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Research Article

Handling and reporting missing data in training load and injury risk research

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 452-464 | Accepted 19 Oct 2021, Published online: 17 Nov 2021

References

  • Albrecht J, Biese KM, Bell DR, Schaefer DA, Watson AM. 2020. Training load and injury among middle school–Aged athletes. J Athl Train. 55(9):954–959. DOI:10.4085/1062-6050-435-19.
  • Andrade R, Wik EH, Rebelo-Marques A, Blanch P, Whiteley R, Espregueira-Mendes J, Gabbett TJ. 2020. Is the acute: chronic workload ratio (ACWR) associated with risk of time-loss injury in professional team sports? A systematic review of methodology, variables and injury risk in practical situations. Sports Med. 50(9) 1613–1635.
  • Bache-Mathiesen L 2021a. Missing data in training load (version 1.0.0). [Accessed 2021 OCt 14]. https://github.com/lenakba/missing-data-in-training-load
  • Bache-Mathiesen L 2021b. Training load and injury studies data file. GitHub: GitHub; [Accessed 2021 Oct 14]. https://github.com/lenakba/missing-data-in-training-load/blob/main/studies_missing_reporting.xlsx
  • Bache-Mathiesen LK 2021c. Performing multiple imputation in R. [Accessed 2021 Oct 14]. https://github.com/lenakba/missing-data-in-training-load/blob/main/guide-multiple-imputation.pdf
  • Bache-Mathiesen LK, Andersen TE, Dalen-Lorentsen T, Clarsen B, Fagerland MW. 2021. Not straightforward: modelling non-linearity in training load and injury research. BMJ Open Sport & Exercise Med. 7(3):e001119. DOI:10.1136/bmjsem-2021-001119.
  • Bahr R. 2016. Why screening tests to predict injury do not work—and probably never will …: a critical review. Br J Sports Med. 50(13):776–780. DOI:10.1136/bjsports-2016-096256.
  • Bahr R, Holme I. 2003. Risk factors for sports injuries—a methodological approach. Br J Sports Med. 37(5):384–392. DOI:10.1136/bjsm.37.5.384.
  • Bahr R, Krosshaug T. 2005. Understanding injury mechanisms: a key component of preventing injuries in sport. Br J Sports Med. 39(6):324–329. DOI:10.1136/bjsm.2005.018341.
  • Barnett AG, Mcelwee P, Nathan A, Burton NW, Turrell G. 2017. Identifying patterns of item missing survey data using latent groups: an observational study. BMJ Open. 7(10):e017284. DOI:10.1136/bmjopen-2017-017284.
  • Benson LC, Stilling C, Owoeye OB, Emery CA. 2021. Evaluating methods for imputing missing data from longitudinal monitoring of athlete workload. J Sports Sci Med. 20:187–195.
  • Borg DN, Nguyen R, Tierney NJ. 2021. Missing data: current practice in football research and recommendations for improvement. Sci Med Football. 1–6. DOI:10.1080/24733938.2021.1922739.
  • Borg G, Hassmén P, Lagerström M. 1987. Perceived exertion related to heart rate and blood lactate during arm and leg exercise. Eur J Appl Physiol Occup Physiol. 56(6):679–685. DOI:10.1007/BF00424810.
  • Bourdon PC, Cardinale M, Murray A, Gastin P, Kellmann M, Varley MC, Gabbett TJ, Coutts AJ, Burgess DJ, Gregson W. 2017. Monitoring athlete training loads: consensus statement. Int J Sports Physiol Perform. 12(s2):S2-161-S2–170. DOI:10.1123/IJSPP.2017-0208.
  • Boyd LJ, Ball K, Aughey RJ. 2011. The reliability of MinimaxX accelerometers for measuring physical activity in Australian football. Int J Sports Physiol Perform. 6(3):311–321. DOI:10.1123/ijspp.6.3.311.
  • Chhabra G, Vashisht V, Ranjan J. 2017. A comparison of multiple imputation methods for data with missing values. Indian J Sci Technol. 10(19):1–7. DOI:10.17485/ijst/2017/v10i19/110646.
  • Dalen-Lorentsen T, Andersen TE, Bjørneboe J, Vagle M, Martin KN, Kleppen M, Fagerland MW, Clarsen B. 2021. A cherry, ripe for picking: the relationship between the acute–chronic workload ratio and health problems. J Orthopaedic & Sports Physical Therapy. 51(4):162–173.
  • Datatilsynet. 2017. The anonymisation of personal data. Norwegian Data Protection Agency; [Accessed 2021 Oct 14]. https://www.datatilsynet.no/en/regulations-and-tools/reports-on-specific-subjects/anonymisation
  • De Leeuw A-W, Van Der Zwaard S, Van Baar R, Knobbe A. 2021. Personalized machine learning approach to injury monitoring in elite volleyball players. Eur J Sport Sci. 1–14. DOI:10.1080/17461391.2021.1887369.
  • Demirtas H, Freels SA, Yucel RM. 2008. Plausibility of multivariate normality assumption when multiply imputing non-Gaussian continuous outcomes: a simulation assessment. J Stat Comput Simul. 78(1):69–84. DOI:10.1080/10629360600903866.
  • Díaz-Ordaz K, Kenward MG, Cohen A, Coleman CL, Eldridge S. 2014. Are missing data adequately handled in cluster randomised trials? A systematic review and guidelines. Clin Trials. 11(5):590–600. DOI:10.1177/1740774514537136.
  • Dwyer DB, Gabbett TJ. 2012. Global positioning system data analysis: velocity ranges and a new definition of sprinting for field sport athletes. J Strength Condi Res. 26(3):818–824. DOI:10.1519/JSC.0b013e3182276555.
  • Eckard TG, Padua DA, Hearn DW, Pexa BS, Frank BS. 2018. The relationship between training load and injury in athletes: a systematic review. Sports Med. 48(8):1929–1961. DOI:10.1007/s40279-018-0951-z.
  • Enright K, Green M, Hay G, Malone JJ. 2019. Workload and injury in professional soccer players: role of injury tissue type and injury severity. Int J Sports Med. 41(02):89–97. DOI: 10.1055/a-0997-6741
  • Fanchini M, Rampinini E, Riggio M, Coutts AJ, Pecci C, Mccall A. 2018. Despite association, the acute: chronic work load ratio does not predict non-contact injury in elite footballers. Sci Med Football. 2(2):108–114. DOI:10.1080/24733938.2018.1429014.
  • Fernández-Cuevas I, Gómez-Carmona P, Sillero-Quintana M, Noya-Salces J, Arnaiz-Lastras J, Pastor-Barrón A. 2010. Economic costs estimation of soccer injuries in first and second spanish division professional teams. 15th Annual Congress of the European College of Sport Sciences ECSS; 23-26 june; Antalya, Turkey.
  • Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin LA, Parker S, Doleshal P, Dodge C. 2001. A new approach to monitoring exercise training. J Strength and Condi Res. 15:10Y115.
  • Griffin A, Kenny IC, Comyns TM, Lyons M. 2020. The association between the acute: chronic workload ratio and injury and its application in team sports: a systematic review. Sports Med. 50(3):561–580.
  • Hägglund M, Waldén M, Magnusson H, Kristenson K, Bengtsson H, Ekstrand J. 2013. Injuries affect team performance negatively in professional football: an 11-year follow-up of the UEFA Champions League injury study. Br J Sports Med. 47(12):738–742. DOI:10.1136/bjsports-2013-092215.
  • Hasler C, Tillé Y. 2016. Balanced k-nearest neighbour imputation. Stat. 50(6):1310–1331. DOI:10.1080/02331888.2016.1230615.
  • Hulin BT, Gabbett TJ, Lawson DW, Caputi P, Sampson JA. 2016. The acute: chronic workload ratio predicts injury: high chronic workload may decrease injury risk in elite rugby league players. Br J Sports Med. 50(4):231–236. DOI:10.1136/bjsports-2015-094817.
  • Janssen KJ, Donders ART, Harrell FE JR, Vergouwe Y, Chen Q, Grobbee DE, Moons KG. 2010. Missing covariate data in medical research: to impute is better than to ignore. J Clin Epidemiol. 63(7):721–727. DOI:10.1016/j.jclinepi.2009.12.008.
  • Jeličić H, Phelps E, Lerner RM. 2009. Use of missing data methods in longitudinal studies: the persistence of bad practices in developmental psychology. Dev Psychol. 45(4):1195. DOI:10.1037/a0015665.
  • Karahalios A, Baglietto L, Carlin JB, English DR, Simpson JA. 2012. A review of the reporting and handling of missing data in cohort studies with repeated assessment of exposure measures. BMC Med Res Methodol. 12(1):96. DOI:10.1186/1471-2288-12-96.
  • Knol MJ, Janssen KJ, Donders ART, Egberts AC, Heerdink ER, Grobbee DE, Moons KG, Geerlings MI. 2010. Unpredictable bias when using the missing indicator method or complete case analysis for missing confounder values: an empirical example. J Clin Epidemiol. 63(7):728–736. DOI:10.1016/j.jclinepi.2009.08.028.
  • Lang T 2004. Twenty statistical errors even you can find in biomedical research articles. Citeseer.
  • Lang T. 2005. Common statistical errors even you can find. part 6: errors in research designs. Part. 6:112–115.
  • Little RJ. 1988. A test of missing completely at random for multivariate data with missing values. J Am Stat Assoc. 83(404):1198–1202. DOI:10.1080/01621459.1988.10478722.
  • Lolli L, Bahr R, Weston M, Whiteley R, Tabben M, Bonanno D, Gregson W, Chamari K, Di Salvo V, Van Dyk N. 2020. No association between perceived exertion and session duration with hamstring injury occurrence in professional football. Scand J Med Sci Sports. 30(3):523–530. DOI:10.1111/sms.13591.
  • Malone JJ, Lovell R, Varley MC, Coutts AJ. 2017. Unpacking the black box: applications and considerations for using GPS devices in sport. Int J Sports Physiol Perform. 12(s2):S2-18-S2–26. DOI:10.1123/ijspp.2016-0236.
  • Mansournia MA, Collins GS, Nielsen RO, Nazemipour M, Jewell NP, Altman DG, Campbell MJ. 2021. A checklist for statistical assessment of medical papers (the CHAMP statement): explanation and elaboration. Br J Sports Med. 55(18):1009-1017. DOI:10.1136/bjsports-2020–103652.
  • Maupin D, Schram B, Canetti E, Orr R. 2020. The relationship between acute: chronic workload ratios and injury risk in sports: a systematic review. Open Access J Sports Med. 11:51. doi:10.2147/OAJSM.S231405.
  • Mccall A, Dupont G, Ekstrand J. 2018. Internal workload and non-contact injury: a one-season study of five teams from the UEFA elite club injury study. Br J Sports Med. 52(23):1517–1522. DOI:10.1136/bjsports-2017-098473.
  • Moreno-Pérez V, Prieto J, Del Coso J, Lidó-Micó JE, Fragoso M, Penalva FJ, Reid M, Pluim BM. 2020. Association of acute and chronic workloads with injury risk in high-performance junior tennis players. Eur J Sport Sci. 21(8):1215–1223.
  • Morris TP, White IR, Crowther MJ. 2019. Using simulation studies to evaluate statistical methods. Stat Med. 38(11):2074–2102. DOI:10.1002/sim.8086.
  • Morris TP, White IR, Royston P. 2014. Tuning multiple imputation by predictive mean matching and local residual draws. BMC Med Res Methodol. 14(1):75. DOI:10.1186/1471-2288-14-75.
  • Moussa I, Leroy A, Sauliere G, Schipman J, Toussaint J-F, Sedeaud A. 2019. Robust exponential decreasing index (REDI): adaptive and robust method for computing cumulated workload. BMJ Open Sport & Exercise Med. 5(1):e000573. DOI:10.1136/bmjsem-2019-000573
  • Musil CM, Warner CB, Yobas PK, Jones SL. 2002. A comparison of imputation techniques for handling missing data. West J Nurs Res. 24(7):815–829. DOI:10.1177/019394502762477004.
  • Nielsen RO, Bertelsen ML, Ramskov D, Møller M, Hulme A, Theisen D, Finch CF, Fortington LV, Mansournia MA, Parner ET. 2019. Time-to-event analysis for sports injury research part 2: time-varying outcomes. Br J Sports Med. 53(1):70–78. DOI:10.1136/bjsports-2018-100000.
  • Nielsen RO, Shrier I, Casals M, Nettel-Aguirre A, Møller M, Bolling C, Bittencourt NF, Clarsen B, Wedderkopp N, Soligard T. 2020. Statement on methods in sport injury research from the first METHODS MATTER meeting, copenhagen, 2019. J Orthopaedic & Sports Physical Therapy. 50(5):226–233. DOI:10.2519/jospt.2020.9876.
  • Riley RD, Snell KI, Ensor J, Burke DL, Harrell FE JR, Moons KG, Collins GS. 2019. Minimum sample size for developing a multivariable prediction model: PART II‐binary and time‐to‐event outcomes. Stat Med. 38(7):1276–1296. DOI:10.1002/sim.7992.
  • Rønneberg KL. 2020. Seasonal training load quantification in men’s Norwegian premier league football: differences in measured external-and internal training load within microcycles and throughout the competition phase. Norwegian School of Sport Sciences, Oslo, Norway.
  • Schouten RM, Lugtig P, Vink G. 2018. Generating missing values for simulation purposes: a multivariate amputation procedure. J Stat Comput Simul. 88(15):2909–2930. DOI:10.1080/00949655.2018.1491577.
  • Schouten RM, Vink G. 2018. The dance of the mechanisms: how observed information influences the validity of missingness assumptions. Sociol Methods Res. 50(3):1243–1258. DOI: 10.1177/0049124118799376.
  • Shmueli G. 2010. To explain or to predict? Stat Sci. 25(3):289–310. DOI:10.1214/10-STS330.
  • Sterne JA, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, Wood AM, Carpenter JR. 2009. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 338(1):b2393. DOI:10.1136/bmj.b2393.
  • Theisen D, Frisch A, Malisoux L, Urhausen A, Croisier J-L, Seil R. 2013. Injury risk is different in team and individual youth sport. J Sci Med Sport. 16(3):200–204. DOI:10.1016/j.jsams.2012.07.007.
  • Theron GF. 2020. The use of data mining for predicting injuries in professional football players. University of Oslo, Oslo, Norway.
  • Udby CL, Impellizzeri FM, Lind M, Nielsen RØ. 2020. How has workload been defined and how many workload-related exposures to injury are included in published sports injury articles? A scoping review. J Orthopaedic & Sports Physical Therapy. 50(10):538–548. DOI:10.2519/jospt.2020.9766.
  • Van Buuren S. 2018. Flexible imputation of missing data. Chapman and Hall, CRC Press, Boca Ration, Florida, USA.
  • Van Smeden M, De Groot JA, Moons KG, Collins GS, Altman DG, Eijkemans MJ, Reitsma JB. 2016. No rationale for 1 variable per 10 events criterion for binary logistic regression analysis. BMC Med Res Methodol. 16(1):1–12. DOI:10.1186/s12874-016-0267-3.
  • Vink G 2016. Towards a standardized evaluation of multiple imputation routines. [Accessed 2021 Oct 14]. https://www.gerkovink.com/docs/Standardized%20evaluation.pdf
  • Von Hippel PT. 2009. 8. How to impute interactions, squares, and other transformed variables. Sociol Methodol. 39(1):265–291. DOI:10.1111/j.1467-9531.2009.01215.x.
  • Wang A, Healy J, Hyett N, Berthelot G, Okholm Kryger K. 2021. A systematic review on methodological variation in acute: chronic workload research in elite male football players. Sci Med Football. 5(1):18–34. DOI:10.1080/24733938.2020.1765007.
  • White IR, Carlin JB. 2010. Bias and efficiency of multiple imputation compared with complete‐case analysis for missing covariate values. Stat Med. 29(28):2920–2931. DOI:10.1002/sim.3944.
  • White IR, Royston P, Wood AM. 2011. Multiple imputation using chained equations: issues and guidance for practice. Stat Med. 30(4):377–399. DOI:10.1002/sim.4067.
  • Windt J, Ardern CL, Gabbett TJ, Khan KM, Cook CE, Sporer BC, Zumbo BD. 2018. Getting the most out of intensive longitudinal data: a methodological review of workload–injury studies. BMJ Open. 8(10):e022626. DOI:10.1136/bmjopen-2018-022626.
  • Windt J, Gabbett TJ. 2017. How do training and competition workloads relate to injury? The workload—injury aetiology model. Br J Sports Med. 51(5):428–435. DOI:10.1136/bjsports-2016-096040.

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