COADAPT: Adaptive environments and conversational agent based approaches for healthy aging and work ability
It may be difficult for an aging person to remain active if aging impairs their ability to interact with digitalized information or digital channels and interfaces or makes digital interaction more difficult.
The aim of the COADAPT project is to provide a framework that promotes change, including the following adaptation support tools:
- Personal adaptation support: The empowerment of aging people is supported in order to make it possible for them to adapt to changing circumstances. A change agent that processes personalized, AI-based, linguistic and psychophysiological data is used as an aid.
- Adaptation of work systems: Shift planning systems, personal cognitive loads on assembly lines and the use of situational applications to support the cognitive activities of older employees are studied.
Materials and techniques
The Finnish Institute of Occupational Health provides a framework that integrates information on how the effects of aging are taken into account:
- in technological design
- in shift planning software
- in the use of optimal change strategies in the context of healthy aging.
The Finnish Institute of Occupational Health will carry out an intervention study on the adaptation of shift planning software according to the needs of older employees.
We will also study the characteristics of working time that support the work ability of older employees. For this purpose, we will use longitudinal data from the follow-up study of the municipal sector. We will examine how changes in the characteristics of working time are related to sickness absences and work ability of younger and older employees.
In a quasi-experimental setting, we will also use the material produced by electronic shift planning software to examine which aspects of working time (for example, the number of night shifts, the length of weekly working time) affect the well-being at work of older employees and their work ability.
With the help of shift planning software, we will examine whether the possibility to influence working time and recovery improve the work ability and well-being of older people.
Results and effectiveness
Ageing was associated with beneficial changes in objective working hour characteristics:
- Older employees had more often shorter weekly working hours and less night work.
- Shorter working hours had mostly similar associations to lower odds for short sickness absences among both the younger and older workers but having less often quick returns was associated with lower likelihood of short sickness absence among older workers.
- Changes towards shorter working hours, less night shifts and lower work tempo among ageing workers were associated with less retirement intentions.
- Among aging workers, digital shift scheduling should be developed to promote sufficient recovery between the shifts and to limit extensive weekly working hours, night shift work and high work tempo.
- Participatory working time scheduling gives employees more influence over scheduling of their shifts. Using participatory working time scheduling was associated with reduced sickness absences on ward level, work-related stress and sleep difficulties amongst social welfare and health care workers, and it also improved their self-perceived work ability. The effects were mostly similar for both young and older employees.
Based on the most recent research results, the Finnish Institute of Occupational Health updated the recommendations of the working time traffic light model concerning night work and shift length. New recommendations were also issued with regards to employees over 50 years of age:
- The opportunity to work fewer night shifts
- Where necessary, the opportunity to work reduced total hours and shorter shifts
- Avoiding short intervals between shifts to ensure adequate recovery
Reducing the stressfulness of work for ageing employees is significant from the perspective of society, as it is likely to reduce sickness absences and extend careers.
Members of the consortium
Helsingin Yliopisto, Helsinki, konsortion johtaja prof. Giulio Jacucci, giulio.jacucci(at)helsinki.fi
Aalto Yliopisto, Espoo
Bnp S.r.l., Cittadella, Italia
Electrolux Italia, Italia
Etsimo Healthcare, Turku
IDEGO, Rooma, Italia
Innovation Sprint, Brysseli, Belgia
Padovan Yliopisto, Padova, Italia
Trenton Yliopisto, Trento, Italia
EU Horizon 2020, members of the consortium
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