Predictability of Fall Risk Assessments in Community-Dwelling Older Adults: A Scoping Review

Area of Science:

• Gerontology
• Biomedical Engineering
• Public Health

Background:

• Fall risk significantly increases with age, affecting one-third of adults over 65 annually.
• The growing elderly population will lead to a rise in fall incidents and associated healthcare costs.
• Accurate prediction of future falls is essential for timely interventions to prevent injuries.

Purpose of the Study:

• To evaluate the predictive value of various fall risk assessments in community-dwelling older adults.
• To synthesize findings from prospective studies on fall risk prediction methods.
• To compare the effectiveness of clinical, sensor-based clinical, and sensor-based daily life assessments.

Main Methods:

• Conducted a scoping review of 37 prospective studies.
• Included assessments using questionnaires, physical tests, combined clinical assessments, sensor-based clinical assessments, and sensor-based daily life assessments.
• Calculated the posttest probability of falling or not falling for different assessment types.

Main Results:

• Fallers were generally better classified than non-fallers across studies.
• Questionnaires demonstrated lower predictive capability compared to other assessment methods.
• The predictive value of physical tests varied significantly in prospective studies, with smaller samples showing better predictive capabilities.
• Sensor-based assessments show promise, especially with increased task complexity, but have been studied in limited sample sizes.

Conclusions:

• Sensor-based fall risk prediction appears superior to conventional methods.
• Further large-scale prospective studies are necessary to validate the predictive accuracy of sensor-based methods.
• Optimizing fall risk prediction is vital for targeted interventions in the aging population.