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The efficiency index (Effindex) combines internal and external loads, and it has been considered a promising tool to evaluate physical fitness status. However, its real applicability and limitations have not been elucidated yet. To examine and discuss the findings from studies that used Effindex as a tool for the evaluation of physical fitness status in team sports. A systematic search was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The databases conferred were PubMed, Scopus, Web of Science, SPORTDiscus, MEDLINE and CINAHL. The articles selected were published up to March 2021. Fourteen articles were included after meeting the inclusion criteria. A wide variety of combinations of external and internal loading parameters to calculate Effindex were found. The pooled sample included 349 male participants (23 ± 3 years). Fifty-nine percent of the sample were soccer players, 20% rugby players, 10% Australian football players, 7% hurling players, and 4% basketball players. Most Effindex calculations used total distance (TD) divided by heart rate derived parameters. However, recent studies have suggested the use of accelerations as the external load parameter. Effindex is a simple and powerful tool for the evaluation of physical fitness status in team sports athletes. The disparity of external and internal loading parameters used to calculate Effindex may affect its sensitivity to detect changes in fitness status in different team sport settings. More studies with indoor team sports and female athletes are warranted.

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PURPOSE: The aim of this study was to systematically review evidence on the prevalence and magnitude of side effects associated with caffeine supplementation in athletes. METHODS: Systematic searches through the PubMed, VHL, Scopus, and Web of Science databases were conducted according to the PRISMA guidelines. Peer-reviewed articles written in English that reported the prevalence/percentage or magnitude/effect size of side effects after caffeine supplementation in athletes in a sports context were included. Studies were grouped by the dose of caffeine administered as follows: low = ≤ 3.0 mg/kg; moderate = from 3.1 to 6.0 mg/kg; high = ≥ 6.1 mg/kg. The magnitude of the side effects was calculated with effect sizes. RESULTS: The search retrieved 25 studies that met the inclusion/exclusion criteria with a pooled sample of 421 participants. The supplementation with caffeine produced a higher prevalence or magnitude of all side effects under investigation when compared to placebo/control situations. The prevalence (magnitude) was between 6 and 34% (ES between 0.13 and 1.11) for low doses of caffeine, between 0 and 34% (ES between -0.13 and 1.20) for moderate doses of caffeine, and between 8 and 83% (ES between 0.04 and 1.52) with high doses of caffeine. The presence of tachycardia/heart palpitations and the negative effects on sleep onset had the highest prevalence and magnitude, in athletes using supplementation with caffeine. CONCLUSION: In summary, caffeine supplementation in the doses habitually used to enhance physical performance produces several side effects, both after exercise and at least 24 h after the ingestion. However, the prevalence and magnitude of side effects with high doses of caffeine were habitually higher than with low doses of caffeine. From a practical perspective, using ~3.0 mg/kg of caffeine may be the dose of choice to obtain the ergogenic benefits of caffeine with the lowest prevalence and magnitude of side effects.

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We performed a systematic review with meta-analysis of randomized controlled trials (RCTs) to assess the effects of strength training (ST), as compared to alternative multimodal or unimodal exercise programs, on the number of falls in older adults (≥60 years). Ten databases were consulted (CINAHL, Cochrane Library, EBSCO, EMBASE, PEDro, PubMed, Scielo, Scopus, SPORTDiscus and Web of Science), without limitations on language or publication date. Eligibility criteria were as follows: RCTs with humans ≥60 years of age of any gender with one group performing supervised ST and a group performing another type of exercise training, reporting data pertaining falls. Certainty of evidence was assessed with Grading of Recommendations, Assessment, Development and Evaluation (GRADE). Meta-analysis used a random effects model to calculate the risk ratio (RR) for number of falls. Five RCTs with six trials were included (n = 543, 76% women). There was no difference between ST and alternative exercise interventions for falls (RR = 1.00, 95% CI 0.77-1.30, p = 0.99). The certainty of evidence was very low. No dose-response relationship could be established. In sum, ST showed comparable RR based on number of falls in older adults when compared to other multimodal or unimodal exercise modalities, but evidence is scarce and heterogeneous, and additional research is required for more robust conclusions. Registration: PROSPERO CRD42020222908.

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BACKGROUND: Given the severe economic and performance implications of hamstring injuries, there are different attempts to identify their risk factors for subsequently developing injury prevention strategies to reduce the risk of these injuries. One of the strategies reported in the scientific literature is the application of interventions with eccentric exercises. To verify the effectiveness of these interventions, different eccentric strength measurements have been used with low-cost devices as alternatives to the widespread used isokinetic dynamometers and the technically limited handheld dynamometers. Therefore, the purpose of the present systematic review was to summarize the findings of the scientific literature related to the evaluation of eccentric strength of hamstring muscles with these new technologies. METHODS: Systematic searches through the PubMed, Scopus, and Web of Science databases, from inception up to April 2020, were conducted for peer reviewed articles written in English, reporting eccentric strength of hamstrings assessed by devices, different to isokinetic and handheld dynamometers, in athletes. RESULTS: Seventeen studies were finally included in the review with 4 different devices used and 18 parameters identified. The pooled sample consisted of 2893 participants (97% male and 3% female: 22 ± 4 years). The parameters most used were peak force (highest and average), peak torque (average and highest), and between-limb imbalance (left-to-right limb ratio). There is inconsistency regarding the association between eccentric hamstrings strength and both injury risk and athletic performance. There is no standardized definition or standardization of the calculation of the used parameters. CONCLUSIONS: The current evidence is insufficient to recommend a practical guide for sports professionals to use these new technologies in their daily routine, due to the need for standardized definitions and calculations. Furthermore, more studies with female athletes are warranted. Despite these limitations, the eccentric strength of hamstring muscles assessed by different devices may be recommended for monitoring the neuromuscular status of athletes.

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BACKGROUND: The application of artificial intelligence (AI) opens an interesting perspective for predicting injury risk and performance in team sports. A better understanding of the techniques of AI employed and of the sports that are using AI is clearly warranted. The purpose of this study is to identify which AI approaches have been applied to investigate sport performance and injury risk and to find out which AI techniques each sport has been using. METHODS: Systematic searches through the PubMed, Scopus, and Web of Science online databases were conducted for articles reporting AI techniques or methods applied to team sports athletes. RESULTS: Fifty-eight studies were included in the review with 11 AI techniques or methods being applied in 12 team sports. Pooled sample consisted of 6456 participants (97% male, 25 ± 8 years old; 3% female, 21 ± 10 years old) with 76% of them being professional athletes. The AI techniques or methods most frequently used were artificial neural networks, decision tree classifier, support vector machine, and Markov process with good performance metrics for all of them. Soccer, basketball, handball, and volleyball were the team sports with more applications of AI. CONCLUSIONS: The results of this review suggest a prevalent application of AI methods in team sports based on the number of published studies. The current state of development in the area proposes a promising future with regard to AI use in team sports. Further evaluation research based on prospective methods is warranted to establish the predictive performance of specific AI techniques and methods.

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BACKGROUND: Sleep quality is an essential component of athlete's recovery. However, a better understanding of the parameters to adequately quantify sleep quality in team sport athletes is clearly warranted. OBJECTIVE: To identify which parameters to use for sleep quality monitoring in team sport athletes. METHODS: Systematic searches for articles reporting the qualitative markers related to sleep in team sport athletes were conducted in PubMed, Scopus, SPORTDiscus and Web of Science online databases. The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. For the meta-analysis, effect sizes with 95% CI were calculated and heterogeneity was assessed using a random-effects model. The coefficient of variation (CV) with 95% CI was also calculated to assess the level of instability of each parameter. RESULTS: In general, 30 measuring instruments were used for monitoring sleep quality. A meta-analysis was undertaken on 15 of these parameters. Four objective parameters inferred by actigraphy had significant results (sleep efficiency with small CV and sleep latency, wake episodes and total wake episode duration with large CV). Six subjective parameters obtained from questionnaires and scales also had meaningful results (Pittsburgh Sleep Quality Index (sleep efficiency), Likert scale (Hooper), Likert scale (no reference), Liverpool Jet-Lag Questionnaire, Liverpool Jet-Lag Questionnaire (sleep rating) and RESTQ (sleep quality)). CONCLUSIONS: These data suggest that sleep efficiency using actigraphy, Pittsburgh Sleep Quality Index, Likert scale, Liverpool Jet-Lag Questionnaire and RESTQ are indicated to monitor sleep quality in team sport athletes. PROSPERO REGISTRATION NUMBER: CRD42018083941.

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BACKGROUND: The ability to jump has been related to muscle strength and power, speed and amplitude of the lower limbs movements, and specifically for the elderly, the vertical jump has been shown to be a good predictor of functional capacity and risk of falling. The use of a mobile application (App) which can measure the vertical jump (i.e., iPhone App My Jump) has recently emerged as a simple, cheap and very practical tool for evaluation of jump ability. However, the validity of this tool for the elderly population has not been tested yet. The elderly usually perform very low jumps and therefore the signal-to-noise ratio may compromise the validity and reliability of this method. Thus, the aim of the current study was to verify the validity and reliability of the iPhone App "My Jump" for the evaluation of countermovement jump (CMJ) height within an elderly population. METHODS: After familiarization, 41 participants performed three CMJs assessed via a contact mat and the My Jump App. The intraclass correlation coefficient (ICC) was used to verify the relative reliability, while the coefficient of variation (CV%) and the typical error of measurement (TEM) were used to verify the absolute reliability. Pearson's correlation coefficient was used to verify the strength of the relationship between methods (i.e., concurrent validity), a Bland-Altman plot to show their agreement, and the Student's t-test to identify systematic bias between them. For reliability analyses, all jumps were considered (i.e., 123). All jumps (i.e., 123), the average height of each attempt (i.e., 41), and the highest jump, were considered for validity analyses. RESULTS: The CMJ height of the highest jump was 10.78 ± 5.23 cm with contact mat, and 10.87 ± 5.32 with My Jump App, with an identified systematic bias of 0.096 cm (P = 0.007). There was a nearly perfect correlation between methods (r = 0.999; P = 0.000, in all cases) with a very good agreement observed (0.3255 to -0.5177 cm, 0.2797 to -0.5594 cm, and 0.3466 to -0.6264 cm, for highest jump height, average jump height, and all jump heights, respectively). The ICC of the My Jump App was 0.948, the TEM was 1.150 cm, and the CV was 10.10%. CONCLUSION: Our results suggest that the My Jump App is a valid and reliable tool compared to the contact mat for evaluating vertical jump performance in the elderly. Therefore, it allows a simple and practical assessment of lower limbs' power in this population. For the elderly, as well as for other populations with low jumping heights, the highest jump height and the average jump height could be used indistinctly.

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ABSTRACT Introduction: The best strategy for improving knee extensor power, a major functional capacity indicator in older adults, is power training. Nonetheless, the training intensity required to induce optimal gains is yet to be found. Objective: Our purpose was to compare knee extensor peak power responses between low, moderate, and high intensity load conditions (30%, 50% and 70% of 1RM). Methods: Thirteen sedentary elderly women performed six knee extensions in each load condition, calculating knee extensor mechanical work/power output and knee extension peak angular velocity. Results: No difference in peak power was found between the high (207.0 ± 68.1 W) and moderate (206.1 ± 71.6 W) load conditions (p = 0.994), and both had higher values (p ≤0.004) than the low intensity condition (135.6 ± 56.3 W). Conclusion: Moderate load at 50% of 1RM appears to be the preferred strategy for inducing knee extensor power output because in contrast with the high intensity condition, the moderate load yielded higher angular peak velocity, which is also a functional indicator. Level of Evidence ll; Therapeutic studies - Investigating treatment results.

RESUMO Introdução: A melhor estratégia para melhorar a potência dos extensores do joelho, principal indicador da capacidade funcional em idosos, é o treinamento de força. No entanto, a intensidade do treinamento exigida para induzir a maiores benefícios ainda não é conhecida. Objetivo: Nosso objetivo consistiu em comparar as respostas de potência máxima dos extensores do joelho entre as condições de carga baixa, moderada e de alta intensidade (30%, 50% e 70% de uma repetição máxima). Métodos: Treze mulheres idosas sedentárias realizaram seis extensões de joelho em cada condição de carga, sendo calculado o trabalho mecânico/débito de força e a velocidade angular máxima (ou pico) dos extensores do joelho. Resultados: Não houve diferença significativa na potência máxima entre as condições de carga alta ((207,0 ± 68,1 W) e moderada (206,1 ± 71,6 W) (p = 0,994), e ambas apresentaram valores maiores (p ≤ 0,004) do que a condição de baixa intensidade (135,6 ± 56,3 W). Conclusão: A carga moderada a 50% de 1RM parece ser a estratégia preferida para induzir o débito de força dos extensores do joelho, uma vez que quando comparada com a condição de alta intensidade, a carga moderada apresentou um pico de velocidade angular maior, o que também é um indicador funcional. Nível de Evidência II; Estudos terapêuticos - Investigação dos resultados do tratamento.

RESUMEN Introducción: La mejor estrategia para mejorar la potencia de los extensores de la rodilla, principal indicador de la capacidad funcional en personas de la tercera edad, es el entrenamiento de fuerza. Sin embargo, la intensidad del entrenamiento exigida para inducir a mayores beneficios aún no es conocida. Objetivo: Nuestro objetivo consistió en comparar las respuestas de potencia máxima de los extensores de la rodilla entre las condiciones de carga baja, moderada y de alta intensidad (30%, 50% y 70% de una repetición máxima). Métodos: Trece mujeres de la tercera edad sedentarias realizaron seis extensiones de rodilla en cada condición de carga, siendo calculado el trabajo mecánico/débito de fuerza y la velocidad angular máxima (o pico) de los extensores de la rodilla. Resultados: No hubo diferencia significativa en la potencia máxima entre las condiciones de carga alta ((207,0 ± 68,1 W) y moderada (206,1 ± 71,6 W) (p = 0,994), y ambas presentaron valores mayores (p ≤ 0,004) que la condición de baja intensidad (135,6 ± 56,3 W). Conclusión: La carga moderada a 50% de 1RM parece ser la estrategia preferida para inducir el débito de fuerza de los extensores de la rodilla, dado que cuando comparada con la condición de alta intensidad, la carga moderada presentó un pico de velocidad angular mayor, lo que también es un indicador funcional. Nivel de Evidencia II; Estudios terapéuticos - Investigación de los resultados del tratamiento.

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BACKGROUND: 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. METHODS: 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. RESULTS: 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.