Well-being and Total Quality Recovery (TQR) questionnaires

Questionnaires are fast, cost-effective and easy data collection, which can be adapted to different contexts.

The information obtained can be used to provide the planned Adapt training or additional regeneration measures if necessary.

Today we introduce you two more query options:

• Wellness Questionnaire
• Total Quality Recovery (TQR)
  
  
  

This could be interesting for you too:

The Hooper`s Index - Control and subjective assessment of fatigue

Wellness Questionnaire

McLean, Coutts, Kelly, McGuigan and Cormack (2010) developed a wellness questionnaire where the athletes on a Likert scale (1-5 points) fatigue, sleep quality, general muscle condition, pain, stress level and mood had to indicate.

Johnston, Gabbett and Jenkins (2013) used the scale to State of fatigue and recovery during a period with high competition density (three games in the same week) to Monitoring. The number of points achieved decreased during the week (figure below), which is due to a increased neuromuscular stressg of the athletes and indicates a muscle damage or an increase in the enzyme "Kreatinkinase (CK).

In addition, there was an increase in general muscle pain and fatigue, which ability to train reduce (Johnston et al., 2013).

After the first game, the athletes achieved a significantly lower overall value compared to the initial values. However, the value before the second game rose and then went down significantly after the game (between 12 and 36 hours after the game). The Subskala muscle pain increased significantly 12 hours after the first game and 12 hours after the second game. A significant increase occurred 12 hours before and 36 hours after the second game. Generally, muscle pain seems to increase up to 12 hours after the game and can even rise up to 36 hours after the game.

With our free tool -Team Management System (TMS) - you can quickly and easily Load and regeneration data by your players.

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It appears therefore that the use of this scale in times of high fatigue of athletes (i.e. high competition density and/or times with high training loads) provides information on the general condition of athletes and on the current state (taking into account the different assessed dimensions) and, on the basis of this information, allows the Adaptation of training.

An example of the application is shown in the figure below. As you can see, the Control of load - with the Edwards indicator, which is determined by the measurement of heart rate and which is still received in a further blog post, and with a wellness questionnaire - the interpretation of the burden and the weekly distribution that allows the team to go to the competition day with a higher level of "fresh".

In this case, the 15th Microcycle a slightly higher load (Edwards) and yet the team managed to be fresher the day before the competition. The values on the competition day were 7 Arbitrary Units (AU) in the 12th microcycle and 7.4 AU in the 15th. Microcycle. With this Monitoring of load and recovery dynamics it is possible to specific needs of the team or the level of physical fitness at different times of the season fine tuning. This information makes it possible to make more and more precise decisions on the distribution of stress in the training week and in the following weeks.

Total Quality Recovery (TQR)

The TQR scale allows direct detection of the condition of the athlete in addition to the intensity of the exposure (information obtained by the subjectively evaluated scale of the perceived effort or RPE) (Kenttä & Hassmén, 1998).

The TQR scale is similar to the scale for the subjectively perceived effort (which is used to measure the training intensity perceived by the athlete), as both use the same interrogation method. Like the original RPE scale (Borg, 1982), the original TQR scale has 15 stages, from 6 to 20 (Kenttä & Hassmén, 1998). However, to simplify how an athlete assigns a value - similar to the scale modified by Foster, Florhaug, Franklin, Gottschall, Hrovatin, Parker, Doleshal and Dodge (2001) for the perception of the intensity of effort - the scale was modified by various authors. The TQR-10 scale therefore refers to the perception of recovery by the athlete and therefore uses a ten-stage scale (figure below).

How to interpret the collected data (load data - RPE and regeneration data - TQR), you can learn in this blog post:

How does a load and regeneration control in football work in detail? – The monitoring cycle

Presentation of queries in the Team Management System

Conclusions on the use of scales

The instruments for monitoring the state of recovery of an athlete can useful the optimally control training process to be able. In this sense, Starling & Lambert (2017) examined how trainers configured questionnaires to measure the response of players to the load. Thus, trainers indicated the factors that should be included in the questionnaire, from the greatest to the least important (Figure 6).

Based on the results, it seems that the questionnaires for the self-assessment of athletes, questions about muscle pain, nutritional condition or motivation for training are most important.

How to interpret the collected data (load data - RPE and regeneration data - TQR), you can learn in this blog post:

How does a load and regeneration control in football work in detail? – The monitoring cycle

With our free tool -Team Management System (TMS) - you can quickly and easily Load and regeneration data by your players.

Join today: Click here!

This could be interesting for you too:

The Hooper`s Index - Control and subjective assessment of fatigue

Training Control in Football – What should you consider when planning to be successful with your team?

Rate of perceived exertion (RPE) – a simple and effective method for controlling loads in football

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Literature

Angeli, A., Minetto, M., Dovio, A. and Paccotti, P. (2004). The overtraining syndrome in athletes: a stress-related disorder. Journal of Endocrinological Investigation, 27(6), 603-12. Borg, G. A. (1982). Psycho bases of perceptiond exertion. Medicine and Science in Sports and Exercise, 14(5), 377-81.

Borresen, J. & Lambert, M. (2008). Quantifying training load: a comparison of subjective and objective methods. International Journal of Sports and Performance, 3(1), 16-30. Chamari, K., Haddad, M., Wong, del P., Dellal, A. y Chaouachi, A. (2012). Injury rates in professional soccer players during Ramadan. Journal of Sports Sciences, 30(1), S93-102.

Coutts, A., Rampinini, E., Marcora, S., Castagna, C. e Impellizzeri, F. (2009). Heart rate and blood lactate correlates of perceived exertion during smallsided soccer games. Journal of Science and Medicine in Sport, 12(1), 79-84.

Foster, C., Florhaug, JA, Franklin, J., Gottschall, L., Hrovatin, LA, Parker, S., Doleshal, P. and Dodge, C. (2001). A new approach to monitoring exercise testing. Journal of Strength and Conditioning Research, 15(1), 109-115.

Gabbett, T. J., Nassis, G. P., Oetter, E., Pretorius, J., Johnston, N., Medina, D., Rodas, G., Myslinski, T., Howells, D., Beard, A. y Ryan, A. (2017). The athlete monitoring cycle: a practical guide to interpreting and applying training monitoring data. British Journal of Sports Medicine, 51(20), 1451-1452.

García Concepción, M. A., Peinado, A. B., Paredes, V. y Alvero Cruz, J. R. (2015). Eficacia de diferentes estrategias de recuperación en jugadores de fútbol de élite. Revista Internacional de Medicina y Ciencias de la Actividad Física y el Deporte, 15(58), 355-369.

Hooper, S. L. & Mackinnon, L. T. (1995). Monitoring overtraining in athletes. Recommendations. Sports Medicine, 20(5), 321-7.

Johnston, R. D., Gabbett, T. J. and Jenkins, D. G. (2013). Influence of an intensified competition on fatigue and match performance in junior rugby league players. Journal of Science and Medicine in Sport, 16(5), 460-5. doi: 10.1016/jsams.2012.10.009.

Kenttä, G. & Hassmén, P. (1998). Overtraining and recovery. A conceptual model. Sports Medicine, 26(1), 1-16.

McLean, B. D., Coutts, A. J., Kelly, V., McGuigan, M. R. and Cormack, S. J. (2010). Neuromuscular, endocrine, and perceptual fatigue responses during different length between-match microcycles in professional rugby league players. International Journal of Sports Physiology and Performance, 5(3), 367-383.

Starling, L. T. & Lambert, M. I. (2017). Monitoring Rugby Players for Fitness and Fatigue: What Do Coaches Want? International Journal of Sports Physiology and Performance. 15, 1-30. doi: 10.1123/ijspp.2017-0416.