Generating recommendations for optimizing heath, safety and well-being of the aging workforce.

Using technology for promoting sustainable aging

The occupational landscape in EU changes rapidly in the face both of the advancing aging of the workforce population and the 4th industrial (digital) revolution. Adaptive per-formance (i.e. learning new tasks, working with new technologies, dealing with uncertain or unexpected situations) within such a context is an important component of overall performance and employability 1. Age on the other hand is associated with poorer adaptability and decline of cognitive functions 2,3. Current and future generations of employees must both work longer until retirement and at the same time keep pace with physical and cognitive performance demands, and maintain productivity rates. This de-velopment poses a challenge for occupational safety and health (OSH) as well as for the general well-being of older workers. The advancing use of technological aids can be both a challenge as well as an opportunity for managing the needs of the aging work-force.

sustAGE aims at utilizing technology as a resource for aging workers through the de-velopment of a person-centred smart solution to support well-being, OSH as well as task performance and productivity. The planned solution shall sustainably drive workers’ behavioural modification and adaptability along three main dimensions:

First, improving OSH based on real-time monitoring respective workplace and person-centred parameters (e.g. noise, dust, fatigue, posture); second, preventing physical and cognitive decline as well as stress of employees via personalised recommendations for physical and mental health; and third, supporting decision making for viable and ac-ceptable options on the team/organisational level regarding flexible task allocation dur-ing work for benefiting both productivity optimization and sustainable aging of workers.

User-centered, recommendation framework

One of the cornerstones of the project is the direct involvement of end-users (i. e. in-dustrial partners and front-line workers) throughout the lifespan of the project. This is also the case for the definition of work demands, risks for OSH and well-being aspects that will be at the heart of the sustAGE person-centred smart solution. The body of val-id knowledge from previous research shall be complemented by empirical data derived directly from the target groups (i.e. elderly front-line workers) at two critical industrial domains for the EU economy: manufacturing and transportation/logistics.

For this reason, a data collection took place at the two industrial sites of FCA in Melfi, Italy (manufacturing) and HPA, Heraklion, Greece (transportation/logistics) in the be-ginning of September until Mid-October 2019. The objective of this step consists in es-tablishing a data-driven “profile” of the target groups of older employees regarding spe-cific cognitive and psychosocial characteristics.

An identical procedure and administration of a test battery consisting of a set of stand-ardized and field-tested psychometric methods (questionnaires, cognitive tests, short interviews) were followed for each participant in both sites in order to ensure equiva-lence and comparability of the data sets. All employed instruments were available in validated and standardized Greek and Italian versions. The methods assessed a broad array of respective work-related and life-related aspects to be covered by sustAGE: risks for OSH, work ability, physical activity, quality of life, burn-out, stress, cognitive errors, affective responses, work-related psychosocial aspects; short-term/working memory, executive functions, processing speed; work organisation and task demands.

The data will be analysed in order to provide necessary information for constructing a broad context-sensitive and personalizable sustAGE recommendation framework. This initial, data-driven pool of recommendations will be incorporated in the first prototype version of sustAGE in order to set the informational basis for tailored real-time commu-nication with users on the aforementioned three main sustAGE dimensions: risks for OHS for older workers, cognitive and psychosocial characteristics of end-users and via-ble approaches for work place re-organization and optimization.

Additionally, data will provide valuable information that will contribute to the further de-velopment of the cognitive and stress-management training suite by specifying cognitive skills and stress-related aspects to be focused upon.

  1. Hedge, J.W. and Borman, W.C. (2019). Employee Age and Performance in Or-ganizations. In: K.S: Schultz and G.A. Adams, Aging and Work in the 21st Century (2nd edition) (pp. 122-144). New York, Oxon: Routledge
  2. Gajewski PD, Hanisch E, Falkenstein M, Thönes S and Wascher E (2018). What Does the n-Back Task Measure as We Get Older? Relations Between Working-Memory Measures and Other Cognitive Functions Across the Lifespan. Front. Psy-chol. 9:2208. doi: 10.3389/fpsyg.2018.02208
  3. Ballesteros, S., Kraft. E., Santana, S. and Tziraki, C. (2015). Maintaining older brain functionality: A targeted review. Neuroscience and Biobehavioral Reviews 55, 453–477.