Teachers’ acceptance ofabsenteeism: towards developing

a specific scaleOrly Shapira-Lishchinsky and Gamal Ishan

Department of Educational Administration, Leadership and Policy,School of Education, Bar-Ilan University, Ramat-Gan, Israel

Abstract

Purpose – This study aims to develop and validate a measure of a specific attitude toward teachers’absenteeism that predicts this behavior more accurately than other general measures of job attitudes.Design/methodology/approach – Participants were 443 teachers from 21 secondary schools in Israel.In the first phase, the teachers answered anonymous questionnaires related to their general attitudes andtheir specific attitude through “absenteeism acceptance”. In the second phase, each teacher submittedcopies of his half-year absenteeism records six months after the end of the first phase.Findings – The authors used CFA to cross-validate the different job attitudes measures. Theyconfirmed the construct validity of “absenteeism acceptance” through convergent and discriminantvalidity, finding relatively weak negative relationships between “absenteeism acceptance” and thegeneral job attitudes. The criterion validity and predictive validity of the new measure was confirmedby intercorrelations that were found to be relatively stronger between “absenteeism acceptance” andthe two measures of absenteeism (frequency, duration) than between the general job attitudes andthese two measures. Quasi-Possion regressions indicated that “absenteeism acceptance” emerges as abetter predictor for both of the absenteeism measures than other general job attitudes.Practical implications – This new measure will benefit schools and principals by allowing them toidentify potential absenteeism antecedents and enable early intervention.Originality/value – Whereas past research on work absence focused primarily on general attitudeantecedents, the present study addresses a specific “absenteeism acceptance” measure. This measurecan be advantageous in both understanding and predicting voluntary absenteeism more accuratelythan general attitude measures.

Keywords Absenteeism, Collective self-efficacy, Organizational commitment,Organizational justice, Schools, Teachers

Paper type Research paper

IntroductionWork absenteeism is one of the major problems of human resource management inmost organizations. It is “the lack of physical presence at a behavior setting when andwhere one is expected to be” (Harrison and Price, 2003, p. 204). Employee replacementcosts and decreased productivity make up the direct financial costs of absenteeism. Tothese costs we must add indirect ones, such as the difficulties of replacing highlyskilled employees who provide an essential service with equally trained personnel,leading to underperformance (Gaudine and Saks, 2001; Koslowsky, 2009).

Work absenteeism is a leading problem in educational institutions as well. In the USA,according to the District Management Council (2004), teachers nationally are absent fromthe classroom an average two weeks each year due to illness, personal days, and otherexcused absences such as staff development. Podgursky (2002) found that when teacherabsences are compared with absences in other professions, teacher absences are almosttwice as frequent. Pay for absent teachers in the USA was estimated at $2 billion per year(Miller et al., 2008) and £300 million in the UK (Bowers and McIver, 2000).

The current issue and full text archive of this journal is available atwww.emeraldinsight.com/0957-8234.htm

Received 31 December 2011Revised 17 March 201218 May 201228 May 2012Accepted 29 May 2012

Journal of EducationalAdministrationVol. 51 No. 5, 2013pp. 594-617r Emerald Group Publishing Limited0957-8234DOI 10.1108/JEA-12-2011-0115

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Data from studies conducted in Ecuador shows that the financial loss was nearly$16 million a year while data from India shows $2 million per year lost due to teacherabsenteeism (Banerjee and Duflo, 2005; Duflo and Hanna, 2005). The overall cost ofteacher absenteeism in Israel in 2002-2003 totaled $53 million, an estimate reached bycombining the salaries of absent teachers with those of the teachers used to replacethem (Rosenblatt and Shirom, 2006). Apart from the financial cost, work absenteeismin schools has a negative effect on the quality of education by reducing bothachievement levels and student attendance levels in school (Bruno, 2002; Miller et al.,2007; Woods and Montagno, 1997).

Recent reviews of the organizational behavior literature and especially in theeducational domain emphasize absenteeism as a variable related to general jobattitudes, such as organizational justice and organizational commitment (Bowers, 2001;Felfe and Schyns, 2004; Martocchio and Jimeno, 2003; Myburgh and Poggenpoel, 2002).These studies showed that teachers with negative attitudes toward their workplacereact by absenting themselves from work.

Based on Ajzen and Fishbein’s (1977) model as it concerns the “attitude-behaviorsequence,” we expect that a specific attitude toward absenteeism will more accuratelypredict absenteeism behavior than general job attitudes (e.g. organizational commitment,organizational justice, and collective efficacy). Understanding and better predictingabsenteeism can benefit schools by allowing them to identify potential absenteeismantecedents, intervene early, and prevent more progressive forms of withdrawal.

For this purpose, we developed a measure of acceptance toward voluntaryabsenteeism that should better predict absenteeism behavior. Although extensiveresearch has been conducted on absenteeism (e.g. Biron and Bamberger, 2012; Johns,2003; Koslowsky, 2009; Sagie, 1998), there is no adequately validated measure of“absenteeism acceptance” in the current literature. Therefore, first, we usedconfirmatory factor analysis (CFA) in order to cross-validate the general jobattitudes measures. Then, a content validation approach was used to construct themeasure. We then gathered preliminary evidence of construct validity by examiningthe relationship of the new measure “absenteeism acceptance” with other constructs,specifically general job attitudes. Then we examined the criterion validity and thepredictive validity by investigating the ability of “absenteeism acceptance” to predictfuture absenteeism behavior above and beyond general attitude measures.

Theoretical backgroundAttitude-behavior correspondence: Ajzen and Fishbein’s (1977) theoryAlthough the literature provides rich theoretical and empirical studies on employees’absenteeism behavior, far more should be done to provide a better understanding of thesimilarities and differences among general predictors of absenteeism behaviors, becauseprevious studies investigating the relationship between general job attitudes (e.g. jobsatisfaction, organizational commitment) and absenteeism behavior showed conflictingfindings across studies (Allen and Meyer, 1996; Brown, 1996; Cohen, 1998; Goldberg andWaldman, 2000; Martocchio, 1992). Moreover, in a case where a significant correlation wasobserved, it was, at best, low to moderate, thus the results have been disappointing (Blau,2000; Carmeli, 2005; Koslowsky, 2009; Koslowsky et al., 1997).

These inconsistent findings point to the need to develop better measures to serve aspredictors of voluntary absenteeism. In retrospect, these inconsistent findings are notsurprising when considered by means of Ajzen and Fishbein’s (1977) correspondencetheory regarding attitude-behavior relationships. According to their approach,

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attitudes toward behaviors are expected to predict these behaviors if the target andaction elements of the attitudinal entity are identical with those of the behavioral entity.The relations between attitude and behavior tend to increase as the attitudinal andbehavioral entities come to correspond more closely in terms of their target and actionelements. Based on 54 previous studies, Ajzen and Fishbein (1977) argued “that lowand inconsistent attitude-behavior relations are attributable to low or partialcorrespondence between attitudinal and behavioral entities” (p. 913).

Consequently, to avoid a low level of correspondence, one cannot expect general jobattitude measures (i.e. organizational justice, organizational commitment, collectiveefficacy) to strongly predict a specific behavior such as voluntary absence, becausethere may be partial or low correspondence between the attitudinal predictor and thebehavioral criterion. Instead of relying on these general attitudes, a specific attitudetoward absenteeism should be used to more accurately predict voluntary absenteeism.Moreover, a positive general attitude toward the organization does not necessarilysignify that the employee believes that it is important to appear regularly at theworkplace (Koslowsky, 2009).

Toward examining the construct validity of “absenteeism acceptance”Construct validity is the extent to which the concept or construct to be measured wasactually measured, and refers to whether a scale measure correlates with the theorizedpsychological construct. Construct validity evidence includes statistical analyses of theinternal structure of the test (Pennington, 2003). Evaluation of construct validity requiresconvergent validity, that is, the correlations of the new measure must be examined inregard to other variables that are expected to be related to the new measure based ontheoretical grounds; and discriminant validity, which describes the degree to which thedeveloped measures are not similar to other variables that it theoretically should not besimilar to these variables (American Educational Research Association, 1999).

Therefore, in the following sections we will present the theoretical backgroundbehind the relationship between general job attitudes and “absenteeism acceptance.”

The relationship between general job attitudes and “absenteeism acceptance”. Sagie(1998) distinguished between two basic types of absenteeism: voluntary absenteeism,which is normally under the direct control of the employee and is frequently utilized forpersonal issues; and involuntary absenteeism, which is usually beyond the employee’simmediate control (e.g. bereavement leave). This distinction is important because theindividual’s attitudes impact only on voluntary absenteeism and is therefore the focusof our proposed study.

In this study we focus on general attitudes such as organizational justice, organizationalcommitment, and collective efficacy which in previous studies were found to be related toteachers’ behaviors in school, including absenteeism (e.g. Shapira-Lishchinsky andRosenblatt, 2009; Imants and Van Zoelen, 1995; Rosenblatt et al., 2010). Based on Ajzen andFishbein’s (1977) theory, attitudes may lead to behaviors, i.e. “absenteeism acceptance”may relate to voluntary absenteeism, thus, these general attitudes may relate not only tovoluntary absenteeism, but also to “absenteeism acceptance.”

Organizational justiceis used to describe equity in the workplace (Greenberg,1995) and is used as a measure of how employees’ perceptions of equity aredetermined. Organizational justice research has focussed on two key dimensions:distributive justice, which refers to the fairness of the outcomes an employeereceives (Adams, 1965) and procedural justice, which describes the fairness ofthe procedures used to determine organizational outcomes (Pillai et al., 2001).

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We anticipate that perceptions of justice may affect teachers’ “absenteeism acceptance.”Thus, if a teacher perceives that the school procedures or/and rewards in schools are notfair, there will be a negative attitude toward work. We then expect a negative relationshipbetween teachers’ perceptions of justice and their “absenteeism acceptance,” such thatthe higher the teachers’ perception of organizational justice, the less likely the attitude of“absenteeism acceptance” at the workplace.

Meyer and Allen (1997) identified two central dimensions of organizationalcommitment. Affective commitment refers to teachers’ emotional attachment to theorganization, and their identification and involvement with it. Normativecommitment reflects their sense of obligation to continue working for the school.When teachers identify with, are involved in, and feel obligated toward anorganization, they will exert their best efforts and try not to be absent from work.Thus, organizational commitment is expected to have a negative relationship withabsenteeism attitude.

Collective efficacy beliefs are a “group’s shared belief in its conjoint capabilities toorganize and execute the courses of action required to produce given levels ofattainments” (Bandura, 1997, p. 477). As a shared belief about the influence the schoolitself can have on student achievement, collective teacher efficacy is the product of theinteractive dynamics of the group members and the emotional tone of the organization(Goddard et al., 2000), which means that collective teacher efficacy is a characteristic ofschools as experienced by teachers. In this way, the scale of collective efficacy beliefitems are worded to measure efficacy as a school-level attribute in order to captureindividuals’ perceptions of school capability (Goddard, 2001).

Collective teacher efficacy differs from a teacher’s individual sense of efficacy,in that it is a group attribute rather than the aggregate of many individual teachers’self-efficacy beliefs (Bandura, 1997). Teachers’ self-efficacy beliefs are based onperceptions of individual classroom performance, whereas collective teacher efficacybeliefs are social perceptions based on an assessment of the capability of the schoolfaculty as a whole (Goddard et al., 2000). In this way, the collective efficacy scalediffers from other teacher self-efficacy scales as teachers are asked about theirperceptions of the collective, rather than their personal beliefs about their ownindividual efficacy.

Collective teacher efficacy constitutes a powerful factor which affects different arenas ofthe school organization and influences attitudes, as well as affective, motivational, andbehavioral aspects of teacher functioning within the school (Schechter and Tschannen-Moran, 2006). Thus, collective efficacy beliefs influence how people feel, think, act, andmotivate themselves. It can be argued, therefore, that a person with a sense of highcollective efficacy will have a negative attitude toward absenteeism at work.

In summary, we expect that the above-mentioned general job attitudes will berelated to “absenteeism acceptance” (convergent validity). However, in light of Ajzenand Fishbein’s (1977) theory regarding the non-specific of these attitudes toabsenteeism behaviors, we expect the relationships to be weak (discriminant validity).

This assertion leads to our first hypothesis:

H1. There will be negative weak relationships between “absenteeism acceptance” and:

(1) organizational justice (procedural/distributive);

(2) organizational commitment (affective/normative); and

(3) collective efficacy.

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Toward examining the “criterion validity” and “predictive validity” of “absenteeismacceptance”Criterion validity is a measure of how well one variable or set of variables predicts anoutcome based on information from other variables (Pennington, 2003). In this study, inorder to test the criterion validity, first we assess the relationships between the generalattitudes measures and voluntary absenteeism. Then, we compare the new measure“absenteeism acceptance” with other measures already held to be valid, by assessingthe ability of the “absenteeism acceptance” measure to predict voluntary absenteeismbetter than the general job attitudes measures (organizational justice, organizationalcommitment, collective self-efficacy).

Because in this study we collect the records of absenteeism at a later point in time,then we also refer to “predictive validity” (Messick, 1995). In the following sections,we will discuss the relationship between general job attitudes and voluntaryabsenteeism in order to provide essential background theory toward examining thecriterion validity of our new measure.

The relationship between general job attitudes and voluntary absence. According tothe “attitudes-behavior sequence theory” proposed by Ajzen and Fishbein (1977,1980) and Mueller (1986), attitudes which are normally directional (positive ornegative) lead to behaviors (positive or negative). Studies show that people whobehave in different ways also differ predictably in their attitudes. Positive attitudeslead to good performance and negative attitudes lead to poor performance. It thenfollows that general job attitudes (negative or positive) will lead to voluntaryabsenteeism behavior (high or low).

For example, studies on organizational justice show consistently that employeesexpect organizational decisions to be fair, and that they engage in negative reactions tothe organization when they perceive that they have been subject to unjust outcomes(Greenberg, 1995; Moorman, 1991). From this perspective, absenteeism behavior is onemeans used to redress an inequitable employment relationship (Blau et al., 2004;Carraher and Buckley, 2008).

Regarding organizational commitment, previous studies indicate that teacherswho are committed to their school make outstanding efforts on its behalf and try tocontribute to its success by reducing their voluntary absenteeism. Gaziel (2004) foundthat teachers who express a high level of commitment to their school tend tovoluntarily absent themselves from school less frequently. The Luchak and Gellatly(2007) study showed that employees who display high organizational commitmenthad a lower rate of absenteeism frequency. Cohen (2003), Somers (1995), and Meyeret al. (2002) provided more direct evidence for the relationship between affectivecommitment and work absence/attendance.

Collective efficacy is a belief about the capability of the group to organize andachieve a stated goal. Previous studies indicate that low collective efficacy amongteachers result in lower effort and persistence (Tschannen-Moran and Woolfolk Hoy,2007). Thus we assume that voluntary absenteeism may be a reflection of a sense oflow capabilities to attain a desired level of performance.

Based on previous studies (Bem, 1970; Koslowsky, 2009; Leigh and Lust, 1988;Rokeach, 1973) positing that attitudes serve as one of the determinants of voluntaryabsenteeism, we propose that teachers who harbor a sense of low organizationaljustice, low organizational commitment, and low collective efficacy are also morelikely to increase their work absence. Accordingly to Ajzen and Fishbein’scorrespondence theory, this leads us to expect nothing more than weak relationships

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between the general job attitudes and absenteeism behaviors. This leads to oursecond hypothesis:

H2. General attitude measures (organizational justice, organizational commitment,collective self-efficacy) will be unrelated or have weak negative relationshipswith voluntary absenteeism behaviors.

Following Ajzen and Fishbein (1977), Steers and Rhodes (1978) highlight theimportance of seeing a specific attitude as influencing a specific behavior. Theirtheoretical process model of attendance proposed that a general job attitude(satisfaction with job situation) indirectly affects a job behavior (employee attendance)through a more specific intervening variable (attendance motivation). Together, themodels proposed by Ajzen and Fishbein (1977) and Steers and Rhodes (1978) serve asthe foundation for our development of a measure of “absenteeism acceptance,” in theanticipation that it will predict actual absenteeism behavior more accurately than othergeneral job attitudes. This leads to our third hypothesis:

H3. “Absenteeism acceptance” predicts voluntary absenteeism better than existinggeneral attitude measures (organizational justice, organizational commitment,collective self-efficacy).

MethodStudy sampleParticipants were 443 teachers (66 percent average response rate in each school) from 21secondary schools belonging to one of the districts of the Ministry of Education in northernIsrael. The average number of teachers in each school was 21.10 (SD¼ 5.54). The teachersincluded in the study were only those who had worked in the school more than one year soas to ensure that all respondents had had sufficient time to develop perceptions andattitudes about their schools. Women represented 66.4 percent of the sample. Participants’average age was 42.12 years (SD¼ 8.42). Average teaching seniority was 12.18 years(SD¼ 9.25). The majority of teachers (71.6 percent) were tenured; the others were employedthrough temporary contracts. 69.0 percent of the teachers had a Bachelor’s degree, and 15.1percent held a Master’s degree; the rest had non-academic degrees. These characteristics,roughly, represent the composition of the teacher population in the district under study,and in Israeli secondary schools in general (Israel Central Bureau of Statistics, 2008).

Data collectionAfter obtaining the approval of the Ministry of Education and the ethics committee inour university to distribute the questionnaires and to collect the absenteeism recordsfrom each school, letters explaining the objectives and methods of the study were sentto all inspectors in the district to encourage principals to allow their schools toparticipate in the study. The 21 schools included in the study were those whoseprincipals agreed to cooperate.

Data collection was performed using a two-phase design. In the first phase, duringtheir free time spent on school premises, the teachers answered anonymousquestionnaires related to their attitudes (e.g. organizational justice, organizationalcommitment, and collective efficacy, absence acceptance) as they perceive them andtheir personal background. The questionnaire includes a cover page describing the

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study goals and the researchers’ obligation to maintain anonymity according to theAmerican Psychological Association (2002). This was a contributing factor in obtainingthe teachers’ consent to participate and may explain the fact that the average response ratein each school was as high as 66 percent.

Each teacher put the questionnaire into an envelope, entered a code number on theenvelope, and gave the envelope to the secretary of the participating school. In thesecond phase, which was conducted half a year later, every teacher put copies of theirabsence records (without identifying names), which were supplied by the schoolsecretary, together with the original code, in an unmarked envelope and again gave theenvelope to the school secretary. The codes helped the researchers link thequestionnaires from the first phase to relevant data from the second phase.

Variables and measuresVoluntary absenteeism. Absenteeism was measured by school records of frequency ofincidents of absences (number of absence incidents over six months) and by duration ofabsence (total number of absence days over six months). We omitted all teachers’absenteeism caused by definitively involuntary absence reasons (i.e. maternity leave,mourning), and tested all other absenteeism records which might be consideredvoluntary (including sickness, because in Israel, in order to get pay for a day ofabsence, the teacher must supply a medical certificate or declaration of sickness).

It is generally believed that absenteeism frequency is the best measure of voluntaryabsenteeism, whereas absenteeism duration is the best reflection of involuntaryabsenteeism (Blau et al., 2004; Sagie, 1998). For example, consider a case where we havetwo teachers, both of them absent ten days in one academic year. However, the first one isabsent in one event lasting ten consecutive days while the other teacher is absent in fiveevents, two days in each event. In this case we assume that the absenteeism of the firstteacher is involuntary, because we expect that a teacher would never choose to be absentfor ten consecutive days in one event. Thus, if a teacher is absent for so many days in oneevent, it may be due to an involuntary reason (i.e. mourning period). However, we mayconsider the absenteeism of the second teacher as voluntary absenteeism, because ateacher may deliberately choose to be absent for short durations of time.

In any case, previous studies (e.g. Shapira-Lishchinsky and Even-Zohar, 2011;Koslowsky, 2009) indicate that sometimes it is difficult to classify a particular incident inthe appropriate category (voluntary absenteeism/involuntary absenteeism). For example,how would we classify a teacher who is absent from school in order to go job-hunting afterreceiving a letter of dismissal for the following academic year? Thus, although we assumethat attitudes may significantly affect measures of voluntary absenteeism more than theyaffect measures of involuntary absenteeism behaviors, the present study examines bothabsenteeism frequency and absenteeism duration measures. Support for ourmethodological approach may be provided by the relatively high correlation foundbetween absence frequency and absence duration (r¼ 0.714, po0.001).

A six-month period of absence frequency reports was determined to be a reasonabletime-span for which schools normally retain such records ( Johns, 1994). In addition, a six-month time-span produces a valid picture of teacher absence, because it represents half ofa work year (Shapira-Lishchinsky, 2012; Shapira-Lishchinsky and Rosenblatt, 2010).

Assessment of the study measuresThe key notion underlying factor analytic models is that some variables of theoreticalinterest cannot be observed directly; these unobserved variables are termed latent

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variables (LV). Information related to them can be obtained indirectly by noting theireffects on observed variables believed to represent them. The best known statisticalprocedure for investigating relations between sets of observed and LV is factor analysis.There are two basic types of factor analyses: exploratory factor analysis (EFA) and CFA.EFA is most appropriately used when links between the observed variables and theirunderlying factors are unknown or uncertain. One logical application of EFA would be inthe development of a new assessment measure (Bryant and Yarnold, 1995). Therefore, inthe present study we used EFA to develop the scale “absenteeism acceptance.”

In contrast, CFA is appropriately used when the researcher has some knowledge ofthe underlying LV structure. Based on empirical research, the researcher postulatesrelations between the observed measures and the underlying factors a priori and thentests this hypothesized structure statistically (Byrne, 2005). Therefore, in the presentstudy, we assessed the general job attitudes (organizational commitment,organizational justice, collective efficacy) using CFA.

The correlations used for the input were estimated based on the pairwise availabledata to overcome the problem of missing data that could have led to biased conclusionsdrawn from the study data (Byrne, 2005).

General job attitudes. Organizational justice. This 21-item measure was based onMoorman (1991) and was translated into Hebrew by Rosenblatt and Hijazi (2004). Basedon the theoretical background, two dominant types of justice (distributive and procedural)were selected. Distributive justice assessed the fairness of various school outcomes,including pay level, work schedule, and work load (seven items, a¼ 0.87, 44 percent ofexplained variance). One sample item is: “Overall, the rewards I receive here are quite fair.”Procedural justice assessed the degree to which job decisions included mechanisms thatensured the acquisition of accurate and unbiased information, a voice for teachersin school matters, and an appeal process (six items, a¼ 0.92). One sample item is:“My principal makes sure that all teachers’ concerns are heard before school decisions aremade.” Response options ranged from 1¼ strongly disagree to 5¼ strongly agree.

Organizational commitment. This measure was based on Meyer and Allen’s (1997)original 22-item measure focussed on two dominant types of commitment (affectiveand normative) according the theoretical background. Affective commitment items(e.g. “I really feel as if this school’s problems are my own”) addressed the teachers’perceptions of their reasons for wanting to remain in their school (eight items,a¼ 0.76). Normative commitment items (One of the main reasons I continue to work inthis school is that I believe loyalty is important) addressed the teachers’ perceptions ofthe reasons why they ought to remain in their school (five items, a¼ 0.70). Responseoptions ranged from 1¼ strongly disagree to 5¼ strongly agree.

Teachers’ sense of collective efficacy. This measure was based on Schechter andTschannen-Moran (2006) who translated from English to Hebrew the Tschannen-Moran and Barr (2004) measurement, a 12-item measure that has two subscales:instructional strategies and student discipline. Instructional strategies (e.g. “How muchcan teachers in your school do to produce meaningful student learning?”) addressedthe teachers’ perceptions of different tools available in schools to improve the quality ofinstruction (six items, a¼ 0.78) and student discipline (e.g. “How much can schoolpersonnel in your school do to control disruptive behavior?”) addressed the teachers’perceptions of tools available in schools to manage the classroom (six items, a¼ 0.88).In the Israeli (Hebrew) version, the response set used a five-point response set with thesame anchors as the English version (nothing, very little, some degree, quite a bit, agreat deal at 1, 2, 3, 4, and 5, respectively).

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To estimate the validity of the general job attitudes, we used CFA which belongs to aclass of methodology known as structural equation modeling (Kline, 1998). Figure 1illustrates the CFA model which is schematically portrayed as path diagrams.

For the purpose of this study, the three-factor model shown in Figure 1 was basedon data representing item scores for the general job attitudes. A review of the relatedgoodness-of fit indexes revealed an exceptionally well-fitting model as indicated by thefollowing: comparative fit index (CFI)¼ 0.994 (X0.93; Hu and Bentler, 1999);standardized root mean square residual (SRMR)¼ 0.045 (o0.08; Hu and Bentler, 1999);root mean square error of approxidence (RMSEA)¼ 0.049 (o0.05; Browne and Cudeck,1993). The overall w2 value was 13.04, p40.05, with 6 df. In this study, all b’s werefound relatively high and statistically significant.

Convergent and discriminant validity are frequently considered to be additional facetsof construct validity (e.g. Bollen, 1989). Average variance extracted (AVE), a measure of theshared variance in a LV, was calculated (according to the Appendix) to check the LV’sconvergent and discriminant validity (DeVellis, 1991). In this study, CFA demonstrates:AVEorganizational commitment¼ 0.70; AVEorganizational justice¼ 0.59; AVEcollective efficacy¼ 0.73which are adequate measures of convergent validity (AVEX0.5; Nunnally, 1993).In addition, the correlations between the LV’s (organizational commitment, organizationaljustice, and collective efficacy) were found to be o0.7, and the squared correlations

Notes: Values above rectangles present percentage explained variance.�2 = 13.040, df = 6, p= 0.062; SRMR = 0.045; RMSEA = 0.049; NFI = 0.989;CFI = 0.994. ***p<0.001

Organizationalcommitment

Organizationaljustice

Collectiveefficacy

Affectivecommitment

Normativecommitment

Distributivejustice

Normativejustice

Instructionalstrategies

Studentdiscipline

E1

E2

E3

E4

E5

E6

0.84***

0.82***

0.66***

0.86***

0.78***

0.92***

0.71

0.70

0.44

0.74

0.60

0.84

0.56

0.570.51

Figure 1.Confirmatory factoranalysis model of thegeneral job attitudes

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between two LV’s were less than either of their individual AVE’s, which are frequentlyaccepted as evidence of discriminant validity (Bagozzi and Phillips, 1982).

Absenteeism acceptance. We based our questionnaire on Foust et al. (2006) whodeveloped and validated a measure of an individual’s lateness attitude among 130undergraduate students and 298 employees working at a university and health carefacility. In this study we analyzed whether we can apply this measure to another typeof withdrawal behavior, namely, “acceptance of absenteeism.” We based our analysison the withdrawal behavior approach which includes both lateness and absenteeismbehaviors (Koslowsky, 2009). Therefore, we posit that we may use this measure as abasis for developing a specific measure for “absenteeism acceptance.”

Content validity, construct definition, and items generation of “absenteeism acceptance”.Content validity is a non-statistical type of validity, referring to the extent to which ameasure covers all facets of a given construct (American Educational ResearchAssociation, 1999). According to Foust et al. (2006), we may define “absenteeismacceptance” as how one feels and thinks about being absent from work, and this measuremay include items that focus specifically on affective and cognitive reactions toabsenteeism behavior. A measure has a content validity through careful selection of itemsreflecting the knowledge actually required for testing the measure. High content validitymay be achieved through experts reviewing the test specifications and selecting the mostrepresentative items (Anastasi and Urbina, 1997). Therefore, the study items wereformulated by both authors, one who has extensive training in educational administration,and the other who has extensive knowledge regarding absenteeism behavior literature andmeasurement development techniques.

There is strong theory and evidence supporting affective and cognitive componentsas separate aspects of attitude structures (Fabrigar et al., 1999). Therefore, wegenerated items according to this categorization scheme. Following Fabrigar et al.(1999) “lateness attitude” measure, items were generated to fully capture the contentdomain of what is included in the teacher’s attitude toward absenteeism at work. Wefocus on three content domains: first, an individual’s affective response to his ownabsenteeism from work (three items); second, an individual’s affective response to hisco-workers’ absenteeism from work (three items); and finally, an individual’s beliefs orcognitions in general about work absenteeism (three items). Three items were re-formulated for each content domain, reflecting various levels of intensity. We usedsome negative items because previous studies (e.g. Idaszak and Drasgow, 1987) arguedthat negatively worded items have the potential to minimize response bias.

Response scale development. It has been demonstrated (e.g. Lissitz and Green, 1975)that coefficient a reliability improves with the use of five Likert scales. Additionally, wechose to use response options ranging from 1¼ strongly disagree to 5¼ strongly agreebecause we thought it would generate sufficient variance for statistical analyses.

Scale development results. Using factor analysis, we then examined the three-factorsolution to identify which of the nine originally developed items should be used in thefinal absence attitude measure. Two specific criteria were used: loading 40.70 on theirrespective dimension and cross-loading o0.30 on the other dimensions (Hinkin, 1995).The items are presented in Table I.

Since teacher responses on the resulting nine items “absenteeism acceptance”measure yielded an internal consistency reliability of 0.58 for the third factor (generalcognitions concerning absenteeism), and an internal consistency reliability of 0.623 forthe entire measure “absenteeism attitude,” we decided to omit the third factor. Thus, thefinal measure of “absenteeism acceptance” that we used to test our study hypotheses

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includes two dimensions. First, an individual’s affective response to his co-workers’absenteeism from work. One sample item is: “My co-workers let me down when theyare absent from work (three items, a¼ 0.79, 23.84 percent of the explained variance).Second, an individual’s affective response to his own absenteeism from work. Onesample item is: “I feel guilty when I am absent from school” (three items, a¼ 0.73, 22.19percent of the explained variance).

ResultsHypotheses results regarding construct validityDescriptive statistics and intercorrelations for the “absenteeism acceptance” and othermeasures for the employee sample are reported in Table II.

H1 argued that negative weak relationships will be found between “absenteeismacceptance” and general job attitudes such as organizational justice, organizationalcommitment, and collective efficacy. Based on examining bivariate correlations, wefound, as we had hypothesized, weak negative relationships in most of the correlationsbetween the general job attitudes and the newly developed “absenteeism acceptance”and its two dimensions.

More specifically, the general job attitudes correlated, respectively, to “absenteeismacceptance,” “affective response to own absence” and to “affective response to co-workers’absence.” Specifically, affective commitment (r¼�0.216, po0.001; r¼�0.216, po0.001;

Items

Affective reaction toco-workers’

absenteeism (factor 1)

Affective reactionto own absenteeism

(factor 2)

Cognitionsconcerning

absenteeism(factor 3)

1 My co-workers let me downwhen they are absent 0.743 0.234 �0.017

2 I believe my co-workersshould never be absent 0.871 0.067 0.071

3 It is unfair when my co-workers absent themselvesfrom work 0.833 0.176 �0.014

4 It is important to me toalways be present 0.055 0.775 �0.073

5 It aggravates me when I amabsent from work 0.194 0.804 �0.092

6 I feel guilty when I am absentfrom work 0.232 0.767 0.003

7 Absence from work should beacceptable as long as thework gets done 0.162 �0.111 0.738

8 Occasional absence fromwork should be acceptable �0.141 0.150 0.741

9 I find it acceptable to beabsent from work once amonth 0.015 �0.189 0.723

a 0.791 0.728 0.580Explainedvariance(%) 23.84 22.19 18.17

Table I.“Absenteeism acceptance”items, factor loadings,internal consistencyreliability (Cronbach’s a)and explained variance

604

JEA51,5

MS

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0.26

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264

1.81

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bse

nte

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3.91

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––

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n¼

443.

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rnal

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reli

abil

ity

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mat

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01;

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0.00

1

Table II.Means, standard

deviations, and reliabilitycoefficients (a) of the study

variables

605

Teachers’acceptance of

absenteeism

r¼�0.120, po0.05), normative commitment (r¼�0.225, po0.001; r¼�0.256, po0.001;r¼�0.127, po0.01), procedural justice (r¼�0.228, po0.001; r¼�0.234, po0.01;r¼�0.150, po0.001), distributive justice (r¼�0.212, po0.001; r¼�0.119, po0.05;r¼�0.226, po0.001). Regarding collective efficacy, the dimension of instructionalstrategies was related to “absenteeism acceptance” (r¼�0.126, po0.001) and to “affectivereaction to the subject’s own absence” (r¼�0.151, po0.01). The dimension “studentdiscipline” was related only to “absenteeism acceptance” (r¼�0.098, po0.05). Thesefindings indicate that, in general, affective reaction to one’s own absence related to thegeneral job attitudes more consistently than did affective reaction to co-workers’ absence.

Hypotheses results regarding “criterion validity” and “predictive validity”H2, which argued that general attitude measures will be unrelated or have weak negativerelationships with voluntary absenteeism behaviors, was supported. Based on previousstudies, indicating that sometimes it is difficult to distinguish between voluntaryabsenteeism and involuntary absenteeism (Koslowsky, 2009), we examined this hypothesiswith regard both to absenteeism frequency and to absenteeism duration measures.

Procedural justice was weakly related to absenteeism frequency (voluntaryabsenteeism) (r¼�0.166, po0.001), slightly higher than the weak relationship thatwas found between procedural justice and absenteeism duration (r¼�0.158, po0.01),while distributive justice was found weakly related only to absenteeism frequency(r¼�0.110, po0.05) and not to absenteeism duration. Affective commitment was notfound related either to absenteeism frequency or to absenteeism duration, while normativecommitment was found weakly negatively related to absenteeism duration (r¼�0.106,po0.05). Both dimensions of collective efficacy (instructional strategies, student discipline)were found significantly and negatively related to absenteeism frequency (r¼�0.124,po0.05; r¼�0.110, po0.05 correspondingly) and not to absenteeism duration. Ingeneral, with regard to H2, we find that more general job attitudes were found related toabsenteeism frequency than to absenteeism duration.

H3 argued that “absenteeism acceptance” predicts voluntary absenteeism betterthan other general attitude measures (organizational justice, organizationalcommitment collective self-efficacy). We found, that in the majority of the casesexamined, our hypothesis was supported. Relationships were found to be relativelystronger between the new measure “absenteeism acceptance” and its two dimensionsand absenteeism measures (frequency and duration) than between the general jobattitudes and absenteeism behavior. “Absenteeism acceptance,” “affective reactionto own absenteeism,” and “affective reaction to co-workers’ absenteeism” emergedas significant predictors of absenteeism frequency, respectively (r¼ 0.264, po0.001;r¼ 0.265, po0.001; r¼ 0.231, po0.01) and absenteeism duration, respectively(r¼ 0.288, po0.001; r¼ 0.298, po0.001; r¼ 0.263, po0.01).

However, most of the other general job attitudes were found to have a relatively lowrelationship to both absenteeism frequency and absenteeism duration as comparedwith the “absenteeism acceptance” and its two dimensions. For example, therelationship between distributive justice and absenteeism frequency (r¼�0.110,po0.05), the relationship between normative commitment and absenteeism duration(r¼�0.106, po0.05), the relationship between instructional strategies and absencefrequency (r¼�0.124, po0.05), the relationship between student discipline andabsence frequency (r¼�0.110, po0.05), the relationship between procedural justiceand absence frequency (r¼�0.166, po0.001), and the relationship between proceduraljustice and absence duration (r¼�0.158, po0.001).

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Furthermore, regarding H3, we employed the GLIMMIX procedure of SAS for thisanalysis (SAS, 2008), in order to determine whether the different dimensions of“absenteeism acceptance” improved the prediction of future absenteeism behavior aboveand beyond the dimensions of other general job attitudes (organizational commitment,organizational justice, and collective efficacy). The GLIMMIX procedure fits statisticalmodels where the dependent variable is not necessarily normally distributed. Becauseabsence is characterized by a Poisson distribution, quasi-Poisson regression models werefound to be best suited to assess the relationship between the dependent variables (absencefrequency, absence duration), and the explanatory variables (organizational commitment,organizational justice, collective self-efficacy, absenteeism acceptance).

The quasi-Poisson regression rather than the Poisson with scale¼ 1 was preferred,since over-dispersion was indicated in the data. Consistent with our approach towardtesting our hypotheses with the two different measures of absenteeism, analyses werecarried out using absenteeism frequency and absenteeism duration as dependentvariables in two separate regressions.

We tested three competitive models. The first model (Table III) included only thegeneral job attitudes. The second model (Table IV) included the two dimensions of thedeveloped measurement “affective reaction to own absenteeism” and “affective reactionto co-worker’s absenteeism.” The third model (Table V) included the integrativedeveloped measurement (average of “affective reaction to own absenteeism” and“affective reaction to co-worker’s absenteeism”).

Akaike information criterion (AIC), the relative goodness-of-fit measure, was usedto compare among the different models. Based on the criterion of the procedure of SAS,that the preferred model is the one with the lower value of AIC (SAS, 2008), we foundthat the third model which focusses on the integrative measure “absenteeismacceptance” was preferred. All other similar fit measures (AICC, BIC, CAIC, HQIC)indicate the same results.

More specifically, we found in model 1 (Table III) that only affective commitmentwas found related to absence frequency (and not to absence duration) (b¼�0.246,po0.05), and procedural justice was found related to both absence frequency andabsence duration, respectively (b¼�0.212, po0.001; b¼�0.206, po0.001), while AICwas the highest both for absenteeism frequency as compared to the other twocompetitive models (AIC¼ 2,451.01) and to absenteeism duration (AIC¼ 1,526.55).

Independent variablesentered

Dependent variableAbsenteeism frequency (b) SE

Dependent variableAbsenteeism duration (b) SE

Constant 2.195 0.361 1.165 0.309Affective commitment �0.246* 0.123 0.1165 0.101Normative commitment �0.069 0.106 �0.1193 0.089Distributive justice �0.051 0.080 0.0536 0.068Procedural justice �0.212** 0.080 �0.206** 0.0682Collective efficacy (IS)Instructional strategies

�0.128 0.103 �0.0311 0.0857

Collective efficacy (SD)Student discipline

�0.0152 0.113 0.0913 0.0946

Notes: AIC (absenteeism frequency)¼ 2,451.01. AIC (absenteeism duration)¼ 1,526.55. *po0.05;**po0.01

Table III.Model 1: relationship ofgeneral job attitudes toabsenteeism measures

(Quasi-Poisson regressionmodels, GLIMMIX

analysis)

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Teachers’acceptance of

absenteeism

Model 2 (Table IV) was found better than model 1 (with smaller AIC value than model 1)for both absenteeism frequency (AIC¼ 24,161.21) and absenteeism duration(AIC¼ 1,507.93). In this model we found that in addition to the relationship betweenaffective commitment and absence frequency (b¼�0.165, po0.05), between proceduraljustice and absence frequency (b¼�0.185, po0.05) and between procedural justice andabsence duration (b¼�0.180, po0.01) – “affective reaction to own absenteeism” emergedas a significant predictor for both dependent variables: absenteeism frequency (b¼ 0.260,po0.05) and absenteeism duration (b¼ 0.244, po0.01), while other general job attitudeswere not found to be related either to absenteeism frequency or to absenteeism duration.“Affective reaction to co-worker’s absenteeism” was not found related to both dimensionsof absenteeism measures (frequency, duration).

Table V presents model 3, the aggregation of the two dimensions: “affective reactionto own absenteeism” and “affective reaction to co-worker absenteeism” as one

Independent variables entered

Dependent variableAbsenteeism frequency

(b) SE

Dependent variableAbsenteeism duration

(b) SE

Constant 1.3627 0.447 0.3245 0.3753Affective commitment �0.1655* 0.122 0.1333 0.1006Normative commitment �0.0514 0.106 �0.1008 0.0883Distributive justice �0.0433 0.081 0.0652 0.0686Procedural justice �0.1855* 0.080 �0.1802** 0.0675Collective efficacy (IS)Instructional strategies

�0.1145 0.102 �0.0257 0.0845

Collective efficacy (SD)Student discipline

�0.0368 0.113 0.0785 0.0934

Affective reaction to own absenteeism 0.260* 0.067 0.2440** 0.0558Affective reaction to co-workerabsenteeism 0.08222 0.061 0.0947 0.0495

Notes: AIC (absenteeism frequency)¼ 2,4161.21. AIC (absenteeism duration)¼ 1,507.93. *po0.05;**po0.01

Table IV.Model 2: relationship ofgeneral job attitudes toabsenteeism measuresincluding “affectivereaction to ownabsenteeism” and“affective reaction toco-worker absenteeism”(Quasi-Poisson regressionmodels, GLIMMIXanalysis)

Independent variables enteredDependent variable

Absenteeism frequency b SEDependent variable

Absenteeism duration b SE

Intercept 1.3239 0.4468 0.2969 0.3758Affective commitment �0.1656* 0.1225 0.1329 0.1010Normative commitment �0.0523 0.1062 �0.1010 0.0885Distributive justice �0.0316 0.0795 0.0723 0.0679Procedural justice �0.1915* 0.0798 �0.1840** 0.0675Collective efficacy (IS)Instructional strategies

�0.1236 0.1015 �0.0311 0.0843

Collective efficacy (SD)Student discipline

�0.0305 0.1128 0.0826 0.0935

Absenteeism acceptance 0.2397** 0.0737 0.2379*** 0.0605

Notes: AIC (absenteeism frequency)¼ 2,409.96. AIC (absenteeism duration)¼ 1,505.68. *po0.05;**po0.01; ***po0.001

Table V.Relationship of general jobattitudes to absenteeismmeasures including“absenteeism acceptance”measure (Quasi-Poissonregression models,GLIMMIX analysis)

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JEA51,5

dimension: “absenteeism acceptance.” We aggregate the two dimensions of “absenteeismacceptance” into one dimension in order to find whether we should omit the dimension of“affective reaction to co-worker absenteeism” from our suggested absenteeism attitudepredictor (based on the findings in Table IV, where “affective reaction to co-workerabsenteeism” was not found related to both dimensions of absenteeism measures). We findthat model 3 was the best model proposed with a smaller AIC value as compared to model1 and model 2 (absenteeism frequency: AIC¼ 2,409.96; absenteeism duration:AIC¼ 1,505.68). Thus, in general, H3 was partially confirmed.

These findings, in addition to the findings in Table II, namely: satisfactory internalconsistency reliability (a¼ 0.76); the relatively satisfactory correlation between“affective reaction to co-worker absenteeism” and “affective reaction to ownabsenteeism” (r¼ 0.363, po0.01), and the significant correlations that were foundbetween “affective reaction to co-worker absenteeism” and the two dimensions ofabsenteeism measures (r¼ 0.231, po0.01; r¼ 0.263, po0.001) – support our decisionto use the two dimensions of “absenteeism acceptance” as an aggregate predictor andto prefer this specific predictor of voluntary absenteeism.

Finally, we may explain the findings, that some of the relationships which werefound significant in Table II were not found significant in the regression analyses(Tables III-V), by the relatively high correlation (due to multicollinearity) between thedifferent predictors.

DiscussionThe main goal of this study was to develop an accurate measure for predictingvoluntary absenteeism among teachers, because as far as we know, no satisfactoryvalidated measure has been developed to date. The importance of such a tool lies in itsability to help understand, predict, and potentially reduce the high costs of absenteeismbehavior. We included this specific measure in the “attitude-behavior sequence”suggested in Ajzen and Fishbein’s (1977) model for predicting actual absenteeism andcompare its predictive validity with other general attitude measures that have beenused in the literature.

We found clear evidence for the reliability and validity of this specific measure.First, this measure was demonstrated to be psychometrically strong, with satisfactoryreliability (a¼ 0.76). Second, considering that reliability is necessary but not sufficientfor validity (Cortina, 1993), all of our hypotheses were either supported or partiallysupported, demonstrating the validity of the measurement.

In addition to the internal and the convergent validly that we found for the generaljob attitudes based on AVE measure, our findings also confirm the construct validity ofthe new measure “absenteeism acceptance.” As expected, we found in most of thecorrelations weak negative relationships between the general job attitudes and“absenteeism acceptance.” This demonstrates the convergent validity and thediscriminant validity of the new measure, showing it is not simply a duplicate of any ofthese general job attitudes.

More specifically, we found that slightly more general job attitudes were related to“affective reaction to own absenteeism” (one of the dimensions of “absenteeismacceptance”) than to “affective reaction to co-workers” absenteeism (the otherdimension of “absenteeism acceptance”). Moreover, we found that the relationshipswere relatively stronger between the general job attitudes and “affective reaction toown absence” than between general job attitudes and “affective reaction to co-workers’absence.” These findings may explained by the fact that different job attitudes may

609

Teachers’acceptance of

absenteeism

reflect intrinsic motivation factors (“I” as a reference point of view) more than extrinsicmotivation factors (“colleagues” as a reference point of view).

According to the intrinsic and extrinsic motivation theory (Deci, 1975), we maydistinguish between the different dimensions of “absenteeism acceptance.” Extrinsicmotivation originates outside of the individual and focusses on the short term. On theother hand, intrinsic motivation refers to motivation that exists within the individualand is not reliant on any external pressure. Research on intrinsic motivation hasfocussed on the long term and directed attention to process aspects (Covington andMueller, 2001; Deci et al., 1999).

The definition of work withdrawal construct presents motivational factors such asthe following definition: “behaviors dissatisfied individuals use to avoid aspects oftheir specific work role or minimize the time spent on their specific work tasks whilemaintaining their current organizational and work-role memberships” (Hanisch andHulin, 1991, p. 111), which may include physical removal from a particular workplace,either for part of a day (voluntary lateness), an entire day (voluntary absenteeism), orpermanently (voluntary turnover) (Blau, 1998; Blau et al., 2004; Johns, 2001).

The most common model of the internal structure of withdrawal behaviors, positsthat withdrawal manifestations occur in progression, starting with relatively mildforms of psychological withdrawal such as occasional lateness and advancing to moresevere forms such as absence or even turnover ( Johns, 2001; Koslowsky, 2009).Previous studies strongly appear to support the progression of the withdrawal model.Longitudinal studies by Clegg (1983), Wolpin et al. (1988), and Rosse (1988) founda lateness-absence progression. Several studies reveal a progression from absence toturnover (Farrell and Peterson, 1984; Kanfer et al., 1988; Krausz et al., 1988; Rosse,1988). In fact, previous meta-analytics showed that the two adjacent relationships inthe progression model (e.g. lateness-absenteeism, absenteeism-turnover) were strongerthan the nonadjacent relationship between lateness and turnover (Koslowsky et al.,1997; Mitra et al., 1992).

Therefore, we may anticipate that “absenteeism acceptance” which presents anattitude toward severe withdrawal behavior such as absenteeism will be affected byinternal factors which relate to the long term, such as organizational commitment,organizational justice, and collective self-efficacy.

The contention that absenteeism frequency is the best measurement of voluntaryabsenteeism seems to be mildly supported by the study results which indicate thatslightly more general job attitudes were related to absenteeism frequency than toabsenteeism duration. However, few job attitudes (e.g. procedural justice, normativecommitment) were found to be related to absenteeism duration which, according to theliterature, is a truer reflection of involuntary absenteeism and logically, should not beaffected by attitude. These findings may be explained by the fact that although a modelof “attitude-behavior sequence” seems to be most appropriate for predicting voluntaryabsenteeism (e.g. Benson and Pond, 1987; Hom and Griffeth, 1995), it is often difficultto classify a particular incident in the appropriate category. Moreover, a change in theparameter used for measuring absenteeism (duration or frequency) is not enough toconsider whether the absenteeism is voluntary or involuntary. Support for thisargument may be found by the satisfactory correlation that was found in this studybetween absenteeism duration and absenteeism frequency.

In addition to the confirmation of the construct validity of “acceptance absenteeism”measure, our study findings also confirm the criterion validity and the predictivevalidity of the new measure of “acceptance absenteeism.” Testing both absenteeism

610

JEA51,5

frequency and absenteeism duration, we found that “absenteeism acceptance” measurepredicts absenteeism behavior above and beyond that predicted by the general jobattitudes. These findings may reinforce Ajzen and Fishbein’s (1977) attitude-behaviorapproach, since accurate predictors relate higher to voluntary absenteeism than doother non-specific predictors, with a potential contribution in the future to reducingvoluntary absenteeism in schools.

Strength, limitation, and future researchThe strength of the study design is in its content, construct, criterion, and predictivevalidity of the new measure “absenteeism acceptance,” reflecting a specific andaccurate measurement to predict absenteeism behavior. Methodologically, thisstudy was based on teachers’ self-reports, school records, and use of separate timeintervals which are more informative as regards causal sequences. However, thereare some limitations to the study. First, the sample was drawn from one district inIsrael. This is a limited sample which may classify our study as exploratory. Thus,the findings should be tested and validated as to whether they can be applicable toother districts in Israel. In addition, one must consider the generalizability ofresearch based on a framework developed in one nation and whether it will provevalid in other countries.

Second, the sample used in the present study included only teachers, which limitsthe generalizability of the findings to other sectors of business and industry. In view ofthe growing awareness and knowledge of the importance of reducing employees’voluntary absenteeism, future research should attempt to replicate the framework ofthis study and apply it to other occupational groups in the public and private sectors,to permit generalization to a wider segment of the workforce.

Finally, despite the prevalent approach which maintains that absenteeismfrequency is the best measure of voluntary absenteeism and absenteeism duration isthe best measure of involuntary absenteeism, our findings indicate that this distinctionis not decisive, because of the problem of defining voluntary absenteeism. Futurestudies should investigate whether we can develop other, more precise predictors andmeasures in order to distinguish between voluntary and involuntary absenteeism.

ConclusionThis study develops and expands upon previous research by creating andvalidating a specific “absenteeism acceptance” measure that seems to be useful inunderstanding and predicting voluntary absenteeism. In the past, research hasattempted to identify predictors of absenteeism behavior by focussing chiefly ongeneral job attitudes and has come up with inconsistent results. We developed ameasure involving a specific attitude toward absenteeism and found that“absenteeism acceptance” behaves differently than general job attitudes. Thestudy findings clearly indicate “absenteeism acceptance” as a reliable and validpredictor of costly absenteeism behavior. Moreover, this study may contribute toexpanding the Ajzen and Fishbein (1977) model as it concerns the “attitude-behavior sequence” by adding a specific “absenteeism acceptance” measure,an approach not tested previously. We encourage schools and principals to usethis simple, reliable, six-item measure as an indicator of teachers’ attitudestoward absenteeism and to predict voluntary absenteeism. It appears to bea psychometrically sound measure that can be used in future absenteeism research,in theory as well as practice.

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Teachers’acceptance of

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Further reading

Bandura, A. (1977), “Self-efficacy: toward a unifying theory of behavioral change”, PsychologicalReview, Vol. 84 No. 2, pp. 191-215.

AppendixThe AVE calculation (Fornell and Larker, 1981).

The AVE for X with indicators x1, x2,y, xn is:

AVE ¼X½l2

i �VarðXÞ=�X

½l2i �VarðXÞ þ

X½VarðeiÞ�

�

where li is the loading of xi on X; Var is the variance; ei is the measurement error of xi.

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About the authors

Orly Shapira-Lishchinsky is a faculty member at the Department of Educational Administration,Leadership and Policy, in Bar-Ilan University, Israel, specializing in organizational ethics, teachers’withdrawal behaviors and mentoring. Her recent publications include articles in Journal of

Educational Administration, Educational Administration Quarterly, Journal of Business Ethics andTeaching and Teacher Education. She was the winner of the 2009 Emerald/EFMD OutstandingDoctoral Research Award in the Education and Leadership Strategy category. Orly Shapira-Lishchinsky is the corresponding author and can be contacted at: Shapiro4@mail.biu.ac.il

Gamal Ishan is an M.A student in the Department of Educational Administration, Leadershipand Policy, at Bar-Ilan University, Israel. He is a social coordinator in high school.

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