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Purpose: This review aimed to determine (1) performance and training characteristics such as training intensity distribution (TID), volume, periodization, and methods in highly trained/elite distance runners and (2) differences in training volume and TID between event distances in highly trained/elite distance runners. Methods: A systematic review of the literature was carried out using the PubMed/MEDLINE, Scopus, and Web of Science databases. Results: Ten articles met the inclusion criteria. Highly trained/elite distance runners typically follow a pyramidal TID approach, characterized by a decreasing training volume from zone 1 (at or below speed at first ventilatory/lactate threshold [LT]) to zone 2 (between speeds associated with either both ventilatory thresholds or 2 and 4 mmol·L⁻¹ LTs [vLT1 and vLT2, respectively]) and zone 3 (speed above vVT2/vLT2). Continuous-tempo runs or interval training sessions at vLT2 in zone 2 (ie, medium and long aerobic intervals) and those in zone 3 (ie, anaerobic or short-interval training) were both used at least once per week each in elite runners, and they were used to increase the number of either vLT2 or z3 sessions to adopt either a pyramidal or a polarized approach, respectively. More pyramidal- and polarized-oriented approaches were used by marathoners and 1500-m runners, respectively. Conclusions: Highly trained and elite middle- and long-distance runners are encouraged to adopt a traditional periodization pattern with a hard day–easy day basis, consisting in a shift from a pyramidal TID used during the preparatory and precompetitive periods toward a polarized TID during the competitive period.

Purpose: The purpose of this commentary is to outline some of the pitfalls when using the fitness–fatigue model to unravel the interaction between training load and performance. By doing so, we encourage sport scientists and coaches to interpret the parameters from the model with some extra caution. Conclusions: Caution is needed when interpreting the fitness–fatigue model since the parameter values are influenced by the starting parameter values, the modeling technique, and the input of the model. Also, the use of general constants should be avoided since they do not account for interindividual differences and differences between training-load methods. Therefore, we advise sport scientists and coaches to use the model as a way to work more data-informed rather than working data-driven.

Context: To understand overtraining syndrome (OTS), it is important to detail the physiological and psychological changes that occur in athletes. Objectives: To systematically establish and detail the physiological and psychological changes that occur as a result of OTS in athletes. Methods: Databases were searched for studies that were (1) original investigations; (2) English, full-text articles; (3) published in peer-reviewed journals; (4) investigations into adult humans and provided (5) objective evidence that detailed changes in performance from prior to the onset of OTS diagnosis and that performance was suppressed for more than 4 weeks and (6) objective evidence of psychological symptoms. Results: Zero studies provided objective evidence of detailed changes in performance from prior to the onset of OTS diagnosis and demonstrated suppressed performance for more than 4 weeks accompanied by changes in psychological symptoms. Conclusions: All studies failed to provide evidence of changes in performance and mood from “healthy” to an overtrained state with evidence of prolonged suppression of performance. While OTS may be observed in the field, little data is available describing how physiological and psychological symptoms manifest. This stems from vague terminology, difficulties in monitoring for prolonged periods of time, and the need for prospective testing. Real-world settings may facilitate the collection of such data, but the ideal testing battery that can easily be conducted on a regular basis does not yet exist. Consequently, it must be concluded that an evidence base of sufficient scientific quality for understanding OTS in athletes is lacking.

Purpose: The objective of the study was to evaluate the relationships among the achievement emotions experienced during physical education classes, the intention to be physically active, and academic achievement. Methods: The sample consisted of 764 Spanish secondary education students (348 boys and 416 girls). Results: Pride, enjoyment, and hopelessness were the main emotions to explain the intention to be physically active, whereas enjoyment and boredom were the most important emotions to explain academic achievement. Given that boys had a better emotional experience than girls, the effect of gender in the prediction was studied. It highlights the significant moderating effect of gender for enjoyment and pride in the intention to be physically active. Discussion/Conclusion: These results show the need to apply strategies focused on each emotion, taking into account the students’ gender, for those that help to improve their emotional experience during physical education classes.

Training load (TL) is a widely used concept in training prescription and monitoring and is also recognized as as an important tool for avoiding athlete injury, illness, and overtraining. With the widespread adoption of wearable devices, TL metrics are used increasingly by researchers and practitioners worldwide. Conceptually, TL was proposed as a means to quantify a dose of training and used to predict its resulting training effect. However, TL has never been validated as a measure of training dose, and there is a risk that fundamental problems related to its calculation are preventing advances in training prescription and monitoring. Specifically, we highlight recent studies from our research groups where we compare the acute performance decrement measured following a session with its TL metrics. These studies suggest that most TL metrics are not consistent with their notional training dose and that the exercise duration confounds their calculation. These studies also show that total work done is not an appropriate way to compare training interventions that differ in duration and intensity. We encourage scientists and practitioners to critically evaluate the validity of current TL metrics and suggest that new TL metrics need to be developed.