Each month we compile a short-list of recently-published papers (full list here) in the world of running science and break them into bite-sized chunks so you can digest them as food for thought to help optimise your training. To help wash it all down, we even review our favourite beer of the month.
Welcome to this month's installment of our "Nerd Alert". We hope you enjoy it.
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Click the title of each article to "drop-down" the summary.
What was the hypothesis or research question?
The external load (e.g. pace, power, or speed) of different exercise modalities cannot be easily compared and the concepts of external and internal (e.g. the psychological and physiological response to external load) load do not have a “gold standard” measure that can be used across modalities. This paper is a commentary and had no hypothesis but the authors sought to determine the influence of exercise modality on training load management by examining physiological and biomechanical mechanisms associated with different endurance exercise modalities.
What did they do to test the hypothesis or answer the research question?
— The authors built a theoretical framework (Fig. 1 below) showing the impact of physiological and biomechanical mechanisms on training loads of different endurance exercise modalities.
— Next, they compared effort-matched low-intensity training sessions performed by world-class endurance athletes competing in long-distance running, road cycling, swimming, rowing, XC skiing and speed -skating.
What did they find?
— The authors argue that sustaining high power output is necessary but not sufficient for endurance performance because of the need to reduce air resistance, which helps sustain power with manageable muscular loads and low injury risks.
— Therefore, they argue that the choice of endurance exercise modality in training will affect the cardiovascular and muscular effort beyond those measured by commonly used external and internal load metrics.
— The authors also pose that the tolerable amount of repetitions (i.e. to minimise structural damage/overload) differs between endurance exercise modalities and, therefore, the duration of a training session within a specific intensity zone (and, by extension, “solving the training program puzzle”) will be highly-influenced by the choice of exercise modality.
— By comparing data from low-intensity steady-state sessions between exercise modalities (see Table 1), they found that the duration of sessions are shortest (45-90-minutes) in runners (likely due to load-bearing action) and speed skaters (likely due to blood flow restriction caused by position) and greatest in cyclists (3 to 5-hours). Yearly training volume follows a similar pattern.
— They speculate that runners have a high injury/overload risk and a low volume tolerance when compared to cyclists, swimmers, and skiers.
— The authors conclude to say that the “choice of exercise modality in endurance training influences effort beyond commonly used external and internal load measurements and should be considered alongside duration, frequency and intensity when managing training load”.
What were the strengths?
— A nice simple overview of training volumes and training load expectations of world-class athletes from diverse endurance disciplines.
What were the weaknesses?
— No additional knowledge about training load management.
Are the findings useful in application to training/coaching practice?
Yes, the sentiments of this narrative are useful to know but the authors’ conclusion does not add new info for a coach’s toolbox. I.e. the info provided in the paper does not help a coach or an athlete optimise their training load management. That said, it is always important for runners and those coaching runners to remember that running is a weight-bearing activity with high impact forces that are further exaggerated on trails or in the mountains. This is an important consideration when planning training load progressions and/or when planning to weave strength training (including plyometric sessions) into a running programme.
What was the hypothesis or research question?
Strenuous exercise is reported to damage the epithelium in the gastrointestinal (GI) tract but the dose-response relationship between exercise intensity and GI damage is unknown. It is also speculated that running causes more GI damage than cycling but this has not been objectively compared. Therefore, the authors completed two studies, first to quantify the relationship between exercise intensity and intestinal damage and secondly to determine if running is associated with greater intestinal damage than energy expenditure-matched cycling. No hypothesis was stated.
What did they do to test the hypothesis or answer the research question?
— All participants were young (25 years old), healthy, moderately-trained (VO2max ~ 50 ml/kg/min) adults without GI disease.
— Study 1 measured changes in the blood levels of intestinal fatty acid binding protein (I-FABP), a marker of GI damage, after 60 mins of exercise at three different intensities (40, 60 and 80% of V̇O2max) on 3 separate days.
— Study 2 measured changes blood levels of I-FABP after 45 minutes of running and cycling at the same absolute V̇O2 (70% of cycle ergometer VO2max).
— Venous blood samples (for measurement of plasma I-FABP) were collected and GI symptoms were reported at baseline and immediately after each exercise bout.
— Participants completed the trials in each study in a randomised order.
What did they find?
Study 1:
— I-FABP levels were more greatly raised in the 80%VO2max trial (large effect size of d = 1.16) compared to 60% (small effect size of d = 0.43)and 40% (negligible effect size of d = 0.22) trials. The 60% and 40% trials were not different from each other.
— When exercise intensity was expressed as a percentage of subject’s second ventilatory threshold (VT2; anaerobic/lactate threshold), there was a significant relationship between higher exercise intensity and higher plasma I-FABP levels (r2 = 0.60, p < 0.0001).
— 4/10 participants reported GI symptoms during the 40% trial, 6/10 reported
symptoms during the 60% trial and 8/10 during the 80% trial. The most common symptoms were
belching, bloating and the urge to defecate.
Study 2:
— The percentage increase in I-FABP was significantly higher following cycling (+ 84.7%) compared to running (+ 19.3%; p = 0.024, moderate effect size of d = 0.68).
— GI symptoms were reported by 5/11 participants during running and 3/11 during cycling. All symptoms were reported to be mild (3 or less on a 10 point scale). Across both studies, 6/11 of participants reported no symptoms.
Summary of studies:
— The authors concluded that increasing exercise intensity is associated with greater intestinal damage and that the individual VT2 may be more predictive of the intensity that induces intestinal damage, when compared to fraction of V̇O2max. They also concluded that the mechanical stress of running does not appear to cause additional GI damage and that the physiological intensity of the exercise rather than the mode of exercise is a greater contributor to GI dysfunction.
What were the strengths?
— Plasma measurements of I-FABP were adjusted to account for changes in plasma volume that concur during exercise.
— Effect sizes were reported.
— The authors noted that relative percentages of VO2max may elicit different metabolic stress because of differences in training status. For example, 70% of VO2max may place a lesser trained person above their second ventilatory threshold (VT2; anaerobic/lactate threshold) while exercising at 70% of VO2max may put a highly-trained athlete below their first ventilatory threshold (VT1; aerobic threshold). So, the authors also reported their data in terms of percentage of VT2
What were the weaknesses?
— Power calculations were not used to justify the sample sizes of people studied.
— The dose-response between intensity and GI damage (study 1) was only examined during cycling and not running.
— I-FABP circulating in the blood is a generalised marker of GI damage and tells us nothing about where the damage has occurred and/or whether there are any functional impairments (such as decreased gastric emptying or intestinal absorption of nutrients).
— A single immediate post-exercise blood sample simply provides a snapshot of I-FABP and does not provide a profile of changes in I-FABP during or following exercise.
— In study 2, prescribing the intensity of running and cycling as 70% of cycling VO2max would, naturally, create a difference in workload between exercise modalities. Consequently, they found that subjects had a higher heart rate, RPE, rectal temperature, and thermal stress sensation during the 45-min cycling bout compared to running, indicating that the ride had a higher training load than the run. Since VO2 was measured real-time during the bouts, the workload could have been adjusted to create the same absolute VO2, therefore matching energy expenditure between trials.
— We are not told anything about the subjects’ dietary habits, susceptibility to exercise-induced GI distress, or feeding status at each exercise bout.
Are the findings useful in application to training/coaching practice?
Yes.
GI problems are documented to be common in athletes, especially during races. Despite some of the weaknesses of this study, the data add to existing evidence that GI issues and GI damage may be more likely at greater exercise intensities. Therefore, it is important to consider this in your training or in your athletes’ training, especially if they are prone to GI issues. GI issues can arise due to poorly-timed and/or large meals before exercise or reactions to foods ingested during exercise but they can also occur under extreme conditions such as heat. Trial and error with your feeding practices will help resolve most GI issues during exercise but if GI problems persist always consult your GP for a referral to a GI specialist to rule out any underlying disease.
What was the hypothesis or research question?
Prior observational studies report that long-distance runners with larger cross-sectional surface area of the psoas major muscle (aka, the hip flexors) have a faster 5000 m running time. Therefore, the authors aimed to test the causality of this correlation. No hypothesis was stated.
What did they do to test the hypothesis or answer the research question?
— Eight young (20 years old), well-trained (VO2max ~70 mL/kg/min) male long-distance runners with a recent 5000-m personal best of 15:10.0 ± 0:20.5 were enrolled in a non-randomised 12-week training intervention.
— Fitness (VO2max, lactate threshold, and running economy), performance (time-to-exhaustion at velocity at VO2max; vVO2max), and cross-sectional surface area (using MRI) of the psoas major were measured before and after the 12-week intervention.
— The 12-week intervention included running sessions on 6 times per week and resistance exercise sessions on 3 times per week.
— Running included one interval session per week (repeats of 1km ot 2 km at 18.0–20.0 kph), one tempo run per week (8 to 12 km at 16.3–18.0 kph), and four 60- to 90-minute jogs per week, without any high-intensity training (e.g. sprinting) that would stimulate the psoas major.
— Resistance sessions were designed to induce muscular hypertrophy of the psoas major and included V sit-up with medicine ball, hip flexion with equipment, and hanging leg raises, 3-sets × 10-reps with 1-minute recovery in the first 4-weeks then 4-sets × 10-reps with 1-minute recovery
during the last 8 weeks.
What did they find?
— There was a significant (P<0.01) but small (effect size 0.34) pre to post-intervention increase in psoas major cross-sectional surface area.
— There was a significant (P < .01) and large (effect size = 1.41) pre to post-intervention increase in time-to-exhaustion at vVO2max (500±108 vs. 715±186 seconds) but no change in VO2max, velocity at 2 or 4 mM lactate, or running economy.
— Multiple regression showed that the pre to post change in the time-to-exhaustion at vVO2max was significantly (β = 0.746, r2 = 0.556 i.e. a large effect size, P = 0.034) correlated with the pre to post change in CSA of psoas major cross-sectional surface area but not with the pre to post change in VO2max, the velocities at 2 and 4 mmol/L of blood lactate, or running economy.
What were the strengths?
— The runners’ hips. (Joke).
— Effect sizes were reported.
— The intervention has a high level of ecological validity (conducted in the field in highly-trained runners).
— The runners were familiar with strength training but had never completed resistance exercise focussed on hip flexor muscles.
What were the weaknesses?
— Power calculations were not used to justify the sample of runners.
— Only males athletes were studied.
— No non-resistance exercise control group and, therefore, no randomisation. As a consequence of a lack of a control group it is not possible to assign changes in performance to the hip flexor strength exercise intervention because the running training may have contributed.
— Without documentation of recent training load, we cannot know whether the 12-week running intervention was a large volume and/or more intense (i.e. a larger training load) and therefore the potential cause of the increase in performance.
— The intensity of resistance training is not provided. E.g Useful variables like target RPE, reps-in-reserve, or load lifted are not reported.
Are the findings useful in application to training/coaching practice?
Yes.
Strength training, especially that which aims to increase the rate of force development, has been shown to improve running economy and, in some cases, performance in already trained runners. It is likely that hip flexor strength plays a role in running performance. In this study, the disappointing lack of a non-strength training control group and the lack of prior running training details makes it difficult to conclude that hip flexor-specific strength training will directly increase performance because it is possible (in this study) that the improved performance was caused by an increase in running training load. That said, the sole use of resistance exercises targeting the psoas major muscle combined with the multiple regression showing a large effect size for the relationship between the change in psoas major muscle size and time-to-exhaustion at vVO2max provides credible evidence that adding hip flexor hypertrophy training into a trained-runner’s strength programme may be advantageous. That said, larger and better-controlled studies that include women would be needed to bolster this evidence.
What was the beer called?
Noa Pecan Mud Cake Stout.
Which brewery made it?
Omnipollo. Gothenburg, Sweden.
What type of beer is it?
Imperial / Double pastry Stout.
How strong is the beer (ABV)?
11 % ABV.
How would I describe this beer?
A slightly nutty aroma (think: “it’s a bit nutty, Basil”) with a slightly sweet and rich feel on the tongue. On the way down it is as thick as its name suggests but is smooth and chocolatey with an aftertaste reminiscent of a visit to your favourite coffee shop. If you like stout, get this in your belly.
What is my Rating of Perceived beer Enjoyment?
RP(be)E(r) = 9 out of 10.
What was the hypothesis or research question?
Predicting the performance of ultra runners is hard due to the difference demands of different race distances, terrains, etc. The goal of this research was to determine if there were specific physiological indicators that would predict performance across a range of race distances on the same day on the same course.
What did they do to test the hypothesis or answer the research question?
— Recruited 51 runners registered in the Sulphur Springs trail races in Ancaster Canada for the 50, 80, or 160km runs that were done on the same 20km loop of course.
— Within a month before the race the subjects underwent VO2max testing, running economy measurements (last stage before ventilatory threshold) heart rate variability measurements, blood draws, training and racing questionnaires, and a few other basic anthropometric measurements.
— On the day of the race the subjects had their body weight measured and dehydration levels were assessed immediately after the race.
— Statistically they compared the various metrics between the different race distances (and non-finishers) and looked for the strongest correlations between their measurements and race finishing time as a percentage of the winning time.
What did they find?
— In general as the distance increased the strength of the relationship between variables and finishing time weakened with none of the variables associated with finishing performance in the 160 km distance.
— In the 50k distance, many physiological variables were associated with performance with training volume in the last month, average volume over the last year, peak speed at VO2max, body mass loss during the race, resting heart rate, and BMI all showing significant correlations (p < 0.05) of moderate to strong effect sizes (absolute r-values ranging between 0.68 and 0.93)
— In the 80km race, only peak velocity at VO2max was associated with better performance and it was correlated to a lesser degree than 50km race.
What were the strengths?
— The same course on the same day.
— Decently broad measurements.
— Racers in different distances were pretty similar physiologically speaking.
What were the weaknesses?
— Different people in different races.
— Lab tests were up to a month out.
— Did not assess many other likely important factors such as race day nutrition, use of anti-inflammatories, GI issues.
— Sample size for each of the race distances was relatively small and a lot of variability existed in the 160km group which may explain why there were no associations found.
Are the findings useful in application to training/coaching practice?
Yes, as coaches we need to focus not just on fitness and training volume for longer ultras but likely psychological and nutritional components as well. There are just so many other variables that play a role in performance in long races. In 50 km races we can still rely on aerobic capacity and more “traditional” measures of endurance performance. Longer races are like polygenic diseases with so many genes contributing just a little to the disease whereas shorter ultras (and marathons) are more like diseases with only a few genes involved and easier to predict what will happen based on someone's genetics.
What was the hypothesis or research question?
Language modifies many aspects of behavior. We spend a lot of time performing self-talk and therefore an interest in how organic (rather than purposeful) self-talk may be related to sports performance. Generally our self-talk should match the task we are performing and therefore the authors hypothesize that the type of self-talk we undertake will vary depending on the type of sport we are performing. Specifically, sports involving fine motor control require more instructional self-talk, while endurance sports require more motivational self-talk. Self-talk is frequently used by endurance athletes and teaching athletes to perform self-talk has improved performance in some, but not all, studies. Therefore, the authors wanted to test whether self-talk differed between two different types of sports and whether the skill level and effort level in runners was related to the way self-talk was performed.
What did they do to test the hypothesis or answer the research question?
— The authors administered a self-talk questionnaire (The Automatic Self-Talk Questionnaire for Sports) which measures four positive and four negative dimensions of self talk to 270 athletes (165 runners, 105 badminton players)
— Rather than using simple linear regression they employed machine learning to predict the sport type and exercise frequency.
— For question 2, the authors created a new questionnaire to assess participants' use of self-talk in high or low intensity situations and the length of the self-talk (ie words versus sentences). New subjects were recruited. For question 2.
— Machine learning was used to predict half marathon and marathon times from the survey answers.
What did they find?
— They found that there were differences in the type of self-talk performed by badminton players and runners with their machine learning able to predict with 88% accuracy whether the survey answers were from a runner or a badminton player.
— Runners typically performed disengagement of their self-talk while badminton players did more worrying and self-control. For instance the question that best differentiated runners from badminton players was “what will I do later today?” and “I want to quit”.
— During high intensity efforts runners were more likely to use encouraging self-talk that was repeated frequently and short in nature. In addition the nature of this self-talk was more extreme (or valenced) in both the positive and negative directions.
— The questionnaire could predict about 20% of the performance of the runners in half-marathons or marathons. Faster performance was associated with the use of repetitive, positive self-talk in high pressure situations.
What were the strengths?
— Validated previous studies.
— First study to use machine learning.
What were the weaknesses?
— Machine learning use in methods (small number of questions to train the model on).
— Questionnaire validity for answers that are retrospectively given.
— Lacks ecological validity.
Are the findings useful in application to training/coaching practice?
Not really. This article describes the use of self-talk but the application is limited. Surely, self-talk is an important part of performing your best. This article adds some evidence to support many standard practices. It suggests that self-talk which is shorter in nature when intensity is higher (i.e a race situation or hard workout) is both more negatively and positively charged (versus neutral) and focused on motivation rather than instructions.
What was the beer called?
Harvest Ale 2015.
Which brewery made it?
JW Lees and Co, UK
What type of beer is it?
Barleywine.
How strong is the beer (ABV)?
11 % ABV.
How would I describe this beer?
Sweet under the tongue. A little smoke on the nose. Candied fruit. Boozy sherry finish that lingers into your next sip, which is quite nice. Too bad I only had a 275 mL can.
What is my Rating of Perceived beer Enjoyment?
RP(be)E(r) = 9 out of 10.
That is all for this month's nerd alert. We hope to have succeeded in helping you learn a little more about the developments in the world of running science. If not, we hope you enjoyed a nice beer…
Until next month, stay nerdy and keep training smart.
Everyday is a school day.
Empower yourself to train smart.
Think critically. Be informed. Stay educated.
Disclaimer: We occasionally mention brands and products but it is important to know that we are not sponsored by or receiving advertisement royalties from anyone. We have conducted biomedical research for which we have received research money from publicly-funded national research councils and medical charities, and also from private companies. We have also advised private companies on their product developments. These companies had no control over the research design, data analysis, or publication outcomes of our work. Any recommendations we make are, and always will be, based on our own views and opinions shaped by the evidence available. The information we provide is not medical advice. Before making any changes to your habits of daily living based on any information we provide, always ensure it is safe for you to do so and consult your doctor if you are unsure.
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About the authors:
Matt and Thomas are both passionate about making science accessible and helping folks meet their fitness and performance goals. They both have PhDs in exercise science, are widely published, have had their own athletic careers, and are both performance coaches alongside their day jobs. Originally from different sides of the Atlantic, their paths first crossed in Copenhagen in 2010 as research scientists at the Centre for Inflammation and Metabolism at Rigshospitalet (Copenhagen University Hospital). After discussing lots of science, spending many a mile pounding the trails, and frequent micro brew pub drinking sessions, they became firm friends. Thomas even got a "buy one get one free" deal out of the friendship, marrying one of Matt's best friends from home after a chance encounter during a training weekend for the CCC in Schwartzwald. Although they are once again separated by the Atlantic, Matt and Thomas meet up about once a year and have weekly video chats about science, running, and beer. This "nerd alert" was created as an outlet for some of the hundreds of scientific papers they read each month.
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and Matt Laye PhD 
What was the hypothesis or research question?
Buy me a beer.
