Absenteeism (alternatively, absence) is an individual’s lack of physical presence at a given location and time when there is a social expectation for that person to be there. An absence is a behavioral outcome or state rather than a behavior itself, because many different actions can make up an absence, such as lying on the beach if at the same time a person is expected to conduct a face-to-face meeting with employees. Moreover, attendance and absence should not be thought of as straightforward opposites. An individual can be absent from many settings simultaneously if groups or individuals from each of those settings have contradicting expectations. In the same way, a person can be in attendance at one location (such as work) while being absent from another (such as home), as long as different social referents generate role conflict about attendance. However, an individual can attend only one setting because attendance is merely physical presence there.
For decades researchers have often ascribed many causes to absence, leading to distinctions between involuntary and voluntary absences. Such attributions are problematic, especially when they are applied to absence measures. Those attributions can be made only on the basis of empirical relationships between absences and other variables and on solid estimates of the proportions of observed variance because of latent voluntary or involuntary factors.
Absenteeism is a narrowly defined construct. Some researchers have suggested that absence be entrenched in a broader psychological construct such as avoidance of work, withdrawal from the work role, or adaptation to the work environment. Studying absence as an isolated phenomenon is likely to undermine the practitioners’ focus on prediction, because of an absence’s high proportions of specific, dynamic, and random variance. By combining many related behaviors (e.g., lateness, grievance filing, sabotage) into a broader construct or behavioral family, the combination might be characterized by more common variance and could be more readily predictable.
Widening the scope of the construct in which to embed absence might improve its predictability. Nevertheless, abandoning the study of absence in favor of the study of work role withdrawal and adaptation is premature. One reason is that those constructs, especially the latter, might be overly broad. Job adaptation could comprise almost any work-related behavior. Another reason is that the terms themselves imply causes for the constructs, and that the purported determinants of the constructs are often part of their stated definitions. That is, the behavioral constructs have been described as responses to negative work attitudes.
Virtually all absence research has been based on variance theories. A variance theory is one that states that X is a necessary and sufficient condition for the outcome Y. In other words, Y is completely determined by X. As such, variance theories of absence suggest that the underlying mechanisms that drive absence are mechanistic. (Remember, in conventional ordinary least squares [OLS] regression, R has a maximum value of 1.0 and unexplained variance is determined by the equation 1 – R.) Thus absence researchers have constructed theories with the prime objective of maximizing the variance explained in the dependent variable by the independent variables, and random variance is considered error.
Researchers should not always evaluate the merits of a theory solely on percentage of variance explained. First, conceptual parsimony may be more preferable than maximization of explained variance if the latter comes with the cost of ambiguity. Second, it is possible to find statistically significant results on the basis of chance alone.
Some have challenged the convention that a good theory of absence explains all the variance by arguing that stochastic or process theories may be better suited for explaining absence than variance theories. Essentially, a process theory tells a little story about how something comes about; but to qualify as a theoretical explanation of recurrent behavior, the manner of the storytelling must conform to narrow specifications. A process theory is defined as follows:
- X is a necessary condition for Y, but not a sufficient condition.
- X will cause Y stochastically (using a random variable).
That is, whether X causes Y depends on some probabilistic process. Thus process theories, unlike variance theories, leave residual uncertainty by construction.
A prominent process theory of absence suggests that absence reflects the dynamic operation of a set of motives, all of which are time varying. Thus to explain the timing of absence and attendance, consider the changing strength of motives to attend work and motives to engage in activities that require absence from work. Unfulfilled motives increase in strength with time, and this changing motive strength can be modeled as a set of differential equations. Thus if all motives were internal, there were not external constraints on time allocation, and a person could act on motives without cost, the individual could construct a deterministic model of time allocation and fully explain the timing and duration of activities. However, random events such as work stoppages, accidents, and illness impose external constraints on time allocation.
The notion of process theories highlights the probability of many possible constructs that could be causes or consequences of absenteeism. However, different sets of researchers have sliced out different sets of explanatory constructs and investigated them using simple hypotheses, all based on variance theories.
The most prominent simple hypothesis is the work attitude-absence hypothesis, in which absenteeism results from negative work attitudes, which are a function of aversive work environments or dissatisfying work experiences. This is the benchmark hypothesis studied since the early 1950s and subject to more investigations than any other hypothesis about absenteeism. Meta-analyses show that work attitudes typically are not strong predictors of absenteeism. Attitude theory suggests that for there to be a relationship between an attitude and behavior or occurrence, both must correspond in terms of their levels of specificity. Job satisfaction, organizational commitment, and job involvement are general attitudes; and absence is a specific behavior. Thus we do not necessarily expect a strong relationship.
Some researchers have argued that absence reflects inherent and long-standing personality characteristics that account for the moderate stability of absence over time and situations. Absence proneness emerged as the explanatory concept. However, unlike most other personality characteristics, which are measured through conventional psychological scales, absence proneness has been inferred through less conventional methods. For example, some researchers have inferred absence proneness from the relationship between prior absence and subsequent absence, arguing that those who tend to be absent more in a given period will continue to be absent more in later periods.
Absence can be influenced by factors outside an individual’s control, including weather conditions, transportation modes and routes, and personal health. Further, perceived control over attendance may also be an important determinant of work absences, more so perhaps than actual control. Albert Bandura’s social cognitive theory provides a basis for the relationship between perceived control and behavior. Perceptions of control over attendance may be a function of past attendance experiences and structural interferences or role conflict between the demands of the work setting and the demands of other settings.
Some theorists have attempted to combine some of the simple theories for integrative theories. However, most are completely inductive integrations, and their usefulness depends on their fit to future data. Others are more properly called frameworks than theories because they specify collections of variables rather than relations between well-defined constructs. To be tested completely, these theories require the operationalization of large numbers of variables in consort. These frameworks have serious flaws, not the least of which is that they all posit relations between extremely broad explanatory constructs and a very narrow dependent construct.
Perhaps absence-specific attitudes, social pressures, perceived environmental constraints, and work morals or ethics can all be modeled as part of an absence or participation decision process. Many researchers have implicitly espoused a decision-making perspective on absenteeism. Despite the potential for overcoming past limitations and integrating diverse findings, only a few investigations of absence have explicitly used a decision-making approach.
Some researchers have maintained that absenteeism is a differentiated phenomenon based on causes attributed to each absence occurrence by the absentee. Potential absence-inducing events should be classified by the freedom those events provide an individual in deciding whether or not to stay away from work. For example, a variety of employees were in home interviews asked to make attributions of their prior absences as well as potential future absences. The vast majority of individuals attributed prior and potential future absence to factors beyond personal control, such as illness, rather than to events within their own control, such as leisure activities. Attributing absence to medical illness is consistent with evolving social beliefs about what constitutes acceptable reasons for absence in a particular context. This conclusion is consistent with research demonstrating that medical absence was systematically related to work and nonwork motives.
Research has found additional factors related to a decision to be absent from work. Using an expectancy theory framework, some researchers have hypothesized that hobby and leisure time, kinship responsibilities, and personal illness influence absence decisions. Others found that absence was related to the value of nonwork hours, which supports the view that absence is a function of motivation processes extant in work and nonwork domains. One set of authors used a policy capturing design to model individual decisions to be absent based on the factors previously reviewed. Employees responded to hypothetical scenarios describing factors that might contribute to their decisions to be absent on a particular day. The relative importance of the antecedents of absence decisions varied substantially across individuals. With the exception of personal illness, which was a significant factor for all employees, some factors that resulted in significantly higher estimated absence for some individuals led to significantly lower estimated absence for others—including hobby or leisure activities, work demands, and day of the week. Although these studies suggest several factors relating to absence decisions, this area of research is largely in an exploratory stage.
One notable development in absence research has been a growing awareness of the importance and mistreatment of time. Some researchers have argued that the ordering of relationships, in time, should prompt researchers to work through their conceptual schemes and methodological choices more deeply and increase the yield of future studies. Slightly more than half used a postdictive design, which seems to be roughly the same proportion overall. This state of affairs raises serious questions about the true sequence of absenteeism’s origins and outcomes. For example, job satisfaction is the affective variable most often connected with absenteeism, in an approach that treats absences as responses to aversive work environments. However, in studies designed to evaluate the reverse ordering, both postdictive and predictive correlations are roughly the same size.
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