Any normative data that is displayed against an individual test result for a profile is based on data collected from tests conducted on VALD products. Each test performed on a VALD device is stored securely in our databases and is used for normative data calculations. Once a certain test threshold limit has been reached for a particular metric, these are utilised to present "norms" based on demographic data such as age and sex.
The data science team at VALD will firstly ensure that the data provided is valid and reliable, then generate a distribution using IQR.
The 1.5 IQR rule is a commonly used method to identify potential outliers in a dataset. This method finds the difference between the lower quartile (25th percentile) and upper quartile (75th percentile) to obtain an IQR. Any result more than 1.5 times the IQR away from the upper or lower quartile is considered an outlier and removed from the normative data calculation.
As you conduct additional tests on your VALD products, this test data will be used to further increase the accuracy of the normative data being referenced. The normative dataset will be refreshed periodically to display up-to-date normative data.
How does it compare an individual to the "norms"?
The test result for the individual profile will be compared against the most relevant age and sex grouping for that user.
This is currently limited to tests conducted on ForceDecks systems, however, will expand to other products in the VALD suite soon.
For strength metrics, the normative data sets are sex specific. For quality of movement metrics (range of motion, asymmetry, etc.), this will compare all test results regardless of sex.
Normative data is not intended to provide an indication of whether a result is good or bad. It is simply a measure of the patient's result against the existing dataset collected from other tests conducted on VALD systems.
While normative data is validated internally by our data scientists once a certain threshold is met, this data is not validated externally through any relevant medical research. Normative data is based only on what other VALD product users have produced.
Currently normative data in VALD Hub is limited to demographic data - namely age and sex.
If age and sex fields are incorrectly entered when an organisation is creating profiles in VALD Hub, this can affect the accuracy of the normative data. It is therefore imperative to ensure accurate data entry when entering patients and athletes into your VALD Hub.
Normative data cannot be toggled off, either on a per-user or per-profile basis.
Normative data is also limited to tests conducted on ForceDecks systems* at this time. Expansion into other VALD systems, as well as the ability to compare different datasets (e.g. males to females, 40-year-olds to 20-year-olds, etc.) will be available in a future release.
* We are currently only able to provide normative data for the following ForceDecks test types:
- Countermovement Jump
- Loaded Countermovement Jump
- Squat Jump
- Loaded Squat Jump
- Squat Assessment
- Single Leg Jump
- Isometric Mid-Thigh Pull