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Conceptualizing a Dynamic Fall Risk Model Including Intrinsic Risks and Exposures.

Jochen Klenk1, Clemens Becker2, Pierpaolo Palumbo3

  • 1Department of Clinical Gerontology, Robert Bosch Hospital, Stuttgart, Germany; Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.

Journal of the American Medical Directors Association
|September 17, 2017
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Summary
This summary is machine-generated.

Falls pose significant risks to older adults. This study introduces a dynamic fall risk model, incorporating time-varying intrinsic factors and contextual activities, to improve fall prediction and prevention strategies.

Keywords:
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Area of Science:

  • Gerontology
  • Biomedical Engineering
  • Public Health

Background:

  • Falls are a leading cause of injury, disability, and loss of independence in older adults.
  • Current fall risk models are limited by their static nature and failure to account for dynamic personal and environmental factors.
  • Improved fall risk assessment is crucial for developing effective prevention interventions.

Observation:

  • Existing fall risk models assume risk factors are constant over time, which does not align with real-life variability.
  • Current models fail to integrate the complex interplay between individual activities and environmental conditions during falls.
  • eHealth sensor technology offers potential for continuous measurement of dynamic risk factors and environmental exposures.

Findings:

  • A novel dynamic fall risk model is proposed, integrating time-varying intrinsic risk factors with contextual exposure (activity and environment).
  • This dynamic framework accounts for the interplay between personal factors and environmental risks in fall occurrences.
  • Real-world fall examples from the FARSEEING database illustrate the model's application.

Implications:

  • The dynamic fall risk model offers a more realistic approach to understanding fall mechanisms.
  • Improved fall risk assessment can lead to more targeted and effective fall prevention interventions.
  • This framework has the potential to enhance the development of personalized fall prevention strategies for older adults.