Context: Monitoring training loads and consequent fatigue responses are usually a result of personal trainers’ experiences and an adaptation of methods used in sports for people without disabilities. Currently, there is little scientific evidence on the relationship between training load and fatigue resulting from training sessions in wheelchair sports. Analogous to the vertical jump, which has been associated with competitive performance and used to assess fatigue in Olympic sports, the medicine ball throw (MBT) is a fast, feasible, and accessible test that might be used to measure performance outcomes in Paralympic athletes. Objective: To test the MBT responsiveness to detect meaningful changes after training sessions in beginner wheelchair basketball players (WBP). Design: Cross-sectional study. Setting: Rehabilitation Hospital Network, Paralympic Program. Participants: Twelve male WBP. Main Outcomes Measures: The participants performed 3 consecutive days of training sessions involving exercises of wheelchair basketball skills, strength, and power. The MBT test was performed pre and post training sessions. Results: The smallest worthwhile change for MBT was 0.10 cm, and the lower and upper limits were 3.54 and 3.75 m, respectively. On the first day, the MBT started below the smallest worthwhile change lower limit and increased above the upper limit (3.53 and 3.78 m, respectively). On the second day, the MBT pretraining and posttraining session results were near the sample mean (3.62 and 3.59 m, respectively). On the third day, the WBP started the MBT test training higher than the upper limit (3.78 m) and decreased to near the mean (3.58 m). Conclusions: During 3 consecutive days of training sessions, the magnitude-based inference model presented meaningful changes in MBT test performance. The accurate association of the magnitude-based inference model with the MBT allows coaches and sports team staff to interpret the correct magnitude of change in WBP performance.

Monitoring training loads and the consequent fatigue responses is usually a result of personal trainers’ experiences and an adaptation of the methods used in sports for people without disabilities.1 Due to the specific characteristics of the wheelchair sports modalities, practical evaluations for daily fatigue monitoring are necessary for this population. One way of monitoring the training load is using a practical test during the training periodization.2 The medicine ball throw (MBT) is an upper-limb assessment used initially to estimate power and strength outputs indirectly. The MBT was included as a performance field test of wheelchair basketball (WB), associated with functional classification,3 analyzed as a comparison outcome between the first and third division of wheelchair basketball players (WBP),4 and used as a predictor of anaerobic performance evaluation.5 Analogous to the vertical jump, which has been associated with competitive performance2 and used to assess fatigue in Olympic sports, the MBT is a fast, feasible, and accessible test that might be used to measure performance outcomes in Paralympic athletes.

In specific populations such as the Paralympians, the null-hypothesis significant statistic often struggles with a sample size issue to achieve a significant P value when assessing a performance outcome.6,7 The magnitude-based inference model seems to be a better statistic proposition compared with inferential statistics to analyze sports performance outcomes.6,7 The smallest worthwhile change (SWC) is a metric used to determine the smallest difference that can lead to a meaningful change in the performance of an individual or team sport.6 In this way, the present study aimed to test the MBT responsiveness to detect meaningful changes after WB training sessions in beginner WBP.

Methods

Participants

Twelve male beginner athletes who participated in WB from the Sports Program of a Network Centre of Rehabilitation Hospitals were recruited (Table 1). The study was approved by the institutional ethics committee (protocol number 3.488.107), and all participants provided written informed consent. The inclusion criteria were (1) WB experience ranging from 6 to 24 months, (2) to have participated in all training sessions in the first week of December 2018, and (3) to present WB eligibility.

Table 1

Group Demographics

Age, y34.1 (11.6)
Time since injury, mo180.6 (149.2)
Age at injury, y20.7 (18.7–22.7)
Body mass, kg74.8 (16.8)
Height, cm171.7 (169.1–180.0)
Body mass index, kg/m224.9 (4.2)
Functional classification
 Class 1.0–2.57 (58.3%)
 Class 3.0–4.55 (41.7%)
Disability (n)
 Myelomeningocele1 (8.3%)
 Poliomyelitis1 (8.3%)
 Spinal cord injury10 (83.3%)

Note: Age at injury and height are presented as median (25th–75th percentiles). Age, time since injury, body mass, and body mass index are presented as mean (SD), and disability and functional classification are presented as absolute values (frequency).

Procedures

The WBP participated in 3 consecutive training day sessions. The workouts were balanced in volume (60 min in total), and the MBT was performed at the beginning and end of each training session. The perception of effort was collected 15 minutes after each training session.8 The internal training load was calculated for each training day using the method proposed by Foster et al8 (total duration of the training session in minutes multiplied by individual training intensity).

On the first day, a circuit with 5 stations was performed (elastic row, medicine ball pass, 2-m front and back fast wheelchair propulsion, barbell push press, and rotate the washer around the head). The athletes were distributed in the 5 stations and performed the exercises for 90 seconds. After that time, they had 30 seconds of transition to the next station. Three rounds of the circuit were performed, totaling 30 minutes of training. The loads used were individually controlled so that the athletes could maintain the repetitions during the 90 seconds. Following the circuit, a WB game was performed without interruption.

On the second day, exercises of WB skills were carried out involving rapid displacements with predominantly cardiovascular characteristics for 30 minutes (2-, 5-, and 30-m sprints, and small-sided games). Following the circuit, a WB game was performed without interruption. On the third day, 60 minutes of a WB game was performed without interruption.

For the MBT, the WBP had to throw a 5-kg medicine ball with a 2-arm overhand as far as possible from a stationary position, with one of the researchers holding the wheelchair in place. The distance between the participant and the spot where the ball hit the floor was measured (in meters). Each participant made 3 attempts with 2-minute rest intervals, and the longest distance was used for further analysis.35

Statistical Analysis

The MBT results of the 3 different training sessions were analyzed using the magnitude-based inference method.7 The SWC for team sports was obtained by multiplying 0.2 by the between-athlete standard deviation.6 The noise of the MBT results was expressed as the standard error of measurement.6 The MBT results during pretraining and posttraining sessions were plotted. A meaningful difference was considered when the test value was outside the SWC area, and its lower/upper limits of the 90% CIs did not overlap the positive or negative differences as established by the SWC.7

The 1-way analysis of variance was performed to compare training loads during days 1, 2, and 3 using SPSS (version 22.0; IBM Corp, Armonk, NY). Statistical significance was set at 5% (P ≤ .05; 2-tailed).

Results

The highest respiratory and muscular training loads were obtained on day 2 (317.9 a.u.) and day 1 (400.0 a.u.), respectively (Table 2).

Table 2

Mean (SD) of Respiratory and Muscular Training Loads for Days 1, 2, and 3

Training load, a.u.Day 1Day 2Day 3
Respiratory302.5 (70.6)317.9 (118.7)275.0 (72.9)
Muscular400.0* (93.4)298.3 (106.7)278.3 (101.8)

*Significant difference compared with day 3 (P ≤ .05).

The meaningful changes results obtained from MBT pre and post training sessions are demonstrated in Figure 1. The SWC for MBT was 0.10 cm, and the lower and upper limits were 3.54 and 3.75 m, respectively. On day 1, the athletes started the training session with MBT below the SWC “trivial zone” (ie, the area established by the upper and lower limits, where there are no meaningful differences between changes) and increased the result to a higher value than the upper limit (3.53 and 3.78 m, respectively; Figure 1). Regarding day 2, the MBT presession and postsession training results were near the sample mean (3.62 and 3.59 m, respectively; Figure 1). On day 3, the athletes started the training higher than the upper limit (3.78 m) and decreased the MBT result to inside the “trivial zone” (3.58 m; Figure 1). The standard error of measurement obtained from the MBT results was 0.19 m.

Figure 1
Figure 1

Pre (black dot) and post (gray dot) MBT performance (90% confidence interval) of 3 consecutive monitored training sessions. The black line corresponds to the MBT mean, and the dotted lines delimit the lower and upper limits of the SWC area. MBT indicates medicine ball throw; SWC, smallest worthwhile change.

Citation: Journal of Sport Rehabilitation 2021; 10.1123/jsr.2020-0222

Discussion

The present study aimed to test the MBT responsiveness to detect meaningful changes after a WB training session in beginner WBP. During 3 consecutive days of training sessions, the magnitude-based inference model presented meaningful changes in MBT performance. Therefore, the MBT associated with the magnitude-based inference model might be a suitable approach for this specific Paralympic sport and population.

The MBT variations observed from SWC before and after training sessions might be the introductory studying process of monitoring physical performance and fatigue in Paralympic team sport athletes. In Olympic athletes, the vertical jump and the countermovement jump tests are currently used with these objectives, and periodic SWC observations of jump height trends allow daily informed decisions on training modifications.2 The MBT might be one alternative to the corresponding test for wheelchair athletes since meaningful responses were observed during the 3 consecutive days. Moreover, a previous study demonstrated that the MBT is a valid test for a nonlaboratory anaerobic performance evaluation as a predictor of mean and peak power.5 Therefore, MBT is a useful tool for controlling WB performance.

On day 1, the pretraining test was the lowest MBT result compared with days 2 and 3, under the lower SWC limit, and it could be interpreted that the athlete started the training session in a fatigued state. However, it is more probable that a “learning effect” has occurred since the athletes did not practice physical activity 72 hours prior to the first training session. Moreover, the confidence interval overlapped the “trivial zone,” being classified as an unclear result,7 and the muscular training load was the highest of the 3 days. The MBT at the end of the training session of the first day was higher than the upper limit and the confidence interval inside the “trivial zone,” indicating a beneficial magnitude7 and demonstrating the sensitivity of the MBT result with SWC analysis. Regarding days 2 and 3, the reduced MBT performance owing to the training session loads occurred at posttraining sessions, as expected. Although the confidence interval of day 2 pretraining and day 3 posttraining overlapped the “trivial zone,” beneficial and trivial magnitude inferences were observed.7

The MBT has been used to assess power in different individual and team sports. Peak power is fundamental to a high sports performance.9 A strength test with constant speed (ie, isokinetic) or a test where muscle action is not accompanied by motion (ie, isometric) may be less suitable for athletics than a test that allows for variable speeds throughout the range of motion (ie, isotonic).10 Using a multijointed exercise that incorporated the stretch-shortening cycle, such as MBT, should be advantageous to understand the relationships with a dynamic movement. The MBT is a practical measurement tool and common in practice routine sports; it could also be examined further for its role in measuring strength and power relative to a return to sport following injury. The magnitude-based inference model is an alternative to use the MBT to assess changes in performance during daily training and to optimize an athlete’s performance. Further studies are needed to elucidate if the present findings might be extrapolated to elite athletes, female athletes, and individual sports associated with injury and performance. In addition, more studies comparing the MBT (analyzed by a magnitude-based inference model) with other fatigue assessments (eg, blood samples or isokinetic fatigue tests) must be performed to ensure the correct use of this tool.

Conclusions

The MBT demonstrated responsiveness to detect meaningful changes after the WB training session in beginner WBP. This test is a fast, feasible, and accessible test alternative that might be used to constantly monitor training progress and assess the fatigue of beginner WBP every day. The proper use of a magnitude-based inference model allows coaches and sports team staff to interpret the correct magnitude of change in athlete performance. The association of MBT with the statistic approach is a novel and inexpensive assessment tool to be used in the practice routine of Paralympic sports.

References

  • 1.

    Perret C. Elite-adapted wheelchair sports performance: a systematic review. Disabil Rehabil. 2017;39(2):164172. PubMed ID: 26505216 doi:

  • 2.

    Loturco I, Pereira LA, Abad CCC, et al. Vertical and horizontal jump tests are strongly associated with competitive performance in 100-m dash events. J Strength Cond Res. 2015;29(7):19661971. PubMed ID: 25627643 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Gil SM, Yanci J, Otero M, et al. The functional classification and field test performance in wheelchair basketball players. J Hum Kinet. 2015;46(1):219230. PubMed ID: 26240665 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Granados C, Yanci J, Badiola A, et al. Anthropometry and performance in wheelchair basketball. J Strength Cond Res. 2015;29(7):18121820. PubMed ID: 25536537 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Marszalek J, Kosmol A, Morgulec-Adamowicz N, et al. Laboratory and non-laboratory assessment of anaerobic performance of elite male wheelchair basketball athletes. Front Psychol. 2019;10:514. PubMed ID: 30930816

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Bernards JR, Sato K, Haff GG, Bazyler CD. Current research and statistical practices in sport science and a need for change. Sports. 2017;5(4):87. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Batterham AM, Hopkins WG. Making meaningful inferences about magnitudes. Int J Sports Physiol Perform. 2006;1(1):5057. PubMed ID: 19114737 doi:

  • 8.

    Foster C, Florhaug JA, Franklin J, et al. A new approach to monitoring exercise training. J Strength Cond Res. 2001;15(1):109115. PubMed ID: 11708692

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Marques MC, van den Tillaar R, Vescovi JD, González-Badillo JJ. Relationship between throwing velocity, muscle power, and bar velocity during bench press in elite handball players. Int J Sports Physiol Perform. 2007;2(4):414422. PubMed ID: 19171959 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Marques MC, Saavedra FJ, Abrantes C, Aidar FJ. Associations between rate of force development metrics and throwing velocity in elite team handball players: a short research report. J Hum Kinet. 2011;29A:5357. PubMed ID: 23487363 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation

If the inline PDF is not rendering correctly, you can download the PDF file here.

Gomes Costa and Ribeiro Neto are with the Paralympic Sports Program, SARAH Rehabilitation Hospital Network, Brasilia, Brazil. Dorneles is with the SARAH Rehabilitation Hospital Network, Brasilia, Brazil. Lopes is with the College of Physical Education, Universidade de Brasilia (UnB), Brasilia, Brazil. Gorla is with the School of Physical Education, State University of Campinas, Campinas, São Paulo, Brazil.

Ribeiro Neto (fredribeironeto@gmail.com) is corresponding author.
  • View in gallery

    Pre (black dot) and post (gray dot) MBT performance (90% confidence interval) of 3 consecutive monitored training sessions. The black line corresponds to the MBT mean, and the dotted lines delimit the lower and upper limits of the SWC area. MBT indicates medicine ball throw; SWC, smallest worthwhile change.

  • 1.

    Perret C. Elite-adapted wheelchair sports performance: a systematic review. Disabil Rehabil. 2017;39(2):164172. PubMed ID: 26505216 doi:

  • 2.

    Loturco I, Pereira LA, Abad CCC, et al. Vertical and horizontal jump tests are strongly associated with competitive performance in 100-m dash events. J Strength Cond Res. 2015;29(7):19661971. PubMed ID: 25627643 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Gil SM, Yanci J, Otero M, et al. The functional classification and field test performance in wheelchair basketball players. J Hum Kinet. 2015;46(1):219230. PubMed ID: 26240665 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Granados C, Yanci J, Badiola A, et al. Anthropometry and performance in wheelchair basketball. J Strength Cond Res. 2015;29(7):18121820. PubMed ID: 25536537 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Marszalek J, Kosmol A, Morgulec-Adamowicz N, et al. Laboratory and non-laboratory assessment of anaerobic performance of elite male wheelchair basketball athletes. Front Psychol. 2019;10:514. PubMed ID: 30930816

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Bernards JR, Sato K, Haff GG, Bazyler CD. Current research and statistical practices in sport science and a need for change. Sports. 2017;5(4):87. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Batterham AM, Hopkins WG. Making meaningful inferences about magnitudes. Int J Sports Physiol Perform. 2006;1(1):5057. PubMed ID: 19114737 doi:

  • 8.

    Foster C, Florhaug JA, Franklin J, et al. A new approach to monitoring exercise training. J Strength Cond Res. 2001;15(1):109115. PubMed ID: 11708692

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Marques MC, van den Tillaar R, Vescovi JD, González-Badillo JJ. Relationship between throwing velocity, muscle power, and bar velocity during bench press in elite handball players. Int J Sports Physiol Perform. 2007;2(4):414422. PubMed ID: 19171959 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Marques MC, Saavedra FJ, Abrantes C, Aidar FJ. Associations between rate of force development metrics and throwing velocity in elite team handball players: a short research report. J Hum Kinet. 2011;29A:5357. PubMed ID: 23487363 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 157 157 54
PDF Downloads 54 54 15