Home Rehab The Functional Movement Screen (FMS) is NOT a predictor of injury (Mini-series Part 1).
The Functional Movement Screen (FMS) is NOT a predictor of injury (Mini-series Part 1).

The Functional Movement Screen (FMS) is NOT a predictor of injury (Mini-series Part 1).


Part 1 of a collaborative mini-series:

The Functional Movement Screen (FMS) is NOT a predictor of subsequent injury based on composite score. It’s time to stop beating a dead horse. This is not to say it doesn’t have it’s place, nor am I bashing the FMS, as it’s developers are fantastic clinicians who should be recognized for their research, thought process and commitment to understanding movement.

I’m going the keep this one short, but the biggest limitation in ANY movement screen is making the assumption that there are “abnormal” or “flawed” movement patterns. (By the way, there’s no need to center out the FMS here; I only use it as an example because it’s the most widely known movement screen.) Put simply: these movement ‘flaws’ likely don’t exist. Consider this: variable anthropometrics (i.e. the measurements and proportions of the human body) and anatomy ALONE dictate that people MUST move very differently under biomechanical frameworks. In other words: we’re not all built the same, so we won’t all move the same. Not to mention the previous two factors are only the tip of the iceberg when it comes what affects how we move. So you see, it can be hard to try to standardize an ‘ideal’ movement pattern. The very fact that so many athletes and regular folks alike move ‘weird’ and are completely happy, pain free and performing just fine should speak to the fact that these ‘abnormal’ patterns are probably just NORMAL after all. To add to that, research looking into these so called “bad” movements and whether or not they increase the likelihood of subsequent injury is lacking significantly.

Here are a few other problems with movement screening:
• They give no consideration to tissue loading/capacity—an athlete may move differently to what is considered ‘ideal’ but have incredible tolerance to this. Consideration of the QUANTITY of loading over time is likely a better predictor of pain and injury.
• Screens assume if you move ‘poorly’ in an unloaded/body weight task you will subsequently move ‘poorly’ in a loaded task—however, many people move better under load. A simple example is the use of a Goblet Squat to improve patterning of people who have trouble moving into functional dorsiflexion during a squat.
• The screening movements used don’t transfer well to certain sports or other activities of daily living, especially when load and/or speed is involved.
• Just because you CAN move a certain way, doesn’t mean you WILL.
• Movement screens can miss aspects of motor control. Using the dorsiflexion example once more: an athlete may have fantastic functional ankle dorsiflexion as measured by a knee to wall test, but seemingly cannot access that range when performing a body weight squat. This is a control issue: the athlete has the range to accomplish the task, but lacks the mobility/motor control to do so).
I’m sure there are many others however this is all I can think of off the top of my head.

However we shouldn’t completely throw away movement screening. They certainly still have a lot of value. What I do love about them is they tell me a lot about how people CHOOSE or DEFAULT to move. Maybe they’ve developed movement habits that they persist into–and they can’t break away from; this can sometimes be the start to sensitized or painful movement. Watching how people choose to move can be a valuable start to rehabilitation! Find out what’s meaningful to your patients/clients and start making your own screens!

If you are going to use the FMS or any movement screen, just make sure you use it purposefully, and not for reasons they aren’t supported for: like predicting injury.

As always: Don’t sit still! Make moves.

Nick Hannah, PT
Registered Physiotherapist

Paper influenced by:

Moran R et al. Do Functional Movement Screen (FMS) composite scores predict subsequent injury? A systematic review with meta-analysis. BJSM 2017; 0:1-10.


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