Background of Study: Females generally have a 6-8 times higher risk for lower extremity injury compared to male counterparts due to biomechanical differences and/or poor landing strategies. In recent years, a great deal of focus has been placed on prevention and reduction of non-contact lower extremity injuries. This has spurred the development of assessment methods to determine how athletes move and tools with which those motions are measured. Efforts have been made to measure and quantify movement strategies, which have given rise to multiple movement tests and measurement devices. One approach is the use of wearable technologies used in conjunction with a movement screening. Objective: Demonstrate a practical approach of using wearable technologies to guide training regimens in a population of female athletes that would be considered at risk for lower extremity injuries. Methods: A cohort of Division I female volleyball athletes were screened using wearable technology then assigned an intervention based on screening results. Comparisons were made between injury rates during the season when the intervention was applied compared to previous seasons. Results: All lower extremity injury rates were reduced after the intervention was applied. Conclusions: The use of wearable technology aids in quantifying movement to then assign a strategic intervention to reduce injuries in an at risk athletic population.

Background of Study: Associations between measures of body composition and vertical jump height have previously been established using a range of instrumentation and prediction equations. Limited data has presented using gold standard measurements for both variables Objective: This investigation sought to examination the relationship between total body and lower extremity measures of body composition and vertical jump performance using gold standard measurements within an athletic population. Methods: Using a cross-sectional, correlational research design fourteen collegiate female volleyball athletes completed body composition, three countermovement jumps (CMJ) and three squat jumps (SJ) analysis using DXA and force platforms. Results: High to very high positive relationships were seen between total body lean (p < 0.001) and fat mass (p < 0.05), lower extremity lean and fat mass (p < 0.01), and CMJ force and power. High negative relationships were present between total body fat percentage(p < 0.05), total fat mass (p < 0.01) and CMJ jump height. Relationships between all body composition variables and SJ performance tended to be weaker, with the exception of total body lean mass (p < 0.05), lower extremity lean mass, and power output (p < 0.01). Conclusions: These findings support much of the previous literature in that increases of mass have subsequent increases in force and power production; however caution should be taken will increases in mass coming from fat or lean tissue.

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