Rate of Perceived Exertion

Everything changed when the stethoscope was invented. Credit Rene Laennec, the 18th-Century French physician and flautist who invented this revolutionary device. Laennec liked to carve his own flutes out of wood, and it was these musical instruments that gave him the inspiration for the medical instrument that has become a symbol of the entire medical profession.

Calling the stethoscope revolutionary is not hyperbolic, for it enabled doctors for the first time to assess the internal health of individuals without reference to how they felt. No longer did patients need to experience pain or some other interoceptive sign that something was wrong with them for physicians to know (or believe) something was wrong with them. Many more technologies that did essentially the same thing in different ways followed, so that in historical hindsight the stethoscope marks the beginning of a modern pivot toward diagnosis-centered medicine, where clinicians place a high priority on identifying health conditions by type, which allows for the best (or most accepted) treatment for each type to be applied.

This cartesian paradigm, where patient subjectivity is regarded as worthless and objective diagnostics are treated as the word of God, has wrought unfortunate consequences, defying Hippocrates’ exhortation to “do no harm.” Yet the consequences are not limited to the medical domain. The dualistic mindset that privileges measurement over qualia has overtaken the entire collective consciousness, not excluding the minds of athletes, coaches, and sports scientists. This is problematic, because feelings and perceptions are and will always be the most reliable source of actionable information for those invested in athletic performance.

Take running shoes, for example. For decades, footwear manufacturers tried to design shoes that improved efficiency and reduced injury risk in individual runners by matching anatomical and biomechanical characteristics such as arch height against design features such as medial posting. Ignored in all this analysis and measurement was how the shoes actually felt on the runner’s foot, an act of scientific arrogance that has been rewarded with well-deserved embarrassment, as research has consistently shown that the traditional paradigm for matching shoes with runners neither improves efficiency nor reduces injury risk, while simply allowing runners to select shoes based on comfort does.

Even more consequential is the failure to properly value athletes’ subjective response to training. Objective training metrics can be useful, because whenever subjective and objective measures disagree on how hard a workout is or how close to the limit an athlete is, the athlete’s perceptions are always right. That’s because endurance performance is ultimately limited by perception. Athletes quit when they feel they cannot continue, regardless of what the measurements say.

The latest evidence that subjective assessments of training are more dependable than objective measurements comes from a study conducted by researchers at Ghent University and published in the International Journal of Sport Physiology and Performance. The subjects were eleven male recreational cyclists, each of whom completed five separate 3 KM time trials, one to establish a baseline and the other four to assess the effect of prior training on performance, as they were done immediately following completion of a workout.

The researchers calculated the training load of the four workouts using seven different methods, six of them objective (including four measures of training impulse, using heart rate data as an import, and two measures of training stress, using power data as an output) and one subjective (rate of perceived exertion). The degree to which time trial performance declined from baseline was used as a standard representing how stressful the preceding workout was in reality vs. theoretically. This allowed the researchers to assess how accurate each method of calculating training load (TL) was in estimating the actual impact of the workout on the athlete.

Can you guess which method was most accurate? Bingo! “TL using the rating of perceived exertion was the only metric showing a response that was consistent with the acute performance decrements found for the different training sessions,” the study’s authors concluded.” In other words, simply asking the athlete how hard they felt the workout was resulted in not just the most accurate indication of how hard the workout really was but the only accurate indication of how hard the workout was.

As technology continues to penetrate all reaches of endurance sports, more and more athletes are getting hopelessly caught up in the diagnostic mindset that regards feelings, emotions, and perceptions as noise and objective data as infallible signal. It’s an unfortunate situation, but one that presents a tremendous opportunity to athletes capable of thinking for themselves instead of passively absorbing the prevailing mindset. The surest path to reaching your full potential as an endurance athlete is to monitor only the most essential data, and not too closely, while giving most of your attention to qualia and factoring them more heavily into your training decisions than you do the modern equivalents of stethoscope readings.

In endurance sports we toss around the word “intensity” as if this word had a clear, singular, and consensual definition. In fact, it is not, and I doubt it ever will. “Why not?” you ask. Because exercise intensity is not a unitary phenomenon. Our problem is not that we have so far failed to discover what intensity is but that there is nothing—no thing—to discover.

This reality was highlighted by a terrific new study appearing in the European Journal of Applied Physiology. It was conducted by the esteemed Alexis Mauger and colleagues at the University of Kent and involved seven recreational cyclists (average VO2max 52.4 ml/kg/min) as subjects. There were two parts to the experiment. In the first part, a pair of incremental exercise tests were performed to identify each subject’s gas exchange threshold (a rough equivalent to the lactate threshold) as well as the intensity corresponding to 115% of power output at the gas exchange threshold (a rough equivalent to critical power). Not only wattage, but also heart rate, oxygen consumption, blood lactate, and perceived exertion were measured

In the second part of the experiment, the subjects returned to the lab on six occasions and rode for 30 minutes, thrice at the perceived effort rating that corresponded to the gas exchange threshold (which averaged 13 on the 6-20 Borg scale) and thrice at the RPE corresponding to GET +15% (which averaged 14.7, though whole numbers were used with each individual). Because RPE tends to increase at any fixed power output, it was expected that subjects’ power output would gradually decrease over the course of 30 minutes as they obeyed instructions to maintain a perfectly steady RPE, and this is precisely what happened.

The results were interesting, to say the least. You can access the complete results by clicking on the hyperlink provided above, then scrolling down and clicking on “Table 1” and “Table 2.” But for your convenience, a summary is given here.

30:00 @ GET 30:00 @ GET +15%
RPE Steady at 13 Steady at 15
Power Modest decline from 184W to 175W Significant decline from 219W to 193W
Heart Rate Significant increase from 144 BPM to 158 BPM Significant increase from 159 BPM to 171 BPM
Oxygen Consumption Steady at 33 ml/kg/min (with very slight increase to 35 ml/kg/min at the end) Steady at 39 ml/kg/min
Blood Lactate Significant increase from 2.46 [La]b to 4.26 [La]b Significant increase from 3.36 [La]b to 6.7 [La]b

As you see, according to RPE, the intensity is steady, whereas according to power, the intensity is decreasing, and according to heart rate, the intensity is increasing, and according to oxygen consumption, the intensity is steady, and according to blood lactate, the intensity is increasing. I’m reminded of the parable of the blind men and the elephant, where one man grabs the trunk and says, “This being is like a snake,” another wraps his arms around a leg and says, “No, it’s like a tree,” a third touches its flank and says, “No, it’s like a wall,” and still another grabs the tail and says, “No, it’s like a rope.”

The lesson of the study I’ve described, I believe, is the same as the lesson of this parable: Beware the illusion of completeness! Just as touching one part of an elephant and assuming it’s the entire elephant results in an inaccurate description of the elephant, measuring intensity with a single metric and assuming that this measurement paints a complete picture of intensity results in dubious assessments of how hard an athlete is exercising and how it’s likely to affect them.

I’m not suggesting that athletes and coaches ought to measure everything. This would be not only foolish but also impossible, as there are plenty of intensity-related processes going on inside the body that aren’t even measurable with existing technology. I think it’s enough for athletes and coaches simply to be aware that intensity is complicated and multifaceted and that no single intensity metric tells the whole story. Combine this awareness with common sense and you should be good to go.

As a final note, I will add that the nearest thing to a complete picture of intensity is perceived effort. Prior research has indicated that perceived effort is linked to activity in brain areas involved in generating muscle contractions as well as to efferent signals sent to the brain from the respiratory muscles. Because the brain has to work harder to generate the same amount of muscle work as the muscles fatigue, perceived effort simultaneously accounts for muscle activation, fatigue, and breathing rate. Not to mention, perceived effort exists not in isolation but in the context of an overall consciousness that is able to interpret perceived effort based on awareness of time elapsed, time remaining, past performance—and yes, external feedback from such things as power meters and heart rate monitors. And it’s the only indicator of intensity that becomes more reliable with repeated use.

There are coaches out there, unfortunately, who fall for the illusion of completeness and treat things like blood lactate measurements as perfect proxies of intensity. I do not. Instead, I focus on developing each athlete’s perceived effort instrument to its full capacity, with the ancillary support of objective indicators of intensity. Frankly, I think this makes me a better coach than the lactate wonks, and the study at the center of this post supports my assertion.

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