Concurrent with high prevalence of sickness presenteeism there are frequent reports on symptoms of burnout among physicians (Arigoni, Bovier, & Sappino, 2010; Houkes, Winants, Twellaar, & Verdonk, 2011; Peterson et al., 2008; Prins et al., 2010). Burnout is defined by the two main dimensions of emotional exhaustion and disengagement resulting from work demands (Demerouti, Bakker, de Jonge, Janssen, & Schaufeli, 2001). Emotional exhaustion may develop as a consequence of demanding cognitive, affective and physical strain (Demerouti, Bakker, Vardakou, & Kantas, 2003). Disengagement refers to the experience of negative attitudes toward work in general, the work object or the work content. It also refers to distancing oneself from one’s job (Demerouti et al., 2003). The relative frequent reports of both sickness presenteeism and burnout among physicians impose the necessity to look at these two phenomena in relation to one another.
The coexisting occurrence of sickness presenteeism and burnout in some occupations has resulted in a few studies investigating the relationship between these two health behaviours and its nature. A study of hospital nurses suggests a reciprocal relationship between burnout and sickness presenteeism (Demerouti, Le Blanc, Bakker, Schaufeli, & Hox, 2009). Sickness presenteeism was reported to increase the likelihood of burnout if there was inadequate physical and psychological recovery after disease or strain (Demerouti et al., 2009; Meijman & Mulder, 1998). In addition, Dellve et al. (2011) found that sickness attendance was associated with burnout, poor health, and sick leave. In a study of doctors having burnout symptoms the decrease of sickness presenteeism measured as increase in sick leave, prevented later burnout (Rø, Tyssen, Gude, & Aasland, 2012). These studies indicate that sickness presenteeism could be a relevant predictor for burnout. However, we lack studies on the relative influence of sickness presenteeism on burnout compared with other work factors known to affect stress, health, and well-being among physicians.
The Job Demand-Resources Model (JD-R) states that when job demands are high and there are few job resources there is a higher risk of burnout (Bakker & Demerouti, 2007; Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). Job demands are organizational, social or physical aspects of the job that require sustained physical and/or psychological effort from the employee (Demerouti, Bakker, de Jonge et al., 2001). Medical academics are exposed to high and often conflicting demands as they are expected to conduct original medical research, teach, and perform administrative and clinical duties. As the nature of the work in university hospitals is in itself stressful, this group of physicians are exposed to occupational stressors and a psychosocial work environment that is characterised by risk factors that according to the JD-R model will be negatively associated with their stress and health (Bakker & Demerouti, 2007; Demerouti, Bakker, Nachreiner et al., 2001; Piko, 2006). Sickness presenteeism among employees, e.g., academic physicians, can result from workplace characteristics creating attendance pressure to fulfil their duties at work (Grinyer & Singleton, 2000; McKevitt & Morgan, 1997; McKevitt et al., 1997; Thun, Saksvik, Mehmetoglu, Ose, & Christensen, 2013). In addition, their high workload combined with concerns for their own career opportunities, patients and colleagues, as well as responsibilities for family and social life can compromise sufficient self-care, restitution, and rest (Fridner, 2004) which in turn can cause high levels of sickness presenteeism in this profession. According to the JD-R model, sickness presenteeism may constitute a demand that can have an effect on employees’ health and well-being. To reduce the negative effects of high demands, the JD-R model shows that physical, social, and organizational aspects of the work may constitute resources that are functional in achieving work goals (Demerouti, Bakker, de Jonge et al., 2001).
The JD-R model shows that resources such as a supportive social network from both supervisors and colleagues are important to moderate stress and burnout (Humphrey, 2013; Viswesvaran, Sanchez, & Fisher, 1999; Eisenberger, Huntington, Hutchison, & Sowa, 1986; Hoff, Whitcomb, & Nelson, 2002; Karasek & Theorell, 1990; Luchman & Gonzalez-Morales, 2013; Russell, Altmaier, & Vanvelzen, 1987). Another important resource is job control (e.g.; Fernet, Austin, Trepanier, & Dussault, 2013; Peterson et al., 2008; Demerouti, Bakker, Nachreiner et al., 2001) which refers to an employee’s decision authority or work autonomy (Demerouti, Bakker, Nachreiner et al., 2001; Lee, Lovell, & Brotheridge, 2010). Job control has been consistently related to high job performance as well as low strain in the organizational literature (Alarcon, 2011; Johns, 2011; Maslach, Schaufeli, & Leiter, 2001) and has also been seen as health promoting (Claes, 2011). Control over work can modify the process of burnout, and research has shown that control over work pace and decisions explain some of the variance in exhaustion and disengagement among physicians in academic medicine (Løvseth, Fridner, Jónsdóttir, Marini, & Linaker, 2013).
The high prevalence of sickness presenteeism among physicians highlights the importance of systematic investigation of this phenomenon because it can affect the quality of health care provided (Shanafelt, Bradly, Wipf, & Back, 2002), the quality of work (Shirom, Nirel, & Vinokur, 2006) as well as their long-term health (Bergström, Bodin, Hagberg, Aronsson et al., 2009; Kivimaki et al., 2005). It is important to investigate this relationship and its associated factors to create appropriate theories of work design and occupational stress interventions (Luchman & Gonzalez-Morales, 2013), which could then be implemented to decrease the prevalence of burnout and sickness presenteeism in the medical profession.
National and occupational contexts are relatively neglected factors for understanding work-related health (Thun et al., 2013). Multinational group comparisons of physician health and work conditions are often necessary in research as they increase the possibility of generalizing the results. There are also studies which show inconsistency in findings in how gender and age affect burnout (Maslach et al., 2001; Purvanova & Muros, 2010). Houkes et al. (2011) found that high levels of depersonalization is found in male general practitioners, while emotional exhaustion is found in female general practitioners, and according to Walsh (2013) it is more likely that female doctors experience burnout. Therefore, it is relevant to investigate whether nationality, age and gender modify the relationship between burnout and sickness presenteeism, and these factors are therefore controlled for in this study.
The main aim for the present study was to explore the relationship between sickness presenteeism and burnout among physicians in four European countries, while controlling for job resources such as social support, control over work pace, and decision-making and demographic variables like age, gender, and nationality.
Hypothesis 1. Sickness presenteeism is positively associated with disengagement when controlling for demographic variables and job resources.
Hypothesis 2. Sickness presenteeism is positively associated with exhaustion when controlling for demographic variables and job resources.
Participants and Procedure. The present study used data from all participants in a study concerning work related health, organizational culture and working conditions among university hospital physicians in Norway, Sweden, Iceland and Italy. The present study is a part of a larger on-going project (e.g., Fridner, 2004; Løvseth et al., 2013; Sendén et al., 2013). The project was approved by the administration of each hospital, the respective Regional Ethics Boards and National Data Inspectorates. In addition to a short oral presentation given in organizational forums, all participants received a letter with a description of the study. All physicians voluntarily participated and completed the informed consent that was required.
The survey was administered both on the web and in paper format. All participants received a letter containing personal password and log-in information for the web-based questionnaire. The joint data collection of the web survey was organized centrally for the three Nordic countries at the project website. The survey was conducted in English in all countries except for Italy. The Italians received questionnaires in their native language and in paper format only. The Italian version was validated using back translation between English and Italian. The data collection was carried out from December 2004 to February 2006. Invited physicians were permanently employed and actively working at the time of data collection (N =3947), and included both full-time and part-time physicians. Anonymity was guaranteed, and it was emphasized that individual data could not be identified in any way.
The total response rate was 52.6% (N=2078/3947). In Norway the response rate was 54.7%, in Sweden 59.8%, Iceland 47.8%, and 41.3% in Italy. There was lower participation among male physicians (48.5%) than female physicians (58.5%). In total, 378 physicians participated from Norway, 1074 from Sweden, 254 from Iceland and 372 from Italy. A response analysis showed that all countries had an acceptable response rate and demographic representation according to physician age, gender and position.
Measures. The questionnaire consisted of 107 items concerning education, work-related health, organizational culture, and working conditions. The present study was based on a selection of variables relevant to the current foci and included burnout measured by the dimensions of exhaustion and disengagement, sickness presenteeism, social support from both colleagues and supervisors, control over work pace and decision-making, gender, age and country.
Burnout. The outcome variable of the current study of burnout was measured by a Mini version of Oldenburg Burnout Inventory (Demerouti et al., 2003; Rudman, Gustavsson, & Hultell, 2014; Løvseth et al., 2013). The two dimensions of exhaustion (α = .80) and disengagement (α = .77) consist of five items each. «After my work, I now need more time to relax than in the past to become fit again» was one item measuring exhaustion. An example of disengagement was: «It happens more and more often that I talk about my work in a derogatory way.» The response scale was «totally agree» (1) to «totally disagree» (4). The index included both positively and negatively worded items. The positive and negative items were presented in mixed order, and the negatively worded items were revised. Peterson et al. (2011) and Halbesleben and Demerouti (2005) have found support for the validity, reliability and the proposed two-factorial structure of the original version of the Oldenburg Burnout Inventory.
Sickness presenteeism. The item «Have you gone to work with an illness in a situation where you would have recommended a patient to stay at home?» measured sickness presenteeism (Rosvold & Bjertness, 2001; Sendén et al., 2013). The response was rated from «very seldom or never» (1) to «very often or always» (5). This type of question is in line with what Johns (2011) labels “subjective presenteeism” meaning that it incorporates a more perceptual take on respondents’ experiences with their own health and attendance as opposed to the most commonly used «days-present» item developed by Aronsson et al. (2000).
Job resources. Social support was measured by the item «How much can people as listed below be relied upon for support when things get tough at work?» The item was rated with references to the immediate supervisor (support supervisor) and the physicians’ colleagues (support colleagues), respectively. Responses were on a five-point scale ranging from «not at all» (1) to «very much» (5). A high score for each item of support indicated high levels of support (Andersen, Aasland, Fridner, & Løvseth, 2010; Fridner et al., 2011; Løvseth et al., 2013).
The scales for the variables «control over work pace» and «control over decision-making» were derived from the General Nordic Questionnaire for Psychological and Social Factors at Work (QPS Nordic) (Lindström, 2000). Control over work pace consists of four items (α =.84). One item asked respondents to consider how often they could set their own work pace. Control over decision-making consisted of two items (α =.45). One item was «If there are alternative methods for doing your work, can you choose which method to use?» The response was rated from «very seldom or never» (1) to «very often or always» (5) on all items of each scale. The scale alphas correspond to the validation data on QPS Nordic (Wannstrom, Peterson, Asberg, Nygren, & Gustavsson, 2009); however, three of the original items of control over decision-making were not thought to be relevant for the participants (e.g., “contacts with customers”), and were removed from the questionnaire.
Control variables. Age was measured in nine age categories (from >29, 30-34 … to <65. Gender was coded with male = 1 and female = 0. All countries were dummy coded, and Sweden was the reference category, meaning that the effects of the other countries were compared to Sweden. The country with the largest sample became the reference category, following the procedures described in Field (2009).
Statistical analysis. Pearson’s correlations were used to measure relationships between the included variables. The predictor variables’ influence on the dimensions of burnout and other relevant correlates of burnout and sickness presenteeism were investigated with a block-wise hierarchical regression analysis. Potential multicollinearity was used to examine the variance inflation factor (VIF). All indices were developed according to recommended criteria (Field, 2009). One-way ANOVA was used to test significant differences between countries. Hochberg GT2 and Games-Howell Post Hoc test was conducted (Field, 2009). Hochberg’s GT2 procedure is designed to manage situations where the sample sizes differ. All independent variables measured with response scales had sufficiently normal distribution to warrant parametric tests. All analyses were conducted with IBM SPSS Statistics, version 19.
Table 1 presents the mean score of each variable of the total sample and of each country. The mean score of exhaustion was M = 2.52 (SD = 0.53), which indicates high scores of exhaustion in the total sample. The participants reported a lower mean score M = 2.14 (SD = 0.48) at disengagement. Scores about 2.25 have been considered as having high exhaustion, and scores over 2.1 on disengagement have been considered as high in other studies using the same instrument (e.g., Peterson et al., 2008). The mean score at M = 3.01 (SD = 1.19) indicates a high score on sickness presenteeism among the participants in the total sample. Because existing knowledge and literature of this type of context specific measure is still limited, we have to base the cut off on other presenteeism measures. In research where they dichotomize a five-point scale, the cutoff is usually between not relevant to yes/once considered as not low sickness presence, and those answer yes/2-5 times and more than 5 times as high sickness presence (Aronsson & Gustafsson, 2005; Gustafsson & Marklund, 2014).
There was significant country differences in disengagement [F (3, 2002) = 17.02, p < .001] and exhaustion [F (3, 2002) = 17.15, p < .001]. The post-hoc tests indicate that the participants from Sweden had higher scores on disengagement than all the other countries (p < .001). The Swedish also had significantly higher scores on exhaustion than the participants from Norway and Iceland (p < .001). The sample from Italy had significantly higher scores on exhaustion than the samples from Norway (p < .05) and Iceland (p < .05).
|Control over decision-making||2.99||0.86||3.09||0.78||3.16||0.86||2.94||1.02||3.02||0.88|
|Control over work pace||2.67||0.98||2.68||0.88||2.67||0.98||3.08||1.08||2.75||0.99|
The bivariate correlations between the variables are presented in Table 2. Sickness presenteeism was positively related to disengagement (r = .10 p < .001) and exhaustion (r = .26, p < .001). Control over decision-making was negatively related to exhaustion (r = –.34, p < .001) and was the strongest correlate of exhaustion. The strongest correlate of disengagement was support from supervisor (r = –.32, p < .001).
|3. Sickness presenteeism||.10***||.26***||-|
|4. Support supervisor||-.32***||-.22***||-.12***||-|
|5. Support colleague||-.20***||-.14***||-.11***||.43***||-|
|6. Control over decision-making||-.29***||-.34***||-.11***||.24***||.15***||-|
|7. Control over work pace||-.24***||-.31***||-.14***||.09***||-.01||.52***||-|
|NOTE: *** p < .001 (Two-tailed)|
We performed hierarchical regression analysis for each burnout dimension. The hierarchical multiple regression analysis (Table 3) indicates that sickness presenteeism was associated with disengagement when age, gender, country, support from superior, support from colleague, control over work pace, and control over decision-making were entered in the model, (β = .07, p < .001). The variables included in the model explained 21% of the variance in disengagement.
The hierarchical multiple regression analysis (Table 3) indicates that sickness presenteeism was associated with exhaustion when age, gender, country, support supervisor, support colleague, control over work pace, and control over decision-making were entered in the model (β = .19, p < .001). Furthermore, the additional variance explained by sickness presenteeism was 4%. The variables included in the model explained 24% of the variance in exhaustion.
|Control over work pace||-.19***||-.12***|
|Control over decision-making||-.17***||-.16***|
|NOTE: ** p < .01***; p < .001. Gender: 0 = Female; 1 = Male. β = Standardized beta.|
The main results of the present study support our initial hypotheses that sickness presenteeism is positively associated with the two dimensions of burnout when we control for known predictors of burnout. We found that sickness presenteeism was a significant predictor of exhaustion and disengagement and that the relationship was significant when controlling for other relevant job resources. It is possible that sickness presenteeism among employees is a risk factor that may worsen physician health and increase symptoms of burnout; however, this relationship needs to be tested in a longitudinal study. According to Demerouti and her colleagues (2009), an employee who is present when sick can become a more exhausted employee. Accordingly, employees who experience exhaustion activate compensation strategies like sickness presenteeism, which could in turn increase their exhaustion (Demerouti et al., 2009). The link between the variables can thus be that sickness presenteeism may predict burnout because it affects recovery (Meijman & Mulder, 1998). It seems that sickness presenteeism is an important risk indicator, and this supports the findings of Dellve et al. (2011) that sickness presenteeism is associated with burnout. However, it is unclear whether sickness presenteeism is a symptom of burnout or pre-burnout condition, or whether it is a cause of burnout. An important finding in this study is that sickness presenteeism has a distinctive contribution after controlling for other factors. Sickness presenteeism affects many employees and offers potential negative consequences at numerous levels (Claes, 2011).
As pointed out by Maslach and colleagues, it is important to control for resources in the prevalence and process of burnout (Maslach et al., 2001). In line with other empirical findings, the results confirm that an employee’s sense of control over work pace and decision-making, as well as high levels of social support, are relevant in the workplace to prevent burnout among physicians (e.g., Løvseth et al., 2013; Tayfur & Arslan, 2013), which indicates the importance of controlling for job resources. The results from this study also show that participants with support from supervisors and co-workers have lower scores on exhaustion and disengagement. Our findings confirm the importance of social support systems for physician’s health and well-being (Wallace & Lemaire, 2007). This result is important because it confirms the parts of the JD-R model which emphasize that low levels of job resources in support of the employees are associated with a higher risk for burnout (Demerouti, Bakker, Nachreiner et al., 2001). This underscores the importance of including a variety of predictors in order to fully understand the relationships between burnout and sickness presenteeism and its effect on the organization, the physician, and provision of healthcare services.
Another way to look at the relationship is that emotional exhaustion can be an important determinant of sickness absence and later sickness presenteeism (de Vroome, Smulders, & Houtman, 2010). The association between sickness presenteeism and exhaustion may be linked to a negative spiral with an unfavourable consequence in the long run. A positive correlation (r = .26, p < .001) may indicate that it is exhaustion that leads to sickness presenteeism. de Vroome et al. (2010) argue that emotional exhaustion may serve as an important marker to reduce sickness presenteeism. According to Demerouti and her colleagues (2009), it is likely that sickness presenteeism and burnout have a reciprocal relationship. There is a need for longitudinal studies to investigate whether there is a reciprocal relationship. This study contributes with an understanding that it is a positive relationship between burnout and sickness presenteeism, and that this knowledge is important to use in developing policies at the workplace. Although the study confirmed a relationship between burnout and sickness presenteeism, the specific link between these two variables remains a matter of speculation.
There are some cross-country differences to be mentioned. For instance, the participants in Sweden experienced higher levels of disengagement than the other countries. Differences between the subsamples can be explained by national differences in the countries studied such as structural factors of employment between the organizations, differences in the well-fare system on sickness absence among other (Bambra, 2007; Heymann, Rho, Schmitt, & Earle, 2010; Osterkamp & Röhn, 2007). Despite possible relevance, the variables mentioned are beyond the scope of the present study. However, this highlights the importance of including a variety of predictors to fully understand the relationships between burnout and sickness presenteeism and its effect on the organization, the physician and provision of health care services, and the need for additional multinational studies. Still, the relationship between sickness presenteeism and burnout were significant when we controlled for nation, which emphasizes that it is a general relation between these variables.
Study strength and limitations. This study contributes to the existing literature by investigating the relationship between sickness presenteeism and burnout in an occupation that has shown high rates of both sickness presenteeism and burnout. The strengths of this study are that it is multinational, has a large sample size, uses the same methodology in three international sites and uses standardized scales.
Limitations that should be considered regarding the findings of the present study are that the study was cross-sectional and relied on self-reported data, and that the study is not oriented toward causality but rather toward the parallel associations between workplace factors and burnout. In this study sickness presenteeism constitutes a demand that may have an effect on employees’ health and well-being. However, there may be a limitation that sickness presenteeism was the only job demand in this study. Future studies should include a variety of other job demands since job demands is an important predictor of burnout (Demerouti, Bakker, & Nachreiner et al., 2001).
In research on sickness presenteeism, it is difficult not to use self-reported data because it is the individual who knows if he or she is sickness present or not (Claes, 2011; Johns, 2011). The item used in this study (Rosvold & Bjertness, 2001) is more specific and context dependent than the most used item in research of sickness presenteeism (e.g. Aronsson et al., 2000; Aronsson & Gustafsson, 2005; Hansen & Andersen, 2009). A more specific item used in this study considers the contextual setting for the physicians and makes the results easier to apply to a specific setting. The advantage is that the question required physicians to consider themselves as patients and relate to situations and conditions where they would have recommended a patient to stay home. The measure of sickness presenteeism used in this study is not limited to a defined period, like 6 or 12 months. It is important to develop a more detailed and objective measure of sickness presenteeism in preference to a single item measure (Demerouti et al., 2009; Thun et al., 2013). Still, in some cases a single-item question may stand out as a good measure (DeSalvo et al., 2006).
The lack of established norms and validated clinical cut-off values for determining high levels of burnout and sickness presenteeism should be noted. The low alpha on the control over decision-making may also be a limitation and may affect the result. Additionally, the moderate response rate may be a limitation and makes it difficult to draw conclusions about university hospital physicians worldwide and in the countries included in the study. However, the sample size is large, the study is cross-national, and the sample is representative related to physician gender and age. We could assume that those who were truly burned out were on sick leave or absent due to other legitimate reasons, which means that those who participated are those who are still managing their daily work.
Furthermore, the Italian sample did not include medical residents, as they were employed at the university and not the university hospital. In research on burnout and sickness presenteeism it can be problematic to focus on only one occupation, because the motives of sickness presenteeism can be heterogeneous across occupations. However, Johns (2010) argues that sickness presenteeism depends upon context. Research findings show that burnout and sickness presenteeism is high irrespective of occupation (e.g Aronsson et al., 2000; Gosselin, Lemyre, & Corneil, 2013); therefore, it is reasonable to assume that these findings are relevant to other occupations.
The findings from this study have a practical applicability and may also contribute to development of theories within the field of work health and especially burnout. The present research contributes to the literature on employee burnout by examining the relationships between sickness presenteeism and employee burnout. In earlier research, health problems have been linked to burnout, but more as outcome variables or consequences of burnout, not as predictors. In this study, sickness presenteeism was significantly associated with employee burnout when controlling for known contributing factors such as job control and social support. The findings, therefore, not only contribute to the literature on burnout but also to the larger body of research on sickness presenteeism.
Sickness presenteeism is positively associated with the two dimensions of burnout.
Many work environments are characterized by high and often conflicting demands, responsibilities and workload. Although the present study focuses on physicians in academic medicine, we believe that the findings from the present study could apply in work environments where high sickness presenteeism and burnout intersect. The findings are assumed to be relevant and valid across several occupations.
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