Accuracy in Predicting Repetitions to Task Failure in Resistance Exercise: A Scoping Review and Exploratory Meta-analysis

Abstract

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. The aim of this study was to examine the accuracy in predicting repetitions to task failure in resistance exercises. Scoping review and exploratory meta-analysis. A systematic literature search was conducted in January 2021 using the PubMed, SPORTDiscus, and Google Scholar databases. 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 covering 12 studies, with a total of 414 participants, were included in our meta-analysis. The main multilevel meta-analysis model including all effects sizes (262 across 12 clusters) revealed that participants tended to underpredict the number of repetitions to task failure by 0.95 repetitions (95% confidence interval [CI] 0.17–1.73), but with considerable heterogeneity (Q(261)\u2009=\u20093060, p\u2009<\u20090.0001, I2\u2009=\u200997.9%). Meta-regressions showed that prediction accuracy slightly improved when the predictions were made closer to set failure (β\u2009=\u2009\u2009−\u20090.025, 95% CI\u2009−\u20090.05 to 0.0014) and when the number of repetitions performed to task failure was lower (≤\u200912 repetitions: β\u2009=\u20090.06, 95% CI 0.04–0.09;\u2009>\u200912 repetitions: β\u2009=\u20090.47, 95% CI 0.44–0.49). Set number trivially influenced prediction accuracy with slightly increased accuracy in later sets (β\u2009=\u2009\u2009−\u20090.07 repetitions, 95% CI\u2009−\u20090.14 to\u2009−\u20090.005). In contrast, participants’ training status did not seem to influence prediction accuracy (β\u2009=\u2009\u2009−\u20090.006 repetitions, 95% CI\u2009−\u20090.02 to 0.007) and neither did the implementation of upper or lower body exercises (upper body – lower body\u2009=\u2009\u2009−\u20090.58 repetitions; 95% CI\u2009−\u20092.32 to 1.16). Furthermore, there was minimal between-participant variation in predictive accuracy (standard deviation 1.45 repetitions, 95% CI 0.99–2.12). 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.