By Anthony Roberts
We need to file this one under the HOLY SH*T category! In the past we’ve been forced to rely on inaccurate measures of fatigue such as heart rate or subjective measures of fatigue such as Rate of Perceived Exertion (“on a scale of 1-10, how tired are you?”). But it appears that those days are over, as a new test has been developed through The United States Airforce, the results of which have been published in the Military Medicine Journal.
The research was performed on candidates in the Tactical Air Combat Party school. The what?
The Black Berets – the guys whose motto is “Death On Call.” These Air Force specialists are tasked to Army combat maneuver units worldwide to form a tactical air control party team that plans, requests and directs air strikes against enemy targets in close proximity to friendly forces. These Airmen work in a two man team, not like Maverick and Goose, but rather on the battlefield as part of an Army forward operations ground unit. They might parachute down with the 82nd Airborne, or find themselves behind enemy lines with a Ranger Unit. They’re the best of the best that the Airforce puts on the ground to fight alongside Army. And in the end, these guys have possibly the worst job in the Airforce – making sure bombs are on target when there’s friendlies nearby.
So it’s no surprise that both the Army and Airforce wanted to develop a way to measure their fatigue levels , but also the potential of new candidates for making it through the hellish TACP schooling. Funding for this research was provided through both the US ARMY and USAF.
In this study, 126 candidates for the Tactical Air Combat Party were given a battery of salivary hormone tests, from which two peptides were ultimately found to be reliable for the prediction of a fatigued state as well as being able to predict the ability of a candidate to make it through TACP candidate school. Although I’m still struggling my way through the 42 page patent, it appears that the difference between two peptides located in saliva can accurately diagnose a fatigued state. Furthermore, the respective levels and difference in levels between these two peptides can also predict physical performance capability.
As a simple analogy, imagine that one of these two newly discovered peptides represented volume for the gas tank of a car and the other represented the level of gas in the tank. We could then see how big the tank was and how much gas was in it. All other factors being equal (knowing the MPG, etc..), we could then predict how far the vehicle could travel. We could also predict how fatigued the car was, i.e. how much gas relative to the size of the tank is left.
When this test was performed on TACP candidates, it was found that these salivary peptides were the third most important correlative factor in their ultimate completion of the schooling, behind their run times and number of miles run per week in the past year (again, two very reliable physical tests for predicting success in SpecOps schooling). Guys who scored high on the predictive portion of the test were far more likely to drop out of the program, while guys who scored higher were faster, had put in more miles in the preceding year, and ultimately had a far greater chance of making it through.
Mil Med. 2011 Apr;176(4):431-7.
Predicting success in the tactical air combat party training pipeline.
Kalns J, Baskin J, Reinert A, Michael D, Santos A, Daugherty S, Wright JK.
Hyperion Biotechnology, 13302 Langtry Street, San Antonio, TX 78248, USA.
To develop a statistical model that predicts the likelihood of success or failure of military training candidates using tests administered before initial skill training as inputs.
Data were acquired from candidates before the start of U.S. Air Force Tactical Air Control Party training, including (1) demographic, (2) psychological composition evaluated using Emotional Quotient Inventory, (3) physical performance capability, (4) a physical activity questionnaire, and (5) salivary fatigue biomarker index. A total of 126 candidates were tracked until they either passed or failed the training, and a total of 55 variables were used as inputs for creation of the model.
Clustering analysis of the data revealed that only 4 of 55 variables were useful for predicting success or failure. The variables in the order of their importance are as follows: run time, number of miles run per week in the last year, level of salivary fatigue biomarker, and height.
The results suggest that simple testing methods can identify candidates at high risk of failure.
[PubMed - indexed for MEDLINE]