Rating of perceived effort but relative to what? A comparison between imposed and self-selected anchors.

PURPOSE: Collecting reliable and valid rating of perceived effort (RPE) data requires properly anchoring the scales' upper limits (i.e., the meaning of 10 on a 0-10 scale). Yet, despite their importance, anchoring procedures remain understudied and theoretically underdeveloped. Here we propose a new task-based anchoring procedure that distinguishes between imposed and self-selected anchors. In the former, researchers impose on participants a specific task as the anchor; in the latter, participants choose the most effortful task experienced or imaginable as the anchor. We compared the impact of these conceptually different anchoring procedures on RPE. METHODS: Twenty-five resistance-trained participants (13 females) attended a familiarization and two randomized experimental sessions. In both experimental sessions, participants performed non-fatiguing and fatiguing isometric maximal voluntary contraction (MVC) protocols with the squat followed by the gripper or vice versa. After each MVC, participants reported their RPE on a 0-10 scale relative to an imposed anchor of the performed task (e.g., gripper MVCs anchored to a gripper MVC) or to a self-selected anchor. RESULTS: In the non-fatiguing condition, imposed anchors yielded greater RPEs than self-selected anchors for both the squat [on average, 9.4 vs. 5.5; Δ(CI95%) = 3.9 (3.2, 4.5)] and gripper [9.4 vs. 3.9; Δ = 5.5 (4.7, 6.3)]. Similar results were observed in the fatiguing condition for both the squat [9.7 vs. 6.9; Δ = 2.8 (2.1, 3.5)] and gripper [9.7 vs. 4.5; Δ = 5.2 (4.3, 5.9)]. CONCLUSIONS: We found large differences in RPE between the two anchors, independent of exercises and fatigue state. These findings provide a basis for further development and refinement of anchoring procedures and highlight the importance of selecting, justifying, and consistently applying the chosen anchors.

Are Trainees Lifting Heavy Enough? Self-Selected Loads in Resistance Exercise: A Scoping Review and Exploratory Meta-analysis.

BACKGROUND: Traditionally, the loads in resistance training are prescribed as a percentage of the heaviest load that can be successfully lifted once (i.e., 1 Repetition Maximum [1RM]). An alternative approach is to allow trainees to self-select the training loads. The latter approach has benefits, such as allowing trainees to exercise according to their preferences and negating the need for periodic 1RM tests. However, in order to better understand the utility of the self-selected load prescription approach, there is a need to examine what loads trainees select when given the option to do so. OBJECTIVE: Examine what loads trainees self-select in resistance training sessions as a percentage of their 1RM. DESIGN: Scoping review and exploratory meta-analysis. SEARCH AND INCLUSION: We conducted a systematic literature search with PubMed, Web of Science, and Google Scholar in September 2021. We included studies that (1) were published in English in a peer-reviewed journal or as a MSc or Ph.D. thesis; (2) had healthy trainees complete at least one resistance-training session, composed of at least one set of one exercise in which they selected the loads; (3) trainees completed a 1RM test for the exercises that they selected the loads for. Eighteen studies were included in our main meta-analysis model with 368 participants. RESULTS: Our main model indicated that on average participants select loads equal to 53% of their 1RM (95% credible interval [CI] 49-58%). There was little moderating effect of training experience, age, sex, timing of the 1RM test (before or after the selected load RT session), number of sets, number of repetitions, and lower versus upper body exercises. Participants did tend to select heavier loads when prescribed lower repetitions, and vice versa (logit(yi) = - 0.09 [95% CI - 0.16 to - 0.03]). Note that in most of the analyzed studies, participants received vague instructions regarding how to select the loads, and only completed a single session with the self-selected loads. CONCLUSIONS: Participants selected loads equal to an average of 53% of 1RM across exercises. Lifting such a load coupled with a low-medium number of repetitions (e.g., 5-15) can sufficiently stimulate hypertrophy and increase maximal strength for novices but may not apply for more advanced trainees. Lifting such a load coupled with a higher number of repetitions and approaching or reaching task failure can be sufficient for muscle hypertrophy, but less so for maximal strength development, regardless of trainees' experience. The self-selected load prescription approach may bypass certain limitations of the traditional approach, but requires thought and further research regarding how, for what purposes, and with which populations it should be implemented.

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

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: The aim of this study was to 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 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. RESULTS: 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) = 3060, p < 0.0001, I2 = 97.9%). Meta-regressions showed that prediction accuracy slightly improved when the predictions were made closer to set failure (ß = - 0.025, 95% CI - 0.05 to 0.0014) and when the number of repetitions performed to task failure was lower (≤ 12 repetitions: ß = 0.06, 95% CI 0.04-0.09; > 12 repetitions: ß = 0.47, 95% CI 0.44-0.49). Set number trivially influenced prediction accuracy with slightly increased accuracy in later sets (ß = - 0.07 repetitions, 95% CI - 0.14 to - 0.005). In contrast, participants' training status did not seem to influence prediction accuracy (ß = - 0.006 repetitions, 95% CI - 0.02 to 0.007) and neither did the implementation of upper or lower body exercises (upper body - lower body = - 0.58 repetitions; 95% CI - 2.32 to 1.16). Furthermore, there was minimal between-participant variation in predictive accuracy (standard deviation 1.45 repetitions, 95% CI 0.99-2.12). 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.