Sara Nicole Lawson1, Neal Zaluski2, Amanda Petrie3, Cathy Arnold4, Jenny Basran5, Vanina Dal Bello-Haas6. 1. Shuya & Associates Integrative Sports Rehab and Wellness, Regina, Sask. 2. Craven SPORT Services. 3. North 49 Balance & Dizziness Centre. 4. School of Physical Therapy, University of Saskatchewan. 5. Geriatric Evaluation and Management Program, Saskatoon City Hospital, Saskatoon, Sask. 6. School of Rehabilitation Science, McMaster University, Institute of Applied Health Sciences, Hamilton, Ont.
Abstract
PURPOSE: To investigate the concurrent validity of the Saskatoon Falls Prevention Consortium's Falls Screening and Referral Algorithm (FSRA). METHOD: A total of 29 older adults (mean age 77.7 [SD 4.0] y) residing in an independent-living senior's complex who met inclusion criteria completed a demographic questionnaire and the components of the FSRA and Berg Balance Scale (BBS). The FSRA consists of the Elderly Fall Screening Test (EFST) and the Multi-factor Falls Questionnaire (MFQ); it is designed to categorize individuals into low, moderate, or high fall-risk categories to determine appropriate management pathways. A predictive model for probability of fall risk, based on previous research, was used to determine concurrent validity of the FSRI. RESULTS: The FSRA placed 79% of participants into the low-risk category, whereas the predictive model found the probability of fall risk to range from 0.04 to 0.74, with a mean of 0.35 (SD 0.25). No statistically significant correlation was found between the FSRA and the predictive model for probability of fall risk (Spearman's ρ=0.35, p=0.06). CONCLUSION: The FSRA lacks concurrent validity relative to to a previously established model of fall risk and appears to over-categorize individuals into the low-risk group. Further research on the FSRA as an adequate tool to screen community-dwelling older adults for fall risk is recommended.
PURPOSE: To investigate the concurrent validity of the Saskatoon Falls Prevention Consortium's Falls Screening and Referral Algorithm (FSRA). METHOD: A total of 29 older adults (mean age 77.7 [SD 4.0] y) residing in an independent-living senior's complex who met inclusion criteria completed a demographic questionnaire and the components of the FSRA and Berg Balance Scale (BBS). The FSRA consists of the Elderly Fall Screening Test (EFST) and the Multi-factor Falls Questionnaire (MFQ); it is designed to categorize individuals into low, moderate, or high fall-risk categories to determine appropriate management pathways. A predictive model for probability of fall risk, based on previous research, was used to determine concurrent validity of the FSRI. RESULTS: The FSRA placed 79% of participants into the low-risk category, whereas the predictive model found the probability of fall risk to range from 0.04 to 0.74, with a mean of 0.35 (SD 0.25). No statistically significant correlation was found between the FSRA and the predictive model for probability of fall risk (Spearman's ρ=0.35, p=0.06). CONCLUSION: The FSRA lacks concurrent validity relative to to a previously established model of fall risk and appears to over-categorize individuals into the low-risk group. Further research on the FSRA as an adequate tool to screen community-dwelling older adults for fall risk is recommended.
Entities:
Keywords:
aged; algorithms; falls, accidental; reproducibility of results; risk assessment
Authors: K L Perell; A Nelson; R L Goldman; S L Luther; N Prieto-Lewis; L Z Rubenstein Journal: J Gerontol A Biol Sci Med Sci Date: 2001-12 Impact factor: 6.053
Authors: Sarah E Lamb; Chris McCabe; Clemens Becker; Linda P Fried; Jack M Guralnik Journal: J Gerontol A Biol Sci Med Sci Date: 2008-10 Impact factor: 6.053
Authors: Alberto Diniz-Filho; Erwin R Boer; Carolina P B Gracitelli; Ricardo Y Abe; Nienke van Driel; Zhiyong Yang; Felipe A Medeiros Journal: Ophthalmology Date: 2015-04-16 Impact factor: 12.079
Authors: Fábio B Daga; Alberto Diniz-Filho; Erwin R Boer; Carolina P B Gracitelli; Ricardo Y Abe; Felipe A Medeiros Journal: PLoS One Date: 2017-12-06 Impact factor: 3.240