Part-time Work and Sickness Absence – an Organization-level Analysis

doi:10.21203/rs.3.rs-2438069/v1

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Research Article

Part-time Work and Sickness Absence – an Organization-level Analysis

https://doi.org/10.21203/rs.3.rs-2438069/v1

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Journal Publication

published 14 Nov, 2023

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Background

Absenteeism is consistently higher in public than in private organizations, and represents great cost for both individuals, organizations, and society. Most research on absenteeism has focused mostly on the individual level, less on whether and eventually how one of all organizations’ basic organization of work – the number of hours worked – affects absence. This study focuses on the relationship between part-time work and sickness absence at the organizational level.

Methods

The data is a six-year panel for all Norwegian municipalities, linking register data on both part-time employment and sickness absence, while controlling for other relevant organizational and environmental variables like municipal size and economic resources. Data were analyzed using OLS regression with fixed effects for municipality and time.

Results

The main findings are that the organizations’ use of part-time work is unrelated to sickness absence.

Conclusions

While concerns have been raised on whether part-employees would be less attached to the organization, leading to higher absenteeism, this study indicates that organizations with extensive use of part-time work do not experience higher levels of absenteeism than those having less extensive use of part-time employees.

Part time work

sickness absence

Human Resource Management architecture

working hours

Absence from work – or absenteeism – is much higher in the public than in the private sector, and this difference cuts across national borders and is stable over time (Mastekaasa 2020). Furthermore, absenteeism is one of the costliest challenges facing the public sector, at all levels (Miraglia & Johns, 2021). The costs come at the individual level in the form of reduced income, both directly as public or private insurances only rarely compensate fully for ordinary wage, and more indirectly through lost tenure. They come at the group level in the form of instability and unpredictability for work groups, and the need for colleagues to “step in” and work extra time to fulfill necessary tasks and function. Costs are also evident for organizations as they need to mobilize resources to fill in vacancies, pay compensation to absent employees while also paying for substitutes and overtime. And finally, absenteeism represents great costs for society in the form of lost working days, and thus general productivity (Gimeno et al., 2014; Harrison & Martocchio, 1998).

Disregarding planned absence where the intention to be absent is registered before the actual absence – i.e., absence from work due to holidays, vacations, pregnancy leaves and the like – most attention has been devoted to involuntary absence, usually in the form of sickness absence. Sickness absence is defined as the “(…) absence from work due to ill health” (Bernstrom & Houkes, 2018:5). As most countries have arrangements allowing employees to stay away from work based on their own judgement, this definition opens for both doctor certified and self-reported illness, again blurring the line between “real” sickness absence and truancy.

Unsurprisingly, much research has been devoted to identifying causes of absenteeism, with a further aim to find effective means to reduce it. It has become clear that sickness absence can`t be fully explained as an employee`s incapacity to work caused by sickness but needs to be understood as complex phenomenon that is influenced by several factors at different levels (Antczak & Miszczynska, 2021). This includes individual characteristics like gender, education, personal health and lifestyle (Fitzgerald et al., 2016; Gohar et al., 2021; Mastekaasa & Olsen, 1998), family related conditions (Antai et al., 2015; Sabbath et al., 2012), work and organizational characteristics (Barmby & Stephan, 2000; Bouville et al., 2018; Griep et al., 2010), sector and business employment (Antczak & Miszczynska, 2021; Hansen et al., 2019; Mastekaasa, 2020), and national differences including institutional arrangements for registering and compensating absence from work (Frick & Malo, 2008; Livanos & Zangelidis, 2013; Peretz & Fried, 2012).

Little research has, however, focused on the relationship between number of working hours and absenteeism, even though organizations vary widely on their use of overtime (Blagoev et al., 2018; Kunisch et al., 2021), and part-time work (Kalleberg, 2000). For instance, in their scoping review of research on causes for absenteeism, (Miraglia & Johns, 2021) do not mention working hours as an organization level antecedent. And even though the use of part-time versus full-time employment can be regarded as an important part of any organization’s “Human Resource Management architecture” (Lepak & Snell, 1999), there is almost no empirical research to investigate whether this employment type is connected to one of the greatest costs for any organization: absenteeism.

Links between absenteeism and working hours is of particular interest for the public sector. The main reason for this is that part time work is particularly common in organizations dependent on 24/7 functioning, and thus includes most large health organizations like emergency care, hospitals, and other health institutions, most of them – at least in Europe - public organizations (Benschop et al., 2013, Cook & Bartram 2015). It is also known that public organizations have a higher rate of sickness absence (Mastekaasa, 2016).

Most research on the connection between working hours and absence from work has been focused on overtime (working more than “normal”) (Bernstrom & Houkes, 2018). Still, we know little on the eventual links between part-time work (working less than “normal”) and absence. Moreover, the findings from empirical studies are “highly inconclusive” (Bernstrom & Houkes, 2018:6). Some report part-time employment (PTE) to be associated with higher absenteeism (Flach, Groothoff, Krol, & Bültmann, 2012; Gjesdal & Bratberg, 2002; Gjesdal & Bratberg, 2003; Kaerlev, Jacobsen, Olsen, & Bonde, 2004), while other report no significant association between the two (Flach, Krol, & Groothoff, 2008; Niedhammer, Chastang, & David, 2008; Smulders, 1993). A few studies conclude that PTE is associated with lower absenteeism (Dionne & Dostie, 2007; Grobe, 2016).

One reason for these inconclusive findings may be that most of this research is conducted on the individual level. Given that part time work may have different and even conflicting effects on absenteeism for different persons (Jacobsen & Fjeldbraaten, 2020), positive and negative effects may balance each other out at the aggregate level. Moreover, research conducted at the organizational level or meso-level are scarce. This is somewhat surprising as such studies may be more apt at finding what is the aggregate effects of an organizational arrangement at the level of all employees. Even though a large body of research on linkages between absenteeism and organizational factors like job design (Väänänen et al., 2003), balance between job demands and resources (Clausen et al., 2014a & b; Schaufeli et al., 2009), temporality of work (shift work) (Jacobsen & Fjeldbraaten, 2018; Tüchsen et al., 2008), leadership (Lokke 2022; Nyberg et al., 2008), and job autonomy (Grund & Rubin, 2021; Kottwitz et al., 2018), the effects are still mainly measured at the individual level, treating absence as an individual decision (Allebeck & Mastekaasa, 2004; de Rijk, 2013).

In this study we move the analysis to the organizational level, studying the use of aggregate part-time work and sickness absence in Norwegian municipalities over a time-period of six years (panel data). Although working part-time may or may not be an individual decision (one cannot find a full-time job), staying away from work will always be an individual decision. This decision may be voluntary in the sense that one is able to go to work but decides to stay at home or do something else. And it may be involuntary in the sense that one wants to go to work, but it is impossible because of sickness or other factors hindering the person (Alexanderson, 1998; Hensing et al., 1998).

Thus, explaining sickness absence at the organizational level will have to rely on micro-processes taking place at the individual level (AMJ, 2022). Sickness absence at the organizational level is then the sum of the individual sickness absence, or the aggregate of the individual decisions to go to work or not. An eventual link between sickness absence and part-time work at the organizational level must be explained by mechanisms functioning at the individual level. Several speculations, based in different theories of human behavior, have been put forward to explain any link between part time work and absenteeism. For simplicity’s sake, we here divide them into positive (part time will reduce absenteeism) and negative (part time will increase absenteeism) linkages.

Starting with the positive effects, organizations offering part-time work can be regarded as providing flexible work schedules (Gascoigne & Kelliher, 2017), making it easier for employees to strike the right balance between work and family/leisure. Studies based in theories on work-family balance or conflict (Netemeyer et al., 1996), tend to assume that working part time is a way to improve the balance between demands from home and from work (Allen et al., 2000; Benschop et al., 2013; Fein & Skinner, 2015; Higgins et al., 2000; Jansen et al., 2006; Olsen & Dahl, 2008). Organizations with a higher level of part time workers may thus represent a working environment with greater possibilities for easing the potential conflict between work and home and should thus result in reduced absenteeism. The above argument assumes that employees freely can choose how many hours they will work (voluntary part time). In many instances, this will not be the case (Kamerāde & Richardson, 2017). Rather, employees will often have no other choice, but the number of hours offered by the organization. This may result in a situation where employees end up working fewer hours than wanted (involuntary part time). As noted by (Jacobsen & Fjeldbraaten, 2020:132), this may set employees in a situation where they “(…) will be more hesitant to take some days off as this might impair future possibilities of getting a higher percentage of work.” Working less than wanted may thus have a disciplining effect on employees, increasing their presenteeism.

Part time work may also reduce the physical and psychic strain for many employees. Previous research has indicated quite clearly that probabilities for developing both physical and mental problems increase with the number of hours worked (Bannai & Tamakoshi, 2014; Sparks et al., 1997), and that a reduction in working hours seems to reduce both physical and mental problems for employees (Voglino et al., 2022). Although most of these studies focus on working longer hours than “normal” (usually defined as the standard number of hours per week defined in the national legislation and/or agreements between labor unions and employers’ unions), they may also be relevant for employees working less than “normal”. Finally, there may be just a statistical artefact explaining why part time workers may have lower absenteeism than full time workers. Part time workers will usually also work fewer days during a week or month. Thus, there will also be a higher probability for these employees that sickness will strike them on days that they are not expected to work. The more days one is working, the higher the statistical probability of being sick on one of the working days.

Moving to the negative effects of part time on sickness absence, the most common explanation seems to be lack of integration in the organization (Clausen et al., 2014a & b; Jacobsen, 2000; Jacobsen & Fjeldbraaten, 2020). Most studies following this line of reasoning are based in theories related to partial inclusion (Katz & Kahn, 1978; Kwon & van Jaarsveld, 2013) and organizational commitment (Allen & Meyer, 1996; Mowday et al., 1982), especially affective organizational commitment (AOC) (Loughlin & Murray, 2012; Mercurio, 2015). As AOC usually is a result of organizational socialization, working less than normal will almost automatically expose the employee less to the organizational elements central in the socialization process: colleagues, management, and clientele. Thus, part time work may entail lower affective commitment. And, as several studies have shown that high AOC is linked to low absenteeism (Clausen et al., 2014b; Hausknecht et al., 2008; Schalk, 2011), we will expect that organizations with more part time workers will exhibit lower levels of AOC and thus higher levels of sickness absence.

A second negative effect may come through an attraction/selection process where employees with health problems are actively applying for jobs in organizations where they know that they will be offered part time work. Studies have indicated that people with health problems apply for positions in organizations where they expect job pressure to be lower (Mastekaasa, 2020). As job pressure probably will be lower the less hours one is working, one could also expect potential employees with health problems to seek out organizations with part time jobs. This again will increase the probability of absenteeism as bad health is unequivocally linked to higher absenteeism. A variant of the selection/attraction mechanism is that part time jobs are mainly occupied by females, mainly married women and women with children (Bachmann et al., 2022). This is probably linked to work-family conflict/balance as women still are the ones primarily taking responsibility for home and children. Furthermore, there is solid evidence that sickness absence is higher for women than for men (Allebeck & Mastekaasa, 2004), both across sectors (Hansen et al., 2019; Mastekaasa, 2020), occupations, and nations (Kwon, 2020). Therefore, one should expect organizations with many part-time jobs to employ more women, and thus to have higher absence rates. A final variant of the selection/attraction mechanism is that part time jobs seem to be occupied by employees with lower education than what one finds in full time jobs (Kauhanen, 2008). Several studies indicate that lower levels of education are related to higher levels of absenteeism (Clausen et al., 2014b; Hammig & Bauer, 2013; Kristensen et al., 2010). Again, we will assume that organization with high levels of part time jobs will attract more employees with lower levels of education, resulting in higher levels of absenteeism.

As both empirical research, and theoretical expectations and mechanisms are conflicting, is it difficult to have any clear expectations on whether organizations with extensive use of part-time work, will have higher or lower sickness absence than organizations basing their employment relations on full-time work.

The organizations studied are Norwegian municipalities. They are multifunctional organizations delivering public services such as basic primary and secondary education (6 to 16 years), primary health care including institutional care for elderly, childcare and kindergartens, as well as services connected to culture (libraries, youth clubs, etc.), emergency (fire services, emergency care), and technical services like road and park maintenance. Thus, they cover a wide variety of occupations. Data originate from the years 2014 to 2019. In 2020, a wave of municipal amalgamations was conducted, reducing the number from 428 to 356. As radical organizational change affects sickness absence (Gronstad et al., 2020), we decided to not include municipalities after 2019. Some amalgamations were also conducted in the period between 2014 and 2019. These municipalities have also been removed from the analysis. As the capital – Oslo – is both a municipality and a county (and extremely larger than the other municipalities in Norway), it has also been removed. The total number of organizations in the current analysis is 422.

Data on sickness absence and part-time/full-time work was retrieved from the National association of local and regional authorities (KS). They register information on employees and wages for all employees in all Norwegian municipalities. Municipalities are by law obliged to register data concerning wages, titles, absence, etc., and to report it to the central register every year. The register thus represents an objective oversight over workdays “lost” in all municipalities and the percentage of a full position employees are working, thus avoiding problems associated with self-reporting (Mueller et al., 1987). Absence is defined as number of days during a year, not the number of events, a measurement that seems to dominate the current research on the topic (Johns, 1997, 2010). Only employees with a registered engagement are included, and any employees below 18 years of age and apprentices are excluded. Employees in temporary (short time) employment, employed on an hourly basis, and those employed less than 12 months are also excluded from the register. Absence is registered at the individual level and aggregated to the organizational (municipal) level as the “sickness absence percent”. The formula for computing this is:

(days of sickness absence/planned workdays) * 100

The term “planned workdays” takes into consideration whether one is working full-time or part-time. For a “normal” employee the number of planned workdays for a year is 235, with some variation depending on occupations (teachers for instance, have 196 days per year) and whether one is working shift work (those working shift work including night shifts have a lower number of planned workdays). An employee working 50% part time will thus have a planned number of workdays of 117,5. The number reported here is thus the number of workdays lost to sickness absence during a year, in relation to the number of workdays that were planned for the whole year.

Part-time work is computed as “mean position percent”, and is the ratio between the number of employees in the organization and the number of planned or “normal” full-time positions:

(planned full-time positions/number of employees) * 100

Planned full-time positions are estimated on hours expected work during a year, again differing somewhat between occupations and shiftwork or not. Part-time/full-time work is thus operationalized as a continuous variable ranging theoretically between zero and 100. This gives us the opportunity not only to scrutinize eventual differences between part-time and full-time workers, but also to see any gradual effects and differences between different degrees of part-time work and to estimate eventual non-linear effects. As data on both working hours and sickness absence are not based on self-reports, they are highly reliable (Johns & Miraglia, 2015; Murphy, 2014).

We also control for possible confounders, i.e., phenomena affecting both the cause (part time work) and effect (absenteeism) simultaneously. Confounders are variables that a) are possible causes for the effect under study (absenteeism), b) correlated with the cause (independent variable) – part time work, c) are not intermediate variables, and d) cannot be affected by the independent variable (one-way causal direction) (McNamee, 2003). As this is a study at the organizational level, the confounders are aggregate variables, showing the situation at the collective unit level (Hausknecht et al., 2008).

First, we control for demographic composition of the organization, especially its gender composition as gender has been one of the variables showing consistent correlation with absenteeism, bot across time and space. We also include educational composition. Second, we control for organizational size. Larger organizations may have better possibilities to “fill up” positions, and thus to offer full time jobs. This will probably be more difficult for smaller organizations, having problems – i.e., economic resources – to offer full time jobs to all employees. Earlier empirical studies also indicate that size is negatively related to organizational commitment (Morris & Steers, 1980; Mowday et al., 1982) and social control and that sickness absence seems to increase with increasing organization size (Allen, 1982). The research on the relationship between organizational size and absenteeism are, however, scarce (Duijts et al., 2007). Data on both these variables are collected from the municipal register where size is operationalized as number of estimated full-time positions and gender composition as the number of estimated full-time positions for employed women in relations to all estimated full-time positions.

In addition, we will include the general economic situation of the organization. Organizations experiencing fiscal stress may be forced to exploit the workforce more optimal than organizations having economic slack, and part-time work may be an indicator of cost savings rather than offering flexible work (Kwon & van Jaarsveld, 2013). Thus, organizations under fiscal stress will probably calculate workforce cost more exactly, offering positions with more diverse working hours to exploit the labor most efficiently. Moreover, fiscal stress will also most likely mean less resources available for employees. Following job-demand and resources theory (Demerouti et al., 2001; Schaufeli et al., 2009), lack of resources will often result in burn-out, something that again may end up in sickness absence (Langseth-Eide & Vitterso, 2021). Fiscal stress is defined in two different ways. First, free income per capita measured in Norwegian kroner (NOK) is an estimation of how much “there is left” for use in the municipality after the basic requirements following national laws have been covered. Second, a yearly net surplus is a measure of how much resources a municipality has for investments/funds after running expenses have been covered. Both are measures of the available resources in the municipality.

Furthermore, we consider important aspects of the organization’s environment. First, as noted by several economists, is the notion that absenteeism is correlated with availability of jobs outside the organization, i.e., how tight the labor market is (Hausknecht et al., 2008; Livanos & Zangelidis, 2013). In a tight labor market, that is where it is easy for an employee to find alternative employment and difficult for the employer to hire substitutes for their employees, incentives to go to work will be less intense. The employee knows that it is not likely to get fired for being away from work, and if one does, finding alternative work may be rather easy. To attract personnel that usually would not consider taking a job, organizations may find it rational to offer jobs that are not full time. Offering such jobs may attract people that would like to work, but not to have a full job. A tight labor market may thus result in a higher differentiation of jobs, including the number of working hours defined. Labor market “tightness” is measured by the percentage of registered unemployed person in relation to all persons in normal working age (18–67) in the municipality. The higher this number, the higher the unemployment rate in the municipality.

Second, we noted above that part time might be a way to ease conflicts between work and family, leading especially women to work part time instead of full time. This conflict can be relieved through offering kindergartens and other home help services, either through public or private providers. A good coverage of such services may result in more people taking full time jobs and reduce the necessity to take some days of to care for children. Studies indicate that childcare load is a significant contributor to increased absenteeism (Bekker et al., 2005). Providing services that may give some relief from this strain may thus reduce days away from work. The provision of child support for employees is measured by the number of children in the municipality having a registered place in a kindergarten in relation to the number of children in the age from 1 to 5 years in the municipality. The higher this number/rate, the better provision of kindergartens in the organization’s environment. There is no official statistic on educational level of municipal employees. As municipalities will to large degree be dependent on a local labor market, we include the percentage of the population in the municipality having the lowest educational level (basic school 1–10).

Data on confounders containing information on the municipal situation were all retrieved from the Norwegian National Bureau of Statistics (SSB).

Table 1 display descriptive statistics for the pooled data (all years) included in the analysis, as well as the bivariate correlations between them.

Table 1

Variables in the analysis, pooled data 2014–2019 (six years). Descriptive statistics (means, standard deviation) and correlations (Pearson’s r). N = 415. * p < .05, ** p < .01
Name	Mean(std)	Y	X1	X2	X3	X4	X5	X6	X7
(Y) Sickness absence (%)	9.6 (1.5)	1
(X1) Percent position	0.76 (0.04)	.25**	1
(X2) Organization size	787.8 (2081.8)	.07	.32**	1
(X3) Ratio female to all full-time employees	0.79 (0.04)	− .06	− .21**	− .19**	1
(X4) Free income per capita	61674 (12484)	− .18**	− .21**	− .21**	− .16**	1
(X5) Net yearly surplus (% of running costs)	2.6 (2.2)	− .14**	.03	.06	− .09	.18**	1
(X6) Ratio children in kindergarten to children 0–5	0.76 (0.32)	− .03	− .11*	− .01	.08	.02	− .04	1
(X7) Ratio secondary education to number of inhabitants	0.36 (0.08)	− .18**	− .26**	− .18**	.03	.06	− .02	.03	1
(X8) Unemployment rate (%)	2.2 (0.8)	.32**	.22**	.12*	− .12**	− .08	− .04	− .06	− .23**

The two main variables (sickness absence and percentage position) are normally distributed both pooled and for individual years (Kolmogorov- Smirnov-tests p > .10). Of the other independent variables, only the number of full-time employees was highly positively skewed because many Norwegian municipalities are small, and that the number of employees almost linearly follow the number of inhabitants. This variable is log-transformed for all years. None of the independent variables are so highly correlated as to fear any collinearity.

To choose the optimal model for estimating the effect of part-time work on sickness absence we first compared a model with municipality fixed effects with a random effects model. A fixed effect model is primarily aimed at estimating changes that occur over time while controlling for time invariant differences between municipalities, thus controlling for non-observed differences between units and reducing the danger of model misspecification due to omitted variables. However, it also assumes that the main independent variable – here: percentage employment - change significantly over time. To test whether a random effect model was preferable to the fixed model, we conducted a Hausman test. This was significant (p < .000), leading us to reject the null hypothesis that a random effect model was preferrable. Next, we conducted the LM test (Breusch-Pagan Lagrange multiplier) to see whether an ordinary least square (OLS) model would fit the data better than the random effects model. Again, the test was highly significant (p < .000), indicating that a random effects model is preferable to an OLS model. We also tested whether time fixed effects would provide a better fit to the data than a model without such effects by conducting a Wald test on whether the coefficients for each year are jointly equal to zero. The test was highly significant (p < .000), indicating that time fixed effects should be included in the model. Using a modified Wald statistic test for groupwise heteroskedasticity yielded a highly significant result (p < .000), leading us to chose a model with robust standard errors.

Table 2

Linear fixed effects regression. Robust standard errors. Dependent variable = sickness absence (percent). Groups = 418, Observations = 2503. * = p < .10, ** = p < .05, *** = p < .01
Variable	Coefficient	Standard error	t-value
Percent position	1.56	1.31	1.19
Organization size (log)	.92*	.53	1.73
Ratio female to all full-time employees	2.87**	1.37	2.10
Free income per capita (1000NOK)	.044***	.014	3.14
Net yearly surplus (percent)	− .008	.009	− .86
Ratio children in kindergarten to children 0–5	1.16***	.46	2.54
Ratio secondary education to number of inhabitants	1.68	2.44	0.69
Unemployment rate (%)	.005	.05	.10
Year (2014 base year)
2015	.20**	.09	2.30
2016	.07	.11	.64
2017	.11	.13	.87
2018	.01	.14	.04
2019	− .31*	.17	-1.82
F-value	3.13***
Overall R-squared	.02
Rho (icc)	.61

Percent position, i.e., the use of part-time work in the municipalities, has a positive, but non-significant effect on sickness absence measured as percent of expected working days in a year. Even though earlier tests clearly indicated that the choice of model used is the best, we compared the results in Table 2 with outcomes for the focus variable when running random effects model and the OLS model. Both these models yielded significant and positive effects of the focus variable percent position (OLS coefficient = 4.90, p < .000, random effects model coefficient = 3.07, p < .000), showing the importance of controlling for unobserved differences between units/municipalities. The high rho shows the importance of differences between municipalities. More than 60% of the variation in sickness absence at the municipal level is explained by (unobserved) differences between municipalities. Although this analysis detects some factors of importance for sickness absence (size, number of female employees, resources, supply of kindergartens, yearly fluctuations), the combined explained variance of these factors is small.

Part-time work is a common, and in many countries increasingly so, phenomenon. In 2020 around 17% of the US workforce worked part-time, while the average in the 27 EU countries was almost 15% in 2021 (OECD, 2022). From the organization point of view, organizing work as part-time has many benefits. It increases numerical flexibility as part-time workers can more easily expand their working capacity on short notice than full time workers, and they can function as a “emergency reserve” to call upon when employees suddenly “go missing” (accidents, sickness) (Arrighetti et al., 2021; Hunter et al., 1993). They may also attract highly sought-after personnel through offering flexible work hours, and they may make optimal use of the workforce easier by avoiding slack many times inherent in full-time positions (Preenen et al., 2017). For many organizations relying on 24/7 production, part-time work may be necessary to be able to fill complex rotation arrangements during the day and week (Jacobsen & Fjeldbraaten, 2020).

Even if the use of part-time work can be regarded as a basic component of the “human resource architecture” of an organization (Lepak & Snell, 1999), we lack knowledge on possible negative organizational consequences or costs of employing people in part-time positions. One of these “knowledge holes” is whether organizations’ use of part-time work affects absenteeism, more precisely sickness absence.

The most reasonable conclusion to draw from this study is that the use of part-time work is unrelated to absenteeism. Reflecting on this finding, it is important to have in mind that this conclusion only holds at the organizational level. Drawing the inference that part-time work is unrelated to sickness absence at the individual level would be an ecological fallacy. As discussed in the theory section of this article, part-time work may have both positive and negative effects on absenteeism concerning individuals, depending on individual characteristics and situational factors. For some, part-time work may be a way to ease work-family tensions, while others may find it stressful because they want to work more hours to get a higher income. For individuals, the effect of part-time work on absenteeism will probably depend on a multitude of contingency factors like personal characteristics (gender, age, education, personality), family situation (children at home, single or not, parent’s age, etc.), and expectations from peers, local community, and society at large (Miraglia & Johns, 2021). At the aggregate – or organizational – level, however, these positive and negative effects may balance each other out, as the conclusions in this study indicate.

Leaving the focus of this study for some of the more peripheral findings, it mainly supports previous knowledge on the antecedents of sickness absence. First, it shows that gender – also at the aggregate level – have a positive effect on sickness absence in the sense that more women employed, the higher the absence. This supports our knowledge about sickness absence as a gendered phenomenon (Allebeck & Mastekaasa, 2004; Antczak & Miszczynska, 2021; Kwon, 2020; Mastekaasa & Olsen, 1998). It also supports other empirical findings indicating that larger organizational size may be associated with higher absenteeism (Barmby & Stephan, 2000). A more surprising finding is that the coverage of places for children in kindergartens is positively connected to sickness absence, not negatively as on should expect if kindergartens functioned as a relief for work-home stressors. A reason for this finding may be that parents with kids in kindergartens are more exposed to communicable diseases often spread in kindergartens (and schools) than employees caring for their kids at home.

Although this study has several strong aspects – objective data both on dependent and independent variable, panel data making it possible to study the phenomenon over time and controlling for unobserved and potentially important explanatory factors, studying large and multifunctional organizations covering a wide range of occupations and professions – it also must be interpreted in its context. It is an open question whether the findings in this study within the Norwegian context will travel to other contexts. A first question should be whether the findings will travel to the same organizations in similar countries (northern Europe) with much of the same responsibilities and tasks delegated to the local level. A second step would be to see if the finding may apply also to other public organizations, and finally to private business organizations. As these contexts differ widely, the effects – or “no-effects” – detected in this study may change, even dramatically (Johns, 2006). One example of findings in this study that may be highly context dependent, is the non-significant effect of unemployment and absenteeism. Most other studies report findings indicating that higher unemployment rates go together with lower absenteeism (Hausknecht et al., 2008). In a country like Norway, with a very good “safety net” for employees, such linkages may be weaker than what one will find in other countries with more strict policies on compensation for sickness absence. This calls for comparative studies across countries and welfare regimes.

Even though this study indicates that the level of part-time work in organizations is unrelated to sickness absence, one should not jump to the conclusion that this can be used as a one-sided argument for using part-time as an overall organizational strategy (Human Resource Management (HRM) policy). As noted by Kwon & van Jaarsveld (2013), it seems of utter importance whether the organizational motivation for extensive use of part-time work is based on flexibility or cost-savings. If it is the latter, one should expect part-time employees to be less integrated into the organization and have higher levels of absenteeism. It part-time is employed as a policy to increase individual flexibility, one may assume that this is done based on an individual evaluation of the fit between the person’s wishes and needs and working hours. This will in turn be a strong indicator on the organization’s willingness to integrate the individual needs into the organizational policy, again probably increasing commitment and attachment, and lowering absenteeism. Further studies on the links between part-time use and absenteeism should include measures on the organization’s motivation.

Furthermore, there should be more studies on the links between organizational characteristics and absenteeism at the organizational level. Transforming knowledge about how different variables are connected to absenteeism at the individual level to knowledge on how to design organizational policies is in many instances difficult. Therefore, research on how organizational characteristics like the extension of part-time work, shift-work and other work arrangements are linked to absenteeism at the organizational level might produce very useful information on how to design policies to meet some of the greatest challenges for organizations: absenteeism.

Ethics approval and consent to participate: No humans were involved in this study

Consent for publication: Not applicable

Availability of data and materials: The datasets used and/or analyzed during the current study will be made available from the corresponding author on reasonable request.

Competing interest: None

Funding: None

Authors' contributions: Both authors contributed equally to the study

Acknowledgements: None

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No competing interests reported.

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Part-time Work and Sickness Absence – an Organization-level Analysis

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