Abstract
Objective. The Tuck Jump Assessment (TJA), a clinical plyometric assessment, identifies 10 jumping and landing technique flaws. The study objective was to investigate TJA interrater and intrarater reliability with raters of different educational and clinical backgrounds. Methods. 40 participants were video recorded performing the TJA using published protocol and instructions. Five raters of varied educational and clinical backgrounds scored the TJA. Each score of the 10 technique flaws was summed for the total TJA score. Approximately one month later, 3 raters scored the videos again. Intraclass correlation coefficients determined interrater (5 and 3 raters for first and second session, resp.) and intrarater (3 raters) reliability. Results. Interrater reliability with 5 raters was poor (ICC = 0.47; 95% confidence intervals (CI) 0.33–0.62). Interrater reliability between 3 raters who completed 2 scoring sessions improved from 0.52 (95% CI 0.35–0.68) for session one to 0.69 (95% CI 0.55–0.81) for session two. Intrarater reliability was poor to moderate, ranging from 0.44 (95% CI 0.22–0.68) to 0.72 (95% CI 0.55–0.84). Conclusion. Published protocol and training of raters were insufficient to allow consistent TJA scoring. There may be a learned effect with the TJA since interrater reliability improved with repetition. TJA instructions and training should be modified and enhanced before clinical implementation.
Highlights
80,000 anterior cruciate ligament (ACL) injuries occur in the United States with an estimated cost of almost a billion dollars [1]
People at high risk of ACL injury frequently demonstrate high dynamic knee valgus during landing from jumping, which may be due to decreased neuromuscular control [3, 5]
The average number of flaws identified on the Tuck Jump Assessment (TJA) (TJA total score) were 6.30 ± 1.76; and technique flaw (2) was the most frequently identified (87.5% of participants), using scoring from rater 5 who was randomly chosen
Summary
80,000 anterior cruciate ligament (ACL) injuries occur in the United States with an estimated cost of almost a billion dollars [1]. The most common mechanisms of ACL injury are noncontact in nature, characterized by sudden deceleration prior to a landing motion or change of direction [2, 3]. Current literature has proposed several laboratory-based tools to identify risk factors for ACL injury [6]. These screening tools require expensive 3D motion capture equipment, highly trained staff, and significant amount of time to administer and analyze rendering these tools inefficient and impractical for a clinical setting [6]
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