Durup1996) In addition in a two-wave longitudinal study (10 monthsrsquo time interval)among teachers Shirom and Oliver (1986) found that burnout was a predictorrather than a consequence of (perceived) job demands

There are several reasons why one may expect that emotional exhaustion inparticular aVects (perceived) working conditions rather than job satisfaction andwork motivation First the drift hypothesis which is rather non-speci c insuggesting that any kind of poor health may cause bad working conditions byworkers drifting to a new and worse job does not apply because job changes wereexcluded from the present study Secondly perceived working conditions ratherthan objective ones were considered so that perceptual mechanisms are more likelyto apply than eVects of well-being on actual (objective) working conditionsThirdly the argument that people with poor aVective health recall more unfavour-able working conditions particularly applies to depression (Daniels amp Guppy1997) Among the variables investigated in the present study emotional exhaustionis most closely linked to depression as indicated by items such as lsquofeelingdepressedrsquo lsquofeeling hopelessrsquo and lsquofeeling worthlessrsquo Fourthly emotional exhaus-tion has been conceived as a general and comprehensive dimension of well-being(Enzmann et al 1998) Hence if emotional exhaustion or any other broadwell-being variable is included further health-related variables may have only weakadditional eVects on the perceptions of job conditions Therefore emotionalexhaustion may have stronger eVects on working conditions than job satisfactionand work motivation

Schaufeli and Enzmann (1998) however explained such reversed causal eVectsfrom burnout to (perceived) job characteristics from a methodological point ofview They stated that regression approaches to control statistically for the initialburnout scores may be inappropriate as a method to study predictors of changeespecially if the stability of burnout scores is high (which often seems to be thecase) Therefore they proposed promising alternative methods for the study ofchange such as growth curve modelling We did not apply this technique as morethan two waves are required for this approach

In conclusion the present results underline the importance of studyingreversed causal eVects in this kind of study (see also Zapf et al 1996) We believethat reversed eVects should always be conceived as a plausible alternativeexplanation for relations between (perceived) job characteristics and employeewell-being

The concept of negative aVectivity (NA) as a confounder of the associationbetween (perceived) job characteristics and job-related strain has been widelyinvestigated (for an overview see Spector Zapf Chen amp Frese 2000) There areimportant diverging reasons for assessing NA in job stress research First NA mayspuriously in ate the associations between the variables which have been measured

Job characteristics and psychological well-being reciprocal relationships 41

by self-report methods Secondly controlling for NA may also mean that variancein job-related strain that could be due to the work environment is removed with theNA measure In other words not controlling for NA could lead to an exaggerationof the job-strain association whereas controlling for NA in attempting to re nemethodology could lead to an underestimation of the relative importance of jobcharacteristics (Dollard amp Wine eld 1998)

Except for job autonomy and work motivation the present study showed thatNA was correlated with all job characteristics and psychological well-being In thestructural equation models however controlling for NA had no impact onjob-strain relationships There are at least three plausible interpretations of this nding First although measures used were self-reports job characteristicsmeasures have been operationalized in such a way that a certain degree ofobjectivity would be derived (cf Frese 1999 Frese amp Zapf 1988) Secondly ifperfect stability of NA is assumed NA need not be considered in panel studiesbecause its eVect is automatically partialled out if the structural equation modelis in a state of equilibrium (Spector et al 2000) Finally a number of studieshave found that NA is not (or weakly) associated with job satisfaction (egChen amp Spector 1991 Dormann amp Zapf 1998 Moyle 1995 Williams Gavinamp Williams 1996) Because the signi cant cross-lagged patterns were mainlyfound with regard to job satisfaction this study underlines the use of jobsatisfaction as an index of strain to help overcome the confounding eVectsproduced by NA

At least two remarks regarding the present study can be made First our data arecollected in discrete time samples while the processes to be observed arecontinuous Therefore we cannot obtain valid parameter estimates until themeasurement period matches the causal lag (Engel amp Meyer 1996 Frese amp Zapf1988) Moreover time mis-speci cations may lead to serious problems if the timelag is too short (Kessler amp Greenberg 1981) We have tried to estimate this periodby means of a pilot study (Vermaat 1994) but the only remedy seems to be theestimation of distributed lag models afterwards in multi-wave studies (Engel ampMeyer 1996) In contrast one could argue that discrete time approximations ofsuch continuous processes are in practice quite adequate since in some instanceschanges do not occur continuously but in distinct stages (Van der Kamp ampBijleveld 1998)

A second point involves the study population Studying people in just oneoccupation has advantages as well as disadvantages An advantage of a single-occupation group like health care professionals is that we had virtually no variancein socio-economic status which precludes confounding eVects The challenge ishowever to obtain enough variance on the variables of interest to allow hypothesistests Compared to large multi-occupation studies we might have some restrictionin range in our variables But health care professionals as an occupational grouphave the advantage of providing much natural variance because of diVerent types ofhealth care areas and because diVerent specialties exist within the same generalhospital or nursing home (Fox Dwyer amp Ganster 1993 Ganster amp Fusilier 1989)Nevertheless generalization of the current results to other occupations awaitsfurther empirical examination

42 Jan d e Jonge et al

In conclusion this study builds on earlier cross-sectional and longitudinal ndings by eliminating confounding factors and diminishing several methodologi-cal de ciencies Empirical support for the in uence of job characteristics onwork-related psychological well-being aYrms what several prominent theoreticalmodels have postulated to be the causal ordering among job characteristics andaVective responses to jobs (see Hackman amp Oldham 1980 Karasek amp Theorell1990 Siegrist 1998 Warr 1987) However this study does not invalidate theevidence that supports a reverse causal relationship (ie from psychologicalwell-being to (perceived) job characteristics) although this evidence is lessconclusive It may preliminarily indicate that (perceived) job characteristics andpyschological well-being in uence each other reciprocally rather than unidirection-ally (cf Edwards 1998) So there is a plea for studying more complex models ofthe job stress process including reciprocal relationships

Practically the present study indicated that job characteristics themselves arerelatively important predictors of employee well-being Worksite interventionsmdashdecreasing or stabilizing job demands and increasing social supportmdashare usefulstarting-points which could improve employee well-being

References

Anderson J C amp Gerbing D W (1988) Structural equation modeling in practice A review andrecommended two step approach Psychological Bulletin 103 411ndash423

Bateman T S amp Strasser S (1983) A cross-lagged regression test of the relationships between jobtension and employee satisfaction Journal of Applied Psychology 68 439ndash445

Bentler P M amp Bonett D G (1980) Signi cance tests and goodness of t in the analysis ofcovariance structures Psychological Bulletin 88 588ndash606

Bentler P M amp Chou C P (1987) Practical issues in structural modelling Sociological Methods andResearch 16 78ndash117

Bergers G P A Marcelissen F H G amp WolV Ch J de (1986) VOS-D VragenlijstOrganisatiestress-D handleid ing [VOS-D Work stress questionnaire Doetinchem] NijmegenUniversity of Nijmegen

Billings A G amp Moos R H (1982) Social support and functioning among community and clinicalgroups A panel model Journal of Behavioral Med icine 5 295ndash311

Bollen K A (1989) Structural equations with latent variables New York WileyBoumans N P G amp Landeweerd J A (1992) The role of social support and coping behaviour in

nursing work Main or buVering eVect Work and Stress 6 191ndash202Browne M W amp Cudeck R (1989) Single sample cross-validation indices for covariance structures

Multivariate Behavioral Research 24 445ndash455Browne M W amp Cudeck R (1993) Alternative ways of assessing model t In K A Bollen amp

J S Long (Eds) Testing structural equation models (pp 136ndash162) Newbury Park CA SageBurke M J Brief A P amp George J M (1993) The role of negative aVectivity in understanding

relations between self-reports of stressors and strains A comment on the applied psychologyliterature Journal of Applied Psychology 78 402ndash412

Caldwell D F amp OrsquoReilly C A (1982) Task perceptions and job satisfaction A question ofcausality Journal of Applied Psychology 67 361ndash391

Chen P Y amp Spector P E (1991) Negative aVectivity as the underlying cause of correlationsbetween stressors and strain Journal of Applied Psychology 76 398ndash407

Clark L A Watson D amp Mineka S (1994) Temperament personality and the mood and anxietydisorders Journal of Abnormal Psychology 103 103ndash116

Daniels K amp Guppy A (1997) Stressors locus of control and social support as consequences ofaVective psychological well-being Journal of Occupational Health Psychology 2 156ndash174

Job characteristics and psychological well-being reciprocal relationships 43

social support were concerned Both variables showed a lagged pattern of relationsimilar to cross-sectional ndings presented in the literature The nding thatpsychological job demands are negatively associated with job satisfaction wasreplicated in the present study (Spector 1997) Interestingly though we found alagged eVect which strengthens earlier cross-sectional ndings in health care work(eg De Jonge et al 1996 Landsbergis 1988 McLaney amp Hurrell 1988) Thelagged relationship between social support and job satisfaction seems to re ect thenature of work of nurses and nursesrsquo aides A key characteristic feature of their jobsis that workplace social support plays an important role in daily work because forthe most part nurses and nursesrsquo aides work closely together in teams (eg ShinnRosario Morch amp Chestnut 1984) This nding also underlines the assumptions ofthe DCS model concerning highly motivated and satis ed employees (Karasek ampTheorell 1990) It is therefore not surprising that this model has been expandedwith workplace social support as a key predictor (Johnson amp Hall 1988) Finallya number of empirical studies indicate that supportive relationships generallyenhance outcomes such as job satisfaction and work motivation (eg see Boumansamp Landeweerd 1992 Parkes et al 1994 Peeters 1994) In all these results provideadditional empirical evidence for these two job characteristics in the prediction ofemployee well-being

Conversely there was weak evidence for only one lagged reversed relationshipwith emotional exhaustion as a predictor for (perceived) psychological jobdemands This contradicts the research that does nd evidence of reversedcausation (eg Zapf et al 1996) Reasons for this can only be speculative Forinstance Daniels and Guppy (1997) found only a weak eVect of poor well-being forthe appraised stressfulness of job demands not their frequency This carries therisk that relationships between demands and well-being are aVected by self-reportor method variance (Wall Jackson Mullarkey amp Parker 1996) We tried to avoidevaluative components like intensity in the measurement of demands and useddescriptive as well as frequency-based measures instead (eg Frese amp Zapf 1988)and this might be a reason for lack of corroboration A similar way of reasoningcould be true for job autonomy to explain lack of reversed causation (eg De Jonge1995 Wall et al 1996)

Previous longitudinal studies that detected reversed eVects on (perceived) socialsupport covered either a very short time lag (eg Daniels amp Guppy 1997 Fisher1985) or longer time lags (Marcelissen Winnubst Buunk amp De WolV 1988)However a panel study by Billings and Moos (1982) which used a similar time lagas our study (ie one year) failed to demonstrate lagged eVects of psychologicalsymptoms on support It might be that in general the eVect of aspects of well-beingon (perceived) social support takes place within a few months rather than aone-year period Another reason might be that reversed eVects of well-being on(perceived) support are speci c rather than global and that the support measureused in our study was not speci c enough to detect reversed eVects For exampleDaniels and Guppy (1997) found a diVerential pattern of associations betweenaspects of well-being and subsequent reported diVerent dimensions of socialsupport More speci cally they found eVects on help support and socialdependability but not on esteem support In a similar vein Marcelissen et al

40 Jan d e Jonge et al

(1988) found that strains aVected only support by co-workers and not by thesupervisor

The reversed association between emotional exhaustion and (perceived) jobdemands was found in earlier burnout studies For instance a two-wave panel studyamong health care professionals (3 monthsrsquo time interval) also showed that Time 1emotional exhaustion predicted Time 2 (perceived) work overload (Leiter amp Durup1996) In addition in a two-wave longitudinal study (10 monthsrsquo time interval)among teachers Shirom and Oliver (1986) found that burnout was a predictorrather than a consequence of (perceived) job demands

There are several reasons why one may expect that emotional exhaustion inparticular aVects (perceived) working conditions rather than job satisfaction andwork motivation First the drift hypothesis which is rather non-speci c insuggesting that any kind of poor health may cause bad working conditions byworkers drifting to a new and worse job does not apply because job changes wereexcluded from the present study Secondly perceived working conditions ratherthan objective ones were considered so that perceptual mechanisms are more likelyto apply than eVects of well-being on actual (objective) working conditionsThirdly the argument that people with poor aVective health recall more unfavour-able working conditions particularly applies to depression (Daniels amp Guppy1997) Among the variables investigated in the present study emotional exhaustionis most closely linked to depression as indicated by items such as lsquofeelingdepressedrsquo lsquofeeling hopelessrsquo and lsquofeeling worthlessrsquo Fourthly emotional exhaus-tion has been conceived as a general and comprehensive dimension of well-being(Enzmann et al 1998) Hence if emotional exhaustion or any other broadwell-being variable is included further health-related variables may have only weakadditional eVects on the perceptions of job conditions Therefore emotionalexhaustion may have stronger eVects on working conditions than job satisfactionand work motivation

Schaufeli and Enzmann (1998) however explained such reversed causal eVectsfrom burnout to (perceived) job characteristics from a methodological point ofview They stated that regression approaches to control statistically for the initialburnout scores may be inappropriate as a method to study predictors of changeespecially if the stability of burnout scores is high (which often seems to be thecase) Therefore they proposed promising alternative methods for the study ofchange such as growth curve modelling We did not apply this technique as morethan two waves are required for this approach

In conclusion the present results underline the importance of studyingreversed causal eVects in this kind of study (see also Zapf et al 1996) We believethat reversed eVects should always be conceived as a plausible alternativeexplanation for relations between (perceived) job characteristics and employeewell-being

The concept of negative aVectivity (NA) as a confounder of the associationbetween (perceived) job characteristics and job-related strain has been widelyinvestigated (for an overview see Spector Zapf Chen amp Frese 2000) There areimportant diverging reasons for assessing NA in job stress research First NA mayspuriously in ate the associations between the variables which have been measured

Job characteristics and psychological well-being reciprocal relationships 41

by self-report methods Secondly controlling for NA may also mean that variancein job-related strain that could be due to the work environment is removed with theNA measure In other words not controlling for NA could lead to an exaggerationof the job-strain association whereas controlling for NA in attempting to re nemethodology could lead to an underestimation of the relative importance of jobcharacteristics (Dollard amp Wine eld 1998)

Except for job autonomy and work motivation the present study showed thatNA was correlated with all job characteristics and psychological well-being In thestructural equation models however controlling for NA had no impact onjob-strain relationships There are at least three plausible interpretations of this nding First although measures used were self-reports job characteristicsmeasures have been operationalized in such a way that a certain degree ofobjectivity would be derived (cf Frese 1999 Frese amp Zapf 1988) Secondly ifperfect stability of NA is assumed NA need not be considered in panel studiesbecause its eVect is automatically partialled out if the structural equation modelis in a state of equilibrium (Spector et al 2000) Finally a number of studieshave found that NA is not (or weakly) associated with job satisfaction (egChen amp Spector 1991 Dormann amp Zapf 1998 Moyle 1995 Williams Gavinamp Williams 1996) Because the signi cant cross-lagged patterns were mainlyfound with regard to job satisfaction this study underlines the use of jobsatisfaction as an index of strain to help overcome the confounding eVectsproduced by NA

At least two remarks regarding the present study can be made First our data arecollected in discrete time samples while the processes to be observed arecontinuous Therefore we cannot obtain valid parameter estimates until themeasurement period matches the causal lag (Engel amp Meyer 1996 Frese amp Zapf1988) Moreover time mis-speci cations may lead to serious problems if the timelag is too short (Kessler amp Greenberg 1981) We have tried to estimate this periodby means of a pilot study (Vermaat 1994) but the only remedy seems to be theestimation of distributed lag models afterwards in multi-wave studies (Engel ampMeyer 1996) In contrast one could argue that discrete time approximations ofsuch continuous processes are in practice quite adequate since in some instanceschanges do not occur continuously but in distinct stages (Van der Kamp ampBijleveld 1998)

A second point involves the study population Studying people in just oneoccupation has advantages as well as disadvantages An advantage of a single-occupation group like health care professionals is that we had virtually no variancein socio-economic status which precludes confounding eVects The challenge ishowever to obtain enough variance on the variables of interest to allow hypothesistests Compared to large multi-occupation studies we might have some restrictionin range in our variables But health care professionals as an occupational grouphave the advantage of providing much natural variance because of diVerent types ofhealth care areas and because diVerent specialties exist within the same generalhospital or nursing home (Fox Dwyer amp Ganster 1993 Ganster amp Fusilier 1989)Nevertheless generalization of the current results to other occupations awaitsfurther empirical examination

42 Jan d e Jonge et al

In conclusion this study builds on earlier cross-sectional and longitudinal ndings by eliminating confounding factors and diminishing several methodologi-cal de ciencies Empirical support for the in uence of job characteristics onwork-related psychological well-being aYrms what several prominent theoreticalmodels have postulated to be the causal ordering among job characteristics andaVective responses to jobs (see Hackman amp Oldham 1980 Karasek amp Theorell1990 Siegrist 1998 Warr 1987) However this study does not invalidate theevidence that supports a reverse causal relationship (ie from psychologicalwell-being to (perceived) job characteristics) although this evidence is lessconclusive It may preliminarily indicate that (perceived) job characteristics andpyschological well-being in uence each other reciprocally rather than unidirection-ally (cf Edwards 1998) So there is a plea for studying more complex models ofthe job stress process including reciprocal relationships

Practically the present study indicated that job characteristics themselves arerelatively important predictors of employee well-being Worksite interventionsmdashdecreasing or stabilizing job demands and increasing social supportmdashare usefulstarting-points which could improve employee well-being

References

Anderson J C amp Gerbing D W (1988) Structural equation modeling in practice A review andrecommended two step approach Psychological Bulletin 103 411ndash423

Bateman T S amp Strasser S (1983) A cross-lagged regression test of the relationships between jobtension and employee satisfaction Journal of Applied Psychology 68 439ndash445

Bentler P M amp Bonett D G (1980) Signi cance tests and goodness of t in the analysis ofcovariance structures Psychological Bulletin 88 588ndash606

Bentler P M amp Chou C P (1987) Practical issues in structural modelling Sociological Methods andResearch 16 78ndash117

Bergers G P A Marcelissen F H G amp WolV Ch J de (1986) VOS-D VragenlijstOrganisatiestress-D handleid ing [VOS-D Work stress questionnaire Doetinchem] NijmegenUniversity of Nijmegen

Billings A G amp Moos R H (1982) Social support and functioning among community and clinicalgroups A panel model Journal of Behavioral Med icine 5 295ndash311

Bollen K A (1989) Structural equations with latent variables New York WileyBoumans N P G amp Landeweerd J A (1992) The role of social support and coping behaviour in

nursing work Main or buVering eVect Work and Stress 6 191ndash202Browne M W amp Cudeck R (1989) Single sample cross-validation indices for covariance structures

Multivariate Behavioral Research 24 445ndash455Browne M W amp Cudeck R (1993) Alternative ways of assessing model t In K A Bollen amp

J S Long (Eds) Testing structural equation models (pp 136ndash162) Newbury Park CA SageBurke M J Brief A P amp George J M (1993) The role of negative aVectivity in understanding

relations between self-reports of stressors and strains A comment on the applied psychologyliterature Journal of Applied Psychology 78 402ndash412

Caldwell D F amp OrsquoReilly C A (1982) Task perceptions and job satisfaction A question ofcausality Journal of Applied Psychology 67 361ndash391

Chen P Y amp Spector P E (1991) Negative aVectivity as the underlying cause of correlationsbetween stressors and strain Journal of Applied Psychology 76 398ndash407

Clark L A Watson D amp Mineka S (1994) Temperament personality and the mood and anxietydisorders Journal of Abnormal Psychology 103 103ndash116

Daniels K amp Guppy A (1997) Stressors locus of control and social support as consequences ofaVective psychological well-being Journal of Occupational Health Psychology 2 156ndash174

Job characteristics and psychological well-being reciprocal relationships 43

(1988) found that strains aVected only support by co-workers and not by thesupervisor

The reversed association between emotional exhaustion and (perceived) jobdemands was found in earlier burnout studies For instance a two-wave panel studyamong health care professionals (3 monthsrsquo time interval) also showed that Time 1emotional exhaustion predicted Time 2 (perceived) work overload (Leiter amp Durup1996) In addition in a two-wave longitudinal study (10 monthsrsquo time interval)among teachers Shirom and Oliver (1986) found that burnout was a predictorrather than a consequence of (perceived) job demands

There are several reasons why one may expect that emotional exhaustion inparticular aVects (perceived) working conditions rather than job satisfaction andwork motivation First the drift hypothesis which is rather non-speci c insuggesting that any kind of poor health may cause bad working conditions byworkers drifting to a new and worse job does not apply because job changes wereexcluded from the present study Secondly perceived working conditions ratherthan objective ones were considered so that perceptual mechanisms are more likelyto apply than eVects of well-being on actual (objective) working conditionsThirdly the argument that people with poor aVective health recall more unfavour-able working conditions particularly applies to depression (Daniels amp Guppy1997) Among the variables investigated in the present study emotional exhaustionis most closely linked to depression as indicated by items such as lsquofeelingdepressedrsquo lsquofeeling hopelessrsquo and lsquofeeling worthlessrsquo Fourthly emotional exhaus-tion has been conceived as a general and comprehensive dimension of well-being(Enzmann et al 1998) Hence if emotional exhaustion or any other broadwell-being variable is included further health-related variables may have only weakadditional eVects on the perceptions of job conditions Therefore emotionalexhaustion may have stronger eVects on working conditions than job satisfactionand work motivation

Schaufeli and Enzmann (1998) however explained such reversed causal eVectsfrom burnout to (perceived) job characteristics from a methodological point ofview They stated that regression approaches to control statistically for the initialburnout scores may be inappropriate as a method to study predictors of changeespecially if the stability of burnout scores is high (which often seems to be thecase) Therefore they proposed promising alternative methods for the study ofchange such as growth curve modelling We did not apply this technique as morethan two waves are required for this approach

In conclusion the present results underline the importance of studyingreversed causal eVects in this kind of study (see also Zapf et al 1996) We believethat reversed eVects should always be conceived as a plausible alternativeexplanation for relations between (perceived) job characteristics and employeewell-being

The concept of negative aVectivity (NA) as a confounder of the associationbetween (perceived) job characteristics and job-related strain has been widelyinvestigated (for an overview see Spector Zapf Chen amp Frese 2000) There areimportant diverging reasons for assessing NA in job stress research First NA mayspuriously in ate the associations between the variables which have been measured

Job characteristics and psychological well-being reciprocal relationships 41

by self-report methods Secondly controlling for NA may also mean that variancein job-related strain that could be due to the work environment is removed with theNA measure In other words not controlling for NA could lead to an exaggerationof the job-strain association whereas controlling for NA in attempting to re nemethodology could lead to an underestimation of the relative importance of jobcharacteristics (Dollard amp Wine eld 1998)

Except for job autonomy and work motivation the present study showed thatNA was correlated with all job characteristics and psychological well-being In thestructural equation models however controlling for NA had no impact onjob-strain relationships There are at least three plausible interpretations of this nding First although measures used were self-reports job characteristicsmeasures have been operationalized in such a way that a certain degree ofobjectivity would be derived (cf Frese 1999 Frese amp Zapf 1988) Secondly ifperfect stability of NA is assumed NA need not be considered in panel studiesbecause its eVect is automatically partialled out if the structural equation modelis in a state of equilibrium (Spector et al 2000) Finally a number of studieshave found that NA is not (or weakly) associated with job satisfaction (egChen amp Spector 1991 Dormann amp Zapf 1998 Moyle 1995 Williams Gavinamp Williams 1996) Because the signi cant cross-lagged patterns were mainlyfound with regard to job satisfaction this study underlines the use of jobsatisfaction as an index of strain to help overcome the confounding eVectsproduced by NA

At least two remarks regarding the present study can be made First our data arecollected in discrete time samples while the processes to be observed arecontinuous Therefore we cannot obtain valid parameter estimates until themeasurement period matches the causal lag (Engel amp Meyer 1996 Frese amp Zapf1988) Moreover time mis-speci cations may lead to serious problems if the timelag is too short (Kessler amp Greenberg 1981) We have tried to estimate this periodby means of a pilot study (Vermaat 1994) but the only remedy seems to be theestimation of distributed lag models afterwards in multi-wave studies (Engel ampMeyer 1996) In contrast one could argue that discrete time approximations ofsuch continuous processes are in practice quite adequate since in some instanceschanges do not occur continuously but in distinct stages (Van der Kamp ampBijleveld 1998)

A second point involves the study population Studying people in just oneoccupation has advantages as well as disadvantages An advantage of a single-occupation group like health care professionals is that we had virtually no variancein socio-economic status which precludes confounding eVects The challenge ishowever to obtain enough variance on the variables of interest to allow hypothesistests Compared to large multi-occupation studies we might have some restrictionin range in our variables But health care professionals as an occupational grouphave the advantage of providing much natural variance because of diVerent types ofhealth care areas and because diVerent specialties exist within the same generalhospital or nursing home (Fox Dwyer amp Ganster 1993 Ganster amp Fusilier 1989)Nevertheless generalization of the current results to other occupations awaitsfurther empirical examination

42 Jan d e Jonge et al

In conclusion this study builds on earlier cross-sectional and longitudinal ndings by eliminating confounding factors and diminishing several methodologi-cal de ciencies Empirical support for the in uence of job characteristics onwork-related psychological well-being aYrms what several prominent theoreticalmodels have postulated to be the causal ordering among job characteristics andaVective responses to jobs (see Hackman amp Oldham 1980 Karasek amp Theorell1990 Siegrist 1998 Warr 1987) However this study does not invalidate theevidence that supports a reverse causal relationship (ie from psychologicalwell-being to (perceived) job characteristics) although this evidence is lessconclusive It may preliminarily indicate that (perceived) job characteristics andpyschological well-being in uence each other reciprocally rather than unidirection-ally (cf Edwards 1998) So there is a plea for studying more complex models ofthe job stress process including reciprocal relationships

Practically the present study indicated that job characteristics themselves arerelatively important predictors of employee well-being Worksite interventionsmdashdecreasing or stabilizing job demands and increasing social supportmdashare usefulstarting-points which could improve employee well-being

References

Anderson J C amp Gerbing D W (1988) Structural equation modeling in practice A review andrecommended two step approach Psychological Bulletin 103 411ndash423

Bateman T S amp Strasser S (1983) A cross-lagged regression test of the relationships between jobtension and employee satisfaction Journal of Applied Psychology 68 439ndash445

Bentler P M amp Bonett D G (1980) Signi cance tests and goodness of t in the analysis ofcovariance structures Psychological Bulletin 88 588ndash606

Bentler P M amp Chou C P (1987) Practical issues in structural modelling Sociological Methods andResearch 16 78ndash117

Bergers G P A Marcelissen F H G amp WolV Ch J de (1986) VOS-D VragenlijstOrganisatiestress-D handleid ing [VOS-D Work stress questionnaire Doetinchem] NijmegenUniversity of Nijmegen

Billings A G amp Moos R H (1982) Social support and functioning among community and clinicalgroups A panel model Journal of Behavioral Med icine 5 295ndash311

Bollen K A (1989) Structural equations with latent variables New York WileyBoumans N P G amp Landeweerd J A (1992) The role of social support and coping behaviour in

nursing work Main or buVering eVect Work and Stress 6 191ndash202Browne M W amp Cudeck R (1989) Single sample cross-validation indices for covariance structures

Multivariate Behavioral Research 24 445ndash455Browne M W amp Cudeck R (1993) Alternative ways of assessing model t In K A Bollen amp

J S Long (Eds) Testing structural equation models (pp 136ndash162) Newbury Park CA SageBurke M J Brief A P amp George J M (1993) The role of negative aVectivity in understanding

relations between self-reports of stressors and strains A comment on the applied psychologyliterature Journal of Applied Psychology 78 402ndash412

Caldwell D F amp OrsquoReilly C A (1982) Task perceptions and job satisfaction A question ofcausality Journal of Applied Psychology 67 361ndash391

Chen P Y amp Spector P E (1991) Negative aVectivity as the underlying cause of correlationsbetween stressors and strain Journal of Applied Psychology 76 398ndash407

Clark L A Watson D amp Mineka S (1994) Temperament personality and the mood and anxietydisorders Journal of Abnormal Psychology 103 103ndash116

Daniels K amp Guppy A (1997) Stressors locus of control and social support as consequences ofaVective psychological well-being Journal of Occupational Health Psychology 2 156ndash174

Job characteristics and psychological well-being reciprocal relationships 43

by self-report methods Secondly controlling for NA may also mean that variancein job-related strain that could be due to the work environment is removed with theNA measure In other words not controlling for NA could lead to an exaggerationof the job-strain association whereas controlling for NA in attempting to re nemethodology could lead to an underestimation of the relative importance of jobcharacteristics (Dollard amp Wine eld 1998)

Except for job autonomy and work motivation the present study showed thatNA was correlated with all job characteristics and psychological well-being In thestructural equation models however controlling for NA had no impact onjob-strain relationships There are at least three plausible interpretations of this nding First although measures used were self-reports job characteristicsmeasures have been operationalized in such a way that a certain degree ofobjectivity would be derived (cf Frese 1999 Frese amp Zapf 1988) Secondly ifperfect stability of NA is assumed NA need not be considered in panel studiesbecause its eVect is automatically partialled out if the structural equation modelis in a state of equilibrium (Spector et al 2000) Finally a number of studieshave found that NA is not (or weakly) associated with job satisfaction (egChen amp Spector 1991 Dormann amp Zapf 1998 Moyle 1995 Williams Gavinamp Williams 1996) Because the signi cant cross-lagged patterns were mainlyfound with regard to job satisfaction this study underlines the use of jobsatisfaction as an index of strain to help overcome the confounding eVectsproduced by NA

At least two remarks regarding the present study can be made First our data arecollected in discrete time samples while the processes to be observed arecontinuous Therefore we cannot obtain valid parameter estimates until themeasurement period matches the causal lag (Engel amp Meyer 1996 Frese amp Zapf1988) Moreover time mis-speci cations may lead to serious problems if the timelag is too short (Kessler amp Greenberg 1981) We have tried to estimate this periodby means of a pilot study (Vermaat 1994) but the only remedy seems to be theestimation of distributed lag models afterwards in multi-wave studies (Engel ampMeyer 1996) In contrast one could argue that discrete time approximations ofsuch continuous processes are in practice quite adequate since in some instanceschanges do not occur continuously but in distinct stages (Van der Kamp ampBijleveld 1998)

A second point involves the study population Studying people in just oneoccupation has advantages as well as disadvantages An advantage of a single-occupation group like health care professionals is that we had virtually no variancein socio-economic status which precludes confounding eVects The challenge ishowever to obtain enough variance on the variables of interest to allow hypothesistests Compared to large multi-occupation studies we might have some restrictionin range in our variables But health care professionals as an occupational grouphave the advantage of providing much natural variance because of diVerent types ofhealth care areas and because diVerent specialties exist within the same generalhospital or nursing home (Fox Dwyer amp Ganster 1993 Ganster amp Fusilier 1989)Nevertheless generalization of the current results to other occupations awaitsfurther empirical examination

42 Jan d e Jonge et al

In conclusion this study builds on earlier cross-sectional and longitudinal ndings by eliminating confounding factors and diminishing several methodologi-cal de ciencies Empirical support for the in uence of job characteristics onwork-related psychological well-being aYrms what several prominent theoreticalmodels have postulated to be the causal ordering among job characteristics andaVective responses to jobs (see Hackman amp Oldham 1980 Karasek amp Theorell1990 Siegrist 1998 Warr 1987) However this study does not invalidate theevidence that supports a reverse causal relationship (ie from psychologicalwell-being to (perceived) job characteristics) although this evidence is lessconclusive It may preliminarily indicate that (perceived) job characteristics andpyschological well-being in uence each other reciprocally rather than unidirection-ally (cf Edwards 1998) So there is a plea for studying more complex models ofthe job stress process including reciprocal relationships

Practically the present study indicated that job characteristics themselves arerelatively important predictors of employee well-being Worksite interventionsmdashdecreasing or stabilizing job demands and increasing social supportmdashare usefulstarting-points which could improve employee well-being

References

Anderson J C amp Gerbing D W (1988) Structural equation modeling in practice A review andrecommended two step approach Psychological Bulletin 103 411ndash423

Bateman T S amp Strasser S (1983) A cross-lagged regression test of the relationships between jobtension and employee satisfaction Journal of Applied Psychology 68 439ndash445

Bentler P M amp Bonett D G (1980) Signi cance tests and goodness of t in the analysis ofcovariance structures Psychological Bulletin 88 588ndash606

Bentler P M amp Chou C P (1987) Practical issues in structural modelling Sociological Methods andResearch 16 78ndash117

Bergers G P A Marcelissen F H G amp WolV Ch J de (1986) VOS-D VragenlijstOrganisatiestress-D handleid ing [VOS-D Work stress questionnaire Doetinchem] NijmegenUniversity of Nijmegen

Billings A G amp Moos R H (1982) Social support and functioning among community and clinicalgroups A panel model Journal of Behavioral Med icine 5 295ndash311

Bollen K A (1989) Structural equations with latent variables New York WileyBoumans N P G amp Landeweerd J A (1992) The role of social support and coping behaviour in

nursing work Main or buVering eVect Work and Stress 6 191ndash202Browne M W amp Cudeck R (1989) Single sample cross-validation indices for covariance structures

Multivariate Behavioral Research 24 445ndash455Browne M W amp Cudeck R (1993) Alternative ways of assessing model t In K A Bollen amp

J S Long (Eds) Testing structural equation models (pp 136ndash162) Newbury Park CA SageBurke M J Brief A P amp George J M (1993) The role of negative aVectivity in understanding

relations between self-reports of stressors and strains A comment on the applied psychologyliterature Journal of Applied Psychology 78 402ndash412

Caldwell D F amp OrsquoReilly C A (1982) Task perceptions and job satisfaction A question ofcausality Journal of Applied Psychology 67 361ndash391

Chen P Y amp Spector P E (1991) Negative aVectivity as the underlying cause of correlationsbetween stressors and strain Journal of Applied Psychology 76 398ndash407

Clark L A Watson D amp Mineka S (1994) Temperament personality and the mood and anxietydisorders Journal of Abnormal Psychology 103 103ndash116

Daniels K amp Guppy A (1997) Stressors locus of control and social support as consequences ofaVective psychological well-being Journal of Occupational Health Psychology 2 156ndash174

Job characteristics and psychological well-being reciprocal relationships 43

In conclusion this study builds on earlier cross-sectional and longitudinal ndings by eliminating confounding factors and diminishing several methodologi-cal de ciencies Empirical support for the in uence of job characteristics onwork-related psychological well-being aYrms what several prominent theoreticalmodels have postulated to be the causal ordering among job characteristics andaVective responses to jobs (see Hackman amp Oldham 1980 Karasek amp Theorell1990 Siegrist 1998 Warr 1987) However this study does not invalidate theevidence that supports a reverse causal relationship (ie from psychologicalwell-being to (perceived) job characteristics) although this evidence is lessconclusive It may preliminarily indicate that (perceived) job characteristics andpyschological well-being in uence each other reciprocally rather than unidirection-ally (cf Edwards 1998) So there is a plea for studying more complex models ofthe job stress process including reciprocal relationships

Practically the present study indicated that job characteristics themselves arerelatively important predictors of employee well-being Worksite interventionsmdashdecreasing or stabilizing job demands and increasing social supportmdashare usefulstarting-points which could improve employee well-being

References

Anderson J C amp Gerbing D W (1988) Structural equation modeling in practice A review andrecommended two step approach Psychological Bulletin 103 411ndash423

Bateman T S amp Strasser S (1983) A cross-lagged regression test of the relationships between jobtension and employee satisfaction Journal of Applied Psychology 68 439ndash445

Bentler P M amp Bonett D G (1980) Signi cance tests and goodness of t in the analysis ofcovariance structures Psychological Bulletin 88 588ndash606

Bentler P M amp Chou C P (1987) Practical issues in structural modelling Sociological Methods andResearch 16 78ndash117

Bergers G P A Marcelissen F H G amp WolV Ch J de (1986) VOS-D VragenlijstOrganisatiestress-D handleid ing [VOS-D Work stress questionnaire Doetinchem] NijmegenUniversity of Nijmegen

Billings A G amp Moos R H (1982) Social support and functioning among community and clinicalgroups A panel model Journal of Behavioral Med icine 5 295ndash311

Bollen K A (1989) Structural equations with latent variables New York WileyBoumans N P G amp Landeweerd J A (1992) The role of social support and coping behaviour in

nursing work Main or buVering eVect Work and Stress 6 191ndash202Browne M W amp Cudeck R (1989) Single sample cross-validation indices for covariance structures

Multivariate Behavioral Research 24 445ndash455Browne M W amp Cudeck R (1993) Alternative ways of assessing model t In K A Bollen amp

J S Long (Eds) Testing structural equation models (pp 136ndash162) Newbury Park CA SageBurke M J Brief A P amp George J M (1993) The role of negative aVectivity in understanding

relations between self-reports of stressors and strains A comment on the applied psychologyliterature Journal of Applied Psychology 78 402ndash412

Caldwell D F amp OrsquoReilly C A (1982) Task perceptions and job satisfaction A question ofcausality Journal of Applied Psychology 67 361ndash391

Chen P Y amp Spector P E (1991) Negative aVectivity as the underlying cause of correlationsbetween stressors and strain Journal of Applied Psychology 76 398ndash407

Clark L A Watson D amp Mineka S (1994) Temperament personality and the mood and anxietydisorders Journal of Abnormal Psychology 103 103ndash116

Daniels K amp Guppy A (1997) Stressors locus of control and social support as consequences ofaVective psychological well-being Journal of Occupational Health Psychology 2 156ndash174

Job characteristics and psychological well-being reciprocal relationships 43

Dollard M F amp Wine eld A H (1998) A test of the Demand-ControlSupport Model of workstress in correctional oYcers Journal of Occupational Health Psychology 3 243ndash264

Doef M van der amp Maes S (1999) The Job Demand-Control(-Support) Model and psychologicalwell-being A review of 20 years of empirical research Work and Stress 13 87ndash114

Dormann C amp Zapf D (1998) Job satisfactionmdasha personality trait A review of stabilities and a variancedecomposition applied to a 5-wave study Manuscript submitted for publication

Dwyer J E (1983) Statistical models for the social and behavioral sciences New York Oxford UniversityPress

Edwards J R (1998) Cybernetic theory of stress coping and well-being Review and extension towork and family In C L Cooper (Ed) Theories of organizational stress (pp 122ndash152) Oxford OxfordUniversity Press

Engel U amp Meyer W (1996) Structural analysis in the study of social change In U Engel ampJ Reinecke (Eds) Analysis of change Advanced techniques in panel d ata analysis (pp 221ndash252) BerlinDe Gruyter

Enzmann D Schaufeli W B Janssen P amp Rozeman A (1998) Dimensionality and validity of theBurnout Measure Journal of Occupational and Organizational Psychology 71 331ndash351

Finkel S E (1995) Causal analysis with panel d ata Thousand Oaks CA SageFirth-Cozens J (1992) Why me A case study of the process of perceived occupational stress Human

Relations 45 131ndash141Firth-Cozens J amp Hardy G E (1992) Occupational stress clinical treatment and changes in job

perceptions Journal of Occupational and Organizational Psychology 65 81ndash88Fisher C D (1985) Social support and adjustment to work A longitudinal study Journal of

Management 11 39ndash53Fox M L Dwyer D J amp Ganster D C (1993) EVects of stressful job demands and control on

psychological and attitudinal outcomes in a hospital setting Academy of Management Journal 36289ndash318

Frese M (1982) Occupational socialization and psychological development An underemphasizedresearch perspective in industrial psychology Journal of Occupational Psychology 55 209ndash224

Frese M (1999) Social support as a moderator of the relationship between work stressors andpsychological dysfunctioning A longitudinal study with objective measures Journal of OccupationalHealth Psychology 4 179ndash192

Frese M amp Zapf D (1988) Methodological issues in the study of work stress Objective vssubjective measurement of work stress and the question of longitudinal studies In C L Cooper ampR Payne (Eds) Causes coping and consequences of stress at work (pp 375ndash411) Chichester Wiley

Ganster D C amp Fusilier M R (1989) Control in the workplace In C L Cooper amp I T Robertson(Eds) International review of industrial and organizational psychology (pp 235ndash280) Chichester Wiley

Hackman J R amp Oldham G R (1980) Work red esign Reading MA Addison-WesleyHagenaars J A (1990) Categorical longitudinal data Log-linear panel trend and cohort analysis Newbury

Park CA SageHu L T amp Bentler P M (1998) Fit indices in covariance structure modeling Sensitivity to

underparameterized model misspeci cation Psychological Methods 3 424ndash453Jaccard J R amp Wan C K (1996) LISREL approaches to interaction eVects in multiple regression Thousand

Oaks CA SageJames L R amp Jones A P (1980) Perceived job characteristics and job satisfaction An examination

of reciprocal causation Personnel Psychology 33 97ndash135James L R amp Tetrick L E (1986) Con rmatory analytic tests of three causal models relating job

perceptions to job satisfaction Journal of Applied Psychology 71 77ndash82Johnson J V amp Hall E M (1988) Job strain work place social support and cardiovascular disease

A cross-sectional study of a random sample of the Swedish working population American Journal ofPublic Health 78 1336ndash1342

Jonge J de (1995) Job autonomy well-being and health A study among Dutch health care workers PhD thesisMaastricht Datawyse

Jonge J de Janssen P P M amp Breukelen G J P van (1996) Testing the Demand-Control-SupportModel among health care professionals A structural equation model Work and Stress 10 209ndash224

44 Jan d e Jonge et al

Jonge J de Landeweerd J A amp Breukelen G J P van (1994) De Maastrichtse AutonomielijstAchtergrond constructie en validering [The Maastricht Autonomy Questionnaire Backgroundconstruction and validation] Gedrag en Organisatie 7 27ndash41

Joreskog K G amp Sorbom D (1993) LISREL 8 Userrsquos reference guid e Chicago Scientic SoftwareInternational

Kamp L J Th van der amp Bijleveld C C J H (1998) Methodological issues in longitudinal researchIn C C J H Bijleveld amp L J Th van der Kamp (Eds) Longitudinal data analysis Designs models andmethods (pp 1ndash45) London Sage

Karasek R A amp Theorell T (1990) Healthy work Stress productivity and the reconstruction of working lifeNew York Basic Books

Kessler R C amp Greenberg D F (1981) Linear panel analysis Models of quantitative change New YorkAcademic Press

Kohn M L amp Schooler C (1983) Work and personality An inquiry into the impact of social straticationNorwood NJ Ablex

Landsbergis P A (1988) Occupational stress among health care workers A test of the jobdemands-control model Journal of Organizational Behavior 9 217ndash239

Leiter M P amp Durup M J (1996) Work home and in-between A longitudinal study of spilloverJournal of Applied Behavioral Science 32 29ndash47

Long J S (1983) Covariance structure models An introduction to LISREL Newbury Park CA SageLorence J amp Mortimer J T (1985) Job involvement through the life course A panel study of three

age groups American Sociological Review 50 618ndash638MacCallum R C Wegener D T Uchino B N amp Fabrigar L R (1993) The problem of equivalent

models in applications of covariance structure analysis Psychological Bulletin 114 185ndash199Marcelissen F H G Winnubst J A M Buunk B amp WolV Ch J de (1988) Social support and

occupational stress A causal analysis Social Science and Med icine 26 365ndash373Maslach C (1998) A multidimensional theory of burnout In C L Cooper (Ed) Theories of

organizational stress (pp 68ndash85) Oxford Oxford University PressMathews A (1993) Biases in processing emotional information The Psychologist 6 493ndash499McLaney M A amp Hurrell J J Jr (1988) Control stress and job satisfaction in Canadian nurses

Work and Stress 2 217ndash224Miller S M (1980) Why having control reduces stress If I can stop the roller coaster I donrsquot want

to get oV In M Seligman amp J Garber (Eds) Human helplessness Theory and applications (pp 71ndash95)New York Academic Press

Moyle P (1995) The role of negative aVectivity in the stress process Tests of alternative modelsJournal of Organizational Behavior 16 647ndash668

Parkes K R Mendham C A amp Rabenau C von (1994) Social support and the Demand-DiscretionModel of job stress Tests of additive and interactive eVects in two samples Journal of VocationalBehavior 44 91ndash113

Peeters M C W (1994) Supportive interactions and stressful events at work An event-record ing approachPhD thesis Nijmegen Quickprint

Reiche H M J K I amp Dijkhuizen N van (1979) Vragenlijst Organisatie Stress Test-handleid ing[Organizational Stress Questionnaire Test-manual] Nijmegen University of Nijmegen

Rijk A E de Blanc P M Le Schaufeli W B amp Jonge J de (1998) Active coping and need forcontrol as moderators of the Job Demand-Control Model EVects on burnout Journal of Occupationaland Organizational Psychology 71 1ndash18

Rogosa D (1980) A critique of cross-lagged correlation Psychological Bulletin 88 245ndash258Scarpello V amp Campbell J P (1983) Job satisfaction Are all the parts there Personnel Psychology 36

577ndash600Schaufeli W B amp Dierendonck D van (1993) The construct validity of two burnout measures

Journal of Organizational Behavior 14 631ndash647Schaufeli W amp Enzmann D (1998) The burnout companion to study and practice A critical analysis

London Taylor amp FrancisSchumacker R E amp Lomax R G (1996) A beginnerrsquos guide to structural equation modeling Mahwah NJ

Erlbaum

Job characteristics and psychological well-being reciprocal relationships 45

Schwarzer R Hahn A amp Jerusalem M (1993) Negative eVect in East German migrantsLongitudinal eVects of unemployment and social support Anxiety Stress and Coping 6 57ndash69

Semmer N Zapf D amp Greif S (1996) lsquoShared job strainrsquo A new approach for assessing thevalidity of job stress measurements Journal of Occupational and Organizational Psychology 69 293ndash310

Shinn M Rosario M Morch H amp Chestnut D E (1984) Coping with job stress and burnout inhuman services Journal of Personality and Social Psychology 46 864ndash876

Shirom A amp Oliver A (1986) Does stress lead to aVective strain or vice versa A cross-lagged regression testPaper presented at the 21st Congress of the International Association of Applied PsychologyJerusalem Israel

Siegrist J (1998) Adverse health eVects of eVortndashreward imbalance at work Theory empiricalsupport and implications for prevention In C L Cooper (Ed) Theories of organizational stress(pp 190ndash204) Oxford Oxford University Press

Spector P E (1997) Job satisfaction Application assessment causes and consequences Thousand Oaks CASage

Spector P E Zapf D Chen P Y amp Frese M (2000) Why negative aVectivity should not becontrolled in job stress research Donrsquot throw out the baby with the bath water Journal ofOrganizational Behavior 21 79ndash95

Taris T W Bok I A amp Calje D G (1998) On the relation between job characteristics anddepression A longitudinal study International Journal of Stress Management 5 157ndash167

Vermaat K (1994) Flexibele werklastbeheersing in d e verpleging [Flexible workload control in nursing]Maastricht Maastricht University

Waldron I Herold J Dunn D amp Staum R (1982) Reciprocal eVects of health and labor forceparticipation among women Evidence from two longitudinal studies Journal of Occupational Med icine24 295ndash310

Wall T D Jackson P R Mullarkey S amp Parker S K (1996) The demands-control model of jobstrain A more speci c test Journal of Occupational and Organizational Psychology 69 153ndash166

Wanous J P Reichers A E amp Hudy M J (1997) Overall job satisfaction How good aresingle-item measures Journal of Applied Psychology 82 247ndash252

Warr P (1987) Work Unemployment and Mental Health Oxford Clarendon PressWatson D amp Clark L A (1984) Negative aVectivity The disposition to experience aversive

emotional states Psychological Bulletin 96 465ndash490Williams L J Gavin M B amp Williams M L (1996) Measurement and nonmeasurement processes

with negative aVectivity and employee attitudes Journal of Applied Psychology 54 87ndash94Williams L J amp PodsakoV P M (1989) Longitudinal eld methods for studying reciprocal

relationships in organizational behavior research Toward improved causal analysis In B M Stawamp L L Cummings (Eds) Research in organizational behavior (Vol II pp 247ndash292) Greenwich CNJAI Press

Zapf D Dormann C amp Frese M (1996) Longitudinal studies in organizational stress research Areview of the literature with reference to methodological issues Journal of Occupational HealthPsychology 1 145ndash169

Received 21 April 1999 revised version received 17 February 2000

46 Jan d e Jonge et al

All in-text references underlined in blue are linked to publications on ResearchGate letting you access and read them immediately