Abstract
There is a need to revisit movement dataset(s) currently used as egress determinants to assess whether they are truly representative of the current diverse occupant base. This is particularly important with our aging population as these sets contain very limited amounts of recent, age-specific data for older adults. This study provides data on walking speeds of older adults, obtained during standardized tests of walking, and compares those to default walking speeds used in current egress models. From experimental, short-distance walking trials (n = 451), it was seen that sex, increasing age, use of walking aids, those who have previously experienced a stroke (n = 116) and walking under cognitive load all resulted in decreases in walking speed. First iteration Pathfinder simulations showed that more realistic inputs for population walking speed resulted in simulated egress times that were on average 8 s slower compared to use of the current default range of walking speeds. Results suggest that the assumption of a uniform population in egress modelling, and consequently the standard practice of using a default walking speed for older adult occupants, should be reconsidered since, in reality the older adult population is extremely heterogeneous with regards to mobility, as reflected in the variability in walking speeds in this study.
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Notes
The impacts of medication described are true across the age range, it is a result of the medication itself, not the age of the individual taking the medication.
Existing tools such as FED calculations, are based on ‘healthy adults’ with additional corrections applied to account for vulnerable populations, although it is not clear how these corrections were determined [35].
Defined as self-care functions, getting up from their bed or chair, walking around their home and ability to walk 5 blocks.
Although there is debate within the community about the applicability of this historical data during the 1950s–1970s, this work does form the basis for many of the current egress calculations and models and in some cases can be selected as a default range.
In Canada, continuum care facilities accommodate a variety of people. Most people will enter healthy and desire to live in a community setting, they are completely independent and reside in a residential condo. As they stay and age, if their functional ability decreases they can then move through different living options, for example they can move into retirement care (services such as housekeeping and some nursing care are offered), and then into a more long-term care setting (additional nursing and caretaker services).
This would define an individual who attends post-stroke check-ups to assess recovery.
If counting down by 3’s was too easy, then the participant was told to count down by 7’s instead, and if counting down by 3’s was too challenging the participant would count down by 1’s instead.
Results of this statistical test are reported as t(df) = W-statistic, p value, d = effect size.
A note on sample sizes utilized in the statistical analysis, for independent t-tests comparing sex and the descriptive statistics in Table 3, sample sizes of n = 238 females and n = 128 males (total n = 366) was used. For independent t-tests comparing aid use, sample sizes of n = 152 aid users, and n = 214 non-aid users (total n = 366) in Table 4 were used. Paired t-tests were conducted on a separate group of aid users, with a sample size of n = 85, who felt comfortable trying the preferred walking condition trial without their aid, Table 5.
A sample size of 10 simulation runs per set was determined to be sufficient (\(\alpha\) = 0.05, power = 95%) to compare whether or not the means of predicted egress time were different between the two groups: older adult assigned and SFPE default.
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Acknowledgements
The authors would like to thank study participants and participating sites of the Canadian Partnership for Stroke Recovery Rehab Affiliates study as well as Schlegel Villages together with the Schlegel-UW Research Institute for Aging, for their contributions to the studies in which these data were collected.
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Forrest, B., Gales, J., Van Ooteghem, K. et al. Using Older Adult Walking Speeds from Controlled Trials as Inputs for Occupants in Simulations. Fire Technol (2024). https://doi.org/10.1007/s10694-024-01574-0
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DOI: https://doi.org/10.1007/s10694-024-01574-0