[
literature review
]
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CHRISTINA LYNGSOE UDBY, PT1 • FRANCO M. IMPELLIZZERI, PhD2 MARTIN LIND, PhD3 • RASMUS ØSTERGAARD NIELSEN, PT, PhD1,4
How Has Workload Been Defined and How Many Workload-Related Exposures to Injury Are Included in Published Sports Injury Articles? A Scoping Review
F
or effective injury prevention, coaches, clinicians, and athletes must understand what causes sports injuries (sports injury etiology). Injury occurs when the load applied to a body structure exceeds the structure’s capacity to withstand load.22,26,36 The definition
of “load” differs across articles.22,36 To avoid comparing apples and pears across studies on sports injury etiology, when reading research, coaches, clinicians, and athletes should check whether the definitions of injury and load are consistent. U OBJECTIVE: To describe how workload-related exposure variables have been defined in sports injury articles, and to identify the number of workload-related exposure variables included in comparative analyses.
U DESIGN: Scoping review.
U LITERATURE SEARCH: PubMed, SPORTDis-
cus, and Scopus were systematically searched on March 13, 2020. Two reviewers independently screened the retrieved literature and selected articles for inclusion.
U STUDY SELECTION CRITERIA: Prospective
cohort studies using workload-related variables as the primary exposure to sports injury were eligible for inclusion.
U DATA SYNTHESIS: The type (eg, distance,
balls bowled) and construct of workload-related exposure variables (eg, acute-chronic workload ratio) were extracted and summarized in frequency tables.
Workload is a common term in sports injury studies. There is no universal definition of workload, and workload and training load are often used interchangeably. One suggested definition for workload, “the cumulative amount of stress U RESULTS: A total of 648 articles were identified,
and 45 were eligible for inclusion. Workload definition differed greatly, as sports- and workload-related exposure variables could be, but were not limited to, distance, balls bowled, session rating of perceived exertion, accelerations, soreness, and sleep. Within and across articles, authors used different constructs for workload-related exposure variables. For example, distance was represented as total distance, distance per week, distance per 2 weeks, and acute-chronic workload ratio. The number of workload-related exposure variables included in comparative analyses ranged from 1 to 336.
U CONCLUSION: Studies used different defini-
tions of workload-related exposure variables. The number of workload-related exposure variables in a single study ranged from 1 to 336. J Orthop Sports Phys Ther 2020;50(10):538-548. doi:10.2519/jospt.2020.9766
U KEY WORDS: athletes, sports injury, systematic scoping review, training, workload
placed on an individual from multiple training sessions and games over a period of time, expressed in terms of either the external workloads performed (eg, resistance lifted, kilometres run) or the internal response (eg, heart rate, rating of perceived exertion) to that workload,”20,62 has also been conflated with training load. It seems that there is some confusion about key terms in the field. Because workload has been included in many scientific articles examining associations with sports injury, it is important to understand what the term “workload” represents. It is important to use identical measures of workload so that results from different studies can be compared. As a result of broad definitions and overlap with other terminology, the possible number of different workloadrelated exposure variables included in articles examining associations between workload and injury varies substantially. Workload-related exposure variables often measure different constructs, which presents a challenge when comparing the results of different studies or combining results from different studies (eg, for systematic review). A scoping review is a type of knowledge synthesis that follows a systematic
Department of Public Health, Aarhus University, Aarhus, Denmark. 2School of Sport, Exercise and Rehabilitation, University of Technology Sydney, Ultimo, Australia. 3Department of Orthopedics, Aarhus University Hospital, Aarhus N, Denmark. 4Research Unit for General Practice in Aarhus, Aarhus, Denmark. No funding was received in connection with this study. The authors certify that they have no affiliations with or financial involvement in any organization or entity with a direct financial interest in the subject matter or materials discussed in the article. Address correspondence to Christina Lyngsoe Udby, Aarhus University, Nordre Ringgade 1, 8000 Aarhus, Denmark. E-mail:
[email protected] t Copyright ©2020 Journal of Orthopaedic & Sports Physical Therapy® 1
538 | october 2020 | volume 50 | number 10 | journal of orthopaedic & sports physical therapy
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approach to map evidence on a topic and identify main concepts.52 We conducted a scoping review aiming to describe how workload-related exposure variables have been defined in sports injury articles, and to identify the number of workloadrelated exposure variables included in comparative analyses.
(1) prospective cohort study design, (2) examination of the association between workload and sports injury, with workload as the primary exposure, (3) human participants only, and (4) computer simulation/modeled data (computer data). We excluded studies of military or army recruit participants.
METHODS
Quality Assessment
Search Strategy
T
his scoping review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines.52 The research question and selection criteria were established a priori. The search strategy was developed with assistance from a health sciences librarian at Aarhus University Library (Denmark). The search terms and Medical Subject Headings (APPENDIX A) were built using the PICOS framework.21 PubMed, SPORTDiscus, and Scopus databases were searched electronically from inception to March 13, 2020. We limited the search to original research articles written in English. We used EndNote X9.2 software (Clarivate Analytics, Philadelphia, PA) to manage the database output.
Study Selection After removing duplicates, 2 reviewers (C.L.U. and R.O.N.) independently screened articles for eligibility based on titles and abstracts, using Covidence systematic review software (Veritas Health Innovation Ltd, Melbourne, Australia). Disagreements were resolved via consensus. If consensus could not be reached, a third reviewer (M.L.) made the final decision about inclusion. Where it was unclear from the title and abstract whether an article should be included, 2 reviewers (C.L.U. and R.O.N.) screened the full text and reached consensus regarding inclusion. To be eligible, articles had to fulfill the following prespecified inclusion criteria:
This scoping review addresses methodological considerations about how workload-related exposure variables are used in original articles examining the relationship between workload and sports injuries. The quality of the included articles relates to the study design. The validity of the outcome of the included studies is not relevant to our scoping review objectives. Therefore, we did not assess the quality of the included studies.
Data Collection We extracted the following information and data from each article: • Type of sport • First author • Year of publication • The definition of workload-related exposure variables, which refers to type (eg, distance, balls bowled) and construct (eg, acute-chronic workload ratio, total). For example, distance (type) could be total, per week, per 2 weeks, or acute-chronic workload ratio (constructs) • The number of workload-related exposure variables for which the relationship to sports injury was assessed. We extracted each workload-related exposure variable that was associated with sports injury based on the information in the Methods and/or Results section. We counted the number of variables for each type of workload. For example, the following are 5 different workload-related exposure variables (workload type: balls bowled): (1) match overs bowled in 5 days, (2) match overs bowled in 17 days, (3) number of days to bowl greater than 100 match overs, (4) session rating of
perceived exertion (sRPE) per week, and (5) sRPE per 2 weeks • Measurement tools (eg, global positioning system, Borg scale, etc) used to assess information on workloadrelated exposure variables • Units in which workload-related exposure variables were reported (eg, kilometers per week, throws per match, arbitrary units, etc) We used the STROBE54 guidelines to direct our data extraction, which are general reporting guidelines for observational studies that investigate associations between exposures and health outcomes. We considered all workload-related exposure variables that were mentioned in the Methods and/or Results section when extracting data. Workload-related exposure variables that were not statistically significantly associated with injuries, and therefore not presented as main results by the authors, were included in our scoping review. When doubts arose about the extracted data, a meeting was held between 3 reviewers (C.L.U., M.L., and R.O.N.) to clarify the accuracy and interpretation of the data.
Data Synthesis To identify the number of workload-related exposure variables that were represented in the included articles, the data synthesis was performed at the study level. We summarized the type (eg, distance, balls bowled) and construct (eg, acute-chronic workload ratio) of workload-related exposure variables for each article in frequency tables.
RESULTS
W
e identified 648 articles in the database search. Among these, 187 were duplicates, leaving 461 articles for title and abstract screening. We assessed the full text of 76 articles and excluded 31 articles. There were 45 articles included in our scoping review (FIGURE).1,2,4-16,18,23-25,27-35,40-43,45-48,50,51,53,56-61
journal of orthopaedic & sports physical therapy | volume 50 | number 10 | october 2020 | 539
Identification
Records identified through database searching in PubMed, Scopus, and SPORTDiscus, n = 648
Screening
Records screened, n = 461
Eligibility
The year of publication for the 45 included articles ranged from 2003 to 2020 (TABLE 1). Thirteen different sports were represented. The most frequently studied sport was Australian football (12 articles). The workload-related exposure variables included in each of the 45 articles are listed in APPENDIX B. In summary, the minimum number of workload-related exposure variables was 1 and the maximum was 336 variables in a single study. The construct of each type of workload-related exposure variable differed.
Full-text articles assessed for eligibility, n = 76
Included
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[
Studies included in qualitative synthesis, n = 45
literature review The workload type “distance” was, for instance, represented by 70 different variable constructs (TABLE 2).
DISCUSSION
T
he number of workload-related exposure variables examined in studies of the association between workload and sports injury ranged from 1 to 336 per study. The constructs used to characterize the different workloadrelated exposure variables varied; for
Duplicates excluded, n = 187
Records excluded, n = 385
Full-text articles excluded, n = 31 • Ineligible study design, n = 11 • Workload not mentioned, n = 14 • Double publication, n = 2 • Ineligible outcome, n = 4
FIGURE. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) diagram visualizing the selection process for the present systematic scoping review.
TABLE 1
Characteristics of Identified Articles
Sport
Year of Articles, n Publication
Workload-Related Exposure Measurement Variables Used, n Tools Used, n
Australian football
12
2014-2020
4-336
Cricket: fast bowlers (junior, n = 1)
10
2003-2020
3-30
4 7
European football (elite, n = 1; youth, n = 1)
4
2016-2019
7-28
2
Soccer (professional, n = 1; female, n = 1)
4
2016-2018
7-36
4
Elite rugby league
3
2015-2018
3-48
1
American football
2
2018-2019
1-12
1
Rugby union
2
2017
2-10
2
Basketball
2
2017-2018
1-13
2
Australian elite cricket
1
2009
5
2
Baseball
1
2020
1
1
CrossFit
1
2017
3
2
Elite Gaelic football
1
2017
9
1
Hurling
1
2018
6
1
International cricket
1
2020
3
1
] example, distance was represented in 70 different ways in the 45 included articles. Combining and/or comparing results from different studies using workload-related exposure variables should be done with extreme caution, if at all, as the underlying measures of workload are likely to be very different. Yet, there are examples from several sports injury articles, opinion papers, educational reviews, and even a consensus statement in which figures were made by combining data from different workload-related exposure variables (eg, balls bowled, sRPE, and total running load).3,19,49,62 We strongly question the validity of such figures, and we encourage athletes, coaches, and clinicians to take a step back and be cautious before implementing them in practice. It is necessary to read beyond the headlines of general conclusions and recommendations regarding safe workload. The reason for the great heterogeneity in the definition of workload-related exposure variables is open to speculation, and we are unable to provide answers to important questions such as, “How should workload be defined?” and “Which construct of workload is most suitable to use as exposure to sports injury?” However, we note that Edwards17 reported that sports injury occurrence was rooted in a biomechanical phenomenon. If this is true and the goal of the research is to gain a deeper understanding of causal inference, more attention to biomechanical-oriented variables that can be measured in a field-based setting may be needed.55 As a concrete example, running distance has been used as exposure to injury in many original articles.38,39 However, the load on body structures can be vastly different, even when runners run the same distance, as Petersen et al44 found slow-speed running to decrease knee joint loads per stride and increase the cumulative load at the knee joint for a given running distance compared to faster running. On this basis, running injury researchers designing large-scale epidemiological
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studies examining the reasons for sports injury occurrence may need to consider combining vertical oscillation step, running speed per step, ground contact time per step, body weight, and/or other measures, because these may allow for calculation of the approximate load per step. If these approximate loads per step are combined, a cumulative approximate workload per running session could be established, which may be more causally linked with running injury than distance alone.37 This example is theoretical and very specific to running. Consequently, other ways of measuring a biomechanically sound approximation of cumulative load in other sports may be more appealing. Our intention is to flag the need for intensive collaboration between sports injury researchers, epidemiologists, and biomechanists. We believe this may be an important step forward to construct sport-specific workload exposures that are better suited to investigate why sports injury occurs in prospective cohort studies.
Limitations Our assessment of how articles defined workload was a subjective interpretation. Consequently, the number of workload-
related exposure variables identified in each article could be different if others had done the subjective evaluation. However, it would probably not change the conclusion that there is considerable variation in the number of workload-related exposure variables and in how they are used. We can only comment on workload, and only in a sports injury context. We did not focus on training load, which is also used in a sports injury setting. Therefore, more work is needed to identify whether the term training load is used to cover a broad range of sports injury exposure variables. Our results cannot be generalized to performance or other health-related outcomes. We did not search gray literature, and only articles written in English were included. Therefore, there is a risk of publication bias and language bias, although it is unlikely to alter the main conclusions.
CONCLUSION
I
ndividual studies reporting on the relationship between workload and sports injury assessed a minimum of 1 workload-related exposure variable and a maximum of 336 variables. t
KEY POINTS FINDINGS: Studies of the relationship be-
tween workload and sports injury have reported on as few as 1 and as many as 336 different workload-related exposure variables. The construct of workload-related exposure variables differed within and across sports. IMPLICATIONS: Different studies used different workload types and constructs in different ways, which suggests that combining and/or comparing results from different studies should be done with extreme caution, if at all. CAUTION: The results are limited to workload in a sports injury context. We did not evaluate how training load, which is also frequently used in sports injury research, has been used.
STUDY DETAILS AUTHOR CONTRIBUTIONS: Christina Lyngsoe
Udby and Dr Nielsen contributed to the concept of the study and the research design. Christina Lyngsoe Udby acquired the data, and all authors contributed to the analysis and interpretation of data and the writing and revision of the manuscript. All authors gave final approval of the manuscript. Christina Lyngsoe Udby takes responsibility for
TABLE 2
Data on Distance as Represented Throughout the 45 Articles
Workload-Related Exposure Variable Type
Constructs of Distance Used, n
Distance
70
Constructs of Distance Represented Total distance; distance per week, 2 weeks, 3 weeks, 4 weeks; 2-week average distance; ACWR; 2-week average ACWR; distance (above 3 km/h); distance load; high-speed-running distance (above 24 km/h); moderate-speed-running distance (between 18 and 24 km/h); sprint distance ACWR; sprint distance chronic load # ACWR; distance chronic load # ACWR; early preseason distance; late preseason distance; precompetition distance; rounds 1-5 precompetition distance; 1-, 2-, 3-, and 4-week cumulative loads and absolute change (previous to current week) in total distance; velocity 1 distance and sprint distance; sprint distance in the last week; sprint distance in the last 2 weeks; 7-, 14-, 21-, and 28-day rolling averages; 7-, 14-, and 28-day smoothed, rolling average ACWR; smoothed ACWR; monotony and strain for total distance; EWMA ACWR for total distance; low-speed distance; moderate-speed distance; high-speed distance; very high–speed distance; total distance covered between matches; EWMA, ACWR, and MSWR for total distance; distance in meters covered above 5.5 m/s; distance covered at metabolic power; distance with a metabolic power above 25.5 W/kg; distance with a metabolic power above 25.5 W/Kg per minute; distance covered above 25.5 W/Kg and below 19.8 km/h; total 1-week high-speed distance; total 1-week sprint distance; absolute weekly change in highspeed distance; absolute weekly change in sprint distance; high-speed distance ACWR; sprint distance ACWR; total 1-week highspeed distance combined with low chronic training load (sRPE); total 1-week high-speed distance combined with high chronic training load (sRPE); total 1-week sprint distance combined with low chronic training load (sRPE); total 1-week sprint distance combined with high chronic training load (sRPE)
Abbreviations: #, interaction between; ACWR, acute-chronic workload ratio; EWMA, exponentially weighted moving average; MSWR, mean over standard deviation workload ratio; sRPE, session rating of perceived exertion.
journal of orthopaedic & sports physical therapy | volume 50 | number 10 | october 2020 | 541
[ the integrity of the work as a whole, from inception to publication. DATA SHARING: There are no data available. PATIENT AND PUBLIC INVOLVEMENT: There was no patient and/or public involvement.
literature review
11.
12.
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workloads and increased risk of injury. Am J Sports Med. 2009;37:1186-1192. https://doi. org/10.1177/0363546509332430 Petersen J, Sørensen H, Nielsen RØ. Cumulative loads increase at the knee joint with slowspeed running compared to faster running: a biomechanical study. J Orthop Sports Phys Ther. 2015;45:316-322. https://doi.org/10.2519/ jospt.2015.5469 Rossi A, Pappalardo L, Cintia P, Iaia FM, Fernàndez J, Medina D. Effective injury forecasting in soccer with GPS training data and machine learning. PLoS One. 2018;13:e0201264. https:// doi.org/10.1371/journal.pone.0201264 Sampson JA, Murray A, Williams S, et al. Injury risk-workload associations in NCAA American college football. J Sci Med Sport. 2018;21:1215-1220. https://doi.org/10.1016/j. jsams.2018.05.019 Sampson JA, Murray A, Williams S, Sullivan A, Fullagar HHK. Subjective wellness, acute:chronic workloads, and injury risk in college football. J Strength Cond Res. 2019;33:3367-3373. https:// doi.org/10.1519/JSC.0000000000003000 Saw R, Dennis RJ, Bentley D, Farhart P. Throwing workload and injury risk in elite cricketers. Br J Sports Med. 2011;45:805-808. https://doi. org/10.1136/bjsm.2009.061309 Soligard T, Schwellnus M, Alonso JM, et al. How much is too much? (Part 1) International Olympic Committee consensus statement on load in sport and risk of injury. Br J Sports Med. 2016;50:1030-1041. https://doi.org/10.1136/ bjsports-2016-096581 Stares J, Dawson B, Peeling P, et al. How much is enough in rehabilitation? High running workloads following lower limb muscle injury delay return to play but protect against subsequent injury. J Sci Med Sport. 2018;21:1019-1024. https://doi. org/10.1016/j.jsams.2018.03.012 Stares J, Dawson B, Peeling P, et al. Identifying high risk loading conditions for in-season injury in elite Australian football players. J Sci Med Sport. 2018;21:46-51. https://doi.org/10.1016/j. jsams.2017.05.012 Tricco AC, Lillie E, Zarin W, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169:467-473. https://doi.org/10.7326/M18-0850 Tysoe A, Moore IS, Ranson C, McCaig S, Williams S. Bowling loads and injury risk in male first class county cricket: is ‘differential load’ an alternative to the acute-to-chronic workload ratio? J Sci Med Sport. 2020;23:569-573. https://doi. org/10.1016/j.jsams.2020.01.004
54. Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Epidemiology. 2007;18:805-835. https://doi.org/10.1097/EDE.0b013e3181577511 55. Verheul J, Nedergaard NJ, Pogson M, et al. Biomechanical loading during running: can a two mass-spring-damper model be used to evaluate ground reaction forces for high-intensity tasks? Sports Biomech. In press. https://doi.org/10.108 0/14763141.2019.1584238 56. Warren A, Williams S, McCaig S, Trewartha G. High acute:chronic workloads are associated with injury in England & Wales Cricket Board Development Programme fast bowlers. J Sci Med Sport. 2018;21:40-45. https://doi.org/10.1016/j. jsams.2017.07.009 57. Watson A, Brickson S, Brooks A, Dunn W. Subjective well-being and training load predict in-season injury and illness risk in female youth soccer players. Br J Sports Med. 2017;51:194-199. https://doi.org/10.1136/bjsports-2016-096584 58. Weiss KJ, Allen SV, McGuigan MR, Whatman CS. The relationship between training load and injury in men’s professional basketball. Int J Sports Physiol Perform. 2017;12:1238-1242. https://doi. org/10.1123/ijspp.2016-0726 59. Williams S, Booton T, Watson M, Rowland D, Altini M. Heart rate variability is a moderating factor in the workload-injury relationship of competitive CrossFit™ athletes. J Sports Sci Med. 2017;16:443-449. 60. Williams S, Trewartha G, Cross MJ, Kemp SPT, Stokes KA. Monitoring what matters: a systematic process for selecting trainingload measures. Int J Sports Physiol Perform. 2017;12:S2-101-S2-106. https://doi.org/10.1123/ ijspp.2016-0337 61. Williams S, Trewartha G, Kemp SPT, et al. How much rugby is too much? A seven-season prospective cohort study of match exposure and injury risk in professional rugby union players. Sports Med. 2017;47:2395-2402. https://doi. org/10.1007/s40279-017-0721-3 62. Windt J, Gabbett TJ. How do training and competition workloads relate to injury? The workload–injury aetiology model. Br J Sports Med. 2017;51:428-435. https://doi.org/10.1136/ bjsports-2016-096040
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journal of orthopaedic & sports physical therapy | volume 50 | number 10 | october 2020 | 543
[
literature review
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APPENDIX A
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SEARCH STRINGS PubMed ((((((((sports injur*) OR sport injur*) OR exercise injur*) OR “ athletic injuries”))) OR ((“training related”) AND injur*))) AND (((“workload”[MeSH Terms] OR “workload”[All Fields]))) Filters: English (144 hits) -13.03.2020: 171 SPORTDiscus (((((((((sports injur*) OR sport injur*) OR exercise injur*) OR “ athletic injuries”))) OR ((“training related”) AND injur*)))) AND workload (81 hits) -13.03.2020: 100 Scopus (TITLE-ABS-KEY (sport AND injur* OR sports AND injur* OR exercise AND injur* OR (“training related” AND injur*))) AND (TITLE-ABS-KEY (workload)) (328 hits) 13.03.2020: 377
544 | october 2020 | volume 50 | number 10 | journal of orthopaedic & sports physical therapy
APPENDIX B
MAIN RESULTS FROM EACH OF THE 45 INCLUDED ARTICLES IN RELATION TO THE 2 PURPOSES OF THIS SYSTEMATIC SCOPING REVIEW
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Results Related to the Main Purposes
Study/Sport
Tool Used to Measure Workload Unit
WorkloadRelated Exposure Variable, n Type and Construct of Workload-Related Exposure Variable
Sampson et al46 American football
GPS
AU
12
Load was calculated for (1) ACWR (7:14 d), (2) ACWR (7:21 d), (3) ACWR (7:28 d), (4) EWMA ACWR (7:14 d), (5) EWMA ACWR (7:21 d), (6) EWMA ACWR (7:28 d) within 3- and 7-d lag periods
Sampson et al47 American football
GPS
AU
1
Carey et al6 Australian football
GPS, sRPE (NA)
Meters, AU, minutes, square meters per minute
336
For all 6 variables: (1) distance (above 3 km/h), (2) sRPE, (3) player load, (4) distance load, (5) high-speed running (distance above 24 km/h), (6) moderate-speed running (distance between 18 and 24 km/h), they examined 56 combinations of acute and chronic time windows, giving a total of 336 combinations
Colby et al10 Australian football
GPS, sRPE (10-point modified Borg scale), wellness questionnaire, Likert scale
Meters, AU, years, pain (yes/no)
19
(1) 2-wk distance, (2) 3-wk distance, (3) 4-wk distance, (4) distance ACWR, (5) 2-wk sprint, (6) 3-wk sprint, (7) 4-wk sprint, (8) sprint distance ACWR, (9) 1-wk on-legs RPE, (10) 2-wk on-legs RPE, (11) 3-wk on-legs RPE, (12) 4-wk on-legs RPE, (13) on-legs RPE ACWR, (14) playing experience, (15) heavy nonfootball activity, (16) old lower-limb pain, (17) sprint distance chronic load # ACWR, (18) distance chronic load # ACWR, (19) on-legs sRPE chronic load # ACWR
Colby et al8 Australian football
GPS
Meters, kilometers
4
(1) Early preseason distance, (2) late preseason distance, (3) precompetition distance, (4) rounds 1-5 precompetition distance
Colby et al7 Australian football
GPS software and separate data analysis package
Meters, AU
30
1-, 2-, 3-, and 4-wk cumulative loads and absolute change (previous to current week) were modeled for (1) total distance, (2) velocity 1 distance, (3) sprint distance, (4) force load, (5) velocity load, and (6) relative velocity change
Colby et al9 Australian football
GPS, sRPE (NA)
Meters, AU
9
(1) Maximum speed in the last 8 wk, (2) maximum speed in the last 4 wk, (3) sprint distance in the last week, (4) on-legs sRPE 20% in the last 2 wk, (9) distance >30% in the last 2 wk
Esmaeili et al18 Australian football
GPS, sRPE (NA)
Meters, AU
44
7-, 14-, 21-, and 28-d rolling averages; 7-, 14-, and 28-d smoothed, rolling average ACWR; smoothed ACWR. Monotony and strain were calculated for (1) sRPE, (2) player load, (3) total distance, and (4) high-intensity running
Murray et al34 Australian football
GPS
Meters, AU
12
ACWR (rolling averages); EWMA ACWR for (1) total distance, (2) low-speed distance, (3) moderate-speed distance, (4) high-speed distance, (5) very high–speed distance, (6) player load
Murray et al33 Australian football
GPS
Meters
12
Acute, chronic, and ACWRs were modeled for (1) total distance, (2) low-speed distance, (3) moderate-speed distance, (4) high-speed distance, and (5) very high–speed distance
Murray et al35 Australian football
GPS
Meters, AU
24
Acute (1 wk), chronic (4 wk), ACWR for the current week, and ACWR for the subsequent week were modeled for each of the 6 variables: (1) total distance, (2) low-speed distance, (3) moderate-speed distance, (4) high-speed distance, (5) very high–speed distance, (6) player load
O’Connor et al40 Australian football
GPS
Meters, kilometers per hour
24
(1) Total distance covered, (2) distance covered at >25 km/h, (3) distance covered at >80% of maximum velocity, (4) distance covered at >85% of maximum velocity, (5) distance covered at >90% of maximum velocity, and (6) distance covered at >95% of maximum velocity were calculated per week and per 4 wk for both relative and absolute exposures
Stares et al51 Australian football
GPS, sRPE (10-point modified Borg scale)
Meters, AU
36
12 different ACWRs were calculated for each of the 3 variables: (1) sRPE, (2) total distance, and (3) sprint distance
ACWR
Table continues on page 546.
journal of orthopaedic & sports physical therapy | volume 50 | number 10 | october 2020 | 545
[
literature review
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APPENDIX B
Results Related to the Main Purposes
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at Univ Canberra on October 3, 2020. For personal use only. No other uses without permission. Copyright © 2020 Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
Study/Sport
Tool Used to Measure Workload Unit
WorkloadRelated Exposure Variable, n Type and Construct of Workload-Related Exposure Variable
Stares et al50 Australian football
GPS, sRPE (10-point modified Borg scale)
Meters, AU, days
12
Mehta32 Baseball
Arm sleeve sensor
Number of throws
1
Caparrós et al5 Basketball (pro male)
Tracking variables Mass times and nontracking average vevariables locity times distance, load per minutes played, meters, meters per square second, meters per hour, AU, milliliters, milliliters per hour
Weiss et al58 Basketball (pro male)
sRPE (Borg CR-10 scale)
AU
1
sRPE ACWR
Ahmun et al1 International cricket
sRPE (10-point rating scale)
AU
3
(1) sRPE per 3 d (acute), (2) sRPE per 14 d (chronic), (3) ACWR
Saw et al48 Australian elite cricket
Video recordings or Number and direct observatype of tion throws
5
(1) Mean throws per week, (2) mean throws per day, (3) mean throwing days per week, (4) mean throws per week, (5) mean rest days per throwing day
13a
(1) sRPE in beginning of stage 3, (2) sRPE in stages 1-3, (3) sRPE in stage 2, (4) sRPE in stage 3, (5) sRPE in stages 2 and 3, (6) total distance in stage 2, (7) total distance in stage 3, (8) total distance in stages 2 and 3, (9) sprint distance in stages 2 and 3, (10) sprint distance in stage 3, (11) days spent in rehabilitation in stage 2, (12) days spent in rehabilitation in stage 3 Throwing ACWR (1) Physiological load, (2) physiological intensity, (3) defensive average speed, (4) offensive average speed, (5) total distance, (6) mechanical load, (7) mechanical intensity, (8) acceleration, (9) deceleration, (10) walking maximum speed, (11) locomotor variables, (12) player efficiency rating, (13) usage percentage
Bayne et al2 Self-reported Cricket (fast bowlers)
Number of overs
7
(1) Average number of overs per week, (2) average number of sessions per week, (3) average number of overs per session, (4) maximum number of overs in a single session, (5) maximum number of overs in a single week, (6) maximum number of overs in any 2-wk period, (7) maximum number of overs in any 4-wk period
Dennis et al16 Cricket (junior fast bowlers)
Number of deliveries
4
(1) Number of days of rest between bowling, (2) days bowled per week, (3) deliveries per day, (4) deliveries per week
Dennis et al15 Training surveilNumber of Cricket (fast bowlers) lance, fixture bowling score cards, and sessions and self-reported deliveries
3
(1) Deliveries per session, (2) deliveries per week, (3) frequency of sessions (days since previous session)
Dennis et al14 Score cards, video Cricket (fast bowlers) surveillance, and selfreported
Number of bowling sessions and deliveries
5
(1) Deliveries per session, (2) deliveries per week, (3) deliveries per month, (4) sessions per week, (5) frequency of sessions
Hulin et al23 sRPE (10-point CR Cricket (fast bowlers) scale)
AU, number of balls bowled
8
(1) sRPE per week (acute), (2) sRPE per 4 wk (chronic), (3) sRPE training-stress balance (acute-chronic) in the current week, (4) sRPE training-stress balance (acute-chronic) in the subsequent week, (5) balls bowled per week (acute), (6) balls bowled per 4 wk (chronic), (7) balls bowled: training-stress balance (acute-chronic) in the current week, (8) balls bowled: training-stress balance (acute-chronic) in the subsequent week
Self-reported (via daily diary)
Table continues on page 547.
546 | october 2020 | volume 50 | number 10 | journal of orthopaedic & sports physical therapy
APPENDIX B
Results Related to the Main Purposes
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at Univ Canberra on October 3, 2020. For personal use only. No other uses without permission. Copyright © 2020 Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
Study/Sport
Tool Used to Measure Workload Unit
WorkloadRelated Exposure Variable, n Type and Construct of Workload-Related Exposure Variable
Orchard et al43 Pre-existing dataCricket (fast bowlers) base extraction
Number of overs
9
Average overs bowled in the match per (1) 7 d, (2) 10 d, (3) 14 d, (4) 21 d, (5) 28 d, (6) 35 d, (7) 42 d, (8) 46 d, and (9) 90 d
Orchard et al42 Pre-existing dataCricket (fast bowlers) base extraction
Number of overs
3
(1) Match overs bowled in 5 d, (2) match overs bowled in 17 d, (3) number of days to bowl >100 match overs
Orchard et al41 Official score cards Number of Cricket (fast bowlers) overs
7
(1) Acute match overs ≥50, (2) career overs ≥1200, (3) overs in previous season ≥400, (4) previous injury: same season, (5) limited match overs, (6) overs in previous 3 mo ≥150 (protective), (7) career overs ≥3000 (protective)
Tysoe et al53 Standardized Cricket (fast bowlers) data-collection form (managed by the physical therapist)
Number of overs
30
Warren et al56 Self-reported by Number of Cricket (fast bowlers) e-mail, text, and overs telephone
3
(1) Balls bowled per week (acute), (2) balls bowled per 4 wk (chronic), (3) ACWR of balls bowled per week to balls bowled per 4 wk
Williams et al59 CrossFit
Smartphone application, sRPE (Borg scale)
3
(1) sRPE per 7 d (acute), (2) sRPE per 28 d (chronic), (3) sRPE (acute)-sRPE (chronic) ACWR
Delecroix et al13 European football
sRPE (modified AU Borg 0-10 scale)
8
(1) sRPE per week (acute), (2) sRPE per 2 wk, (3) sRPE per 3 wk, (4) sRPE per 4 wk (chronic), (5) week-to-week workload changes, (6) 4-wk ACWR, (7) 3-wk ACWR, (8) 2-wk ACWR
Delecroix et al12 European football
sRPE (modified AU Borg 0-10 scale)
8
(1) sRPE per week (acute), (2) sRPE per 2 wk, (3) sRPE per 3 wk, (4) sRPE per 4 wk (chronic), (5) week-to-week workload changes, (6) 4-wk ACWR, (7) 3-wk ACWR, (8) 2-wk ACWR
Bowen et al4 Youth football
GPS
Meters, kilometers per hour, AU
McCall et al31 Elite European football
sRPE (Borg scale)
AU
7
(1) sRPE per week, (2) sRPE week-to-week change, (3) sRPE rolling averages per 2 wk, (4) sRPE rolling averages per 3 wk, (5) ACWR (1:2), (6) ACWR (1:3), (7) ACWR (1:4)
Malone et al30 Elite Gaelic football
sRPE (Borg CR-10 rating scale)
AU
9
(1) sRPE per week, (2) sRPE per 2 wk, (3) sRPE per 3 wk, (4) sRPE per 4 wk, (5) absolute change in sRPE from previous week, (6) ACWR (1:4), (7) weekly training monotony, (8) weekly training strain, (9) 1-km time trial
Cummins et al11 Elite rugby league
GPS
Meters, minutes, AU, counts
48
2-wk, 3-wk, 4-wk, ACWR, MSWR, and strain were calculated for each of the 8 variables: (1) duration, (2) distance, (3) relative distance, (4) high-speed distance, (5) very high–speed distance, (6) number of accelerations, (7) number of decelerations, (8) player load
Hulin et al24 Elite rugby league
GPS
Kilometers
3
(1) Total distance covered between matches, (2) total distance covered per 4 wk (rolling average), (3) ACWR (total distance covered per 1:4 wk)
Hulin et al25 Elite rugby league
GPS
Meters
11
Acute total distance covered in (1) the current week, (2) the subsequent week, (3) and 2-wk average; chronic total distance covered (4 wk) in (4) the current week, (5) the subsequent week, (6) and 2-wk average; ACWR in (7) the current week, (8) the subsequent week, (9) and 2-wk average; (10) ACWR combined with low chronic workload; (11) ACWR combined with high chronic workload
Malone et al27 Hurling
sRPE (modified Borg CR-10 scale)
AU
6
(1) sRPE per week, (2) sRPE per 2 wk, (3) sRPE per 3 wk, (4) sRPE per 4 wk, (5) ACWR (1:4) (sRPE), (6) absolute change in sRPE from the previous to the current week
Williams et al61 Rugby union
Self-reported counts
Number of matches, minutes
2
(1) Match exposure per month, (2) match exposure per 12 mo
AU, minutes
28
10 different (1) chronic load measures, (2) change-in-load measures, and (3) acute load measures were explored
1-wk, 2-wk, 3-wk, 4-wk, and overall ACWRs; ACWR combined with low chronic workloads; and ACWR combined with high chronic workloads were calculated for all 4 variables: (1) total distance, (2) high-speed distance, (3) accelerations, and (4) total load
Table continues on page 548.
journal of orthopaedic & sports physical therapy | volume 50 | number 10 | october 2020 | 547
[
literature review
]
APPENDIX B
Results Related to the Main Purposes
Journal of Orthopaedic & Sports Physical Therapy® Downloaded from www.jospt.org at Univ Canberra on October 3, 2020. For personal use only. No other uses without permission. Copyright © 2020 Journal of Orthopaedic & Sports Physical Therapy®. All rights reserved.
Study/Sport
Tool Used to Measure Workload Unit
WorkloadRelated Exposure Variable, n Type and Construct of Workload-Related Exposure Variable
Williams et al60 Rugby union
sRPE (modified Borg CR-10 scale)
AU
10
(1) sRPE per day, (2) sRPE per week, (3) sRPE per 2 wk, (4) sRPE per 3 wk, (5) sRPE per 4 wk, (6) week-to-week change, (7) training monotony, (8) training strain, (9) ACWR (daily sRPE-4-wk sRPE), (10) EWMA
Malone et al28 Soccer
GPS and sRPE (modified Borg CR-10 scale)
AU, minutes, meters, meters per second, kilometers per hour
10
(1) Total 1-wk high-speed distance, (2) total 1-wk sprint distance, (3) absolute weekly change in high-speed distance, (4) absolute weekly change in sprint distance, (5) high-speed distance ACWR, (6) sprint distance ACWR, (7) total 1-wk high-speed distance combined with low chronic training load (sRPE), (8) total 1-wk high-speed distance combined with high chronic training load (sRPE), (9) total 1-wk sprint distance combined with low chronic training load (sRPE), (10) total 1-wk sprint distance combined with high chronic training load (sRPE)
Malone et al29 Soccer (pro)
sRPE (modified AU Borg CR-10 scale), test of intermittent aerobic capacity
Rossi et al45 Soccer
GPS
Watson et al57 Soccer (female youth)
sRPE (1-10 scale) and Likert scale via online software
7
(1) sRPE per week, (2) sRPE per 2 wk, (3) sRPE per 3 wk, (4) sRPE per 4 wk, (5) absolute change in sRPE from previous week, (6) ACWR (sRPE), (7) aerobic fitness level
Meters, meters per second, watts per kilogram, meters per square second, kilometers per hour
36
EWMA, ACWR, and MSWR were modeled for (1) total distance, (2) distance in meters covered above 5.5 m/s, (3) distance covered at metabolic power, (4) distance with a metabolic power above 25.5 W/kg, (5) distance with a metabolic power above 25.5 W/kg/min, (6) distance covered above 25.5 W/kg and below 19.8 km/h, (7) number of accelerations above 2 m/s2, (8) number of accelerations above 3 m/s2, (9) number of decelerations above 2 m/s2, (10) number of decelerations above 3 m/s2, (11) DSL (total of weighted impacts of magnitude above 2 g), (12) ratio between DSL and speed intensity
AU, days
11
(1) sRPE daily, (2) sRPE: prior day, (3) sRPE weekly, (4) sRPE monthly, (5) weekly-monthly sRPE ratio, (6) fatigue, (7) mood, (8) stress, (9) soreness, (10) sleep quality, (11) sleep hours
Abbreviations: #, interaction between; ACWR, acute-chronic workload ratio; AU, arbitrary unit; CR, category ratio; DSL, dynamic stress load; EWMA, exponentially weighted moving average; GPS, global positioning system; MSWR, mean over standard deviation workload ratio; NA, not available; RPE, rating of perceived exertion; sRPE, session rating of perceived exertion. a We chose to count all the exposure variables from Table 1 of this study, and not only those that were found to be significantly associated with injuries from Table 4 (in accordance with STROBE guidelines).
548 | october 2020 | volume 50 | number 10 | journal of orthopaedic & sports physical therapy