Validation of the Saskatoon Falls Prevention Consortium's Falls Screening and Referral Algorithm

Area of Science:

• Gerontology
• Public Health
• Biostatistics

Background:

• Falls are a significant public health concern among older adults, leading to injury and reduced quality of life.
• Effective fall risk screening tools are crucial for implementing timely and appropriate interventions.
• The Saskatoon Falls Prevention Consortium developed the Falls Screening and Referral Algorithm (FSRA) to assess fall risk in community-dwelling seniors.

Purpose of the Study:

• To evaluate the concurrent validity of the Falls Screening and Referral Algorithm (FSRA).
• To determine if the FSRA accurately categorizes fall risk compared to a validated predictive model.

Main Methods:

• A study involving 29 older adults (mean age 77.7 years) residing in an independent-living facility.
• Participants completed the FSRA, comprising the Elderly Fall Screening Test (EFST) and Multi-factor Falls Questionnaire (MFQ), and the Berg Balance Scale (BBS).
• Concurrent validity was assessed by comparing FSRA categorization with a predictive model of fall risk probability.

Main Results:

• The FSRA classified 79% of participants as low fall risk.
• The predictive model indicated a wide range of fall risk probabilities (0.04-0.74, mean 0.35).
• No statistically significant correlation was found between the FSRA and the predictive fall risk model (Spearman's ρ=0.35, p=0.06).

Conclusions:

• The FSRA demonstrates a lack of concurrent validity when compared to an established fall risk model.
• The FSRA may over-categorize individuals into the low-risk group, potentially delaying necessary interventions.
• Further investigation is recommended to establish the FSRA's adequacy for screening community-dwelling older adults for fall risk.