Injury Risk Estimation Expertise Assessing the ACL Injury Risk Estimation Quiz

Abstract

Background: Available methods for screening anterior cruciate ligament (ACL) injury risk are effective but limited in application as they generally rely on expensive and time-consuming biomechanical movement analysis. A potential efficient alternative to biomechanical screening is skilled movement analysis via visual inspection (ie, having experts estimate injury risk factors based on observations of athletes’ movements). Purpose: To develop a brief, valid psychometric assessment of ACL injury risk factor estimation skill: the ACL Injury Risk Estimation Quiz (ACL-IQ). Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: A total of 660 individuals participated in various stages of the study, including athletes, physicians, physical therapists, athletic trainers, exercise science researchers/students, and members of the general public in the United States. The ACL-IQ was fully computerized and made available online (www.ACL-IQ.org). Item sampling/reduction, reliability analysis, cross-validation, and convergent/discriminant validity analysis were conducted to optimize the efficiency and validity of the assessment. Results: Psychometric optimization techniques identified a short (mean time, 2 min 24 s), robust, 5-item assessment with high reliability (test-retest: r = 0.90) and consistent discriminability (average difference of exercise science professionals vs general population: Cohen d = 1.98). Exercise science professionals and general population individuals scored 74% and 53% correct, respectively. Convergent and discriminant validity was demonstrated. Scores on the ACL-IQ were most associated with ACL knowledge and various cue utilities and were least associated with domain-general spatial/decision-making ability, personality, or other demographic variables. Overall, 23% of the total sample (40% exercise science professionals; 6% general population) performed better than or equal to the ACL nomogram. Conclusion: This study presents the results of a systematic approach to assess individual differences in ACL injury risk factor estimation skill; the assessment approach is efficient (ie, it can be completed in\3 min) and psychometrically robust. The results provide evidence that some individuals have the ability to visually estimate ACL injury risk factors more accurately than other instrument-based ACL risk estimation methods (ie, ACL nomogram). The ACL-IQ provides the foundation for assessing the efficacy of observational ACL injury risk factor assessment (ie, does simple skilled visual inspection reduce ACL injuries?). It also provides a representative task environment that can be used to increase our understanding of the perceptual-cognitive mechanisms underlying observational movement analysis and to improve injury risk assessment performance