 Normative data  Validity  Reliability  Sensitivity  specificity

 209 individuals, 108 female 101 male  Mean score was 15.7 with a standard deviation of 1.9  Median of 16  Range from  Inter-rater reliability was.971

 Similar mean composite score  Males scored better on rotary stability and trunk stability push up  Females performed better on active straight leg raise and shoulder mobility

 test actually measures what it is setting out to measure.

 identify compensation patterns as they are performed in sport  Whether such compensation patterns are detrimental to performance or injurious and whether the FMS is able to predict such reduced performance

 Closed testing environment versus open unpredictable playing environment

 knowledge of the ability to perform a perfect score led to a significant improvement in FMS score from 14.1 ± 1.8 to 16.7 ± 1.9 points. Therefore, the researchers concluded that changes in FMS score may not therefore reflect actual changes in the mobility, stability or co-ordination of an athlete but rather simply a knowledge of what the tester requires.

 Knowledge of a screen/assessment shouldn’t change the results  If I do an impingement test telling you what it’s for should change anything

 The number one risk factor for a future injury is a previous injury.- Gray Cook  No statistically different in scores between those who reported previous injury and those who did not- “functional movement screen normative values in a young, active population”

 Past injury is probably a risk factor for future injuries — for instance, the reasons for the original injury may persist and cause re-injury, or a new injury. If FMS cannot detect any sign of recent injuries, it seems unlikely that it can detect future risk, let alone be used as a basis for a specific therapy

 the researcher investigated the capability of the FMS to predict injury rates in 57 (26 male and 31 female) division I track and field athletes. They took pre- season FMS scores and then monitored the incidence of injury during the season. They found that 9 of the 57 subjects suffered an injury that resulted lost playing time for >4 days. The researcher found no statistically significant difference between the pre-season FMS scores of injured (15.9 ± 1.8 points) and non-injured (15.6 ± 2.7 points) groups, nor did they identify any ideal cut-off point for differentiating between injured and non-injured athletes.  article=1177&context=gradreports article=1177&context=gradreports

 Risk of injury 2x greater with FMS scores < 14  PT scores were just as predictive of future injury as FMS scores with a higher sensitivity

 Cumulative injury incidence was higher at FMS scores of 18 compared to FMS scores of 17.  The risk of injury was significantly higher in the 18 category for the LC group, which suggest a bimodal distribution.

 Although asymmetries were assessed and recorded, no statistical evidence supported asymmetry as a risk factor for injury.  Mean FMS scores of /- 1.7 for those who had “no” injury were comparable to those who suffered “any” injury (16.7 +/- 1.8).

 The odds of sustaining a serious injury was 11.7 times higher in those with an FMS score 14

 at least 18 studies have assessed whether the FMS score can predict the incidence of injury. Of these 18 studies, 11 have assessed the relative risk of individuals with an FMS score of ≤14 points being injured in comparison with individuals with an FMS score of >14 points. Out of these 11 studies, 4 found that the FMS could not predict injury risk. In the remaining 7 studies, the relative risk was between 1.65 – times, which suggests that the FMS may well differentiate between individuals who are at a greater or lesser risk of injury.

 measures the proportion of actual positives which are correctly identified as such  Positive with high sensitivity means you have what the tester is testing for  If a test is highly sensitive and the result is negative you can be certain what is being tested for won’t happen

.54 for professional football players .45 for marine officer candidates and.12 for same population for serious injury .083 for marathon runners .54 for basketball players

 measures the proportion of negatives which are correctly identified as such  If you’re negative for the test you don’t have what the test is testing for  If the test is highly specific and positive you can be certain that the person will get hurt.

.91 for professional football players .71 for marine officer candidates and.94 for serious injury .95 for marathon runners .52 for basketball players

 this principle describes whether a test can be repeated either by the same person at a slightly different time (intra- rater) or by different people at the same time (inter-rater) and produce the same result.  FMS has high reliability

 FMS is a set of physical tests intended to “identify assymetries and limitations,” based on the assumption that they are a problem — classic structuralism  This has lead to us using a lot of “corrective” exercise

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