The Impact of the Employee’s Personal Characteristics on the Abuse of Sickness Absence: Empirical Evidence From Poland

The abuse of sick leave is a problem that is still relatively poorly understood. Above all, there is a lack of empirical research on the issue. Research in this area is difficult to conduct due to the blurred distinction between justified and unjustified use of sick leave. Researchers are forced to observe high levels of caution in interpreting the available data, as it is never fully clear whether an absence is forced by an actual illness, or whether it is the effect of other non-health-related causes.

In Poland, the abuse of sick leave has not as yet been the subject of scientific research, and as a result the scale of the phenomenon is not known. The one available source of information on the topic is the results of spot checks carried out by the welfare authorities (ZUS). Unfortunately, the possibility of conclusions based on this data is severely limited as the spot checks are selective and cover only a narrow group of sick leave referrals (long-term sick leave absence).

The lack of reliable and complete data from public sources requires the sourcing of information in another way. One of the potential solutions is to use a survey-based study. Of course, the information gathered in this way does not reflect the actual state of affairs, and merely contains the declarations of respondents, which can to a lesser or greater degree diverge from reality, especially if difficult and/or morally questionable topics are covered

Bostyn et al., ‘Of Mice, Men, and Trolleys: Hypothetical Judgment Versus Real-Life Behavior in Trolley-Style Moral Dilemmas.’ Psychological Science, 29(7), 2018, 1084–1093. https://doi.org/10.1177/0956797617752640

The source material is from a survey study conducted in December 2021 by the research agency BBiAS. The information was gathered using the CAWI method, that is, via an internet survey. The territory covered by the research encompassed the whole of Poland, and the participants were full-time employees covered by national health insurance. The research sample was 1067 respondents. The random sampling was made up of national panels of respondents. It can be assumed that the randomised character of the sample provides grounds for generalisation of the results. The maximum measurement error was +/− 3% with a reliability level of 95%. The structure of the sample due to chosen personal characteristics of respondents is presented in Table 1.

Based on the results of prior research, eleven circumstances were isolated that particularly encourage the abuse of sick leave referrals. These are situations in which employees may feel a particular temptation to partake in unethical behavior. These circumstances are:

CIR1: extending the period away from work during public holidays or long weekends,

The respondents were asked to respond to each of these eleven cases and declare if they had ever taken sick leave in such circumstances. The results (in general and due to personal characteristics) are presented in Table 2. Employees in Poland use sick leave the least often (8.4%) to demonstrate dissatisfaction with working conditions, and the most often (22.9%) in situations of higher necessity.

The research aimed to assess the influence of various factors related to personal characteristics on the abuse of sick leave in Poland. For structural equation modelling the MLR algorithm was used (maximum likelihood estimation with robust (Huber-White) standard errors), which is recommended when the assumption of a multivariate normal distribution is not met

Lai, ‘Estimating Standardized SEM Parameters Given Nonnormal Data and Incorrect Model: Methods and Comparison.’ Structural Equation Modeling, 25(4), 2018, 600–620. https://doi.org/10.1080/10705511.2017.1392248

Basing on the classic ‘Fraud Triangle’ concept

Cressey, Other people’s money: A study of the social psychology of embezzlement. 1953, Free Press.

In the compulsion category, the motivation for absence is the pressure related to the need to deal with an important and/or unpredicted matter that is in conflict with working hours. Such pressure is related to an important administrative matter or another situation of higher necessity, renovation work, or the need to provide personal care for a loved one or an animal. In the escape abuse category the motivation is the desire to ‘escape from’ unwanted work tasks, or ‘escape to’ desired activities that collide with working hours. This desire is related to various factors that either push away from work (push factors), such as avoiding unpleasant events and/or people, or attract towards absence (pull factors) such as the wish to participate in a spontaneous escapade (fishing, mushroom picking, attending a favorite team’s match). In the recreation abuse category, the motivation to abuse sick leave is rest and recuperation. These circumstances take place in situations such as extending one’s free time away from work (e.g., a long weekend), or as a reaction to weariness, overtiredness, and/or overwork.

The independent variables were various factors related to the respondents’ personal characteristics. The list and description of those variables is presented in Table 5. Variables related to age, gender, number of children, education, place of living, and marital status are nominal. In statistical analysis they were linked with reference categories. For the age-related variables reference category was ‘young’. For the gender-related variable, reference category was ‘female’. For the variable related to number of children, reference category was ‘childless’. For the education-related category, reference category was ‘lower’. For the variables related to a place of living, reference category was ‘medium city’. For the variable related to marital status, reference category was ‘single’. Variables related to financial situation and health were ordinal and treated as numerical.

To estimate the effect of the personal characteristic factors on abuse in the compulsion category, a multivariate linear regression analysis was conducted. The obtained model proved to be statistically significant, F (24, 1056) = 9.26; p < 0.001. It explains around 8% (7% after correction) of the variability of the tested variable (R² = 0.08, adj.R² = 0.07). The results of the model estimation are presented in Figure 1.

Figure 1:

In the model, five of ten analysed predictors were statistically significant: (1) age: mature, (2) number of children: with children, (3) place of living: provincial, (4) marital status: in a relationship, (5) gender: male.

As for age, mature workers less often declare propensity to abuse compulsion absence than young workers. In case of old workers, such propensity is higher in comparison to young ones, but the result was statistically insignificant.

As for number of children, workers with children far more often declare abusing compulsion absence than childless workers.

As for place of living, workers living in both provincial and metropolitan places more often declare abusing compulsion absence than workers living in medium cities. However, the result was statistically significant only in accordance with workers living in the provinces.

As for education, workers with higher education less often declare abusing compulsion absence, however this result is statistically insignificant.

As for marital status, employees in a relationship far less often declare abusing compulsion absence than singles. As for gender, male workers far more often declare abusing compulsion absence than female workers. Both results were statistically significant.

As for financial situation and health, better assessment of those factors is linked with an increase in propensity to abuse compulsion absence. It means, that employees feeling better in terms of health status or financial status, more often declare abusing such absence. Both of those results were, however, statistically insignificant.

Similarly to the previous category of abuse, multivariate linear regression analysis was conducted. The obtained model was shown to be statistically significant, F(24, 1042) = 5,80; p < 0.001. It explains around 5% (4% after correction) of the variability of the tested variable (R² = 0.05, adj.R² = 0.04. The results of the model estimation are presented in Figure 2.

Figure 2:

In the model, four of ten analysed predictors were statistically significant: (1) number of children: with children, (2) place of living: provincial, (3) marital status: in a relationship, (4) gender: male. In addition, two factors turned out to be on the borderline of statistical significance: health and higher education.

As for age, there was no link between mature and young workers in terms of propensity to abuse escape sickness absence. Old workers more often declare abusing such absence than young ones, however, this result was statistically insignificant.

As for number of children, employees with children far more often declare abusing escape sick leaves than childless employees.

As for place of living, workers from both metropolitan and provincial areas more often declare abusing escape absence than workers living in middle cities, but only in the case of provincial was the result statistically significant. As for education, workers with higher education are less likely to abuse such absence than workers with lower education, and this result is on the borderline of statistical significance. As for marital status, workers in a relationship less often declare abusing escape absence than single ones, and this result is statistically significant. As for gender, males are far more likely to abuse the escape absence than females, and this result is statistically significant.

As for health, a better assessment of own health status is linked with more often abusing escape absence. This result was on the borderline of statistical significance. The financial situation was not related to this kind of abuse.

Similarly to the previous category of abuse, multivariate linear regression analysis was conducted. The obtained model was shown to be statistically significant, F(24, 1042) = 3.17; p < 0.01. It explains around 3% (2% after correction) of the variability of the tested variable (R² = 0.03, adj.R² = 0.02). The results of the model estimation are presented in Figure 3.

Figure 3:

In the model, four of ten analysed predictors were statistically significant: (1) number of children: with children, (2) place of living: provincial, (3) marital status: in a relationship, (4) gender: male. In addition, two factors turned out to be on the borderline of statistical significance: (1) age: mature and (2) gender: male.

As for age, both mature and old workers less often declare abusing recreation sickness absence than young workers. The result was statistically significant only in the case of mature workers.

As for number of children, workers with children were more likely to abuse recreation absence than childless workers, and this result was statistically significant. As for place of living, workers from both metropolitan and provincial areas more often declare abusing absence than workers from middle cities, but the result was statistically significant only in the case of provincial. As for education, workers with higher education were more likely to abuse absence than less educated ones, but this result was statistically insufficient. The result was significant also for marital status – workers in a relationship were less likely to abuse such absence than single workers. As for gender, males more often declare abusing than females, and this result was on the border of statistical significance.

As for health and financial situation, better assessment of own status in both cases was linked with a higher propensity to abuse recreation absence. This result was statistically significant only for health.