Prescribing the frequency, duration, or volume of training is simple as these factors can be altered by manipulating the number of exercise sessions per week, the duration of each session, or the ...total work performed in a given time frame (e.g., per week). However, prescribing exercise intensity is complex and controversy exists regarding the reliability and validity of the methods used to determine and prescribe intensity. This controversy arises from the absence of an agreed framework for assessing the construct validity of different methods used to determine exercise intensity. In this review, we have evaluated the construct validity of different methods for prescribing exercise intensity based on their ability to provoke homeostatic disturbances (e.g., changes in oxygen uptake kinetics and blood lactate) consistent with the moderate, heavy, and severe domains of exercise. Methods for prescribing exercise intensity include a percentage of anchor measurements, such as maximal oxygen uptake (Formula: see text), peak oxygen uptake (Formula: see text), maximum heart rate (HR
), and maximum work rate (i.e., power or velocity-Formula: see text or Formula: see text, respectively), derived from a graded exercise test (GXT). However, despite their common use, it is apparent that prescribing exercise intensity based on a fixed percentage of these maximal anchors has little merit for eliciting distinct or domain-specific homeostatic perturbations. Some have advocated using submaximal anchors, including the ventilatory threshold (VT), the gas exchange threshold (GET), the respiratory compensation point (RCP), the first and second lactate threshold (LT
and LT
), the maximal lactate steady state (MLSS), critical power (CP), and critical speed (CS). There is some evidence to support the validity of LT
, GET, and VT to delineate the moderate and heavy domains of exercise. However, there is little evidence to support the validity of most commonly used methods, with exception of CP and CS, to delineate the heavy and severe domains of exercise. As acute responses to exercise are not always predictive of chronic adaptations, training studies are required to verify whether different methods to prescribe exercise will affect adaptations to training. Better ways to prescribe exercise intensity should help sport scientists, researchers, clinicians, and coaches to design more effective training programs to achieve greater improvements in health and athletic performance.
Health and wellness coaching (HWC) interventions have been reported to improve health outcomes for individuals with chronic diseases such as diabetes, cardiovascular disease, or cancer. However, HWC ...also holds potential as an effective intervention within a biopsychosocial chronic pain management framework. The aim of the present study was to evaluate the effects of HWC on individuals with chronic pain. Four hundred nineteen participants (female, 58.9%; mean age, 54.8) enrolled in the program and 181 completed the intervention. After 12 months in the program, statistically and clinically significant reductions were observed for pain intensity (Hedges' g = 1.00) and pain-related interference (Hedges' g = 1.13). Linear mixed-effects modeling indicated that improvements in physical functioning and psychological factors were associated with improvements in pain intensity. Our results provide a novel analysis on the effects of HWC on chronic pain and pain-related interference. HWC appears to be a promising intervention to improve pain-related outcomes in a population with chronic pain. Further investigation of HWC as an intervention for chronic pain is warranted.
How parameters derived from oxygen uptake Formula: see text kinetics relate to critical speed is not fully understood, and how such parameters relate to more sport-specific performances, such as ...shuttle running, has not been investigated. Therefore, the primary aims of the present student were to examine the Formula: see text kinetics during all-out linear and shuttle running and compare physiological variables of all-out running to variables measured during a graded exercise test (GXT). Fifteen male soccer players performed a graded exercise test (GXT) and the Formula: see text kinetics from a series of three different 3-min all-out tests (3MT's) were evaluated. Formula: see text achieved during the GXT did not differ from maximal Formula: see text achieved during the all-out tests (F = 1.85, p = 0.13) (overall ICC = 0.65; typical error = 2.48 ml∙kg-1∙min-1; coefficient of variation = 4.8%). A moderate, inverse correlation (r = -0.62, p = 0.02) was observed between τ (14.7 ± 1.92 s) and CS (3.96 ± 0.52 m∙s-1) despite the narrow SD for τ. No differences (p > 0.05) were observed for any of the Formula: see text kinetics between continuous and shuttle running bouts. The linear running 3MT (r3MT) represents a viable surrogate to the GXT and data beyond CS and D' may be gleaned by using the bi-exponential speed-time model.
The search for variables involved in the regulation and termination of exercise performance has led to integrative models that attribute a central role to the brain and utilize an array of ...psychological terms (e.g. sensation, perception, discomfort, tolerance). We propose that theorizing about exercise regulation would benefit from establishing cross-disciplinary bridges to research fields, such as affective psychology and neuroscience, in which changes along the dimension of pleasure-displeasure are considered the main channel via which homeostatic perturbations enter consciousness and dictate corrective action (slowing down or stopping). We hypothesized that ratings of pleasure-displeasure would respond to the severity of homeostatic perturbation and would be related to time to exhaustion during exercise performed at an unsustainable intensity. In a within-subjects experiment (
=15, 13 men and 2 women, age 23.4±2.2 years; maximal oxygen uptake 46.0±8.0 ml kg
min
), we compared the slope of ratings of pleasure-displeasure (acquired every 1 min) during cycling exercise at a power output 10% above critical power until volitional termination under glycogen-loaded and glycogen-depleted conditions. As hypothesized, ratings of pleasure-displeasure declined more steeply under glycogen depletion (
=0.009,
=0.70) and correlated closely with time to exhaustion under both glycogen-loaded (
=0.85;
<0.001) and glycogen-depleted conditions (
=0.83;
<0.001). We conclude that in exercise, as in other domains, changes in pleasure-displeasure may be the main channel via which homeostatic perturbations enter consciousness. This proposal may have important implications for conceptualizing and identifying the neurobiological mechanisms of the sense of exertional physical fatigue.
The maximal oxygen uptake (VO2max) is deemed the highest predictor for all-cause mortality, and therefore, an ability to assess VO2max is important. The YMCA submaximal test is one of the most widely ...used tests to estimate VO2max; however, it has questionable validity.
We validated a customized submaximal test that accounts for the nonlinear rise in VO2 relative to power output and compared its accuracy against the YMCA protocol.
Fifty-six men and women performed a graded exercise test with a subsequent exhaustive, square wave bout for the verification of "true" VO2max. In counterbalanced order, subjects then completed the YMCA test and our new Mankato submaximal exercise test (MSET). The MSET consisted of a 3-min stage estimated at 35% VO2max and a second 3-min stage estimated at either 65% or 70% VO2max, where VO2max was estimated with a regression equation using sex, body mass index, age, and self-reported PA-R.
VO2 values from the graded exercise test and square wave verification bout did not differ with the highest value used to identify "true" VO2max (45.1 ± 8.89 mL · kg(-1) · min(-1)). The MSET (43.6 ± 8.6 mL · kg(-1) · min(-1)) did not differ from "true" VO2max, whereas the YMCA test (41.1 ± 9.6 mL · kg(-1) · min(-1)) yielded an underestimation (P = 0.002). The MSET was moderately correlated with "true" VO2max (ICC = 0.73, CV of 11.3%). The YMCA test was poorly correlated with "true" VO2max (ICC = 0.29, CV of 15.1%).
To our knowledge, this is the first study to examine submaximal exercise protocols versus a verified VO2max protocol. The MSET yielded better estimates of VO2max because of the protocol including a stage exceeding gas exchange threshold.
The use of personal records (PRs) for running different distances may be used to derive critical speed (CS) and the finite capacity for running speeds exceeding CS (D'). Using CS and D', ...individualized speed-time and distance-time relationships can be modeled (ie, time limits associated with running at a given speed or a given distance can be derived via linear regression with a high degree of accuracy). The running 3-min all-out exercise test (3 MT) has emerged as a method for estimating CS and D' on a large group of athletes in a single visit. Such a procedure is useful when PRs are not readily available (eg, team-sport athletes). This article reviews how to administer and interpret the running 3 MT, how CS and D' can inform racing strategy, and how CS and D' can be used to prescribe and evaluate high-intensity interval training (HIIT). Directions for deriving HIIT bouts using either fixed distances or fixed speeds are provided along with CS dose-responses to short-term HIIT programs.
Introduction
A customized submaximal exercise test for cycle ergometry was reported as a superior estimate of maximum oxygen uptake (VO
2max
) in comparison to the traditional YMCA ergometry test.
...Purpose
Following similar methodology, we sought to validate a customized submaximal treadmill test (CustomTM) compared with the widely used Bruce submaximal protocol.
Methods
Participants (29 women and 21 men; age = 31.37 ± 11.44 year, BMI = 24.02 ± 3.03) performed a graded exercise test (GXT) with a subsequent exhaustive, square-wave bout for the verification of “true” VO
2max
. In counterbalanced order, subjects then completed submaximal protocols. The CustomTM protocol consisted of two 3-min stages estimated at 35 and 70% of VO
2max
, where VO
2max
was estimated with a linear regression equation utilizing sex, BMI, age, and self-reported physical activity.
Results
VO
2
values from the GXT and verification bout were 47.2 ± 7.7 and 47.0 ± 7.7 ml kg
−1
min
−1
, respectively (ICC = 0.99, CV = 2.0%, TE = 0.83 ml kg
−1
min
−1
), with the highest value used as “true” VO
2max
(47.7 ± 7.7 ml kg
−1
min
−1
). Neither the Bruce (45.95 ± 6.97 ml kg
−1
min
−1
) nor the CustomTM (47.3 ± 9.4 ml kg
−1
min
−1
) protocol differed from “true” VO
2max
. The CustomTM had a “very large” measurement agreement with “true” VO
2max
(ICC = 0.78, CV of 9.1%, TE = 4.07 ml kg
−1
min
−1
). Bruce had a “large” measurement agreement with “true” VO
2max
(ICC = 0.62, CV of 10.0%, TE = 4.51 ml kg
−1
min
−1
).
Conclusion
The CustomTM was superior to the Bruce protocol, because it included a stage below and above gas exchange threshold, yielded a better measurement agreement for “true” VO
2max
, and was more time efficient.
The study evaluated firearm draw performance (FDP), trigger cadence (TC), and survivability rate (SR) against charging knife attacks (KA) from different distances utilizing different movement ...tactics. Twenty active-duty law enforcement officers (age = 36.9
$ \pm $
±
10.6 y.) outfitted with wearable motion sensors and a practice pistol executed three randomized defensive tactics against an attacker charging from four distances armed with a rubber knife. FDP during the charging KA trials spanned between 0.87 and 1.19 s, compared to the baseline FDP (no duress) of 1.41 ± 0.3 s. TC was between 0.21 and 0.29 s to discharge two rounds. Using a firearm from 30 ft had 100% SR, 21 ft had 95% SR, 15 ft had 58.33% SR, and 10 ft had 15% SR. Backward (72.5%) was the safest movement response, followed by lateral (71.25%), then stationary (57.5%). Improving FDP around 1s, a lateral or backward movement in response to getting charged, and shortening the firearm draw, specifically at 21 ft and closer are recommended against KAs.
Purpose
All-out, non-steady state running makes for difficult comparisons regarding linear and shuttle running; yet such differences remain an important distinction for field-based sports. The ...purpose of the study was to determine whether an energetic approach could be used to differentiate all-out linear from shuttle running.
Methods
Fifteen male field-sport athletes volunteered for the study (means ± SD): age, 21.53 ± 2.23 years; height, 1.78 ± 0.68 m; weight, 83.85 ± 11.73 kg. Athletes completed a graded exercise test, a 3-min linear all-out test and two all-out shuttle tests of varied distances (25 m and 50 m shuttles).
Results
Significant differences between the all-out tests were found for critical speed (CS)
F
(8.97),
p
< 0.001),
D
′ (finite capacity for running speeds exceeding critical speed)
F
(7.83),
p
= 0.001, total distance covered
F
(85.31),
p
< 0.001, peak energetic cost (
EC
)
F
(45.60),
p
< 0.001, peak metabolic power (
P
˙
)
F
(23.36),
p
< 0.001, average
EC
F
(548.74),
p
< 0.001, maximal speed
F
(22.87),
p
< 0.001 and fatigue index
F
(3.93),
p
= 0.027. Non-significant differences were evident for average
P
˙
F
(2.47),
p
= 0.097, total
EC
F
(0.86),
p
= 0.416 and total
P
˙
F
(2.11),
p
= 0.134.
Conclusions
The energetic approach provides insights into performance characteristics that differentiate linear from shuttle running, yet surprising similarities between tests were evident. Key parameters from all-out linear and shuttle running appear to be partly interchangeable between tests, indicating that the final choice between linear and shuttle testing should be based on the requirements of the sport.
CrossFit
began as another exercise program to improve physical fitness and has rapidly grown into the "sport of fitness". However, little is understood as to the physiological indicators that ...determine CrossFit
sport performance. The purpose of this study was to determine which physiological performance measure was the greatest indicator of CrossFit
workout performance. Male (
= 12) and female (
= 5) participants successfully completed a treadmill graded exercise test to measure maximal oxygen uptake (VO
), a 3-minute all-out running test (3MT) to determine critical speed (CS) and the finite capacity for running speeds above CS (D'), a Wingate anaerobic test (WAnT) to assess anaerobic peak and mean power, the CrossFit
total to measure total body strength, as well as the CrossFit
benchmark workouts: Fran, Grace, and Nancy. It was hypothesized that CS and total body strength would be the greatest indicators of CrossFit
performance. Pearson's r correlations were used to determine the relationship of benchmark performance data and the physiological performance measures. For each benchmark-dependent variable, a stepwise linear regression was created using significant correlative data. For the workout Fran, back squat strength explained 42% of the variance. VO
explained 68% of the variance for the workout Nancy. Lastly, anaerobic peak power explained 57% of the variance for performance on the CrossFit
total. In conclusion, results demonstrated select physiological performance variables may be used to predict CrossFit
workout performance.
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