Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Nursing

Date Submitted: Nov 20, 2024
Date Accepted: Mar 18, 2025

The final, peer-reviewed published version of this preprint can be found here:

Detecting Older Adults’ Behavior Changes During Adverse External Events Using Ambient Sensing: Longitudinal Observational Study

Fritz R, Cook D

Detecting Older Adults’ Behavior Changes During Adverse External Events Using Ambient Sensing: Longitudinal Observational Study

JMIR Nursing 2025;8:e69052

DOI: 10.2196/69052

PMID: 40311115

PMCID: 12061350

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Behavior Changes in Older Adults During Adverse External Events: A Longitudinal Observational Study

  • Roschelle Fritz; 
  • Diane Cook

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


 Citation

Please cite as:

Fritz R, Cook D

Detecting Older Adults’ Behavior Changes During Adverse External Events Using Ambient Sensing: Longitudinal Observational Study

JMIR Nursing 2025;8:e69052

DOI: 10.2196/69052

PMID: 40311115

PMCID: 12061350

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.