Change in VO2max and time trial performance in response to high-intensity interval training prescribed using ventilatory threshold

Astorino, Todd A.; DeRevere, Jamie; Anderson, Theodore; Kellogg, Erin; Holstrom, Patrick; Ring, Sebastian; Ghaseb, Nicholas

doi:10.1007/s00421-018-3910-3

Cited by 24 publications

(32 citation statements)

References 51 publications

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“…; Montero and Lundby ; Astorino TA et al. ), threshold‐based dichotomous classification approaches misclassify individuals who have a high probability of a positive response as non‐responders, and 2) using response CIs with zero‐ and/or SWC‐based thresholds provides more information than dichotomous classification approaches regarding an individual's response. Application of these statistical approaches has the potential to improve evidence‐informed exercise prescription decision‐making.…”

Section: Discussionmentioning

confidence: 99%

“…The current study demonstrated how recently proposed statistical approaches (Hopkins 2000b;Swinton et al 2018) can be used to improve the confidence when classifying non-responders. The major novel findings are: 1) despite its growing popularity in the individual response literature (Scharhag-Rosenberger et al 2012;Astorino and Schubert 2014;Ross et al 2015;Gurd et al 2016;Alvarez et al 2017;de Lannoy et al 2017;Montero and Lundby 2017;Astorino TA et al 2018), threshold-based dichotomous classification approaches misclassify individuals who have a high probability of a positive response as non-responders, and 2) using response CIs with zeroand/or SWC-based thresholds provides more information than dichotomous classification approaches regarding an individual's response. Application of these statistical approaches has the potential to improve evidenceinformed exercise prescription decision-making.…”

Section: Discussionmentioning

confidence: 99%

“…; Astorino TA et al. ), which fails to consider “non‐response” within the context of meaningful benefit (Swinton et al. ).…”

Section: Introductionmentioning

confidence: 99%

“…Much of the recent literature has dichotomously classified individuals as either "responders" or "non-responders" using a pre-determined threshold (Scharhag-Rosenberger et al 2012;Astorino and Schubert 2014;Ross et al 2015;Montero and Lundby 2017) including two times the typical error (2x TE) (Bouchard et al 2012;Bonafiglia et al 2016;Gurd et al 2016;Raleigh et al 2016;Alvarez et al 2017;de Lannoy et al 2017;Astorino TA et al 2018). Although 2x TE is a relatively robust threshold for the classification of "responders" (i.e., the true change for observed responses >29 TE above zero is >90% likely to be positive) (Hopkins 2000a), dichotomous classification of "non-responders" has significant limitations.…”

Section: Introductionmentioning

confidence: 99%

“…Although 2x TE is a relatively robust threshold for the classification of "responders" (i.e., the true change for observed responses >29 TE above zero is >90% likely to be positive) (Hopkins 2000a), dichotomous classification of "non-responders" has significant limitations. First, dichotomous classification fails to consider the continuous range of probabilities of a positive response and almost certainly misclassifies individuals as "non-responders;" and second, 2x TE has typically been applied relative to zero Gurd et al 2016;Raleigh et al 2016;Alvarez et al 2017;de Lannoy et al 2017;Astorino TA et al 2018), which fails to consider "non-response" within the context of meaningful benefit (Swinton et al 2018).…”

Section: Introductionmentioning

confidence: 99%

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Moving beyond threshold-based dichotomous classification to improve the accuracy in classifying non-responders

et al. 2018

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We examined maximal oxygen consumption responses following exercise training to demonstrate the limitations associated with threshold‐based dichotomous classification of responders and non‐responders and proposed alternative methods for classification. Specifically, we: 1) calculated individual probabilities of response, and 2) classified individuals using response confidence intervals (CI) and reference points of zero and a smallest worthwhile change of 0.5 METs. Our findings support the use of individual probabilities and individual CIs to improve the accuracy in non‐response classification.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…; Astorino TA et al. ), which fails to consider “non‐response” within the context of meaningful benefit (Swinton et al. ).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Moving beyond threshold-based dichotomous classification to improve the accuracy in classifying non-responders

et al. 2018

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Cardiorespiratory coordination reveals training-specific physiological adaptations

García‐Retortillo

Gacto

O’Leary³

et al. 2019

Eur J Appl Physiol

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Modelling inter-individual variability in acute and adaptive responses to interval training: insights into exercise intensity normalisation

Bossi,

Naumann,

Passfield

et al. 2023

Eur J Appl Physiol

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Purpose To investigate the influence of exercise intensity normalisation on intra- and inter-individual acute and adaptive responses to an interval training programme. Methods Nineteen cyclists were split in two groups differing (only) in how exercise intensity was normalised: 80% of the maximal work rate achieved in an incremental test (%$$\dot{\text{W}}$$ W ˙ max) vs. maximal sustainable work rate in a self-paced interval training session (%$$\dot{\text{W}}$$ W ˙ max-SP). Testing duplicates were conducted before and after an initial control phase, during the training intervention, and at the end, enabling the estimation of inter-individual variability in adaptive responses devoid of intra-individual variability. Results Due to premature exhaustion, the median training completion rate was 88.8% for the %$$\dot{\text{W}}$$ W ˙ max group, but 100% for the %$$\dot{\text{W}}$$ W ˙ max-SP the group. Ratings of perceived exertion and heart rates were not sensitive to how intensity was normalised, manifesting similar inter-individual variability, although intra-individual variability was minimised for the %$$\dot{\text{W}}$$ W ˙ max-SP group. Amongst six adaptive response variables, there was evidence of individual response for only maximal oxygen uptake (standard deviation: 0.027 L·min−1·week−1) and self-paced interval training performance (standard deviation: 1.451 W·week−1). However, inter-individual variability magnitudes were similar between groups. Average adaptive responses were also similar between groups across all variables. Conclusions To normalise completion rates of interval training, %$$\dot{\text{W}}$$ W ˙ max-SP should be used to prescribe relative intensity. However, the variability in adaptive responses to training may not reflect how exercise intensity is normalised, underlining the complexity of the exercise dose–adaptation relationship. True inter-individual variability in adaptive responses cannot always be identified when intra-individual variability is accounted for.

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Change in VO2max and time trial performance in response to high-intensity interval training prescribed using ventilatory threshold

Abstract: A greater volume of HIIT may be needed to maximize the training response for all individuals.

Cited by 24 publications

References 51 publications

Moving beyond threshold-based dichotomous classification to improve the accuracy in classifying non-responders

Moving beyond threshold-based dichotomous classification to improve the accuracy in classifying non-responders

Cardiorespiratory coordination reveals training-specific physiological adaptations

Modelling inter-individual variability in acute and adaptive responses to interval training: insights into exercise intensity normalisation

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