Clinical Implications of Landing Distance on Landing Error Scoring System Scores.

Context: The Landing Error Scoring System (LESS) screens for risk of noncontact anterior cruciate ligament injury. The LESS requires individuals to jump forward from a 30-cm box to a distance of 50% of their body height. However, different landing distances have been cited in the scientific literature.

Objective: To examine whether landing distance influences LESS outcomes.

Design: Cross-sectional study.

Setting: Laboratory.

Participants Or Other Participants: Seventy young active individuals (34 males, 36 females).

Intervention(s): Participants performed 3 × 30-cm jump-landing tasks under 2 landing conditions in randomized order: (1) 50% of body height (d50%), (2) self-selected distance (dss).

Main Outcome Measure(s): Mean LESS scores, proportions of individuals categorized at high (LESS: ≥ 5 errors) and low (LESS: < 5 errors) injury risk, and landing distances were compared between conditions using generalized estimating equations. Consistency of risk categorization was examined using odds ratios (ORs) and McNemar tests. McNemar and Wilcoxon signed rank tests were used to compare the occurrence of specific LESS errors.

Results: Participants landed closer to the box under the dss condition (difference = -23.28 [95% CI = -20.73, -25.81]%, P < .001). Group mean LESS scores (difference = -0.01 [95% CI = -0.59, 0.57] error, P = .969) and risk categorization (OR = 0.94 [95% CI = 0.47, 1.88], P = .859) were similar between conditions. However, individual-level risk categorization was inconsistent in 33% of participants, as was the occurrence of specific errors.

Conclusions: Using dss during the LESS might lead to different LESS errors and risk categorizations at an individual level than using d50%. Given that individual LESS scores are of primary interest in clinical and sport settings and the injury-risk threshold has not been validated for dss, we recommend use of the original LESS protocol. When only group mean LESS scores or proportions of at-risk individuals are of interest, using dss is feasible to facilitate the testing of large cohorts.