Relationship between functional movement screening score and history of injury and identifying the predictive value of the FMS for injury

Abstract

This study aimed to reveal the functional ability of functional movement screening (FMS) scores in determining an athlete's predisposition to injury. One hundred (50 females and 50 males) university level athletes, weight of 69.44 ± 5.84 kg, height of 172.69 ± 7.26 cm, age of 22.56 ± 2.99 years and Baecke score 21.66 ± 1.73, practised in football, handball and basketball sports (at least for 5 years), with no recent (<6 weeks) history of musculoskeletal injury were recruited. Of the 100 subjects, 35 of them suffered an acute, lower extremity (ankle = 20 and knee = 15 subjects) injury. An odds ratio was calculated at 4.70, meaning that an athlete has an approximately 4.7 times greater chance of suffering a lower extremity injury during a regular competitive season if they score less than 17 on the FMS. This study provides FMS reference values for university level athletes that will assist in the interpretation of individual scores when screening athletes for musculoskeletal injury and performance factors. More research is still necessary before implementing the FMS into a pre-participation physical examination for athletics, but due to the low cost and its simplicity to implement, it should be considered by clinicians and researchers in the future.

Keywords:

• pre-participation screening
• functional movement screening
• injury risk
• athletic performance
• university level athletes

Acknowledgements

Gratitude is expressed to the subjects who participated in this study as well as to each of the assistants who were instrumental in the collection of the data. The researchers independently collected, analyzed and interpreted the results and have no financial interests in the results of this study. Also, dissemination of the results in this study does not constitute endorsement by the researchers or their institutional affiliations.

Notes

1. Subjects with a score above 20 in the Baecke questionnaire was considered in active persons.

2. Receiver operator characteristic curve is a plot of false positives against true positives for all cut-off values. The area under the curve of a perfect test is 1.0 and that of a useless test, no better than tossing a coin, is 0.5. Many clinical tests are used to confirm or refute the presence of a disease or further the diagnostic process. Ideally, such tests correctly identify all patients with the disease, and similarly, correctly identify all the patients who are disease free. In other words, a perfect test is never positive in a patient who is disease free and is never negative in a patient who is in fact diseased. Most clinical tests fall short of this ideal.