antecedents and consequences of employee absenteeism: a longitudinal perspective on the role of job...

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Antecedents and consequencesof employee absenteeism: Alongitudinal perspective onthe role of job satisfaction andburnoutJan F. Ybema a , Peter G. W. Smulders a & Paulien M.Bongers aa TNO Work and Employment , Hoofddorp, TheNetherlandsPublished online: 24 Mar 2010.

To cite this article: Jan F. Ybema , Peter G. W. Smulders & Paulien M. Bongers (2010)Antecedents and consequences of employee absenteeism: A longitudinal perspective onthe role of job satisfaction and burnout, European Journal of Work and OrganizationalPsychology, 19:1, 102-124, DOI: 10.1080/13594320902793691

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Antecedents and consequences of employee absenteeism:

A longitudinal perspective on the role of job satisfaction

and burnout

Jan F. Ybema, Peter G. W. Smulders, and Paulien M. BongersTNO Work and Employment, Hoofddorp, The Netherlands

This study examined the interrelations between registered employeeabsenteeism, job satisfaction, and burnout in a longitudinal design with fouryearly waves of data. The participants were 844 workers in 34 companies inThe Netherlands. In line with the predictions, a reciprocal relationshipbetween job satisfaction and absence frequency was found. Lower jobsatisfaction increased absence frequency in the following year, whereashigher absence frequency lowered subsequent job satisfaction. Contrary tothe prediction, more time lost due to absence increased job satisfaction in thefollowing year. Furthermore, it was found that higher burnout enhancedfuture time lost due to absence, and lowered future job satisfaction. Finally,individuals who were frequently absent in one year, were more likely to have aprolonged absence in the following year.

Keywords: Burnout; Employee absenteeism; Job satisfaction; Longitudinalresearch.

Absence from work is a major problem for many work organizations andtheir employees. Such absence disrupts the work processes, leads to loss ofproductivity, and heightens the work load among colleagues. Moreover,absence is an indicator of the worker’s health and well-being. Frequentabsence from work may mean that a worker needs to recover from thestresses at work. Long-term absence may indicate that a worker has seriousproblems that may or may not be due to the work. Although a lot ofresearch has focused on how absenteeism is related to job satisfaction andpsychological health at work (see Johns, 1997, for an overview), it remainslargely unclear whether these indicators of well-being at work should be seen

Correspondence should be addressed to Jan F. Ybema, TNO Work and Employment, PO

Box 718, 2130 AS Hoofddorp, The Netherlands. E-mail: [email protected]

EUROPEAN JOURNAL OF WORK AND

ORGANIZATIONAL PSYCHOLOGY

2010, 19 (1), 102–124

� 2009 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

http://www.psypress.com/ejwop DOI: 10.1080/13594320902793691

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as antecedents or as consequences of absenteeism. In the present study wetry to unravel the interrelations between job satisfaction, burnout, andabsenteeism in a four-wave longitudinal study.

The present study focuses on the direction of the causal flow in theinterrelations between job satisfaction, burnout, and absenteeism. The firstissue in this research concerns whether job satisfaction should be seen as anantecedent or a consequence of absenteeism. The second issue is howburnout relates to both job satisfaction and absence, and whether burnoutcan explain the relationship between these two variables. The third issue iswhether different aspects of absence, i.e., the frequency of absence and thetime lost due to absence, are differentially related to job satisfaction andburnout. Next, we summarize some of the empirical evidence on therelationship between job satisfaction and absenteeism, and burnout andabsenteeism.

JOB SATISFACTION AND ABSENTEEISM

Several meta-analyses have been done on studies that include correlationsbetween job satisfaction and absenteeism (Hackett, 1989; Scott & Taylor,1985). These meta-analyses consistently showed that job satisfaction has amodest negative relationship with both the frequency and the duration ofabsence. This negative relationship may be explained in several ways: (1)Dissatisfaction with the job may lead to higher absence, (2) high absencemay lead to lower job satisfaction, or (3) a third variable (e.g., burnout) maylower job satisfaction and heighten absence. This is shown in Figure 1.

When people are dissatisfied with their jobs, they may respond to thisdissatisfaction by increasing their absence from work (relation a in Figure 1).This notion is found in the so-called ‘‘withdrawal’’ models of absence (DeBoer, Bakker, Syroit, & Schaufeli, 2002; Johns, 1997; Sagie, 1998), whichregards absence from work as voluntary withdrawal from aversive work

Figure 1. Predicted relationships between job satisfaction, absence from work, and burnout.

ABSENTEEISM, JOB SATISFACTION, AND BURNOUT 103

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conditions. According to the seminal work of Steers and Rhodes (1978),dissatisfaction with the job may lower the motivation to attend, which is amajor determinant of attendance (i.e., the opposite of absence). However,people who are dissatisfied with their jobs have an array of ways to react, andmore frequent or prolonged absence is only one of their options. Farrell (1983)presented a typology of responses to job dissatisfaction, which included exit(e.g., turnover), voice (e.g., protest, consult), neglect (e.g., absence, tardiness),and patience (e.g., wait and see). This means that the relationship between jobsatisfaction and absence is not necessarily a strong one. Moreover, jobdissatisfaction is one amongmany potential antecedents of absenteeism.Mostshort-term absences are due to common colds and influenza, and long-termabsences are generally due to physical and psychological illnesses (Allegro &Veerman, 1998). This means that health and illness could explain a substantialportion of an individual’s absences, and only a moderate relationship could beexpected between job dissatisfaction and absence. Nevertheless, we mayconclude that job dissatisfaction may be an antecedent of absence from work.

When people are frequently absent from their job, or are absent for aprolonged time, this may result in increased dissatisfaction with the job(relation b in Figure 1). Such reversed causation (De Lange, Taris, Kompier,Houtman & Bongers, 2004) is predicted in the so-called ‘‘drift-hypothesis’’(Cardano, Costa, & Demaria, 2004; Zapf, Dormann, & Frese, 1996), whichmaintains that individuals with a bad health and high absenteeism drift intoworse jobs or positions with fewer responsibilities. Workers who are absentfrequently or for a prolonged time may get less interesting tasks, may get intoconflict with their supervisors or their colleagues for not fulfilling the tasksthat they are supposed to do, may not be promoted, may be paid less, andmaybe treated with less respect than workers who are not absent (Steers &Rhodes, 1978). In addition, especially when they are absent for a prolongedtime, workers may distance themselves from their jobs as a way of coping withtheir situation, and selectively evaluate their situation such that workers cometo view their jobs as less important in their life than previously was the case(Buunk & Ybema, 1995). Nevertheless, job dissatisfaction may result frommany different circumstances. Individuals may for example be dissatisfiedwith their job as a result of a dislike for their tasks or assignments, conflictswith colleagues or the supervisor, unfavourable pay or promotion prospects,or unfair treatment by the company. Frequent or prolonged absence is oneamong many potential causes for dissatisfaction, which implies that the size ofeffects of absenteeism on job satisfaction will be modest (cf. Zapf et al., 1996).

In a search of relevant literature, we found three longitudinal studies thatfocused on the relationship between job satisfaction and absenteeism.Tharenou (1993) showed in a study among electrical apprentices, thatnoncertified (short-term) absence from work influenced job satisfaction inthe following year. The reverse relationship was not found in this study.

104 YBEMA, SMULDERS, BONGERS

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More recently, Hardy, Woods, and Wall (2003) showed in a study amonghealthcare workers that low job satisfaction contributed to highersubsequent absence from work. Similarly, Mohren, Swaen, Kant, vanSchayck, and Galama (2005) found that low job satisfaction enhancedsubsequent absence during common infections (a cold). However, theselatter two studies did not test whether the reverse relationship held. We didnot locate other longitudinal studies on the relationship between jobsatisfaction and absenteeism, and we therefore conclude that further insightin the nature of the relationship between these two variables is needed.However, our prediction is that absence and job satisfaction may influenceeach other in a reciprocal or cyclical way. Thus, we predict that bothrelation a and relation b in Figure 1 will hold.

BURNOUT AND ABSENTEEISM

A large portion of those who are absent from work for a prolonged time arediagnosed as emotionally exhausted, burned out, overstrained, or depressed(Houtman & Blatter, 2005). The central element of burnout is emotionalexhaustion (Maslach & Jackson, 1986), which refers to a loss of emotionalresources and a lack of energy. In so-called ‘‘stress’’ models (De Boer et al.,2002; Johns, 1997), absence from work is seen as a consequence of stressfulwork conditions. Workers do not feel able to work, due to their (subjective)health condition, or try to prevent further stress or illness by temporaryabsence from work. Burnout may make absence from work necessary torecover from job stresses. In addition, burnout may undermine satisfactionand the motivation to attend, and burnout may therefore operate as a thirdvariable that may heighten absence and lower job satisfaction (relation c inFigure 1). In this study, we consider burnout as an indicator ofpsychological ill-health at work, which may result from either personalitycharacteristics such as negative affectivity, work characteristics such as jobdemands, and somatic health complaints.

Iverson, Olekalns, and Erwin (1998) presented and tested a model in whichjob satisfaction was considered an attitudinal consequence of burnout(relation c1 in Figure 1), whereas absence from work was regarded as abehavioural consequence (relation c2 in Figure 1). Such a model would implythat correlations between job satisfaction and absence could be spurious, andare due to third variables, most notably, burnout. Nevertheless, in their study,a negative relationship between job satisfaction and absence remained aftercontrolling for burnout. Iverson and his colleagues found evidence for astrong relation between burnout and job satisfaction, but only a weakrelationship between burnout and the frequency of absence from work.

Saxton, Phillips, and Blakeney (1991) examined the correlates of burnout(emotional exhaustion) among airline reservation workers with computerized


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work in a cross-sectional study. In contrast to Iverson et al. (1998), Saxtonet al. considered low job satisfaction as an antecedent of burnout rather thana consequence. Moreover, absence frequency was considered a consequenceof burnout. This study tested a model in which burnout could be regarded asa mediator of the relationship between job satisfaction and absencefrequency. Their data seemed to confirm the mediating role of burnout,but Saxton et al. did not explicitly test or mention mediation.

Although not specifically concerned with burnout, the Hardy et al. (2003)study on the relationship between psychological distress and absenteeism isrelevant here. This study showed that both general psychological distressand work-related anxiety and depression contributed to higher subsequentabsence. Moreover, they hypothesized and found that job satisfaction andpsychological distress were independently related to subsequent absence.Finally, Toppinen-Tanner, Ojajarvi, Vaananen, Kalimo, and Jappinen(2005) found that burnout predicted future medically certified sick-leaveabsences. Especially absences due to mental and behavioural disorders weremore likely among those high in burnout.

We conclude that these studies conceptualized, tested, and foundevidence for different kinds of relationships between employee absenteeism,job satisfaction, and burnout. We did not find more conclusive research thatfocused on the role of burnout in explaining the interrelation between jobsatisfaction and absenteeism, and therefore examine this issue in the presentstudy in an exploratory fashion.

ABSENCE MEASURES

Many researchers (e.g., Frese & Zapf, 1988; Ganster & Schaubroeck, 1991)have argued that nonreactive measures of employee absenteeism should beused to supplement information from questionnaires and interviews. Theabsence data for this study were recorded by the company’s PersonnelDepartment during the four calendar years in which the study was carriedout. At the time of this study, companies needed to register absences to becompensated by the government according to the Sickness Benefit Act. Thispromoted a careful registration of absenteeism.

Two absence measures were used: the absence frequency (number ofabsence spells per person per year, irrespective of their duration), and totaltime lost (the total duration in calendar days of all spells in 1 year combined).These are two common measures in academic studies (Hensing, Alexander-son, Allebeck, & Bjurulf, 1998; Johns, 1994; Rhodes & Steers, 1990). Bothmeasures may include short-term absence periods as well as periods of longerduration. Theoretically, one absence spell could have a minimum duration of1 day and a maximum duration of 365 days. Absences because of sicknesswere included, but absences because of holidays were excluded.


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Measuring both absence frequency and time lost is important since theyare only partly determined by the same variables (e.g., Gellatly, 1995;Smulders, 1980, 1983). For example, absence frequency is more influencedby the employee’s task, the workgroup organization, leadership, shift work,and absence control measures, whereas the time lost (or absence rate) ismore influenced by age, working conditions, sickness benefits, and accesstime to medical specialists and hospitals (Smulders, 1980). Frequencymeasures of absence are often presumed to tap voluntary absence more thantime lost measures do (Johns, 1994).

OVERVIEW OF THE RESEARCH QUESTIONS

This research focuses on disentangling the relationships between jobsatisfaction, burnout, and employee absenteeism in a longitudinal four-wave study. Our research questions are the following:

1. Is low job satisfaction an antecedent or a consequence ofabsenteeism?

2. Does burnout explain the relationship between job satisfaction andabsenteeism?

3. Are absence frequency and total time lost differentially related to jobsatisfaction and burnout?

Only for the first research question, we state a specific hypothesis. In linewith our literature review, we hypothesize that the causal flow between jobsatisfaction and absenteeism goes both ways, such that low job satisfactionis both an antecedent and an consequence of higher absenteeism. Weexamine the potential role of burnout, and the differences between absencefrequency and total time lost in an exploratory fashion.

METHOD

Procedure

This study is part of a larger prospective cohort study in The Netherlands, theStudy on Musculoskeletal disorders, Absenteeism, Stress and Health(SMASH) (Ariens et al., 2001; De Jonge, Reuvers, Houtman, Bongers &Kompier, 2000; De Lange, Taris, Kompier, Houtman, & Bongers, 2002, 2004;Hoogendoorn et al., 2000). This study had a longitudinal design with fouryearly waves of data. At the first measurement, 1789 employees working in 34companies in TheNetherlands participated in the study. The participants filledout a self-administered questionnaire. The questionnaire included questionson general work conditions, physical and psychosocial demands at work, job


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satisfaction, and health. Each following year, participants filled out a similarquestionnaire. In addition, the participants’ individual absenteeism in eachcalendar year was registered by their company, and included in the database.

Sample

Originally, 2064 employees of 34 companies were invited to participate inthe study. These companies included, for example, hospitals, metal factories,chemical plants, building companies, and food processing industries. Theemployees were mostly blue collar workers (e.g., welders, brick layers,mechanics, machine operators), and lower class white collar workers (e.g.,nurses, child workers, office clerks). Of these employees, 1789 participated atT1 (87%). At the fourth measurement, the sample was reduced to 1473participants. A substantial number of participants had missing values onone or more of the variables of our study, leaving 844 participants with fulldata for all four measurements. Of these 844 participants, 592 were male(70%) and 252 were female (30%). At T1, they varied in age from 18 to 59years (M¼ 35, SD¼ 9). In Table 1 we compare these 844 participants with731 participants with full data at the first measurement who were notincluded in the study. This table shows that included participants weresomewhat higher in job satisfaction (p5 .05), and somewhat lower inburnout (p5 .05). Moreover, included participants were substantially lessfrequently absent from their jobs (p5 .001), and lost less days due toabsence (p5 .001) than excluded participants. This issue of selectiveattrition will be dealt with in the Discussion section.

Measures

Employee absenteeism. Absence was registered in each company, with theonset and end of each absence spell. Especially in long-term absence,employees may be absent partially, e.g., working for less hours due to the

TABLE 1Differences between included and excluded participants at T1

Included (N¼ 844) Excluded (N¼ 731)

Mean SD Mean SD

Absence frequency 1.55 1.63 1.87 1.84

Total time lost 14.44 25.20 22.99 37.54

Job satisfaction 3.39 0.69 3.33 0.74

Burnout 0.16 0.21 0.19 0.23


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illness. Conforming to Dutch law, such partial absence is considered asabsence in this study. The raw absence data were condensed into two absencemeasures for each calendar year: frequency of absence and total time lost (incalendar days). Table 2 gives the range and other descriptive statistics on thesemeasures for all four measurements. It can be seen that the distribution ofboth absence measures were highly positively skewed, and had a high kurtosis(i.e., fat tails). This implies that analyses for nonnormal data are indicated.

Burnout. As a measure for burnout, seven items from the emotionalexhaustion scale were adapted from the Utrecht Burnout Scale (Schaufeli &van Dierendonck, 1994), which is a translated and modified version of theMaslach Burnout Inventory (Maslach & Jackson, 1986). Examples of theseitems are: ‘‘Do you feel mentally exhausted by your work?’’, ‘‘Do you feelempty at the end of a working day?’’, and ‘‘Do you think you invest too muchin your work?’’ These items could be answered ‘‘yes’’ (1) or ‘‘no’’ (0). Theitems were averaged to a scale for burnout, ranging from 0 to 1. Cronbach’salpha for this scale ranged from .72 to .78 at the four measurements.

Job satisfaction. Job satisfaction was measured with a single item, ‘‘Doyou mostly enjoy your work?’’, with a scale ranging from ‘‘not at all’’ (1) to

TABLE 2Descriptive statistics

Minimum Maximum Mean SD Skewness Kurtosis

Absence frequency

T1 0 13 1.55 1.63 1.95 7.08

T2 0 11 1.72 1.55 1.12 2.01

T3 0 10 1.68 1.54 1.46 3.55

T4 0 14 1.61 1.62 1.83 6.76

Total time lost

T1 0 270 14.44 25.20 3.90 22.02

T2 0 291 18.70 32.98 3.94 20.80

T3 0 365 19.28 34.45 3.94 21.71

T4 0 325 21.14 40.22 3.60 15.75

Job satisfaction

T1 1 4 3.39 0.69 70.80 70.09

T2 1 4 3.34 0.69 70.60 70.57

T3 1 4 3.28 0.73 70.64 70.34

T4 1 4 3.28 0.74 70.64 70.44

Burnout

T1 0 1 0.16 0.21 1.60 2.39

T2 0 1 0.16 0.22 1.72 2.70

T3 0 1 0.17 0.23 1.53 1.73

T4 0 1 0.16 0.23 1.71 2.47


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‘‘very much’’ (4). The stability of the answers over measurements on thisitem may function as an indication of reliability. The correlations betweenthese measures for job satisfaction in two consecutive years ranged from .54to .61, p5 .001. Such single item measures of overall job satisfaction havebeen shown to be reliable and valid (Wanous, Reichers, & Hudy, 1997).

Analysis

The data were analysed using SPSS for Windows, and with the packagesPRELIS 2 (Joreskog & Sorbom, 1996b), and LISREL 8 (Joreskog & Sorbom,1996a). In the SPSS-analyses, both parametric and nonparametric tests wereused to examine the changes over time in the variables of study. In theLISREL-analyses, a Robust Maximum Likelihood (RML) method, withasymptotic variances and covariances was used. RML is appropriate forvariables with nonnormal distributions (Boomsma & Hoogland, 2001). Inthese models, the residual covariances within each measurement between jobsatisfaction, burnout and absenteeism were estimated, but set equal acrossmeasurements. Moreover, the effects of job satisfaction, burnout, andabsenteeism on these variables a year later were estimated, and set equalacross measurements. For evaluating the fit of the model, the Sattora-Bentlerscaled Chi Square was used, which is developed for evaluating models withnonnormal data (Boomsma&Hoogland, 2001). In addition, as recommendedby Bentler (2007), the Comparative Fit Index (CFI), the Root Mean SquareError of Approximation (RMSEA), and the Standardized RootMean SquareResidual (SRMR) were used. Values of .95 and above for CFI, and values of.08 and below for RMSEA and SRMR indicate a good fit of the model (Hu &Bentler, 1998). Modification indices and standardized residuals were used tosuggest improvements of the model, and w2-tests were used for evaluatingimprovements and comparing competing models. In the Appendix, a Pearsoncorrelation matrix of the variables in this study is included.

RESULTS

Changes over time

Descriptive statistics are presented in Table 2. With regard to employeeabsenteeism, nonparametric rank tests (Friedman tests) showed that therewere significant differences across years for both absence frequency, w2(3,N¼ 844)¼ 16.39, p5 .001, and for total time lost, w2(3, N¼ 844)¼ 28.26,p5 .001. These differences were due to a lower frequency and less time lostat the first measurement (T1). Absence frequency, w2(2, N¼ 844)¼ 2.83, ns,and total time lost, w2(2, N¼ 844)¼ 0.39, ns, did not differ across the threeremaining years (T2–T4).


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Job satisfaction was generally high among this sample. This wasespecially the case in the first 2 years of participation in the study. At T3and T4, job satisfaction was somewhat lower. The differences betweenmeasurements were tested by GLM, and proved significant, F(3, 841)¼ 9.66,p5 .001. This means that the participants in our study on average got lesssatisfied with their job. Burnout was generally low at all four measurements.GLM showed no significant differences between measurements, F(3,841)¼ 2.39, ns.

Modelling the interrelationships

In PRELIS, the data were examined, and a covariance matrix and a matrixwith asymptotic covariances were constructed. These matrices were used asinput data for a LISREL-model. In this model, residual covariances amongburnout, satisfaction, and both absence measures (frequency and total timelost) within one measurement were estimated, but were set equal across allfour measurements. Similarly, the longitudinal effects of the four variableson each of these variables at the next measurement were estimated, but alsorestricted to be equal to corresponding longitudinal effects in followingmeasurements. For example, the effects of (1) job satisfaction at T1 on totaltime lost at T2, (2) job satisfaction at T2 on total time lost at T3, and (3) jobsatisfaction at T3 on total time lost at T4 were all restricted to be equal.

This resulted in a model with an acceptable fit, Sattora Bentler w2(98,N¼ 844)¼ 192.03, p5 .001, CFI¼ .92, RMSEA¼ .034, SRMS¼ .079.Examination of the residuals and the modification indices showed that themodel could be improved by releasing the (Tþ2) lagged relationships of thefour variables. For example, the effect of job satisfaction at T1 on jobsatisfaction at T3 is freed, and set equal to the effect of job satisfaction at T2on job satisfaction at T4. Similar lagged relationships were freed for bothabsence measures and for burnout. This model has a very good fit, SattoraBentler w2(94, N ¼ 844) ¼ 100.99, ns, CFI ¼ .98, RMSEA ¼ .009,SRMR¼ .059. The improvement in fit is substantial, Dw2(4)¼ 91.04,p5 .001. The pattern of significant regression paths (beta) is shown inFigure 2. For reasons of clarity, residual covariances (psi) are not shown inFigure 2. Table 3 contains the unstandardized parameters (which were setequal to each other across measurements), and the standardized parameters(averaged across measurements) that are estimated in this model. Figure 3contains five extracts from the model, each showing two pairs of variablesand their interrelations, with the averaged standardized coefficients.

As can be seen in Table 3 and Figure 3, there was some stability in all fourvariables. Individuals who were frequently absent in one year, werefrequently absent in subsequent years as well. Similar stability was foundfor job satisfaction and burnout. For total time lost, the stability was


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Figure

2.

ThefinalLISREL-m

odel

withthepatternofsignificantregressionpaths.

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somewhat lower than for the other three variables. These findings confirmthose of several other studies which show that frequency measures are morestable than time lost measures (Breaugh, 1981; Hammer & Landau, 1981;Ivancevich, 1985).

TABLE 3Significant regression weights (beta) and residual covariances (psi)

Unstandardized

regression weight

(beta)

Average

standardized

regression weight

T-test

(df¼ 843)

Absence frequency T

! Absence frequency Tþ10.43 0.41 14.82**

Absence frequency T

! Absence frequency Tþ20.25 0.23 7.85**

Absence frequency T

! Time lost Tþ13.05 0.13 4.83**

Absence frequency T

! Job satisfaction Tþ170.02 70.04 72.35*

Time lost T ! Time lost Tþ1 0.22 0.18 6.00**

Time lost T ! Time lost Tþ2 0.11 0.09 2.79*

Time lost T ! Job

satisfaction Tþ10.00 0.05 2.17*

Job satisfaction T

! Absence frequency Tþ170.13 70.06 73.21*

Job satisfaction T

! Job satisfaction Tþ10.45 0.43 21.76**

Job satisfaction T


Burnout T ! Time lost Tþ1 11.61 0.07 2.82*

Burnout T


Burnout T ! Burnout Tþ1 0.50 0.48 19.72**

Burnout T ! Burnout Tþ2 0.26 0.24 9.04**

Unstandardized

residual

covariance (psi)

Average

standardized

residual covariance

T-test

(df¼ 843)

Absence frequency T

$ Time lost T

16.38 0.35 17.05**

Absence frequency T

$ Job satisfaction T

70.05 70.05 73.59**

Absence frequency T $ Burnout T 0.02 0.06 3.71**

Time lost T $ Job satisfaction T 70.94 70.04 72.32*

Job satisfaction T $ Burnout T 70.03 70.18 710.63**

*p5 .05, **p5 .001.


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Figure 3. Five extracts from the LISREL-model with averaged standardized regression

weights: (A) the interrelations between job satisfaction and absence frequency; (B) the

interrelations between job satisfaction and total time lost; (C) the interrelations between

burnout and total time lost; (D) the interrelations between burnout and job satisfaction; and (E)

the interrelations between absence frequency and total time lost.


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The first research question concerned the longitudinal relationshipbetween job satisfaction and absenteeism. We predicted that low jobsatisfaction would be both an antecedent and a consequence of absenteeism.Figure 3A shows that for job satisfaction and absence frequency, thepredicted reciprocal relationship was found. Within one time measure, jobsatisfaction and absence frequency were negatively related. More impor-tantly, after controlling for earlier absence frequency, high job satisfactionreduced absence frequency in the following year. At the same time, highabsence frequency reduced subsequent job satisfaction. Thus, in line withour prediction, those who were relatively satisfied with their jobs wereabsent less often in the following year, whereas the job satisfaction of thosewho were absent relatively frequently was reduced in subsequent years. Thisresembles a vicious circle, in which the job satisfaction of those who are

Figure 3. (Continued).


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frequently absent is reduced, which leads to even higher absence frequency,which further reduces job satisfaction, and so on.

However, the predicted reciprocal relationship between job satisfactionand absenteeism was not found for total time lost. Figure 3B shows thatthere was a negative cross-sectional relationship between job satisfactionand total time lost: employees who were absent for a prolonged time wereless satisfied with their jobs. However, contrary to the prediction, thelongitudinal relationship shows that more time lost in one year enhanced jobsatisfaction a year later after controlling for job satisfaction in the previousyear. This suggests that the relatively low job satisfaction of employees whohad been absent for a prolonged time improved considerably after theyresumed their jobs. We will consider this unpredicted result in more detail inthe Discussion section.

The second research question was whether burnout could explain therelationship between job satisfaction and absenteeism. To examine thisissue, we first considered whether burnout is an antecedent of absentee-ism. In our model, there was a positive cross-sectional relationshipbetween burnout and absence frequency: Those who were frequentlyabsent were higher in burnout. However, there were no longitudinalrelationships between burnout and absence frequency. This means thatburnout cannot explain the relationship between job satisfaction andabsence frequency. With regard to time lost, a different pattern wasfound. As shown in Figure 3C, burnout influenced future time lost. Therewas no cross-sectional relationship between burnout and total time lost.But after controlling for earlier total time lost, higher burnout increasedtotal time lost in the following year. The unstandardized regression weightof 11.61 (Table 3) shows that individuals who were highest in burnout(i.e., score 1) in one year were on average 11.61 days more absent in thefollowing year than those who were lowest in burnout (i.e., score 0). Thissuggests that those high in burnout are more at risk for long-term absencein future.

To further examine whether burnout could explain the relationshipbetween job satisfaction and absenteeism, we consider whether burnout is anantecedent of job satisfaction. Figure 3D shows the interrelations betweenburnout and job satisfaction. Within one time measure, burnout and jobsatisfaction were negatively related, showing that those who experiencedburnout were less satisfied. More importantly, there also was a longitudinaleffect, showing that burnout lowered subsequent job satisfaction, control-ling for earlier job satisfaction. This can easily be understood: individualswho feel exhausted by their work are less likely to get satisfaction from theirjobs in the long run. This finding confirms the model of Iverson et al. (1998)and shows that job satisfaction is partly an attitudinal consequence ofburnout. The combination of Figures 3C and 3D shows that burnout may


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partly explain the relationship between low job satisfaction and total timelost.

There were also longitudinal relationships between the two absencemeasures.1 As shown in Figure 3E, absence frequency and total time lostwere substantially positively related within one time measure. This couldbe expected, because individuals who were not absent at all in one year,had no absence spells and lost no days. It should be noted that includingboth absence measures in one model, influences the meaning of thelongitudinal effects of absence frequency and total time lost. Longitudinaleffects of total time lost should be interpreted as effects of prolongedabsence, because these effects are corrected for the number of absencespells. Longitudinal effects of absence frequency were corrected for theeffects of total time lost, and should be interpreted as the effects of short-term absences. Table 3 shows a longitudinal effect of absence frequency ontotal time lost: a higher absence frequency in one year increased the totaltime lost in the following year. This finding suggests that frequent short-term absence could indicate a higher risk for long-term absence in future.Individuals who frequently stay away from their work may do so out of aneed to recover from the stresses and demands at their jobs. When theseshort absences do not sufficiently ameliorate these stresses and demands,long-term absence may follow.

DISCUSSION

The present study examined a heterogeneous sample of workers for 4 years,and focused on the intertwined relationships of employee absenteeism,burnout, and job satisfaction. Our first research question was whether jobsatisfaction should be considered an antecedent or a consequence ofabsenteeism. In line with our prediction, this study shows that jobsatisfaction and absence from work influence each other reciprocally.Individuals who are dissatisfied with their jobs are more likely to befrequently absent in future, and individuals who are frequently absent aremore likely to become less satisfied with their jobs. Although Steers andRhodes (1978) previously hypothesized such a cyclical relationship, thisstudy is among the first to give empirical evidence for reciprocity betweenjob satisfaction and employee absenteeism.

1It could be argued that entering both absence frequency and total time lost in one model is

not appropriate, because there is some overlap between these variables, potentially leading to

multicollinearity. Indeed, a person who has an absence frequency of 0 in a given year, will also

have a total time lost of 0 in that year. Inspection of the correlation matrix showed that the

correlations between both absence measures within each year ranged from .35 to .48.

Correlations within this range are not considered problematic.


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However, different results were found for the time lost measure ofabsence. Contrary to our prediction it was found that total time lostenhanced job satisfaction a year later. A possible explanation for thisunanticipated result is that this effect was due to individuals who wereabsent for a prolonged time. The results show that these individuals wereless satisfied with their jobs during the year in which the long-term absencefell. After resuming their work, job satisfaction increased considerably,probably to the level of job satisfaction prior to the absence spell, orperhaps to an even higher level. One interpretation of this result may bethat these individuals were happy with their jobs because they survived theprolonged absence and remained employed in their current jobs. Given thelow stability of time lost due to absence, most individuals who were absentfor a prolonged time in one year will have resumed their work in the nextyear. An additional explanation could be that the result is partly due toselection of those individuals who did survive the long-term absence.Those who had been absent for a prolonged time and who were forced toleave their jobs as a result (because of disability or dismissal) were notincluded in this study because they would have had incomplete data. Wewill further discuss this issue in relation to selective attrition from thestudy.

Another important finding concerns the role of burnout. The secondresearch question was whether burnout explains the relationship betweenjob satisfaction and absenteeism. This seems to be the case for total timelost, but not for absence frequency. In line with Iverson et al.’s (1998) model,burnout had a longitudinal effect on both job satisfaction and on total timelost due to absence. This means that in previous studies, burnout may haveoperated as an unobserved third variable, leading to spurious relationshipsbetween job satisfaction and time lost due to absence. Nevertheless, as wesaw before, an unanticipated longitudinal relationship between jobsatisfaction and time lost remained after controlling for burnout, whichmeans that burnout did not fully explain this relationship.

The third research question was whether absence frequency and totaltime lost have different antecedents and consequences. This clearly is thecase. The present study shows that burnout contributes to future time lost,whereas low job satisfaction contributes to the frequency of absence. Thissuggests that the ‘‘withdrawal’’ and the ‘‘stress’’ models of employeeabsenteeism are both valid, but for different aspects of absence.Dissatisfaction contributes to frequent withdrawal from the job, whereasindividuals high in burnout are more likely to remain absent for a prolongedtime. These findings are largely in line with (cross-sectional) findings ofBakker, Demerouti, De Boer, and Schaufeli (2003), who showed that highcommitment was related to lower absence frequency, whereas burnout wasrelated to more days lost.


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We consider our absence measures as highly valid indicators ofabsenteeism which have relevance for both the organization and theindividual. Total time lost is strongly related to loss of production and thetotal costs of absence for the organization, whereas frequency of absencecan be viewed as a measure of the disruption of work processes due toabsenteeism. Our measures do not directly represent voluntary andinvoluntary absence, although frequent short-term absence may in generalbe more voluntary than long-term absence from work. It certainly is the casethat short-term absence will often not be certified by a physician, and mayinclude cases in which the individual has a free choice of whether or not togo to work (Allegro & Veerman, 1998). Long-term absence is generallycertified by a physician, and such absence may initially be necessary giventhe physical or mental state of the worker. However, the duration of suchabsence from work is often not clearly involuntary. Recovering workers mayhave a considerable freedom to choose when they will resume their work(and to what degree). Nevertheless, the finding that burnout influences totaltime lost, and job satisfaction influences frequency of absence suggests thatthe frequency measure taps voluntary absence more than the total time lostmeasure.

This study has several strengths and limitations that need to bementioned. A noteworthy strength of this study is the longitudinal four-wave data collection in a heterogeneous sample of workers in TheNetherlands. Although causality can only be established in an experimentaldesign, the present longitudinal design shows which causal order is plausiblegiven the data.

In the present study, we focused on burnout as a potential third variableto explain the interrelationships between job satisfaction and burnout. It hasto be noted that there are many other potential third variables that were notincluded in this study. Zapf et al. (1996) argue that longitudinal researchdoes not automatically counter all these potential third variables. The effectsof third variables that generally do not change over time, such asdemographics and personality variables, are effectively ruled out bylongitudinal research. However, variables that do vary across time, suchas working conditions and health status, may still explain longitudinalresults. The present study could not include all these potential thirdvariables, which means that causal inferences cannot be made. Nevertheless,this research is a step forward in disentangling the directional and reciprocalrelationships between burnout, job satisfaction, and employee absenteeism.

A second strength is the use of registered absence data, which lowers thebias due to common method variance (Frese & Zapf, 1988). Many studiesonly obtain subjective measures of both the central outcome variables(absence measures) and their psychosocial correlates (satisfaction, burnout),and do so in a single questionnaire. This may lead to inflated correlations


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due to answering tendencies and hypothesis guessing among respondents.Using archival records of absence precludes such inflation of interrelations.

A limitation of this study is that there was evidence for selective attritionin this study. Only participants with full data on all four measures wereincluded in this study. At the first measurement, included participants weresomewhat higher in job satisfaction, lower in burnout, were less frequentlyabsent from their jobs, and lost less days due to absence than excludedparticipants. Part of this selective attrition may be due to job turnover ofdissatisfied participants. Moreover, participants who were absent frequentlyor for a prolonged time may have been dismissed or put on a disabilitypension. This means that the remaining participants were both moresatisfied and healthier than those who left their company (and dropped outof the present study). Another explanation could be that dissatisfied workersare less motivated to repeatedly fill out a questionnaire, which may beregarded as organizational citizenship behaviour (Organ, 1988). A relatedissue is that the least satisfied workers perhaps did not participate in thisstudy at all. We therefore have to be careful in generalizing our results to theoriginal sample, let alone to the whole working population of TheNetherlands. Following the earlier reasoning, selective attrition and selectiveparticipation may have led to a restriction of range for satisfaction, whichcould mean that smaller effects are found in the present study than wouldexist in the larger population.

Another limitation of this study is that the found longitudinal effects aresmall. This is by no means unexpected. Hackett’s (1989) meta-analysisshowed a small (but consistent) relationship between job satisfaction andabsenteeism. Moreover, the longitudinal effects of one variable on the otherare established after controlling for earlier measures of the dependentvariable, which may preclude stronger longitudinal effects. Finally, andmost importantly, the measurements are steadily spaced one year apart, anddo not necessarily correspond to critical incidents that may lead toabsenteeism, or may lower or heighten job satisfaction or burnout. Thismeans that only generalized effects of job satisfaction and burnout onabsenteeism and vice versa can be found in this study. Prospective, largescale studies like this one should therefore be complemented with small scalenatural experiments and case studies of the changes in these variables priorto, during and after critical incidents, such as an individual’s long-termillness, a work conflict, reorganizations, or downsizing. These in-depthstudies may be necessary to further our understanding of the interrelation-ships between job satisfaction, burnout, and absenteeism.

It should further be noted that job satisfaction and burnout are notmeasured with validated scales in this study. Job satisfaction was measuredwith a single item, instead of with an available multiitem scale. Burnout wasmeasured with multiple items that were derived from a validated scale, but


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used dichotomized response scales instead of the original 7-point scales.Despite this suboptimal measurement, our job satisfaction item proved tohave a high test-retest reliability, which indicates that it adequatelymeasured a construct that was stable in time. Moreover, the burnout itemsformed a homogeneous scale with high test–retest reliability. If anything,more reliable scales of these constructs would have been likely to heightenthe interrelations that were found in this study, and may have led to strongerlongitudinal effects as well.

One practical implication of our study is that future long-term absence isto some extent predictable based on the past absence frequency and burnoutof a worker. This means that a company may identify high-risk groups ofworkers to target individual interventions to prevent future long-termabsence (e.g., Van Dierendonck, Schaufeli, & Buunk, 1998). Anotherpractical implication would be that when a company is plagued by frequentshort-term absenteeism of personnel, it should focus on the role of jobsatisfaction and related constructs. Job dissatisfaction and absencefrequency are reciprocally related, and enhance each other as in a viciouscircle. Such a circle may be broken by intervening at either variable: Onecould try to increase job satisfaction or to decrease absence frequency byinterventions at the organizational or individual level (e.g., Bond & Bunce,2001).

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Original manuscript received 24 January 2007

Revised manuscript received 28 January 2008

First published online May 2009


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antecedents and consequences of employee absenteeism: a longitudinal perspective on the role of job...

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