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

N. F. J. Waterval, Cindy Claassen, F.C.T. van der Helm, Eline van der Kruk

2023Sensors14 citationsDOIOpen Access PDF

Abstract

Fall risk increases with age, and one-third of adults over 65 years old experience a fall annually. Due to the aging population, the number of falls and related medical costs will progressively increase. Correct prediction of who will fall in the future is necessary to timely intervene in order to prevent falls. Therefore, the aim of this scoping review is to determine the predictive value of fall risk assessments in community-dwelling older adults using prospective studies. A total of 37 studies were included that evaluated clinical assessments (questionnaires, physical assessments, or a combination), sensor-based clinical assessments, or sensor- based daily life assessments using prospective study designs. The posttest probability of falling or not falling was calculated. In general, fallers were better classified than non-fallers. Questionnaires had a lower predictive capability compared to the other assessment types. Contrary to conclusions drawn in reviews that include retrospective studies, the predictive value of physical tests evaluated in prospective studies varies largely, with only smaller-sampled studies showing good predictive capabilities. Sensor-based fall risk assessments are promising and improve with task complexity, although they have only been evaluated in relatively small samples. In conclusion, fall risk prediction using sensor data seems to outperform conventional tests, but the method's validity needs to be confirmed by large prospective studies.

Topics & Concepts

PredictabilityProspective cohort studyRisk assessmentPredictive valuePredictive validityMedicinePoison controlFall preventionInjury preventionPredictive modellingFalling (accident)PopulationGerontologyPhysical therapyComputer scienceMedical emergencyMachine learningStatisticsEnvironmental healthSurgeryComputer securityMathematicsClinical psychologyInternal medicineBalance, Gait, and Falls PreventionContext-Aware Activity Recognition SystemsInjury Epidemiology and Prevention
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