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Accuracy in predicting repetitions to task failure in resistance exercise

a scoping review and exploratory meta-analysis

##article.authors##

  • Israel Halperin
  • Tomer Malleron
  • Itai Har Nir
  • Patroklos Androulakis-Korakakis
  • Milo Wolf
  • James Fisher
  • James Steele

DOI:

https://doi.org/10.31236/osf.io/x256f

Keywords:

effort, erf, estimated repetitions to failure, estimation, prediction, repetitions in reserve, resistance training, rir, rpe

Abstract

Background: Prescribing repetitions relative to task-failure is an emerging approach to resistance training. Under this approach, participants terminate the set based on their prediction of the remaining repetitions left to task-failure. While this approach holds promise, an important step in its development is to determine how accurate participants are in their predictions. That is, what is the difference between the predicted and actual number of repetitions remaining to task-failure, which ideally should be as small as possible. Objective: Examine the accuracy in predicting repetitions to task-failure in resistance exercises. Design: Scoping review and exploratory meta-analysis. Search and Inclusion: A systematic literature search was conducted with PubMed, SPORTDiscus, and Google Scholar in January 2021. Inclusion criteria included studies with healthy participants who predicted the number of repetitions they can complete to task-failure in various resistance exercises, before or during an ongoing set, which was performed to task-failure. Sixteen publications were eligible for inclusion, of which 13 publications that cover 12 studies were included in our meta-analysis with a total of 414 participants. Results: The main multilevel meta-analysis model including all effects sizes (262 across 12 clusters) revealed that participants tended to under predict the number of repetitions to task-failure by 0.95 repetitions (95% CIs= 0.17 to 1.73), but with considerable heterogeneity (Q(261)= 3060, p< 0.0001; I2 = 97.9%). Meta-regressions showed that prediction accuracy slightly improved when the predictions were made closer to set failure (β= -0.025 [95% CIs= -0.05 to 0.0014]) and when the number of performed to task-failure was lower (<12 repetitions, β= 0.06 [95% CIs= 0.04 to 0.09]; >12 repetitions, β= 0.47 [95%CIs= 0.44 to 0.49]). Set number trivially influenced prediction accuracy with slightly increased accuracy in later sets (β= -0.07 repetitions [95% CIs= -0.14 to -0.005]). In contrast, participants training status did not seem to influence prediction accuracy (β= -0.006 repetitions [95% CIs= -0.02 to 0.007]) and neither did the implementation of upper or lower body exercises (Upper body – Lower body = -0.58 repetitions [95% CIs -2.32 to 1.16]). Further, there was minimal between participant variation in predictive accuracy (standard deviation = 1.45 repetitions [95% CIs = 0.99 to 2.12]). Conclusions: Participants were imperfect in their ability to predict proximity to task-failure independent of their training background. It remains to be determined whether the observed degree of inaccuracy should be considered acceptable. Despite this, prediction accuracies can be improved if they are provided closer to task-failure, when using heavier loads, or in later sets. To reduce the heterogeneity between studies, future studies should include a clear and detailed account of how task-failure was explained to participants and how it was confirmed.

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Posted

2021-05-16