Cross-lagged effects of resilience and indicators of sustainable employability; a study among Dutch police officers

Judith H. Semeijn (Faculty of Management, Science and Technology, Open University of the Netherlands, Heerlen, The Netherlands) (Research Centre for Education and the Labour Market, Maastricht University, Maastricht, The Netherlands)
Marjolein C.J. Caniëls (Faculty of Management, Science and Technology, Open University of the Netherlands, Heerlen, The Netherlands)
Daniël Kooistra (Faculty of Management, Science and Technology, Open University of the Netherlands, Heerlen, The Netherlands)

Policing: An International Journal

ISSN: 1363-951X

Article publication date: 30 May 2019

Issue publication date: 20 November 2019

2642

Abstract

Purpose

Sustainable employability is an important goal for individuals and organizations alike. However, scarce knowledge is available on possible cross-lagged relations of resilience among police officers and different aspects of their sustainable employability over time. Based on assumptions of COR theory, the purpose of this paper is to test these relations in a two-wave design.

Design/methodology/approach

A total of 532 police officers participated in a time-lagged survey design (time interval of six months) concerning their resilience and relevant aspects, i.e., self-reported vitality, workability and organization-reported individual absenteeism rates. Data were analyzed with structural equation modeling.

Findings

Results indicate cross-lagged effects between resilience and vitality with an acceptable model fit. Thus, the level of resilience at T1 affected the level of vitality at T2 and vice versa. In addition, a nearly significant negative effect of vitality on T1 was found on absenteeism on T2.

Research limitations/implications

More measurements over time are needed to test reciprocal relations and possible gain spirals. Different samples are needed to assess generalizability. Cross-lagged effects may indicate a reciprocal relation between resilience and vitality that can be further facilitated.

Practical implications

For example, resilience can be addressed explicitly in training.

Originality/value

This study is the first to test the cross-lagged relations between resilience and indicators of sustainable employability among police officers. It is important to further study this for the sake of both police officers, as well as society as a whole.

Keywords

Citation

Semeijn, J.H., Caniëls, M.C.J. and Kooistra, D. (2019), "Cross-lagged effects of resilience and indicators of sustainable employability; a study among Dutch police officers", Policing: An International Journal, Vol. 42 No. 6, pp. 961-975. https://doi.org/10.1108/PIJPSM-01-2019-0003

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Judith H. Semeijn, Marjolein C.J. Caniëls and Daniël Kooistra

License

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode


Introduction and contribution

Resilience and sustainable employability are of key importance for police officers. Police officers face a high work load, high pressure and emotional contacts with civilians (Juniper et al., 2010). The high work load, emotional client contacts, and long/irregular working hours can hamper police officers’ health, workability and vitality (see e.g. Andersen et al., 2015) and thereby the continuation of their work “in the line of duty.” Sustainable employability refers to the continuous possibilities and capabilities of individuals for current and future work (Le Blanc et al., 2017; Semeijn et al., 2015; Ybema et al., 2017). A mixture of developments in the context of work (such as, economic, demographic, personalization) makes it a topic of interest, not only at the individual level, but at the organizational and societal levels as well. Questions arise as to what is needed to keep people sustainably employable over their lifespan (Semeijn, 2018; Truxillo and Fraccaroli, 2016).

This study aims to elicit the importance of resilience for sustainable employability of, in particular, police officers. After and during their work, police officers have a need for quick recovery from stressful situations to restore and enlarge their resources. In this way they are able to preserve their sustainable employability. Resilience is such a resource. More specifically, resilience is a personal resource that is part of the so-called psychological capital (PsyCap) of people (Luthans et al., 2007). It is generally defined as the capacity to bounce back from adversity, conflict and failure, or even positive events (Luthans et al., 2007). Britt et al. (2016) argue that resilience is used in different forms and meanings, and still lacks conceptual clarity. In our study, we align to the stream of research that considers (police officer) resilience as an important personal resource in the context of work (see e.g. Andersen et al., 2015; Kossek and Perrigino, 2016). The job demands-resources (JDR) model (Demerouti et al., 2001; Bakker and Demerouti, 2007) explains that resilience serves as an antecedent of sustainable employability, at least when it comes to work engagement, which includes vigor (or vitality), dedication and absorption.

Empirical studies confirm that resilience is related to indicators of sustainable employability, such as employability, vitality and workability (Avey et al., 2009; Avey et al., 2011). Thus, resilience can be seen as a personal resource that may help to deal with job demands and therefore help to conserve or even lead to increased vitality and workability, and a possible reduction in absenteeism. However, scarce empirical knowledge is available on the causality over time of the effects of employee resilience on indicators of sustainable employability (see also Britt et al., 2016; Kossek and Perrigino, 2016). Are there reversed or even cross-lagged effects between resilience and its outcomes in terms of vitality and workability, such as assumed by the conservation of resources (COR) theory (Hobfoll, 2001, 2011)? The aim of our study is to investigate the cross-lagged impact of resilience on indicators of sustainable employability, i.e. vitality, workability and a more objective (organizational measure) indication of absenteeism.

Since resilience and sustainable employability are relevant topics in the context of police work, we use a two-wave time-lagged study design with a sample of 532 Dutch police officers to investigate resilience and its cross-lagged effects with indicators of their sustainable employability.

The present study advances prior research in several ways. First, most studies about resilience focus on personal characteristics and coping styles to handle trauma and (extreme) adversity (e.g. Bonanno, 2004). The present study specifically addresses the work-related ability to bounce back and adapt to work-related stress and illness, based on the conceptualization of Luthans et al. (2007). Second, although several studies have addressed resilience at work, these studies mainly focus on one-way relationships; between resilience and personal psychological predictors of resilience (e.g. positive emotions, see Meneghel et al., 2016), or relevant outcomes, such as thriving at work, job satisfaction and employee well-being over time (see e.g. Kossek and Perrigino, 2016). The present study investigates possible cross-lagged effects between resilience, vitality, workability and absenteeism. Third and finally, our study explicitly connects literature about resilience and sustainable employability, a connection that hitherto has not been studied.

Sustainable employability and personal resources

Sustainable employability is of major concern to individuals, organizations and society as well, since in current Western society individuals need to work longer and meanwhile stay healthy and preferably also happy at work (De Lange et al., 2016; De Vos et al., 2018). Happy and healthy people contribute to healthy businesses and organizations (Stewart, 2010). Core values in work and business have shifted toward more social responsibility (Lindgreen and Swaen, 2010) and more sustainability, also in the management of human resources (Ehnert and Harry, 2012; Beer et al., 2015) and careers (De Vos et al., 2018; De Vos and Vander Heijden, 2015). In all, sustainable employability refers to the individual’s possibilities and capabilities to continue to work, and further develop in one’s work, while staying happy (vital) and healthy (workable). Although sustainable employability can be measured in different ways and by different concepts (see e.g., Fleuren et al., 2018), for the purpose of this study we focus on vitality and workability aspects, as well as a more objective indication of health aspects, namely absenteeism.

Research indicates that (personal) resources are important antecedents for sustainable employability (Semeijn et al., 2015). In COR theory, resources are described as “[…] those entities that either are centrally valued in their own right, or act as means to obtain centrally valued ends” (Hobfoll, 2002, p. 307). Studies indicate that personal resources are important for functioning at work (Luthans et al., 2007; Van Dam, 2013). The importance of resilience as a “psychological capital” resource (Luthans et al., 2007) has already been confirmed by several authors (see e.g. Upadyaya et al., 2016), also in the police context (see e.g. Papazoglou and Andersen, 2014; Siu et al., 2015).

In these studies, resilience is generally defined in line with “the capacity to rebound or bounce back from adversity, conflict, failure, or even positive events, progress, and increased responsibility” (Luthans, 2002, p. 702). Exemplary studies into positive effects of resilience in the work context are indicating effects on, for example, thriving at work (Paterson et al., 2014), well-being (Roche et al., 2014; Siu et al., 2015) and higher levels of employee performance over time (Peterson et al., 2011). However, so far the effect of resilience on indicators of sustainable employability among police officers has not been addressed.

The impact of resilience on aspects of sustainable employability

In this study we follow two basic assumptions of the COR theory (Hobfoll, 2001, 2002, 2011) to underpin our hypotheses. The first is that people are motivated to invest in their resources to attain their (work-related) goals (Hobfoll, 1989). Second, people will not only try to protect their resources but also try to let these grow and develop. Therefore, we propose that resilience will result in (different) resource gains for individual employees, and hence lead to (better) vitality and workability, and a reduction in absenteeism. Similarly, in line with COR theory, we expect that perceived vitality, and workability of individual employees will also be positively related to individual resilience.

Several studies have investigated the positive relationship between resources and work engagement as an outcome (see e.g. Salanova et al., 2010). Also personal resources have been associated with work engagement. For example, Llorens et al. (2007) found that efficacy beliefs play an important role for engagement, which also includes a vitality dimension. Moreover, this positive relationship is also found with respect to different personal resources, such as self-esteem, optimism and resilience (see e.g. Bakker and Demerouti, 2008; Xanthopoulou et al., 2009). More recently, Upadyaya et al. (2016) confirmed a positive cross-lagged association between resilience and work engagement (including vitality) with a sample of Finnish workers. Therefore, it is expected that resilience is positively related to the vitality among Dutch police officers as well. Hence, we hypothesize:

H1.

Resilience will have a positive cross-lagged impact on the vitality of police officers.

As regards the workability of police officers, we argue that resilience will also have a positive effect on their workability. Resilience is known to be beneficial for health (Papazoglou and Andersen, 2014; Smith et al., 2008) and health is known to be associated with workability (Van den Berg et al., 2009). The process of affecting workability could work as follows: when police officers reveal more resilience, according to COR theory (Hobfoll, 1989) they are in a better position to invest in resources, as compared to their less resilient colleagues. Thus, they are motivated and have the opportunities to nourish and conserve other (new) resources, such as their health. These other resources can also generate relevant outcomes in terms of sustainable employability of police officers. More specifically, better resilience may be related to better health and well-being among police officers (Papazoglou and Andersen, 2014), which is also closely connected to their workability. Hence we expect that:

H2.

Resilience will have a positive cross-lagged impact on the workability of police officers.

In the same line of thought, resilience can be expected to have a cross-lagged impact on absenteeism rates. The relationship between resilience and absenteeism rates was already investigated by Avey et al. (2006). This study showed that positive psychological capital reduces levels of both involuntary and voluntary absenteeism. As resilience can be considered positive psychological capital, we hypothesize:

H3.

Resilience will have a cross-lagged negative impact on absenteeism rates of police officers.

Theoretical and conceptual studies have suggested that positive adaptation to work stressors as reflected by increased health and well-being, may feed back into increasing the capacity for resilience (Britt et al., 2016). Moreover, according to COR theory (Hobfoll, 1989, 2001), people are motivated to seek, obtain, conserve and develop resources. The positive effects of having resources and obtaining positive outcomes as a result, motivate individuals to further invest in resources to obtain further positive outcomes again. In this way, even so-called gain spirals can be created (Salanova et al., 2010). Gain spirals refer to a positive growth process that includes both resources and outcomes.

While resilience of police workers can be of crucial value in enhancing vitality and workability and lowering absenteeism rates, having a better vitality and workability will also have a beneficial effect on the future resilience of these police officers. More specifically, police officers will become resilient over time as they encounter work stressors and successfully cope with them. By gaining personal resources in terms of vitality and workability when adapting to adversities and coping with work experiences, they are likely to fortify their resilience. Thus, building on the notions of the COR theory of Hobfoll (2001), and in line with empirical evidence on the relations between personal resources and work-related outcomes so far, we expect a reciprocal relationship between resilience and indicators of sustainable employability. Hence, we hypothesize:

H4.

Vitality will have a positive cross-lagged impact on resilience of police officers.

H5.

Workability will have a positive cross-lagged impact on resilience of police officers.

In sum, the conceptual model for this study and their relations is presented in Figure 1.

Method

Sample and procedure

We tested our hypotheses using a two-wave longitudinal design with six months’ time lag. It is theoretically difficult to determine the “right” period (Britt et al., 2016). We consider six months as an appropriate time-lag for testing cross-lagged relationships, herewith following other recent studies into concepts related to sustainable employability, such as, psychological well-being (Dagenais-Desmarais et al., 2017) and employability (Philippaers et al., 2016). The targeted sample consisted of 2,512 Dutch police workers. We expected that the response rate would drop in the second wave, therefore we aimed at reaching as many respondents as possible for the first wave. An online survey was accompanied by a cover letter that ensured strict confidentiality of responses and explained that participation was voluntary.

We received 1,489 (of 2,512) completed questionnaires at T1, referring to a response rate of 59 percent on T1. Data gathering at T2, among the respondents of T1, resulted in 532 (of 573) completed sets with employee responses at T1 and T2, yielding a response rate of 38 and net 36 percent. Representativeness of the data was satisfactory with regard to demographics and control variables as compared to the respondents on T1, and as compared to our targeted sample of 2,512 respondents, as far as information was available.

Measures

Key concepts were measured with validated and reliable survey measures. All variables were measured at two moments in time (T1 and T2) with a six months’ lag, except for the absenteeism rates that we retrieved from the organization at T2.

Resilience was measured with the Dutch version of the 25-item resilience scale of Wagnild and Young (1993) ranging from 1 (totally disagree) to 5 (totally agree). An example item is “I usually manage one way or another.” Reliability of the scale was confirmed by Ahern et al. (2006). In our study, α was 0.92 at T1 and 0.93 at T2. Validity of the two-factor scale was tested by examining two-factor solutions on T1 and T2 using Varimax and Oblimin rotations of the factor loading matrix. Initial Eigen Values on T1 indicated that one factor explained 35.8 percent, and the second to the fifth factor 18.5 percent (T1). On T2 Eigen Values indicated that one factor explained 38.8 percent, and the second to the fourth factor 15.8 percent. For the purpose of our study, the single factor solutions for resilience in T1 and T2 were preferred and used for further analysis, considering resilience as one integrated concept. These solutions explain 35.8 and 38.2 percent of the variance in factor loadings, respectively. KMO values were satisfactory with 0.94 (T1) en 0.94 (T2);>0.6 en Bartlett’s was significant T1 (χ2=5,531.4, p<0.05)/T2 (χ2=5,596.9, p<0.05). However, two items were eliminated for our definite measurement of resilience on T1 and T2, because they did not meet the criterion of having a primary factor loading of 0.1 or above, and no cross-loading of 0.3 or above (Hair et al., 1998). The items are item 3 (“I am able to depend on myself more than anyone else”) and item 23 (“When I’m in a difficult situation, I can usually find my way out of it”) on T1 and T2. We further tested the fit of the resulting resilience data with Confirmatory Factor Analysis in AMOS.

Vitality was assessed with the three items of the vitality dimension of the nine-item Dutch Utrecht Work Engagement Scale (UWES, or UBES in Dutch; Schaufeli and Bakker, 2003). An example item is “At my work, I feel bursting with energy.” Items were rated on a seven-point scale ranging from 0 (“never”) to 6 (“daily”). Validity and reliability of this scale have been confirmed extensively in previous research (see e.g. Seppälä et al., 2009; Schaufeli et al., 2006). For the current study, reliability of the vitality scale is high as well (0.83 at T1 and 0.84 at T2). Validity appeared to be good as well, with one-factor solutions on both T1 and T2 that explained 63.8 and 64.5 percent of the variances, respectively.

Workability was measured with the one-item dimension of the validated shortened Dutch version of the Workability Index (Ilmarinen et al., 2005). The item requires respondents to rate their current workability on a 1–10 rating scale.

Absenteeism was retrieved from the absenteeism data registration system of the organization, and refers to the total number of days absent from work at T2 divided by the total of potentially available days at T2 per employee.

We controlled for age (calendar years), gender (male =1, female =2), working hours per week, tenure in the organization (measured by years of experience in the current job) as this reflects domain expertise (Oldham and Cummings, 1996). Furthermore, educational level was added as a possible control variable, measured in five categories ranging from 1 for basic education to 5 for Master level.

Analytical method

Structural equation modeling (SEM) and AMOS software (Arbuckle, 2014) were used to analyze the data and the hypothesized relationships. Missing values are automatically dealt with in AMOS, by using full information maximum likelihood estimation. We examined a series of models to test the appropriate operationalization for our data. We started by conducting an item-level confirmatory factor analysis (CFA) to test whether it was suitable to use the observed total scores of our self-reported constructs. The results indicated an incremental fit with a comparative fit index (CFI)>0.9.

Next, a model without cross-lagged paths but with autocorrelations and synchronous correlations was assessed (stability model; M1). It appeared that with the full stability model based on our data, it was not possible to obtain fit. Results indicated a CFI of 0.93, but also a root mean square error of approximation (RMSEA) of 0.143, which is above its range for fit. Therefore, we systematically tested the stability model without vitality, then without workability and finally without absenteeism. It appeared that the stability model without workability showed the best possible, although still marginally acceptable, RMSEA, with a value of 0.098 (see also Table II). We therefore decided to continue our comparative analyses based on the stability model without workability included (our final resulting M1).

The stability model was compared with several different competing models; the second model (M2) was identical to the stability model, but included the direct causal effects as well, by additional structural paths from T1 resilience to T2 vitality and to T2 absenteeism. The third model (M3) was identical to the stability model but included (solely) additional paths from T1 vitality to T2 resilience and T2 absenteeism. In the next step, a fourth model (M4) tests the paths of M2 without including absenteeism, as well as a fifth model that tests the paths of M3 without absenteeism (M5). In two further models, and following the procedure as recommended by Kenny (http://davidkenny.net/cm/fit.htm), time-reversed effects are tested; from vitality T2 to resilience T1 (M6) and from resilience T2 to vitality T1 (M7). Notably, these models are not expected to have an acceptable fit because of these unreal time-reversed paths, hence serve as a validity check. Finally, the structural cross-lagged model (M8) included all paths of the Models 1–3.

The fit of the nested models to the data was assessed with χ2 statistic and the RMSEA. In addition, two fit indices were used for comparative analysis: the CFI and the Tucker–Lewis Index (TLI). For each of these statistics, values of 0.90 are acceptable and of 0.95 or higher are indicative of good fit (Hu and Bentler, 1999). For the RMSEA values of up to 0.08 represent acceptable errors of approximation (Browne and Cudeck, 1993).

Results

Descriptives and correlations

Descriptive statistics and correlations of all variables included in the study are presented in Table I. As can be seen from the table, only small to modest associations are present between all variables included. The largest correlation shows between age and tenure (r=0.71, p<0.01), which is quite interpretable as most of the older police officers have tenure. Table I indicates that the control variables are not structurally associated with any of the main variables.

To arrive at a parsimonious design of our model, and after testing the effects of age that appeared not to make any significant difference, we decided to leave out the control variables as advised by Becker (2005).

Model testing

Table II shows the fit indices of our competing models, as well as the model comparisons. The stability model (M1) including resilience, vitality and absenteeism showed a rather minimum acceptable fit to the data. M2 and M3 showed not much better fits, considering the indices testing the criteria. M4 and M5, referring to the cross-lagged relations, appeared no eligible alternatives either. Models M6 and M7 can be considered test cases that are supposed to reveal bad fits, because of the reversed effects, which were indeed confirmed. Only our final structural cross-lagged model (M8) revealed an acceptable fit (RMSEA=0.080; CFI= 0.98; TLI=0.90; χ2=19.14; df=2; p=0.000). M8 fits the data fairly well based on CFI and RMSEA, but the value of χ2 is actually too large. The optimal range of this value should be upper than 1, lower than 5 (Epitropaki and Martin, 2005; Schumacker and Lomax, 1998). However, the p-value is still significant.

These findings therefore show that the model including cross-lagged relationships among resilience, vitality, and absenteeism on T2 best explains our data.

Hypothesis testing

The path coefficients of the resulting cross-lagged structural model (M8) are displayed in Table II. We used Maximum Likelihood Estimation to examine the hypothesized relationships.

The results of Table II can be interpreted as follows. Resilience has a positive cross-lagged impact on the vitality of police workers, confirmed by the estimate of 0.047 (p=0.000) in Table II. This is supportive for H1. The positive cross-lagged impact of resilience on the workability of police officers could not be tested, because workability does not fit the structural model. Therefore H2 could not be tested with our data. Furthermore, we found no cross-lagged negative impact of resilience on absenteeism rates of police officers, as the estimate in Table II indicates a value of 0.014 ns. Hence H3 was not supported. Vitality shows a positive cross-lagged impact on resilience, as indicated by the relevant estimate of 0.387 (p=0.000) in Table II. Therefore, H4 could be confirmed.

Finally, as workability did not fit our model, it was not possible to test whether it would have a positive cross-lagged impact on resilience. H5 could therefore not be tested with our data either. The resulting standardized path coefficients of the cross-lagged structural model (M8) for this study is presented in Figure 2.

Conclusion and discussion

Conclusion

This study aimed at identifying possible cross-lagged effects of resilience as a personal resource at work, and outcomes of sustainable employability. Several models were tested to reveal the best fit within a sample of 532 Dutch police officers. Our results advance theoretical insights about sustainable employability as our study is the first to investigate and demonstrate longitudinal support for crossed lagged relationships between work-related resilience and aspects of sustainable employability, notably vitality. Hitherto, these links have not been studied and tested explicitly before. A model in which resilience, vitality and absenteeism were included appeared to have the best fit. In this model, COR as well as cross-lagged effects were present among resilience and vitality, supporting H1 and H4. A negative impact of resilience on absenteeism rates could however not be confirmed (H3). Workability appeared not fit the structural model on resilience and sustainable employability. Hence, H2 and H5 could not be tested with our data.

Discussion

These results imply that, in the context of police work, the cross-lagged effect of resilience on indicators of sustainable employability is partly confirmed, namely for vitality. In our sample of Dutch police officers, the level of resilience is important for vitality six months later. Similarly, the level of vitality is important for the resilience of police officers as well. In other words, resilient employees are more vital and vice versa. This finding is in line with our expectations, based on the assumptions of the COR theory. Although the two-way relationship between resilience and aspects of sustainable employability has never been explored as such, several studies provide initial evidence for relationships between resilience and different work-related outcome variables. Prior research has shown that resilience of employees is crucial with regard to, for example, job satisfaction, work happiness and organizational commitment (e.g. Youssef and Luthans, 2007; Huang and Luthans, 2015). Other studies show that resilience is an outcome of the interaction between job resources and demands (Meneghel et al., 2016). Moreover, research indicates a two-way relationship between resilience and work engagement (see e.g. Bakker and Demerouti, 2008). Our results indicate that the relationship between resilience and vitality goes both ways for Dutch police officers as well.

We found that workability did not fit a model in which both resilience and indicators of sustainable employability were included. This finding may be explained by our study design. In the present study workability was measured by a single item. Although this way of measuring workability is legitimate in workability research (see e.g. Ahlstrom et al., 2010) and has been shown to reduce common method bias (Gardner et al., 2016), its meaning and value within our model may not be fully captured by employing a single-item scale. Furthermore, arguably, the six month time lag between measurement moments may be too short to capture effects of an improved resilience on workability and vice versa. In a review of the literature on longitudinal organizational stress, Zapf et al. (1996) found that most studies use a six months or a one year time lag. However, for determining crossed lagged effect between resilience and workability, a one year period might be recommendable.

We did not find support for a positive cross-lagged effect of resilience on absenteeism. Extant studies about absenteeism have demonstrated that absenteeism is reduced when job resources are present, such as social atmosphere (Cortese et al., 2010; Ulleberg and Rundmo, 1997) and work-life balance (Hobson et al., 2001; Hughes and Bozionelos, 2007). A possible explanation could be that work-related resilience is a construct that captures job aspects as well as personal aspects and therefore has a different effect on absenteeism than pure job-related characteristics. Notably, we did find a cross-lagged effect of vitality on absenteeism at the 0.10 significance level, which means that vitality may have an impact on absenteeism rates. However, the cross-lagged effects of indicators of sustainable employability among themselves were not the primary focus of this study (Table III).

Limitations and future research

Our study is subject to several limitations which give rise to further research. First, we measured the key variables in our study at two moments in time. In this way we addressed a shortcoming of the existing empirical literature which is predominantly based on cross-sectional data. Although the significant cross-lagged effects we have found may suggest causation, they do not yet prove causation. Longitudinal data collection and analysis of cross-lagged effects are vital steps toward advancing insights on the dynamic processes that take place between resilience and sustainable employability of police officers.

Moreover, considering our additional finding that vitality tends to have a cross-lagged effect on absenteeism, the role and reciprocal cross-lagged effects of indicators of sustainable employability themselves could be included and explored in future research as well. Our findings are a starting point for other studies, as our model may provide key inputs to the construction of more complex causal models about the interplay between resilience and sustainable employability. In more advanced models it would be useful to include variables that were not considered in the present study, but could have an influence on the interplay between resilience and sustainable employability. For example, social support structures and social networks may be crucial in building resilience and sustainable employability (Fugate et al., 2004), as well as self-management skills (Wittekind et al., 2010). In this way, it would be possible to arrive at a more complete model specification of the dynamic characteristics of sustainable employability.

A second limitation pertains to our study design. Unfortunately, we could not use absenteeism scores on T1, due to the cumulative calculation of absenteeism rates in the organization that was based on the full year at the specific time of measurement. When using a six month time lag this implies overlap and therefore bias when using both absenteeism scores at T1 and T2. Future studies that are able to align time-lags with possible organizational measures, may overcome this limitation. In addition, it is also recommendable that organizations carefully (re)consider their measures and methods used too, to allow and optimize monitoring of relevant data on the sustainable employability of their workers.

Finally, our sample was highly homogenous; meaning we only included Dutch police officers. This is a potential limitation when considering the generalizability of our findings toward police officers from other countries. It would be worthwhile for other studies to replicate our design in different national settings to see whether our findings are generalizable or “typically Dutch.”

Nevertheless, we believe that our study addresses interesting dynamic processes concerning sustainable employability, with specific relevance for the police context these days. It has advanced current insights about the interplay between resilience and sustainable employability for police officers, a subject that has not previously been explored at this level of detail.

Implications for practice

This study has important managerial implications. The results of this study indicate that when employees are resilient, they are vital too. Resilience and vitality are interrelated. This provides several opportunities for human resource departments of organizations to enhance sustainable employability, and specifically resilience and vitality. A first opportunity lies in the facilitation of measures that increase resilience. This can be done, for example by adding valuable “job resources” and making them available to employees in order to strengthen the motivational process in the line of duty. For police officers this may entail organizing explicit social support and enhancing social network structures among colleagues and supervisors (see also Graf, 1986).

Second, in similar vein, the process of energetic depletion can be buffered as much as possible. Various studies have been undertaken to identify mechanisms via which stress and burnout can be prevented (see e.g. Arnetz et al., 2013). For example, a common stressor in daily police practice stems from mistakes that are made in volatile situations. Officers can ruminate about decisions they made and feel that they should have made. Provide adequate back up and help facilities in these cases could be useful to curtain the negative (depleting) energetic process. This process may occur when police officers handle situations and take decisions under strain and that backfire on the amount and quality of their personal resources, such as the quality of their sleep (see also Gerber et al., 2013).

Third, organizational training programs that are dedicated to increasing resilience and vitality in employees may have beneficial effects (see e.g. Papazoglou and Andersen, 2014; Robertson et al., 2015) and might aim at life-style awareness (sleep quality) next to exploring resilient behavior itself.

In all, this study reveals cross-lagged effects between resilience and vitality of police officers. This might indicate possible gain spirals that are further research efforts worthy in the context of police work. After all, the sustainable employability of police officers is an important topic for the near future and requires knowledge and insights on how to facilitate and stimulate them best for optimizing their sustainable employability.

Figures

Conceptual model for cross-lagged effects of resilience and indicators of sustainable employability

Figure 1

Conceptual model for cross-lagged effects of resilience and indicators of sustainable employability

Standardized path coefficients in the resulting model for cross-lagged effects of resilience and indicators of sustainable employability

Figure 2

Standardized path coefficients in the resulting model for cross-lagged effects of resilience and indicators of sustainable employability

Means, standard deviations and correlations for all variables in the study

Goodness-of-fit indices of the competing models

Model Model contents χ2 df p RMSEA CFI TLI Model comp Delta χ2 Delta df
M1 Stability model 50.60 7 0.000 0.098 0.93 0.86
M2 M1+causal model RS1>Vit2/Abs2 36.68 5 0.000 0.099 0.95 0.86 M1–M2 13.92 2
M3 M1+causal model Vit1>RS2/Abs2 32.9 5 0.000 0.093 0.95 0.87 M1–M3 17.7 2
M4 M1+cross-lagged model Vit1>RS2 32.91 5 0.000 0.093 0.96 0.87 M1–M4 17.69 2
M5 M1+cross-lagged model RS1>Vit2 33.52 4 0.000 0.094 0.96 0.87 M1–M5 17.08 3
M6 M1+time-reversed model Vit2>RS1 21.44 2 0.000 1.22 0.97 0.85 M1–M6 29.6 5
M7 M1+time-reversed model RS2>Vit1 45.62 2 0.000 0.182 0.93 0.66 M1–M7 4.98 5
M8 Cross-lagged structural model 19.14 2 0.000 0.080 0.98 0.90 M1–M8 31.2 5

Note: n=532

Path coefficients of the structural cross-lagged model

Estimate SE CR p
Vit2 ← RS1 0.047 0.013 3.724 0.000
RS2 ← RS1 0.429 0.040 10.796 0.000
Vit2 ← Vit1 0.655 0.032 20.617 0.000
RS2 ← Vit1 0.387 0.102 3.801 0.000
Abs2 ← RS1 0.014 0.037 0.376 0.707
Abs2 ← Vit1 −0.170 0.094 −1.820 0.069

Note: n=532

References

Ahern, N.R., Kiehl, E.M., Lou Sole, M. and Byers, J. (2006), “A review of instruments measuring resilience”, Issues in Comprehensive Pediatric Nursing, Vol. 29 No. 2, pp. 103-125.

Ahlstrom, L., Grimby-Ekman, A., Hagberg, M. and Dellve, L. (2010), “The work ability index and single-item question: associations with sick leave, symptoms, and health – a prospective study of women on long-term sick leave”, Scandinavian Journal of Work, Environment & Health, Vol. 36 No. 5, pp. 404-412.

Andersen, J.P., Papazoglou, K., Arnetz, B.B. and Collins, P.I. (2015), “Mental preparedness as a pathway to police resilience and optimal functioning in the line of duty”, International Journal of Emergency Mental Health and Human Resilience, Vol. 17 No. 3, pp. 624-627.

Arbuckle, J. (2014), AMOS (version 23.0), Computer Program, IBM SPSS, Chicago, IL.

Arnetz, B.B., Arble, E., Backman, L., Lynch, A. and Lublin, A. (2013), “Assessment of a prevention program for work-related stress among urban police officers”, International Archives of Occupational and Environmental Health, Vol. 86 No. 1, pp. 79-88.

Avey, J.B., Luthans, F. and Jensen, S.M. (2009), “Psychological capital: a positive resource for combating employee stress and turnover”, Human Resource Management, Vol. 48 No. 5, pp. 677-693.

Avey, J.B., Patera, J.L. and West, B.J. (2006), “The implications of positive psychological capital on employee absenteeism”, Journal of Leadership & Organizational Studies, Vol. 13 No. 2, pp. 42-60.

Avey, J.B., Reichard, R.J., Luthans, F. and Mhatre, K.M. (2011), “Meta-analysis of the impact of positive psychological capital on employees’ attitudes, behaviors, and performance”, Human Resource Development Quarterly, Vol. 22 No. 2, pp. 127-52.

Bakker, A.B. and Demerouti, E. (2007), “The job demands-resources model: State of the art”, Journal of Managerial Psychology, Vol. 22 No. 3, pp. 309-328.

Bakker, A.B. and Demerouti, E. (2008), “Towards a model of work engagement”, Career Development International, Vol. 13 No. 3, pp. 209-223.

Becker, T.E. (2005), “Potential problems in statistical control of variables in organizational research”, Organizational Research Methods, Vol. 8 No. 3, pp. 274-289.

Beer, M., Boselie, P. and Brewster, C. (2015), “Back to the future: implications for the field of HRM of the multistakeholder perspective proposed 30 years ago”, Human Resource Management, Vol. 54 No. 3, pp. 427-438.

Bonanno, G.A. (2004), “Loss, trauma, and human resilience”, American Psychologist, Vol. 59 No. 1, pp. 20-28.

Britt, T.W., Shen, W., Sinclair, R.R., Grossman, M.R. and Klieger, D.M. (2016), “How much do we really know about employee resilience?”, Industrial and Organizational Psychology, Vol. 9 No. 2, pp. 378-404.

Browne, M.W. and Cudeck, R. (1993), “Alternative ways of assessing model fit”, Sage Focus Editions, Vol. 154, pp. 136-136.

Cortese, C.G., Colombo, L. and Ghislieri, C. (2010), “Determinants of nurses’ job satisfaction: the role of work-family conflict, job demand, emotional charge and social support”, Journal of Nursing Management, Vol. 18 No. 1, pp. 35-43.

Dagenais-Desmarais, V., Leclerc, J.-S. and Londei-Shortall, J. (2017), “The relationship between employee motivation and psychological health at work: a chicken-and-egg situation?”, Work & Stress, Vol. 32 No. 2, pp. 147-167.

De Lange, A.H., Kooij, T.A.M. and Van der Heijden, B.I.J.M. (2016), “Human resource management and sustainability across the life-span: an integral perspective”, in Finkelstein, L., Truxillo, D., Fraccaroli, F. and Kanfer, R. (Eds), Facing the Challenges of a Multi-Age Workforce: A Use-Inspired Approach, SIOP Organizational Frontiers Series, Routledge, New York, NY, pp. 50-79.

De Vos, A. and Van der Heijden, B.I. (Eds) (2015), Handbook of Research on Sustainable Careers, Edward Elgar Publishing.

De Vos, A., Van der Heijden, B.I.J.M. and Akkermans, J. (2018), “Sustainable careers: towards a conceptual framework”, Journal of Vocational Behavior, available at: https://doi.org/10.1016/j.jvb.2018.06.011

Demerouti, E., Bakker, A.B., Nachreiner, F. and Schaufeli, W.B. (2001), “The job demands-resources model of burnout”, Journal of Applied Psychology, Vol. 86 No. 3, pp. 499-512.

Ehnert, I. and Harry, W. (2012), “Recent developments and future prospects on sustainable human resource management: introduction to the special issue”, Management Review, Vol. 23 No. 3, pp. 221-238.

Epitropaki, O. and Martin, R. (2005), “From ideal to real: a longitudinal study of the role of implicit leadership theories on leader-member exchanges and employee outcomes”, Journal of Applied Psychology, Vol. 90 No. 4, pp. 659-676.

Fleuren, B.P., van Amelsvoort, L.G., Zijlstra, F.R., de Grip, A. and Kant, I. (2018), “Handling the reflective-formative measurement conundrum: a practical illustration based on sustainable employability”, Journal of Clinical Eepidemiology, Vol. 103, pp. 71-81.

Fugate, M., Kinicki, A.J. and Ashforth, B.E. (2004), “Employability: a psychosocial construct, its dimensions, and applications”, Journal of Vocational Behavior, Vol. 65 No. 1, pp. 14-38.

Gardner, D.G., Cummings, L.L., Dunham, R.B. and Pierce, J.L. (2016), “Single-item versus multiple-item measurement scales: an empirical comparison”, Educational and Psychological Measurement, Vol. 58 No. 6, pp. 898-915.

Gerber, M., Kellmann, M., Elliot, C., Hartmann, T., Brand, S., Holsboer-Trachsler, E. and Pühse, U. (2013), “Perceived fitness protects against stress-based mental health impairments among police officers who report good sleep”, Journal of Occupational Health, Vol. 55 No. 5, pp. 376-384.

Graf, F.A. (1986), “The relationship between social support and occupational stress among police officers”, Journal of Police Science & Administration, Vol. 14 No. 3, pp. 178-186.

Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis, Prentice Hall, London.

Hobfoll, S.E. (1989), “Conservation of resources: a new attempt at conceptualizing stress”, American Psychologist, Vol. 44 No. 3, pp. 513-524.

Hobfoll, S.E. (2001), “The influence of culture, community, and the nested-self in the stress process: advancing conservation of resources theory”, Applied Psychology, an International Review, Vol. 50 No. 3, pp. 337-370.

Hobfoll, S.E. (2002), “Social and psychological resources and adaptation”, Review of General Psychology, Vol. 6 No. 4, pp. 307-324.

Hobfoll, S.E. (2011), “Conservation of resource caravans and engaged settings”, Journal of Occupational and Organizational Psychology, Vol. 84 No. 1, pp. 116-122.

Hobson, C.J., Delunas, L. and Kesic, D. (2001), “Compelling evidence of the need for corporate work/life balance initiatives: results from a national survey of stressful life-events”, Journal of Employment Counseling, Vol. 38 No. 1, pp. 38-44.

Hu, L.T. and Bentler, P.M. (1999), “Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives”, Structural Equation Modeling: A Multidisciplinary Journal, Vol. 6 No. 1, pp. 1-55.

Huang, L. and Luthans, F. (2015), “Toward better understanding of the learning goal orientation–creativity relationship: the role of positive psychological capital”, Applied Psychology, Vol. 64 No. 2, pp. 444-472.

Hughes, J. and Bozionelos, N. (2007), “Work-life balance as source of job dissatisfaction and withdrawal attitudes – an exploratory study on the views of male workers”, Personnel Review, Vol. 36 Nos 1-2, pp. 145-154.

Ilmarinen, J., Tuomi, K. and Seitsamo, J. (2005), “New dimensions of work ability”, International Congress Series, Vol. 1280, pp. 3-7.

Juniper, B., White, N. and Bellamy, P. (2010), “A new approach to evaluating the well-being of police”, Occupational Medicine, Vol. 60 No. 7, pp. 560-565.

Kossek, E.E. and Perrigino, M.B. (2016), “Resilience: a review using a grounded integrated occupational approach”, The Academy of Management Annals, Vol. 10 No. 1, pp. 729-797.

Le Blanc, P.M., Van der Heijden, B.I. and Van Vuuren, T. (2017), “‘I will survive’ a construct validation study on the measurement of sustainable employability using different age conceptualizations”, Frontiers in Psychology, Vol. 8, pp. 1690-1702.

Lindgreen, A. and Swaen, V. (2010), “Corporate social responsibility”, International Journal of Management Reviews, Vol. 12 No. 1, pp. 1-7.

Llorens, S., Schaufeli, W., Bakker, A. and Salanova, M. (2007), “Does a positive gain spiral of resources, efficacy beliefs and engagement exist?”, Computers in Human Behavior, Vol. 23, pp. 825-841.

Luthans, F. (2002), “The need for and meaning of positive organizational behavior”, Journal of Organizational Behavior, Vol. 23 No. 6, pp. 695-706.

Luthans, F., Avolio, B.J., Avey, J.B. and Norman, S.M. (2007), “Positive psychological capital: measurement and relationship with performance and satisfaction”, Personnel Psychology, Vol. 60 No. 3, pp. 541-572.

Meneghel, I., Salanova, M. and Martínez, I.M. (2016), “Feeling good makes us stronger: how team resilience mediates the effect of positive emotions on team performance”, Journal of Happiness Studies, Vol. 17 No. 1, pp. 239-255.

Oldham, G.R. and Cummings, A. (1996), “Employee creativity: personal and contextual factors at work”, Academy of Management Journal, Vol. 39 No. 3, pp. 607-634.

Papazoglou, K. and Andersen, J.P. (2014), “A guide to utilizing police training as a tool to promote resilience and improve health outcomes among police officers”, Traumatology: An International Journal, Vol. 20 No. 2, pp. 103-111.

Paterson, T.A., Luthans, F. and Jeung, W. (2014), “Thriving at work: impact of psychological capital and supervisor support”, Journal of Organizational Behavior, Vol. 35 No. 3, pp. 434-446.

Peterson, S.J., Luthans, F., Avolio, B.J., Walumbwa, F.O. and Zhang, Z. (2011), “Psychological capital and employee performance: a latent growth modeling approach”, Personnel Psychology, Vol. 64 No. 2, pp. 427-450.

Philippaers, K., De Cuyper, N., Forrier, A., Vander Elst, T. and De Witte, H. (2016), “Perceived employability in relation to job performance: a cross-lagged study accounting for a negative path via reduced commitment”, Scandinavian Journal of Work and Organizational Psychology, Vol. 1 No. 2, pp. 1-15.

Robertson, I.T., Cooper, C.L., Sarkar, M. and Curran, T. (2015), “Resilience training in the workplace from 2003 to 2014: a systematic review”, Journal of Occupational and Organizational Psychology, Vol. 88 No. 3, pp. 533-562.

Roche, M., Haar, J.M. and Luthans, F. (2014), “The role of mindfulness and psychological capital on the well-being of leaders”, Journal of Occupational Health Psychology, Vol. 19 No. 4, pp. 476-489.

Salanova, M., Schaufeli, W.B., Xanthopoulou, D. and Bakker, A.B. (2010), “The gain spiral of resources and work engagement: sustaining a positive worklife”, in Bakker, A.B. (Ed.), Work Engagement: A Handbook of Essential Theory and Research, Psychology Press, New York, NY, pp. 118-131.

Schaufeli, W.B. and Bakker, A.B. (2003), “UWES–Utrecht work engagement scale: test manual”, unpublished manuscript, Department of Psychology, Utrecht University, Utrecht.

Schaufeli, W.B., Bakker, A.B. and Salanova, M. (2006), “The measurement of work engagement with a short questionnaire: a cross-national study”, Educational and Psychological Measurement, Vol. 66 No. 4, pp. 701-716.

Schumacker, R.E. and Lomax, R.G. (1998), A Beginner’s Guide To Structural Equation Modeling, Erlbaum, Mahwah, NJ.

Semeijn, J.H. (2018), “Loopbanen op weg naar Duurzaamheid; over paden, hobbels en gidsen [Careers reaching for sustainability; on routes, rocks and guides along the road]”, Gedrag & Organisatie, Vol. 2, pp. 134-150.

Semeijn, J.H., Van Dam, K., Van Vuuren, T. and Van der Heijden, B. (2015), “Sustainable labour participation for sustainable careers”, in De Vos, A. and Van der Heijden, B. (Eds), Handbook of Research on Sustainable Careers, Edward Elgar Publishing, Chapter 10, pp. 146-160.

Seppälä, P., Mauno, S., Feldt, T., Hakanen, J., Kinnunen, U., Tolvanen, A. and Schaufeli, W. (2009), “The construct validity of the Utrecht work engagement scale: multisample and longitudinal evidence”, Journal of Happiness Studies, Vol. 10 No. 4, pp. 459-481.

Siu, O.L., Cheung, F. and Lui, S. (2015), “Linking positive emotions to work well-being and turnover intention among Hong Kong police officers: the role of psychological capital”, Journal of Happiness Studies, Vol. 16 No. 2, pp. 367-380.

Smith, B.W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P. and Bernard, J. (2008), “The brief resilience scale: assessing the ability to bounce back”, International Journal of Behavioral Medicine, Vol. 15 No. 3, pp. 194-200.

Stewart, H.J. (2010), “Do happy staff make for happy customers and profitable companies?”, Journal of Direct, Data and Digital Marketing Practice, Vol. 11 No. 4, pp. 275-280.

Truxillo, D.M. and Fraccaroli, F. (Eds) (2016), Age in the Workplace: Challenges and Opportunities, Routledge, New York, NY.

Ulleberg, P. and Rundmo, T. (1997), “Job stress, social support, job satisfaction and absenteeism among offshore oil personnel”, Work & Stress, Vol. 11 No. 3, pp. 215-228.

Upadyaya, K., Vartiainen, M. and Salmela-Aro, K. (2016), “From job demands and resources to work engagement, burnout, life satisfaction, depressive symptoms, and occupational health”, Burnout Research, Vol. 3 No. 4, pp. 101-108.

Van Dam, K. (2013), “Employee adaptability to change at work: a multidimensional, resource-based framework”, in Oreg, S., Michel, A. and By, R.T. (Eds), The Psychology of Organizational Change: Viewing Change from the Employee’s Perspective, Cambridge University Press, Cambridge, pp. 123-142.

Van den Berg, T.I., Elders, L.A., de Zwart, B.C. and Burdorf, A. (2009), “The effects of work-related and individual factors on the work ability index: a systematic review”, Occupational and Environmental Medicine, Vol. 66 No. 4, pp. 211-220.

Wagnild, G. and Young, H. (1993), “Development and psychometric validation of the Resilience scale”, Journal of Nursing Measurement, Vol. 1 No. 2, pp. 165-178.

Wittekind, A., Raeder, S. and Grote, G. (2010), “A longitudinal study of determinants of perceived employability”, Journal of Organizational Behavior, Vol. 31 No. 4, pp. 566-586.

Xanthopoulou, D., Bakker, A.B., Demerouti, E. and Schaufeli, W.B. (2009), “Reciprocal relationships between job resources, personal resources, and work engagement”, Journal of Vocational Behavior, Vol. 74 No. 3, pp. 235-244.

Ybema, J.F., van Vuuren, T. and van Dam, K. (2017), “HR practices for enhancing sustainable employability: implementation, use, and outcomes”, The International Journal of Human Resource Management, pp. 1-22, available at: https://doi.org/10.1080/09585192.2017.1387865

Youssef, C.M. and Luthans, F. (2007), “Positive organizational behavior in the workplace the impact of hope, optimism, and resilience”, Journal of Management, Vol. 33 No. 5, pp. 774-800.

Zapf, D., Dormann, C. and Frese, M. (1996), “Longitudinal studies in organizational stress research: a review of the literature with reference to methodological issues”, Journal of Occupational Health Psychology, Vol. 1 No. 2, pp. 145-169.

Acknowledgements

The authors would like to thank and acknowledge Hans Holterman Msc, for gathering the data for this study and sharing these with us.

Corresponding author

Judith H. Semeijn can be contacted at: judith.semeijn@ou.nl

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