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Behavior Changes in Older Adults During Adverse External Events: A Longitudinal Observational Study
ABSTRACT
Background:
Older adults manage multiple impacts on health, including chronic conditions and adverse external events like pandemics and wildfires. Understanding behavior changes related to these events is important for assessing risk and designing interventions. Information derived from smart home sensors can provide objective data about behavior changes to support a learning healthcare system.
Objective:
Our objective is to examine digital markers collected before and during two events (COVID-19 pandemic, wildfires) to determine whether clinically relevant behavior changes can be observed and targeted upstream interventions suggested.
Methods:
Secondary analysis of historic ambient sensor data collected on n=39 adults managing one or more chronic conditions was performed. Interrupted Time Series analysis was used to extract behavior markers related to external events. Comparisons were made to examine differences between exposures using machine learning classifiers.
Results:
Significant pandemic-related behavior changes ranked by impact included a (3.8 hours/day) decrease in time spent out of home, increase in restless sleep (946.74%), and decrease in indoor activity (38.89%). Although participants exhibited less restless sleep during exposure to wildfire smoke (120%), they also decreased their indoor activity (114.29%). Sleep duration trended downward during the pandemic shutdown. Time out of home and sleep duration gradually decreased while exposed to wildfire smoke. Behavior trends differed across exposures.
Conclusions:
Behavior changes were detected for the two adverse external events (pandemic, wildfire smoke) initially and over time. However, the direction and magnitude of change differed between participants and events. Sensor-based findings could support the learning healthcare system’s ability to promote health equity ideals by providing environmental contexts affecting social determinants of health. The smart home’s novel, evidence-based information could inform future management of chronic conditions, allowing nurses to understand patients’ health-related behaviors between the care points so timely interventions are possible. Clinical Trial: N/A
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