A framework for test measurement selection in athlete physical preparation

Preparing athletes for competition requires the diagnosis and monitoring of relevant physical qualities (e.g., strength, power, speed, endurance characteristics). Decisions regarding test selection that attempt to measure these physical attributes are fundamental to the training process yet are complicated by the myriad of tests and measurements available. This article presents an evidenced based process to inform test measurement selection for the physical preparation of athletes. We describe a method for incorporating multiple layers of validity to link test measurement to competition outcome. This is followed by a framework by which to evaluate the suitability of test measurements based on contemporary validity theory that considers technical, decision-making, and organisational factors. Example applications of the framework are described to demonstrate its utility in different settings. The systems presented here will assist in distilling the range of measurements available into those most likely to have the greatest impact on competition performance.

"You can't shoot another bullet until you've reloaded the gun": Coaches' perceptions, practices and experiences of deloading in strength and physique sports

Deloading refers to a purposeful reduction in training demand with the intention of enhancing preparedness for successive training cycles. Whilst deloading is a common training practice in strength and physique sports, little is known about how the necessary reduction in training demand should be accomplished. Therefore, the purpose of this research was to determine current deloading practices in competitive strength and physique sports. Eighteen strength and physique coaches from a range of sports (weightlifting, powerlifting, and bodybuilding) participated in semi-structured interviews to discuss their experiences of deloading. The mean duration of coaching experience at ≥ national standard was 10.9 (SD = 3.9) years. Qualitative content analysis identified Three categories: definitions, rationale, and application. Participants conceptualised deloading as a periodic, intentional cycle of reduced training demand designed to facilitate fatigue management, improve recovery, and assist in overall training progression and readiness. There was no single method of deloading; instead, a reduction in training volume (achieved through a reduction in repetitions per set and number of sets per training session) and intensity of effort (increased proximity to failure and/or reduction in relative load) were the most adapted training variables, along with alterations in exercise selection and configuration. Deloading was typically prescribed for a duration of 5 to 7 days and programmed every 4 to 6 weeks, although periodicity was highly variable. Additional findings highlight the underrepresentation of deloading in the published literature, including a lack of a clear operational definition.

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

The magnitude of change following strength and conditioning (S&C) training can be evaluated comparing effect sizes to thresholds. This study conducted a series of meta-analyses and compiled results to identify thresholds specific to S&C, and create prior distributions for Bayesian updating. Pre- and post-training data from S&C interventions were translated into standardised mean difference (SMD_pre) and percentage improvement (%Improve) effect sizes. Bayesian hierarchical meta-analysis models were conducted to compare effect sizes, develop prior distributions, and estimate 0.25-, 0.5-, and 0.75-quantiles to determine small, medium, and large thresholds, respectively. Data from 643 studies comprising 6574 effect sizes were included in the analyses. Large differences in distributions for both SMD_pre and %Improve were identified across outcome domains (strength, power, jump and sprint performance), with analyses of the tails of the distributions indicating potential large overestimations of SMD_pre values. Future evaluations of S&C training will be improved using Bayesian approaches featuring the information and priors developed in this study. To facilitate an uptake of Bayesian methods within S&C, an easily accessible tool employing intuitive Bayesian updating was created. It is recommended that the tool and specific thresholds be used instead of isolated effect size calculations and Cohen's generic values when evaluating S&C training.

The Minimum Effective Training Dose Required for 1RM Strength in Powerlifters

The aim of this multi-experiment paper was to explore the concept of the minimum effective training dose (METD) required to increase 1-repetition-maximum (1RM) strength in powerlifting (PL) athletes. The METD refers to the least amount of training required to elicit meaningful increases in 1RM strength. A series of five studies utilising mixed methods, were conducted using PL athletes & coaches of all levels in an attempt to better understand the METD for 1RM strength. The studies of this multi-experiment paper are: an interview study with elite PL athletes and highly experienced PL coaches (n = 28), an interview and survey study with PL coaches and PL athletes of all levels (n = 137), two training intervention studies with intermediate-advanced PL athletes (n = 25) and a survey study with competitive PL athletes of different levels (n = 57). PL athletes looking to train with a METD approach can do so by performing ~3-6 working sets of 1-5 repetitions each week, with these sets spread across 1-3 sessions per week per powerlift, using loads above 80% 1RM at a Rate of Perceived Exertion (RPE) of 7.5-9.5 for 6-12 weeks and expect to gain strength. PL athletes who wish to further minimize their time spent training can perform autoregulated single repetition sets at an RPE of 9-9.5 though they should expect that strength gains will be less likely to be meaningful. However, the addition of 2-3 back-off sets at ~80% of the single repetitions load, may produce greater gains over 6 weeks while following a 2-3-1 squat-bench press-deadlift weekly training frequency. When utilizing accessory exercises in the context of METD, PL athletes typically utilize 1-3 accessory exercises per powerlift, at an RPE in the range of 7-9 and utilize a repetition range of ~6-10 repetitions.

Functional relevance of resistance training-induced neuroplasticity in health and disease

Repetitive, monotonic, and effortful voluntary muscle contractions performed for just a few weeks, i.e., resistance training, can substantially increase maximal voluntary force in the practiced task and can also increase gross motor performance. The increase in motor performance is often accompanied by neuroplastic adaptations in the central nervous system. While historical data assigned functional relevance to such adaptations induced by resistance training, this claim has not yet been systematically and critically examined in the context of motor performance across the lifespan in health and disease. A review of muscle activation, brain and peripheral nerve stimulation, and imaging data revealed that increases in motor performance and neuroplasticity tend to be uncoupled, making a mechanistic link between neuroplasticity and motor performance inconclusive. We recommend new approaches, including causal mediation analytical and hypothesis-driven models to substantiate the functional relevance of resistance training-induced neuroplasticity in the improvements of gross motor function across the lifespan in health and disease.

A Narrative Review of Methods for Causal Inference and Associated Educational Resources

BACKGROUND AND OBJECTIVES

Root cause analysis involves evaluation of causal relationships between exposures (or interventions) and adverse outcomes, such as identification of direct (eg, medication orders missed) and root causes (eg, clinician's fatigue and workload) of adverse rare events. To assess causality requires either randomization or sophisticated methods applied to carefully designed observational studies. In most cases, randomized trials are not feasible in the context of root cause analysis. Using observational data for causal inference, however, presents many challenges in both the design and analysis stages. Methods for observational causal inference often fall outside the toolbox of even well-trained statisticians, thus necessitating workforce training.

METHODS

This article synthesizes the key concepts and statistical perspectives for causal inference, and describes available educational resources, with a focus on observational clinical data. The target audience for this review is clinical researchers with training in fundamental statistics or epidemiology, and statisticians collaborating with those researchers.

RESULTS

The available literature includes a number of textbooks and thousands of review articles. However, using this literature for independent study or clinical training programs is extremely challenging for numerous reasons. First, the published articles often assume an advanced technical background with different notations and terminology. Second, they may be written from any number of perspectives across statistics, epidemiology, computer science, or philosophy. Third, the methods are rapidly expanding and thus difficult to capture within traditional publications. Fourth, even the most fundamental aspects of causal inference (eg, framing the causal question as a target trial) often receive little or no coverage. This review presents an overview of (1) key concepts and frameworks for causal inference and (2) online documents that are publicly available for better assisting researchers to gain the necessary perspectives for functioning effectively within a multidisciplinary team.

CONCLUSION

A familiarity with causal inference methods can help risk managers empirically verify, from observed events, the true causes of adverse sentinel events.