Note that GPS points are a close approximation and will not be exact. Because of the nature of GPS tracking, any driving within an undercover carpark cannot be mapped. Similarly, the time spent underground in a train/bus/car will not be completely accurate due to environmentally-produced error.
Data included in the guide are taken directly from recordings on the GPS devices. As some participants stated in their diaries that they forgot to take their GPS on one or more occasions, the GPS will not have recorded their total actual movement for the tracking period.
All statistical information is based on the group of older adults who participated in our study, with the findings highlighting the complex lived experience of older adults who reside in Australia.
Time spent walking includes the time playing golf for two of the participants. Analysis of the GPS data shows this time to be predominantly walking but with many stops of 1-3 minutes, which is difficult to distinguish from slow walking - this leads to a slight over-estimation of walking time in these two cases. Conversely, short walking trips made by two participants in the inner-city have been excluded from this calculation due to environmental error preventing the determination of a clear GPS track, leading to a slight under-estimation.
The amount of time spent on public transport is very small but it should be noted that no regular public transport systems exists in Roma (13/49 participants) and only a limited system exists in Toowoomba (which none of the 12 Toowoomba participants used).
Walking and biking comprise walking/biking for the purpose of commuting as well as for leisure.
Please note also, that participants were not questioned about their sleep. The sleep component contained within some graphs is based on an estimate only of the time an average person may be expected to sleep (7.5 hours). This estimate has been included so as to provide a sense of the proportion of time people spend engaged in their various activities relative to the time spent sleeping.
“Other” accounts for time spent on quad-bikes and private coaches/buses.
Two strategies were utilised to recruit participants. The high density residents were contacted from an existing research database and had previously been recruited through a random postal survey exploring how people (of all ages) experienced life in high density Brisbane. Suburban Brisbane, Toowoomba and Roma participants were recruited using convenience and snowball sampling techniques, specifically through the networks of industry partners and local seniors organisations. We endeavoured to include a wide-range of socio-demographic characteristics (such as age, gender, income, marital status and cultural background) in our sample participants, however, given the relatively small sample a detailed focus and examination of these differences was beyond the scope of this study. Future research should explore the extent to which such characteristics may affect the experience of liveability in Australian communities.