Edited by: Gregoire P. Millet, University of Lausanne, Switzerland
Reviewed by: Pascal Edouard, University Hospital of Saint-Etienne, France; François Fourchet, Hôpital de la Tour, Switzerland
*Correspondence: Robert J. Aughey
This article was submitted to Exercise Physiology, a section of the journal Frontiers in Physiology
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Musculoskeletal screening refers to a series of tests designed to detect internal abnormalities that are associated with increased injury risk, or incomplete recovery from training or previous injuries (Dennis et al.,
Pre-season (pre-participation) musculoskeletal screening is a widely studied approach where athletes are tested at the start of pre-season and then monitored prospectively for occurrence of injuries for the remainder of the season. Cut scores are then set with the aim of identifying athletes with high injury risk (Bahr,
Repeated-measures or regular screening is another approach that involves frequently conducting testing and measuring the change in screening test scores (Paul et al.,
Injuries to hamstring, groin, and calf muscles are among the most common injuries in Australian football, and the musculoskeletal screening tests implemented by Australian Football League (AFL) clubs attempt to monitor some of the intrinsic risk factors associated with these injuries (Gabbe et al.,
Accumulation of training-induced stress on the musculoskeletal system may result in maladaptation and increased risk of injuries (Vanrenterghem et al.,
All the 44 elite male players from one Australian football club were invited and agreed to participate in this study (mean age ±
Weekly musculoskeletal screening scores and daily internal training load were recorded for individual players over an entire AFL season. Weekly musculoskeletal screening tests were conducted within 3 h prior to the first field training session of the week which was planned 2 or 3 days apart from a previous field training session or a match. Based on the club's training schedule, screening occurred on Monday mornings during pre-season and Tuesday afternoons during in-season. This timing was chosen to allow the medical staff to further investigate players with abnormally reduced scores or accompanying symptoms prior to the training session. Pre-season and in-season periods were analyzed separately due to the possible effects of diurnal variation (Manire et al.,
Players placed their bare feet against the sit and reach box and their middle fingers on top of each other. They were then asked to stretch forward as far as possible and hold the position for 1 s while keeping the knees straight. The reach distance from the tip of the middle fingers relative to the toe line was recorded (Gabbe et al.,
A permanent tape measure was fixed on the floor with 0 cm mark at a wall junction. Players were asked to place the big toe and heel of the testing leg beside the tape. They were then instructed to lunge forward until the knee touches the wall while keeping the heel in contact with the floor. The maximum distance from the tip of the big toe to the wall was recorded (Bennell et al.,
With players in a supine position, a sphygmomanometer cuff pre-inflated to 20 mmHg was placed between the knees. Players were asked to maximally squeeze the cuff and hold for 1 s and the maximum pressure displayed on the dial was recorded. The test was conducted in three hip flexion angles of 0°, 45°, and 90° (Malliaras et al.,
The session rating of perceived exertion (sRPE) method was used to quantify the individual internal training load for all training sessions and matches (RPE multiplied by the session duration) (Foster,
Correlations between cumulative and smoothed training loads of various periods on a given day
Smoothed 3 day | 0.81 | 0.63 | 0.39 | 0.18 | |
Smoothed 5 day | 0.83 | 0.81 | 0.58 | 0.33 | |
Smoothed 7 day | 0.73 | 0.89 | 0.71 | 0.46 | |
Smoothed 10 day | 0.60 | 0.81 | 0.82 | 0.61 | |
Smoothed 14 day | 0.46 | 0.67 | 0.72 | ||
Smoothed 21 day | 0.32 | 0.48 | 0.68 | 0.75 | |
Smoothed 28 day | 0.24 | 0.36 | 0.52 | 0.62 | |
Smoothed 3 day | 0.70 | 0.59 | 0.48 | 0.42 | |
Smoothed 5 day | 0.81 | 0.77 | 0.66 | 0.59 | |
Smoothed 7 day | 0.75 | 0.84 | 0.78 | 0.72 | |
Smoothed 10 day | 0.66 | 0.81 | 0.87 | 0.83 | |
Smoothed 14 day | 0.57 | 0.75 | 0.90 | 0.90 | |
Smoothed 21 day | 0.46 | 0.66 | 0.84 | 0.90 | |
Smoothed 28 day | 0.40 | 0.58 | 0.77 | 0.86 |
The analyses were performed in three parts using the Statistical Analysis System (version 9.4, SAS Institute, Cary, NC). Based on the scale of the test scores, only the AST scores were log-transformed before modeling (Hopkins et al.,
In the second part, another general linear mixed model was devised to identify any possible linear trends in the scores at each phase by including the week as a numeric fixed effect. The week number and player identity were defined as nominal random effects. A model in which a different variability (the residual) was specified for each player failed to converge for any of the tests. To account for the real differences in variability, the players were therefore assigned to three subgroups of low, moderate, and high variability based on the findings of the previous part, with a separate residual for each subgroup. A dummy variable for the number of days post-match that the screening occurred (two or three) was added to the model. This dummy variable was used to compare the within-subject differences in the scores as a result of an extra recovery day post-match.
In the third part, a quadratic mixed model was developed to evaluate the effects of various measures of training load on the screening scores. The intercept, training load measure, and the square of the training load measure were the fixed effects which collectively estimated the mean quadratic. The random effects were player identity (to estimate different between-player means across each season phase), the interaction of player identity with the training measure and with the square of the training measure (to estimate individual differences in the players' quadratics), and the residual error (within-player week to week variability). This model estimated the within-subject changes in a given screening score associated with within-subject changes in a given measure of training load. Within-player
The findings were interpreted using mechanistic magnitude-based inference (Hopkins et al.,
The findings for the left and right DLTs were nearly identical as were the findings for the three ASTs. Hence, only the results for the right DLT and AST at 0 degrees of hip flexion are shown. One player sustained a season-ending injury at the end of pre-season and was excluded from the in-season analysis. Table
Statistics summarizing screening test scores for an AFL team in a pre- and in-season phase derived from parts 1 and 2 of the analysis.
Pre-season | 2.3 ± 8.2 | 0.21; ± 0.24ML↔ | 0.98; ± 0.01 | 0.92; ± 0.14ML↕ | 1.66; × /÷1.12 VL↕ |
In-season | 3.1 ± 7.9 | 0.03 ± 0.23ML↔ | 0.97; ± 0.01 | 1.01; ± 0.12ML↕ | 1.52; × /÷1.09 VL↕ |
Pre-season | 11.4 ± 3.2 | −0.05; ± 0.14ML↔ | 0.97; ± 0.01 | 0.50; ± 0.08P↕ | 1.43; × /÷1.15 L↔ |
In-season | 11.3 ± 3.3 | −0.05; ± 0.09ML↔ | 0.96; ± 0.01 | 0.48; ± 0.06P↕ | 1.37; × /÷1.10 L↔ |
Pre-season | 253 mm Hg ± 20% | 0.4%; ± 2.9%ML↔ | 0.74; ± 0.08 | 7.8%; ± 0.8%ML↕↕ | 1.38; × /÷1.10 VL↕ |
In-season | 266 mm Hg ± 21% | 6.5%; ± 2.2%VL↑ | 0.81; ± 0.07 | 7.4%; ± 0.6%ML↕↕ | 1.31; × /÷1.07 L↕ |
The effects of an increase in training load from −1
Effects of training load on the test scores derived from part 3 of the analysis.
Cumulative 3 day | 410 ± 380 | −0.09; ± 0.17ML↔ | −0.07; ± 0.07ML↔ | 1.1; ± 1.6ML↔ |
Cumulative 7 day | 2, 440 ± 1, 260 | −0.18; ± 0.20ML↔ | −0.07; ± 0.10ML↔ | 0.4; ± 1.9ML↔ |
Cumulative 14 day | 4, 260 ± 2, 160 | −0.13; ± 0.20ML↔ | −0.05; ± 0.10ML↔ | 1.8; ± 1.9VL↔ |
Cumulative 28 day | 8, 120 ± 2, 300 | 0.02; ± 0.17ML↔ | −0.01; ± 0.05ML↔ | 0.6; ± 1.8ML↔ |
Smoothed 3 day | 210 ± 120 | −0.12; ± 0.19ML↔ | −0.05; ± 0.09ML↔ | 0.3; ± 1.9ML↔ |
Smoothed 7 day | 280 ± 120 | −0.16; ± 0.22ML↔ | −0.04; ± 0.10ML↔ | 0.5; ± 2.0VL↔ |
Smoothed 14 day | 300 ± 90 | −0.06; ± 0.18ML↔ | −0.03; ± 0.10ML↔ | 1.0; ± 1.8VL↔ |
Smoothed 28 day | 330 ± 90 | −0.09; ± 0.20ML↔ | −0.11; ± 0.15ML↔ | 1.4; ± 2.0VL↔ |
Acute:Chronic ratio | 1.20 ± 0.80 | −0.11; ± 0.17ML↔ | −0.05; ± 0.07ML↔ | 0.8; ± 1.7ML↔ |
Monotony | 0.86 ± 0.22 | −0.30; ± 0.25ML↔ | −0.04; ± 0.10ML↔ | 0.7; ± 2.2VL↔ |
Strain | 2, 560 ± 1, 150 | −0.30; ± 0.21ML↔ | −0.07; ± 0.09ML↔ | −0.1; ± 1.7ML↔ |
Cumulative 3 day | 950 ± 360 | 0.08; ± 0.14ML↔ | 0.03; ± 0.05ML↔ | 0.1; ± 1.1ML↔ |
Cumulative 7 day | 1, 750 ± 340 | 0.05; ± 0.13ML↔ | 0.01; ± 0.04ML↔ | −1.1; ± 0.9ML↔ |
Cumulative 14 day | 3, 510 ± 530 | 0.02; ± 0.11ML↔ | −0.05; ± 0.05ML↔ | −1.7; ± 0.9ML↔ |
Cumulative 28 day | 7, 080 ± 980 | 0.14; ± 0.15ML↔ | −0.02; ± 0.08ML↔ | −2.6; ± 1.3L↔ |
Smoothed 3 day | 250 ± 60 | 0.04; ± 0.15ML↔ | 0.00; ± 0.05ML↔ | −0.7; ± 1.0ML↔ |
Smoothed 7 day | 260 ± 40 | 0.09; ± 0.12ML↔ | −0.02; ± 0.05ML↔ | −1.1; ± 0.9ML↔ |
Smoothed 14 day | 260 ± 30 | 0.10; ± 0.13ML↔ | −0.04; ± 0.06ML↔ | −2.0; ± 0.9ML↔ |
Smoothed 28 day | 260 ± 30 | 0.09; ± 0.19ML↔ | 0.01; ± 0.13ML↔ | −3.3; ± 1.6P↔ |
Acute:Chronic ratio | 1.0 ± 0.19 | −0.06; ± 0.15ML↔ | 0.00; ± 0.04ML↔ | 1.0; ± 0.9ML↔ |
Monotony | 0.82 ± 0.20 | −0.04; ± 0.15ML↔ | −0.04; ± 0.08ML↔ | −1.8; ± 1.2ML↔ |
Strain | 1, 430 ± 430 | 0.01; ± 0.13ML↔ | −0.02; ± 0.07ML↔ | −1.4; ± 1.2ML↔ |
Changes in screening scores with changes in training load (cumulative 7 day, smoothed 3 day, acute:chronic ratio, strain). *The estimates for the screening scores were calculated for zero training load where −2
Changes in screening scores with changes in training load (cumulative 3 day, cumulative 14 day, cumulative 28 day, monotony). *The estimates for the screening scores were calculated for zero training load where −2
Changes in screening scores with changes in training load (smoothed 7 day, smoothed 14 day, smoothed 28 day).
There were substantial small to moderate amounts of normal variability with some individual differences in variability associated with the weekly musculoskeletal screening tests. The tests which were conducted two or three days post-match (or main training session during pre-season) were not sensitive to changes in internal training load and may not provide an accurate indication of the athletes' readiness for training when used as measures of recovery.
This study is the first to have tracked weekly test scores throughout an entire season. The intra-tester reliability of the tests in the current study as quantified using ICC, were similar to those in studies with test-retest gaps of between 30 min and 1 week (Bennell et al.,
The typical error (noise) obscures the important change (signal) in any measure (Hopkins,
Training, like any intervention, interacts with the athletes' individual characteristics making the effects more or less beneficial, harmful, or ineffective in different individuals (Hopkins,
A survey of athlete monitoring practices in high performance sports revealed that the majority of coaching and support staff rely on visual identification of trends in the athletes' data to identify the ones who may benefit from an adjustment to training load (Taylor et al.,
The observed trivial effects of training load on the test scores indicate that these tests are not sensitive to changes in internal training load when performed 2 or 3 days post-match or post-training. Subsequently, the screening scores should be interpreted cautiously when used as measures of recovery. This finding is supported by the observed trivial differences between the test scores obtained at 2 vs. 3 days post-match in the current study as well as the previously reported timeline of change in the measures of flexibility and peak force post-match (Dawson et al.,
Training load has an established association with the recovery of athletes and injury risk (Gabbett,
Overall, while weekly musculoskeletal screening appears to be a valuable athlete monitoring tool, clinicians need to be aware of the normal variability of the test scores and the individual differences in such variability when interpreting changes in screening scores. The lack of sensitivity of the investigated tests to training load should prompt clinicians to investigate the reasons behind substantial reductions in screening scores rather than casually attributing them to a match or training session that occurred more than 2 days prior to the screening.
A limitation of this study is that the current findings in regards to the effects of training load on the musculoskeletal screening scores are based on the sRPE derived internal measures of training load and may not necessarily apply to the external measures of training load (e.g., running distance). Considering the differences between adaptation pathways to physiological and biomechanical loads (Vanrenterghem et al.,
A change in the screening scores larger than the identified normal variability is required to be considered a true change and the flagging systems applied to the screening scores need to account for the individual differences in variability. The studied tests are not sensitive to changes in training load as the scores return back to baseline by day 2 post-match or post-training when the screening is normally conducted.
AE, RA, AS, WH, GE: conceived and designed the study; AE: performed the tests; WH, AE, BL, AR: analyzed the data; AE, WH, RA, AS: interpreted the results; AE: drafted the manuscript and prepared the tables/figures; AE, RA, WH, BL, AR, GE, AS: edited, critically revised the manuscript, and approved the final version.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The authors would like to sincerely thank Chris Bell, Justin Cordy, and all other staff and players at the Western Bulldogs Football Club for their kind assistance with conducting this study.