"It's problematic because I have a tendency to sacrifice myself. Because I can't say no when it comes to patients. I could not prevent the illness from my secretary. Painful for me, because I know that I am part of it and could not prevent it, although I would like to have" [. . .] "There are so many requests and requirements in a hospital that need my attention and which I would like to see met. It is simply not possible, however. It is difficult to draw the line. Taking care of everyone is not easy. On the contrary, it often does not succeed at all" (CP 07).

"You have to be a little flexible yourself, organizational skills are important. But many people can't do that, get sick, get job anxiety" (SN 20). "A high workload makes you somehow headless. You notice that you sometimes can't implement your plans. Sometimes you walk a fine line: you want to be good to your employees, but you also want to take care of the tasks and demands of the nursing service management" (SN 28).

Finally, measures with a focus on justice, appreciation, and participation of employees were mentioned. Even if there is a general lack of functioning duty schedules in hospitals, managers see possibilities for action by letting employees participate to design and to ensure a most fair work time distribution. Appreciation can be given by managers in offering trainings, feedback, new tasks or job autonomy to employees.

"I can let employees participate in creating the duty schedule so that they can express their wishes. I can try to consider their wishes by priority, so that they are somehow satisfied" (SN 22). "I have the opportunity to treat everyone equally. No matter what I think of them. I try to do that very hard. I can give someone a goodie when people step in for others. Equal treatment is very important (patient distribution, creating the duty schedule)" (SN 17).

### **External focus on managers' behavioral control**

The perception of managers' behavioral control to implement work design measures is influenced, and often limited, by organizational factors. Restrictions for the implementation of work design measures are mainly perceived at the organizational level, partly also at the team level. Few managers perceive supportive organizational structures. The perceptions differ between occupational groups and across departments.

The managers perceive that high work intensity, the economic requirements, the lack of staff and missing job autonomy are the biggest challenges. These factors are often mentioned as difficulties to implement better working conditions by work design.

"Economic demands regulate our action's" (CP 09). "Improvement measures cannot be implemented for financial reasons" (CP 08). "We feel that we are doing a balancing act between work intensity, the necessary overall performance in patient treatment and ensuring that employees maintain their work-ability" (CP 11).

"Changes that cost something are not popular here in the hospital. Times in healthcare have become more difficult" (SP 33).

The development of functioning team structures is experienced as challenging or impossible, especially by physicians. The cooperation in the departments is characterized by continuous staff fluctuations. Various system-related reasons are mentioned. The medical training system requires a continuous change of personnel in the department. In-house rotations of the personnel are called complicating. Illness-related absences or dismissals aggravate the situation.

"The training of medical specialists alone makes for a continuous change in the team and it's functioning. No matter how good the functional units may be, we reach our limits in terms of personnel and economic responsibility" (CP 07).

"Too much rotation in personnel deployment makes people dissatisfied: a physician who takes the trouble today and thinks about what can be done better is somewhere else tomorrow and does not see the result. It also prevents team spirit. Our employees have no home base" (CP 013).

"I can make sure that the team function. But that has become more and more difficult in recent years. The team has changed completely since the acquisition of the new company" (SN 22).

Two chief physicians describe limitations in team development because of the strict separation between care and medicine. In general, limited possibilities to participate in the recruitment and selection of staff are described. They feel externally determined by the upper hospital management or the nursing service management and restricted in their job autonomy.

"Today, as chief physicians, we no longer have the autonomy (the position) to control a functioning unit. Today we are the foremen and are externally controlled by a superior economist. This makes it difficult to manage a functioning team from one's point of view. Besides, as chief physicians, we lead two different questions: medical (physicians) and care (nurses). But they are not one unit. The nursing management defines how it has to work and we have limited access" (CP 05).

Regular (interdisciplinary) team communication within flat hierarchical team structures are perceived by nursing staff and senior physicians as helpful in preventing work stress. While some managers perceive organizational structures that facilitate such an exchange, other managers describe their possibilities in that respect as limited. Senior physicians mention that due to the lack of communication in the team, many problems arise that have could have been avoided. Flat hierarchies are particularly appreciated by senior physicians and nurses but still not existing, which complicate the implementation of work design measures.

"I would always wish for it, but there is no time to reflect on certain things in the team. For example, what we can do to minimize stress. We don't realize that enough, we should do it much more often" (SP 37).

"It is really a pity that there is no real team spirit here. That would have to be strengthened. There are many more issues that have to be addressed in order to get more job satisfaction, but, unfortunately, there is no dialog for improvement. The general attitude toward improvement is very conservative" (SP 38). "Hierarchies and stuck working structures exist. This makes it difficult to change situations in a positive manner" (SP 32).

"We have a management circle in our department: the chief physician, the senior physicians and me as a senior nurse. On that board, I am able to communicate the information collected from the senior nurses. We talk about urgent things with an immediate need for action. Which might be handled in a small project. I let my colleagues participate and I thank God they join in. We also have case conferences and supervision. The communication is good, also the networking of the senior nurses works well" (SN 27).

Managers experience the greatest challenge in designing cross-departmental cooperation. Interface problems are difficult to solve and the physicians in particular often complain about the lack of cooperation with managers from other departments. Solving interface problems take time, energy, persistence, and requires suitable organizational structures to work on coordinated changes. The complexity of organizational structures in the hospital makes improvements of working conditions more difficult.

"Chief physicians do not work with the same goals in mind" (CP 01). "Many are very egocentric, and our enterprise fails because of this. What matters is the subject at work, not personal interests or vanities. The hospital extremely unorganized to the extent that one hand does not know what the other is doing" (CP 03). "Improving processes and structures takes several years. To implement measures across departments is difficult. Especially frustrating when you have tried everything. The fact that improvement often fails at the interfaces is already known (CP 02)."

In terms of this challenge, some interviewees see opportunities for chief physicians to form stronger alliances to bring across their common goals to the upper hospital management.

"Suggestions for work design would have to be bundled and sent to the employer via the chief physicians. I think that is how it would work. The departments, the chief physicians as representatives, would have to submit a consensus and ask for implementation. That would be the easiest way" (SP 33).

"If all the managers were to stand together, this would already be a great potential for cooperation with upper hospital management" (SN 23).

The cooperation with the upper hospital management is often perceived as restrictive and exhausting. Some managers point out that it takes a lot of time and effort to deal with the upper hospital management to get the problems solved. Others, who have made bad experiences in the support of the hospital management, seem resigned. They do not describe any possibilities on their own to change working conditions to the positive.

"Sometimes it's a long-lasting struggle with the upper hospital management to get demands accepted. However, it works" (CP 15). "I have no autonomy on my own to improve the situation for employees. I have little influence on my own and can only delegate the demands from above to the bottom-up" (CP 08).

"Management by Waiting. I simply sit things out. Someone takes care of it. You're looking forward to be free and then you keep on running in the hamster wheel. I don't see any possibilities for me to act, I don't have them. I can't take the pressure out; the patients are there. Of course, I transmit the pressure" (SN 19).

On the other hand, some managers benefit from the continuity in cooperative contact with upper hospital management or other stakeholders. A good and active contact with the upper hospital management or the nursing service management does not enable the direct implementation of improvements, but there is a perception that change processes can be initiated.

"I've been on the job for years and know what managing, leading and motivating means. I also know when my possibilities are exhausted, when I have reached my limit. Then I can contact the upper hospital management and nursing service management that support me. You can compensate for a lot of things by reflecting on yourself. But there are also moments when you somehow need feedback, what are you doing wrong, why are you feeling so bad. We are in a department in which with me and a new deputy have many possibilities to change things. Now we are doing everything possible and have already changed a lot. Our managers give us autonomy, as long as things work. And our colleagues are invited to join us. Thank God they do" (SN 27).

# SUMMARY AND DISCUSSION

Organizational research has shown that the support from managers is one of the key factors for the success or failure of organizational interventions (Bond and Bunce, 2001; Mattila and Elo, 2006; Nielsen et al., 2006; DeJoy et al., 2010; Bourbonnais et al., 2011; Petrou et al., 2016; Lundmark et al., 2017). However, current implementation research criticizes that success factors or obstacles for effective implementation were neglected or only considered retrospectively (Nielsen, 2013). There is a need for a theoretically sound and proactively oriented implementation research (Nielsen, 2013; Müller, 2016). With our qualitative approach and the application of the Theory of Planned Behavior (TPB) (Ajzen, 1991), we therefore explored the attitudes, organizational norms, and perceived behavioral control of managers concerning the promotion of health-related work design measures in hospitals, in order to contribute to the further theoretical and conceptional underpinning of the design and successful implementation of much needed work design interventions in hospitals.

The results on "attitude" show that the interviewed managers are sensitized to the topic of mental health and attach great importance to work design measures. In general, this finding indicates that the surveyed managers are willing to support health-related work design measures. However, the reasons differ depending on the occupational group: Almost all interviewees feel responsible for the mental health of their employees, but some perceive a role conflict between the fulfillment of medical and economic responsibility and the needs of the employees. Particularly, chief physicians describe the desired outcomes of work design measures from a more functional perspective (i.e., better health increases employee motivation, work ability, productivity, etc.) than the other two occupational groups (senior physicians and the senior nurses). The arguments of the latter two groups are rather based on an individual or moral health-related perspective, i.e., they consider the benefits of health promotion as a value in itself. This finding is in accordance to a study by Downey and Sharp (2007), which assumes that managers who are more under financial pressure report less moral responsibility for the employees' health promotion than others. Even though we did not ask the question about financial pressure directly, the role of the chief physicians is in German hospitals associated with more responsibility for the budget than in the other occupational groups. Those differences between occupational groups are important, when it comes to recruiting or motivating managers for work design interventions.

Organizational norms are perceived very differently depending on the individual experiences of the managers and depending on their occupational group. The majority of managers do not perceive health-promoting organizational norms. They state that there seems to be almost no official or open dialogue on mental health promotion, neither at the organizational level nor at the departmental level. A credible and transparent positioning of the hospital management to the topic mental health promotion is mainly missing. Poor leadership styles of colleagues are criticized, departmental differences are perceived, especially by chief physicians. Few managers who have personally experienced previous support in the implementation of work design measures organizational change processes by upper hospital management describe that workplace health promotion has a high priority for the executive board. Others report the opposite. They perceive little support and sometimes appear resigned. Managers who perceive hospital management as more supportive often experience more behavioral control to implement health-related organizational measures than others. At this point, we assume a relationship between organizational norms and perceived behavioral control, which has to be examined in future studies.

In accordance with previous studies (Downey and Sharp, 2007; Wilde et al., 2011), we believe that interventions to strengthen health-promoting organizational norms can make an important contribution to ensure that managers support organizational health-promoting measures. This assumption is supported in a very recent study by Biron and Karanika-Murray (2014) which is referring to the Psychosocial Safety Climate (PSC) a specific dimension of organizational climate which describes common perceptions relating to "policies, practices and procedures for the protection of worker psychological health and safety" (Dollard and Bakker, 2010, p. 580). The study of Biron and Karanika-Murray (2014) shows that organizational factors in terms of PSC influence managers' ownership of health-related intervention activities. Also, Biron and Karanika-Murray (2014) were able to show that the perception of

support by the upper hospital management, the integration of the topic mental health in the strategic management as well as functioning communication processes are important to strengthen the managers' commitment to health-related work design interventions.

In respect to perceived behavioral control, managers report that they are mainly able to provide social support, appreciation or equal rights for employees on an individual or team or departmental level. Concerning structural measures such as work design and improvement of work organization; managers perceive a rather low behavioral control. The implementation often fails due to lack of time and staff, especially due to fluctuations and absence due to illness. Cross-departmental organizational change processes are perceived as even more difficult or even impossible to implement. Success factors are considered to be an open and interdisciplinary communication culture, a common health-related goal orientation of all stakeholders, resources for the development of measures in project structures and support by hospital management. All in all, it can be assumed that work design measures are not implemented very frequently by managers. They seem to prefer individual and team related measures, focused on providing social support. Interventions to increase managers' perception of self-efficacy and the controllability to strengthen the mental health of their employees should therefore primarily concentrate on organizational approaches to work design.

### Limitations and Future Research

Due to the voluntary participation of managers in the interview study, we cannot rule out a sampling bias. We must assume that we have primarily reached those managers who had already positive attitudes toward the topic of employees' mental health. Moreover, participants might have shown a socially desirable response behavior. Other recruitment settings (e.g., congresses, in-house trainings) or strategies (e.g., direct letters and financial compensation) might have led to a different selection of participants.

Since we only interviewed managers of one hospital, the results cannot be generalized without further ado. The interview guideline appears to be suitable for use in other hospitals, so that its generalizability could be tested. It should be also taken into account that the results of our study only describe the perception of medical and nursing management. No conclusions can be made about how the upper hospital management really acts to improve the mental health of employees. In a follow-up study the upper hospital management also might be asked about their perception toward the topic of mental health promotion (e.g., in a focus group) and then compared with the results of the medical and nursing management.

Moreover, the study design does not allow us to make any statements about the actual behavior of managers. We decided against the assessment actual behavior for several reasons: In the context of the interviews it is difficult to make valid statements about actual behavior. Conceptually, it is difficult to separate actual behavior in the interviews from the perception of "behavioral control." In some cases we have concluded from reported behavior on PBC. Furthermore, quantitative studies have shown that the three predictors of the TPB can predict actual behavior. In view of the reference studies and our results, we assume that managers who report more positive attitudes, perceive supportive norms and behavioral control indeed design more health-promoting working conditions for their employees. We have retrospectively examined this assumption by additionally analyzing the interviews of two managers with contrary perspectives the TPB components (**Table 4**). The statements in **Table 4** indicate that medical and nursing managers who show higher values for the TPB components are more likely to practice health-promoting measures in work design than managers with lower values.

Nevertheless, it would have been desirable if we could have matched the statements of the managers with the assessments of their employees regarding their actual leadership behavior.

Leadership behavior has a significant impact on the employees' health (Kuoppala et al., 2008; Montano et al., 2017), the perception and the behavior of employees in the departments. Future quantitative research might examine the interactions between managers' perceived organizational norms (organizational culture) and the managers' actual behavior with regard to employee well-being and their work situation.

We are aware that all qualitative research is contextual; it takes place within a specific time and place between two or more people (Dodgson, 2019). The interviewers used a structured and pre-tested interview guide, to minimize situational or personal bias. However, complete objectivity is not given in qualitative research (Dodgson, 2019). For example, it cannot be excluded that in-depth questions differed due to personal or professional experience and interests of the interviewers.

## Conclusion and Practical Implications

Our study contributes to the research on health-related work design by showing that the theory of planned behavior (Ajzen, 1991) might be a useful theoretical framework for planning organizational interventions that are aimed to maintain and enhance the mental health of employees in hospitals. The theory can be used to capture the action guiding perceptions of managers, e.g., in relation to the implementation of health-related work design interventions. Moreover, the theory of planned behavior can be used to identify approaches for interventions that directly affect behavioral changes of managers in order to support such measures. In this way, the results of our study complement existing recommendations on how to improve the quality of the implementation of organizational interventions (Murta et al., 2007; Egan et al., 2009; Nielsen and Randall, 2012). While previous papers state that managers need to be supportive, or have even the role of "active crafters" (Nielsen, 2013) that participate in the design of organizational interventions, using the TPB allows us to understand why managers are often not willing or able to do so. Or, to put it positively: Our study allows us to better understand how to initiate the support of managers:

In respect to managers attitudes our findings indicate, that good treatment quality of patients and cost efficiency are often top priorities, especially for chief physicians and upper

### TABLE 4 | Examples of managers' statements with higher and lower TPB values.

hospital management. Managers are often not aware that the health of employees is a main resource for achieving these priorities. From our point of view, managers who have not yet been sensitized to the topic of mental health promotion of employees could be reached more easily by informing them on the interrelationships between mental health, staff motivation, treatment quality, economic success and patient satisfaction (Podsakoff et al., 2007; Angerer et al., 2012; Weigl et al., 2016; Han et al., 2019). The reported role conflicts

TABLE 5 | Practical approaches to foster managerial support of health-related work design interventions according the dimensions of the Theory of Planned Behavior model.

of the managers could be addressed if managers and the upper hospital management recognizes that employee health and cost efficiency are no contradictions. Moreover, when planning interventions, the different attitudes of different groups of managers should be taken into account: Chief physicians are more likely to be convinced with arguments that emphasize the link between mental health and performance. For senior physicians and nurses, moral and ethical aspects may be more important.

Our results on organizational norms suggest that hospitals need to establish an official and continuous dialogue on common health-related goals at the organizational or departmental level. This dialogue could be initiated by upper hospital management with the participation of upper and middle managers. Health-related company goals and offers should be developed transparently with the participation of employees. The existing management structures or instruments should be examined for possibilities to integrate health-related goals.

Our results on perceived behavioral control indicate that managers particularly need additional personal and external resources to implement health-related work design interventions (e.g., time, know-how). One the one hand the managers need more competencies to design work structures and processes. For example, they should be made familiar with participative approaches for healthy work design, that are based on wellfounded theory and empirical evidence (e.g., Aust and Ducki, 2004; Bourbonnais et al., 2006, 2011). On the other hand, upper hospital management should provide additional external

resources and accompany the development of work design measures ideally and operationally (Daniels et al., 2017). The key messages are summarized in **Table 5**.

Our qualitative findings might stimulate future studies that further validate our results. Moreover, our findings might further guide the development of interventions to improve health-related work design in hospitals. These measures are important to reduce the risk of impaired mental well-being among hospital staff and increase job satisfaction, which in turn have a positive effect on the quality of patient treatment.

### AUTHOR'S NOTE

The interview study was embedded in the cluster-randomized collaborative study "Mental Health in the workplace hospital" (SEEGEN), which aims to develop and implement behavioral and relational interventions to reduce stress in hospitals (Mulfinger et al., 2019). This project was funded by the German Federal Ministry of Education, and Research (BMBF), The University of Duisburg-Essen, Heinrich-Heine University Düsseldorf, Universities of Ulm, Tübingen, and Heidelberg are affiliated partners.

### DATA AVAILABILITY STATEMENT

The data sets generated for this study will not be made publicly available. The data supporting the results of

## REFERENCES

this study can be requested from MG, but restrictions apply if the use could endanger the anonymity of the participants.

## ETHICS STATEMENT

The studies involving human participants were reviewed and approved by the Ethics Committee of the Medical Faculty, University Düsseldorf. The patients/participants provided their written informed consent to participate in this study.

### AUTHOR CONTRIBUTIONS

AM developed the study concept. MG and BW performed the data collection. MG performed the data analysis and interpretation, and drafted the manuscript. AM, PA, and BW provided the critical revision of the manuscript. All authors designed the study and approved the final version of the manuscript for submission.

# FUNDING

We acknowledge support by the Open Access Publication Fund of the University of Duisburg-Essen.

safety, professionalism, and patient satisfaction: a systematic review and metaanalysis. JAMA Intern. Med. 178, 1317–1330. doi: 10.1001/jamainternmed.2018. 3713

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Genrich, Worringer, Angerer and Müller. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# "I Just Can't Take It Anymore": How Specific Work Characteristics Impact Younger Versus Older Nurses' Health, Satisfaction, and Commitment

Beatrice I. J. M. Van der Heijden1,2,3,4,5 \*, Inge Houkes<sup>6</sup> , Anja Van den Broeck7,8 and Katarzyna Czabanowska9,10

1 Institute for Management Research, Radboud University, Nijmegen, Netherlands, <sup>2</sup> School of Management, Open University of the Netherlands, Heerlen, Netherlands, <sup>3</sup> Department of Marketing, Innovation and Organisation, Ghent University, Ghent, Belgium, <sup>4</sup> Business School of Hubei University, Hubei University, Wuhan, China, <sup>5</sup> Kingston Business School, Kingston University, London, United Kingdom, <sup>6</sup> Social Medicine, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, Netherlands, <sup>7</sup> Department of Work and Organization Studies, KU Leuven, Leuven, Belgium, <sup>8</sup> Optentia, North West University, Vanderbijlpark, South Africa, <sup>9</sup> Department of International Health and Care, Public Health Research Institute, Maastricht University, Maastricht, Netherlands, <sup>10</sup> Institute of Public Health, Faculty of Health Sciences, Jagiellonian University, Krakow, Poland

### Edited by:

Kevin Rui-Han Teoh, Birkbeck, University of London, United Kingdom

### Reviewed by:

Montgomery Anthony, University of Macedonia, Greece Asta Medisauskaite, University College London, United Kingdom

\*Correspondence: Beatrice I. J. M. Van der Heijden

<EMAIL_ADDRESS>
### Specialty section:

This article was submitted to Organizational Psychology, a section of the journal Frontiers in Psychology

Received: 30 November 2019 Accepted: 27 March 2020 Published: 27 May 2020

### Citation:

Van der Heijden BIJM, Houkes I, Van den Broeck A and Czabanowska K (2020) "I Just Can't Take It Anymore": How Specific Work Characteristics Impact Younger Versus Older Nurses' Health, Satisfaction, and Commitment. Front. Psychol. 11:762. doi: 10.3389/fpsyg.2020.00762 Given the increasing shortage of active nurses in industrialized countries throughout the world, it is of utmost importance to protect their health, satisfaction, and commitment so that they can continue working in their healthcare institution. Building upon the proposed pattern of specific relationships developed by Houkes et al. (2003), we investigated a model of relationships among working conditions (quantitative, emotional, and physical demands), labor relations (quality of interpersonal relations and psychological support), work content (meaning of work, influence at work), and employment conditions (opportunities for development) on the one hand, and health, job satisfaction, and institutional affective commitment on the other hand, for younger versus older nurses. We used data of 3,399 nurses from the Netherlands and 3,636 nurses from Poland from the larger European Nurses' Early Exit Study (NEXT) and performed longitudinal structural equation modeling (SEM) and multi-group analyses. The results showed that the proposed pattern of relationships generally holds, but that the nurses' level of commitment is more determined by meaning of work than by opportunities for development and that psychological support is associated with job satisfaction (and not only with burnout as hypothesized, in both the Netherlands and Poland). Comparing younger (<40 years) versus older (≥40 years) nurses, we found ample support for differences in the proposed model relationships across age category, some being in line with and some being contradictory to our expectations. We argue that a nonnormative, tailor-made approach to aging at work might help us to protect the nurses' career sustainability across the life span. This study provides evidence-based practical recommendations on how to enhance the health, job satisfaction, and commitment of nurses throughout their working life.

Keywords: nurses, labor relations, work content, conditions of employment, burnout, job satisfaction, institutional affective commitment, age

# INTRODUCTION

fpsyg-11-00762 May 25, 2020 Time: 12:43 # 2

Demographic changes such as aging and dejuvenization have increased the need for care in Europe (Wang and Shi, 2014). At the same time, Europe faces a considerable shortage of nurses (Chan et al., 2013) due to the "baby boomer" generation approaching (early) retirement and the high level of premature professional turnover (Buchan et al., 2015). This is not expected to improve in the short run (Chan et al., 2013).

Nursing is a highly demanding profession which entails high risks for health problems (Aiken et al., 2001; Mark and Smith, 2012), limiting nurses' work ability (Ilmarinen, 1999) and employability (career potential) (Fugate et al., 2004; Van der Heijden et al., 2009), and herewith their capacity to work until official retirement age. In addition, many nurses leave the nursing profession, which they consider unattractive and extremely burdensome, due to the nature of the work, no sense of purpose of their own work, and negative interpersonal relations, as well as a disconnection with the profession and the institution, lack of job satisfaction, burnout, and low assessment of their own health (Aiken et al., 2012).

Nurses' health, job satisfaction (Lu et al., 2019), and organizational commitment (Brunetto et al., 2013) are among the key factors that predict whether they are able to stay active in the labor market and to prevent premature leave (Hasselhorn et al., 2003). Based on the literature on work characteristics (Parker et al., 2017a) and highly influential models in the scholarly domain of aging (Ilmarinen, 2007; Brady et al., 2019), work characteristics can be seen as of essential importance to maintain or even improve employees' health, job satisfaction, and organizational commitment and – therefore – their work ability, especially of older workers. It is therefore of utmost importance to understand the impact of work characteristics on nurses' health, satisfaction, and commitment and age-related differences therein.

As a part of the European Nurses' Early Exit Study (NEXT) research project,<sup>1</sup> this study aims to increase our understanding of how work characteristics subdivided into four clear categories (in line with Houkes et al., 2001) – (1) working conditions, (2) labor relations, (3) work content, and (4) conditions of employment (see also Kompier and Marcelissen, 1990; Kompier and Di Martino, 1995) – impact over time on nurses' health (i.e., burnout, disability), job satisfaction (as a motivational variable), and institutional affective commitment (as a careerrelated variable). Building on the Selection, Optimization, and Compensation Theory (SOC) and the Socio-emotional Selectivity Theory (SST) – being two complementary perspectives on aging at work – we moreover investigate whether this pattern of relationships is different for younger (<40 years) versus older (≥40 years) nurses [see Finkelstein and Farrell, 2007, p. 100, on the Age Discrimination in Employment Act (ADEA); see also Boerlijst et al., 1998; Taylor and Walker, 1998; Van der Heijden et al., 2009, for justification for this dichotomy in research that has been conducted in Europe]. Although age is often included as a covariate or confounder in research studying the associations between work characteristics and outcomes, more empirical work is needed to study if and how age affects relationships between model variables (De Lange et al., 2010).

Considering the recommendations by Lave and March (1990) and Kristensen (1996), and in line with Houkes et al. (2001), we will test our proposed research model in two different countries. This will help us to gain more insight into the robustness and generalizability of our study and adds to the paucity of comparative career research (Thomas and Inkson, 2007). In particular, we will focus on the Netherlands and Poland, which both experience a severe shortage of nurses due to the increase in healthcare needs of the aging society, the rising incidence of chronic diseases and disabilities, retiring older generations of nurses, the emigration of staff, and changes in the educational system (Zgliczynski et al., 2016 ´ ; Taskforce Healthcare, 2017). The problems related to the shortages of the workforce are thus similar in both countries, however, in the literature some overlapping and divergent experiences have been reported among nurses in the Netherlands and Poland, which makes it particularly relevant to examine whether one theoretical model can explain these experiences. Levels of emotional exhaustion, for example, are lower in the Netherlands than in Poland (Huisman-de Waal et al., 2019; Kózka et al., 2019). Eight out of 10 Dutch nurses are proud to work in their healthcare setting but would appreciate more managerial support and recognition. Polish nurses' desire to leave is related to organizational and socio-economic factors, such as bad working conditions, interpersonal conflicts, wrong management system, low status of work in social hierarchy, shortage of human resources, job insecurity, competition, lack of trust, and low salaries in relation to their efforts. Given the similarities and differences between both countries, we argue that they are a good basis for our empirical research.

The outline given above stresses that, apart from adding to the theory development on the impact of work characteristics on nurses' health, job satisfaction, and organizational commitment, this study also has practical merits in providing healthcare managers in the Netherlands and Poland with evidence-based advice on how to fine-tune work characteristics for nurses across the life span.

# THEORETICAL FRAMEWORK

## Work Characteristics as Predictors of Health, Job Satisfaction, and Commitment

Work design, which is defined as the content and organization of one's work tasks, activities, relationships, and responsibilities (Parker, 2014, p. 662), has implications for important employee and organizational outcomes, including health and wellbeing, motivation, innovation, and performance. In their seminal work, Houkes et al. (2001) aimed to contribute to the work design literature by improving and refining exemplary work design models, such as the model for Work, Stress, and Health (Kompier and Marcelissen, 1990; Kompier and Di Martino, 1995), the Demand–Control–Support

<sup>1</sup>The NEXT study was financed by the European Commission within the Fifth Framework, Project ID: QLK-6-CT-2001-00475.

model (DCS model; Johnson and Hall, 1988; Karasek and Theorell, 1990), and the Effort–Reward Imbalance model (ERI model; Siegrist, 1996). Notwithstanding the contribution of these models to the theorizing in the field of work psychology and their added value for the design of employee jobs, Houkes et al. (2001) argued that the work design literature was in need of more refined models to better understand specific patterns of relationships between various work characteristics and outcome variables and to suggest evidence-based interventions at the workplace.

To arrive at more specific and testable hypotheses, Houkes et al. (2001) studied how various characteristics of the working conditions, labor relations, work content, as well as conditions of employment yield specific relationships with outcomes such as exhaustion, as an indicator of employees' health and well-being; job satisfaction, being a motivational outcome; and turnover intentions, which can be considered a career outcome. They argued and found that emotional exhaustion was most strongly predicted by workload, which is indicative of the conditions under which work needs to be done, and social support, referring to an aspect of the social and labor relations at work. In line with Hobfoll (1989); Houkes et al. (2001) posited that this is the case because workload threatens people's abilities to maintain and obtain resources, which in turns triggers emotional exhaustion. Social support, in contrast, is considered a valuable resource, as it brings direct instrumental help, feedback, information, or emotional support (House, 1981), and is helpful in buffering the demanding characteristics of one's work (Bakker et al., 2005). The availability of social support may therefore increase employees' pool of resources and contribute to their health and prevent emotional exhaustion.

Intrinsic motivation was primary predicted by work content variables such as feedback, autonomy, and skill use. These factors are enjoyable aspects of the job itself and speak to the interest of employees, and, following Hackman and Oldham (1976), these factors have great motivating potential. Finally, Houkes et al. (2001) argued and found that turnover was most strongly predicted by employment conditions such as unmet expectations regarding one's salary, job security, and position. The lack of good employment conditions frustrates employees' growth needs, and as a result, it is likely that employees are pushed to look for growth opportunities elsewhere.

Several studies have provided support for the applicability of the model of Houkes et al. (2001) in the nursing sector. More specifically, these studies showed that job control was consistently a stronger predictor of motivational outcomes such as job satisfaction, while job demands consistently were the strongest predictors of emotional exhaustion (primary indicator of burnout) (Tummers et al., 2002; Janssen et al., 2004). We aim to build on the model of Houkes et al. (2001) by studying the specific longitudinal effects of several aspects of nurses' working conditions (quantitative, emotional, and physical demands), labor relations (quality of interpersonal relations and psychological support), work content (meaning of work and influence at work), and conditions of employment (opportunities for development) on nurses' burnout and disability as health indicators, job satisfaction as a motivational outcome, and institutional affective commitment as a career-related outcome. Earlier empirical work in the nursing sector has already shown that these variables matter. For example, meta-analytic findings indicate that nurses who are confronted with working conditions such as high workload and a lack of social relations are more prone to burnout (Li et al., 2018). Other working conditions such as quantitative, emotional, and physical demands are furthermore an important risk factor for nurses' well-being, both in their personal life and at the workplace (see, for instance, Van der Heijden et al., 2008), while social support of one's direct supervisor and near colleagues are among the most important factors to maintain health and well-being when nurses face challenging work demands (Estryn-Behar et al., 2007; Van der Heijden et al., 2017).

Furthermore, an overview of the literature indicates that work content variables such as meaningfulness and control are among the most important work aspects that contribute to nurses' motivation for the job and are associated with nurses' job satisfaction (Toode et al., 2011; Lu et al., 2019). Finally, nurses' turnover intent increases when employment conditions, such as opportunities for growth and development as well as pay and salary, are unsatisfactory (Flinkman et al., 2010; Halter et al., 2017). Perceived organizational support for further development (Tansky and Cohen, 2001) and career growth (Weng et al., 2010; Weng and McElroy, 2012) also appear to be associated with organizational commitment, being one of the outcome indicators in our research model.

Although these studies convincingly show that working conditions, labor relations, work content, and employment conditions matter for nurses' health, motivation and career outcomes, they did not systematically test the relative importance of these categories of work characteristics in predicting these outcomes as proposed by Houkes et al. (2001). For example, the reviews by Lu et al. (2019) and by Toode et al. (2011) also indicate that demanding working conditions are associated with job satisfaction, being our motivational outcome, and that social relations contribute to nurses' motivation as well, yet the relative contributions of working conditions and labor relations vis-à-vis work content and conditions of employment in the prediction of outcomes were not examined. In order to bring more specificity in the way we theorize and study the impact of work characteristics among nurses, and to allow for specific interventions, we tie in with the model of Houkes et al. (2001) and formulate the following hypotheses (see **Figure 1**):

Hypothesis 1: Nurses' health, in terms of their burnout and disability, is primarily predicted by working conditions (quantitative, emotional, and physical demands) and labor relations (quality of interpersonal relations and psychological support). More specifically, burnout is mainly predicted by quantitative demands, emotional demands, quality of interpersonal relations, and psychological support, and disability is mainly predicted by physical demands.

Hypothesis 2: Nurses' job satisfaction is primarily predicted by work content (meaning of work and influence at work).

Hypothesis 3: Nurses' institutional affective commitment is primarily predicted by conditions of employment (opportunities for development).

Please note: Our current selection of indicators of the four areas of work characteristics in the NEXT data set expands upon the theoretical model and the selection of variables of Houkes et al. (2001) and the initial work of Kompier and colleagues (Kompier and Marcelissen, 1990; Kompier and Di Martino, 1995). Working conditions refer to the amount of work, the physical conditions, and the safety issues related to work. In line with this definition, we included three different types of work demands (i.e., quantitative, emotional, and physical demands), thereby expanding the work of Houkes et al. (2001), who focused on quantitative demands only. Labor relations refer to the (formal and informal) relationships and interactions employers and employees have with each other and the amount of support these relationships provide (Kompier and Marcelissen, 1990; Houkes et al., 2001, 2003). Although social support was not an available measure in the NEXT data set, we were able to include quality of interpersonal relations and psychological support, thereby stretching the operationalization of this construct in the work by Houkes et al. (2001). Work content refers to content and characteristics of the tasks to be done (e.g., Kompier and Marcelissen, 1990). For this category of work characteristics, we have included meaning of work and influence at work, which resembles the operationalization of Houkes et al. (2001) (that is, motivating potential, consisting of autonomy and task significance). Conditions of employment refer to the agreements that are being made between employee and the organization, and concerns aspects such as salary and career and growth opportunities (Kompier and Marcelissen, 1990). Houkes et al. (2001) used the more negative indicator "unmet career expectations" including expectations around salary, position, and job security. We focus on opportunities for development as a good alternative indicator for conditions of employment in the contemporary labor market, as it focuses on one's intrinsic growth opportunities in the job.

### The Impact of Nurses' Age

Because the workforce is aging, researchers are increasingly examining how older employees – compared to their younger colleagues – experience their work and work setting. While considerable attention has been devoted to whether maintenance- (e.g., participation) and growth-related (e.g., training and development) HR practices have different implications for workers differing in age (e.g., Kooij et al., 2010), the job design literature has been relatively silent about the potential differences in the impact of work characteristics on

older and younger employees' health and well-being, on their motivation (see Schreurs et al., 2012, for a cross-sectional paper example), and on (other) career-related outcomes.

To formulate specific hypotheses, we borrow from life span development theories, in particular, the SOC (Baltes et al., 1999) and SST (Carstensen, 1995), in arguing that older nurses face the challenges of loss, growth, and change over time (Kanfer and Ackerman, 2004). Older workers, for example, experience a decline in physical capacities and fluid intelligence yet an incline in crystallized intelligence and experiences. Moreover, the salience of particular life goals fluctuates depending on one's life cycle, with some goals gaining more importance and others becoming less valuable when employees grow older. All this, in turn, may influence how the various aspects of work conditions, labor relations, work content, and conditions of employment influence employee health, motivational, and career-related outcomes.

First, because older employees are confronted with several losses, they may become more sensitive to demanding situations. We argue that this may be the case because such situations may appeal to the impaired skills, abilities, or energy of older workers or require them to mobilize all remaining energy and other resources to overcome these demands (Hobfoll, 1989; Hobfoll et al., 2018). Given that older employees may lack the relevant compensatory resources, they would rather use other strategies, such as preventing such demanding situations from happening or disengaging from situations that pose unattainable goals (Moghimi et al., 2017). Within the work context, however, nurses are unlikely to be able to avoid all demanding working conditions. Therefore, we expect that the health-impairing impact (Bakker et al., 2005) of demanding working conditions, such as quantitative, emotional, and physical demands, may be stronger for older than for younger workers. More specifically, we assume:

Hypothesis 4: Age impacts the relationship between working conditions and health such that the positive relationship between quantitative and emotional demands and nurses' burnout and the positive relationship between physical demands and nurses' disability are stronger for older compared to younger workers.

Second, because of the experience of loss, older employees are also likely to become more sensitive to resourceful situations, which are beneficial in and of themselves but are especially valuable because they help older employees to deal with the wide range of demands they are confronted with (Hobfoll, 1989; Hobfoll et al., 2018). Not all resources may, however, be experienced as equally beneficial. Following the SST (Carstensen, 1995), with increasing age, one's time frame changes, causing older employees to value different things than younger employees. While younger nurses may perceive time as more "open-ended" (Carstensen, 1995; Kooij et al., 2018; Dordoni et al., 2019), older nurses' future time perspective is more limited and framed in terms of the "remaining time." Younger employees are therefore more likely to focus on all possibilities lying ahead and value keeping all options open. This translates, for example, into attaching high importance to extrinsic rewards, such as pay and promotion, as these help to achieve other things in life. In addition, younger workers also highly value opportunities for development. Even when such opportunities do not serve immediate payoff, they might come in handy somewhere in the future. This line of reasoning also applies to social relations. Younger employees have a wish to expand their social network, as new people may help them to gain new knowledge and information and may be helpful to reach future goals.

Older employees, in contrast, are more oriented toward making the remaining time count. They therefore have a stronger focus on the present and prioritize emotional well-being over growth and learning. Older workers therefore highly value intrinsic qualities of a job, such as the work content, rather than opportunities for growth and development, and they attach more importance to the quality of relationships in comparison with their quantity. Rather than having more relationships, they deepen their existing ones and value the support they get from these. Therefore, we argue that for the older nurses, the impact of the quality of their interpersonal relationships with various stakeholders, ranging from nursing management to colleagues, and the quality of the psychological support (e.g., in terms of their satisfaction with the support provided at work) are especially important for their emotional well-being (i.e., prevention of burnout). Given that we expect labor relations to be one of the primary predictors of health, work content to be the primary predictor of job satisfaction, and opportunities for development to be the primary predictor of organizational commitment, we therefore formulate:

Hypothesis 5: Age impacts the relationship between labor relations and health such that the positive relationship between the quality of interpersonal relations and psychological support on the one hand and nurses' burnout on the other hand is stronger for older compared to younger workers.

Hypothesis 6: Age impacts the relationship between work content and job satisfaction such that the positive relationship between meaning of work and influence at work with nurses' job satisfaction is stronger for older compared to younger workers.

Hypothesis 7: Age impacts the relationship between conditions of employment and institutional affective commitment such that the positive relationship between opportunities for development and institutional affective commitment is weaker for older workers.

# METHODOLOGY

### Design, Participants, and Procedure

This study comprises an incomplete two-wave panel design (Zapf et al., 1996) utilizing the Dutch and the Polish part of the database of a large European survey study on nurses' reasons, circumstances, and consequences surrounding premature departure from the nursing profession (NEXT). The

NEXT study has been approved by the ethical committee of the University of Wuppertal in Germany. Stratified sampling has been used in order to, as far as possible, reflect the national distribution of nurses working in the Netherlands and in Poland in three different types of institutions (hospitals, nursing homes, and home care institutions) and to cover the different regions in the two countries in a representative way. In particular, the researchers have tried their best to ensure proportionate ratios regarding employment figures, gender distribution, age structure, and working hours across the distinguished types of institutions, while at the same time incorporating the geographical spread across the specific regions in the Netherlands and Poland. To reach this goal, a thorough analysis of the healthcare industry across the two countries, and the population of nurses working in it, was conducted in order to make sure that the study sample would be representative of the participating country's industry breakdown as regards the distinguished criteria.

The longitudinal design of the study (1-year time lag) comprised a baseline questionnaire and a follow-up questionnaire covering aspects of nurses' working and private lives, which were sent to a total of 9,309 Dutch and 7,091 Polish nurses at baseline measurement. These two samples covered all nurse qualification levels, as this was expected to increase the variation in (the level of) work characteristics and resources (Warr, 1990) of nurses who were working in hospitals, nursing homes, and home care institutions. A total of 4,024 Dutch and 4,354 Polish participants returned the baseline (T0) questionnaire, which means a response rate of 43.2 and 61.4%, respectively. The follow-up questionnaire (T1) was returned by 2,433 (25.1%) and 4,547 (64.5%) nurses, respectively. **Table 1** provides some descriptives of the Dutch and Polish sample (distribution of age, gender, and type of institution).

### Measures

Three indicators for working conditions were included in the present study. Quantitative demands were measured using a four-item scale from the COPSOQ (Copenhagen Psychosocial Questionnaire) (Kristensen and Borritz, 2001), which refers to demands in terms of number of work hours (extensive demand) and/or work pace (intensive demand). An example item was: "How often do you lack time to complete all your work tasks?" Response categories ranged from: 1, "hardly ever," to 5, "always." One missing item per subject was allowed for scale calculation. Emotional demands were measured using a four-item scale specifically developed for healthcare professionals by De Jonge et al. (1999). Participants were asked to indicate on a fivepoint rating scale how often they were confronted with "death," "illness or any other human suffering," "aggressive patients," and "troublesome patients" in their work. Response categories ranged from: 1, "never," to 5, "always." One missing item per respondent was allowed for scale calculation. Physical demands were measured using three items that were constructed by the NEXT study group (Hasselhorn et al., 2003) (physical load major factors in nursing index): (a) "lifting patients in bed without aid," (b) "maintaining an uncomfortable posture," and (c) "working in a standing posture." The response categories for the first two items were: (1) "0 to 1 times a day," (2) "2–5 times a day," (3) "6– 10 times a day," and (4) "more than 10 times a day." The response categories for the third item were: (1) less than 2 h, (2) 2–3 h, (3) 4–5 h, and (4) 6 h or more. The final score has been computed as a sum score divided by three. Physical load was considered to be low when scored from 1 through 2, medium when scored from 2.01 through 2.99, and high when scored from 3 through 4. No missing item was allowed to calculate the mean score.

As regards labor relations, two indicators were used. The quality of interpersonal relations between nurses and five relevant groups in their working environment (i.e., nursing management, the sister/charge nurse, colleagues, doctors, and administration) was assessed using a five-point scale ranging from: 1, "hostile and tense," to 5, "friendly and relaxed." No missing item was allowed for calculating the mean score. The original scale range of 1–5 has been recorded into 1–4 (by combining scores 2 and 3) to make the variables measured at T0 and T1 comparable. Psychological support was measured by means of one item (Hasselhorn et al., 2003): "Are you satisfied about the psychological support at work?" The response scale ranged from 1, "very unsatisfied," to 4, "very satisfied."

As regards work content, we incorporated two indicators. Meaning of work was measured using three items from the COPSOQ (Kristensen and Borritz, 2001) ("Is your work meaningful?", "Do you feel that the work you do is important?", and "Do you feel motivated and involved in your work?"). The possible scale range was from: 1, "to a very small extent," to 5, "to a large extent." No missing items were allowed for calculation of the means. Influence at work was measured using a four-item scale containing modified items based on the Demand–Control Questionnaire (Theorell et al., 1988). An example item was: "I can decide for myself how to fulfill the tasks that are assigned to me." The respondents were asked to indicate on a five-point rating scale how accurate the statements were in relation to their personal occupational situation, with response categories ranging from: 1, "totally inaccurate," to 5, "totally accurate." One missing item per participant was allowed for scale construction.

As regards conditions of employment, we included one indicator, i.e., opportunities for development. Opportunities for development was measured using a four-item scale from the COPSOQ (Kristensen and Borritz, 2001). An example item was: "Do you have the possibility to learn new things through your work?" Response categories ranged from: 1, "to a very small extent," to 5, "to a large extent." One missing item per participant was allowed for construction of the scale mean.

As regards the outcomes variables in our research model, the indicators for health were burnout and disability. Burnout was assessed using a five-item scale taken from the COPSOQ (Kristensen and Borritz, 2001). An example item was: "How often are you emotionally exhausted?" The response scale ranged from: 1, never/almost never, to 5, (almost) every day. One missing item per participant was allowed to calculate the mean score. Disability was measured with Von Korff et al.'s (1992) four-item instrument to measure peoples' pain and/or disability due to low back pain and neck/shoulder pain. An example item was: "Considering the past half year, how much has neck or low back pain interfered with your daily activities?" The response categories ranged from

TABLE 1 | Demographics, descriptives and reliabilities for the samples of the Netherlands and Poland (N ranges from 1,150 to 4,200).

\*Original range 1–5, recoded into 1–4 (by combining scores 2 and 3) to make variable comparable to T1 measurement. \*\*α between brackets after deletion of Item 1 (number of days kept off work due to Neck Shoulder/Low Backpain complaints). Disability score was calculated following the method described by the author (Von Korff et al., 1992).

0 (no interference or change) to 10 (highest interference or very much change). Back- or neck-pain-related disability was considered to be low for nurses scoring 0, medium for nurses scoring from 1 through 2, and high for nurses scoring from 3 through 10. One missing item per participant was allowed for score building. Job satisfaction was measured with four items from the COPSOQ (Kristensen and Borritz, 2001). A sample item was: "How pleased are you with your job as a whole?" Responses were made on a four-point rating scale (1, very unsatisfied, to 4, very satisfied). One missing item per participant was allowed to calculate the mean score. Institutional affective commitment was measured with Allen and Meyer's (1996) four-item scale. This scale was used in its original form; however, the wording was – where appropriate – slightly changed. An example item was: "I am proud to belong to this institution." Responses were made on a five-point rating scale (1, strongly disagree, to 5, strongly agree). One missing item per respondent was allowed to calculate the mean score.

Gender and type of institution (hospital, nursing home, and home care) were included as control variables that could be expected to confound relationships between work characteristics and the outcomes. Cronbach's alphas of all variables are shown in **Table 1**. The measures used in this study have all proven to be valid and reliable in this study and in previous empirical work.

### Analyses

All data were analyzed for the Netherlands and Poland separately. Prior to testing the hypotheses, we performed dropout analyses (to examine possible mean differences between employees in the panel group and the dropouts) and several preliminary analyses (means, standard deviations, Pearson's r correlations, and Cronbach's alphas). We first tested whether the proposed pattern of relationships (Hypotheses 1–3) held for the complete Dutch and Polish samples and then tested for differences between younger and older nurses by means of multi-group analyses (MGAs) (Hypotheses 4–7) in IBM AMOS25 (Byrne, 2016).

In all structural equation modeling (SEM) analyses, we simplified the covariance structure by assuming that the latent and observed variables were identical in order to prevent identification problems and unreliable parameter estimates (cf. Schumacker and Lomax, 2010). MGA enables investigating to what extent a proposed pattern of relationships is actually

consistent with the observed data in two or more samples simultaneously (Byrne, 2004; Schumacker and Lomax, 2010). Furthermore, with MGA, it is possible to investigate whether a proposed pattern of relationships is invariant (i.e., has the same strength and direction) across different groups (cf. Byrne, 1994, 2016) and whether differences exist between groups (Schumacker and Lomax, 2010).

We used an incomplete panel design to analyze the longitudinal data, using work characteristics measured at T0 and outcome variables measured at both T0 and T1 (e.g., Zapf et al., 1996). We specified the synchronous and cross-lagged paths in accordance with the pattern of relationships as depicted in **Figure 1**. We allowed the work characteristics as well as the residual errors of the outcome variables to correlate. To assess the overall model fit, several commonly used fit indices were used (cf. Diamantopoulos and Siguaw, 2002; Schumacker and Lomax, 2010; Byrne, 2016): the chi-square statistic, the root mean square residual (RMR), the goodness-of-fit index (GFI), the adjusted goodness-of-fit index (AGFI), the normed fit index (NFI), the comparative fit index (CFI), and the root mean square error of approximation (RMSEA). Models were adjusted based on the modification indices, which provide information as to what specific relationships should be added to the model, when theoretically plausible, in order to improve the fit between the hypothesized model and the data (Byrne, 2016). Nested models were compared by means of the chi-square difference test. Finally, t-values were used to assess the significance of specific relationships.

## RESULTS

### Dropout Analyses

In order to rule out selection problems due to panel loss, we determined whether employees in the panel group (who filled out both the T0 and T1 questionnaires) and the dropouts (who only filled out the T0 survey) differed with regard to their mean scores on the research variables and demographics by means of t-tests and chi-square difference tests. For most research variables and demographics, the mean differences did not differ significantly between the panel group and the dropouts for both the Netherlands and Poland. More specifically, for the Netherlands though, we found a significant mean difference of 0.82 regarding age. In particular, employees in the panel group [mean (SD) = 38.78 (9.70)] were slightly older than the dropouts [Mean (SD) = 37.96 (9.74)]; the mean difference was less than one-tenth of the SD. We also found a mean difference of 0.06 regarding burnout, with the dropouts scoring slightly higher [mean (SD) = 1.70 (0.55)] in comparison with the panel group [mean (SD) = 1.64 (0.55)]; the mean difference was approximately one-tenth of the SD. Finally, the Dutch panel group contained slightly more male nurses (5.6%) than the dropouts (1.9%). For Poland, we found a mean difference of 0.05 regarding quantitative demands, with the panel group scoring slightly higher [mean (SD) = 3.41 (0.64)] than the dropouts [mean (SD) = 3.56 (0.67)]; the mean difference was less than one-tenth of the SD. With these outcomes, we can conclude that mean differences between the panel group and the dropouts were few and small, and hence that selection problems did not occur in our study.

### Preliminary Analyses

**Table 1** shows the demographics of both the Dutch and Polish samples and the means, standard deviations, and internal consistencies of the study variables. **Table 2** shows the correlation matrix of all study variables. The reliabilities (in Cronbach's alphas) of the study variables appeared to be adequate to good. The pattern of correlations was generally in line with Hypotheses 1 and 2 in both samples (the Netherlands and Poland), but opportunities for development tended not to correlate with institutional commitment. In addition, meaning of work was correlated with job satisfaction (as hypothesized) but also with institutional commitment. The variables quality of interpersonal relations and psychological support appeared to be correlated with both burnout (as hypothesized) and job satisfaction.

# Testing the Associations Between Work Characteristics and Outcomes

In the Dutch sample, the fit of base model M1 was not optimal, so based on modification indices, the following relationships were added (one by one): psychological support to job satisfaction T0 and meaning of work to institutional commitment T0. This adjusted model M2 fitted significantly better (see **Table 3**). As shown in **Figure 2**, the hypothesized pattern of relationships was generally supported (Hypotheses 1 and 2 were largely confirmed). In particular, as regards Hypothesis 1 (impact on health), the Dutch nurses' disability was indeed predicted by physical demands, both in the synchronous and cross-lagged analyses (see **Figure 2**). The path between psychological support and burnout was significant, yet at T0 only. Contrary to our expectations, the synchronous paths between emotional demands and quality of interpersonal relations, on the one hand, and burnout, on the other hand, were not significant. As regards Hypothesis 2, both the synchronous paths between meaning of work and of influence at work, on the one hand, and job satisfaction were significant. Meaning of work was also positively related to institutional affective commitment T0 (added path) and to job satisfaction at T1 in the Dutch sample. Contrary to our expectations, opportunities for development was unrelated to institutional affective commitment at T0 (with these outcomes, Hypothesis 3 was not confirmed with our data).

Considering the cross-lagged paths, the number of significant relationships was relatively low due to the strong stabilities of the outcome variables over time. The cross-lagged path between physical demands and disability was significant for the Dutch nurses. Moreover, meaning of work was related to job satisfaction at T1 as well.

Also, in the Polish sample, the fit of base model M1 was not optimal. Based on modification indices, the following relationships were therefore added (one by one): psychological support to job satisfaction T0, psychological support to institutional commitment T0, and meaning of work to institutional affective commitment at T0. This adjusted model

\*p < 0.05.

TABLE 3 | Fit measures for all employees and per age group (<40 and >40) for the Netherlands and Poland.

\*p < 0.05.

M2 fitted significantly better (see **Table 3**). As shown in **Figure 2**, also in this sample, the hypothesized pattern of relationships was generally supported (Hypotheses 1 and 2 were largely confirmed), but several paths had to be added to achieve optimal model fit. The synchronous path between emotional demands and burnout was not significant (just as in the Dutch sample). As regards Hypothesis 2, only influence at work appeared to be related to job satisfaction. In addition, meaning of work had a strong relationship with institutional commitment at T0 and was not significantly related to job satisfaction at T0. Hypothesis 3

was only weakly confirmed when using the synchronous analysis in the Polish sample.

Considering the cross-lagged paths for the Polish sample, emotional demands and psychological support were significantly related to burnout at T1. Moreover, both meaning of work and influence at work appeared to be significantly related to job satisfaction at T1.

## Testing the Impact of Age: Multi-Group Analyses

In accordance with suggestions by Byrne (2004), we tested the hypothesized models in the younger and older groups separately prior to performing MGA. **Table 3** shows the model fit of the base models (M1) and the adjusted models (M2) for younger (<40) and older (≥41) Dutch and Polish nurses. For the younger nurses in the Netherlands, we added the following paths: psychological support to job satisfaction T0 and meaning of work to institutional commitment T0. For the older Dutch nurses, we added these paths as well, plus an additional path from psychological support to institutional commitment T0.

For the younger nurses in Poland, we added paths from psychological support, on the one hand, to job satisfaction T0 and institutional commitment T0, on the other hand. In addition, we added a path from meaning of work to institutional affective commitment at T0. For the older nurses in Poland, we added paths from psychological support to job satisfaction T0 and institutional commitment T0 (similar to the younger nurses), and from quality of interpersonal relations to institutional commitment at T0. These adjusted models M2 fitted significantly better than the base models M1 for all four samples and were used as input for the MGA. In these MGAs, we compared a fully constrained invariant model M1 with two less constrained fully and partially non-invariant models M2 and M3 by means of the chi-square difference test (see **Table 4**).

For the Dutch sample, we found that M2 and M3 both had a better fit than M1 (invariant model) but that M3 was not better than M2. Hence, M2 (partially invariant) is the best model, and M2 also has the best practical fit indices. This outcome means that the pattern and strength of relations was not similar for younger and older Dutch nurses. **Figure 3** shows the path coefficients of younger and older Dutch nurses in M2. This figure shows ample differences between younger and older Dutch nurses. Physical demands relate to disability and emotional demands to burnout in the synchronous analysis for the older but not for the younger nurses (in line with Hypothesis 4). Surprisingly, the cross-lagged path between physical demands and disability is significant for younger nurses but not for the older nurses. Contradictory to Hypothesis 5, the quality of interpersonal relationships was not related to burnout, either for younger or for older nurses. In line with our expectations, psychological support appeared to be more strongly related to burnout for older nurses. Moreover, for both younger and older nurses, psychological support is related to job satisfaction, and meaning of work is related to institutional commitment (additional paths). In addition, for both younger and older nurses, psychological support is related to institutional affective commitment, but more so for older nurses. As regards Hypothesis 6, we found that influence at work was only significantly related to job satisfaction for older nurses but that meaning of work was more relevant for younger nurses. In addition, for both categories of nurses, especially for the younger ones, meaning of work was significantly and strongly related to institutional affective commitment (additional path). Hypothesis 7 could not be confirmed with our data, as opportunities for development did not relate to institutional commitment.

For the Polish sample, we found that M2 had a better fit than M1 (invariant model), but M3 did not. Hence, M2 (partially invariant) is the best model, and it also appeared to have the best practical fit indices on average (see **Table 4**). This means that the pattern and strength of relationships is not similar for younger and older Polish nurses (just as for the Dutch nurses). **Figure 4** shows the path coefficients of younger and older Polish nurses in M2. Contrary to the findings in the Dutch sample and in contradiction to Hypothesis 4, the relationships between the various types of demands, on the one hand, and disability and burnout, on the other hand, are stronger for the younger Polish nurses than for their older counterparts. In accordance with Hypothesis 5, we found the relationship between quality of interpersonal relationships and burnout to be stronger for older nurses, yet only in the synchronous paths. In case psychological support was the predictor, the cross-lagged paths indicated that older nurses benefit from more psychological support. In accordance with Hypothesis 6 (and the Dutch findings), influence at work was more important in the light of one's job satisfaction for older nurses synchronously. However, contrary to our expectations, meaning of work appeared to be more relevant for younger nurses in the prediction of job satisfaction (in line with the outcomes for their Dutch counterparts). In addition, for both young and old nurses, meaning of work was significantly and strongly related to institutional affective commitment (additional path). Hypothesis 6 was not confirmed for the cross-lagged paths. As regards Hypothesis 7, the results are a bit ambiguous: The synchronous path between opportunities for development and institutional affective commitment was stronger for older nurses (contrary to our expectations), while the cross-lagged path (over time) was stronger for younger nurses. For both younger and older Polish nurses, we found that the labor relations variables, that is, quality of interpersonal relationships and psychological support, were related to institutional commitment. So, for the Polish nurses, meaning of work and labor relations were more important in the light of institutional affective commitment than opportunities for development. **Table 5** provides a complete overview of the extent to which our hypotheses have been confirmed and the relationships that have been added.

# DISCUSSION

# Reflection Upon the Results

As the nursing profession comprises a highly demanding field, while at the same time suffering from a severe shortage of

TABLE 4 | Fit measures and chi-square difference tests of the nested models in the Multi-Group Analyses (young versus old) for the Netherlands and Poland.

\*p < 0.05. <sup>a</sup>All hypothesized and additional paths were specified as invariant for both young and old. <sup>b</sup>All hypothesized and additional paths were set free for both young and old. The path between psychological support and job satisfaction T0 and the paths between opportunities for development and institutional commitment T0 and T1 were specified as invariant. <sup>c</sup>All hypothesized and additional paths were set free for both young and old. <sup>d</sup>All hypothesized and additional paths were set free for both young and old. The paths between psychological support and job satisfaction/institutional commitment T0 and the path between influence at work and job satisfaction T1 specified as invariant.

workers, this study focused on the impact of work characteristics and nurses' experiences that were supposed to be of essential importance to maintain the sustainable employability of nurses throughout the life span. Four categories of work characteristics were taken into account – (1) working conditions, (2) labor relations, (3) work content, and (4) conditions of employment – and we examined their associations with nurses' health, satisfaction, and commitment.

From a theoretical point of view, our study builds on and elaborates the model of Houkes et al. (2001). Despite being coined almost 20 years ago, we contend that this model has yet to receive the empirical attention it deserves. In contrast to popular models, such as the model for Work, Stress, and Health (Kompier and Marcelissen, 1990; Kompier and Di Martino, 1995), the DCS model (Johnson and Hall, 1988; Karasek and Theorell, 1990), and the ERI model (Siegrist, 1996), the model of Houkes et al. (2001) allows for a further differentiation of demanding and resourceful job characteristics and for studying their unique impact on various aspects of employee functioning. Our results confirm the earlier findings of Houkes et al. (2001, 2003) in different samples and confirm that more accurate predictions regarding the relationships between a relevant range of work characteristics and outcome variables are possible. This allows for the refinement of well-known job design models and more concrete practical recommendations tailored to the problems at hand, as will be discussed below.

In addition, building upon SOC theory and SST, we investigated whether the pattern of relationships is different for younger (<40 years) versus older (≥40 years) nurses. As in previous scholarly work (see, for instance, Kuokkanen et al., 2003; Vahey et al., 2004), age is often included as a covariate or confounder. Our findings show that such practices may mask important differences in the relationships

TABLE 5 | Overview of confirmation of hypotheses tested (cross-sectional; cl = cross-lagged confirmation as well; ns = not significant).

between work characteristics and outcomes for different age groups and, hence, may limit our theoretical understanding of the impact of work across the life span and the practical recommendations that flow from it. An important contribution of this work is thus that it moves the empirical research on aging at work forward and sheds further light on how age should be taken into account in the job design literature (Schreurs et al., 2012).

A third contribution of this research is that we add to the domain of comparative career research (Thomas and Inkson, 2007), by investigating nurses who are working in Dutch and Polish healthcare institutions. Given the differences in outcomes between the two countries, we argue that the influence of economic, legal, and political characteristics of a society, in relation to the nursing field, should not be ignored by important stakeholders, as they do have an effect on attitudes, beliefs, perceptions, and expectations that people have about work characteristics and their outcomes (Thomas and Inkson, 200).

From our empirical model testing, we may conclude that for both the Dutch and the Polish nurses, our proposed pattern of relationships between work characteristics and outcome variables was generally supported, although we had to add several paths to achieve a better model fit for both countries' samples. These study results are in line with previous empirical studies among nurses that focused on one of the three outcome variables (e.g., Estryn-Behar et al., 2007; Toode et al., 2011; Van der Heijden et al., 2017; Li et al., 2018; Lu et al., 2019).

More specifically, as regards Hypothesis 1 and in line with Houkes et al. (2001), we found health (burnout) to be primarily predicted by working conditions (i.e., quantitative job demands) and labor relations (i.e., psychological support). Emotional demands [not included in the studies by Houkes et al. (2001)]

appeared to be unrelated to burnout among both Dutch and Polish nurses. It might be that this professional group is well able to deal with the emotional demands that are an integral and probably anticipated part of their work. The significant relationship between physical demands and disability (not studied by Houkes and colleagues) shows – in line with the Demand-Induced Strain Compensation (DISC) model by De Jonge et al. (2008) – that particular types of job demands relate to matching health outcomes, which may be an important addition to the model of Houkes et al. (2001).

Pertaining to Hypothesis 2, job satisfaction appeared to be related with work content (i.e., influence at work). The relationship between the other indicator of work content (i.e., meaning of work) appeared to be less relevant for nurses' job satisfaction in both countries. This may be due to the relatively high mean score and low variance on meaning of work in both countries, leading to ceiling effects: Meaning of work may be so salient for this professional group that a further increase in meaning of work does not lead to an increase in job satisfaction. Next to work content, labor relations (i.e., psychological support) also appeared to be an important predictor of job satisfaction in the current study. Job satisfaction is a broader motivational outcome than mere intrinsic motivation, which was the focus in the study of Houkes et al. (2001), which may explain why this additional relationship was found.

Finally, as regards Hypothesis 3, the relationship between conditions of employment (i.e., opportunities for development) and institutional affective commitment was significant for the Polish nurses but not for the Dutch ones. Interestingly, however, for both the Netherlands and Poland, we found meaning of work to be related to institutional affective commitment, and this relationship was even stronger than the relationship between conditions of employment and institutional affective commitment. Apparently, nurses may be committed to their work because they can perform meaningful work, and less so because of personal development goals. This stresses the importance of this factor in the light of protecting nurses from prematurely leaving the organization or even their profession as a whole.

Comparing the younger and older nurses (Hypotheses 4–7), we found ample support for our assumption that the hypothesized relationships might be impacted by age. In particular, age seemed to moderate the relationship between working conditions and health (Hypothesis 4), yet results were different in the Dutch compared to the Polish sample. In particular, in the Netherlands, physical demands are associated with older nurses' disability (synchronous analysis). Yet, as regards the analysis over time, it appears that only for the younger nurses, the higher the amount of physical demands, the higher their disability. Emotional demands go together with more burnout for the older nurses (synchronous analysis). Surprisingly, younger nurses experienced more health issues due to poor working conditions compared to older workers in Poland, but emotional and physical demands were more problematic for older workers in the Netherlands, although the latter could not be confirmed when considering the analyses over time. Such findings could be in line with theories on aging, but it is not easy to explain why these relationships differ across countries and were not stable across cross-sectional and longitudinal analysis. We therefore suggest taking into account multi-wave approaches to better disentangle these findings.

As regards the impact of age on the relationship between labor relations and health (Hypothesis 5), we found support for a stronger negative association between quality of interpersonal relationships and burnout for older nurses, yet only in Poland. For the Dutch nurses, psychological support appeared to prevent burnout and, in line with our expectations, indeed more so for the older ones.

We also found some support that age impacts on the relationship between work content and job satisfaction (Hypothesis 6). Across samples, influence at work was more strongly related to job satisfaction for older than for younger nurses. This indicates that older employees benefit relatively more from having a voice in the work context, while this is less relevant for younger workers. As regards meaning of work, it appeared that, in particular for younger nurses, this entails more job satisfaction.

Overall, across the Dutch and Polish samples, we found no impact of age on the relationship between conditions of employment and commitment in the hypothesized direction (Hypothesis 7).

## Limitations of the Study and Recommendations for Future Research

This study has some limitations. First, all data were collected using surveys, herewith opening the possibility of response set consistencies. Moreover, as we used self-report measures for both the predictor variables and the outcomes, a common-method bias may exist (Doty and Glick, 1998; Podsakoff et al., 2003). Another limitation comprises the possibility of chance capitalization, given the large amount of relationships tested. However, we have tried our utmost to prevent this by testing the model relationships simultaneously. Future research wherein data on both nurses' self-assessments and supervisors' assessments are gathered to compare their perceptions on the work characteristics might be interesting. In addition, as we focused specifically on nurses, our empirical findings are highly relevant for this particular professional group. Also, to increase generalizability across healthcare settings, nurses were sampled across hospitals, nursing homes, and home care institutions. Future research might be aimed at cross-validation at different professional settings and/or to other countries. In addition, personality characteristics may moderate the effect of work characteristics on health, job satisfaction, and organizational commitment. More scholarly work is needed, for instance, using the "Big Five" (Costa and McCrae, 1992) in order to gain more insight into possible moderating effects. It is also important to continue empirical work in this field to better understand the possible impact of age, using different cutoff points, such as 50 or 55 years of age [cf. Armstrong-Stassen and Schlosser (2008) who found that job development climate played an important role in the retention of workers older than 50 years old]. We also recommend future research incorporating different age

conceptualizations to shed more light on the possible role of age [see, for instance, the categorization by Sterns and Doverspike (1989) into chronological age, functional or performance-based age, psychosocial or subjective age, organizational age, and the concept of life span age]. Other factors that may have predictive validity in the light of nurses' health, satisfaction, and commitment, such as leadership style, work–family interference, rostering, shift work, positive and negative affectivity, effort– reward imbalance, to mention but a few appealing ones, should be taken into account in future empirical work as well.

Last but not least, we recommend expanding the impact of work characteristics on nurses' health, satisfaction, and commitment to patient-related outcome variables such as medical errors and patient experiences and satisfaction. It was the primary aim of this study to get more insight into specific determinants of employee well-being, but in the context of healthcare, it seems relevant to study the impact of these work characteristics on patient satisfaction as well.

### Implications for Practice

This study has increased our insights into the impact of work characteristics on key outcomes in the nursing profession. All in all, this empirical work indicates that managers in healthcare institutions have to pay careful attention to the working conditions, labor relations, and employment conditions in order to protect nurses' health, motivation, and career decisions. First, our results point out that depending on the most prevalent problems in their particular organization (health issues, motivational problems, or commitment issues), managers could focus on particular work characteristics. In general, our results point out that in the case of burnout, managers should primarily focus on lowering quantitative demands, for example, through preventing too-high levels of demands that are increasing nurses' workload, by reorganizing work, through job crafting (Parker et al., 2017b), or by increasing psychological support, for example, through encouraging and supporting fruitful interpersonal relationships on the work floor (Jungert et al., 2018). When satisfaction is low, the focus should furthermore be on increasing employee influence, for example, by enabling nurses to participate in decision-making and governance arrangements (Uchiyama et al., 2013). In general, the results thus indicate that managers have to protect their nurses from a too-high amount of quantitative, emotional, and physical demands and have to ensure that there is enough room for nurses' influence at the workplace. This study also stresses the importance of meaningful work, not only in the light of the added value for nurses' job satisfaction but, in particular, given its unexpected impact in the light of nurses' commitment. Managers in healthcare institutions can furthermore increase nurses' job satisfaction by providing ample psychological support. Psychological support is found to be important in the light of combatting burnout symptoms but also increases one's job satisfaction. Our findings support the importance of one's direct supervisor in the light of sustainable career theory (Van der Heijden and De Vos, 2015). Overall, nurses seem to have chosen their profession mainly because they want to do meaningful work and less so because of the opportunities for further development. Therefore, we argue that managers in healthcare organizations who want to foster passion at work and who supervise nurses for whom emotional demands and helping other people can even be a challenge instead of a burden (Bakker and Sanz-Vergel, 2013) should offer employees meaningful work and promote work valuation (Vallerand and Houlfort, 2003).

Second, apart from this generic advise, our results also clearly point to the importance of generating more in-depth understanding of the relationships between work characteristics and nurses' health, job satisfaction, and commitment in one's particular context, both in terms of the age of the staff and country. This implies that within each context, managers should allow for a thorough assessment of the work characteristics and functioning of their staff and the relations between them before considering particular interventions. Hence, we stress the importance of a non-normative, tailor-made approach to aging at work, herewith doing justice to idiosyncrasy (Van der Heijden and De Vos, 2015) in order to protect and further the career sustainability of all workers across the life span.

# CONCLUSION

To conclude, the results of this study can be translated into further clear recommendations for management in healthcare settings. Management should invest in the attractiveness of the profession and the quality of the practice environment aimed at the inclusion and retention of nurses across the life span. To improve nurses' health, satisfaction, and commitment, they should pay attention to the working conditions, labor relations, work content, and employment conditions.

# DATA AVAILABILITY STATEMENT

The datasets generated for this study are available on request to the corresponding author.

# ETHICS STATEMENT

The studies involving human participants were reviewed and approved by Ethics committee, University of Wuppertal. The patients/participants provided their written informed consent to participate in this study.

# AUTHOR CONTRIBUTIONS

BV, IH, and AV worked on design, modeling and analyses, and writing. KC worked on writing. All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

# FUNDING

The NEXT study was financed by the European Commission within the Fifth Framework, Project ID: QLK-6-CT-2001-00475.

### REFERENCES

fpsyg-11-00762 May 25, 2020 Time: 12:43 # 17

Swedish working population. Am. J. Public Health 78, 1336–1342. doi: 10.2105/ ajph.78.10.1336

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Van der Heijden, Houkes, Van den Broeck and Czabanowska. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# An Open Time Perspective and Social Support to Sustain in Healthcare Work: Results of a Two-Wave Complete Panel Study

Annet H. de Lange1,2,3,4 \*, Karen Pak2,5, Eghe Osagie<sup>2</sup> , Karen van Dam<sup>1</sup> , Marit Christensen<sup>3</sup> , Trude Furunes2,4, Lise Tevik Løvseth<sup>6</sup> and Sarah Detaille<sup>2</sup>

<sup>1</sup> Department Work and Organizational Psychology, Faculty of Psychology, Open University, Heerlen, Netherlands, <sup>2</sup> Human Resource Management, HAN University of Applied Sciences, Nijmegen, Netherlands, <sup>3</sup> Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway, <sup>4</sup> Norwegian School of Hotel Management, University of Stavanger, Stavanger, Norway, <sup>5</sup> Institute of Management Research, Radboud University Nijmegen, Nijmegen, Netherlands, <sup>6</sup> Department of Psychiatry, St. Olav's University Hospital, Trondheim, Norway

### Edited by:

Carlos María Alcover, Rey Juan Carlos University, Spain

### Reviewed by:

Gretchen A. Petery, Curtin University, Australia Marcello Nonnis, University of Cagliari, Italy

### \*Correspondence:

Annet H. de Lange<EMAIL_ADDRESS><EMAIL_ADDRESS>
### Specialty section:

This article was submitted to Organizational Psychology, a section of the journal Frontiers in Psychology

Received: 25 January 2020 Accepted: 18 May 2020 Published: 17 June 2020

### Citation:

de Lange AH, Pak K, Osagie E, van Dam K, Christensen M, Furunes T, Løvseth LT and Detaille S (2020) An Open Time Perspective and Social Support to Sustain in Healthcare Work: Results of a Two-Wave Complete Panel Study. Front. Psychol. 11:1308. doi: 10.3389/fpsyg.2020.01308 Based on lifespan developmental psychology and psychosocial work characteristics theory, we examined longitudinal relations between calendar age, occupational time perspective, different types of job demands and job resources in relation to sustainable employability (i.e., work ability, vitality and employability) among healthcare workers in Netherlands (N = 1478). Results of our two-wave complete panel study revealed satisfactory fit indices for the metric invariance of the included variables across the two waves (6-month time lag). Our results revealed a negative relation between calendar age and external employability of healthcare workers (limited support for hypothesis 1), and more consistent evidence for positive relations between an open future time perspective and across-time changes in vitality, work ability and external employability (supporting hypothesis 2). Few significant findings were found for relations between specific job demands or job resources and indicators of sustainable employability of healthcare workers (mixed results hypotheses 3 and 4). Our explorative tests of possible moderating effects of age or occupational time perspective in predicting relations between psychosocial work characteristics and indicators of sustainable employability revealed only a significant interaction effect of supervisor support and future time perspective in explaining across-time changes in external employability of healthcare workers (rejecting hypothesis 5 and confirming hypothesis 6). We discuss the practical as well as theoretical implications of these findings, and present recommendations for future research.

Keywords: future time perspective, longitudinal research, psychosocial work characteristics successful aging at work, sustainable employability, work ability

# INTRODUCTION

Within the healthcare sector in the Western society, various labor market trends have the potential to impact the quality of healthcare provided by available staff. One of the most important trends and developments among them are the graying, as well as dejuvenation of the available workforce, resulting in an overall decreasing number of healthcare staff (Herkes et al., 2019; Prins et al., 2019).

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Furthermore, a growing number of patients with health problems make use of the healthcare sector, implying increased numbers of patients and work pressure for the aging group of healthcare staff in coming years (Van Dam et al., 2017; Teoh et al., 2019). Consequently, work in healthcare is characterized by high levels of physical, emotional and mental demands, making the work quite taxing and stressful (Tomietto et al., 2019).

As a result, an increasing percentage of healthcare workers report serious mental health problems (Nonnis et al., 2017; Herkes et al., 2019) and find it more difficult to continue working in their profession until the official retirement age. Some of these healthcare workers decide to leave their job and transfer to another sector to find less demanding work (Boumans et al., 2008). While the need for healthcare workers increases, the number of workers is therefore likely to decline owing to the increased workload and decreased work ability of healthcare workers. This situation is urgent for healthcare organizations and society at large and it is imperative to identify factors that can facilitate the sustainable employability of healthcare workers to prolong their careers within healthcare (e.g., De Lange et al., 2015; Osagie et al., 2019).

Fortunately, a growing number of studies focuses on the antecedents of successful aging at work and sustainable employability to prolong working lives of workers in different sectors (e.g., De Lange et al., 2015; Kooij, 2015). Several definitions of successful aging have been presented in earlier research. For example, Zacher et al. (2018a) state that employees age successfully at work if they sustain the same level or deviate in increasingly positive ways from average developmental trajectories in subjective and objective work outcomes (i.e., work ability) across the working lifespan and maintain a person-job fit across time (Kooij, 2015; Zacher, 2015). More recently, De Lange et al. (2020) stated that successful aging refers to the fact that employees can pro-actively recover and improve over time through self-management, skills and actions, and with support or interventions from the work environment.

Considering new research on successful aging at work, De Lange et al. (2020) emphasize that more research can include the influence of individual difference variables that are related to aging, like an open future time perspective, to better explain developments in worker outcomes across time. This is in line with suggestions of Zacher et al. (2018a), who noted that the current body of research on successful aging at work has not yet examined the influence of individual difference variables like the experienced future time perspective in predicting sustainable employability of workers across time (Weigl et al., 2013; Baltes et al., 2014; Pak et al., 2018).

Furthermore, only a few studies on sustainable employability have been conducted in healthcare settings and no longitudinal study to date has been conducted on the influence of future time perspective in relation to sustainable employability of healthcare workers (Rudolph et al., 2018; Zacher et al., 2018a). Such insights are crucial to better understand the underlying mechanisms in successful aging and sustainable employability of healthcare workers. Increased insights in the influence of individual difference variables like time perspective will enable employers to stimulate successful aging more effectively and better intervene if necessary.

The current study is the first multi-wave study that aims to overcome the aforementioned research gaps by formulating and testing new theory-based hypotheses for relations between aging, time perspective and indicators of sustainable employability in healthcare work. As a result, the results of this new two-wave complete panel study can provide new insights into the question on how to better sustain aging workers in healthcare. Before we present the hypotheses of our study, we will first pay attention to the concepts and related theories addressing the topic of sustainable employability, the factor of time perspective and the influence of psychosocial work. We will start with describing the indicators of sustainable employability.

### Sustainable Employability: Vitality, Work Ability, and Employability Sustainable Employability

Several important aspects of sustainable employability have been distinguished by social partners (SER, 2009) and researchers (De Lange et al., 2015; De Vos and Van der Heijden, 2015; Semeijn et al., 2015; Van der Klink et al., 2016; Van Dam et al., 2017). These aspects include: (i) work ability (Ilmarinen, 2007), (ii) vitality (Schaufeli et al., 2006; Bakker and Demerouti, 2017), and (iii) employability (Fugate et al., 2004; Van der Heijde and Van der Heijden, 2006). These aspects of sustainable employability relate to human strengths, health, and motivation in organizations and are considered essential for employees to sustain their performance at work (Semeijn et al., 2015; Van Dam et al., 2017).

More specifically, work ability represents the health component of sustainable employability, and is defined as the extent to which one is physically and mentally able to keep performing one's job now and in the future (Ilmarinen et al., 2005; Ilmarinen, 2006, 2007; Van Vuuren, 2012). Furthermore, vitality represents the motivational component of sustainable employability and is characterized by high levels of energy and mental resilience while working, and the willingness to invest effort in one's work, and persist even in the face of difficulties (Schaufeli et al., 2006). Within the Job Demands-Resources model (JD-R), vitality is an important component of work engagement (Bakker and Demerouti, 2017; Bakker, 2018; Bakker et al., 2019).

Employability refers to the individuals' opportunity to retain or find work inside and outside of the current organization (Van Dam et al., 2017; Van der Heijde and Van der Heijden, 2006). Although the opportunity to retain or find work might depend on labor market characteristics, it is generally noted that individuals' characteristics, such as their abilities, skills, and knowledge, contribute to employability and labor market participation (Berntson et al., 2006; Semeijn et al., 2015).

### Sustainable Employability and Aging Healthcare Workers

Healthcare workers' sustainable employability is likely to decline when they age. Although individual differences may exist, the aging process of employees is generally accompanied by decreases in physical and mental capacities (Ilmarinen, 2006; Truxillo

et al., 2015; Van der Mark-Reeuwijk et al., 2019). As the work demands in healthcare will further increase in the future, healthcare workers may be faced with even more mental or physical health challenges and thus with lowered work ability. Similarly, vitality and employability may also diminish over time. Organizations are often inclined to provide older employees with fewer learning opportunities, job changes, and challenging task assignments compared to younger employees (Furunes and Mykletun, 2010; Truxillo et al., 2015). This might relate to some persistent stereotypes as well as the risk of self-stereotyping concerning older workers' learning motivation and capabilities, and their openness toward change (Kanfer and Ackerman, 2004; Ng and Feldman, 2012; Finkelstein et al., 2013). Therefore, older workers can find themselves stuck in repetitive jobs with little learning potential, which may undermine their employability and motivation (Truxillo et al., 2012; Van Dam et al., 2017). Moreover, older employees often perceive fewer labor market opportunities, which can lower their employability perceptions (Rothwell and Arnold, 2007).

Previous studies have indeed found negative relationships between calendar age and the three aspects of sustainable employability (see for example Ilmarinen, 2007; Monteiro et al., 2006; Van den Berg et al., 2009; Van Dam et al., 2017). For instance, Ilmarinen (2007) observed differences in the development of work ability in different age groups and different types of occupations. Studying workers in a public health institution, Monteiro et al. (2006) found that higher age, lower education (i.e., employability), and long work history in the organization were associated with reduced work ability. Van Dam et al. (2017) observed that older employees generally reported lower employability, while only those who had challenging and rewarding jobs reported similar employability levels as their younger colleagues. Similarly, Van Vuuren et al. (2011) found that work ability and employability generally declined with age, while this effect did not occur for those employees who were provided with ample opportunities for formal and informal learning (see also Van der Heijden et al., 2015). Based on these studies, we expect to find negative relations between calendar age and indicators of sustainable employability (i.e., vitality, work ability, and employability; Hypothesis 1). Another important individual difference variable is future time perspective.

# Socioemotional Selectivity Theory and Future Time Perspective: Concepts and Theory

Socioemotional Selectivity Theory (SST theory; Carstensen, 2019) describes the motivational consequences of a changing "temporal horizon" as people age. According to SST theory individuals will select goals in accordance with their perceptions of the future as being limited or open-ended (Lang and Carstensen, 2002). More specifically younger people perceive time as open-ended (holding a "time since birth" perspective) and will therefore be especially motivated by growth or knowledgerelated goals (new information or social interactions) that may be useful in their future. In contrast, older people perceive time as a constraint (holding a "time till death" perspective) and will be more motivated by achieving short-term emotion-related goals, such as deepening one's existing social relations. As such, future time perspective appears an important precursor of workers' goal striving and self-management at work and is therefore an important individual factor to consider in terms of successful aging and sustainable employability. Studies have found consistent negative associations between an open occupational future perspective and calendar age as well as positive associations with work outcomes like continuance work motivation (Lang and Carstensen, 2002; Schmitt et al., 2013; Rudolph et al., 2018). In short, the socioemotional selectivity theory has received empirical support in many experimental as well as field studies (Henry et al., 2017; Rudolph et al., 2018). The results of this body of research indicates that especially an open occupational time perspective is associated with indicators of sustainable employability. In this study we will test whether this hypothesis is true for healthcare workers. Moreover, we will test whether this association holds over time. That is, whether future time perspective can predict across-time changes in sustainable employability of healthcare workers (Hypothesis 2).

# Psychosocial Work Characteristics

Zacher et al. (2018b) stress the importance of paying attention to the pivotal role of psychosocial work characteristics in explaining developments in sustainable employability of aging workers across time (see also Truxillo et al., 2015). According to the Job Demands-Resources (JD-R) model (Bakker and Demerouti, 2017; Bakker, 2018) psychosocial work characteristics can best be measured by a combination of job demands and job resources. Job demands refer to "physical, psychological, social, or organizational aspects of the job that require sustained physical and/or psychological (cognitive and emotional) effort or skills and are therefore associated with certain physiological and/or psychological costs" (Bakker and Demerouti, 2017, p. 312). Examples of job demands are physical or mental demands or workload. Job resources are defined as the "physical, psychological, social, or organizational aspects of the job that are either/or functional in achieving work goals, reduce job demands and the associated physiological and psychological costs and stimulate personal growth, learning, and development" (Bakker and Demerouti, 2017, p. 312). Examples of job resources are pay, supervisor support, and autonomy. The JD-R model (Bakker and Demerouti, 2017; Vagharseyyedin, 2016; Bakker, 2018) suggests that job demands have a negative effect on employee outcomes as they trigger a health impairment process; having too much job demands deplete one's personal resources and lead to exhaustion. Job resources, on the other hand, have a positive effect on work outcomes as they trigger a motivational process (Bakker, 2018). More recently, Pak et al. (2018) also confirmed these findings in their systematic review of 110 empirical studies examining relations between job characteristics and indicators of sustainable employability. As a consequence, we expect to replicate these results in this new longitudinal study among healthcare workers, and hypothesize that job demands will have a significant negative relation with indicators of sustainable employability (Hypothesis 3), and job resources will have a

positive relation with indicators of sustainable employability (Hypothesis 4).

### Interaction Effects Age-Related Variables, Job Demands, Job Resources

Previous studies suggest that individual factors and contextual factors interact in determining work behavior and outcomes (Johns, 2006; Withagen et al., 2012). Therefore, it is possible that calendar age and occupational future time perspective, in addition to their direct impact, will moderate the relationships between the psychosocial work characteristics and indicators of sustainable employability (Zacher and Schmitt, 2016). Healthcare workers' age might be especially relevant for the impact of job demands. As workers age, their psychological and physical resources may decline while their ability to recover is reduced (Kiss et al., 2008; Truxillo et al., 2015). As such, the impact of high job demands will be larger for older workers than for younger workers. This will be especially true for healthcare professionals who are faced with high emotional and physical demands. Research provides general support for an interaction effect of age with work characteristics on workers' well-being, vitality, and employability (Zacher and Schmitt, 2016; Van Dam et al., 2017). Therefore, it is expected that the negative relationships of job demands with sustainable employability are stronger for older workers than for younger workers (Hypothesis 5).

Similarly, future occupational time perspective might moderate the relationships of job resources with sustainable employability, such that job resources will contribute more to sustainable employability for those healthcare workers with an open future time perspective (Hypothesis 6). This is in line with SST's claim that future time perspective is an important precursor of workers' goal striving and self-management at work. Only a few studies have focused on a possible moderating role of future time perspective. For instance, Schmitt et al. (2013) found that future time perspective moderated the relationship of autonomy with work engagement.

Summarizing, we will test the following hypotheses in this two-wave complete panel study among healthcare workers:

of sustainable employability of healthcare workers (i.e., vitality, employability, and work ability).

• Hypothesis 6: Future time perspective moderates the relations between job resources (i.e., autonomy, supervisor support, and colleague support) and indicators of sustainable employability of healthcare workers (i.e., vitality, employability, and work ability).

# MATERIALS AND METHODS

# Design of the Study and Procedure

This study is embedded in a larger research project among 25 healthcare institutions in Netherlands, referred to as "the Healthy Healthcare project" that emphasizes a systembased understanding of the interrelation between organizational structure, workers health and quality of patient care. Within this project, data was collected longitudinally using a questionnaire at T1 and T2 with a mean time lag of 6 months (i.e., a panel design). This length of time lag is in line with the recommendations of Dormann and Griffin (2015) of a relatively short time lags in survey research focusing on psychosocial work characteristics and worker outcomes. Moreover, a time lag of 6 months was considered appropriate as previous studies have demonstrated that the outcomes included in this study can fluctuate in rather short periods (De Lange et al., 2004; Zacher et al., 2014; Akkermans et al., 2019; Rudolph and McGonagle, 2019; Rudolph and Zacher, 2020). The first questionnaire (T1) was sent to the participants between November 2017 and the end of January 2018, the second questionnaire (T2) between June 2018 and the middle of August 2018.

## Sample

The 25 healthcare institutions included in this study mainly focused on elderly care, care for the disabled and home care, but also included facilities for addiction treatment, youth services, mental health care and home care. The final sample consists of the 1478 employees from these institutions who completed the questionnaire at both the first (T1; 2967 of 6866 employees, response rate = 39.3%) and the second measurement moment (T2; 2132 employees, follow-up response rate = 71,9%). Mage = 46.8 years (SD = 11.06 years), range = 18–58 years, with most respondents being female (84%, n = 1242), with fixed contracts (89.6%, n = 1325). Vocational education (37.8%, n = 558) and a bachelor's degree (35.7%; n = 527) were the most common education levels. 779 employees held a healthcare position (52.7%) with the remainder working in a leadership or support functions. Caregiver was the most common job category (15.1%), followed by leader (6.9%), nurse with a vocational degree (6.4%), and pedagogical employee (5.1%).

### Measures Work Ability

The Work Ability Index (WAI; Ilmarinen, 2006) was used to measure work ability. The WAI consists of seven constructs (60 items in total): i.e., (1) current work ability, (2) work ability in relation to the physical and mental demands of the job,

(3) current diseases, illnesses, and injuries, (4) limitations due to diseases, illnesses, and injuries, (5) sick leave, (6) future expectation of work ability, and (7) mental resources. Although work ability is measured as a multidimensional construct with the WAI, it is mainly employed as a unidimensional construct in most studies and in practice, and the healthcare practice in Netherlands in particular (see Osagie et al., 2019 for a review). So, for comparison and recognition reasons, we will also address it as a unidimensional construct in the current study. An example item from the WAI is "Assume that your work ability at its best has had a value of 10. How many points would you give your current work ability?" Scores on each dimension were summed, with a minimum score of 7 and a maximum score of 49. In our sample, work ability scores ranged from 14.5 to 49 at T1 and from 12 to 49 at T2 with a median of 42 at both time points.

### Vitality

Vitality was measured with three items of the shortened Utrecht Engagement Scale (Schaufeli et al., 2006). Items were measured on a six-point Likert scale ranging from 'never' (1) to 'daily' (6). An example item is "At my work, I feel bursting with energy."

### Internal and External Employability

Internal and external employability were measured with the eight items scale of De Cuyper and De Witte (2008) using a five-point Likert scale ranging from 'completely disagree' (1) to 'completely agree' (5). Four items covered internal employability (An example item: "I am able to get different jobs with my current employer") and four items covered external employability (An example item: "I would be able to find a different, equivalent job").

### Job Demands and Resources

Job demands were measured with four scales from the VBBA (Van Veldhoven and Meijman, 1994) at the first and second measurement moment. Physical demands were measured with three items (an example item: "Does your work require physical strength?") mental demands (an example item: "Do you have to work very precisely?") with four items, emotional demands with five items (an example item: "Is your work emotionally demanding?"), and workload with six items (an example item: "Do you need to rush at work?"). All items were measured on a four-point scale ranging from 'always' (1) to 'never' (4) and recoded in the opposite direction to facilitate interpretation.

### Job Resources

Job resources were measured with three scales of the VBBA (Van Veldhoven and Meijman, 1994) at the first and second measurement moment. Autonomy was measured with four items (an example item: "Can you organize your work yourself?"). Colleague support (an example item: "If necessary, can you ask your colleagues for help?") and supervisor support (an example item: "If necessary, can you ask your direct guidance for help?") were each measured with six items. All items were measured on a four-point scale ranging from 'always' (1) to 'never' (4) and recoded in the opposite direction to facilitate interpretation.

### Future Time Perspective

Occupational future time perspective was measured with a six item scale developed by Zacher and Frese (2009) which is an adaptation of the future time perspective scale of Carstensen and Lang (1996). An example item is 'Many opportunities await me in my occupational future.' Items were measured on a five-point Likert scale ranging from 'does not apply at all' (1) to 'applies completely' (5).

### Calendar Age

Age was measured at the first measurement moment as a continuous variable.

### Analyses

We conducted hierarchical regression analyses to test our hypotheses using M-Plus (version 8; see **Table 3** through 6) because we aimed to predict changes in sustainable employability through the selected individual factors and work characteristics and because our hypotheses were in part explorative (e.g., the interaction hypotheses) in nature (cf. Bollen and Pearl, 2013). In the first models the control variables (i.e., the outcome variables at the first measurement moment) were included. Next, because, as mentioned before, one's work behavior is influenced by both individual factors and contextual factors simultaneously (Johns, 2006; Withagen et al., 2012) we included both sets of variables (with workers' experiences of job demand and job resources as a proxy for contextual factors) in the second models. In the final models (the third model to be tested) the interaction terms of job demands with age, job demands with future time perspective, job resources with age and job resources with future time perspective were added. This allowed us to examine the effects of the predictors as they occur in practice, namely interrelated and simultaneously.

# RESULTS

To examine whether the different variables in this study captured different constructs, confirmatory factor analyses were conducted for the variables included in this study using M-Plus (version 8). In line with the recommendations of Hu and Bentler (1999) we used multiple fit indices, including the chi-square test (1χ 2 ), comparative fit index (CFI; Bentler, 1990), Tucker-Lewis Index (TLI; Tucker and Lewis, 1973), the root mean square error of approximation (RMSEA; Steiger and Lind, 1980) and the standardized root mean square residual index (SRMR; Hu and Bentler, 1995) to determine model fit. We compared the proposed 12-factor model at T1 (i.e., internal employability, external employability, vitality, work ability, emotional demands, mental demands, physical demands, workload, autonomy, supervisor support, colleague support, and future time perspective), with a nine factor model (i.e., Factor 1 = internal employability and external employability; Factor 2 = vitality and work ability; Factor 3 = emotional demands; Factor 4 = mental demands; Factor 5 = physical demands; Factor 6 = workload; Factor 7 = autonomy; Factor 8 = supervisor support and colleague support; Factor 9 = future time perspective) and a four factor model (i.e.,

Factor 1 = internal employability, external employability, vitality and work ability; Factor 2 = emotional demands, mental demands, physical demands, and workload; Factor 3 = autonomy, supervisor support, and colleague support; Factor 4 = future time perspective) and a one factor model.

We found that the 12-factor model (χ <sup>2</sup> = 3789.50, df = 1519, p < 0.001, CFI = 0.94, TLI = 0.94, RMSEA = 0.03, SRMR = 0.06) fit the data significantly better than the nine-factor model (1χ <sup>2</sup> = 3162.16, 1df = 30, p < 0.001), and the four-factor model (1χ <sup>2</sup> = 14796.52, 1df = 62, p < 0.001). The one factor model could not be converged. At the second measurement moment we compared the proposed 11 factor model (i.e., internal employability, external employability, vitality, work ability, emotional demands, mental demands, physical demands, workload, autonomy, supervisor support, and colleague support), with an eight factor model (i.e., Factor 1 = internal employability and external employability; Factor 2 = vitality and work ability; Factor 3 = emotional demands; Factor 4 = mental demands; Factor 5 = physical demands; Factor 6 = workload; Factor 7 = autonomy; Factor 8 = supervisor support and colleague support) and a three factor model (i.e., Factor 1 = internal employability, external employability, vitality and work ability; Factor 2 = emotional demands, mental demands, physical demands, and workload; Factor 3 = autonomy, supervisor support, and colleague support) and a one factor model. We found that the 11-factor model (χ <sup>2</sup> = 3281.47, df = 1219, p < 0.001, CFI = 0.91, TLI = 0.90, RMSEA = 0.03, SRMR = 0.06) fit the data significantly better than the eight-factor model (1χ <sup>2</sup> = 3160.879.15, 1df = 27, p < 0.001), the three-factor model (1χ <sup>2</sup> = 11377.53, 1df = 52, p < 0.001), and the one-factor model (1χ <sup>2</sup> = 15662.14, 1df = 55, p < 0.001). These results support the notion that our measures can be empirically distinguished.

Based on recommendations of Van de Schoot et al. (2012), the measurement invariance over time was examined for all outcome variables (**Table 1**). For vitality the requirements of configural measurement invariance were met. For employability and work ability the chi square test suggests measurement variance, however as the CFI and RMSEA test suggest invariance the requirement of configural invariance were met. The requirements for metric invariance are also met for vitality and work ability but not for employability. Next, scale scores were created for each of the variables to simplify the model. In **Table 2**, the correlations between the variables that are included in this study are shown as well as the Cronbach's alphas.