In this paper we describe how we engaged a group of healthy older adults in lifelogging and how we used their data to help design a healthy-aging intervention. 35 participants (mean age = 73.6, age range 59-88, Men=15, Women = 20) were tracked longitudinally for 18 months. Participants provided data at three time points. This involved the use of activity trackers, GPS trackers, and paper diaries. A number of well-established psychometric scales were also administered to gather standardised measures of health and wellbeing. While the data provides insight into the relationship between physical and social activity with regards to wellbeing, we aim to show that the nature of these relationships provide insight into how to design effective healthy-living interventions for older adults. By using the better predictors of wellbeing, we can target change in specific areas and assess change in those areas. While our sample is of relatively high-functioning older adults, we argue that understanding how they maintain wellbeing allows us to understand how to promote wellbeing amongst more inactive and frail older adults. Results showed the importance of specific types of social involvement such as meeting activity-group members and we propose that recommender systems should target these more important predictors of well-being.
|Title of host publication||The 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments PETRA 2019|
|Number of pages||10|
|Publication status||Published - 5 Jun 2019|
|Event||Pervasive Technologies Related to Assistive Environments Conference 2019 - Rhodes, Greece|
Duration: 5 Jun 2019 → 7 Jun 2019
|Conference||Pervasive Technologies Related to Assistive Environments Conference 2019|
|Period||5/06/19 → 7/06/19|