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• Published: 21 April 2022

Reverse Periodization for Improving Sports Performance: A Systematic Review

• José M. González-Ravé   ORCID: orcid.org/0000-0001-5953-4742 1 ,
• Fernando González-Mohino 1 , 2 ,
• Víctor Rodrigo-Carranza   ORCID: orcid.org/0000-0003-1637-7550 1 &
• David B. Pyne   ORCID: orcid.org/0000-0003-1555-5079 3  

Sports Medicine - Open volume  8 , Article number:  56 ( 2022 ) Cite this article

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Reverse periodization is commonly touted as a salient planning strategy to improve sport performance in athletes, but benefits have not been clearly described.

We sought to identify the main characteristics of reverse periodization, and the influence of training volume and periodization models on enhancing physiological measures and sports performance.

Systematic review.

The electronic databases Scopus, PubMed and Web of Science were searched using a comprehensive list of relevant terms.

A total of 925 studies were identified, and after removal of duplicates and studies based on title and abstract screening, 17 studies remained, and 11 finally included in the systematic review. There was a total of 200 athletes in the included studies. Reverse periodization does not provide superior performance improvements in swimming, running, muscular endurance, maximum strength, or maximal oxygen uptake, compared to traditional or block periodization. The quality of evidence levels for the reverse periodization studies was 1b (individual randomized controlled trial) for two investigations, 2b (individual cohort study) for the remaining studies and a mean of 4.9 points in the PEDro scale (range 0–7).

Conclusions

It appears that reverse periodization is no more effective than other forms of periodization in improving sports performance. More comparative studies on this alternative version of periodization are required to verify its effectiveness and utility across a range of endurance sports.

Reverse periodization is no more effective than other forms of periodization in improving sports performance, muscular endurance, maximum strength, or maximal oxygen uptake.

The use of reverse periodization likely induces similar improvements to a traditional model in shorter events such as the 100-m swimming event.

More comparative studies of periodization models in endurance sports require careful planning of experimental design, longer study periods, and where appropriate matching of training volumes and intensities.

Introduction

Periodization is a process that serves as the macromanagement of an athlete’s training program in the context of the annual plan [ 1 , 2 ]. Matveyev’s original model of periodization was developed through monitoring of Soviet athletes preparing for the 1952 and 1956 Olympic Games [ 3 ]. Periodization continues to be a valid and reliable model for athletes and is the predominant training methodology used in individual sports such as swimming [ 4 , 5 , 6 ]. However, prior to Matveyev’s seminal contribution to the topic, there was foundational work that underpins the theory of periodization [ 3 , 7 , 8 , 9 ]. A large number of authors have conceptualized periodized training in various models, with different variations of the underlying training process, planning, progressions in training volume and intensity, and recovery [ 10 , 11 , 12 ]. The original concept of periodization was proposed initially by Boris Kotov in his book “Olympic Sport” in 1916; later, Pihkala [ 13 ] postulated a number of principles such as dividing the annual cycle into preparatory, spring and summer phases, and active rest ending the season [ 14 ]. These authors have conceptualized various approaches without an accepted formal definition of periodization as promulgated by Kataoka et al. [ 1 ]. The term Periodization was originally employed to describe programs taking the form of predetermined sequential chains of specifically focused training periods. Periodization is a cyclical method of training, where the removal of linearity, and appropriate variation in the form of repeating load oscillations, can provide a superior method of training as Stone et al. identify in their recent (and provocative) narrative review [ 11 ]. Kiely [ 12 ] asserts the term periodization is frequently engaged to describe any form of training plan, regardless of structure. The challenge is to provide evidence-based guidelines on periodization that meet the conceptual and practical requirements of a wide variety of sports and events.

The rationale of periodized models of strength and power training in athletes originated in western countries centering on the work of Stone and O´Bryant [ 15 ], Stone and O’Bryant [ 16 ] and Fleck [ 17 ]. The models from Verkhoshansky or Bondarchuck have become known in Europe for their translations to different European languages such as Italian [ 18 ], Spanish [ 19 ], German [ 20 ] and also English. It soon became apparent that coaches and athletes needed to examine different periodized models other than traditional strength/power approaches. Subsequently, the meta-analysis of Rhea and Alderman [ 21 ] concluded that strength training periodization is more effective than non-periodized models for men and women. This conclusion was based on comparing different programming strategies after controlling the different parameters of workload (i.e., volume, intensity, frequency). Similar outcomes were evident in the review of Hartman et al. [ 22 ] who evaluated the effects of different short-term periodization models on strength and speed–strength training, with subjects of different performance levels and sports, who used a particular periodization model during the off-season, pre-season and/or in-season conditioning. From the early works of Matveyev [ 23 ], based on the general concept of periodized training proposed in the 1960s, the strength–speed model has been adopted by many generations of analysts and coaches [ 10 , 24 ].

Over recent decades, many approaches have evolved that can be broadly categorized as traditional, block, or reverse periodization, each offering a differing rationale and template for subdivision of the training program into sequential elements. Bompa [ 25 ] classified the periodization in mono-,bi-, and tri-cycle with different models from different authors on each: Matveyev Ozolin, Bondarchuck, Tschiene [ 5 ]. Stone et al. [ 11 ] contend that periodization can take different forms including reverse periodization, where in contrast to traditional periodization, high-intensity low-volume training predominates during the preparatory period, before the volume is increased slightly, and intensity is maintained as the season progresses. Coaches and researchers have reversed the traditional order of volume and intensity (and therefore programming) of phases to yield different physiological and performance outcomes, sometimes subtle, but nevertheless different to traditional models [ 11 ]. Reverse periodization has received attention in both the coaching and scientific literature, especially in swimming [ 26 , 27 ], and other endurance-oriented sports such as athletics or triathlon [ 28 , 29 ]. Incorporating a higher proportion of high-intensity training early in the season is thought to stimulate physiological and performance adaptations. Reverse periodization has been used in combination with a polarized intensity distribution for improving sprint events in swimming [ 30 ]. However, a small number of relevant studies in swimming have not reported any substantial differences between traditional and reverse periodization models in enhancing 50-m performance, with a modest improvement of 1% in 100-m performance in both forms [ 27 , 31 ]. A polarized three zone model of training is another approach characterized by covering ~ 80% of the volume in zone 1 (blood lactate [La − ]b ≤ 2 mmol L −1 ) with most of the remaining 20% conducted in zone 3 (above velocity of 4 mmol L −1 ) [ 32 , 33 ]. Reverse periodization has been evaluated in youth swimmers [ 26 , 34 ], moderately trained runners [ 28 , 35 ], recreational triathletes [ 29 ] and female fitness athletes [ 36 ].

All periodized models (traditional, blocks and reverse) can be considered a useful means of coordinating training to improve human sporting performance. However, more research is needed to provide a better understanding of the benefits of reverse training periodization in comparison with other models. The aim of this study was to conduct a systematic review of periodization studies to evaluate the effectiveness and utility of reverse periodization, and the influence of training volume/intensity in enhancing sports performance.

Search Strategy

A literature search was completed in December 2021 by two independent researchers (VR-C and JM-G) using the three industry-standard databases with no date restrictions: PubMed, Web of Science and Scopus. The search strategy consisted of identifying the relevant studies, with all terms searched in the title, abstract and keywords (where applicable).This systematic review was conducted following the guidelines of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement [ 37 ].

The keywords used in the searches were: periodization, training, reverse, linear traditional and block. Title, abstract and keyword fields were searched using the following search strategy: ((("periodization" OR "Training") AND "reverse") AND ("linear" OR "traditional" OR "block")).

Following the literature search, the identification, screening, eligibility assessments and inclusion of studies were performed by the same researchers with disagreement settled by consensus. All duplicate references were removed, and remaining records examined by title and abstract to exclude irrelevant records. Studies were then selected following the eligibility criteria (Table 1 ). Descriptive data including publication details, modality, participant characteristics, study design, description of methods and results, were extracted from all eligible studies. If insufficient information was reported for any particular study, the authors were contacted to confirm the relevant details required.

Inclusion Criteria

The summary of eligibility criteria is shown in Table 1 . Studies were deemed eligible for further analysis if the following inclusion criteria were met: (1) when published in English language, (2) published in a peer-reviewed journal, (3) analyzed the effects of reverse periodization vs other type of periodization model, (4) involved at least 8 weeks of training intervention/analysis, (5) provided training zones, volumes and/or periodization details and (6) involved participants without a current injury or disability.

Type of Participants

The level of the sample was classified as recreational and trained athletes using the criteria of each study included in the systematic review.

Data Extraction

Two of the authors (VR-C and JG-R) independently extracted characteristics of training protocols and results using a standardized form. A total of 11 studies were identified (Fig.  1 ).

PRISMA flow diagram of the process used in selection of the journal articles included in the systematic review with the content of this article

Quality Assessment

Two independent reviewers (VR-C and FG-M) analyzed the quality of included studies using the modified PEDro scale [ 38 ] and Oxford Levels of Evidence [ 39 ] (Table 2 ). The classic PEDro scale consists of 11 items to assess scientific rigor. A score of ≥ 6 represents the threshold for studies with a low risk of bias [ 40 ]. Item 1 is rated as Yes/No, while Items 2–11 are scored as 0 (absent) or 1 (present), and a score out of 10 is obtained by summation. Given that the assessors are rarely blinded, and that it is impossible to blind the participants and investigators in supervised exercise interventions for elite athletes, the items related to blinding (5–7) were removed from the scale for the purpose of this review. The maximum result on the modified PEDro 8-point scale was 7, as the first item was not included in the total score, resulting in a maximum score of 7 instead of 10, with adjusted quality ratings ranging from 6 to 7 deemed “excellent”, 5 “good”, 4 “moderate” and 0–3 “poor” [ 38 ]. Oxford Level of Evidence [ 39 ] scores range from 1a to 5, with 1a a systematic review of high-quality randomized controlled trials, and 5 an expert opinion.

Final Study Selection

A total of 925 potential manuscripts were identified following database examination (Fig.  1 ). References list of selected manuscripts were also examined for any other potentially eligible manuscripts. Following this examination, 3 potential manuscripts were added. After removal of duplicates and elimination of papers based on title and abstract screening, 17 studies remained. Only 11 out of 17 studies met the inclusion criteria and were, therefore, included in the systematic review (Fig.  1 ).

Characteristics of the Studies Selected

In terms of the quality of the studies selected, all studies were evaluated with the PEDro scale, with a mean score of 4.91 (Table 2 ). Using the Oxford Level of Evidence, two studies [ 27 , 31 ] were classified as 1b (independent randomized controlled trial), while the remaining studies [ 26 , 28 , 29 , 34 , 35 , 36 , 41 , 42 , 43 ] were deemed as 2b (individual cohort study) level. The characteristics of the studies selected are presented in Table 3 . A total of 11 intervention studies met all the inclusion requirements. Five studies performed reverse periodization in swimming [ 26 , 27 , 31 , 34 , 41 ], two studies in strength training [ 36 , 42 , 43 ], three studies in running [ 28 , 35 , 43 ] and one in triathlon [ 29 ]. Two of the studies compared block periodization and reverse periodization models [ 26 , 35 ], whereas 9 studies compared traditional periodization and reverse periodization models [ 27 , 28 , 29 , 31 , 34 , 36 , 41 , 42 , 43 ].

Six studies were conducted in mostly recreational athletes and five in trained athletes. There were a total of 230 athletes in the included studies, involving a total of 134 females (58%). The mean age of the athletes was 23 y (standard deviation of 6 y), with a range of 16–37 y. Two of the studies assessed females only, nine studies involved both males and females, and none of the studies assessed males only. In addition, only two studies used a control group to evaluate periodization models during the experimental intervention. The training programs evaluated in this review were predominantly short-term interventions [ 26 , 27 , 29 , 31 , 41 , 43 ] lasting ~ 10 weeks, and only four studies had a duration equal to or greater than 12 weeks [ 28 , 34 , 35 , 36 ]. The mean duration of the training interventions was 11.5 ± 1. 5 weeks. One of the studies was 8 weeks, five were 10 weeks, three were 12 weeks, one was 14 weeks and one was of 15 weeks' duration. All studies except that of Clemente-Suárez and Ramos-Campo [ 29 ] provided quantitative details of the training volume, and all studies except that of Rhea et al. [ 42 ] and Bradbury et al. [ 28 ] provided the training intensity of the training intervention. In addition, the study of Clemente-Suárez and Ramos-Campo [ 29 ] and Clemente-Suarez et al. [ 43 ] provided the training load in training impulse (TRIMPS) units.

Three typical patterns detailing the distribution of training intensity in a macrocycle - traditional periodization, block periodization and reverse periodization - are illustrated in Fig.  2 . Training intensity distribution (TID) was shown only in six studies. Traditional periodization was characterized by programming that used a pyramidal TID (characterized by a decreasing training volume in zones 1, 2 and 3 [80%) of the volume is conducted in z1, and the remaining 20% in Z2 and Z3]) in the studies of Arroyo-Toledo et al. [ 34 ] and polarized TID (characterized by covering ∼ 80% of the volume at Z1, with most of the remaining 20% conducted at Z3) in the studies of Clemente-Suárez et al. [ 27 , 41 ] and Clemente-Suárez and Ramos-Campo [ 29 ]. The reverse periodization was featured as a polarized TID in the studies of Clemente-Suárez et al. [ 27 , 31 , 41 ], and pyramidal TID in the studies of Arroyo-Toledo et al. [ 26 , 34 ]. Gómez Martin et al. [ 35 ] used a polarized TID in the first mesocycle, and a pyramidal distribution in the second and third mesocycle for the reverse periodization group, while the block periodization applied a polarized distribution in the second mesocycle and a pyramidal distribution in the first and third mesocycles. Block periodization using a pyramidal TID was employed in the studies of Arroyo-Toledo et al. [ 26 ] and Gómez Martin et al. [ 35 ]. In relation to the strength training studies, the recreationally trained women of the study of Prestes et al. [ 36 ] performed 67% of training between 7 and 11 repetition maximum (RM), followed by 27% of training > 12RM, and 5% < 6RM. This classification was used in the review following the guidelines established by Haff et al. [ 44 ]. However, Rhea et al. [ 42 ] did not report the training intensity used for the periodization groups.

Example of mesocycle distribution of traditional periodization, block periodization and reverse linear periodization. A Intensity distribution of the different periodization models. B Volume distribution of the different periodization models

Regarding training volume, the running studies reported the volume using different metrics of either time or distance. The athletes in the study of Gómez Martin et al. [ 35 ] performed about 3300 min of training over 12 weeks, without substantial differences between periodization model groups. In the case of the study of Bradbury et al. [ 28 ], the runners completed 290–300 km in 12 weeks without substantial differences in the mean weekly volume between the periodization groups. However, this volume differed between the training blocks according to the periodization model. All swimming studies displayed the training volume in meters. In the studies of Clemente-Suárez et al. [ 27 , 31 , 41 ] conducted with the same sample of athletes, those swimmers undertaking traditional periodization performed double the training volume of the reverse periodization swimmers (340 km vs. 160 km). In addition, the traditional periodization group performed 324 km compared to 212 km for the reverse periodization group in the study of Arroyo-Toledo et al. [ 34 ]. However, the same training volume was performed by the block and reverse periodization groups (90 km) in the study of Arroyo-Toledo et al. [ 26 ]. Finally, regarding the strength training studies, the athletes of Prestes et al. [ 36 ] performed a total of 9,500 repetitions without a substantial difference between periodization model groups. Similarly, the athletes in the study of Rhea et al. [ 42 ] lifted between 80,000 and 85,000 kg without differences between periodization model groups.

Effects on Physiology Parameters

There are three main physiological parameters [ 45 ] affecting endurance performance: (i) maximal oxygen uptake (V̇O 2max ), (ii) lactate threshold and (iii) movement economy. Both reverse periodization and block periodization training have yielded similar improvements in V̇O 2max and the velocity corresponding to V̇O 2max (vV̇O 2max ) [ 35 ]. Greater improvements in V̇O 2max for reverse periodization and reductions for the traditional periodization model were reported in the study of Clemente-Suárez et al. [ 27 ]. Similar improvements in running economy and peak oxygen uptake (V̇O 2peak ) were reported for traditional and reverse periodization [ 28 ]. Energy cost of swimming was impaired following traditional periodization, without any substantial changes after reverse periodization [ 41 ]. Finally, aerobic and anaerobic thresholds remained largely unchanged following both traditional and reverse periodization [ 41 ].

Effects of Exercise Performance

Two studies [ 27 , 31 ] reported 50-m swimming performance with reverse periodization compared to traditional periodization. The pre-post training intervention times in the 50-m test were similar with both forms of training (traditional periodization: 28.81 ± 1.72 vs. 28.78 ± 1.44 s; reverse periodization: 29.50 ± 2.07 vs. 30.24 ± 2.83 s). The studies of Arroyo-Toledo et al. [ 26 , 34 ] reported an improvement of 100-m swimming performance in both forms of periodization (5% in 100-m time in reverse periodization and 1.2% in block periodization). In relation to running performance, 2000 m [ 29 ] and 5000 m [ 28 ] time trials improved 2.4% after 12 weeks of both reverse periodization and traditional periodization training. In the case of the study of Clemente-Suárez et al. [ 43 ], the authors did not find improvements in the performance of 1000 m running test regarding the use of traditional or reverse periodization. Similarly, both forms of periodization showed gains in maximum strength levels (1RM) with different exercises analyzed in the study of Prestes et al. [ 36 ]. However, the increases were greater with traditional periodization when compared with reverse periodization. Regarding muscular endurance gains, both forms of periodization increased similarly (16 and 15% for reverse periodization and traditional periodization respectively)[ 42 ].

This systematic review identified 11 studies that directly compared traditional periodization ( n  = 9) and block periodization ( n  = 2) training with reverse periodization. Studies were conducted in both recreational [ 28 , 29 , 31 , 35 , 42 , 43 ] and trained athletes [ 26 , 27 , 34 , 36 , 41 ]. The training programs evaluated in this review were predominantly short-term interventions [ 26 , 27 , 29 , 31 , 41 , 43 ] lasting ~ 10 weeks, and only four studies had a duration longer than 12 weeks [ 28 , 34 , 35 , 36 ] ranging from 12 to 15 weeks. The short duration of the interventions in periodization studies makes it difficult to draw firm conclusions regarding longer-term changes in exercise and/or sports performance of any particular periodization model.

In relation to competitive (sports) performance, 5 of the 11 studies included in this review were in swimming. A systematic review on swimming periodization identified that the traditional periodization was the most common form used in well-trained swimmers, but only four studies compared traditional versus reverse periodization [ 5 ]. Our results suggest that reverse periodization improved swimming performance [ 26 ] more than block periodization, while Clemente-Suárez and Ramos-Campo [ 29 ], reported a similar improvement in swimming technical ability and swimming performance with reverse periodization and traditional periodization. However, neither traditional (characterized by pyramidal TID) nor reverse periodization (characterized by polarized TID) yielded significant improvements in 50-m swimming performance [ 27 , 31 ]. Only two studies [ 26 , 34 ] reported significant improvements in 100-m swimming performance following reverse periodization and block periodization. The greater improvements for the reverse periodization group (5%) could be explained by the low performance level of swimmers used in these studies (~ 65 s in 100-m), or a greater specificity of stimulus in the first weeks of training (high-intensity training). In addition, it appears that traditional periodization can improve the swimming efficiency by ~ 2% most likely related to the higher volume of technical work performed during the training program, while reverse periodization can increase the VO 2max by 6.4% in trained swimmers [ 27 ]. Reverse periodization has been used in combination with a polarized TID for improving performance in sprint events. On the other hand, both reverse periodization and traditional periodization improved 2000 m and 5000 m running time trials [ 28 , 43 ], without a substantial difference between periodization models, and anaerobic running performance improved in reverse periodization compared to block periodization; although the sample was recreational runners, the study supports the proposition that both periodization models are better than non-planned training [ 35 ]. However, the study of Clemente-Suárez et al. [ 43 ] did not show improvements in 1000 m performance regarding the use of traditional or reverse periodization. These results indicate that reverse periodization could be a viable alternative for improving performance in short distance events (primarily anaerobic in nature) such as the 100-m swim event, while traditional periodization seems to be the best choice for long distance (swimming) events, without a clear effect on short sprint events such as the 50-m swim or middle and long-distance running events. The lack of effects on swim performance could relate to training a variety of fitness adaptations rather than emphasizing the primary fitness characteristic [ 11 ].

To our knowledge, only two studies have reported greater gains in 1RM strength in traditional periodization/programming as opposed to reverse periodization/programming [ 36 , 42 ]. Regarding the effects of periodization on muscular strength, Prestes et al. [ 36 ], reported increases in muscular strength for both forms of periodization (traditional periodization vs. reverse periodization) in bench press (17% and 16%), lat pull-down (30% and 22%), arm curl (20% and 16%) and leg extension (37% and 32%). However, Prestes et al. [ 36 ], asserted that traditional periodization rather than reverse periodization is more effective for strength and hypertrophy. There is a possibility for traditional periodization to be more effective as it allows for more quality training with heavier weights at the end of the program [ 36 ]. A similar comparison also showed a greater increase in strength after traditional periodization in the study of Rhea et al. [ 42 ]. However, both reverse periodization (16%) and traditional periodization (15%) showed a similar increase in muscular endurance [ 42 ]. Analysis of the effect size (ES) indicates that traditional periodization was more effective at eliciting strength than reverse periodization [ 42 ] (ES = − 0.31). Both studies matched the intensity and volume of training, with the only difference being the distribution of training over the weeks. The similar increase in muscular strength for both periodization approaches likely relates to the training stimulus involving matched loads, and a similar pattern of the functional responses to training stress. With respect to improvements in muscular endurance, reverse periodization was characterized by decreased intensity and increased volume toward the last few weeks of training in these studies, which is more like a strength-endurance training stimulus. It seems reasonable to improve the muscular endurance with training more specific to this strength attribute before the post-test evaluation. Prior training history will influence adaptations to further training interventions, particularly in strength training [ 46 ]. Although subjects are typically categorized as recreational or trained, only the study of Prestes et al. [ 36 ] formally detailed that the subjects performed at least three times per week (3 × 10RM) in the previous 6 months, without details of the periodization model used. Similarly, the study of Rhea et al. [ 42 ] only reported that subjects participated in strength training programs for at least 12 months, but without specifying the underlying training and periodization model.

In addition to effects on performance and physiological parameters, different types of periodization may have variable effects on body composition. Arroyo Toledo et al. [ 26 ] reported that block periodization can elicit more favorable improvements in body composition than reverse periodization in moderately trained female swimmers. The primary premise of block periodization is employing highly concentrated training workload phases (periodization blocks) to stimulate adaptation and residual effects [ 26 ]. The blocks must be sequenced in a logical order to benefit from the residual effects [ 26 ]. Reductions in fat mass can be achieved during a period of high-intensity training [ 46 ], and including a specific phase of training for this purpose maybe useful in sports where body composition is important for performance.

There were some limitations to this review given the heterogeneity of sports, training and methodological approaches of the underlying studies. There was substantial inter-individual variability regarding the participants in the different studies (which included teenage swimmers, local/regional swimmers, experienced runners, etc.) across all performance variables that may have impaired the ability to establish conclusive outcomes in this systematic review. In addition, as periodization generally refers to periods of a season or more, it may be logical for future research to evaluate longer periods, so that differences after each periodization model can become more pronounced. A critical drawback in some of these studies is the lack of a randomized controlled design (the majority of studies did not equalize volume nor intensity when comparing two different workloads across time) as shown in Table 3 . For example, the total volume of traditional periodization during 10 weeks of training in one study was more than 337,000 m, while for the reverse periodization the volume was only ~ 160,000 m [ 27 , 31 ]. The absence of a control group did not reflect the improvements in periodized models vs. control group. More research over a longer term is needed to develop a stronger evidence base comparing and contrasting the different types of periodization models. Most of the existing studies have not reported details of nutritional status, fatigue levels and/or variations in motivation and other psychological attributes, that can all influence adaptation and performance. Future work will identify individual athlete characteristics associated with the different models of periodization, and which events and sports might benefit substantially from reverse periodization training.

It is not clear if reverse periodization is more effective in improving sports performance than other periodized models. Use of reverse periodization likely induces similar improvements to a traditional model in shorter events such as the 100-m swimming event. Comparative studies of periodization models in endurance sports require careful planning of experimental design, longer study periods, and where appropriate careful matching of training volumes and intensities.

Availability of data and materials

All data and material reported in this systematic review are from peer-reviewed publications.

Code availability

Not applicable.

Abbreviations

Blood lactate

Training impulse

Training intensity distribution

Reverse periodization

Repetition maximum

Maximal oxygen uptake

Peak oxygen uptake

Effect size

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José M. González-Ravé, Fernando González-Mohino & Víctor Rodrigo-Carranza

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JMG-R, FG-M and VR-C conceptualized the review and criteria, and JMG-R, FG-M and VR-C completed the screening and data extraction of data within this manuscript. All authors created the tables and figures. All authors contributed to the writing of the manuscript. All authors read and approved the final manuscript.

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González-Ravé, J.M., González-Mohino, F., Rodrigo-Carranza, V. et al. Reverse Periodization for Improving Sports Performance: A Systematic Review. Sports Med - Open 8 , 56 (2022). https://doi.org/10.1186/s40798-022-00445-8

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CrossFit Overview: Systematic Review and Meta-analysis

João gustavo claudino.

1 School of Physical Education and Sport, Laboratory of Biomechanics, University of São Paulo, São Paulo, Brazil

2 Faculty of Physical Education, University of Itaúna, Itaúna, Brazil

Tim J. Gabbett

3 Gabbett Performance Solutions, Brisbane, Australia

4 Institute for Resilient Regions, University of Southern Queensland, Ipswich, Australia

Frank Bourgeois

5 Sport Performance Research Institute New Zealand, Auckland University of Technology, Auckland, New Zealand

Helton de Sá Souza

6 Department of Psychobiology, Federal University of São Paulo, São Paulo, Brazil

Rafael Chagas Miranda

Bruno mezêncio, rafael soncin, carlos alberto cardoso filho, martim bottaro.

7 College of Physical Education, University of Brasília, Brasília, Brazil

Arnaldo Jose Hernandez

8 Orthopedics and Traumatology Institute, University of São Paulo, São Paulo, Brazil

Alberto Carlos Amadio

Julio cerca serrão, associated data.

After publication, all data necessary to understand and assess the conclusions of the manuscript are available to any reader of Sports Medicine-Open.

CrossFit is recognized as one of the fastest growing high-intensity functional training modes in the world. However, scientific data regarding the practice of CrossFit is sparse. Therefore, the objective of this study is to analyze the findings of scientific literature related to CrossFit via systematic review and meta-analysis.

Systematic searches of the PubMed, Web of Science, Scopus, Bireme/MedLine, and SciELO online databases were conducted for articles reporting the effects of CrossFit training. The systematic review followed the PRISMA guidelines. The Oxford Levels of Evidence was used for all included articles, and only studies that investigated the effects of CrossFit as a training program were included in the meta-analysis. For the meta-analysis, effect sizes (ESs) with 95% confidence interval (CI) were calculated and heterogeneity was assessed using a random-effects model.

Thirty-one articles were included in the systematic review and four were included in the meta-analysis. However, only two studies had a high level of evidence at low risk of bias. Scientific literature related to CrossFit has reported on body composition, psycho-physiological parameters, musculoskeletal injury risk, life and health aspects, and psycho-social behavior. In the meta-analysis, significant results were not found for any variables.

Conclusions

The current scientific literature related to CrossFit has few studies with high level of evidence at low risk of bias. However, preliminary data has suggested that CrossFit practice is associated with higher levels of sense of community, satisfaction, and motivation.

Electronic supplementary material

The online version of this article (10.1186/s40798-018-0124-5) contains supplementary material, which is available to authorized users.

• For a large majority of studies, a low level of evidence and a high risk of bias were found. There is a need to improve the methodological approaches in further studies.
• In the scientific literature, there is a gap to be filled in the area of controlling training load. Given the importance of managing training load in reducing injury risk and optimizing athletic performance, these approaches could be used to support CrossFit practice.
• Initial reports of higher levels of sense of community, satisfaction, and motivation during CrossFit training were found in the scientific literature.

CrossFit is recognized as one of the fastest growing modes of high-intensity functional training. According to the official CrossFit website (map. crossfit.com ), CrossFit boxes are located in 142 countries across seven continents with more than 10,000 affiliates [ 1 ]. This strength and conditioning program is used to optimize physical competence in ten fitness domains: (1) cardiovascular/respiratory endurance, (2) stamina, (3) strength, (4) flexibility, (5) power, (6) speed, (7) coordination, (8) agility, (9) balance, and (10) accuracy [ 2 ]. CrossFit training is usually performed with high-intensity, functional movements called “workout of the day” (WOD) [ 3 ]. In these training sessions, high-intensity exercises are executed quickly, repetitively, and with little or no recovery time between sets [ 4 ]. With the focus on constantly varying functional movements, CrossFit training uses the main elements of gymnastics (e.g., handstand and ring exercises), weightlifting exercises (e.g., barbell squats and presses), and cardiovascular activities (e.g., running or rowing) as exercise tasks [ 5 ]. According to Glassman, who is the founder of CrossFit, the methodology that drives CrossFit training is entirely empirical. Furthermore, Glassman described that “meaningful statements about safety, efficacy, and efficiency, the three most important and interdependent facets of any fitness program, can be supported only by measurable, observable, repeatable facts, i.e., data” [ 3 ].

CrossFit is also considered an option for high-intensity interval training (HIIT). Consequently, HIIT has become one of the top 3 worldwide fitness trends since 2013 according to the American College Sports Medicine (ACSM) annual survey [ 6 – 9 ]. Notably, CrossFit was indicated as the primary reason HIIT workouts were ranked so high [ 6 – 9 ]. However, a consensus paper produced by the Consortium for Health and Military Performance (CHAMP) and ACSM associated a potential emergence of a high injury risk with programs such as CrossFit [ 10 ]. While positive influences on body composition and physical fitness were recognized, the consensus highlighted a “disproportionate musculoskeletal injury risk from these demanding programs, particularly for novice participants, resulting in lost duty time, medical treatment and extensive rehabilitation”. In addition, the consensus suggested the existence of a training paradigm requiring advanced level technique during maximal timed exercise repetitions without adequate rest intervals between sets, as well as an insufficient recovery time between high-volume loads and training sessions. This overload situation can lead to early fatigue, additional oxidative stress, less resistance to subsequent repetitive exercise strain, greater perception of effort, and unsafe movement execution [ 10 ]. Furthermore, this training context associated with inadequate training load progression increases the risk of overuse injury, overreaching, and overtraining. The consensus authors suggested, as a possible solution, individual monitoring of training load to minimize these risks [ 10 ]. Despite the proposed risks of CrossFit, others have suggested that high-intensity functional training programs, including CrossFit, have similar or lower potential for injury than many traditional physical training activities [ 11 ]. However, the authors also stated that controlling training volume must be done in order to reduce injury risk in military populations. For an effective training process and adaptation to occur, the monitoring [ 12 ], quantification [ 13 ], and regulation [ 14 ] of training load is necessary. However, managing training load poses a considerable challenge for sport scientists [ 15 , 16 ]. Despite this challenge, managing training load is fundamental to achieving the objectives of reducing injury risk and optimizing sports performance [ 17 – 22 ].

Although there are a large number of CrossFit participants, empirical evidence demonstrating the improvements in physical fitness that arise from this form of training are far from substantive. Furthermore, an overview of CrossFit’s outcomes has not been verified. Therefore, the purpose of the present study was to analyze the findings of the scientific literature related to CrossFit through a systematic review and meta-analysis.

Literature Search

One author conducted the literature search, collated the abstracts, and applied the initial inclusion criteria. The keyword “CrossFit” was used during the electronic search. The following electronic databases were searched on the 25th of November 2016: PubMed, Web of Science, Scopus, Bireme/MedLine, and SciELO (Fig.  1 ). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines were adhered to in this manuscript. In the initial analysis, all CrossFit articles included in this manuscript were peer-reviewed and not limited to specific years or language. During the second phase of study selection, two authors reviewed and identified the titles and abstracts based on the inclusion criteria.

Study selection PRISMA flow diagram

Inclusion Criteria

To meet the inclusion criteria for the meta-analysis, studies investigating humans “in vivo” or “in obitus” and analyzed the effects of CrossFit as a training program were considered. The meta-analysis was only conducted on variables from short-term intervention studies (i.e., ≥ 3 weeks) with healthy male and/or female participants split into distinct gender groups (the procedures were consistent from those of another meta-analysis) [ 23 ]. Moreover, the variables analyzed were to be found in more than one study. If pertinent data were absent, authors were contacted and the necessary information requested via e-mail. If the original data were not provided by the authors, the mean and standard deviations were extracted from graphical representation using Ycasd [ 24 ] or estimated from the median, range, and sample size [ 25 ]. The remaining articles were included in the systematic review.

Study Quality

The Consolidated Standards of Reporting Trials (CONSORT) statement was adapted and used for checking the quality of reporting by two authors independently. Thus, the articles’ quality was evaluated based on the 25 items identified in the CONSORT criteria, providing a maximal possible score of 37. The CONSORT items are distributed in sections and topics such as “Title and abstract”; “Introduction” (Background and objectives); “Methods” (Trial design, Participants, Interventions, Outcomes, Sample size, Blinding, Statistical methods); “Results” (Participant flow, Recruitment, Baseline data, Numbers analyzed, Outcomes and estimation, Ancillary analyses, Harms); “Discussion” (Limitations, Generalizability, Interpretation); and “Other information” (Registration, Protocol, Funding) [ 26 ]. Additionally, the Oxford Levels of Evidence [ 27 ] were used to evaluate the level of evidence for all articles found in the literature on CrossFit. Where the five levels (i.e., Level 1 = systematic reviews; Level 2 = randomized controlled trials with low/moderate risk of bias or observational studies with dramatic effect; Level 3 = cohort study, non-randomized controlled trials with low/moderate risk of bias or randomized controlled trial at high risk of bias; Level 4 = case series, case report, case-control studies, cohort study, historically controlled studies or non-randomized controlled trials at high risk of bias; and Level 5 = mechanism-based reasoning/expert opinion) are determined based on the following questions: (i) “How common is the problem?”; (ii) “Is this diagnostic or monitoring test accurate? (diagnosis)”; (iii) “What will happen if we do not add a therapy? (prognosis)”; (iv) “Does this intervention help? (treatment benefits)”; (v) “What are the COMMON harms? (treatment harms)”; (vi) “What are the RARE harms? (treatment harms)”; and (vii) “Is this (early detection) test worthwhile? (screening)”.

Bias Analysis

For the systematic review, two authors independently assessed the quality of the included studies using the Cochrane risk of bias tool [ 28 ] with a priori formulated criteria adopted from the studies of Pas et al. [ 29 ] and Winters et al. [ 30 ]. Five domains of bias were appraised: selection bias (random allocation and allocation concealment), performance bias (blinding of personnel and participants), detection bias (blinding of outcome assessment), attrition bias (loss to follow-up), reporting bias (outcome reporting), and other biases. Each item was scored as low (+), high (−), or unclear (?) risk of bias. Studies were considered low risk of bias when all domains were scored as low risk of bias or if one item was scored as high risk or unable to determine. If two domains were scored as high or unable to determine risk of bias, the study received a moderate risk of bias. Finally, when more than two domains were scored as high risk of bias, the study was regarded to possess a high risk of bias. In case of disagreement between authors, consensus was sought during a consensus meeting. If no consensus was reached, a third author was asked to provide a final verdict. Publication bias was determined for the meta-analysis using an approach where differences in baseline assessments were checked for all intervention groups. Next, the interventions were divided into non-significant ( p  > 0.05) or significant ( p  < 0.05) results to determine the percentage of interventions with non-significant differences (these procedures were followed as per another meta-analysis) [ 23 ].

Statistical Analysis

For the meta-analysis, the heterogeneity of the included studies was evaluated by examining forest plots, confidence intervals (CI), and I 2 . I 2 values of 25, 50, and 75 indicated low, moderate, and high heterogeneity, respectively [ 31 ]. Random effects were analyzed using the DerSimonian and Laird [ 32 ] approach. The meta-analysis was conducted based on the number of variables from short-term intervention studies. Statistical significance was set at p  ≤ 0.05, and the magnitude of differences for each dependent variable was calculated using effect size (ES) with 95% CI [ 32 ]. The ES classification was large > 0.80; moderate = 0.20–0.80; small < 0.20 [ 33 ]. Inferential statistics were used for the descriptive analysis of the data. All data were analyzed using CMA v3 trial (Biostat, New Jersey, USA) and Excel 2010 worksheet (Microsoft, Washington, USA).

The initial search found 204 articles (Fig. ​ (Fig.1). 1 ). When the inclusion criteria were applied, 32 articles were included in the systematic review. When the inclusion criteria were applied for the meta-analysis, five of these articles met the criteria and were included in the manuscript [ 4 , 5 , 34 – 63 ]. However, during this manuscript peer-reviewing process, one of 32 articles had a retraction published [ 64 ].

Quality assessment of the 31 included articles ranged from 22 to 84% with a mean CONSORT rating of 37% [ 26 ]. Only 9% (i.e., absolute number = 3) of the included articles [ 38 , 53 , 54 ] had ratings exceeding 50% (Additional file  1 : Table S1). Ethical approval was obtained in all articles. The evidence level ranged between levels 2 and 4 for included articles. However, just 6% (i.e., absolute number = 2) of articles were considered level 2 (i.e., randomized controlled trials with low risk of bias) (Fig.  2 ) [ 53 , 54 ].

Risk of bias and level of evidence

For the systematic review, only 6% of the assessed articles were at low risk of bias (Fig.  2 ) [ 53 , 54 ]. These articles performed adequate randomization and allocation methods, blinding strategy, and clinical trial registry. In contrast, a majority of the non-controlled trials, cross-sectional studies based on an electronic questionnaire, and correlation studies or case report/case series did not explicitly describe if and how they controlled for detection bias. For the included articles in the meta-analysis, 78% of the intervention groups resulted in non-significant ( p  > 0.05) differences in baseline assessments (i.e., 83 interventions with non-significant differences ÷ 106 overall interventions = 78%).

The pooled sample size for this manuscript was 3597 with 81% of participants in the CrossFit group and the remaining 19% in the control group. Male participants (60%) were utilized more so than females (40%). CrossFit samples were composed of adolescents (male 4%, n  = 112 and age = 15 ± 1 years; female 3%, n  = 94 and age = 15 ± 1 years), adults (male 56%, n  = 1638 and age = 30 ± 7 years; female 37%, n  = 1065 and age = 30 ± 7 years), and elderly (male 0.2%, n  = 5 and age > 60 years; female 0.1%, n  = 2 and age > 60 years). The sample profile included 6% competitors (i.e., in the CrossFit Games), 63% trained individuals (i.e., in the CrossFit program more than 6 months), 22% physically active individuals, and 9% sedentary individuals. The average duration of each CrossFit intervention was 9 ± 3 weeks.

In summary, the following aspects of CrossFit were examined in the scientific literature: body composition ( n  = 4), psycho-physiological parameters ( n  = 12), musculoskeletal injury risk ( n  = 7), life and health aspects ( n  = 4), and psycho-social behavior ( n  = 11) (Table  1 ).

Main findings of CrossFit’s scientific state of the art

ACSM American College of Sports Medicine, AMRAP as many rounds as possible, BMI body mass index, bpm beats per minute, HR max maximum heart rate, mmol/L millimole/liter, MR maximum repetitions, RPE ratings of perceived exertion, VO 2max maximal oxygen uptake, WOD workout of the day

Among the included short-term intervention studies, five CrossFit fitness domains were found in the literature, i.e., cardiovascular/respiratory endurance [ 50 , 53 ], stamina [ 50 , 53 ], strength [ 53 ], flexibility [ 53 ], and power [ 50 , 53 ]. Five domains were yet to be verified, i.e., speed, coordination, agility, balance, and accuracy.

Forty-three variables were found from short-term intervention studies in the meta-analysis. These variables represented cardiovascular/respiratory endurance and stamina (i.e., absolute and relative maximal oxygen consumption, VO 2max ), as well as body composition (i.e., body mass, body mass index, relative body fat, fat mass, lean body mass, and waist circumference). No significant results were found for any of the variables (Fig.  3 ).

Meta-analysis of short-term intervention studies

Although CrossFit has a large number of participants, a high level of evidence demonstrating positive outcomes has yet to be established in the literature. Therefore, the present study aimed to verify the findings of scientific investigations related to CrossFit fitness domains as well as present outcome validity of CrossFit via systematic review and meta-analysis. Five of ten CrossFit fitness domains (cardiovascular/respiratory endurance, stamina, strength, flexibility, and power) were found in short-term intervention studies, with the remaining fitness domains (speed, coordination, agility, balance, and accuracy) lacking. Furthermore, CrossFit’s outcome evidence was provided for studies examining body composition, psycho-physiological parameters, musculoskeletal injury risk, life and health aspects, and psycho-social behavior. With respect to these studies, few achieved a high level of evidence at low risk of bias.

Meta-analyses were performed on body composition parameters including body mass index, relative body fat, fat mass, lean body mass, and waist circumference. All variables had non-significant results, reinforcing the need for more high-quality studies on CrossFit as well as long-term interventions.

Psycho-physiological Parameters

A study comparing CrossFit training with a training approach based on ACSM recommendations reported CrossFit training as more strenuous and considered a “very hard” activity by participants [ 52 ]. CrossFit participants also reported greater fatigue, greater muscle pain and swelling, and limb movement difficulties during or within 48 h after the workout [ 52 ]. Furthermore, the authors reported the five most frequently used and hardest WODs were “Fran,” “Murph,” “Fight Gone Bad,” “Helen,” and “Filthy Fifty.” Except for “Fran,” the psycho-physiological responses to these WODs were not reported. “Fran” and another popular WOD known as “Cindy” presented greater magnitudes for heart rate (95–97% of HR max ), %VO 2max (57–66%), blood lactate (14–15 mmol/L), and rate of perceived exertion (RPE) [ 44 ]. Perciavalle et al. [ 59 ] also observed lactate concentrations around 14 mmol/L following a WOD called “15.5”. “Cindy” (98% HR max and RPE = 9) also presented an acute blood oxidative stress response similar to a traditional bout of high-intensity treadmill running (running at a minimum intensity of 90% maximum heart rate over 20 min) [ 47 ].

Researchers have reported a decrease in anti-inflammatory cytokines without decrements in muscle power following two consecutive days of CrossFit training sessions [ 62 ]. The WODs employed included a rest interval between sets and exercises (i.e., 2–5 min, for more details see Table  1 ). Thus, IL-6 displayed an increase immediately after training WOD 1 and WOD 2 while IL-10 displayed an increase immediately after WOD 1 only and decreased 24 and 48 h following WOD 2 when compared to baseline values [ 62 ]. These findings should be considered with caution as while there are designated rest intervals in some CrossFit workouts (e.g., Fight Gone Bad, 5 × 500 m row), the inclusion of rest intervals is not common practice in CrossFit prescriptions.

In an acute study, the WOD “CrossFit triplet” (i.e., three burpees, four push-ups, and five squats; for details see Table  1 ) was associated with significant changes in physiological responses [ 51 ]. Participants achieved approximately 12,000 mmHg for rate pressure product, 6 mmol/L for blood lactate, and 54% of HR max [ 51 ]. According to the authors, “CrossFit triplet” was of moderate to high intensity and thus considered a viable interval training option that provides sufficient intensity in a safe manner [ 51 ].

In the correlation studies, whole-body strength, power, endurance, and experience seemed to be important measures associated with performance in CrossFit [ 42 , 43 ]. Butcher et al. [ 43 ] reported whole-body strength as a predictor of performance in some WODs such as “Grace,” “Fran,” and “Cindy”. The authors also found VO 2max , Wingate power, and anaerobic thresholds were unsuccessful in predicting WOD performance. Conversely, Bellar et al. [ 42 ] found VO 2max and anaerobic power to be significant predictors of performance after one CrossFit training session. The authors also divided 32 young healthy men into two groups and found CrossFit experience, or CrossFit training history, was also a predictor of performance during a WOD. Nonetheless, more research is required as the present literature is inconclusive regarding predictors of CrossFit performance.

Based on the systematic review, in general, WODs present highly varied psycho-physiological demands: heart rate between 54 and 98% of HR max , blood lactate levels between 6 and 15 mmol/L, %VO 2max between 57 and 66%, RPE between 8 and 9 (out of 10), and rate pressure product around 12,000 mmHg. Some WODs (e.g., “Fran,” “Cindy,” and “15.5”) can be identified as high-intensity level whereas others (e.g., “CrossFit triplet”) can be considered moderate.

Musculoskeletal Injury Risk

In one of the first publications on musculoskeletal injury risk, a descriptive epidemiological investigation used an electronic questionnaire to examine 132 CrossFit participants [ 34 ]. Results revealed 74% of CrossFit participants suffered at least one injury. The most common injury sites were shoulder and lower back followed by arm/elbow, with an injury rate of 3.1 events every 1000 h of training [ 34 ]. A total of 186 lesions were reported with some participants injured more than once in a period of 18 months. Nine of these cases required surgical intervention. In another study that examined the epidemiological profile of CrossFit participants, an injury prevalence of 31% was recorded [ 4 ]. In addition, when the participants were separated according to CrossFit experience, those who practiced CrossFit for more than 6 months (35%) showed significantly ( p  = 0.004) higher injury rates than those who practiced for less than 6 months (23%). This study also reported a 45% injury prevalence rate among athletes with more than 2 years of practice [ 4 ].

Another descriptive epidemiological study employed an electronic questionnaire to verify injury risk of the shoulder in CrossFit participants ( n  = 187). The authors found that 24% of participants reported at least one shoulder injury in the last 6 months of practice, with an injury rate of 1.9 per 1000 h. The most common attributed causes of injury were inadequate form of movement (33%) and exacerbation of previous injury (33%). Furthermore, 64% of those who suffered an injury reported a reduction in training for 1 month or less due to injury [ 61 ].

Similar electronic questionnaire and experimental approaches have also been used to examine injury risk in CrossFit ( n  = 381). Musculoskeletal injuries accounted for 19% of all injuries, with men injured more frequently than women ( p  = 0.03). The shoulder was injured most often during gymnastic movements whereas the lower back was injured most often during power lifting movements [ 41 ].

In addition, two case reports offered insight on injury risk. The first case study examined a traumatic tear of the latissimus dorsi myotendinous junction inflicted during the “muscle up” exercise [ 45 ]. This injury usually occurs in the acute configuration of forced abduction and external rotation during resisted contraction. Performing this exercise requires sound technique and high levels of strength, particularly at the transition point of the maneuver. The participant in this case report returned to complete pre-injury level of activity within 6 months after the inciting event, with mild residual functional deficit. The second case report was a retinal detachment due to CrossFit training [ 35 ]. A 25-year-old male presented an inferior scotoma in the right eye after engaging in a CrossFit workout which required “pull ups” with an elastic band tied around the waist and secured to the pull up bar, thus partially supporting body weight. The retina was successfully reattached, and vision was successfully recovered after 4 months.

The acute effects of high-intensity CrossFit training on tendon properties were evaluated via ultrasonography ( n  = 34). Thickness of the patellar and Achilles tendons increased significantly after the session. These findings suggest the high-intensity loads associated with concentric and eccentric muscle actions during CrossFit exercise may result in an increase in patellar and Achilles tendon thickness. However, long-term interventions are needed to investigate the effect of recovery between high-intensity sessions as a deterministic factor in altering the structure of biomaterials within tendons and the subsequent effects of changes in tendon morphology on risk of injury [ 5 ].

In summary, the number of injuries that affect CrossFit participants varies between 19 and 74% with 1.9–3.1 per 1000 training hours. In this sense, the percentage of injury is relatively high while the incidence of injuries per 1000 h is low. These results may reflect a sampling bias or inadequate management of training volume. Although higher training volume and perception of intensity have been found in CrossFit participants [ 49 , 52 ], further studies directly comparing the injury rates of CrossFit with other ACSM-recommended training modalities are warranted.

The second aspect highlighted by the CHAMP and ACSM consensus was monitoring individual-specific training load and its potential to minimize injury risk [ 10 ]. Although the cause of injury is multifactorial, injury can result from the summation of load that imposes a force that exceeds the capacity of the biological tissue involved [ 65 ]. To attenuate this deleterious outcome, an integrated approach that incorporates individual-specific monitoring [ 12 ], quantification [ 13 ], and regulation [ 14 ] may aid in decreasing injury risk. Monitoring is defined as the verification of responses to the training loads performed that were previously planned by the coach [ 12 ]. Quantification is defined as the sum of the training load that was effectively executed by the athlete [ 13 ]. Regulation is defined as the adjustments in the training loads lifted in relation to the athlete responses [ 14 ]. However, no studies investigating training load management were found in the systematic review, which presents a gap in current knowledge. Presently, controlling training load is based on the coach’s anecdotal and scientific background which can be highly varied around the world. Due to the potentially positive impact an evidence-based integrated approach to training load management could have on reducing injury, risk while achieving training objectives (i.e., enhancing sports performance) [ 17 – 22 ] warrants greater research in this area.

Life and Health Aspects

Though sparse, case report and case series studies were found in the literature examining life and health aspects. Only two reported cases of rhabdomyolysis were found [ 39 , 52 ]. However, this does not rule out the need to develop strategies of recovery between training sessions, respecting biological individuality of participants.

Other life and health aspects related to CrossFit training were found in the literature. Lu et al. [ 48 ] reported three cases of cervical carotid dissection that were associated with CrossFit workouts. Specifically, participant 1 suffered a distal cervical internal carotid artery dissection near the skull base and a small infarct in Wernicke’s area. The individual was placed on anticoagulation and on follow-up was near complete recovery. Participant 2 suffered a proximal cervical internal carotid artery dissection that led to arterial occlusion and recurrent middle cerebral artery territory infarcts, in addition to significant neurological sequelae. Participant 3 had a skull base internal carotid artery dissection that led to a partial Horner’s syndrome but no cerebral infarct. None of the three individuals died. While direct causality cannot be proven, the authors speculated the high-intensity CrossFit workouts likely led to the internal carotid artery dissections in these participants.

Similarly, Alexandrino et al. [ 37 ] examined 10 cases of stroke in participants aged between 27 and 65 years (80% being male). Among them, one man (32 years old) had an intracerebral hemorrhage stroke during a CrossFit session. The participant did not die, but he was left disabled ( no. 3 in the modified Rankin scale = moderate disability; requiring some help, but able to walk without assistance). The authors’ conclusion was that stroke during sport activity is rare, occurring mostly in healthy young males and that cervicocerebral arterial dissection is the primary mechanism of stroke, often without an explicit history of trauma.

Finally, researchers demonstrated neither beneficial nor deleterious effects on pelvic floor strength or support in nulliparous young women after CrossFit training [ 58 ]. The majority of these studies were evidence level 4 with high risk of bias and, as such, did not permit any recommendation.

To date, no studies have examined the effect of CrossFit training on resting blood pressure or heart rate. Further research examining the acute and chronic effects of CrossFit training on these health indicators is warranted.

Psycho-social Behavior

A greater sense of community in CrossFit sessions was verified when compared to traditional training whether in a group or analyzed on an individual basis. This social interaction level was assessed via questionnaire in physically active participants [ 60 , 63 ]. However, sense of community was not related to participant retention/adherence for any of the modalities analyzed [ 63 ].

The retention/adherence of participants was assessed in a randomized intervention study involving obese individuals (BMI > 30). The same number of dropouts was also revealed after 8 weeks of traditional training when compared to CrossFit with aerobic and resistance training. Nonetheless, the intention for continuing physically vigorous activity was greater for the CrossFit group [ 38 ]. Furthermore, a European Organization for Research and Treatment of Cancer core 30-item questionnaire revealed 5 weeks of CrossFit training was well received by cancer survivors with an adherence rate of 75%. This intervention was also considered feasible and effective in improving emotional function [ 46 ].

Motivation for the practice of physical activity was also assessed by questionnaire in four groups: CrossFit, resistance exercise, alone, and in individuals who train with a personal trainer. Enjoyment, challenge, and affiliation were identified in the CrossFit group more than all other training groups. Such source of motivation is compatible with that presented in sports practice. Individuals who trained with a personal trainer had higher health-related motives. However, this group was older than the other groups, which may represent a confounding factor in the response [ 54 ].

In schoolchildren (i.e., 12 to 16 years) participating in CrossFit exercise, an older age has been associated with higher ratings of perceived intensity and less enjoyment. In the between-sex comparison, boys perceived greater intensity and enjoyment [ 49 ]. Among adults, no sex difference was identified for the perceived motivational climate of CrossFit sessions, although the achievement goals varied between males and females [ 40 ]. With respect to achievement goals, the mastery-based motivational climate is initially predominant, but when a domain of the tasks is reached, the performance approach becomes predominant. These variations are also present between sexes, with females emphasizing mastery avoidance (i.e., to do as well as I can) and males emphasizing the performance approach (i.e., to do better than others) [ 40 ].

Although the goals within CrossFit practice vary with practice time, the same does not appear to be true for psychological functioning as well-being, affection, body awareness, and self-esteem were not influenced by the time or frequency of CrossFit practice [ 56 ]. Similar results were found in an 8-week intervention study in adolescent students (i.e., 15 years), where no improvement in mental health was observed. However, a subgroup of individuals at risk of psychological distress presented significant improvements in mental health [ 53 ]. In another study of the same research group, high levels of retention (i.e., 82%), adherence (i.e., 94%), and satisfaction (4.2–4.6 where 5 is the highest level) were found in the students after 8 weeks of CrossFit Teens training [ 54 ].

Lastly, CrossFit’s motivational characteristics, which aim to lead the individual to achieve the best performance possible, generated a 5% prevalence of exercise addiction in CrossFit participants which is similar to other exercise programs. This observation has also been shown to be even greater in men and young individuals (i.e., < 30 years). Exercise addiction was associated with a tendency to exercise despite injury, feelings of guilt when unable to exercise, passion turning into obsession, and taking medication to be able to exercise. These negative attitudes toward exercise can facilitate damage, such as injuries and losses in social relations, within participants [ 57 ].

In summary, there is preliminary evidence of a higher sense of community, satisfaction, and motivation among CrossFit participants. However, it is still necessary for new studies to verify the positive relationship between these factors and retention/adherence of participants.

Brief Statement

Before finalizing, we wish to emphasize that this study did not seek to define CrossFit as “bad” or “good.” Rather, this investigation sought to present the possible benefits and risks associated with CrossFit according to current findings in the scientific literature. The low level of evidence at high risk of bias revealed by this study does not allow a stronger position on the advantages and disadvantages of CrossFit. The authors believe this disparity demonstrates the need to improve current methodological approaches in further studies, thus influencing current practice.

Until now, current CrossFit scientific literature has been based on studies that investigated the effects of CrossFit on body composition, psycho-physiological parameters, musculoskeletal injury risk, life and health aspects, and psycho-social behavior. Meta-analysis did not find a significant effect of CrossFit training changes in body mass index, relative body fat, fat mass, lean body mass, and waist circumference. Unfortunately, the number of studies investigating CrossFit with high level of evidence at low risk of bias is sparse. As a result, these findings neither firmly establish the benefits or risks of CrossFit, nor provide definitive practical recommendations concerning CrossFit training. Despite this disparity, there is the existence of initial evidence of higher levels of sense of community, satisfaction, and motivation among CrossFit participants.

Additional file

Table S1. The Consolidated Standards of Reporting Trials (CONSORT). (DOCX 43 kb)

Acknowledgements

We would like to thank the authors of the cited articles who collaborated to obtain the data and “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior/ Programa de Excelência Acadêmica” (CAPES/PROEX), “Conselho Nacional de Desenvolvimento Científico e Tecnológico” (CNPq), “Fundação de Amparo à Pesquisa do Estado de Minas Gerais” (FAPEMIG), and “Fundação de Amparo à Pesquisa do Estado de São Paulo” (FAPESP).

No sources of funding were used to assist in the design, collection, analysis, and interpretation of data or in writing of this manuscript.

Availability of data and materials

Authors’ contributions.

JGC contributed in the design, collection, analysis, and interpretation of data and in writing. TJG contributed in the interpretation of data and in writing. FB and HSS helped in the design, collection, analysis, and interpretation of data and in writing. RM, BM, RS, CACF, AJH, and MB contributed in the design and interpretation of data and in writing.. ACA and JCS helped in the design, analysis, and interpretation of data and in writing. All authors read and approved the final manuscript.

Ethics Approval and Consent to Participate

Not applicable.

Competing interests

All authors – João Gustavo Claudino, Tim J. Gabbett, Frank Bourgeois, Helton de Sá Souza, Rafael Chagas Miranda, Bruno Mezêncio, Rafael Soncin, Carlos Alberto Cardoso Filho, Martim Bottaro, Arnaldo Jose Hernandez, Alberto Carlos Amadio and Julio Cerca Serrão – declare that they have no conflicting interests.

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João Gustavo Claudino, Email: rb.psu@ogjonidualc .

Tim J. Gabbett, Email: ua.moc.ecnamrofrepttebbag@mit .

Frank Bourgeois, Email: moc.liamg@iisioegruobaf .

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• Volume 6, Issue 1
• Recommendations for return to sport during the SARS-CoV-2 pandemic
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• Herbert Löllgen 1 ,
• Norbert Bachl 1 , 2 , 3 , 4 ,
• Theodora Papadopoulou 1 , 4 , 5 , 6 ,
• Andrew Shafik 7 , 8 ,
• Graham Holloway 5 ,
• Karin Vonbank 9 ,
• Nigel Edward Jones 5 , 10 , 11 ,
• Xavier Bigard 1 , 4 , 12 ,
• http://orcid.org/0000-0003-3089-1222 David Niederseer 13 ,
• Joachim Meyer 14 ,
• http://orcid.org/0000-0002-9191-9033 Borja Muniz-Pardos 15 ,
• Andre Debruyne 1 , 4 ,
• Petra Zupet 1 , 4 , 16 ,
• http://orcid.org/0000-0001-8901-9450 Jürgen M Steinacker 1 , 4 , 17 ,
• Bernd Wolfarth 4 , 18 ,
• http://orcid.org/0000-0002-6701-7603 James Lee John Bilzon 4 , 5 , 19 ,
• Anca Ionescu 1 ,
• http://orcid.org/0000-0002-1126-7849 Michiko Dohi 4 , 20 ,
• http://orcid.org/0000-0001-7098-0313 Jeroen Swart 4 , 21 ,
• http://orcid.org/0000-0003-4291-679X Victoriya Badtieva 4 , 22 , 23 ,
• Irina Zelenkova 15 , 22 ,
• Maurizio Casasco 1 , 4 , 24 ,
• Michael Geistlinger 4 , 25 ,
• http://orcid.org/0000-0002-2522-126X Luigi Di Luigi 4 , 26 ,
• Nick Webborn 27 , 28 ,
• Patrick Singleton 29 ,
• Mike Miller 29 ,
• Fabio Pigozzi 1 , 4 , 30 , 31 ,
• http://orcid.org/0000-0001-6210-2449 Yannis P Pitsiladis 1 , 4 , 32
• 1 European Federation of Sports Medicine Associations (EFSMA) , Lausanne , Switzerland
• 2 Institute of Sports Science , University of Vienna , Vienna , Austria
• 3 Austrian Institute of Sports Medicine , Vienna , Austria
• 4 International Federation of Sports Medicine (FIMS) , Lausanne , Switzerland
• 5 British Association of Sport and Exercise Medicine , Doncaster , UK
• 6 Defence Medical Rehabilitation Centre , Loughborough , UK
• 7 South Tyneside NHS Foundation Trust , Sunderland , UK
• 8 Newcastle Thunder Rugby , Newcastle , UK
• 9 Department of Pneumology, Pulmonary Function Laboratory, Medicine Clinic (KIMII) , University of Vienna , Vienna , Austria
• 10 British Cycling , Manchester , UK
• 11 University of Liverpool , Liverpool , UK
• 12 Union Cycliste Internationale (UCI) , Aigle , Switzerland
• 13 Heart Centre , University of Zurich , Zurich , Switzerland
• 14 Lung Center , Clinic Bogenhausen , Munich , Germany
• 15 GENUD (Growth, Exercise, Nutrition and Development) , University of Zaragoza , Zaragoza , Spain
• 16 Institute of Medicine and Sports , Ljubljana , Slovenia
• 17 Division of Sports and Rehabilitation Medicine , Ulm University Hospital , Ulm , Germany
• 18 Department of Sport Medicine , Humboldt University and Charité University School of Medicine , Berlin , Deutschland , Germany
• 19 Department for Health , University of Bath , Bath , UK
• 20 Sport Medical Center , Japan Institute of Sports Sciences , Tokyo , Japan
• 21 UCT Research Unit for Exercise Science and Sports Medicine , University of Cape Town (UCT) , Cape Town , South Africa
• 22 I.M. Sechenov First Moscow State Medical University (Sechenov University) , Moscow , Russian Federation
• 23 Moscow Research and Practical Centre for Medical Rehabilitation, Restorative and Sports Medicine , Moscow Healthcare Department , Moscow , Russian Federation
• 24 Italian Federation of Sports Medicine (FMSI) , Rome , Italy
• 25 Unit International Law, Department of Constitutional, International and European Law , University of Salzburg , Salzburg , Austria
• 26 Unit of Endocrinology, Department of Movement, Human and Health Sciences , University of Rome “Foro Italico” , Rome , Italy
• 27 School of Sport and Service Management , Eastbourne , UK
• 28 School of Sport, Exercise and Health Sciences , Loughborough University , Loughborough , UK
• 29 World Olympians Association , Lausanne , Switzerland
• 30 University of Rome “Foro Italico” , Rome , Italy
• 31 FIFA Medical Center of Excellence , Villa Stuart Sport Clinic , Rome , Italy
• 32 Collaborating Centre of Sports Medicine , University of Brighton , Eastbourne , UK
• Correspondence to Dr Yannis P Pitsiladis; Y.Pitsiladis{at}Brighton.ac.uk

In this viewpoint we make specific recommendations that can assist and make the return to sport/exercise as safe as possible for all those impacted – from the recreational athlete to the elite athlete. We acknowledge that there are varying rules and regulations around the world, not to mention the varying philosophies and numerous schools of thought as it relates to return to sport/exercise and we have been cognisant of this in our recommendations. Despite the varying rules and circumstances around the world, we believe it is essential to provide some helpful and consistent guidance for return to training and sport for sport and exercise physicians around the world at this most difficult time. The present viewpoint provides practical and medical recommendations on the resumption to sport process.

• communicable disease
• sports rehabilitation programs
• physical fitness

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjsem-2020-000858

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The COVID-19 pandemic and the restrictive measures adopted internationally in order to contain the virus has led to a disruption of organised sport at all levels. During the lockdown period, outdoor exercise was forbidden or partly restricted in some cases without access to sports facilities including gyms or sports centres. As the number of infections and hospitalisations decreased, the strict lockdown was gradually lifted. Team sports have commenced reintroducing their training routines in groups, and the Bundesliga reactivated the professional league behind closed doors on 16 May 2020 despite serious concerns raised by some in the scientific community. 1 Additional sporting competitions such as boxing, Ultimate Fighting Championship and Formula 1 are also scheduled to resume. 2 It is worth noting that social distancing is possible in some sports (eg, tennis, swimming, athletics and golf) whereas this is not always possible in other cases (eg, football, rugby, basketball, cycling and boxing), and careful measures of hygiene and control are especially needed for these more at risk sports to regulate the safety of sport resumption and to avoid possible infections. For more thorough information about the risk factors and symptoms to be considered to make the return to sport as safely as possible, consult Carmody et al 3 and Nieß et al . 4 The present viewpoint provides practical and medical recommendations on the resumption to sport process.

Group identification

During the resumption to sport process, the following groups must be distinguished (individuals below refer to both leisure time and professional athletes or persons starting new with regular physical activities). This group classification is a more developed version of that recently published by Phelan et al . 5 :

Individuals without symptoms and signs that never have been tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Individuals with a positive SARS-CoV-2 test without any COVID-19 symptoms but isolating at home (quarantine) under close medical observation (telephonic or video).

Individuals who experienced COVID-19 with mild symptoms, only needing outpatient treatment and quarantine for 14 days.

Individuals with moderate symptoms but had inpatient treatment due to an increased risk derived from pre-existing conditions (eg, asthma, diabetes).

Individuals with severe symptoms, inpatient treatment, including intensive care without artificial respiration.

Individuals with severe symptoms, inpatient treatment in intensive care and on artificial respiration.

It is imperative that a medical examination is performed in cooperation with a respiratory physician and/or cardiologist, if suspicious findings of the pulmonary and/or cardiovascular systems arise.

Recommendations for individual groups

In individuals without symptoms and signs of COVID-19 and without any pre-existing medical condition(s), risk stratification to safely resume to sport has to be evaluated through questionnaires compiling data related to personal and medical history, close contact with people with positive SARS-CoV-2 test, or contact with people of high risk of having been infected without being tested positive, or in so called hotspots. The individual has to confirm being free of any symptoms and this must be documented. Exercise testing is likely to be necessary in some sports due to the expected detraining after lockdown, 6 and exercise testing must be performed according to the latest COVID-19/SARS-CoV-2 health and safety regulations.

Resumption after 14 days quarantine. Examinations ought to include medical history, physical examination, 12-channel ECG, lung function assessment with typical respiratory signs and symptoms, and ECG stress test. 5 7–9 Echocardiography if clinically indicated.

Resumption after a quarantine period of 2 weeks and strict social distancing for another 2 weeks.

A medical examination by a sport and exercise medicine physician with medical history, physical examination, blood test focused on critical markers (eg, C-reactive protein, high sensitivity troponin-I, natriuretic peptides), and resting ECG (eg, changes of Q-wave, ST-stretch, T-wave). 8 Additional lung function assessment and stress test with ECG, blood gas analysis and spiroergometry as well as echocardiography are recommended if symptoms have involved respiratory or cardiac impairment. Return to regular sport is possible 3–4 weeks after beginning of the symptoms under medical surveillance for 6 months after return to sport if any symptoms are present but not limiting return to sport.

Same procedure as for group 3 but including compulsory ergometry with blood gas analysis and/or spiroergometry. 3–5 10 Chest X-ray examination and depending on the findings obtained during the inpatient stay, high-resolution CT of the thorax in the most severe cases always in consultation with a lung specialist. Cardiac examinations depending on medical history, symptoms and signs, cardio-MRI after consultation with a cardiologist. Return to sport will vary from 2 to 6 months depending on the severity of respiratory (lung) and/or cardiac (myocarditis) involvement.

Groups 5 and 6

Following SARS-CoV-2 discharge, rehabilitation is recommended. A complete pulmonary and cardiological examination is necessary (‘cardiac markers’ such as high sensitivity troponin-I or natriuretic peptides) including resting ECG, lung function, echocardiography, stress test with ECG and blood gas analysis. 8 10–13 Return to sport will be after several months depending on the severity and completeness of recovery.

Depending on previous findings in heart rate, CT of the thorax and cardiac MRI examination in consultation with a respiratory physician and cardiologist, hospital discharge can take place. A final medical check and sports statement is mandatory.

Resumption of sport can occur 10–14 days after complete recovery from SARS CoV-2 infection for athletes included in groups 1 and 2. In patients with more severe organ involvement, pneumonia, myocarditis or neurological signs, an individualised plan is necessary. 4 5 Testing for SARS CoV-2 can be carried out to support a return to play decision but is not essential unless stipulated (eg, National/International Sports Federation, Government).

Conclusions

An adequate assessment of the resumption of sporting activity is based on a case-by-case decision that must consider the individual situation of the athlete including pre-existing conditions, the type of sport and the risk of infection from other athletes (eg, increased risk in contact/team sports). The recommendation to return to play will be based on the results of the examination and individual assessment in consultation with the sport and exercise medicine physician, specialists in pulmonary medicine and sport cardiology (or extended multidisciplinary team), coaches and training specialists. After a contact ban, an athlete should be provided with recommendations on sports resumption that are in accordance with national and regional guidelines. After a longer period of interruption in sport caused by more severe health issues, increases in training should be gradual and individualised by monitoring signs and symptoms of the health issue.

• Corsini A ,
• Bisciotti GN ,
• Eirale C , et al
• ↵ Coronavirus and sports: what happened in April 2020 | Sports| German football and major international sports news | DW | 01.05.2020 . Available: https://www.dw.com/en/coronavirus-sports-cancellations/a-52569936 [Accessed 8 May 2020 ].
• Carmody S ,
• Borodina M , et al
• Friedmann-Bette B , et al
• Janse van Rensburg DCC ,
• Jansen van Rensburg A , et al
• Schellhorn P ,
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• Bhatia RT ,
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Twitter @DavidNiederseer

Contributors All authors contributed significantly to merit publication and in accordance with the BJSM instructions to authors.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; externally peer reviewed.

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Physical activity more effective than counseling or medications to manage depression

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University of South Australia researchers are calling for exercise to be a mainstay approach for managing depression as a new study shows that physical activity is 1.5 times more effective than counseling or the leading medications.

Image Credit: University of South Australia

Published in the British Journal of Sports Medicine, the review is the most comprehensive to date, encompassing 97 reviews, 1039 trials and 128,119 participants. It shows that physical activity is extremely beneficial for improving symptoms of depression, anxiety, and distress.

Specifically, the review showed that exercise interventions that were 12 weeks or shorter were most the effective at reducing mental health symptoms, highlighting the speed at which physical activity can make a change.

The largest benefits were seen among people with depression, pregnant and postpartum women, healthy individuals, and people diagnosed with HIV or kidney disease.

According to the World Health Organization, one in every eight people worldwide (970 million people) live with a mental disorder. Poor mental health costs the world economy approximately $2.5 trillion each year, a cost projected to rise to $6 trillion by 2030. In Australia, an estimated one in five people (aged 16–85) have experienced a mental disorder in the past 12 months.

Lead UniSA researcher, Dr Ben Singh, says physical activity must be prioritized to better manage the growing cases of mental health conditions.

Physical activity is known to help improve mental health. Yet despite the evidence, it has not been widely adopted as a first-choice treatment. Our review shows that physical activity interventions can significantly reduce symptoms of depression and anxiety in all clinical populations, with some groups showing even greater signs of improvement. Higher intensity exercise had greater improvements for depression and anxiety, while longer durations had smaller effects when compared to short and mid-duration bursts. We also found that all types of physical activity and exercise were beneficial, including aerobic exercise such as walking, resistance training, Pilates, and yoga. Importantly, the research shows that it doesn't take much for exercise to make a positive change to your mental health." Dr Ben Singh, Lead UniSA Researcher

Senior researcher, UniSA's Prof Carol Maher, says the study is the first to evaluate the effects of all types of physical activity on depression, anxiety, and psychological distress in all adult populations.

"Examining these studies as a whole is an effective way to for clinicians to easily understand the body of evidence that supports physical activity in managing mental health disorders.

"We hope this review will underscore the need for physical activity, including structured exercise interventions, as a mainstay approach for managing depression and anxiety."

University of South Australia

Singh, B., et al. (2023) Effectiveness of physical activity interventions for improving depression, anxiety and distress: an overview of systematic reviews. British Journal of Sports Medicine. doi.org/10.1136/bjsports-2022-106195 .

Posted in: Medical Research News | Medical Condition News | Healthcare News

Tags: Anxiety , Depression , Exercise , HIV , Kidney , Kidney Disease , Medicine , Mental Disorder , Mental Health , Physical Activity , Research , Sports Medicine , Walking , Yoga

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Griby i mukhi : a historical contextualization of the esoteric mushroom religion of moscow conceptualism: fungal erotic imagery of entheogens and insects.

“ The most beautiful thing we can experience is the mysterious. It is the source of all true art and all science. He to whom this emotion is a stranger, who can no longer pause to wonder and stand rapt in awe, is as good as dead: his eyes are closed. The insight into the mystery of life, coupled with fear, has also given rise to religion. To know what is impenetrable to us really exists, manifesting itself as the highest wisdom and the most radiant beauty, which our dull faculties can comprehend only in their most primitive forms—this knowledge, this feeling is at the center of true religiousness .” Albert Einstein ( 1954 ).

1. Preliminary Remarks

2. introducing the subject: esoteric context and the fungi.

“I have come to the conclusion that much can be learned about music by devoting oneself to the mushroom.”. —John Cage, 1954

2.1. Mushrooms, Humans, and Religious Systems: Analytical Observations

2.2. new age esotericism, gnosticism, and the world of fungi: the problematics of spermic religious imagery.

Zohar Sitrei Torah 1: 147b–148b, ( Jacob’s Journey ) ‘ The secret of secrets: Out of the scorching noon of Isaac , out of the dregs of wine, a fungus emerged, a cluster , male and female together, red as a rose , expanding in many directions and paths . The male is called Sama’el , his female is always included within him . Just as it is on the side of holiness , so it is on the other side: male and female embracing one another . The female of Sama’el is called Serpent , Woman of Whoredom, End of All Flesh, End of Days . Two evil spirits joined together: the spirit of the male is subtle; the spirit of the female is diffused in many ways and paths but joined to the spirit of the male .’ ( Sitrei Torah is translated in ( Zohar 1983, p. 77 ))

“ If you force me to say something still more daring, it is his essence to be pregnant (kuein) with all things and to make them .”

“ We know you, O intellectual Light, O Life of life, We know you, O Womb of every creature, We know you, O Womb pregnant by the member [physis = phallus] of the Father. We know you, O eternal permanence of the begetting/pregnant Father .”

2.3. Fungal Eros: Phallic Occult Esotericism and Russian Cultural Links

2.4. mushroom art: several important visual models, 3. russian post-avant-garde conceptualism: the case of moscow milieus, the world of flies complements the universe of fungi.

In the garden, if you glance, you’ll see insects, old friends by chance , As if in cages, they now stay, perched on branches in dismay . Bees and flies, a buzzing sound, they once would dance and circle ‘round , In your ear, a letter Zh , 22   they’d bite you and your Shura, free . Now unhealthy, pale to see, Petrova the flea, sadly , Not a sight for pleasant eyes, trapped beneath the somber skies . Life is harsh, no comfort found, dawn winds howl with mournful sound , Wolves tear at the hapless hare, life’s cruel tale laid bare . From the oak, a bird takes flight, seeking food by day and night , Providence, with brutal charm, offers worms instead of farm . Calves beneath the butcher’s blade, fish ensnared in nets displayed , Lions roar through night’s domain, cats on chimneys cry in pain . In this world, a sorrowed dance, bourgeois, worker, no chance , Both these beetles in their class plight, struggle through the endless night . (1932). 23

“ Look now at Behemoth, which I made as I made you:   He eats grass like an ox . Look at his strength in his balls, and his power in the muscles of his penis . He makes his penis stiff like a cedar, the sinews of his balls are tightly wound . His balls are tubes of bronze, His balls like bars of iron ”. (Quick 345)

4. Concluding Remarks: Fungi, Esoteric Sensual Occult, and Russian (Post)-Avant-Garde

Fa-Fa I’m nervous, I’m loyal, so far… I’m tender . Fa-fa, fa-fa, fa-fa, fa-fa . Hallucinogens, the South… There’s plenty of us! The essence is coming . I’m a fugitive, I’m poor, so far… I’m white Fa-fa, fa-fa, fa-fa, fa-fa . Smokey grandfathers, snow… I’d like to go on the run , There’s an essence… Aha! I’m nervous, I’m loyal, bye-bye . I’m harmful . Fa-fa, fa-fa, fa-fa, fa-fa, fa-fa . If I were magic, taiga … I’d be on fire, I’d be living … The essence is coming! yeah . 25

… you inspire knowledge To both heart and mind: The distance is clearer When you look at the moon And time and separation , And the aunt of the arts The occult science , And many different feelings . The faces of the dead You make them pretty , And sometimes you dream …you’ll make a mindless mouse You confuse, you broadcast , You tumble your sickle And you accurately mark Only profit and damage . Your name is Hecate , Your name is Shepherd , The cats are your pay And a crowing rooster . 29

Share and Cite

Ioffe, D. Griby i Mukhi : A Historical Contextualization of the Esoteric Mushroom Religion of Moscow Conceptualism: Fungal Erotic Imagery of Entheogens and Insects. Religions 2024 , 15 , 777. https://doi.org/10.3390/rel15070777

Ioffe D. Griby i Mukhi : A Historical Contextualization of the Esoteric Mushroom Religion of Moscow Conceptualism: Fungal Erotic Imagery of Entheogens and Insects. Religions . 2024; 15(7):777. https://doi.org/10.3390/rel15070777

Ioffe, Dennis. 2024. " Griby i Mukhi : A Historical Contextualization of the Esoteric Mushroom Religion of Moscow Conceptualism: Fungal Erotic Imagery of Entheogens and Insects" Religions 15, no. 7: 777. https://doi.org/10.3390/rel15070777

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β-alanine supplementation to improve exercise capacity and performance: a systematic review and meta-analysis

Affiliations.

• 1 Applied Physiology and Nutrition Research Group, University of São Paulo, São Paulo, Brazil.
• 2 Musculoskeletal Physiology Research Group, Sport, Health and Performance Enhancement Research Centre, Nottingham Trent University, Nottingham, UK.
• 3 School of Health Sciences, Robert Gordon University, Aberdeen, UK.
• PMID: 27797728
• DOI: 10.1136/bjsports-2016-096396

Objective: To conduct a systematic review and meta-analysis of the evidence on the effects of β-alanine supplementation on exercise capacity and performance.

Design: This study was designed in accordance with PRISMA guidelines. A 3-level mixed effects model was employed to model effect sizes and account for dependencies within data.

Data sources: 3 databases (PubMed, Google Scholar, Web of Science) were searched using a number of terms ('β-alanine' and 'Beta-alanine' combined with 'supplementation', 'exercise', 'training', 'athlete', 'performance' and 'carnosine').

Eligibility criteria for selecting studies: Inclusion/exclusion criteria limited articles to double-blinded, placebo-controlled studies investigating the effects of β-alanine supplementation on an exercise measure. All healthy participant populations were considered, while supplementation protocols were restricted to chronic ingestion. Cross-over designs were excluded due to the long washout period for skeletal muscle carnosine following supplementation. A single outcome measure was extracted for each exercise protocol and converted to effect sizes for meta-analyses.

Results: 40 individual studies employing 65 different exercise protocols and totalling 70 exercise measures in 1461 participants were included in the analyses. A significant overall effect size of 0.18 (95% CI 0.08 to 0.28) was shown. Meta-regression demonstrated that exercise duration significantly (p=0.004) moderated effect sizes. Subgroup analyses also identified the type of exercise as a significant (p=0.013) moderator of effect sizes within an exercise time frame of 0.5-10 min with greater effect sizes for exercise capacity (0.4998 (95% CI 0.246 to 0.753)) versus performance (0.1078 (95% CI -0.201 to 0.416)). There was no moderating effect of training status (p=0.559), intermittent or continuous exercise (p=0.436) or total amount of β-alanine ingested (p=0.438). Co-supplementation with sodium bicarbonate resulted in the largest effect size when compared with placebo (0.43 (95% CI 0.22 to 0.64)).

Summary/conclusions: β-alanine had a significant overall effect while subgroup analyses revealed a number of modifying factors. These data allow individuals to make informed decisions as to the likelihood of an ergogenic effect with β-alanine supplementation based on their chosen exercise modality.

Keywords: Amino acids; Exercise; Meta-analysis; Supplements.

Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

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• Volume 55, Issue 6
• Infographic. Clinical recommendations for return to play during the COVID-19 pandemic
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• Herbert Löllgen 1 , 2 ,
• Norbert Bachl 1 , 3 , 4 , 5 ,
• Theodora Papadopoulou 1 , 3 , 6 , 7 ,
• Andrew Shafik 7 ,
• Graham Holloway 7 ,
• Karin Vonbank 8 ,
• Nigel Edward Jones 7 , 9 ,
• Xavier Bigard 1 , 10 ,
• http://orcid.org/0000-0003-3089-1222 David Niederseer 11 ,
• Joachim Meyer 12 , 13 ,
• Borja Muniz-Pardos 14 ,
• Andre Debruyne 1 , 3 ,
• Petra Zupet 1 , 15 ,
• http://orcid.org/0000-0001-6210-2449 Jürgen M Steinacker 1 , 3 , 16 ,
• Bernd Wolfarth 3 , 17 ,
• http://orcid.org/0000-0002-6701-7603 James Lee John Bilzon 3 , 7 , 18 ,
• Anca Ionescu 1 , 19 ,
• http://orcid.org/0000-0002-1126-7849 Michiko Dohi 3 , 20 ,
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• Fabio Pigozzi 1 , 3 , 29 , 30 ,
• http://orcid.org/0000-0001-6210-2449 Yannis P Pitsiladis 1 , 3 , 31
• 1 European Federation of Sports Medicine Associations (EFSMA) , Lausanne , Switzerland
• 2 Cardiology Practice , Remscheid , Germany
• 3 International Federation of Sports Medicine (FIMS) , Lausanne , Switzerland
• 4 Institute of Sports Science , University of Vienna , Vienna , Austria
• 5 Austrian Institute of Sports Medicine , Vienna , Austria
• 6 Lower Limbs-ADMR Hip & Groin , Defence Medical Rehabilitation Centre Headley Court , Loughborought , UK
• 7 British Association of Sport and Exercise Medicine , Doncaster , UK
• 8 Department of Pulmology , Medical University of Vienna , Vienna , Austria
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• 11 Department of Cardiology , University Heart Center Zurich , Zurich , Switzerland
• 12 German Respiratory Society (DGP) , Berlin , Germany
• 13 Lungenzentrum (Bogenhausen-Harlaching) , München Klinik , Munich , Germany
• 14 GENUD (Growth, Exercise, Nutrition and Development), Department of Physiatry and Nursing , University of Zaragoza , Zaragoza , Spain
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• 20 Sport Medical Center , Japan Institute of Sports Sciences , Tokyo , Japan
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• 23 Moscow Research and Practical Centre for Medical Rehabilitation, Restorative and Sports Medicine , Moscow Healthcare Department , Moscow , Russian Federation
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• 31 Collaborating Centre of Sports Medicine , University of Brighton , Eastbourne , UK
• Correspondence to Professor Yannis P Pitsiladis, Collaborating Centre of Sports Medicine, University of Brighton, Eastbourne BN20 7SN, UK; Y.Pitsiladis{at}Brighton.ac.uk

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• communicable disease
• elite performance
• exercise testing

COVID-19 and return to play

The world of sport has recently returned to training and competition following suspension due to the COVID-19 pandemic. It is concerning that a number of athletes have tested positive for COVID-19 after returning to competition. 1 Numerous authors have attempted to address return to play given the importance and complexity of the issue, with notable attention on possible cardiac implications. 2–6

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Correction notice This article has been corrected since it published Online First. Ref 8 has been corrected.

Contributors All authors contributed significantly and in line with the instructions to authors to merit publication.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; externally peer reviewed.

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