Interpreting magnitude of change in strength and conditioning: Effect size selection, threshold values and Bayesian updating

Give it a rest: a systematic review with Bayesian meta-analysis on the effect of inter-set rest interval duration on muscle hypertrophy

We systematically searched the literature for studies with a randomized design that compared different inter-set rest interval durations for estimates of pre-/post-study changes in lean/muscle mass in healthy adults while controlling all other training variables. Bayesian meta-analyses on non-controlled effect sizes using hierarchical models of all 19 measurements (thigh: 10; arm: 6; whole body: 3) from 9 studies meeting inclusion criteria analyses showed substantial overlap of standardized mean differences across the different inter-set rest periods [binary: short: 0.48 (95%CrI: 0.19-0.81), longer: 0.56 (95%CrI: 0.24-0.86); Four categories: short: 0.47 (95%CrI: 0.19-0.80), intermediate: 0.65 (95%CrI: 0.18-1.1), long: 0.55 (95%CrI: 0.15-0.90), very long: 0.50 (95%CrI: 0.14-0.89)], with substantial heterogeneity in results. Univariate and multivariate pairwise meta-analyses of controlled binary (short vs. longer) effect sizes showed similar results for the arm and thigh with central estimates tending to favor longer rest periods [arm: 0.13 (95%CrI: -0.27 to 0.51); thigh: 0.17 (95%CrI: -0.13 to 0.43)]. In contrast, central estimates closer to zero but marginally favoring shorter rest periods were estimated for the whole body [whole body: -0.08 (95%CrI: -0.45 to 0.29)]. Subanalysis of set end-point data indicated that training to failure or stopping short of failure did not meaningfully influence the interaction between rest interval duration and muscle hypertrophy. In conclusion, results suggest a small hypertrophic benefit to employing inter-set rest interval durations >60 s, perhaps mediated by reductions in volume load. However, our analysis did not detect appreciable differences in hypertrophy when resting >90 s between sets, consistent with evidence that detrimental effects on volume load tend to plateau beyond this time-frame. Systematic Review Registration: OSF, https://doi.org/10.17605/OSF.IO/YWEVC.

The Effect of Strength Training Methods on Middle-Distance and Long-Distance Runners' Athletic Performance: A Systematic Review with Meta-analysis

BACKGROUND

The running performance of middle-distance and long-distance runners is determined by factors such as maximal oxygen uptake (VO2max), velocity at VO2max (vVO2max), maximum metabolic steady state (MMSS), running economy, and sprint capacity. Strength training is a proven strategy for improving running performance in endurance runners. However, the effects of different strength training methods on the determinants of running performance are unclear.

OBJECTIVE

The aim of this systematic review with meta-analysis was to compare the effect of different strength training methods (e.g., high load, submaximal load, plyometric, combined) on performance (i.e., time trial and time until exhaustion) and its determinants (i.e., VO2max, vVO2max, MMSS, sprint capacity) in middle-distance and long-distance runners.

METHODS

A systematic search was conducted across electronic databases (Web of Science, PubMed, SPORTDiscus, SCOPUS). The search included articles indexed up to November 2022, using various keywords combined with Boolean operators. The eligibility criteria were: (1) middle- and long-distance runners, without restriction on sex or training/competitive level; (2) application of a strength training method for ≥ 3 weeks, including high load training (≥ 80% of one repetition maximum), submaximal load training (40-79% of one repetition maximum), plyometric training, and combined training (i.e., two or more methods); (3) endurance running training control group under no strength training or under strength training with low loads (< 40% of one repetition maximum); (4) running performance, VO2max, vVO2max, MMSS and/or sprint capacity measured before and after a strength training intervention program; (5) randomized and non-randomized controlled studies. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. A random-effects meta-analysis and moderator analysis were performed using Comprehensive meta-analysis (version 3.3.0.70).

RESULTS

The certainty of the evidence was very low to moderate. The studies included 324 moderately trained, 272 well trained, and 298 highly trained athletes. The strength training programs were between 6 and 40 weeks duration, with one to four intervention sessions per week. High load and combined training methods induced moderate (effect size =  - 0.469, p = 0.029) and large effect (effect size =  - 1.035, p = 0.036) on running performance, respectively. While plyometric training was not found to have a significant effect (effect size =  - 0.210, p = 0.064). None of the training methods improved VO2max, vVO2max, MMSS, or sprint capacity (all p > 0.072). Moderators related to subject (i.e., sex, age, body mass, height, VO2max, performance level, and strength training experience) and intervention (i.e., weeks, sessions per week and total sessions) characteristics had no effect on running performance variables or its determinants (all p > 0.166).

CONCLUSIONS

Strength training with high loads can improve performance (i.e., time trial, time to exhaustion) in middle-distance and long-distance runners. A greater improvement may be obtained when two or more strength training methods (i.e., high load training, submaximal load training and/or plyometric training) are combined, although with trivial effects on VO2max, vVO2max, MMSS, or sprint capacity.

Dose-Response Modelling of Resistance Exercise Across Outcome Domains in Strength and Conditioning: A Meta-analysis

BACKGROUND

Resistance exercise is the most common training modality included within strength and conditioning (S&C) practice. Understanding dose-response relationships between resistance training and a range of outcomes relevant to physical and sporting performance is of primary importance for quality S&C prescription.

OBJECTIVES

The aim of this meta-analysis was to use contemporary modelling techniques to investigate resistance-only and resistance-dominant training interventions, and explore relationships between training variables (frequency, volume, intensity), participant characteristics (training status, sex), and improvements across a range of outcome domains including maximum strength, power, vertical jump, change of direction, and sprinting performance.

METHODS

Data were obtained from a database of training studies conducted between 1962 and 2018, which comprised healthy trained or untrained adults engaged in resistance-only or resistance-dominant interventions. Studies were not required to include a control group. Standardized mean difference effect sizes were calculated and interventions categorized according to a range of training variables describing frequency (number of sessions per week), volume (number of sets and repetitions performed), overall intensity (intensity of effort and load, categorised as low, medium or high), and intensity of load (represented as % of one-repetition maximum [1RM] prescribed). Contemporary modelling techniques including Bayesian mixed-effects meta-analytic models were fitted to investigate linear and non-linear dose-responses with models compared based on predictive accuracy.

RESULTS

Data from a total of 295 studies comprising 535 groups and 6,710 participants were included with analyses conducted on time points ≤ 26 weeks. The best performing model included: duration from baseline, average number of sets, and the main and interaction effects between outcome domain and intensity of load (% 1RM) expressed non-linearly. Model performance was not improved by the inclusion of participant training status or sex.

CONCLUSIONS

The current meta-analysis represents the most comprehensive investigation of dose-response relationships across a range of outcome domains commonly targeted within strength and conditioning to date. Results demonstrate the magnitude of improvements is predominantly influenced by training intensity of load and the outcome measured. When considering the effects of intensity as a % 1RM, profiles differ across outcome domains with maximum strength likely to be maximised with the heaviest loads, vertical jump performance likely to be maximised with relatively light loads (~ 30% 1RM), and power likely to be maximised with low to moderate loads (40-70% 1RM).

Dryland Performance Tests Are Not Good Predictors of World Aquatics Points in Elite Male and Female Swimmers

Background: Swim performance can be reliant on strength and power. Standardisation of swim performance in different events, distances, and sexes can be completed using World Aquatics points, allowing for ranking of swimmers. The aim of this retrospective cross-sectional study was to assess whether relationships between World Aquatics points and dryland markers of performance existed in male and female elite swimmers separately and combined. Methods: Dryland tests included Optojump® photoelectric cell countermovement jump, countermovement jump reach with a Vertec® system, standing broad jump using a tape measure, repetition maximum testing in the barbell back squat, barbell deadlift, and barbell bench press. Swim performance data and dryland test data on elite male (n = 38) and female (n = 20) Scottish swimmers from 2009-2017 were collected. Swim performance data were converted to World Aquatics federation points, and Bayesian linear regression analyses examined relationships between World Aquatics points and dryland performance tests: countermovement jump height (cm) using an Optojump® photoelectric cells system, countermovement jump height (cm) using a Vertec® device, standing broad jump distance (cm), relative strength (load lifted (kg) per kg of body mass) in the barbell bench press (kg/kg), barbell back squat (kg/kg), barbell deadlift (kg/kg). Results: The Bayesian estimates of change of World Aquatics points for a unit change in jump-based measures were: Optojump®-men = 0.6, women = 0.6, combined = 0.4; Vertec®-men = 4.3, women = -1.6, combined = 2.4; standing broad jump-men = 0, women = 0, combined = 0.4. Strength-based measures were: barbell back squat-men = 2.3, women = 22, combined = -2.5; barbell deadlift-men = -5; barbell bench press-men = 41.8. Conclusions: Dryland performance tests are not good predictors of World Aquatics points and should rather be used for assessing training quality and monitoring injury risks.

Effect of Strength Training Programs in Middle- and Long-Distance Runners' Economy at Different Running Speeds: A Systematic Review with Meta-analysis

BACKGROUND

Running economy is defined as the energy demand at submaximal running speed, a key determinant of overall running performance. Strength training can improve running economy, although the magnitude of its effect may depend on factors such as the strength training method and the speed at which running economy is assessed.

AIM

To compare the effect of different strength training methods (e.g., high loads, plyometric, combined methods) on the running economy in middle- and long-distance runners, over different running speeds, through a systematic review with meta-analysis.

METHODS

A systematic search was conducted across several electronic databases including Web of Science, PubMed, SPORTDiscus, and SCOPUS. Using different keywords and Boolean operators for the search, all articles indexed up to November 2022 were considered for inclusion. In addition, the PICOS criteria were applied: Population: middle- and long-distance runners, without restriction on sex or training/competitive level; Intervention: application of a strength training method for ≥ 3 weeks (i.e., high loads (≥ 80% of one repetition maximum); submaximal loads [40-79% of one repetition maximum); plyometric; isometric; combined methods (i.e., two or more methods); Comparator: control group that performed endurance running training but did not receive strength training or received it with low loads (< 40% of one repetition maximum); Outcome: running economy, measured before and after a strength training intervention programme; Study design: randomized and non-randomized controlled studies. Certainty of evidence was assessed with the GRADE approach. A three-level random-effects meta-analysis and moderator analysis were performed using R software (version 4.2.1).

RESULTS

The certainty of the evidence was found to be moderate for high load training, submaximal load training, plyometric training and isometric training methods and low for combined methods. The studies included 195 moderately trained, 272 well trained, and 185 highly trained athletes. The strength training programmes were between 6 and 24 weeks' duration, with one to four sessions executed per week. The high load and combined methods induced small (ES = - 0.266, p = 0.039) and moderate (ES = - 0.426, p = 0.018) improvements in running economy at speeds from 8.64 to 17.85 km/h and 10.00 to 14.45 km/h, respectively. Plyometric training improved running economy at speeds ≤ 12.00 km/h (small effect, ES = - 0.307, p = 0.028, β1 = 0.470, p = 0.017). Compared to control groups, no improvement in running economy (assessed speed: 10.00 to 15.28 and 9.75 to 16.00 km/h, respectively) was noted after either submaximal or isometric strength training (all, p > 0.131). The moderator analyses showed that running speed (β1 = - 0.117, p = 0.027) and VO2max (β1 = - 0.040, p = 0.020) modulated the effect of high load strength training on running economy (i.e., greater improvements at higher speeds and higher VO2max).

CONCLUSIONS

Compared to a control condition, strength training with high loads, plyometric training, and a combination of strength training methods may improve running economy in middle- and long-distance runners. Other methods such as submaximal load training and isometric strength training seem less effective to improve running economy in this population. Of note, the data derived from this systematic review suggest that although both high load training and plyometric training may improve running economy, plyometric training might be effective at lower speeds (i.e., ≤ 12.00 km/h) and high load strength training might be particularly effective in improving running economy (i) in athletes with a high VO2max, and (ii) at high running speeds.

PROTOCOL REGISTRATION

The original protocol was registered ( https://osf.io/gyeku ) at the Open Science Framework.

The Effects of Repeated-Sprint Training on Physical Fitness and Physiological Adaptation in Athletes: A Systematic Review and Meta-Analysis

BACKGROUND

Repeated-sprint training (RST) is a common training method for enhancing physical fitness in athletes. To advance RST prescription, it is important to understand the effects of programming variables on physical fitness and physiological adaptation.

OBJECTIVES

This study (1) quantifies the pooled effects of running RST on changes in 10 and 20 m sprint time, maximal oxygen consumption (VO2max), Yo-Yo Intermittent Recovery Test Level 1 (YYIR1) distance, repeated-sprint ability (RSA), countermovement jump (CMJ) height and change of direction (COD) ability in athletes, and (2) examines the moderating effects of program duration, training frequency, weekly volume, sprint modality, repetition distance, number of repetitions per set and number of sets per session on changes in these outcome measures.

METHODS

Pubmed, SPORTDiscus and Scopus databases were searched for original research articles up to 04 July 2023, investigating RST in healthy, able-bodied athletes, between 14 and 35 years of age, and a performance calibre of trained or above. RST interventions were limited to repeated, maximal running (land-based) sprints of ≤ 10 s duration, with ≤ 60 s recovery, performed for 2-12 weeks. A Downs and Black checklist was used to assess the methodological quality of the included studies. Eligible data were analysed using multi-level mixed-effects meta-analysis, with standardised mean changes determined for all outcomes. Standardised effects [Hedges G (G)] were evaluated based on coverage of their confidence (compatibility) intervals (CI) using a strength and conditioning specific reference value of G = 0.25 to declare an improvement (i.e. G > 0.25) or impairment (i.e. G < - 0.25) in outcome measures. Applying the same analysis, the effects of programming variables were then evaluated against a reference RST program, consisting of three sets of 6 × 30 m straight-line sprints performed twice per week for 6 weeks (1200 m weekly volume).

RESULTS

40 publications were included in our investigation, with data from 48 RST groups (541 athletes) and 19 active control groups (213 athletes). Across all studies, the effects of RST were compatible with improvements in VO2max (G 0.56, 90% CI 0.32-0.80), YYIR1 distance (G 0.61, 90% CI 0.43-0.79), RSA decrement (G - 0.61, 90% CI - 0.85 to - 0.37), linear sprint times (10 m: G - 0.35, 90% CI - 0.48 to - 0.22; 20 m: G - 0.48, 90% CI - 0.69 to - 0.27), RSA average time (G - 0.34, 90% CI - 0.49 to - 0.18), CMJ height (G 0.26, 90% CI 0.13-0.39) and COD ability (G - 0.32, 90% CI - 0.52 to - 0.12). Compared with the reference RST program, the effects of manipulating training frequency (+ 1 session per week), program duration (+ 1 extra training week), RST volume (+ 200 m per week), number of reps (+ 2 per set), number of sets per session (+ 1 set) or rep distance (+ 10 m per rep) were either non-substantial or comparable with an impairment in at least one outcome measure per programming variable.

CONCLUSIONS

Running-based RST improves speed, intermittent running performance, VO2max, RSA, COD ability and CMJ height in trained athletes. Performing three sets of 6 × 30 m sprints, twice per week for 6 weeks is effective for enhancing physical fitness and physiological adaptation. Additionally, since our findings do not provide conclusive support for the manipulation of RST variables, further work is needed to better understand how programming factors can be manipulated to augment training-induced adaptations.

STUDY REGISTRATION

Open Science Framework registration https://doi.org/10.17605/OSF.IO/RVNDW .

The Effect of Time-Equated Concurrent Training Programs in Resistance-Trained Men

The purpose of this investigation was to compare the effects of three different concurrent training (CT) programs and a resistance training (RT) program. Twenty-three resistance trained men (age: 24 ± 3 years) were randomized into four groups: concurrent RT and high intensity interval cycling (CTH, n = 6), concurrent RT and moderate intensity continuous cycling (CTM, n = 5), RT and barbell circuit training (RTC, n = 6), or RT only (RT, n = 6). Back squat and bench press strength, quadriceps, and pectoralis muscle thickness, VO2peak, and maximum workload (Wmax, Watts) were assessed. Squat strength gains were meaningful in all groups and comparable among CTH (16.88 kg [95% CrI: 11.15, 22.63]), CTM (25.54 kg [95% CrI: 19.24, 31.96]), RTC (17.5 kg [95% CrI: 11.66, 23.39]), and RT (20.36 kg [95% CrI: 15.29, 25.33]) groups. Bench press strength gains were meaningful in all groups and comparable among CTH (11.86 kg [95% CrI: 8.28, 15.47]), CTM (10.3 kg [95% CrI: 6.49, 14.13]), RTC (4.84 kg [95% CrI: 1.31, 8.47]), and RT (10.16 kg [95% CrI: 7.02, 13.22]) groups. Quadriceps hypertrophy was meaningful in all groups and comparable among CTH (2.29 mm [95% CrI: 0.84, 3.76]), CTM (3.41 mm [95% CrI: 1.88, 4.91]), RTC (2.6 mm [95% CrI: 1.17, 4.05]), and RT (2.83 mm [95% CrI: 1.55, 4.12]) groups. Pectoralis hypertrophy was meaningful in CTH (2.29 mm [95% CrI: -0.52, 5.1]), CTM (5.14 mm [95% CrI: 2.1, 8.15]), and RTC (7.19 mm [95% CrI: 4.26, 10.02]) groups, but not in the RT group (1 mm [95% CrI: -1.59, 3.59]); further, between-group contrasts indicated less pectoralis growth in the RT compared to the RTC group. Regarding cardiovascular outcomes, only the RTH and RTM groups experienced meaningful improvements in either measure (VO2peak or Wmax). These data suggest that the interference effect on maximal strength and hypertrophy can be avoided when the aerobic training is moderate intensity cycling, high intensity cycling, or a novel barbell circuit for ~one hour per week and on non-RT days. However, the barbell circuit failed to elicit meaningful cardiovascular adaptations.

Publication bias, statistical power and reporting practices in the Journal of Sports Sciences: potential barriers to replicability

Two factors that decrease the replicability of studies in the scientific literature are publication bias and studies with underpowered desgins. One way to ensure that studies have adequate statistical power to detect the effect size of interest is by conducting a-priori power analyses. Yet, a previous editorial published in the Journal of Sports Sciences reported a median sample size of 19 and the scarce usage of a-priori power analyses. We meta-analysed 89 studies from the same journal to assess the presence and extent of publication bias, as well as the average statistical power, by conducting a z-curve analysis. In a larger sample of 174 studies, we also examined a) the usage, reporting practices and reproducibility of a-priori power analyses; and b) the prevalence of reporting practices of t-statistic or F-ratio, degrees of freedom, exact p-values, effect sizes and confidence intervals. Our results indicate that there was some indication of publication bias and the average observed power was low (53% for significant and non-significant findings and 61% for only significant findings). Finally, the usage and reporting practices of a-priori power analyses as well as statistical results including test statistics, effect sizes and confidence intervals were suboptimal.

Meta-analysis of variation in sport and exercise science: Examples of application within resistance training research

Meta-analysis has become commonplace within sport and exercise science for synthesising and summarising empirical studies. However, most research in the field focuses upon mean effects, particularly the effects of interventions to improve outcomes such as fitness or performance. It is thought that individual responses to interventions vary considerably. Hence, interest has increased in exploring precision or personalised exercise approaches. Not only is the mean often affected by interventions, but variation may also be impacted. Exploration of variation in studies such as randomised controlled trials (RCTs) can yield insight into interindividual heterogeneity in response to interventions and help determine generalisability of effects. Yet, larger samples sizes than those used for typical mean effects are required when probing variation. Thus, in a field with small samples such as sport and exercise science, exploration of variation through a meta-analytic framework is appealing. Despite the value of embracing and exploring variation alongside mean effects in sport and exercise science, it is rarely applied to research synthesis through meta-analysis. We introduce and evaluate different effect size calculations along with models for meta-analysis of variation using relatable examples from resistance training RCTs.

What are small, medium and large effect sizes for exercise treatments of tendinopathy? A systematic review and meta-analysis

Objective

To quantify and describe effect size distributions from exercise therapies across a range of tendinopathies and outcome domains to inform future research and clinical practice through conducting a systematic review with meta-analysis.

Design

Systematic review with meta-analysis exploring moderating effects and context-specific small, medium and large thresholds.

Eligibility criteria

Randomised and quasi-randomised controlled trials involving any persons with a diagnosis of rotator cuff, lateral elbow, patellar, Achilles or gluteal tendinopathy of any severity or duration.

Methods

Common databases, six trial registries and six grey literature databases were searched on 18 January 2021 (PROSPERO: CRD42020168187). Standardised mean difference (SMD_pre) effect sizes were used with Bayesian hierarchical meta-analysis models to calculate the 0.25 (small), 0.5 (medium) and 0.75 quantiles (large) and compare pooled means across potential moderators. Risk of bias was assessed with Cochrane's Risk of Bias tool.

Results

Data were obtained from 114 studies comprising 171 treatment arms 4104 participants. SMD_pre effect sizes were similar across tendinopathies but varied across outcome domains. Greater threshold values were obtained for self-reported measures of pain (small=0.5, medium=0.9 and large=1.4), disability (small=0.6, medium=1.0 and large=1.5) and function (small=0.6, medium=1.1 and large=1.8) and lower threshold values obtained for quality of life (small=-0.2, medium=0.3 and large=0.7) and objective measures of physical function (small=0.2, medium=0.4 and large=0.7). Potential moderating effects of assessment duration, exercise supervision and symptom duration were also identified, with greater pooled mean effect sizes estimated for longer assessment durations, supervised therapies and studies comprising patients with shorter symptom durations.

Conclusion

The effect size of exercise on tendinopathy is dependent on the type of outcome measure assessed. Threshold values presented here can be used to guide interpretation and assist with further research better establishing minimal important change.

Replication concerns in sports and exercise science: a narrative review of selected methodological issues in the field

Known methodological issues such as publication bias, questionable research practices and studies with underpowered designs are known to decrease the replicability of study findings. The presence of such issues has been widely established across different research fields, especially in psychology. Their presence raised the first concerns that the replicability of study findings could be low and led researchers to conduct large replication projects. These replication projects revealed that a significant portion of original study findings could not be replicated, giving rise to the conceptualization of the replication crisis. Although previous research in the field of sports and exercise science has identified the first warning signs, such as an overwhelming proportion of significant findings, small sample sizes and lack of data availability, their possible consequences for the replicability of our field have been overlooked. We discuss the consequences of the above issues on the replicability of our field and offer potential solutions to improve replicability.