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Overtraining Syndrome
... accelerometers and pedometers) provide objective monitoring of physical activity. Of importance to the present investigation is that the step counts measured by accelerometers and pedometers can be used to estimate energy expenditure during physical activity (50). ...
... momentary) RPE can be measured on a moment-to-moment basis. In addition, a RPE-session can be obtained immediately following completion of an exercise task (50). The RPE-session provides a measure of the global exertion experienced during the just completed task. ...
... The RPE-session provides a measure of the global exertion experienced during the just completed task. Several previous investigations conclude that the RPE-session provides a psychophysiological estimate of the average exertion experienced during either a steady or non-steady state exercise session (50,165,175). RPEsession was originally used to monitor monotony and intensity of training in athletes. Recent research has focused on the use of RPE-session in non-athletic populations to monitor the relative intensity of a physical activity bout. ...
PURPOSE: The primary purposes of this investigation were (a) to examine the validity of the PAI, (b) to develop a statistical model to predict cumulative Kcal expenditure using PAI as the predictor variable and (c) to develop a statistical model to predict total Kcal expenditure using PAItotal and selected physiological and behavioral measures as the predictor variables for children and adolescents performing load incremented maximal treadmill exercise. The secondary purpose of the study was to develop a prediction model to estimate total Kcal expenditure using the PAI (session) alone and in combination with selected physiological measures as the predictor variables. METHODS: Eighty-four children and adolescents (12.5±2.4 yrs) performed a maximal Bruce treadmill (TM) protocol. During TM, heart rate (HR), oxygen consumption (VO2), rating of perceived exertion (RPE-overall), pedometer step count, and Kcal expenditure were measured. Post-TM, RPE-session was obtained and a physical activity questionnaire administered. The PAI, PAItotal, and PAI (session) were calculated as:
PAI = Cumulative step count x RPE-overall
PAItotal = Total step count x RPE-overall at test termination
PAI (session) = Total step count x RPE-session
RESULTS: Multiple regression analyses revealed a strong, positive relation between the PAI score and VO2 in L.min-1(r=0.607, p<0.05), VO2 in mL.kg-1.min-1 (r=0.725, p<0.05) and HR in beats.min-1 (r=0.755, p<0.05). These findings established a high level of concurrent validity for the PAI. The following models to predict Kcal expenditure were developed:
Model I : Cumulative Kcal = 21.632 + 0.006(PAI) p<0.05, SEE=17.59, r=0.74, r2=0.54.
Model II : Total Kcal = -11.59+0.002(PAItotal)+27.245(VO2max) p<0.05, SEE=15.37, r=0.86, r2=0.739.
Model V : Total Kcal = 38.6 + 0.004(PAIsession), p<0.05, SEE=24.23, r=0.36, r2=0.13.
Model VI : Total Kcal = -64.759+26.998(VO2max)+0.305(HRmax)+0.001 (PAIsession) p<0.05, SEE=10.46, r = 0.918 , r2 = 0.842.
In comparison to the PAI (session), PAI was a stronger predictor of Kcal expenditure during a load incremented treadmill protocol in a sample of children and adolescents. CONCLUSIONS: The PAI has public health implications, provides an easy tool to estimate total physical activity load (i.e. volume x intensity) and predicts Kcal expenditure in children and adolescents performing standard treadmill exercise protocols. Generalizability of findings is limited to healthy children and adolescents performing load incremented maximal treadmill exercise.
... Based on the results of the quantification of training load for the 8 footballers according to the figures from 1 to 8, we note that in the majority of the cases, the AL is higher than the CL at the end of each week, which explains that at the end of each week the players and more and more tired, which makes him susceptible to develop an injury [5][6][7][8][9][10][11][12][13][14][15][16][17][18], and this result confirms that the training program delivered by the coach is not adapted to the athletes' requirements. ...
The aim of this paper is to use a training load quantification tool (RPE) to evaluate if the training load programmed by the coach is appropriate to the characteristics of these footballers. The study was conducted at the football section of the Sale Sports Association, Morocco, on a sample of 8 football players who practice in the club of the Association, aged between 18 and 21 years, the study was established during a mesocycle in a period from 18/03/2019 to 20/04/2019. For the quantification of the training load (TL) we chose the (RPE) tool, where each footballer must give his own perception of the effort felt in each training session, taking into consideration also the duration of the session. This will allow us to calculate the intensity of the session estimated, on a scale from 0 to 10. Based on the results of the quantification of training load for the 8 footballers, we note that in the majority of the cases, the acute load (AL) is higher than the chronic load (CL) at the end of each week. On the other hand, for the monotony index (MI) that provides information on the negative adaptations of training and overtraining, we note that it present a high value among the majority of footballers (1.8UA <MI <2.1UA). For the average of the ratio of the training load: acute/chronic, we note that for the first three footballers the training loads are higher compared to the others. The monitoring training load help to better conceptualize the adaptations of the athlete to the training, and also allows the prediction of the performance.
... El proceso de adaptación de un deportista se define como las transformaciones de los sistemas funcionales físicos y psíquicos que se producen con la repetición sucesiva de estímulos de entrenamiento que llevan a estados de fatiga aguda que requieren un periodo óptimo de recuperación (Arrese, 2012). La dificultad estriba en establecer la diferencia en entrenar lo justo para conseguir el mejor estado de prestación posible sin perjudicar la salud y sin realizar una preparación excesiva, que puede provocar daño muscular, lesiones, sobrecargas o una combinación de estos procesos, abocando al sujeto a una situación de fatiga crónica y finalmente sobreentrenamiento (Foster & Lehmann, 1997). ...
Las mediciones de la variabilidad de la frecuencia cardiaca (VFC) en atletas de resistencia de alto nivel han mostrado potencial para ser usadas en la monitorización de las respuestas de adaptación a las cargas de entrenamiento. Sin embargo, poca información existe en atletas recreacionales que realizan entrenamiento de este tipo. Este caso de estudio monitoreó diariamente la VFC en un triatleta de nivel recreacional durante un periodo de 56 días. Los cambios semanales en el volumen de entrenamiento, frecuencia cardiaca en reposo (FCR), el logaritmo natural de la raíz cuadrada del valor medio de la suma de las diferencias al cuadrado de todos los intervalos RR (tiempo entre dos latidos) sucesivos (Ln RMSSD) y el promedio móvil del coeficiente de variación de Ln RMSSD (Ln RMSSD cv) fueron evaluados. Los resultados demostraron aumentos sobre el cambio más pequeño que vale la pena (por sus siglas en inglés, SWC) en la FCR (7.9 %, 6.5% y 5.2% en las semanas 2, 6 y 8 respectivamente) y disminución en la semana 3
(-4.5%), decrementos moderados en el tamaño del efecto (TE) del Ln RMSSD semana 3 (-0.27) estabilizándose en las semanas posteriores y aumento grande en TE (1.80) en la última semana de monitoreo. El Ln RMSSDCV presentó una diferencia de 64% y 89% de los valores por fuera del SWC (día 1-28 y 29-56 respectivamente). Los aumentos en los valores de la VFC y el descenso de la FCR demuestran una adaptación positiva al entrenamiento durante las ocho semanas de monitorización.
... Monotony has been defined as the variability of practice over the course of a season (Anderson et al 2003) and is suggested as a training error that increases the risk of overtraining syndromes (Kellmann 2002). High training monotony has been linked to poor performance and an increased frequency of banal infections, whereas a reduction in monotony was related to attainment of personal best performances (Foster & Lehmann 1997, Suzuki et al 2003. Accordingly, an index of training monotony, calculated using performer ratings of perceived exertion, has been employed as a useful training-monitoring tool in rowing (Suzuki et al 2003) and sprinting (Suzuki et al 2006). ...
La Actividad Física(AF) entendida como aquel movimiento corporal producido por los
músculos esqueléticos y que tiene como resultado un gasto energético que se añade al
metabolismo basal (Gálvez, y otros, 2001; Martínez-González & Guillén Grima, 1999), en las
dos últimas décadas, constituye uno de los principales triunfos de un estilo de vida saludable
y de una verdadera protección y promoción de la salud. Diversos estudios científicos han
demostrado que la práctica habitual de AF regular proporciona importantes beneficios en
la salud (Carpersen, Powell, & Christenson, 1985; Corbin, 2008; Balius Juli, 1989; Andersen
& Haradsodóttir, 1995; Eaton, Lapane, Garber, Assaf, Lasater, & Carleton, 1995; Oja, 1995;
Pate, 1995; Young, Sharp, & Curb, 1995; Myers, Strikmiller, Webber, & Berenson, 1996; Pate,
Heath, Dowda, & Trost, 1996; Sánchez Bañuelos, 1996; Raitakari, Taimela, Porkka, Telama,
Välimäki, & Akerblom, 1997; Boreham, Twist, & Savage, 1997; Perula de Torres, Lluch, Ruiz
Moral, Espejo Espejo, Tapia, & Mengual Luque, 1998; Graf, Bjarnason-Wehresn, & Rost,
2001; Boreham, Twisk, Murray, Savage, & Strain-Cran, 2001) y de igual manera, la relación
que su ausencia mantiene con el desarrollo, mantenimiento y agravamiento de diversas
enfermedades crónicas.
Background
Measuring the physical work and resultant acute psychobiological responses of basketball can help to better understand and inform physical preparation models and improve overall athlete health and performance. Recent advancements in training load monitoring solutions have coincided with increases in the literature describing the physical demands of basketball, but there are currently no reviews that summarize all the available basketball research. Additionally, a thorough appraisal of the load monitoring methodologies and measures used in basketball is lacking in the current literature. This type of critical analysis would allow for consistent comparison between studies to better understand physical demands across the sport.
Objectives
The objective of this systematic review was to assess and critically evaluate the methods and technologies used for monitoring physical demands in competitive basketball athletes. We used the term ‘training load’ to encompass the physical demands of both training and game activities, with the latter assumed to provide a training stimulus as well. This review aimed to critique methodological inconsistencies, establish operational definitions specific to the sport, and make recommendations for basketball training load monitoring practice and reporting within the literature.
Methods
A systematic review of the literature was performed using EBSCO, PubMed, SCOPUS, and Web of Science to identify studies through March 2020. Electronic databases were searched using terms related to basketball and training load. Records were included if they used a competitive basketball population and incorporated a measure of training load. This systematic review was registered with the International Prospective Register of Systematic Reviews (PROSPERO Registration # CRD42019123603), and approved under the National Basketball Association (NBA) Health Related Research Policy.
Results
Electronic and manual searches identified 122 papers that met the inclusion criteria. These studies reported the physical demands of basketball during training (n = 56), competition (n = 36), and both training and competition (n = 30). Physical demands were quantified with a measure of internal training load (n = 52), external training load (n = 29), or both internal and external measures (n = 41). These studies examined males (n = 76), females (n = 34), both male and female (n = 9), and a combination of youth (i.e. under 18 years, n = 37), adults (i.e. 18 years or older, n = 77), and both adults and youth (n = 4). Inconsistencies related to the reporting of competition level, methodology for recording duration, participant inclusion criteria, and validity of measurement systems were identified as key factors relating to the reporting of physical demands in basketball and summarized for each study.
Conclusions
This review comprehensively evaluated the current body of literature related to training load monitoring in basketball. Within this literature, there is a clear lack of alignment in applied practices and methodological framework, and with only small data sets and short study periods available at this time, it is not possible to draw definitive conclusions about the true physical demands of basketball. A detailed understanding of modern technologies in basketball is also lacking, and we provide specific guidelines for defining and applying duration measurement methodologies, vetting the validity and reliability of measurement tools, and classifying competition level in basketball to address some of the identified knowledge gaps. Creating alignment in best-practice basketball research methodology, terminology and reporting may lead to a more robust understanding of the physical demands associated with the sport, thereby allowing for exploration of other research areas (e.g. injury, performance), and improved understanding and decision making in applying these methods directly with basketball athletes.
Recent research has demonstrated decreases in resting metabolic rate (RMR), body composition and performance following a period of intensified training in elite athletes, however the underlying mechanisms of change remain unclear. Therefore, the aim of the present study was to investigate how an intensified training period, designed to elicit overreaching, affects RMR, body composition, and performance in trained endurance athletes, and to elucidate underlying mechanisms.Thirteen (n = 13) trained male cyclists completed a six-week training program consisting of a "Baseline" week (100% of regular training load), a "Build" week (~120% of Baseline load), two "Loading" weeks (~140, 150% of Baseline load, respectively) and two "Recovery" weeks (~80% of Baseline load). Training comprised of a combination of laboratory based interval sessions and on-road cycling. RMR, body composition, energy intake, appetite, heart rate variability (HRV), cycling performance, biochemical markers and mood responses were assessed at multiple time points throughout the six-week period. Data were analysed using a linear mixed modeling approach.The intensified training period elicited significant decreases in RMR (F(5,123.36) = 12.0947, p
Von dem Moment an, an dem man sich für das erste Rennen registriert, tritt man in die Welt der Läufer und verlässt die gemütliche Sphäre des Joggers. Mit dem ersten absolvierten Rennen bekommt man einen guten Eindruck, zu was man wirklich fähig ist. Allerdings besteht die Gefahr, dass man dann natürlich schneller und schneller werden will und dem Körper oftmals mehr abverlangt, als er zu geben in der Lage ist. Ist man sich dieser Gefahr nicht bewusst, kommt es unvermeidlich zum Phänomen des Übertrainings.
Sporting performances have continued to improve ever since records have been kept. This continued ability of athletes to improve and perform at higher levels is a function of enhanced exercise training adaptation, technological developments in equipment, and improved health–medical care. The exercise training adaptations are seen as paramount in this process and represent a more clear understanding by exercise scientist of the physiology of adaptation and the exercise stimulus to bring about those adaptations. Physiologically, one system critical in the adaptation process (“plasticity”) is the endocrine system and the hormones associated with it. Hormones serve as chemical messengers to initiate and regulate key aspects of anabolism and catabolism in cells. In the context of skeletal muscle cells, this involves enhancing contractile elements as well as energy substrate mobilization–utilization capacity, all potentially leading to improved sporting performance. With this in mind, the intent of this specific chapter is to review the responses and adjustments/adaptations of the endocrine system as affected by exercise training. Specifically, the discussion is focused on this topic as it pertains to athletes who participate in sporting activities that involve training which predominantly emphasizes endurance (e.g., distance runners) versus resistance (e.g., weight lifters) training activities.
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