Y-Balance Test: A Valid and Reliable Assessment in Older Adults.

Testing balance and fall risk with older adults of varying abilities is of increasing importance. The primary aim of this study was to evaluate the validity of the lower quarter Y-balance test (YBT-LQ) in older adults. A secondary aim was to provide estimates of reliability with this population. A total of 30 male (n = 15) and female (n = 15) subjects (66.8 ± 6.5 years) performed the YBT-LQ, 30-s chair stand test, 8-foot up and go test, timed up and go test, single-leg stance, and Activities-Specific Balance Confidence Scale questionnaire. The YBT-LQ was performed on two separate occasions by two investigators in random order. YBT-LQ was significantly correlated with age (p < .01), timed up and go test (p = .003), 8-foot up and go test (p < .001), 30-s chair stand test (p < .001), Activities-Specific Balance Confidence Scale (p = .002), and single-leg stance (p = .005) performance. The intraclass correlation coefficient(3,1) score for the reliability of the YBT-LQ was .95 (95% confidence interval [.89, .97]). The YBT-LQ appears to be a valid and reliable assessment to use with older adults.

Developing predictive models for return to work using the Military Power, Performance and Prevention (MP3) musculoskeletal injury risk algorithm: a study protocol for an injury risk assessment programme.

BACKGROUND: Musculoskeletal injuries are a primary source of disability in the US Military, and low back pain and lower extremity injuries account for over 44% of limited work days annually. History of prior musculoskeletal injury increases the risk for future injury. This study aims to determine the risk of injury after returning to work from a previous injury. The objective is to identify criteria that can help predict likelihood for future injury or re-injury. METHODS: There will be 480 active duty soldiers recruited from across four medical centres. These will be patients who have sustained a musculoskeletal injury in the lower extremity or lumbar/thoracic spine, and have now been cleared to return back to work without any limitations. Subjects will undergo a battery of physical performance tests and fill out sociodemographic surveys. They will be followed for a year to identify any musculoskeletal injuries that occur. Prediction algorithms will be derived using regression analysis from performance and sociodemographic variables found to be significantly different between injured and non-injured subjects. DISCUSSION: Due to the high rates of injuries, injury prevention and prediction initiatives are growing. This is the first study looking at predicting re-injury rates after an initial musculoskeletal injury. In addition, multivariate prediction models appear to have move value than models based on only one variable. This approach aims to validate a multivariate model used in healthy non-injured individuals to help improve variables that best predict the ability to return to work with lower risk of injury, after a recent musculoskeletal injury. TRIAL REGISTRATION NUMBER: NCT02776930.