Danielle Hernandez1, Debra J Rose. 1. Center for Successful Aging at California State University, Fullerton, CA 92832, USA. dahernandez@fullerton.edu
Abstract
OBJECTIVE: The purpose of this study was to determine if the Fullerton Advanced Balance (FAB) scale can predict faller status in a group of independently functioning older adults. DESIGN: A cross-sectional design was used to establish the sensitivity and specificity of the FAB scale to predict faller status based on a retrospective self-reported fall history. For the purpose of this study, a faller was classified as an older adult with a history of 2 or more falls in the previous 12 months. SETTING: Multipurpose senior centers in an urban community. PARTICIPANTS: A sample of independently functioning older adults (N=192; mean age+/-SD, 77+/-6.5 y). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: FAB scale, a retrospective history of falls. RESULTS: Binary logistic regression analysis indicated that the total FAB scale score could be used to predict faller status (as determined by a retrospective self-reported fall history). In the present sample, the probability of falling increased by 8% with each 1-point decrease in total FAB scale score. Receiver operating characteristic analysis determined that a cut-off score of 25 out of 40 on the FAB scale produced the highest sensitivity (74.6%) and specificity (52.6%) in predicting faller status. Five individual test items on the FAB scale were particularly predictive of faller status and could be combined to form a short version of the scale that may be even more predictive of faller status and require less time to administer. CONCLUSIONS: The FAB scale is a predictive measure of faller status when used with independently functioning older adults. A practitioner can be confident in more than 7 out of 10 cases that an older adult who scores 25 or lower on the FAB scale is at high risk for falls and in need of immediate intervention.
OBJECTIVE: The purpose of this study was to determine if the Fullerton Advanced Balance (FAB) scale can predict faller status in a group of independently functioning older adults. DESIGN: A cross-sectional design was used to establish the sensitivity and specificity of the FAB scale to predict faller status based on a retrospective self-reported fall history. For the purpose of this study, a faller was classified as an older adult with a history of 2 or more falls in the previous 12 months. SETTING: Multipurpose senior centers in an urban community. PARTICIPANTS: A sample of independently functioning older adults (N=192; mean age+/-SD, 77+/-6.5 y). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: FAB scale, a retrospective history of falls. RESULTS: Binary logistic regression analysis indicated that the total FAB scale score could be used to predict faller status (as determined by a retrospective self-reported fall history). In the present sample, the probability of falling increased by 8% with each 1-point decrease in total FAB scale score. Receiver operating characteristic analysis determined that a cut-off score of 25 out of 40 on the FAB scale produced the highest sensitivity (74.6%) and specificity (52.6%) in predicting faller status. Five individual test items on the FAB scale were particularly predictive of faller status and could be combined to form a short version of the scale that may be even more predictive of faller status and require less time to administer. CONCLUSIONS: The FAB scale is a predictive measure of faller status when used with independently functioning older adults. A practitioner can be confident in more than 7 out of 10 cases that an older adult who scores 25 or lower on the FAB scale is at high risk for falls and in need of immediate intervention.
Authors: Christine Miaskowski; Judy Mastick; Steven M Paul; Kimberly Topp; Betty Smoot; Gary Abrams; Lee-May Chen; Kord M Kober; Yvette P Conley; Margaret Chesney; Kay Bolla; Grace Mausisa; Melissa Mazor; Melisa Wong; Mark Schumacher; Jon D Levine Journal: J Pain Symptom Manage Date: 2017-01-04 Impact factor: 3.612
Authors: Jessica Battisto; Katharina V Echt; Steven L Wolf; Paul Weiss; Madeleine E Hackney Journal: Neurorehabil Neural Repair Date: 2018-10-15 Impact factor: 3.919
Authors: Kord M Kober; Melissa Mazor; Gary Abrams; Adam Olshen; Yvette P Conley; Marilyn Hammer; Mark Schumacher; Margaret Chesney; Betty Smoot; Judy Mastick; Steven M Paul; Jon D Levine; Christine Miaskowski Journal: J Pain Symptom Manage Date: 2018-08-30 Impact factor: 3.612
Authors: Christine Miaskowski; Steven M Paul; Judy Mastick; Mark Schumacher; Yvette P Conley; Betty Smoot; Gary Abrams; Kord M Kober; Steven Cheung; Jennifer Henderson-Sabes; Margaret Chesney; Melissa Mazor; Margaret Wallhagen; Jon D Levine Journal: Eur J Oncol Nurs Date: 2017-11-07 Impact factor: 2.398
Authors: Dana L Judd; Joshua D Winters; Jennifer E Stevens-Lapsley; Cory L Christiansen Journal: Clin Biomech (Bristol, Avon) Date: 2015-12-31 Impact factor: 2.063