Integrating Work Ability into the Organizational Science Literature: Advancing Theory and Developing the Nomological Network

i List of Tables . iv List of Figures . v Chapter 1: Introduction . 1 Chapter 2: Opening the Black Box: Examining the Nomological Network of Work Ability and Its Role in Organizational Research . 12 Chapter 3: Age Discrimination and Job Outcomes: The Mediating Role of Perceived Work Ability and Fit . 86 Chapter 4: Linking Perceived Work Ability to Supervisor-Rated Job Performance . 123 Chapter 5: General Discussion.145 References . 155 Appendix Study Level Results from Meta-Analysis . 209 WORK ABILITY, AGE DISCRIMINATION, PERFORMANCE iv List of Tables Table 1 Random-Effects Meta-Analytic Estimates of the Relationships between Work Ability and Its Theoretical Antecedents.72 Table 2 Random-Effects Meta-Analytic Estimates of the Relationships between Work Ability and its Theoretical Outcomes.74 Table 3 Mixed-Effects Meta-Analytic Estimates of the Relationships Between WA and its Antecedents (by WA Measure). 75 Table 4 Mixed-Effects Meta-Analytic Estimates of the Relationships Between WA and its Outcomes (by WA Measure). 78 Table 5 Mixed-Effects Meta-Analytic Estimates of the Relationships Between WA and its Antecedents and Outcomes (by Occupation). 79 Table 6 Mixed-Effects Meta-Analytic Estimates of the Relationships Between WA and Its Antecedents and Outcomes (by Occupation). 82 Table 7 Zero-Order Correlations among Study 2 Variables.83 Table 8 Sequential Multiple Regression Models Examining Incremental Variance Explained by Perceived WA in Relation to Correlates over and above Perceived Fit, General Self-Efficacy, and Job Self-Efficacy.85 Table 9 Study 2 Sample Descriptive Statistics.120 Table 10 Means, Standard Deviations, and Zero-Order correlations among Study 2 Variables.122 Table 11 Means, Standard Deviations, and Zero Order Correlations among Study 3 Variables.142 WORK ABILITY, AGE DISCRIMINATION, PERFORMANCE v List of Figures Figure 1 Theoretical Model of Work Ability.70 Figure 2 Results Study 1A.71 Figure 3 Study 2 Conceptual Model.119 Figure 4 Study 2 Results.121 Figure 5 Study 3 Results.143 Figure 6 Study 3 Moderation Plot.144 WORK ABILITY, AGE DISCRIMINATION, PERFORMANCE 1 Chapter 1: Introduction Older workers are a growing portion of the population, and this trend is expected to continue for the foreseeable future (Toossi, 2015; U.S. Census Bureau, 2019). As the workforce continues to age, workforce participation is also expected to continue decreasing to an estimated 61% by 2026 in the United States (U.S. Bureau of Labor Statistics, 2017). This is problematic because retirement systems and other social safety programs rely on funds from the active workforce. However, lower workforce participation likely means fewer available funds, but a larger pool of people pulling from those funds. Additionally, the loss of human capital may cause labor shortages and cause organizations to lose important institutional knowledge (e.g. “the brain drain”; Docquier & Rapoport, 2012; Hawkes, Kolenko, Hockness, & Diwaker, 2009). This is increasingly a concern for organizations in general (Kulik, Ryan, Harper, & George, 2014) and among specific industries, such as nursing, where the workforce is aging, but demand for those roles is increasing as societies age and require more healthcare services (Eley et al., 2007; Sherman, Chiang‐Hanisko, & Koszalinski, 2013). In order to address this demographic shift, two factors are becoming increasingly important to consider: First, identifying methods to promote working later in life (Kulik et al., 2014; Truxillo, Cadiz, & Hammer, 2015) and second, gaining a better understanding of how workers are treated across the lifespan (Armstrong-Stassen & Schlosser, 2008; Bilinska, Wegge, & Kliegel, 2016; Fisher, Truxillo, Finkelstein, & Wallace, 2017). One line of research aimed at better understanding how to retain workers and extend working careers is research on work ability (WA) and perceived WA (PWA; WORK ABILITY, AGE DISCRIMINATION, PERFORMANCE 2 Feldt, Hyvönen, Mäkikangas, Kinnunen, & Kokko, 2009; Ilmarinen et al., 1991, 1997, McGonagle, Fisher, Barnes-Farrell, & Grosch, 2015). This research has shown that WA can predict important outcomes such as exit from the workforce via retirement and disability later in life (von Bonsdorff et al., 2011). More recently, organizational researchers have found that a range of psychosocial variables influence WA, particularly when measured as PWA (e.g., social support, job demands, personal resources; McGonagle et al., 2015; Palermo, Fuller-Tyszkiewicz, Walker, Appannah, 2013). Although older workers are an increasing portion of the US population (Toossi, 2015; U.S. Census Bureau, 2017), negative stereotypes about older workers persist (Cuddy, Norton, & Fiske, 2005; Posthuma & Campion, 2008) and occur both implicitly and explicitly (Nosek et al., 2007). These stereotypes include being low in competence (Cuddy et al., 2005; Fiske, Cuddy, Glick, & Xu, 2002), less willing to engage in trainings (Ng & Feldman, 2012), unable to learn new material, and more likely to turnover (Posthuma & Campion, 2009). Further, age stereotypes have been shown to exist acrosscultures (Chiu, Chan, Snape, & Redman, 2001) and are viewed as more culturally acceptable than other forms of bias (e.g., racism, sexism; Levy & Banaji, 2002). Based on evidence that age discrimination occurs and the need to better understand how to extend working careers, it is important to understand how the treatment of older workers, specifically age discrimination or the lack thereof, influences WA and organizational outcomes. Work Ability, Its Antecedents, and Its Outcomes Before delving into the theoretical background of WA, it is important to understand the development of the WA construct itself. As a concept, WA was formally WORK ABILITY, AGE DISCRIMINATION, PERFORMANCE 3 developed in Finland in the early 1980s to help understand how long individuals could be expected to continue working (Ilmarinen et al., 1991, 1997). In their initial series of studies, Ilmarinen and colleagues (1991, 1997) found that WA could predict actual exit behaviors including disability pension status and retirement years after the initial measurement of WA. These studies also identified a number of factors associated with increased risk for poor WA. Specifically, they found that those working in blue-collar occupations and those 55 years old or older tended to experience greater declines in WA compared to white-collar and younger workers (Ilmarinen et al., 1991, 1997). Since the initial research, WA research has expanded dramatically and the most common measure of WA, the Work Ability Index (WAI), is now available in over 26 languages (Ilmarinen, 2009; Morschhäuser & Sochert, 2007). Researchers have also identified a wide range of individual (e.g., personal health and core self-evaluations; McGonagle et al., 2015; Palermo et al., 2015) and organizational factors that positively (e.g., autonomy; Weigly et al., 2013) or negatively (e.g., physical job demands; von Bonsdorff, 2012) influence WA. Further, researchers have demonstrated the utility of WA measures for identifying those in need of rehabilitation services (Bethge, Radoschewski, & Gutenbrunner, 2012b) in addition to longer term outcomes (e.g., retirement, disability status). Taken together, WA clearly has great potential for individuals, organizations, and societies in terms of being able to predict important longterm outcomes, and thus, WA has the potential to serve as a leverage point to promote working successfully across the lifespan. WORK ABILITY, AGE DISCRIMINATION, PERFORMANCE 4 Although this research has been informative, a number of serious gaps remain in the extent WA literature. First, despite its widespread use, no studies have quantitatively synthesized the antecedents and outcomes of WA in a comprehensive manner. Second, as the WA literature has developed, the way WA is measured has shifted in fundamental ways, yet the WA literature has not sufficiently investigated how these different types of measures influence the predictive utility of WA.