Beyond chronological age. Examining perceived ...

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Beyond chronological age. Examining perceived future time and subjective health as age-related mediators in relation to work-related motivations and well-being a

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c

Dorien T.A.M. Kooij , Annet H. de Lange , Paul G.W. Jansen & Josje S.E. Dikkers

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School of Social and Behavioral Sciences, Department of Human Resource Studies, Tilburg University, The Netherlands b

Faculty of Social Sciences, Department of Work and Organizational Psychology, Radboud University Nijmegen, The Netherlands c

Faculty of Economics and Business Administration, VU University Amsterdam, The Netherlands d

Human Resource Management, University of Applied Sciences Utrecht, The Netherlands Version of record first published: 15 Feb 2013.

To cite this article: Dorien T.A.M. Kooij , Annet H. de Lange , Paul G.W. Jansen & Josje S.E. Dikkers (2013): Beyond chronological age. Examining perceived future time and subjective health as age-related mediators in relation to work-related motivations and well-being, Work & Stress: An International Journal of Work, Health & Organisations, 27:1, 88-105 To link to this article: http://dx.doi.org/10.1080/02678373.2013.769328

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Work & Stress, 2013 Vol. 27, No. 1, 88105, http://dx.doi.org/10.1080/02678373.2013.769328

Beyond chronological age. Examining perceived future time and subjective health as age-related mediators in relation to work-related motivations and well-being Dorien T.A.M. Kooija*, Annet H. de Langeb, Paul G.W. Jansenc and Josje S.E. Dikkersd


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School of Social and Behavioral Sciences, Department of Human Resource Studies, Tilburg University, The Netherlands; bFaculty of Social Sciences, Department of Work and Organizational Psychology, Radboud University Nijmegen, The Netherlands; cFaculty of Economics and Business Administration, VU University Amsterdam, The Netherlands; dHuman Resource Management, University of Applied Sciences Utrecht, The Netherlands

Since workforces across the world are aging, researchers and organizations need more insight into how and why occupational well-being, together with work-related attitudes and motivations, change with age. Lifespan theories point to subjective health and future time perspective (i.e. an individual’s perceptions of his or her remaining time to live) as potentially relevant age-related variables. Using two Dutch samples, a health care company (N448) and university employees (N1271), we examined whether subjective health and future time, perceived as open-ended or limited, mediate the relation between age and work-related motivations (growth, security, esteem and generativity), and whether those motivations in turn influence work engagement. In line with lifespan theories, the study demonstrated that the relations of chronological age with work-related growth, esteem and security motivations were mediated by an open-ended future time perspective and a good subjective general health. The association between age and generativity motivations was not mediated by a limited future time perspective. Furthermore, growth, esteem and generativity motivations had a positive association with work engagement. These findings imply that the future time perspective and subjective health of older workers should be taken into account, and not just chronological age, when examining or managing their occupational well-being. Keywords: age; subjective health; future time perspective; work motivation; work engagement; occupational well-being

Introduction In the near future, workforces of many developed countries will increasingly consist of older workers (UN, 2007; Schalk et al., 2010). Therefore, studies focus increasingly on the impact of age on occupational health and well-being. For example, Nun˜ez (2010) examined the effect of increases in age on health problems that affect paid work. Furthermore, De Lange et al. (2006) examined how relations between work characteristics and occupational well-being changed with age-related factors. Warr *Corresponding author. Email: [email protected] # 2013 Taylor & Francis


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(1987) defined occupational well-being as the overall quality of an employee’s experience and functioning at work. Although Warr (1987) had already distinguished between four dimensions (i.e. affective well-being, aspiration, autonomy and competence) of occupational well-being, recently broader conceptualizations of occupational well-being have been proposed, including not only affect, but also behaviour and motivation (Van Horn, Taris, Schaufeli, & Schreurs, 2004; Maertens, Putter, Chen, Diehl, & Huang, 2012). Therefore, Van Horn et al. (2004) examined the structure of occupational wellbeing and found that it is a multidimensional concept, including affective (e.g. emotional exhaustion), professional (e.g. aspiration), social (e.g. quality of social functioning), cognitive (e.g. cognitive weariness), and psychosomatic (e.g. psychosomatic complaints) dimensions. In this study we examine two dimensions of occupational well-being; work motivations (i.e. professional dimension) and work engagement (i.e. affective dimension). Although work motivations and work engagement are both dimensions of occupational well-being, work engagement represents a worker attitude and is therefore included as an outcome of work motivations (see also Ryan & Deci, 2000; Ten Brummelhuis, Ter Hoeven, Bakker, & Peper, 2011). Few studies focus on how and why work motives or motivations change with age (Kanfer & Ackerman, 2004; Kooij, De Lange, Jansen, Kanfer, & Dikkers, 2011; Rhodes, 1983). Kooij et al. (2011) have recently revealed that motivations concerned with growth and development decrease with age, and that those concerned with various aspects of security at work increase with age. Earlier studies (e.g. Maehr & Kleiber, 1981; McAdams & De St. Aubin, 1992) suggested and found that with age there is a shift from competition and social comparison toward generativity (i.e. sharing knowledge and skills with younger generations) and affiliation. In this study we build on and extend earlier research on age and occupational well-being by examining processes that mediate the relationship between chronological age and growth, security, esteem and generativity work motivations, and in turn the association between these work motivations and work engagement. Griffiths (1997) suggested that ‘‘we should stop accepting chronological age as a factor in itself’’. Following this suggestion, Kanfer and Ackerman (2004) called for a theory of work motivation that incorporates age-related differences that go beyond chronological age. Similarly, Heckhausen, Wrosch, and Schulz (2010) argued that a motivational theory of lifespan development should take the constraints of biological maturation on individuals into account: ‘‘chronological age itself does not automatically propel progression through the timetable of development tasks’’ (Heckhausen, Wrosch, & Schulz, 2010, p. 37). In the same line of reasoning, several scholars (Kanfer & Ackerman, 2004; Ng & Feldman, 2008; Settersten & Mayer, 1997; Sterns & Doverspike, 1989; Zacher, Heusner, Schmitz, Zwierzanska, & Frese, 2010) have suggested that chronological age may only serve as a proxy for age-related processes that influence work motivation more directly. They argued that aging refers to gains, losses, reorganization and exchanges that occur in biological, psychological and social functioning over time. As such, aging may involve biological maturation, psychological development, membership in larger social categories (e.g. cohorts), or life stage (Settersten & Mayer, 1997). Because chronological aging is only one sub-process of this general process of aging, individuals with the same chronological age may differ in terms of job tenure, health, family status and the subjective meaning that age has for them (Cleveland &


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D.T.A.M. Kooij et al.

McFarlane Shore, 1992; Settersten & Mayer, 1997). Since these aging-related factors (also referred to as ‘‘age-related’’ factors or processes in this study) might influence work motivations in a different way (Kooij, De Lange, Jansen, & Dikkers, 2008), we will include multiple conceptualizations of aging in this paper. Lifespan theories i.e. Selection, Optimization and Compensation (SOC) theory (Baltes, Staudinger, & Lindenberger, 1999), and Socio-emotional Selectivity Theory (SST; Carstensen, 2006) point particularly to the importance of changes in biological potential and perceived time. In addition, Kooij and Van De Voorde (2011) found that changes in subjective general health and future time perspective influence generativity and development motivations. We will build on this research by investigating whether the relations between chronological age and development and generativity, and also security and esteem work motivations, are mediated by subjective general health and future time perspective (FTP; an individual’s perceptions of his or her remaining time to live; Carstensen, 1995; Lang & Carstensen, 2002) and by examining whether work motivations increase work engagement. We define work motivations as the (un)conscious importance that workers attach to job characteristics and work outcomes (based on the earlier work of Baard, Deci & Ryan, 2004; Dose, 1997; Kooij et al., 2011; Latham & Pinder, 2005; Sagie, Elizur, & Koslowsky, 1996). As such, motivations refer to preferred work characteristics and outcomes that an individual has explicit knowledge of, but also to non-conscious needs that influence preferences without explicit awareness (Baard et al., 2004). Further, based on categorizations in earlier studies (e.g. Barrick, Stewart, & Piotrowski, 2002; Kooij et al., 2011; Mor-Barak,1995; Ronen, 1994), we categorize work motivations into four theoretically meaningful categories: (1) Growth or development motivations, which refer to the perceived importance or preference for job characteristics and work outcomes that relate broadly to achievement and mastery (Dweck, 1999), such as motivations for challenging work; (2) Esteem motivations (or status striving, Barrick et al., 2002), which assess the importance or preference for job characteristics and work outcomes that relate to feelings of recognition, status, power and prestige; (3) Security motivations, which refer to the importance or preference for job features and work outcomes that satisfy or safeguard against loss of material and physiological desires related to one’s general welfare at work, such as pay, job security and physical working conditions; and, finally (4) Generativity motivations, which assess the importance or preference for job features and work outcomes that pertain to teaching, training and sharing skills with younger generations (Mor-Barak, 1995, see for more recent studies Zacher, Rosing, Henning, & Frese, 2011; Zacher, Schmitt, & Gielnik, 2012). We believe that this study contributes to existing knowledge in a number of ways. First, we build on Kanfer and Ackerman’s (2004) framework by testing pathways through which ‘‘dynamics of adult development’’ (p. 440; i.e. age-related factors) influence ‘‘input variables involved in motivational processes’’ (p. 441; i.e. work motivations). Second, we answer Ng and Feldman’s (2010) call for more research on age-related processes, in order to explain unique and additional variance in work motivations, by examining how subjective health and FTP underlie the association of chronological age with work motivations. Third, in line with Cozzolino, Sheldon, Schachtman, and Meyers (2009), we capture open-ended FTP and limited FTP as two distinct dimensions of FTP that differently mediate relations between work motivations and age (see also Cate & John, 2007; Kooij & Van de Voorde, 2011;

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Zacher & Frese, 2009). Finally, we examine the associations between two dimensions of occupational well-being; the professional (work motivations) and the affective (work engagement) dimension.

Subjective general health and future time perspective as mediators in the relation between age and occupational well-being


As discussed above, aging refers amongst other things to processes of gains and losses (Kanfer & Ackerman, 2004; Warr, 2001). Since lifespan theories of SOC (Baltes & Baltes, 1990; Baltes et al., 1999) and SST (Carstensen, 1995, 2006) explain how people cope with gains and losses over their lifespan, we will use these theories to hypothesize on the mediating effects of subjective health and FTP in the relation between chronological age and work motivations.

Selection, optimization and compensation theory. Several studies (e.g. Kooij et al., 2011; Rhodes, 1983) have revealed that growth motivations decrease and security motivations increase with age. According to SOC theory (Baltes & Baltes, 1990) the allocation by an individual of resources aimed at growth will decrease with age, whereas the allocation of those used for maintenance and regulation of loss will increase with age. This proposition is supported by Freund (2006), who found that goal focus shifts from emphasizing promotion in young adulthood to emphasizing maintenance and prevention of loss in later adulthood (see also, Ebner, Freund, & Baltes, 2006). SOC theory further argues that this shift in the allocation of resources is caused by a number of specific age-related losses in biological potential, such as fluid intelligence or physical abilities, that particularly occur among older workers (Baltes, 1997; Warr, 2001). Since aging is associated with losses in both physical and cognitive abilities (Baltes, 1997; Sliwinski & Hall, 1998; Maertens, et al., 2012; Verhaeghen, Steitz, Sliwinski, & Cerella, 2003), we focus on general health in this study. Furthermore, since individuals will only change their goal focus when they experience these losses affecting their health, we focus on self-perceived or subjective general health. Based on SOC theory, we argue that the age-related decrease in subjective general health causes the allocation of available resources to shift away from growth towards prevention or regulation of loss (Baltes, 1997). Older people perceive their general health to be worse than younger people and thus no longer focus on growth, but on prevention. In other words, subjective general health decreases with age, and results in decreased motivations concerned with growth and increased motivations concerned with security. Based on SOC theory and the aforementioned studies, we therefore expect that the negative impact of chronological age on growth motivations and the positive impact on security motivations run through subjective general health. This leads to the following hypotheses: Hypothesis 1: There will be a negative association between age and growth motivations and this will be mediated by subjective general health. Age will have a negative association with growth motivations through decreased subjective general health. Hypothesis 2: There will be a positive association between age and security motivations and this will be mediated by subjective general health. Age will have a positive association with security motivations through decreased subjective general health.


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Socio-emotional selectivity theory (SST). Several studies (e.g. De Lange, Van Yperen, Van der Heijden, & Bal, 2010; Kanfer & Ackerman, 2004; Maehr & Kleiber, 1981; Zacher et al., 2011; Zacher et al., 2012) have argued and found that esteem motivations decrease and generativity motivations increase with age. According to SST (Carstensen, 1995, 2006), age-related changes in the perception of (future) time (or future time perspective; FTP) explain these changes in social goals or motivations. Although Carstensen and colleagues treat FTP as a unidimensional and bipolar variable ranging from a limited to an expansive future (e.g. Lang & Carstensen, 2002), Cate and John (2007) demonstrated that FTP consists of two dimensions, limited and open-ended FTP, which change differently with age. They argued and found that middle age consists of psychological growth and of realizing limits, suggesting that individuals who perceive time as increasingly limited may not necessarily also perceive time as less full of opportunity. Similarly, Zacher and Frese (2009) introduced ‘‘remaining time’’ (i.e. expansive or open-ended FTP) as one dimension of occupational FTP, and Rabinovich, Morton, and Postmes (2010) and Cozzolino et al. (2009) distinguished between limited and open-ended time perspective. In line with these studies, and consistent with SST, we distinguish open-ended (similar to remaining time; Zacher & Frese, 2009) and limited FTP. SST argues that individuals who perceive their future as limited prioritize emotionally meaningful social goals, such as generativity, emotional intimacy and feelings of social embeddedness, whereas individuals who perceive their future as open-ended prioritize instrumental social goals, such as knowledge acquisition, autonomy, social acceptance and status attainment (Carstensen, Isaacowitz, & Charles, 1999; Lang & Carstensen, 2002; Treadway, Breland, Adams, Duke, & Williams, 2010). With chronological age, individuals approach the end of life, resulting in higher limited FTP and lower open-ended FTP (Kooij & Van de Voorde, 2011), and thus in less instrumental goals and more emotionally satisfying goals (Zacher, Degner, Seevaldt, Frese, & Lu¨ dde, (2009). Thus, an age-related decrease in open-ended FTP results in a decrease in social motivations to gain resources, such as knowledge and social acceptance (i.e. growth and esteem motivations). Older people perceive their future time as less open-ended than younger people and thus no longer prioritize instrumental social goals. In contrast, an age-related increase in limited FTP results in an increase in social motivations to obtain affective rewards: such motivations are generativity and social embeddedness (i.e. generativity motivations). As older people perceive their future time as more limited than younger people, they give higher priority to emotionally meaningful social interactions and goals (see Lang & Carstensen, 2002). In other words, open-ended FTP decreases with age, which in turn results in decreased growth and esteem motivations, and limited FTP increases with age, which in turn results in increased generativity motivations. As such, age indirectly influences growth, esteem and generativity motivations, through open-ended and limited FTP. This leads to the following hypotheses: Hypothesis 3: There will be a negative association between age and growth motivations and it will be mediated by open-ended FTP. Age will have a negative association with growth motivations through decreased open-ended FTP. Hypothesis 4: There will be a negative association between age and esteem motivations that will be mediated by open-ended FTP. Age will have a negative association with esteem motivations through decreased open-ended FTP.

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Hypothesis 5: There will be a positive association between age and generativity motivations that will be mediated by limited FTP. Age will have a positive association with generativity motivations through increased limited FTP.


Occupational well-being: Associations between work motivations and work engagement Work engagement is a positive work-related state of mind that is characterized by vigour, dedication and absorption. Vigour is characterized by high levels of energy, the willingness to put effort in the job and to persist when confronted with difficulties, dedication is characterized by a sense of significance, pride and enthusiasm, and absorption is characterized by being fully concentrated and focused on the job (Schaufeli & Bakker, 2004). Schaufeli, Taris, and Van Rhenen (2008) found that work engagement is a conceptually and empirically distinct dimension of employee well-being. Similarly, Van Horn et al. (2004) examined the structure of occupational well-being. They tested a model including five dimensions of occupational well-being (i.e. affective, professional, social, cognitive and psychosomatic), and found that a five-factor oblique model (in which the factors are correlated) fitted the data best. Therefore, we hypothesize that work motivations (i.e. aspirational or professional dimension of occupational well-being) and work engagement (i.e. affective dimension of occupational well-being) are positively associated. Hypothesis 6: Work motivations will be positively associated with work engagement.

Method Participants Data for this quantitative study were collected through a survey in two samples; (1) among employees of a Dutch health care company and (2) among employees of a Dutch university (see also Kooij & Van De Voorde, 2011). The two samples were relatively diverse, thereby enhancing the generalizability of our findings to a broader population. Study 1. A questionnaire was distributed among the 2159 health care employees in January 2008, resulting in 448 respondents (a response rate of 22%). After listwise deletion, the sample consisted of 385 respondents without missing values on the central research variables. These respondents were mostly female (89%), working part time (81%), with an average company tenure of 10.5 years (SD7.0), an average job tenure of 8.2 years (SD7.5), and an average age of 45.7 years (SD 9.6). Fortytwo per cent had a bachelor degree or higher. Respondents did not differ from all employees within the health care company in terms of gender (89% female), but were older (mean age 45.7) compared to all employees (mean age 41), which is more often the case in studies on aging at work (e.g. Elovainio et al., 2005). Study 2. In March 2008 a similar questionnaire was distributed among 3812 university employees, resulting in 1429 respondents (a response rate of 37.5%). After listwise deletion the sample of university employees consisted of 1169 respondents

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without missing values on the central research variables. About half of these respondents were female workers (52%), working full time (51%), with an average company tenure of 10.3 years (SD9.8), an average job tenure of 5.8 years (SD 7.0), and an average age of 42.5 years (SD11.6). Eighty-four per cent had a bachelor degree or higher and 42% was considered scientific staff. Compared to the sample of health care workers, this sample was younger (F (1, 1551) 22.79, pB .001), more highly educated (F (1, 1552) 331.17, pB.001), had a lower job tenure (F (1, 1552 33.59, pB.001), and consisted of more male workers (F (1, 1552) 187.45, p B.001), and more full-time workers (F (1, 1552) 131.32, pB.001).


Measures Chronological age. Chronological age was operationalized as calendar age, ranging from 16 to 64 among health care workers and from 19 to 67 among university workers. Subjective general health. Subjective general health was measured with a single item construed by Kristensen, Hannerz, Høgh, and Borg (2005) that asked respondents to rate their general health (see also Elovainio et al., 2005; Freund & Baltes, 1998). Participants could respond on a five-point scale (1 poor, 2 average, 3 good, 4 very good or 5 excellent). Open-ended and limited future time perspective. Open-ended and limited future time perspectives were measured with five items of the Future Time Perspective Scale (Carstensen & Lang, 1996) with answer alternatives ranging from strongly disagree (1) to strongly agree (5). Consistent with Cate and John (2007), Cozzolino et al. (2009) and Rabinovich et al. (2010), two dimensions of FTP were distinguished, open-ended FTP (‘‘Most of my life still lies ahead of me’’, ‘‘My future seems infinite to me’’ and ‘‘Many opportunities await me in the future’’, a .76 among health care employees/a .77 among university employees) and limited FTP (‘‘I have the sense that time is running out’’ and ‘‘As I get older, I begin to experience time as limited’’, a .81/a .80). A confirmatory factor analysis (CFA; Jo¨ reskog & So¨ rbom, 1996) revealed that the two-factor model (x2 6.34 (4), Goodness of Fit Index (GFI) .99, Comparative Fit Index (CFI) 1.0, Root Mean Square Error of Approximation (RMSEA) .04, health care employees/x2 29.28 (4), GFI .99, CFI.99, RMSEA .07, university employees) fitted the data significantly better than the one-factor model (x2 154.33 (5), GFI .86, CFI.75, RMSEA .28; Dx2 (1) 147.99, pB.001/x2 452.53 (5), GFI .86, CFI .77, RMSEA .28; Dx2 (1) 422.95, p B.001). Work motivations. Based on Mor-Barak (1995), Ronen (1994), Porter (1961), and Warr, Cook, and Wall (1979), work motivations were measured with 12 items that asked participants to indicate the importance they attached to certain job features or work outcomes that can be part of a job. Answer alternatives ranged from totally not important (1) to very important (7). Our pre-specified ideas about which motivations would involve which category of motivations was confirmed by a CFA, which revealed that this four-factor model fits the data significantly better (x2 159.35 (48), GFI .94, CFI.94, RMSEA .08, health care employees; x2 280.88 (48),

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GFI .96, CFI .95, RMSEA.06, university employees) than a one-factor model (x2 851.22 (54), GFI .71, CFI .60, RMSEA.20; Dx2 (6) 691.87, pB .001/x2 2332.74 (54), GFI .74, CFI.50, RMSEA.19; Dx2 (6) 2051.86, pB.001). Growth motivations consist of ‘‘fully using my skills and abilities’’, ‘‘challenging work’’ and ‘‘the opportunity for personal growth and development’’ (a .79/.73); security motivations consist of ‘‘job security’’, ‘‘good physical working conditions’’ and ‘‘good benefits’’ (a .80/.73); esteem motivations consist of ‘‘prestige and status outside the company’’, ‘‘prestige and status inside the company’’ and ‘‘possibilities for promotion’’ (a.78/.76); and generativity motivations consist of ‘‘the opportunity to share my skills with younger people’’, ‘‘the chance to teach and train others’’ and ‘‘pass my knowledge to the next generation’’ (a .85/.79). Work engagement. Work engagement was measured with the shortened version of the Utrect Work Engagement Scale (UWES; Schaufeli, Bakker, & Salanova, 2006). The UWES measures three dimensions of work engagement each with three items: Vigour (e.g. ‘‘I am bursting with energy in my work’’), dedication (e.g. ‘‘My job inspires me’’) and absorption (e.g. ‘‘I feel happy when I am engrossed in my work’’). Previous studies have shown that the three dimensions are highly correlated and that it is therefore justified to use work engagement as a one-dimensional construct (Seppa¨ la¨ et al., 2009). Participants responded on a seven-point scale ranging from never (1) to every day (7). The reliability in both samples was respectively .92 and .91. Control variables. Control variables included gender (0 female, 1 male), management position (0 no, 1 yes), educational level (ranging from (1) a basic education to (5) a university degree), and employment contract (0 part time, 1 full time). We only kept significant control variables in our models.

Statistical analyses We performed structural equation modelling using Amos 18 (Arbuckle, 2006) to test Hypotheses 1 to 6. Considering the proportion of items to the number of participants, we decided to include the validated FTP, motivations and work engagement scores as manifest variables rather than as latent variables in our model in order to maintain a favourable indicator-to-sample size ratio. A structural model was specified in which age influences subjective health, open-ended FTP, and limited FTP, in which subjective health influences growth and security motivations, openended FTP influences growth and esteem motivations, and limited FTP influences generativity motivations, and in which work motivations influence work engagement. We included paths from the control variables to the work motivations and work engagement, and allowed the measurement errors of subjective health, open-ended FTP, and limited FTP, and the measurement errors of the work motivations to covary with each other. Based on Bollen and Long (1993), Byrne (2001), and Hu and Bentler (1998) we used four fit indices; CFI, Normed Fit Index (NFI), GFI (which all three should be close to .95), and RMSEA (which should be close to .06). To test the mediating effects, we followed MacKinnon, Fairchild, and Fritz (2007) and Preacher and Hayes (2004), who proposed that two conditions must be met to establish mediation: (1) the independent variable (i.e. age) is significantly related to the mediator (e.g. limited FTP); and (2) the mediator is significantly related to the

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dependent variable (e.g. generativity motivations). Additionally, we used the bootstrapping method to test the significance of the indirect effect. Based on Shrout and Bolger (2002), Zacher et al. (2010) explain that this method estimates the sampling distribution of the indirect effect by repeatedly drawing random samples with replacement from the original data, providing bootstrapped confidence intervals to test the indirect effect for significance. We conducted the bootstrap analyses in Amos 18 as described by Cheung and Lau (2008) and Shrout and Bolger (2002, Appendix B). Finally, since age can have an indirect effect on growth motivations through both subjective health and open-ended FTP, we used an SPSS macro by Preacher and Hayes (2008) to test the specific indirect effects of age on growth motivations through respectively subjective health and open-ended FTP.

Results Descriptive results Means, standard deviations, and correlations of the key variables are reported in Table 1. The two samples differed significantly on all key variables, except growth motivations. As can be seen in Table 1, health care workers were older than university workers (F (1, 1552) 22.79, pB.001). Further, health care workers felt less healthy (F (1, 1552) 4.80, pB.05), and had a lower open-ended FTP (F (1, 1552) 17.19, pB.001), but also a lower limited FTP (F (1, 1552) 7.45, pB.01) than university workers. With respect to the work motivations and engagement, health care workers had lower esteem motivations (F (1, 1552) 21.03, pB.001), but higher security (F (1, 1552) 145.41, pB.001) and generativity motivations (F (1, 1552) 19.69, pB.001) and work engagement (F (1, 1552) 31.11, pB.001) than university workers.

Model fit The finally fitted structural model is shown in Figure 1. The proposed full mediation model fitted well in both the health care and university sample (x2 93.61/147.45, df 37/34, GFI .97/.98, NFI .91/.95, CFI .94/.96, RMSEA.06/.05 for the two samples respectively). To evaluate whether the full mediation model obtained a better fit than a partial mediation model, we constructed a model with direct paths from chronological age to the work motivations. This partial mediation model obtained good fit (x2 78.19/ 106.86, df 33/30, GFI .97/.99, NFI .92/.96, CFI .95/.97, RMSEA .06/.05) and even a significantly better fit than the full mediation model (D x2 (4) 15.42, p B.01/D x2 (4) 40.59, pB.001). However, only the path from chronological age to security motivations was significant in the university sample, and the path from chronological age to generativity motivations was significant in both samples.

Hypotheses testing Contrary to Hypothesis 1, age was not found to be related to subjective general health, and subjective health was not related to growth motivations among health care workers. In line with Hypothesis 1, however, we found that age was negatively

Means, standard deviations (SD), and correlations of key variables. Mean

Mean SD 1. Age 2. Subjective health 3. Open-ended FTP 4. Limited FTP 5. Growth motivations 6. Security motivations 7. Esteem motivations 8. Generativity motivations 9. Work engagement

45.7 3.3 2.9 2.1 5.8 5.7 3.6 5.2 5.8

SD

1

2

3

4

5

6

7

8

9

9.6 .8 .9 1.1 .9 1.0 1.3 1.2 1.1

42.5 11.6 .02 .58*** .35*** .16** .01 .08 .15** .03

3.4 .8 .09** .13* .12* .02 .19*** .03 .04 .17**

3.1 .9 .67*** .17*** .43*** .32*** .08 .25*** .05 .21***

2.3 1.1 .31*** .18*** .45*** .04 .07 .03 .05 .10

5.9 .80 .14*** .14*** .22*** .10** .29*** .40*** .49*** .27***

5.0 1.0 .07* .07* .04 .05 .11*** .33*** .42*** .14**

3.9 1.1 .08** .09** .14*** .03 .33*** .23*** .38*** .26***

4.9 1.1 .20*** .06* .03 .04 .39*** .22*** .31*** .27***

5.5 1.0 .06 .23*** .12*** .16*** .33*** .03 .21*** .33***

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Table 1.

Note: Sample of health care employees (N 385) below diagonal and sample of university employees (N 1169) above diagonal. FTP future time perspective. *pB.05; **pB.0; ***pB.001.

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D.T.A.M. Kooij et al. –.02/.06*

Subjective health

–.09*/–.08** –.58***/–.67***

Security motivations .03/–.10***

Open-ended FTP .20***/.17***

.35***/.31***

.09/.21***

.28***/.21***

–.02/–.09**

Age

Growth motivations

Esteem motivations

Work engagement

.13*/.09**

Limited FTP .16*/.20*** –.02/–.02

Generativity motivations


Figure 1. Standardized effects for the hypothesized model. Health care employees: N 448. University employees, N 1271. Note: *p B.05; **p B.01; ***p B.001.

related to subjective general health (b.09, p B.01), and subjective general health was positively related to growth motivations among university workers (b .06, pB .05). Furthermore, analyses to test for specific indirect effects confirmed a significant indirect effect of chronological age on growth motivations through subjective general health (standardized effect .01, p B.05). Thus, Hypothesis 1 was supported for university workers. Contrary to Hypothesis 2, age was not related to subjective general health among health care workers. In line with Hypothesis 2, however, we found that subjective health was negatively related to security motivations among health care workers as expected (b .09, p B.05). Further in line with Hypothesis 2, we found that age was negatively related to subjective general health (b.09, pB.01), and subjective general health was negatively related to security motivations among university workers (b.08, p B.01). Furthermore, bootstrap analyses confirmed a significant indirect effect of chronological age on security motivations through subjective general health (standardized effect.01, pB.01). Thus, Hypothesis 2 was supported for university workers. In line with Hypothesis 3 we found that age was negatively related to open-ended FTP in both samples (b.58, pB.001/b .67, p B.001), and that open-ended FTP was positively related to growth motivations in both samples (b.28, pB.001/b.21, p B.001). Furthermore, analyses to test for specific indirect effects confirmed a significant indirect effect of chronological age on growth motivations through open-ended FTP (standardized effect .19, p B.01/ .12, pB.01). Thus, Hypothesis 3 was supported. In line with Hypothesis 4 we found that age was negatively related to open-ended FTP in both samples (b .58, p B.001/b.67, pB.001), and that open-ended FTP was positively related to esteem motivations in both samples (b.20, pB.001/b .17, pB.001). Furthermore, bootstrap analyses confirmed a significant indirect effect of chronological age on esteem motivations through open-ended FTP (standardized effect 0.12, pB.01/.11, p B.01). Thus, Hypothesis 4 was supported. In line with Hypothesis 5, we found that age was positively related to limited FTP in both samples (b.35, pB.001/b .31, p B.001). However, limited FTP was unrelated to generativity motivations in both samples. Thus, Hypothesis 5 was not supported. Finally, in line with Hypothesis 6, we found that esteem and generativity motivations were positively related to work engagement in both samples (b.13,

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pB.05; b.16, p B.05/b.09, pB.01; b.20, p B.001), but that growth motivations were only positively related to work engagement in the university sample (b.21, pB.001). Contrary to our hypothesis, security motivations were unrelated to work engagement in the health care sample and negatively related to work engagement in the university sample (b .10, pB.001).


Discussion As few earlier studies have addressed the influence of age-related process variables such as time perspective and subjective general health in relations between chronological age and work motivations, this two-sample survey study aimed to fill this research gap and develop and test new theory-based hypotheses. In line with our hypotheses, we found in two very different samples that the negative relations between age and growth and esteem motivations were mediated by open-ended FTP. As proposed by Socio-emotional Selectivity Theory (SST), growth and esteem motivations decrease with age because of an age-related decrease in open-ended FTP. Because older workers see their future as less open, their motivation for social interaction shifts away from knowledge acquisition and status attainment. Contrary to our hypothesis based on SST, we did not find that the relation between age and generativity motivations was mediated by limited FTP. Thus, generativity motivations increased with chronological age, but not with limited FTP. It might be that chronological age is a better proxy for limited FTP at work, because in the Netherlands chronological age determines when workers are legally obliged to retire (i.e. at age 65). Further, we found that subjective general health mediated the negative association between age and growth motivations and the positive association between age and security motivations among university workers. As proposed by SOC theory, growth motivations decrease and security motivations increase with age, because of age-related biological constraints. Since older workers experience losses in subjective general health, they will shift their resources away from growth and towards maintenance and regulation of loss. However, contrary to SOC theory we did not find that subjective general health mediates the negative relation between age and growth motivations and the positive relation between age and security motivations in the sample of health care workers. Chronological age and subjective general health were unrelated in this sample. Possibly biological constraints are caused by job position here; a job consisting of physically demanding tasks might cause biological constraints irrespective of age. In addition, we did not find that growth motivations decreased with losses in subjective general health. Since health care work is a rather physically and psychologically demanding profession, it might be that health care workers experiencing a deterioration in their subjective health try to advance to higher and physically less demanding job positions which might offset the tendency to reduce resource allocation towards growth motivations. Armstrong-Stassen (2005) indeed found that ‘‘providing reassignment to less physically demanding jobs’’ was important in older nurses’ decision to remain in the workforce. Finally, as expected, we found that esteem and generativity motivations were positively related to work engagement. However, although growth motivations were positively related to work engagement among university employees, they were

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unrelated to work engagement among health care workers. A possible explanation for this finding is that there are too few opportunities for advancement in the health care organization. Also contrary to our expectation, security motivations were unrelated to work engagement among health care workers, and negatively related to work engagement among university employees. It could be that the university and health care organizations did not provide their workers with enough job security and good physical working conditions.


Theoretical contributions With this study we have contributed to lifespan theories, and the literature on aging at work. First of all, our results extend the literature on lifespan theories of SOC (Baltes & Baltes, 1990; Baltes et al., 1999) and SST (Carstensen, 1995) by investigating their implications in different work contexts. As proposed by SOC and SST theories, we found that particularly subjective health and open-ended FTP were important aging-related factors causing work motivations to change with age. Furthermore, our findings support the distinction between open-ended and limited FTP, because they have different effects on work motivations; we found that whereas open-ended FTP mediated the relation between age and growth and esteem motivations, limited FTP did not influence work motivations. SST seems thus partly applicable to the work context; as proposed by the theory, younger workers with a more open-ended FTP have higher growth and esteem motivations than older workers with a less expansive FTP, and older workers have higher generativity motivations than younger workers, but contrary to the theory this age-related change in generativity motivations is not due to a change in limited FTP. Future research should examine other aging-related factors influencing generativity motivations. Moreover, our results indicate that SOC theory works differently in different sectors or types of jobs; although we found full support for our hypotheses based on SOC theory among university workers, we found no support for these hypotheses among health care workers. This indicates that SOC theory might need to be adapted to fit sectors or types of job that involve physically demanding work. Here, older workers might keep allocating resources toward growth to advance to less demanding jobs, such as team leader. Secondly, this study has implications for the literature on aging at work by examining the influence of different conceptualizations of age on work motivation. Subjective general health and open-ended FTP influence work motivation beyond chronological age, and theories on work motivation incorporating age should thus include subjective health and open-ended FTP as mediators in associations of chronological age with work motivations. Finally, this study has implications for the literature on occupational well-being, and extends earlier research (e.g. Van Horn et al., 2004) that demonstrated that work motivations and work engagement are both dimensions of occupational well-being, by examining different types of work motivations. To summarize, our findings suggest that not all work motivations can be considered as a dimension of occupational well-being, and that this might also differ according to the context. Future research could build on these preliminary findings to increase our understanding of work motivations as a professional (i.e. an aspirational) dimension of occupational well-being.

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Practical implications


This study has important practical implications. Since chronological age is merely one aging-related factor that can influence worker outcomes directly or indirectly, we believe that organizations should stop using this factor as primary determinate of particularly HR practices that accommodate or reduce workloads of workers as they grow older. Given that other aging-related factors, such as subjective health and FTP, might have different effects on work motivations, organizations should also take these aging-related factors into account. In contrast to chronological age, subjective health and FTP can be affected by organizations (Griffiths, 1997). For example, organizations could aim to lengthen older workers’ time perspective by specifically outlining their future within the company (see also, Carstensen et al., 1999), thereby increasing their occupational well-being.

Limitations and future research Despite the theoretical and practical implications of the findings of our study with two very different samples, we need to recognize some important limitations. Firstly, the study is cross-sectional, and therefore it is difficult to disentangle the age differences found in this study from so-called ‘‘cohort’’ effects; the result of common experiences characteristic of a particular historical period in which workers were born (Kanfer & Ackerman, 2004). Also, we cannot draw conclusions about causality (De Lange, Taris, Kompier, Houtman, & Bongers, 2003). Although age is a causal variable (i.e. it cannot be influenced by other variables), and we therefore expect that the aging-related factors influence work motivations, it might be that work motivations have a reversed effect on future time perspective, for example. According to the broaden-and-build theory of Fredrickson (2001), positive emotions such as increased work motivation can build enduring psychological resources and trigger upward spirals in which motivated workers can further improve their own situation and may therefore create a more open time perspective. Furthermore, the data were collected from a single source (i.e. employees) using self-reporting, which might lead to common method bias (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). However, since this study focuses on employees’ perceptions of aging and their work motivations and engagement, it is not feasible to obtain measures of these constructs from alternative sources. Another limitation is how we measured the aging-related factors. We used a single-item scale to measure subjective general health. Although earlier research has demonstrated the validity of this scale (Van Hooff, Geurts, Kompier, & Taris, 2007), single-item scales might have some disadvantages (e.g. low reliability). Since we lack measurement instruments that can be used to measure the various conceptualizations of age (Kooij et al., 2008), future research should develop a measurement tool to measure all indicators of aging at work. Finally, we measured general agingrelated factors instead of aging at work. For example, we included general FTP, whereas occupational FTP (Zacher et al., 2010; Zacher & Frese, 2011) might have been more appropriate.

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Conclusion This study has shown that it is important to look beyond chronological age and include meaningful age-related process variables such as future time perspective and subjective general health in order to further understand the relations between aging and occupational well-being.


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