TRAINING AND ABSENCE REDUCTION: THE EFFECTIVENESS OF TRAINING SUPERVISORS ON LEADER BEHAVIOR AS AN INTERVENTION TO REDUCE
ABSENTEEISM RATES.
Master's Thesis Human Resource Management January 16, 2016
Carin Meems S2202565 Aquamarijnstraat 679
9743 PS Groningen 06-46549050 a.c.meems@student.rug.nl
Supervisor: Prof. Dr. H.B.M. Molleman University of Groningen Faculty of Economics and Business MSc Human Resource Management
TRAINING AND ABSENCE REDUCTION: THE EFFECTIVENESS OF TRAINING SUPERVISORS ON LEADER BEHAVIOR AS AN INTERVENTION TO REDUCE
ABSENTEEISM RATES.
ABSTRACT
High absenteeism rates can have detrimental effects on organizations. The Gelre Hospital therefore decided on intervening by training supervisors on leader behavior as a means to reduce absenteeism. This study investigated the mediating effect of absence culture, affective organizational commitment, job satisfaction and motivation on the relationship between training supervisors on leader behavior and absenteeism rates. Even though no support was found for the hypotheses, job satisfaction, commitment and absence culture predicted absenteeism rates. This leads to the conclusion that employee well-being is crucial to decrease absence. Additional research is however necessary to fully understand the effectiveness of the training.
CONTENT
Abstract ... 1
Introduction ... 3
Theoretical Framework ... 4
Absenteeism ... 4
Absence Duration and Frequency ... 4
Antecedents ... 4
Leader Behavior ... 4
Leadership style. ... 5
Employee-work balance. ... 6
Communication. ... 6
Methodology ... 7
Sample and Procedure ... 7
Measures ... 8
Leader behavior training. ... 8
Mediators. ... 8
Absence. ... 9
Control variables. ... 10
Results ... 10
Documented company information ... 10
Job satisfaction. ... 10
Descriptives ... 12
Model testing ... 12
Analysis of Variance (ANOVA). ... 12
Correlations. ... 12
Regression and mediation. ... 13
Discussion ... 14
Absence culture ... 15
Psychological reactance. ... 15
Job satisfaction ... 16
Affective organizational commitment ... 16
Motivation ... 16
Limitations ... 17
Directions for further research ... 17
Managerial implications ... 18
Conclusion ... 18
References ... 19
INTRODUCTION
High rates of absenteeism in organizations have a detrimental effect on financial performance. Causes are the direct costs of sick pay, as well as the indirect costs of lower productivity and decreased service quality (Mayfield & Mayfield, 2009; Diestel, Wegge &
Schmidt, 2014).
Especially health care organizations tend to have high rates of absenteeism, resulting in significant financial losses (Gaudine , Saks, Dawe, & Beaton, 2013). In the Netherlands the average absenteeism rate in the health care sector was 4.0% in 2014, which was higher than the overall average of 3.8% of all sectors in that year (Centraal Bureau voor de Statistiek (CBS), 2015). The costs of absenteeism in the Dutch health care sector amounted to around 5 billion euros in 2010, with an average absenteeism rate of 4.3% (CBS, 2015; Rijksoverheid, 2013). As hospitals need to take economic measures due to the austerity policy of the Dutch government, the changes on the insurance market, and the ageing population, high rates of absenteeism are undesirable.
Fortunately, even modest reductions in absenteeism rates can result in considerable cost savings in organizations (Mayfield & Mayfield, 2009). Following from research by the Dutch government, between 667 million and 2.6 billion euros can potentially be saved in the health care sector when effective interventions like participative work adaptions are utilized (Rijksoverheid, 2013).
To substantiate effective interventions, the Human Resource department at the Gelre Ziekenhuizen (a hospital) in Apeldoorn, the Netherlands, decided to address absenteeism with training supervisors on communication practices and leader behavior. As for instance
communication practices have an influence on motivation (Pettit, Goris & Vaught, 1997; De Boer, Bakker, Syroit & Schaufeli, 2002), which on its turn influences absenteeism (Bakker, Demerouti, De Boer & Schaufeli, 2003), it would follow that by training supervisors, absenteeism rates would be reduced.
Although literature exists on the influence of antecedents of absenteeism, like employee attitudes, little attention has been given to how employee attitudes can be
influenced, in particular by training supervisors. This research therefore will investigate the effects of the training given to supervisors on employee attitudes and consequent absenteeism rates in the Gelre Ziekenhuizen. With the help of a field study, two employee populations will be compared, to see whether the training has had the desired effect. The supervisors of one group received the training, while the supervisors of the other group did not.
In the following sections first the theories underlying the conceptual model and the resulting hypotheses will be discussed, after which the research methodology will be introduced. Following that, the results will be presented and subsequently analyzed in the discussion section. The research will end with a conclusion.
THEORETICAL FRAMEWORK Absenteeism
The literature on absenteeism is abundant. Although definitions of the term might slightly differ, a general definition that captures the essence is as follows: “Any failure to report for or remain at work as scheduled, regardless of the reason” (Cascio, 2000: p. 59).
However, not all absenteeism is equal. There are basically two types: in the first place unavoidable absence, and secondly discretionary absence. The first type is due to
circumstances like serious personal or family member illness, while the latter is due to factors such as personal needs or stress (Mayfield & Mayfield, 2009).
Absence Duration and Frequency
Absence can be measured in two different ways: absence duration and absence frequency. A distinction between the two is often made in the absenteeism literature (Darr &
Johns, 2008). Where absence duration is thought to be a result of health issues, absence frequency is thought to be caused by the employee’s dislike for the job (Hardy, Woods, &
Wall, 2003). Critics however argue that it is possible that absence duration and absence frequency each do not have unique predictors, but that the causes may be intertwined. The number of times someone calls in sick can also partially be due to an impaired health
condition, while taking longer sick leaves may also include voluntary, or avoidable, absence (Darr & Johns, 2008; Hardy et al., 2003). A recent study by Brummelhuis, Ter Hoeven, De Jong and Peper (2013) has supported this view, and concluded that it is hard to justify a distinction between the two. Therefore, this study will not consider duration and frequency to have different predictors, although both measures of absenteeism will be taken into
consideration.
Antecedents
A vast amount of explanations for absenteeism have been proposed over time, and they all make one thing clear: absenteeism is not easy to dissect. However, the antecedents can roughly be divided into three main categories: personal factors, job-related factors, and contextual factors. A personal factor for instance is age or attitude. Pay and work stress are examples of job-related factors, while contextual factors include absence culture and leader behavior.
Leader Behavior
This research will specifically focus on the effect of leader behavior on absenteeism of followers, as in the literature the importance of leadership, or supervisory, behavior as one of the antecedents of absenteeism has been emphasized to a great extent. However, very few studies have directly investigated the link between the two (Van Dierendonck, Le Blanc, &
Van Breukelen, 2002). One of the studies that did investigate this link, a study by Schreuder, Roelen, Van Zweeden, Jongsma, Van der Klink and Groothoff (2011), showed that effective leader behavior was associated with both a shorter duration and lower frequency of absence among nursing staff. Research by Bernstrom and Kjekshus (2012) did also show a
relationship between leader behaviors and absence. The rationale behind this relationship is that supervisors have the ability to influence some determinants of absenteeism, like
employee attitudes, in such a way that absence rates decrease. Leader behavior would therefore influence absenteeism rates.
For this reason the Gelre Hospital decided on training supervisors on leader behavior as to reduce absenteeism. According to the training documents, specific leader behavior that supervisors were trained on included leadership styles, monitoring the employee-work balance, and communication practices.
Leadership style. In the first place, displaying a low level of absenteeism acceptance would establish an absence culture of low acceptance of absenteeism, which consequently leads to low levels of absenteeism. Absence culture is a social phenomenon that is defined as the “set of shared understandings about absence legitimacy in a given organization and the established
‘custom and practice’ of employee behavior and its control” (Johns & Nicholson, 1982, p.
136). It has been identified as an important predictor of individual absence behavior, due to the power of social influences (Rentsch & Steel, 2003). Employees learn the type and degree of absence behavior that for instance managers and peers will accept, and they adjust their own behavior accordingly (Chadwick-Jones, Nicholson, & Brown, 1982; Gaudine & Saks, 2001). Therefore, if managers show a low level of absenteeism acceptance, employees adjust their behavior accordingly, and absenteeism rates will decrease. Training supervisors on a leadership style that is associated with a low level of absenteeism acceptance would therefore be effective in reducing absenteeism. The hypothesis is formulated accordingly:
Hypothesis 1: The indirect negative effect that training supervisors on displaying a low degree of acceptance of absenteeism has on absenteeism is mediated by the absence culture as perceived by the employee.
Secondly, great willingness to help the employees will improve the affective organizational commitment of the employees, leading to a reduction in absenteeism rates.
Willingness to help the employee can be seen as part of perceived organizational support, which is defined as the perception that the organization values one’s contribution and is concerned about his or her well-being (Rhoades & Eisenberger, 2002). As employees view their supervisor as an agent of the organization, the concern of a supervisor about the employee’s well-being is partly attributed to the organization (Eisenberger, Shoss, Karagonlar, Gonzalez-Morales, Wickham, & Buffardi, 2014). When employees form a positive belief regarding the organization’s commitment to them, employees become more committed on the basis of reciprocity. To the contrary, if no organizational support is
perceived, employees become less committed, and consequently further reduce organizational involvement by being absent more often (Eisenberger, Cummings, Armeli, & Lynch, 1997;
Harrison & Martocchio, 1998). Therefore, if supervisors display compassion and support employees (i.e. organizational support), employees become more committed to the
organization, which would lead to reduced absenteeism rates. The correlating hypothesis is as follows:
Hypothesis 2: The indirect negative effect that training supervisors in terms of their willingness to help the employee has on absenteeism is mediated by affective organizational commitment of the employee.
Employee-work balance. In addition to leadership style, the supervisors were trained on monitoring the balance between the employee and his capacities, needs, and expectations and the actual job. When the supervisor ensures a good balance between the employee and his or her job, a higher level of job satisfaction will be present, which consequently would reduce absenteeism rates.
Job satisfaction is defined as a positive and pleasurable attitude resulting from an individual’s job appraisal or job experience (Locke, 1976). It is based on a comparison between the desired and actual outcomes (Rad & De Moraes, 2009). If the desired and actual outcomes are not aligned misbalance will occur, for instance when the job is too monotonous for the employee or the workload is too high, and job satisfaction will decrease (McNeese- Smith, 1999; Rad & De Moraes, 2009; Heywood, Siebert, & Wei, 2002). A good balance between the employee and his job is therefore essential for job satisfaction.
Job satisfaction has been regarded as an important predictor of absenteeism. Several researchers have established the relationship between the two variables (Brooke & Price, 1989; Steel, Rentsch & Van Scotter, 2007). When employees do not like their job, they for instance call in sick more often (Johns, 1997), or illegitimately extend their sick leave (Brummelhuis et al., 2013). Increased job satisfaction would thus decrease absenteeism.
Therefore, when the supervisor establishes a good balance between the subordinate and his job, job satisfaction will increase, thus decreasing absenteeism. This is reflected in the following hypothesis:
Hypothesis 3: The indirect negative effect that training supervisors on their
capabilities to monitor the balance between the employee and his job has on absenteeism is mediated by the employee’s job satisfaction.
Communication. To help establish effective leader behavior, supervisors were additionally trained on communication skills. These communication skills were mostly focused on discussing absenteeism behavior with employees. This meant that the supervisors were for instance equipped with practical knowledge on conversation practices to point out undesirable behavior (absence), to explore the causes for this behavior, and to place demands on the employee in such a way that the desired outcome would be attained (goal-setting). This combines both the empathic and demanding factor of the leader behavior discussed
previously. When the supervisor uses these communication skills properly, employee motivation can be enhanced, leading to a reduction in absenteeism.
Motivation has been referred to as the internal factors that impel action and the external factors that can act as inducements of action (Locke & Latham, 2004, p. 388).
Communication practices, both implicit and explicit, have been associated with employee motivation (Mayfield & Mayfield, 2002; Mayfield & Mayfield, 2009). Communication
increases the knowledge that employees have, and this is crucial for motivation (Sullivan, 1988). For instance, when using communication for feedback, as in pointing out undesirable behavior, it can give the employee additional information on desired behavior, and thus increase motivation to display that behavior. In the case of goal-setting, like reducing absenteeism, specific information motivates employees to attain the goal.
Both goal-setting and leader initiated feedback have been recognized as feasible interventions to reduce absenteeism (Gaudine & Saks, 2001). As just pointed out, these types of communication practices increase employee motivation. As higher employee motivation has also been linked to reduced absenteeism (Brummelhuis et al., 2013), this suggests that the reduction in absenteeism is mediated by employee motivation. Therefore the hypothesis is formulated as follows:
Hypothesis 4: The negative indirect effect that training supervisors on their communication skills has on absenteeism is mediated by employee motivation.
The conceptual model that is based on the four hypotheses is graphically represented in Figure 1.
Figure 1 Conceptual Model
METHODOLOGY Sample and Procedure
The data were collected at the Gelre Ziekenhuizen in October and November 2015.
The Gelre Ziekenhuizen is a Dutch hospital with two branches, one in Apeldoorn and one in Zutphen, and it is employing over 3,500 people.
To collect the data a Dutch web-based questionnaire combined with a stratified sampling method was used. The sample was divided into two groups of employees. One group of employees was subordinate to supervisors that had received the training on absenteeism reduction. These employees (521) were all working in the General Supportive
Training leaders on:
- Displaying low absenteeism acceptance;
- Willingness to help the employee;
- Monitoring the balance between the employee and his/her job;
- Communication skills.
Absence Culture (H1)
Employee Motivation (H2)
Employee Job Satisfaction (H3) +
-
Employee Affective Organizational Commitment
(H4)
Absenteeism +
+
+ - - -
Services (GSS) department of the hospital. The other group of employees was subordinate to supervisors that did not receive the training yet. These employees (587) were all working in the nursing department of the branch in Zutphen.
The link to the questionnaire was put on the intranet of the hospital. Employees were informed about the questionnaire by their supervisors, and if they did not have access to the intranet they received the link to the questionnaire by email. Two weeks after launching the survey, employees were reminded to fill out the survey. Filling out the survey was voluntary, and it was made clear that the survey was anonymous. After a total of three weeks, data collection was closed.
Of a total of 1108 employees, 218 employees completed the survey, of which 91 were working in the GSS department. The total number of respondents translates into a response rate of 19.7% percent. Out of the respondents 173 were female and 45 (20.6%) were male. A large percentage of the employees was over 50 years old (42.7%). When comparing this with the hospital’s personnel statistics, the sample is quite representative. Of the employees in the hospital about 17% is male, and about 36.5% of the employees is over 50 years old. The employees in the sample worked on average 27.3 hours per week. Most of the employees were highly educated (50%), which means they had either completed higher professional education or university. On average, people were absent 4.51 days per year, with a mean frequency of 0.98 times per year.
In addition to the survey data, access to the hospital’s absence records and personnel statistics was provided, so comparison between the sample outcomes and the departmental statistics was possible to check whether the sample represented the population.
Measures
Leader behavior training. The independent variable in this study is the training of leader behavior of supervisors. It was measured as a categorical variable, as respondents were asked to indicate whether they were working in the General Supportive Services department.
This immediately indicated whether their supervisors took part in the training or not. From supervisors who did receive the training it is assumed that they are currently applying (to a greater extent) the behavior that was trained on. This assumption is based on the hospital's internal training evaluation documents, where participants indicated that based on the training they planned to for instance 'approach employees differently when they intend to be absent', 'pick up on signals of dissatisfaction at an earlier stage', 'discuss employees' absence behavior and take preventive actions', and 'listen better to employees to find out the underlying reason for their absence' (Gelre Ziekenhuizen, 2013).
Mediators. 4 different mediators of the relationship between the training and absence reduction were measured. First of all, absence culture was measured based on perceived standards using Markham and McKee’s (1995) operationalization. Two single-item metrics were used for this. The first item, external managerial standard, contained the following item: “What do you think management’s goal for absenteeism is for you?” The second item, internal personal standard, was measured by the following item: “In your view, what is an acceptable level of absenteeism here?” The answer options ranged from ‘perfect attendance’
to ‘7 days a year or more’ on a 5-point Likert scale. These two variables perfectly align with the definition of absence culture described previously, and therefore provided an excellent measurement. Even though the measures correlated significantly, they were not transformed into one variable, as the reliability turned out to be low (Cronbach’s α = .43).
Affective organizational commitment was measured using the 6-item scale developed by Meyer, Allen and Smith (1993) (Cronbach’s α = .83). A 5-point Likert scale was used to measure respondents’ level of agreement with each of the statements (1 = “strongly
disagree”, 5 = “strongly agree”). Examples of statements are ‘I would be very happy to spend the rest of my career with this organization’ and ‘This organization has a great deal of
personal meaning for me’. The reversed items were inverted, as grammatical problems (multiple negation) emerged when translating the items.
In line with previous research (amongst others Hytti, Kautonen & Akola, 2013), a 5- item scale selected from the 18-item index by Brayfield and Rothe (1951) was used to
measure job satisfaction (Cronbach’s α = .82). Again, a 5-point Likert scale was employed (1
= “strongly disagree”, 5 = “strongly agree”). Included in this scale were statements like ‘Most days I am enthusiastic about my job’ and ‘I find real enjoyment in my work’.
Motivation was measured as intrinsic job motivation according to the intrinsic motivation subscale as developed by Bakker (2008) (Cronbach’s α = .76). Items included ‘I work because I enjoy it’ and ‘I would still do this work, even if I received less pay’. Also for this variable a 5-point Likert scale was used to measure respondents’ level of agreement (1 =
“strongly disagree”, 5 = “strongly agree”).
Absence. The dependent variable of absence was measured in terms of frequency and duration. Only absence related to health was included in the measurement. Respondents were asked to fill out how many days and how many periods of time they were not able to work due to health problems during the last year.
Some of the respondents filled out inconsistent data (e.g. being absent for 2 days, but 0 periods). These data were deleted and treated as missing data. The number of cases that were deleted and treated as missing data were 4 for absence duration, and 7 for absence frequency.
Because the distributions of both absence duration (skewness = 8.45, SE = 0.17;
Kurtosis = 85.16, SE = 0.33) and absence frequency (skewness = 9.04, SE = 0.17; Kurtosis = 107.25, SE = 0.33) were severely skewed, log transformations were conducted. This lead to reasonable normality distributions for absence duration (skewness = 1.30, SE =0.17; Kurtosis
= 1.89, SE = 0.33) and absence frequency (skewness = 1.02, SE = 0.17; Kurtosis = 2.49, SE = 0.33).
Survey results on this variable were compared with the recorded company results to check whether they were representative. It turned out that the percentages for absence
frequencies are quite similar to each other (e.g. hospital reports 42% of the employees with no absence in 2014 vs. 43% in the sample), as shown in Table 1. The average frequency is a little lower, being 1.0 in the sample, while 1.2 for the entire hospital in 2014. In terms of absence duration though, there is a significant difference. The average reported absence duration within the hospital equaled 17 days in 2014, while in the sample this was only 4.5 days. A possible explanation for the latter difference might be that the employees with high absence
rates were reluctant to fill out the survey, or that they were ill at the moment the survey was distributed and thus were not able to participate in the research.
Table 1 Comparison of absence frequencies in the hospital records and the sample Absence Frequency Hospital Records (2014) Sample
0 42% 43%
1 31% 37%
2 15% 12%
3 7% 5%
> 3 5% 3%
Average 1.2 1
Control variables. In this study a few control variables were used, namely gender, age, educational level and contract hours. These variables may correlate with absence, and
therefore confound relationships under scrutiny.
Gender was included as a control variable because various studies have pointed out that women are absent more often than men (Steers & Rhodes, 1978; Harrison & Martocchio, 1998). Explanations for this might be the types of jobs that women have or their family responsibilities. Therefore it is expected that gender and absence are related.
Age was included as research has pointed out that younger employees tend to be absent more often and for shorter times (Tanhiälä, Linna, Von Bonsdorff, Pentti, Vahtera, Kivimäki & Elovaino, 2013). One of the reasons behind this would be that older employees experience a better person-organization fit (Harrison and Martocchio, 1998). It could also be that older employees for instance do not experience domestic crises, and therefore are absent less often. Therefore, age may correlate with absence, and thus was included as a control variable.
Educational level was included as studies have shown that education level strongly relates to sickness absence (Sumanen, Pietiläinen, Lahti, Lahelma & Rakonen, 2015; Piha, Laaksonen, Martikainen, Rahkonen & Lahelma, 2010). Underlying reasons may be that higher educated people have more knowledge on health, and therefore live healthier. In addition to that, lower educated people in general are positioned lower in the organizational structure, which may lead to higher physical demands of the work, and thus increase sickness absence.
Contract hours were included as a control variable because the more hours employees work per week, the bigger the chance is that they are sick on a day of work, which affects absence rates.
RESULTS Documented company information
Job satisfaction. From the results of the employee survey that was distributed in 2012 (a year before the training was given to the supervisors) it follows that in terms of job
satisfaction the GSS group scores lowest (7.3 out of 10) on this variable, while the non-GSS group of this survey scores the highest on job satisfaction (7.7 out of 10). According to the
Table 2 Means, standard deviations, correlations, and reliabilities of the variables included in the analysis.
M SD 1 2 3 4 5 6 7 8 9 10 11
1. Absence durationa .89 1.02
2. Absence frequencya .51 .52 .84**
3. Job Satisfaction 3.72 .62 -.11 -.14* α=.82
4. Organizational Commitment 3.45 .66 -.06 -.15* .57** α=.83
5. Motivation 3.65 .90 -.06 -.09 .54** .45** α=.76 6. Internal Personal Standard 3.11 1.08 .24** .27** -.14* -.12 -.05
7. External Managerial Standard 2.02 1.06 -.09 -.06 .03 .07 .24** .27**
8. Gender (1 = male) 1.79 0.41 .00 .05 .14* .07 -.03 .07 .01
9. Age 3.97 1.12 .03 -.05 .06 .31** .18** .00 .09 -.07
10. Education Level 3.44 1.39 .04 .04 -.13 -.16* .00 .07 .10 -.17* .00
11. Contract Hours 27.33 9.45 .10 .06 .10 .20** .07 -.04 -.04 -.26** .38** -.03
12. GSS (1 = no) 1.42 .49 -.02 -.04 -.10 -.03 .01 -.10 -.16* -.14* .02 .14* -.15*
Note: Scale reliabilities are shown on the diagonal.
a Log-transformed variable.
** p<.01.
* p<.05.
included analysis, both of the scores differ significantly from the average job satisfaction in the hospital (7.5 out of 10), and thus from each other.
Descriptives
Table 2 shows the descriptive statistics of all the variables involved in the study. They include the variables’ means, standard deviations, correlations, and (if applicable) their reliability. Absence duration and absence frequency show a significant positive correlation, and both correlate positively with internal personal standard as well (p < .01). Absence frequency additionally shows a negative correlation with both job satisfaction and
organizational commitment (p < .05). Job satisfaction on its turn shows a negative correlation with internal personal standard (p < 0.5), while organizational commitment positively
correlates with age as well as contract hours (p < .01). Interesting is the fact
that GSS negatively relates to external managerial standard (p < .05), which means that employees with trained supervisors perceive their supervisors as tolerating less absence.
Surprisingly, motivation turns out to correlate positively with external managerial standard with a high level of significance (p < .01). This means that the employees that perceive their supervisor as tolerating less absence are less motivated. Expected correlations are those between internal personal standard and external managerial standard (p < .01), as well those between job satisfaction, organizational commitment, and motivation (p < .01).
Model testing
Analysis of Variance (ANOVA). To determine whether there was a difference
between the GSS group and the non-GSS group in the mean values of the mediating variables, a one-way ANOVA was carried out. A statistically significant difference was found between the external managerial standard of the groups (F(1,216)=5.63, p = .02). The GSS group therefore had a lower external managerial standard for absence (M = 1.82, SD = 1.07) than the non-GSS group (M = 3.20, SD = 1.08), meaning that the GSS group perceived the standard that management set for an acceptable level of absenteeism to be higher than the non-GSS group did. For the other variables there was no statistically significant difference between the means of the groups. An overview of the results is given in Table 3. These results suggest that regarding the followers the training has only been successful in terms of supervisors tolerating less absence.
Correlations. To assess the effect of the mediating variables on absence in terms of absence duration and absence frequency, correlation outcomes were used (see Table 2).
Internal personal standard showed a statistically significant positive correlation with absence duration (p < .01), and absence frequency (p<.01). This means that the higher the level of absenteeism that the employee considers acceptable, the more, and the longer this person is absent. Job satisfaction and organizational commitment showed a statistically significant negative correlation with absence frequency (p < .05). This means that the more satisfied about his work and the more committed an employee is to the organization, the less this person is absent.
Table 3 Results of the one-way ANOVA analysis.
GSS M SD F Sig.
Internal Personal Standard Yes No
2.99 3.20
1.07 1.08
1.97 .16 External Managerial Standard Yes
No
1.82 2.17
.97 1.10
5.63 .02*
Job Satisfaction Yes
No
3.65 3.77
.64 .61
1.95 .16 Organizational Commitment Yes
No
3.43 3.47
.71 .62
.19 .66
Motivation Yes
No
3.66 3.64
.93 .89
.02 .88
* p < .05
Regression and mediation. The last step of the research involved using
regression analysis to determine whether the proposed hypotheses were supported by the data or not. This was done by using the PROCESS application to analyze mediating effects.
Following the recommendations of Becker (2005) no control variables were included in this analysis, as none of them correlated significantly with absenteeism measures (see Table 2).
First the analysis was carried out for each mediator separately, and after that all variables were entered simultaneously. An overview of the outcomes can be found in Tables 4 and 5.
Hypothesis 1 states that absence culture mediates the negative indirect effect that training supervisors has on absenteeism. The results do not support this hypothesis as a 0 is found in between the lower and upper confidence intervals (LLCI and ULCI). To the contrary, a statistically significant positive effect was found for the mediation of the relationship between training and absence duration (LLCI = .0002 and ULCI = .1594) and absence frequency (LLCI = .0008 and ULCI = .0793) by external managerial standard, but only when the effects of all mediators were assessed simultaneously. This might mean that employees with untrained supervisors had lower external managerial standards (meaning management is seen as accepting more absences), and therefore were absent less often and shorter times. The opposite then holds for employees with trained supervisors.
Table 2 Outcomes of the mediation analyses when assessing the effects of separate mediators.
Absence Duration Absence Frequency
Mediator Effect LLCI ULCI Effect LLCI ULCI
Internal Personal Standard
Direct effect of GSS .0031 -.2726 .2788 -.0092 -.1502 .1318 Indirect effect -.0528 -.1521 .0040 -.0281 -.0806 .0065 External Managerial
Standard
Direct effect of GSS -.0855 -.3706 .1995 -.0486 -.1959 .0988 Indirect effect .0359 -.0087 .1134 .0112 -.0084 .0522 Job Satisfaction Direct effect of GSS -.0702 -.3519 .2115 -.0523 -.1973 .0926 Indirect effect .0205 -.0071 .0865 .0150 -.0038 .0564 Organizational
Commitment
Direct effect of GSS -.0520 -.3338 .2297 -.0427 -.1868 .1015 Indirect effect .0023 -.0112 .0499 .0054 -.0124 .0418 Motivation Direct effect of GSS -.0481 -.3300 .2337 -.0347 -.1799 .1105 Indirect effect -.0015 -.0574 .0153 -.0026 -.0338 .0104 Note: The effect is significant (p <.05) when there is no 0 in between the LLCI and ULCI.
Hypothesis 2 states that training supervisors has an indirect negative effect on
absenteeism that is mediated by affective organizational commitment. No support was found for this hypothesis either with or without controlling for other mediators. For instance for absence duration LLCI = -.0347 and ULCI = .0206, and for absence frequency LLCI = -.0061 and ULCI = .0389 when controlling for the other mediators, which means there is no
statistically significant effect and the relationship between training and absenteeism cannot be explained by affective organizational commitment.
Hypothesis 3 was not supported either. No statistically significant mediating effect of job satisfaction on the relationship between training and absenteeism was found. When controlling for the other mediators for absence duration LLCI = -.0110 and ULCI = .1131, and for absence frequency LLCI = -.0110 and ULCI = .0659. Job satisfaction therefore does not explain the aforementioned relationship.
Table 3 Outcomes of the mediation analyses when assessing the effects of all mediators simultaneously.
Absence Duration Absence Frequency Effect LLCI ULCI Effect LLCI ULCI Direct effect of GSS -.0717 -.3518 .2048 -.0425 -.1681 .1010 Total Mediation .0221 -.0970 .1443 .0052 -.0670 .0851 Internal Personal Standard -.0594 -.1631 .0035 -.0295 -.0840 .0042 External Managerial Standard .0613 .0002 .1594 .0233 .0008 .0793 Job Satisfaction .0197 -.0110 .1131 .0074 -.0110 .0659 Organizational Commitment -.0007 -.0347 .0206 .0031 -.0061 .0389
Motivation .0011 -.0207 .0474 .0010 -.0109 .0351
Note: The effect is significant (p <.05) when there is no 0 in between the LLCI and the ULCI.
No support was found for hypothesis 4. The relationship between training and absenteeism was not found to be mediated by motivation, as both when just motivation was entered as a separate variable (LLCI = -.0574 and ULCI = .0153) and when all variables were entered (LLCI = -.0207 and ULCI =.0474) 0 was found in between the lower and upper bounds, and therefore the mediating relationships were not statistically significant.
DISCUSSION
Although in general the results do not show significant support for the hypotheses, it would not be right to jump to conclusions about the relationship between training and absence yet. Therefore this section will discuss the research outcomes in the light of the current
literature and managerial practice.
This study investigates the link between training supervisors on absence reducing behavior, and employee absenteeism. By comparing employee attitudes of two separate groups, the mediating effect of these attitudes on the relationship between training and absenteeism is investigated.
Absence culture
Firstly, it is found that in terms of absence culture, internal personal standard does not mediate the indirect negative relationship between training and absenteeism. Significant correlations however are found for internal personal standard and absenteeism (for both absence frequency and duration). The latter is in line with previous research of Markham and McKee (1995) where supervisory groups with lower internal personal standards (meaning accepting more absences) had more absence incidents.
A possible explanation for these correlations can be found in the cognitive dissonance theory by Festinger (1957). This theory states that inconsistent cognitions provoke a state of dissonance, which in turn elicits the need to reduce the underlying inconsistency and preserve a state of consonance (Gawronski, 2012). When applying this to absence and internal personal standard this would mean that lower absence of an employee is due to the need for
consonance between the employee’s high personal absence standard (cognition) and his absence behavior (actions).
However, no significant differences are present between the GSS and non-GSS group on this variable, which might explain why no mediating effect is found for internal personal standard, even though the internal personal standard does have a significant effect on absence behavior.
For external managerial standard a significant mediating relationship is found, but only when all mediators are included in the analysis simultaneously. The effect is not significant when the mediating effect of just external managerial standard is assessed. Thus, the results are not straightforward (and do need additional investigation).
In addition to that, the significant effect is the exact opposite of the hypothesized relationship, and contradicts previous research like that of Markham & McKee (1995), as it is found that employees with untrained supervisors perceive their supervisors as tolerating more absence and therefore have lower absence frequency and shorter absence duration. The opposite holds for employees with trained supervisors. An explanation for this might lie in the psychological reactance theory.
Psychological reactance. Psychological reactance is a motivational force that may arise when someone’s (behavioral) freedom is lost that might lead to the employment of different types of behavior to regain or prevent the loss of (behavioral) freedom (Middleton, Buboltz & Sopon, 2015). In this case employees with trained supervisors experience lower tolerance of absence behavior (a higher managerial standard), and therefore experience a loss in their freedom to be absent.
The reactant responses to losing freedom vary, but can be categorized in roughly two types: a verbal response, and a behavioral response. The latter refers to actual conduct to regain control, for instance by increasing preference for the banned behavior and attempting to engage in that behavior (Middleton, Buboltz & Sopon, 2015). Thus, the behavior that is to be banned is increasingly employed. This might explain why employees with trained
supervisors, who are trying to ban absenteeism, are absent more often and for a longer time.
The degree to which reactance occurs depends on various factors, for instance the way the message is framed. Empirical evidence shows that negative framing might induce
psychological reactance (Shen, 2015). Supervisors should therefore be careful in
communicating their managerial absence standards, as this might adversely impact the results of higher standards.
The explanation presented above however is post-hoc, tentative and somewhat speculative, and therefore needs further research.
Job Satisfaction
While in correspondence with previous research (e.g. Brooke & Price, 1989; Steel, Rentsch & Van Scotter, 2007) a significant negative correlation exists between job
satisfaction and absence frequency (see Table 2), in this study job satisfaction does not mediate the relationship between training and absenteeism. A possible reason for this may be that the groups do not differ significantly from each other in their scores on job satisfaction.
However, when taking into account the fact that in the employee survey from 2012 the GSS group had a significant lower score on job satisfaction it might still be the case that the training increased job satisfaction among the GSS employees, leading to a non-significant difference between the scores of the two groups after the training. But again, this is a post-hoc explanation that needs further empirical support.
Affective Organizational Commitment
Affective organizational commitment does not mediate the relationship between training and absenteeism in this study. Nevertheless, a negative correlation is found between organizational commitment and absence frequency. This supports previous research on the relationship between organizational commitment and absence (Woods, Poole & Zibarras, 2012; Harrison & Martocchio, 1998). An underlying reason for this relationship might be that people feel a greater obligation to adhere to the attendance policy and are thus more motivated to attend work every day (Burton, Lee & Holtom, 2002).
No significant differences are found between the two groups in terms of affective organizational commitment though, as the difference in score was only 0.04. An underlying reason for this could be the current job insecurity of people working in healthcare
organizations, due to the free market processes, cost cutting and the resulting continuous changes in the working environment. As research has pointed out, job insecurity has a negative effect on work attitudes and changes an employee's behavior towards the
organization (De Witte, 1999; Vujicic, Jovicic, Lalic, Gagic & Cvejanov, 2015). This might have ruled out the effect of the training, which might explain why the training did not have the hypothesized impact.
Motivation
For the last hypothesis no support is found either. Besides that, no significant correlations between motivation and absence are present in this study. The latter is
remarkable, as it contradicts previous research, like that of Brummelhuis et al. (2013), who found a significant relationship between motivation and absence.
A possible explanation for this outcome might be that some of the highly motivated employees put that much energy in their work that they need to take time off from work to
recuperate (Shantz & Alfes, 2015), especially when doing physically demanding work like nurses and people in the GSS department. This might then balance out the effect of lower absence as a result of high motivation, and thus lead to a non-significant relationship between motivation and absence. Again, such post-hoc explanations are speculative and need further empirical support.
Limitations
The presented results must be seen in the light of several limitations. In the first place, the study was carried out as a cross-sectional study, which means that the data were gathered at one specific point in time. Because the training had already taken place before the study was set up, it was not possible to collect data before the training was given. (Long term) trends in scores of both groups on the proposed mediating variables could therefore not be analyzed. Changes in scores (due to the training) might have taken place within groups, but have not been assessed. This increases difficulty to substantiate cause and effect relationships.
Secondly, the groups under scrutiny differ in terms of type of occupation. There is a possibility that this affected the results in terms of comparability and bias (the survey from 2012 indeed indicates that the two groups differed in terms of job satisfaction before the training was given). Both groups do however function in the same organizational
environment, and are built up of employees with varying occupations on various levels, which might minimize these effects.
Lastly, even though the participants indicated that they had the intent to change their behavior due to the training, this does not give any certainty about an actual change.
Therefore, it is unknown whether the training had the intended effect on the behaviors mentioned in the hypotheses (i.e. displaying a low degree of acceptance of absenteeism, willingness to help the employee, monitoring the balance between the employee and his or her work, communication skills), and whether these effects had an influence on the dependent variables through the mediators. Thus, there are variables that mediate the relationship
between the independent variable and the mediators in this study that have not been included.
Directions for Further Research
The study also provides some leads for further research. In the first place, the results for external managerial standard are not straightforward, and thus it would be interesting to further explore the effect of this variable on absence, more specifically regarding
psychological reactance. As outlined before, it might be that the way the managerial standard is set, determines the effect that this variable has on absenteeism. Moreover, this study specifically focused on employee behaviors as mediating variables for the relationship between training and absence, and implied that the training did change the behavior of the supervisors. The impact of the training on leader behavior has therefore not been assessed, but it would be interesting to find out whether their behavior actually changed. It would be
preferable to test leader behavior before and after the training, to be able to substantiate cause and effect relationships. Lastly, because internal personal standard shows a strong positive correlation with both absence frequency and absence duration, it would be valuable to further
investigate the antecedents of internal personal standard, as to find out whether there is a possibility for supervisors to influence this variable as a means to reduce absenteeism.
Managerial Implications
The research conducted provides useful insights for managerial practice. Even though the effects of the training are rather unclear, the results do show the importance of
employees’ wellbeing at work as a means to decrease absenteeism. When employees are satisfied with their job and committed to the organization they will be absent less frequent.
Therefore, it is crucial for supervisors to monitor employee wellbeing. Additionally, this study shows that the nature of the relationship between setting a managerial standard and absenteeism is probably quite complex. Although previous research has established the positive relationship between external managerial standard and absenteeism, this study does not support this finding. Supervisors should therefore be cautious when communicating desired absence behavior, as adverse effects might occur.
CONCLUSION
This study investigates the mediating effects of absence culture, job satisfaction, organizational commitment and motivation on the relationship between training and absence by means of regression analysis. Although no support for the hypotheses is found, and thus no conclusions can be drawn on the effectiveness of the training, the results show that job
satisfaction, affective organizational commitment and absence culture do indeed predict absenteeism. Additionally, the results indicate that, as part of absence culture, external managerial standard does mediate the relationship between training and absence in a manner exactly opposite of the hypothesis, as employees with untrained supervisors are absent less frequent and shorter times because the supervisors tolerate a higher absence level. This contradicts previous findings, and therefore additional research is necessary to fully
understand the effects of managerial standards on absenteeism. Nevertheless, we can conclude that employee well-being plays a crucial role in reducing absenteeism rates.
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