The ageing workforce is an international social policy concern, a leading topic of interest for organisations and academics, and a priority research area for the UK Health and Safety Executive (HSE). This project builds on an existing collaboration between Alliance Manchester Business School, University of Manchester and the HSE. The research enabled the development of a network of stakeholders interested in age and health and wellbeing in the transport sector www.ambs.ac.uk/ahpdn. The Age, Health and Professional Drivers’ (AHPD) network currently has over 70 member organisations, including transport and logistic firms and representatives, unions, employers and employees.
During the research project the team explored the experiences and viewpoints of professional drivers and employers via: interviews with 10 health and safety managers and trainers; 1 focus group; a discussion forum with representatives from a transport union; interviews with 36 drivers of 7.5 to 44 tonne vehicles and 6 managers of two large national companies. Interim findings of the research were published in a HSE Research Report and presented at EAOHP 2018.
Research findings and the network have now been utilised to produce industry-led guidelines for best practice regarding age and wellbeing in the transport sector. These guidelines were made freely available on the AHPD Network webpage in May 2019 and to date have been downloaded over 100 times by a range of companies in the transport sector. The guidelines detail ten areas of health and wellbeing identified through the research as relevant for older workers. These are displayed in a Wellbeing Wheel, and are detailed fully in the best practice guidelines available to download here: www.ambs.ac.uk/ahpdn
The Best Practice Guidelines are separated into ten ‘spokes’ showing the key themes relating to driver health and wellbeing, with separate emphasis on Support, Implementation and Evaluation. The broad areas covered in the guidelines are: Support (how to help and encourage); Implementation (how to do it); Evaluation (is it working? Has it worked?); Mental Health (e.g. limiting the job impact on wellbeing); Physical Health (e.g. increasing the opportunity for physical activity); Healthy Eating (e.g. encouraging healthy eating habits); Working Practices (e.g. reducing health damage); Working Patterns (e.g. considering shift patterns and flexible working); Retirement (e.g. providing advice and planning); Culture (e.g. recognising the importance of management attitudes); Communication (e.g. how best to do it); Training (e.g. helping people to perform well); Bereavement (e.g. giving support and introducing policies); Resources (where to go for more detailed information); and References.
The guidelines are designed to be accessible for everyone. We provide links to useful resources for managers and employees at all levels that are involved in promoting, protecting and addressing health and wellbeing needs of drivers. The guidelines apply to employees of all ages, with highlighted advice of particular relevance to older employees. They are focused specifically on professional drivers but can be used when considering the needs of all employees.
Fed by the demographic change the share of older workers among the European workforce increases rapidly. Better health status of older workers and the political ambition to relieve pension systems drive extended working lives. Consequently, organizations have to deal with increased age diversity and specific demands by older workers. In order to summarize and describe appropriate organizational practices and working conditions for older workers nearing retirement age and beyond, we developed and operationalized the Later Life Work Index. It is based on qualitative interviews in Germany (Wöhrmann, Deller, & Pundt, 2018) and evidence from the “Age Smart Employer Award” in New York City. The index contains nine dimensions covering age-friendly organizational culture and leadership, as well as more specific age-friendly practices regarding work design, health management, individual development, knowledge management, transition to retirement, continued employment options and health and retirement coverage.
We operationalized and validated the index in multiple studies. We first developed an extensive item pool based on pre-studies with human resource representatives from 30 to 56 companies in Germany. Secondly, EFAs were conducted on responses from 600 employees of all industries to form a compact, reliable and valid scale. Third, we cross-validated results against convergent and criterion variables in a third sample of 350 older workers. Fourth, we administered the scales in 50 organizations in Germany with 900 older workers, managers and human resource representatives in total to proof a shared within-organization perception of the index and a valid measurement on the organizational level. Finally, the scales were translated and back-translated to English by two independent English-German bilinguals and are currently cross-validated among older workers in the United States.
The index can be assessed by 80 items in total, showing good to acceptable CFA model fit and reliabilities. The validation proofs sufficient independence from positive and negative affect, as well as discriminant validity among the index dimensions. Moreover, criterion validity proves effects on e.g. older workers’ commitment towards the organization, stress level and perceived health status.
So far, the validation of the developed LLWI scale is limited to individual level criterions. However, we continue the organizational study to validate the effects on organizational level outcomes such as performance, illness absence and turnover.
The index allows organizations to self-assess their capabilities and opportunities for improvement regarding employment of older workers in a straightforward and low-effort manner. Individual dimensions of the index may serve researchers as a standardized and validated measure to evaluate interventions in specific research areas. We will present and discuss the index and its operationalization and are eager to show a validated English version to facilitate the application of the index in different cultural settings.
Introduction: The concept of successful aging at work has become a popular research topic and received theoretical as well as conceptual research attention (De Lange, Kooij, van der Heijden, 2015). For example, Zacher, Kooij & Beier, Wang (2018) point to a process-based definition focusing on elements of selfmanagement and adaptation of aging workers across time. More specifically, they argue that personal resources, active regulation of behavior and optimal investment of resources (Baltes & Baltes, 1990), maintenance of the (perceived) capacity to influence the environment (or self-efficacy), and focusing on positive events and experiences (Carstensen, Isaacowitz, & Charles, 1999) enable individuals to age successfully. Surprisingly, to-date no validated scale is available to tap and monitor successful aging at work. As a result, based on the aforementioned theoretical and conceptual work, we developed a new scale measuring selfmanagement as basis of successful aging at work, including proactive behavior to age successfully, self-efficacy at work, and positive perceptions about aging at work. In this presentation we present the first psychometric test of this new survey measure among bridge workers (aged 65 years and older).
Method: Using an online survey study among N=392 bridge workers, we administered a 14-item measure scale of successful aging at work (response categories varied from 1= totally disagree till 7= totally agree). Including items measuring: a) proactive behavior to age successfully at work (3 items; I actively work on keeping my body fit), b) positive perceptions of aging at work (6 items; I like to be a positive role model for others considering aging at work), c) self-efficacy at work (5 items; when faced with difficulties at work, I have enough resiliency to cope). The alpha of the overall scale was α= .94.
Results: We used latent class cluster analysis, confirmatory latent class factor analysis and an exploratory latent class factor analysis in Latent Gold 5.1 (Vermunt & Magidson, 2016) to further explore the structure of the scale in the data. The latent class factor model with cross-loadings was satisfactory for the 14 included items, that distinguished 3 factors with 4 latent classes each, fitted better (i.e. lowest BIC) than the both the confirmatory and exploratory latent class factor models and better than the latent class cluster model. The fit of the model was as follows: bootstrap of the L2 was higher than .01 and entropy R2 > .90. To inspect whether the three factors that correlated above .6 can be conceived as three dimensions of an overall latent construct we tested whether a second order factor model fitted better than the three factor model. The model comparison procedure showed that L2 was significantly lower (p < 0.05) for the second order latent class factor model; indicating that the new scale successful aging at work fitted the data better than separate subscales.
Discussion: Our first psychometric test revealed a satisfactory fit of the new scale successful aging at work among a sample of successful bridge workers, and revealed promising results for a new scale in the domain of successful aging at work.
Although one’s capabilities and correspondingly work performance may change through the life course, the available empirical evidence on the relationship between age and performance is, at best, inconclusive and, at worst, contradictory. It is possible that the nature of the relationship between performance and age is not consistent throughout the full range of ages. We challenge the general expectation of a negative linear relationship and draw on relevant research to propose and then examine the possibility for differential and curvilinear relationships between chronological age and three types of job performance: proficiency, proactivity, and adaptivity. Furthermore, we hypothesise that each of these curvilinear relationships is intensified by job complexity so that the curvilinear relationship is buffered when cognitive demands are high.
Using survey data from a public organization and 903 participants we tested the relationships between age and each aspect of performance using polynomial regression analysis. For proficiency we found no evidence of either a curvilinear relationship or a moderation by job complexity. For adaptivity there was a U-shaped relationship between age and adaptivity and a main effect for job complexity but there was no interaction between the two. For proactivity though the curvilinear relationship followed a sigmoid pattern. Specifically, proactivity reduced between the ages of 18 to 30 after which point plateaued until approximately 55 to 60 years of age. This pattern was more pronounced for jobs with low job complexity indicating that proactivity was more stable throughout the lifespan for individuals whose job required them to perform more cognitive demanding tasks.
These findings are strongly indicative of the hypothesis that changes in aspects of performance are not consistent throughout the range of working ages and that the complexity of the job is a major moderator in this relationship. As such, they can be especially useful for developing ways to optimize performance for different groups of employees and for channelling resources where they are needed the most, in order to support workers through their life course.
This work is supported by the European Union Programme for Employment and Social Solidarity - PROGRESS (2007-2013) awarded to the first and fifth authors.