The impact of task (un)certainty on repeated grip force production.

Many studies found that in physical tasks, reducing certainty regarding their endpoints hinders performance. However, the impact of reducing certainty regarding other aspects of physical tasks is unknown. Here we manipulated the certainty of the required effort on an unrelated, parallel task (i.e., off-task uncertainty) and examined how it impacts force production in two within-subject experiments (N = 79). In two sessions, subjects completed 20 repetitions composed of maximal forces using a gripper with their dominant hand. Between repetitions, participants applied either submaximal constant or varied grip forces, with their non-dominant arm, matched for total forces across repetitions. While we observed trivial differences in total forces between conditions, under the varied condition, participants produced a steeper decrease in forces, suggesting that off-task uncertainty impacted their effort allocation strategy. We speculate that this pattern can be attributed to cognitive overload and/or changes in motivation stemming from the imposed uncertainty.

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.

Energy expenditure and perceived effort during uphill and downhill walking in people with multiple sclerosis.

BACKGROUND: Walking on different slopes is a common daily activity for many ambulatory people with multiple sclerosis (pwMS) AIM: Investigate energy expenditure measures of walking on level, uphill and downhill slopes in pwMS. DESIGN: Observational case-control study. SETTING: Sheba Multiple Sclerosis Center, Tel-Hashomer, Israel. POPULATION: Eighteen pwMS; 10 women and 8 men, aged 39.7 (SD=6.8), mean EDSS was 2.9 (SD=1.2) and 23 healthy adults; 8 women and 15 men, aged 37.1 (S.D.=5.3). METHODS: Energy expenditure values were obtained via a metabolic device during four conditions: sitting, comfortable walking, uphill and downhill walking. Each walking trial, obtained on a treadmill, lasted 6-min and were separated by10-min recovery intervals. RESULTS: For both pwMS and healthy controls, the O2 rate and O2 cost was higher during uphill walking compared to level walking and lower during downhill walking compared with level walking. O2 rate and net O2 cost during uphill walking was lower in pwMS compared with the healthy controls. The most demanding effort was during uphill walking, with pwMS rating it more demanding compared with the healthy controls. CONCLUSIONS: Perceived effort of walking on different slopes is not consistent with changes in the energy expenditure values in pwMS. CLINICAL REHABILITATION IMPACT: pwMS describe the effort of walking on different slopes higher than normal, regardless of the energy expenditure values.

Seeing Effort: Assessing Coaches' Prediction of the Number of Repetitions in Reserve Before Task-Failure.

BACKGROUND: A key role of resistance training (RT) coaches is to personalize programs based on their trainees' abilities and goals. Specifically, coaches often assess how many repetitions in reserve (RIR) their trainees have until task-failure. Coaches can then modify the number of repetitions assigned per set accordingly. However, coaches' ability to predict the number of RIR is unknown. METHODS: Certified RT coaches (n = 259) were randomly assigned to watch a video of one of eight trainees. The trainees performed two sets of barbell squats and preacher biceps-curls, using 70% or 80% of their 1RM, to task-failure. The coaches predicted trainees' RIR at 33%, 66%, and 90% of the total number of repetitions the trainees completed in each set. We fitted a linear mixed model with various predictors to the prediction errors as the outcomes (i.e., signed and unsigned values of the predicted minus actual repetitions to task-failure). RESULTS: The overall average number of repetitions completed by the trainees was 13.9. The average absolute errors were 4.8, 2.0, and 1.2 repetitions for the 33%, 66%, and 90% time-points, respectively. The absolute prediction error increased for the biceps-curl compared to the squat (1.43, 95% CI [1.13, 1.74]), but decreased for heavier loads (- 1.17, 95% CI [- 2.16, - 0.19]), and in the second set of each exercise (- 1.20, 95% CI [- 1.38, - 1.02]). Surprisingly, coaches' years of experience had a negligible effect on the absolute error (- 0.020, 95% CI [- 0.039, - 0.0007]). Finally, coaches underpredicted the RIR at early time-points but reverted to slight overprediction at later time-points. CONCLUSIONS: Prior coaching experience seems to play a minor role in RIR predictions. However, even short-term exposures to new trainees performing different exercises can substantially improve coaches' RIR predictions.

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.

Prescribing Intensity in Resistance Training Using Rating of Perceived Effort: A Randomized Controlled Trial.

Introduction: Rating of perceived effort (RPE) scales are used to prescribe intensity in resistance training (RT) in several ways. For instance, trainees can reach a specific RPE value by modifying the number of repetitions, lifted loads, or other training variables. Given the multiple approaches of prescribing intensity using RPE and its growing popularity, we compared the effects of two RPE prescription approaches on adherence rates, body composition, performance and psychological outcomes, in an online RT intervention. Methods: We randomly assigned 57 healthy participants without RT experience (60% females, age range: 18-45) to one of two groups that received two weekly RT sessions using a resistance-band for 8 weeks. In the fixed-repetition group, participants adjusted the band resistance with the goal of completing 10 repetitions and reaching a 7-RPE on a 0-10 scale by the 10th repetition. In the open-repetition group, participants selected their preferred band resistance and completed repetitions until reaching a 7-RPE by the final repetition. We measured body composition, performance, and program satisfaction rates. Results: We assessed 46 participants at post-test, 24 from the fixed-repetition group and 22 from the open-repetition group. We observed non-significant and trivial differences between groups in all outcomes (p > 0.05). We then combined the pre-post change scores of the two groups. We found that adherence rates began at 89% and gradually decreased to 42%. On average, participants increased their fat-free mass [0.3 kg (95% CI: 0.1-0.6)], isometric mid-thigh pull [5.5 kg (95% CI: 0.8-10.4)], isometric knee-extension [2.2 kg (95% CI: 0.8-3.7)], and push-ups [6.3 repetitions (95% CI: 4.5-8.2)]. We observed non-significant and trivial changes in bodyweight, grip-force, and countermovement jump. Participants reported high satisfaction rates with all components of the program. Conclusion: Participants in both groups improved their body composition and physical capacity to a similar extent, and reported comparable satisfaction rates with the programs they followed. Accordingly, either prescription approach can be used to deliver online RT sessions based on personal preferences and logistical constraints. However, since adherences rates declined over the course of the study, future research should test additional strategies aiming to maintain adherence rates.

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.

Staying physically active during the COVID-19 quarantine: exploring the feasibility of live, online, group training sessions among older adults.

The COVID-19 outbreak has led to recurring quarantines resulting in drastic reductions in physical activity (PA) levels. Given its health benefits, there is a need to explore strategies to increase PA rates during this period. Video-conferencing platforms can be used to deliver live, online, group PA sessions. However, there are only few established PA protocols on how to use such platforms. Hence, the purposes of this study were to (a) design an online PA protocol and (b) explore its feasibility among older adults during a quarantine. A group of exercise specialists developed a PA protocol while accounting for challenges that may arise when using a video-conferencing platform ("Zoom"). A special focus was placed on safety, individualization, and motivational aspects. Then, 31 community dwelling older adults (71.5 ± 4 years) were recruited via social media to follow this protocol twice a week for 8 weeks. Outcome measures included adverse events, adherence rates, and satisfaction with the protocol, its delivery, and technological aspects. Twenty-eight participants completed the protocol. No adverse events occurred, and adherence rates were high (90%). Most participants (97%) indicated they would participate in such a program in the future and highly rated all aspects of the protocol (median score >6 in 1-7 Likert scales). The PA protocol delivered live via a video-conferencing platform was found to be safe and feasible with this cohort. It can therefore be implemented in practice, and in future studies planning to utilize home-based PA sessions for older adults.

The effect of self-selecting the number of repetitions on motor performance and psychological outcomes.

In resistance-training, the number of repetitions can be either fixed and predetermined (e.g., 3 sets of 10 repetitions), or selected by the trainee during ongoing sets (e.g., 3 sets of 8-12 repetitions). The first approach is more goal-focused while the latter is more autonomy-focused. Here we compared these two approaches in motor performance and psychological outcomes. Nineteen resistance-trained participants (10-males) first completed one repetition-maximum (RM) tests in the barbell-squat and bench-press, and were familiarized with the isometric mid-thigh pull (IMTP). In the next two counterbalanced sessions, participants completed two sets of the squat and bench-press using 70%1RM, and two sets of the IMTP. In the predetermined session, participants completed 10 repetitions in all sets, and in the self-selected session, participants chose how many repetitions to complete out of an 8-12 range. Bar-velocity was measured in the squat and bench-press, and force production in the IMTP. Enjoyment, perceived-autonomy, and approach-preferences were collected post-sessions. We observed comparable bar-velocity, force production, and enjoyment in both conditions (all BF01 > 2.1), and an even approach-preferences split. However, in the self-selected condition, participants demonstrated considerable variability in the number of repetitions and reported greater perceived-autonomy. Given the similarities between approaches, both can be used with this cohort based on their personal-preference.