Technology based interventions to promote Healthy and Active Ageing: the role of positive emotions and physical activity

An active lifestyle is of utmost importance for the quality of life of the older adults. With active lifestyle is meant not only physically active, but also engaged with the social environment. Although some individuals can achieve a desired level of physical activity and engagement by themselves, others seem to be in need of an external motivation. Technology based interventions show promising results promoting healthy behaviours, namely physical activity, in daily life. However, to the best of our knowledge, the promotion of an active lifestyle has been less explored. We intend to bring technology-based interventions beyond the state of the art by designing tailored strategies to motivate people to be physically active through engagement in pleasurable activities, thereby promoting healthy and active ageing. Our approach is to look at how the experience of positive emotions relate to physical activity in the daily lives of older adults and, based on that, design tailored strategies to support older adults in becoming more active. Therefore we define two objectives: (1) to increase understanding on the relationship between positive emotions and physical health in daily lives of older adults living independently and (2) to investigate how technology can support in monitoring and coaching towards active ageing in daily life. To achieve these objectives we perform a systematic literature review and two observational studies. We hypothesize that the experience of positive emotions in daily life is highly personal, with our studies focusing on a deep understanding in an individual level, making use of wearable technology and experience sampling on a smartphone. The results of the literature and observational studies are used to define the parameters and relations of a model to be implemented in a mobile system to promote active ageing in daily life. The literature review is concluded as well as the data acquisition of one observational study. This PhD trajectory is expected to be concluded by the end of 2016.