Classification of lower extremity movement patterns based on visual assessment: Reliability and correlation with 2-dimensional video analysis

Context: Abnormal movement patterns have been implicated in lower extremity injury. Reliable, valid, and easily implemented assessment methods are needed to examine existing musculoskeletal disorders and investigate predictive factors for lower extremity injury. Objective: To determine the reliability of experienced and novice testers in making visual assessments of lower extremity movement patterns and to characterize the construct validity of the visual assessments. Design: Cross-sectional study. Setting: University athletic department and research laboratory. Patients or Other Participants: Convenience sample of 30 undergraduate and graduate students who regularly participate in athletics (age = 19.3 ± 4.5 years). Testers were 2 experienced physical therapists and 1 novice postdoctoral fellow (nonclinician). Main Outcome Measure(s): We took videos of 30 athletes performing the single-legged squat. Three testers observed the videos on 2 occasions and classified the lower extremity movement as dynamic valgus, no change, or dynamic varus. The classification was based on the estimated change in frontalplane projection angle (FPPA) of the knee from single-legged stance to maximum single-legged squat depth. The actual FPPA change was measured quantitatively. We used percentage agreement and weighted j to examine tester reliability and to determine construct validity of the visual assessment. Results: The κ values for intratester and intertester reliability ranged from 0.75 to 0.90, indicating substantial to excellent reliability. Percentage agreement between the visual assessment and the quantitative FPPA change category was 90%, with a j value of 0.85. Conclusions: Visual assessments were made reliably by experienced and novice testers. Additionally, movement-pattern categories based on visual assessments were in excellent agreement with objective methods to measure FPPA change. Therefore, visual assessments can be used in the clinic to assess movement patterns associated with musculoskeletal disorders and in large epidemiologic studies to assess the association between lower extremity movement patterns and musculoskeletal injury.