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Enhancing Performance & Preventing Injuries in Team Sport Players van der Does, Hendrike

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Enhancing Performance & Preventing Injuries in Team Sport Players

H.T.D. van der Does

506196-L-bw-vd Does Processed on: 17-11-2016 The studies in this thesis has been conducted at the School of Sport Studies, Hanze University of Applied Sciences Groningen and Center for Human Movement Sciences, UMCG, University of Groningen.

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Ruby Otter Carola Heijdra ‘˜‡”‡•‹‰ǣ

 Carola Heijdra ”‹–‡†„›ǣ

Ipskamp Printing ǣ  

ǣ   978-90-367-9182-3 (printed version)  978-90-367-9180-9 (electronic version)  ̹‘’›”‹‰Š–ʹͲͳ͸  

, H.T.D. van der Does, Haarlem, The Netherlands All rights reserved. No part of this publication may be reproduced in any form or by any means, electronic or mechanical, including photocopy, recording or any information storage or retrieval system, without prior written permission of the copyright owner.

506196-L-bw-vd Does Processed on: 17-11-2016 

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506196-L-bw-vd Does Processed on: 17-11-2016 Promotores

Prof. dr. K.A.P.M. Lemmink Prof. dr. C. Visscher Copromotor

Dr. M.S. Brink Beoordelingscommissie

Prof. dr. R.L. Diercks Prof. dr. F.J.G Backx

Prof. dr. T. Meyer

506196-L-bw-vd Does Processed on: 17-11-2016 TABLE OF CONTENTS

Chapter 1 7

ChapterGeneral Introduction 2 19

‡’‡ƒ–‡†‘†‹ϐ‹‡†‰‹Ž‹–›Ǧ–‡•–ǣ‘Ž‡‘ˆ–Š‡‡‡”‰›•›•–‡•ƒ† Chapterƒ–Š”‘’‘‡–”‹ •‹–‡ƒ•’‘”–’Žƒ›‡”• 3 35

ChapterŠ‡‡ˆˆ‡ –‘ˆ•–”‡••ƒ†”‡ ‘˜‡”›‘ϐ‹‡Ž†Ǧ–‡•–’‡”ˆ‘”ƒ ‡‹ 4 ϐŽ‘‘”„ƒŽŽ 55

Chapter Œ—”›”‹•‹•‹ ”‡ƒ•‡†„› Šƒ‰‡•‹’‡” ‡‹˜‡†”‡ ‘˜‡”›‘ˆ–‡ 5 ƒ•’‘”–’Žƒ›‡”• 71

›ƒ‹ ’‘•–—”ƒŽ•–ƒ„‹Ž‹–›†‹ˆˆ‡”‡ ‡•„‡–™‡‡ƒŽ‡ƒ†ˆ‡ƒŽ‡’Žƒ›‡”• Chapter™‹–Šƒ†™‹–Š‘—–ƒŽ‡•’”ƒ‹ 6 89

—’Žƒ†‹‰ Šƒ”ƒ –‡”‹•–‹ •’”‡†‹ –Ž‘™‡”‡š–”‡‹–›‹Œ—”‹‡•‹‹†‘‘” Chapter–‡ƒ•’‘”–• 7 109

”‘•’‡ –‹˜‡•–—†›‘ˆ–Š‡”‡Žƒ–‹‘„‡–™‡‡Žƒ†‹‰„‹‘‡ Šƒ‹ •ƒ† ChapterŒ—’‡”ǯ•‡‡ 8 125

Summary ‡‡”ƒŽ‹• —••‹‘ / Samenvatting 137

Dankwoord 147

Curriculum Vitae 155

Previous SHARE Dissertations 160

Financial Support 163

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506196-L-bw-vd Does Processed on: 17-11-2016 General Introduction

506196-L-bw-vd Does Processed on: 17-11-2016 Chapter 1

In indoor team 6,21,22,40 sports like basketball, volleyball and korfball the game efforts

are known 30,35,42 to be high . During a volleyball game, players jump approximately

60 times . In a basketball game, players 7 perform up to 70 jumps per game, and approximately 980 running movements . These jumping and running movements include sudden accelerations, decelerations and changes of direction in anticipation to the ball and other players. Furthermore, they are executed in small field dimensions,

ranging from 18m by 9m up to 40m by 20m. This evokes short bouts of high-intensity

to20,21,42,43 near maximal effort that is alternated with periods of low-intensity activities . The frequency, types of movements and activity patterns make these types of sport very complex and demanding. Consequently, well-developed physical capacities and a good movement technique are required to perform optimal and prevent injuries. To develop these physical capacities and this movement technique, regular

training is combined with recovery in between. In addition to the physical29 stress of training, psychosocial stress and recovery also plays an important role . It is

assumed that changes in training load, stress 29 and recovery need to be monitored to enhance performance and prevent injuries . Figure 1 depicts the outline of this approach as introduced by Kenttä and Hassmén (1998). It also shows that physical charateristics and movement technique of players can be assessed at the start of the season in order to determine the injury risk.

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1

Figure 1. Model measuring physical capacities & movement technique and monitoring training load, recovery and psychosocial stress and recovery over the course of a season in team sport players. Adapted

from Kenntä and Hassmén (1998).

MONITORING

Performance

There are several factors that influence game performance in indoor team sports such

as strength of the opponent, ranking in the competition, tactics, 23,28,41 first half performance, physical and mental fitness of individual players, and so forth . This results in a

high variability between games, making game 23 analyses unsuitable to assess changes in physical performance of individual players . Currently, performance is mainly

measured by determining physical capacities once or twice 5 during the season 25 for 2 example with gold standards like the 30-second Wingate and VO max test to measure anaerobic power and aerobic endurance respectively. While these tests are suitable to measure anaerobic power and aerobic endurance, they are not very sport specific for indoor team sports. In sports like volleyball and basketball physical

capacities are measured with more sport specific6,10,11,13,17,20 field-tests like repeated sprint tests, intermittent running tests and jump tests . The type of activities of these sports also shows the importance of anaerobic (explosive) power and changes of

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direction/agility. Agility tests are more specific in comparison to the intermittent running tests when looking at movement characteristics during games. Therefore to evaluate performance more sport-specific, next to anaerobic power and aerobic

intermittent endurance, agility should be measured. Training load & Recovery

To prevent players from becoming injured and optimize performance over time, coaches and players struggle daily with finding the right balance between what they do (training load) and what they are capable of (capacities and technique) to eventually push boundaries. The training load comprises of an external and internal training load. A too high training load can negatively affect the outcome in terms of performance decrement or injury occurrence (Figure 1). The external training load is the load as imposed on the player. This is determined by frequency, duration,

intensity and 26variation of the activities and should be applied regularly to optimize

performance . Due to individual differences in capacities the impact of 29external training load, which is the internal training load, differs between players . Tools like

the Rating of Perceived Exertion 19,26 (RPE) and Heart Rate (HR) monitors, give insight in the internal training load . Next to training load, recovery is also important in the process of training and adaptation (Figure 1). The amount of recovery needed after training depends on the internal training load. Thus, a higher internal training load requires more recovery. It is assumed that a balance between internal training load and recovery is needed to optimize performance and prevent injuries. Individual monitoring of this process over the course of a season will give adequate insight and allow for on-time interventions. Research up until now showed a decrement in field-

test performance after a period of intensified training 12-14 load, while a period of reduced training load increased field-test performance . Monitor studies relating training

load to field-test performance over the season are limited and show improved 10 performance with increased training duration in the week before testing . This indicates the need for monitoring studies over the course of a season that measure performance more regular. Psychosocial stress & recovery

Recent studies show the importance 11,12,17 of psychosocial stress and recovery to enhance performance and prevent injuries . Psychosocial stress arises when there is a perceived imbalance between expectations and performance capabilities. This

imbalance can be perceived in sports, but also in work, 27,29 home situations, or from the interaction with people and/or (personal) life events . These additional stress

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factors also influence the response to the imposed training load and the recovery 27,37 needed. A tool like the Recovery Stress Questionnaire Sport (RESTQ-Sport) can give insight in psychosocial stress and recovery related activities. Players fill out the questionnaire regularly, for example every three weeks. Since these activities are

personal, 27 changes over time should be compared with a players’ own individual profile . The process of training load, recovery and psychosocial stress and recovery has an effect on the outcome in terms of both performance and injury occurrence. 1

Therefore continuous monitoring of these processes and their outcome is important. MOVEMENT TECHNIQUE & INJURY

The load on the lower extremities in indoor team sports is high due to the running,

jumping, sudden decelerations,38,39 cutting movements and16 changes of 2direction, this 39 increases the injury risk . In sports like basketball , volleyball and floorball

55% up to 77% of the injuries occur at18 the lower extremities, of which 27% to the knee and 22% up to 41% to the ankle . Research shows about 30% of lower

extremity injuries occur3,4,34 from sharp twist and turns, whereas 45 up to 86% occur from jump landing . So the execution of the jump is crucial and in particular the technique and stability during the jump-landing phase. When poorly performed the

load on the lower2,15,16,44 extremities increases, which in turn increases the injury risk of both knee and ankle . An optimal jump-landing technique is relevant to efficiently

absorb1,32 the impact forces of the landing, decreasing the loads on the lower extremities

. Studies have shown that a suboptimal 24,36jump-landing technique (Figure 2) and less landing stability are related to acute knee and acute ankle injury occurrence 33,46 respectively .

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Figure 2. Example of an optimal (left) and suboptimal (right) jump-landing. On the left the player has good knee and hip flexion, on the right the joint flexion is limited.

A limitation of current research is the focus on acute injuries,15 while overuse injuries also account for a great part of the injuries. In basketball and volleyball the

jumpers knee is the most common overuse 31,47injury, due to the repetitive jumping, with a prevalence of 45% and 32% respectively . Recently it was suggested that 8,9,45 suboptimal landing technique is also a potential indicator of overuse injuries . Screening tools that measure landing stability and technique of a player are therefore important to incorporate at the start of the season to get insight in risk profiles. By monitoring the injury occurrence the relation can be explored between the risk profiles at the start of the season and the injuries over the season. This knowledge can guide training and prevention programs of both acute and overuse injuries over the

course of a season. THESIS OUTLINE

The aim of this thesis is two-fold. First to investigate if changes in training load, recovery and psychosocial stress and recovery are related to (field-test) performance and injury occurrence during the season. Secondly, to provide more insight in the

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predictive value of movement technique measured at the start of season for injury occurrence during the season. To reach these goals 129 male and female volleyball, basketball, korfball and floorball players were monitored over the course of two seasons. First, it was investigated to what extent anaerobic and aerobic energy systems were related to a team sport specific agility test. Thereafter, training load and recovery and psychosocial stress and recovery 1 were related to field-test performance in chapter 3. Since changes in psychosocial stress and recovery could also increase injury risk, the association with acute and overuse injuries is presented in chapter 4.

The following three chapters focus onth the movement technique at baseline and the injury risk during the season. In the 5 Chapter the landing stability was investigated in relation to ankle injuries during the subsequent season. After that, Chapter 6 investigated the predictive value of both landing stability and landing technique at the start of the season for acute and overuse ankle and knee injuries over

2 seasons. Jump landingth as risk factor for a jumper’s knee was more closely investigated in the 7 Chapter. The methods and results of Chapter 2 through 7 are discussed in the general discussion, after which the final conclusions are drawn. Lastly, the results are put into

a practical perspective, giving implications for coaches, players and medical staff.

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1 Aerts I, Cumps E, Verhagen E, et al. A related to patellar tendinopathy? Br J systematic review of different jump- Sports Med 2008;42:483-489. landing variables in relation to injuries. J Sports Med Phys Fitness 2013;53:509-519. 9 Bisseling RW, Hof AL, Bredeweg SW, et al. Relationship between landing strategy 2 Agel J, Palmieri-Smith RM, Dick R, et al. and patellar tendinopathy in volleyball. Br Descriptive epidemiology of collegiate J Sports Med 2007;41:e8. women's volleyball injuries: National Collegiate Athletic Association Injury 10 Brink MS, Nederhof E, Visscher C, et al. Surveillance System, 1988-1989 through Monitoring load, recovery, and 2003-2004. J Athl Train 2007;42:295-302. performance in young elite soccer players. J Strength Cond Res 2010;24:597-603. 3 Bahr R, Bahr IA. Incidence of acute volleyball injuries: a prospective cohort 11 Brink MS, Visscher C, Coutts AJ, et al. study of injury mechanisms and risk Changes in perceived stress and recovery factors. Scand J Med Sci Sports 1997;7:166- in overreached young elite soccer players. 171. Scand J Med Sci Sports 2012;22:285-292.

4 Bahr R, Karlsen R, Lian O, et al. Incidence 12 Coutts AJ, Reaburn P. Monitoring and mechanisms of acute ankle inversion changes in rugby league players' perceived injuries in volleyball. A retrospective stress and recovery during intensified cohort study. Am J Sports Med training. Percept Mot Skills 2008;106:904- 1994;22:595-600. 916.

5 Bar-Or O. The Wingate anaerobic test. An 13 Coutts AJ, Reaburn P, Piva TJ, et al. update on methodology, reliability and Monitoring for overreaching in rugby validity. Sports Med 1987;4:381-394. league players. Eur J Appl Physiol 2007;99:313-324. 6 Ben Abdelkrim N, Castagna C, Jabri I, et al. Activity profile and physiological 14 Coutts AJ, Wallace LK, Slattery KM. requirements of junior elite basketball Monitoring changes in performance, players in relation to aerobic-anaerobic physiology, biochemistry, and psychology fitness. J Strength Cond Res 2010;24:2330- during overreaching and recovery in 2342. triathletes. Int J Sports Med 2007;28:125- 134. 7 Ben Abdelkrim N, El Fazaa S, El Ati J. Time-motion analysis and physiological 15 Cumps E, Verhagen E, Meeusen R. data of elite under-19-year-old basketball Prospective epidemiological study of players during competition. Br J Sports basketball injuries during one competitive Med 2007;41:69-75; discussion 75. season: ankle sprains and overuse knee injuries. J Sports Sci Med 2007;6:204-211. 8 Bisseling RW, Hof AL, Bredeweg SW, et al. Are the take-off and landing phase 16 Dick R, Hertel J, Agel J, et al. Descriptive dynamics of the volleyball spike jump epidemiology of collegiate men's basketball injuries: National Collegiate

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Athletic Association Injury Surveillance 25 Howley ET, Bassett DR,Jr, Welch HG. System, 1988-1989 through 2003-2004. J Criteria for maximal oxygen uptake: Athl Train 2007;42:194-201. review and commentary. Med Sci Sports Exerc 1995;27:1292-1301. 17 Faude O, Kellmann M, Ammann T, et al. Seasonal changes in stress indicators in 26 Impellizzeri FM, Rampinini E, Marcora high level football. Int J Sports Med SM. Physiological assessment of aerobic 2011;32:259-265. training in soccer. J Sports Sci 2005;23:583-592. 1 18 Fong DT, Hong Y, Chan LK, et al. A systematic review on ankle injury and 27 Kellmann M, Kallus KW. Recovery- ankle sprain in sports. Sports Med stress questionnaire for athletes: User 2007;37:73-94. manual. Champaign, IL: Human Kinetics 2001. 19 Foster C. Monitoring training in athletes with reference to overtraining syndrome. 28 Kempton T, Sirotic AC, Cameron M, et al. Med Sci Sports Exerc 1998;30:1164-1168. Match-related fatigue reduces physical and technical performance during elite rugby 20 Gabbett T, Georgieff B, Domrow N. The league match-play: a case study. J Sports use of physiological, anthropometric, and Sci 2013. skill data to predict selection in a talent- identified junior volleyball squad. J Sports 29 Kentta G, Hassmen P. Overtraining and Sci 2007;25:1337-1344. recovery. A conceptual model. Sports Med 1998;26:1-16. 21 Girard O, Mendez-Villanueva A, Bishop D. Repeated-sprint ability - part I: factors 30 Lian O, Engebretsen L, Ovrebo RV, et al. contributing to fatigue. Sports Med Characteristics of the leg extensors in male 2011;41:673-694. volleyball players with jumper's knee. Am J Sports Med 1996;24:380-385. 22 Godinho M, Fragoso I, Vieira F. Morphologic and anthropometric 31 Lian OB, Engebretsen L, Bahr R. characteristics of high level Dutch korfball Prevalence of jumper's knee among elite players. Percept Mot Skills 1996;82:35-42. athletes from different sports: a cross- sectional study. Am J Sports Med 23 Gregson W, Drust B, Atkinson G, et al. 2005;33:561-567. Match-to-match variability of high-speed activities in premier league soccer. Int J 32 Louw Q, Grimmer K, Vaughan C. Knee Sports Med 2010;31:237-242. movement patterns of injured and uninjured adolescent basketball players 24 Hewett TE, Myer GD, Ford KR, et al. when landing from a jump: a case-control Biomechanical measures of neuromuscular study. BMC Musculoskelet Disord control and valgus loading of the knee 2006;7:22. predict anterior cruciate ligament injury risk in female athletes: a prospective study. 33 McGuine TA, Greene JJ, Best T, et al. Am J Sports Med 2005;33:492-501. Balance as a predictor of ankle injuries in high school basketball players. Clin J Sport Med 2000;10:239-244.

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34 McKay GD, Goldie PA, Payne WR, et al. performance. Int J Sports Med Ankle injuries in basketball: injury rate and 2007;28:1018-1024. risk factors. Br J Sports Med 2001;35:103- 108. 42 Sheppard JM, Gabbett T, Taylor KL, et al. Development of a repeated-effort test for 35 Mroczek D, Januszkiewicz A, elite men's volleyball. Int J Sports Physiol Kawczynski AS, et al. Analysis of male Perform 2007;2:292-304. volleyball players' motor activities during a top level match. J Strength Cond Res 43 Sheppard JM, Young WB. Agility 2014;28:2297-2305. literature review: classifications, training and testing. J Sports Sci 2006;24:919-932. 36 Myer GD, Ford KR, Khoury J, et al. Biomechanics laboratory-based prediction 44 Terada M, Pietrosimone B, Gribble PA. algorithm to identify female athletes with Individuals with chronic ankle instability high knee loads that increase risk of ACL exhibit altered landing knee kinematics: injury. Br J Sports Med 2011;45:245-252. potential link with the mechanism of loading for the anterior cruciate ligament. 37 Nederhof E, Brink MS, Lemmink KAPM. Clin Biomech (Bristol, Avon) Reliability and validity of the Dutch 2014;29:1125-1130. Recovery Stress Questionnaire for athletes. International Journal of Sport Psychology 45 Van der Worp H, de Poel HJ, Diercks RL, 2008;39:301-311. et al. Jumper's knee or lander's knee? A systematic review of the relation between 38 Olsen OE, Myklebust G, Engebretsen L, jump biomechanics and patellar et al. Injury mechanisms for anterior tendinopathy. Int J Sports Med cruciate ligament injuries in team 2014;35:714-722. handball: a systematic video analysis. Am J Sports Med 2004;32:1002-1012. 46 Wang HK, Chen CH, Shiang TY, et al. Risk-factor analysis of high school 39 Pasanen K, Parkkari J, Kannus P, et al. basketball-player ankle injuries: a Injury risk in female floorball: a prospective controlled cohort study prospective one-season follow-up. Scand J evaluating postural sway, ankle strength, Med Sci Sports 2008;18:49-54. and flexibility. Arch Phys Med Rehabil 2006;87:821-825. 40 Pasanen K, Parkkari J, Pasanen M, et al. Effect of a neuromuscular warm-up 47 Zwerver J, Bredeweg SW, van den programme on muscle power, balance, Akker-Scheek I. Prevalence of Jumper's speed and agility: a randomised controlled knee among nonelite athletes from study. Br J Sports Med 2009;43:1073-1078. different sports: a cross-sectional survey. Am J Sports Med 2011;39:1984-1988. 41 Rampinini E, Coutts AJ, Castagna C, et al. Variation in top level soccer match

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506196-L-bw-vd Does Processed on: 17-11-2016 ‡’‡ƒ–‡†‘†‹ϐ‹‡†‰‹Ž‹–›Ǧ–‡•–ǣ Role of the energy systems and anthropometrics in team sport players

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506196-L-bw-vd Does Processed on: 17-11-2016 Chapter 2

The aim of this study was to determine 1) the relation between the anaerobic and aerobic energy systems and RMAT performance and 2) to what extent this relation is affected by anthropometrics in male and female indoor team sport players. Twenty- three male and 31 female players performed a repeated Wingate Anaerobic Test

(WAnT), a VO2max test and a RMAT. The RMAT consists of 10 sprints with changes of direction, starting every 30 seconds. Prior to testing general anthropometrics were measured. Pearson correlations showed for the WAnT higher absolute power (Watt) resulted in faster Total Time (sec) of the RMAT in female players (r= -0.36 - -0.45, p κͶǤͶͻȌǤƒŽŽ‡”ƒ†Š‡ƒ˜‹‡”ˆ‡ƒŽ‡’Žƒ›‡”•Šƒ†ƒˆƒ•–‡”‘–ƒŽ‹‡ȋ•‡ Ȍ‘ˆ–Š‡ȋ”ε- 0.50 and -ͶǤ͹ͽ”‡•’‡ –‹˜‡Ž›ǡ’κͶǤͶͻȌǤ ‘”ƒŽ‡’Žƒ›‡”•‘”‡Žƒ–‹‘•™‹–Š performance were found. The multiple regression model for Total Time of the RMAT in female players showed an explained variance of 22% for height. The remaining variables did not significantly contribute to the model. In conclusion, in female players a better anaerobic energy system is related to faster RMAT performance. However anthropometrics, especially height, seem to be slightly more dominant than the contribution of the energy systems.

Keywords: physiology, testing, agility, height

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INTRODUCTION

Physical game demands of indoor team sports, such as basketball and volleyball, 12 involve repeated short bouts of high-intensity or maximal exercise alternated with periods of low-intensity activities, also described as repeated sprinting . These high-

intensity activities 2,25,26 include quick changes in forward, backward and lateral directions

while accelerating and decelerating usually in reaction to a stimulus such 26as an

opponent or ball . These activities fit the definition of agility; “a rapid whole-body 26,29

movement with change of velocity or direction in response to a stimulus” . The

21physical component of agility is known as change of direction speed (CODS) .

12,13,27 High-intensity activities place high demands on the anaerobic energy system and over the game the contribution of the aerobic energy system slowly increases 2

. So, the anaerobic and aerobic energy 14,24 systems seem important as performance indicators for CODS. The Repeated Modified Agility T-test (RMAT) is proposed to measure CODS for indoor team sports . However, it is not clear to what extend the energy systems are related to RMAT performance. Only one study investigated the role of the anaerobic energy system in RMAT

performance. A higher 14 absolute and relative peak and mean power output on a 30 second Wingate test resulted in faster peak and total sprint times on the RMAT in

male college students 2,18. These findings are in 17 line with the results of studies investigating the role of the anaerobic energy system in repeated straightforward sprinting in both male and female players . The contribution of the aerobic energy system to RMAT performance is not

yet known. However, 7 from straight sprint tests it appears that this contribution

depends on characteristics of the field test protocol (trajectory, duration and 1,16,17 number 2 of repetitions) . It has been shown that a higher absolute and relative VO max was related to faster sprint times when the protocol consisted of longer sprints . This was the case for peak time and total sprint time in repeated straight sprint tests. On 2 the contrary no relation 3,10,18 was found between absolute and relative VO max and sprint times on repeated sprint tests in male players with protocols involving sprints of shorter duration . In sum, protocols with sprints of longer duration and more repetitions depend heavier on the aerobic energy system compared to protocols

involving sprints 26 of shorter duration and fewer repetitions.

Anthropometrics, in terms of both body 8 weight and height, are suggested to

influence CODS . Heavy players may find it difficult to coordinate the directional 9 changes while accelerating and decelerating . Height has only been investigated in relation to lunge performance, which accounted for 85% of the common variance . Most research up until now confirms that male and female players with more body

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8,19

20 mass have a slower CODS . Since more body mass is also related to lower relative 2 VO max and lower vertical jump height as an indicator of anaerobic power , both body weight and height might affect the relation between energy systems and CODS. Up until now studies investigating CODS did not look specifically at the role of both anaerobic and aerobic energy systems and anthropometrics at the same time. Studies that did include the role of both energy systems are limited to straightforward sprinting. Furthermore, the role of the energy systems has not been studied in both male and female players within the same study using the same protocol. Agility

studies1,17,18 with female players are limited but some differences appear to exist between sexes . Therefore, the aim of this study was to determine the relation between the anaerobic and aerobic energy systems and RMAT performance along with discovering to what extent this is affected by anthropometrics in male and female indoor team sport players. METHODS

Subjects

Fifty-four sub-elite volleyball, basketball, floorball and korfball players; 23 males (mean±SD: age 21.9 ± 2.7 yr, body mass 85.2 ± 10.8 kg, height 191.9 ± 5.1 cm) and 31 females (mean ± SD: age 21.9 ± 3.2 yr, body mass 69.7 ± 9.9 kg, height 176.1 ± 6.8 cm) participated in this study. Sub-elite was defined as playing at the highest regional or national level having on average three weekly training sessions and one game a week. After being fully informed about the study, each player signed an informed consent. The study was performed in accordance with the guidelines of the medical ethical committee of the University Medical Center. This study is part of a larger study called Groningen MAPS; Groningen Monitoring Athletic Performance Study. Procedures

A cross-sectional study design was used. At the start of the 2011-2012 season anaerobic and aerobic capacities (independent variables) were measured in the 2 exercise lab with the repeated WAnT and a VO max test, respectively. Also general anthropometrics were measured. To measure CODS (dependent variable) the RMAT was performed indoor within 6 weeks. For both laboratory tests players were asked to restrain from eating and drinking anything except water two hours prior to testing. During all tests players were verbally encouraged by the test instructor to evoke

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5 maximal effort. To exclude cardiovascular risks a sports medical physician screened all players according to the Lausanne recommendations . Anthropometrics.

Prior to the tests in the lab, general anthropometrics were measured 15 in terms of body mass and height. Body mass in kg was measured with a Tanita BC-418MA (Tanita corp, Tokio, Japan), which showed good validity and reliability . Height in cm ° was measured by using a tape measure attached to a wall with a sliding horizontal 22 headpiece which was placed on the top of the head in a 90 angle. Players were asked to remove their shoes and stand erect with the heels together . Repeated Wingate Anaerobic Test. 2

The 30-second WAnT is the most common test to measure anaerobic power.

However, this protocol does not reflect the characteristics of the high-intensity 17,27 activities in indoor team sports. Therefore a repeated WAnT protocol was developed to reflect the game demands of indoor team sports with an intermittent character . The repeated WAnT was performed on a cycle ergometer (Excalibur Sport, Lode B.V., Groningen, The Netherlands). The test started with a warm up period of five minutes at a resistance of 150 Watts for males and 100 Watts for females. Players were asked to keep the pedal frequency on a self-chosen RPM between 80 and 90 during the

warm up and active rest periods. The protocol consisted of 6 all out 4 sprints of 10 seconds from a rolling start with one minute of active rest in between. The resistance for the sprints was set at a torque factor of 0.75 times body mass . Performance was expressed as Peak Power Output (PPO), Total Peak Power Output (TPPO), Mean Power Output (MPO) and Total Mean Power Output (TMPO). The PPO and MPO refer

to the highest power output and TPPO and TMPO to the total power output from the

six sprints together. VO2max test.

2 A VO max test was executed to determine the maximal aerobic capacity and

was assessed on a treadmill (Valiant, Lode B.V., Groningen, The Netherlands)-1 using a

”ƒ’’”‘–‘ ‘ŽǤˆ–‡”ƒˆ‹˜‡‹—–‡™ƒ”—’’‡”‹‘†ƒ–‡‹‰Š–ήŠ-1 with a slope of two-1

’‡” ‡–ǡ–Š‡˜‡Ž‘ ‹–›‰”ƒ†—ƒŽŽ›‹ ”‡ƒ•‡†™‹–ŠͲǤͺήŠ-1 ‡ƒ Š‹—–‡—–‹ŽͳͺήŠ . ˆ–‡”ͳͺήŠ the slope increased by one percent each minute. Players ran until volitional exhaustion. Metabolic measurements were made using a breath-by-breath gas analyzer (Cortex Metalyzer 3B, Procare B.V. Groningen, The Netherlands). The 2 highest VO was determined as a moving average over 30 sec when at least two of the

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following criteria were met: (1) respiratory exchange ratio value of at least 1.15, (2) 2 the Rating 6,11 of Perceived Exertion after the test was above 18, and (3) the VO reached 2 a plateau . Both RER and RPE were measured and the VO plateau was determined based on visual inspection of the data. 2 For both the repeated WAnT as well as the VO max test performance was expressed in absolute and relative measures to investigate the affect of anthropometrics on the relationship between the energy systems and CODS. Repeated Modified Agility T-test. 24

CODS was measured by way of the RMAT . The RMAT was performed using the protocol described by Haj-Sassi et al. (2011) consisting of ten maximal sprints starting every 30 seconds. The players started at the start line placed 55cm before A. After a countdown from 3, the athletes sprinted forward towards mark B, shuffled left or right to C or D, shuffled back to B onward to C or D, back to B and ran backwards to A (Figure 1). Players were instructed not to cross their feet while shuffling, and touch the tape at B,C and D with their feet. In contrast to the protocol of Haj-Sassi et al. (2011), where they touched the mark with their hand, the mark was touched with their feet being more sport specific. Sprint times were recorded using an electronic timing system (TAG Heuer, Marinn, Swiss), which was positioned at either side of mark A. The sensors were mounted on tripods and placed 1.35 m above the ground (approximately at shoulder height). The performance indices were the fastest time of the ten sprints named Peak Time (PT) and Total Time (TT) of the ten sprints. Both indices have shown to be reliable illustrated by an ICC (95% CI) of 0.94 (0.77-0.99) r p 14 and 0.97 (0.89 – 0.99) for PT and TT respectively. Furthermore, validity was supported against vertical and horizontal jumping ( = -0.43 to -0.72; ζͲǤͲͷȌ .

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2

14 Figure 1. Repeated Modified Agility T-test (RMAT) modified from Haj-Sassi et al.

Statistical analysis

Data analysis was performed using IBM SPSS Statistics 20 for Windows. Descriptive statistics (means and standard deviations) were computed for all variables. Pearson product-moment correlations were calculated to determine the relationship between the various performance indices including anthropometrics. First the relationship of the performance indices of the multiple WAnT and the 2 VO max with the performance of the RMAT was determined. Second, the relationship of the anthropometrics with performance of the RMAT was determined. With backward stepwise multiple regression analysis the contribution of the multiple 2 WAnT, the VO max performance indicators and anthropometrics to the variance of the RMAT scores was determined. The indicators with the best single correlation were added to the model of the RMAT scores. These correlations and regression p models were computed for male and female players separately. The level of statistical significance was set at ζͲǤͲͷǤ

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Multiple WAnT Male Female

PPO (W) 1611.75 ± 244.08 1103.91 ± 191.56

TPPO (W) 8487.55 ± 1308.28 5999.74 ± 1008.72 -1 ȋލ‰ ) 18.92 ± 1.83 15.84 ± 1.44 -1 ȋލ‰ ) 99.70 ± 10.17 86.07 ± 7.00

MPO (W) 1049.91 ± 118.56 714.69 ± 105.28

TMPO (W) 5266.57 ± 561.90 3798.64 ± 548.78 -1 ȋލ‰ ) 12.37 ± 0.97 10.28 ± 0.77 -1 VO2max test ȋލ‰ ) 62.24 ± 6.22 54.66 ± 4.38

-1 2 VO ƒšȋŽή‹ ) 4.25 ± 0.34 2.97 ± 0.32 -1 -1 2 RMAT VO ƒšȋŽή‹ ήkg ) 50.36 ± 5.28 42.95 ± 4.67

Peak Time (s) 5.48 ± 0.24 6.20 ± 0.41 Total Time (s) 57.48 ± 2.35 64.82 ± 4.00 n n 2 SD Table 1. Descriptive data of the Multiple Anaerobic Wingate test (WAnT), VO max test and Repeated Modified Agility T-test (RMAT) for male ( =23) and female ( =31) players. Values are mean± . PPO= Peak Power Output; TPPO = Total Peak Power Output; MPO = Mean Power Output; TMPO = Total Mean Power Output

RESULTS

2 The descriptives for the multiple WAnT, the VO max test and the RMAT are presented in Table 1 for both male and female players. For male players there was no relation between performance indices of the multiple 2 WAnT the VO max test, and RMAT performance. Next, the results showed that female p players with higher absolute PPO, TPPO and MPO of the multiple WAnT had faster TT of the RMAT (r= -0.45, -0.41 and -0.36 respectively; ζͲǤͲͷȌǤ

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The relationship between anthropometrics and performance of the RMAT, specifically TT, are shown in Figure 2 and 3. Anthropometrics and RMAT performance p p were not related in male players. However, taller female players had faster PT (r =- p 0.40; ζͲǤͲͷȌƒ†ȋ”α-0.50; ζͲǤͲͳǡ ‹‰—”‡ʹȌ‘ˆ–Š‡ƒ†Š‡ƒ˜‹‡”ˆ‡ƒŽ‡ players had faster TT (r =-0.37; ζͲǤͲͷǡ ‹‰—”‡͵ȌǤ

2

Figure 1. Relationship between height (cm) of male and female players separately and total time of the Repeated Modified Agility Test (RMAT).

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Figure 2. Relationship between body weight (kg) of male and female players separately and total time of the Repeated Modified Agility Test (RMAT).

The results of the backward multiple regression analysis showed no significant models for male players, neither for PT in female players. Table 2 shows the results for the regression model made for female players of the TT of the RMAT. The model for TT on the RMAT showed a 22% explained variance of height in female players. The PPO did not contribute significantly to the model.

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Step Constant Beta R2 p

Total Time

1 107.32 0.23

PPO -0.237 0.240

Height -0.357 0.082 2 116.28 0.22

Height -0.496 0.005 2 n Table 2. Backward stepwise multiple regression for the Total Time (TT) on the Repeated Modified Agility

Test (RMAT)2 of the female ( =31) team sport players. PPO= Peak Power Output; Beta = standardized beta weights; R = Shared variance

DISCUSSION

This study aimed to determine the relation between the anaerobic and aerobic energy systems and RMAT performance in male and female indoor team sport players. The second aim was to discover to what extent this is affected by anthropometrics. Female players with higher absolute anaerobic power and females that were taller and heavier showed faster TT of the RMAT. Height showed to be the best predictor for TT 2 of the RMAT in females. No significant relation was found between VO max and RMAT performance. For male players there was no significant relation between anaerobic and aerobic energy systems, anthropometrics and RMAT performance. It should be noted that relations were found with TT of the RMAT but not with PT. This may be due to the repeated protocol, enabling a pacing strategy. This is supported by the large inter-individual differences between the sprints in which players reached their PT; some in their first sprint and others during the last. As a result maximal PT may not be reached. Although in female players the anaerobic system indeed contributed to RMAT performance, this was not the case for male players. The latter is in contrast with

previous findings showing 14 higher relative and absolute anaerobic power resulting in both faster PT and TT . An explanation for this can be that the male players in the study of Haj-Sassi et al. (2011) had comparable anthropometrics as our female players. In contrast, our male players are much taller and heavier. Being taller the players may have an advantage being able to take bigger steps and touch the marks

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more easily with their feet during the RMAT protocol. The optimal height of around 1.90m (Figure 2) probably coincides with an optimal step length that is beneficial for the task. However, when players are taller than this optimum it seems that their

weight becomes a disadvantage. Being heavier the male players may have more 8,20,28 difficulty with the quick accelerations and decelerations needed for CODS tests . The fact that the male group was more homogenous regarding length and weight may have weakened this relation even more. Another explanation for the fact that weaker and more non-significant relations were found between the anaerobic energy system and RMAT performance may be in the protocols used for anaerobic power and CODS. The movements in the RMAT protocol may require coordination and motor skills, while the multiple WAnT just involves a simple cyclic movement. In addition, in the RMAT protocol of Haj-Sassi et al. (2011) the players touched the mark with their hand in contrast to our protocol where the mark was touched with their feet increasing the advantage for players with wider step length. 2 Between VO max and RMAT performance no relation was found 8,10,16,17 in both male and female players. Studies up until now show no consistent results . This may be due to the differences in protocols varying in the duration of sprints and of

recovery between sprints. The 8 protocols used in the 1,16,17 studies showing a relation 2 between VO max and CODS or repeated sprinting have sprints of longer duration with relatively short recovery periods, around eight and ten seconds

respectively. On the contrary the protocols of studies showing no relation 3,10,18 involve sprints of shorter duration with relatively longer recovery periods . In the latter studies players are able to recover sufficiently to be able to use mainly the anaerobic energy system for the successive sprints. Our protocol is in line with these studies since it consisted of five-second sprints, with 25 seconds of recovery in between. This is probably enough to recover in between sprints. The TT of our players of the RMAT supports this since there seem to be no decrease over the 10 sprints indicating

sufficient recovery. As stated before it seems that the duration of 7sprints and recovery between sprints determine the role of the aerobic energy system

A recent study shows that jumping, sprinting and CODS are independent 23 motor abilities, having a low common variance ranging from six to 23% . In our study the results indicated a more important influence of anthropometrics compared

to2 the aerobic or anaerobic energy system. Anthropometrics explained 25% (r =-0.50;

R =0.25) of the variance2 in female players, while for the anaerobic energy system this was 20% (r =-0.45; R =0.20). This indicates that CODS is an independent motor ability. It can be argued that compared to the WAnT, jump and straight sprint tests

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this motor ability is especially relevant for CODS. This means that in male and female players it is important to use separate performance tests to asses the aerobic and anaerobic energy system as well as CODS, jump and straight sprint performance. This study is the first to include to what extent the relation between the anaerobic and aerobic energy systems and RMAT performance is affected by anthropometrics. Furthermore in this study both male and female players participated and the results were presented separately. To conclude, in female players a better anaerobic energy system was weakly related to better RMAT performance. Height showed to be the best single predictor for RMAT performance. The aerobic energy system does not seem to play a role in CODS. The energy systems don’t seem to be dominant in CODS, anthropometrics seem to play a more important role in 2 CODS. PRACTICAL APPLICATIONS

CODS plays an important role in indoor team sports. Although the anaerobic energy system influence RMAT performance in female players anthropometrics seem to be slightly more dominant. This may be taken into account when testing CODS and interpreting the performance on CODS tasks. The role of the energy systems in CODS is limited therefore other tests should be used to specifically test the anaerobic and/or aerobic energy systems. ACKNOWLEDGEMENTS

The authors would like to thank all players and coaches of the Groningen Monitoring Athletic Performance Study (MAPS) who took part in this study. We also like to thank the staff and students participating in the SportsFieldLab Groningen in the study year 2011-2012 and 2012 – 2013 for their assistance in the data collection. This work was supported by the SIA RAAK-PRO under Grant PRO-2-018.

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REFERENCES

9 Cronin J, McNair PJ, Marshall RN. Lunge performance and its determinants. J Sports Sci 2003;21:49-57. 1 Aziz AR, Chia M, Teh KC. The relationship between maximal oxygen uptake and repeated sprint performance indices in 10 da Silva JF, Guglielmo LG, Bishop D. field hockey and soccer players. J Sports Relationship between different measures Med Phys Fitness 2000;40:195-200. of aerobic fitness and repeated-sprint ability in elite soccer players. J Strength Cond Res 2010;24:2115-2121. 2 Aziz AR, Chuan TEHK. Correlation between Tests of Running Repeated Sprint Ability and Anaerobic Capacity by Wingate 11 Faulkner J, Eston R. Overall and Cycling in Multi-Sprint Sports Athletes. peripheral ratings of perceived exertion International Journal of Applied Sports during a graded exercise test to volitional Sciences 2004;16:14-22. exhaustion in individuals of high and low fitness. Eur J Appl Physiol 2007;101:613- 620. 3 Aziz AR, Mukherjee S, Chia MY, et al. Relationship between measured maximal oxygen uptake and aerobic endurance 12 Girard O, Mendez-Villanueva A, Bishop performance with running repeated sprint D. Repeated-sprint ability - part I: factors ability in young elite soccer players. J contributing to fatigue. Sports Med Sports Med Phys Fitness 2007;47:401-407. 2011;41:673-694.

4 Bar-Or O. The Wingate anaerobic test. An 13 Glaister M. Multiple sprint work : update on methodology, reliability and physiological responses, mechanisms of validity. Sports Med 1987;4:381-394. fatigue and the influence of aerobic fitness. Sports Med 2005;35:757-777. 5 Bille K, Figueiras D, Schamasch P, et al. Sudden cardiac death in athletes: the 14 Haj-Sassi R, Dardouri W, Gharbi Z, et al. Lausanne Recommendations. Eur J Reliability and validity of a new repeated Cardiovasc Prev Rehabil 2006;13:859-875. agility test as a measure of anaerobic and explosive power. J Strength Cond Res 2011;25:472-480. 6 Borresen J, Lambert MI. Changes in heart rate recovery in response to acute changes in training load. Eur J Appl Physiol 15 Jackson AS, Pollock ML, Graves JE, et al. 2007;101:503-511. Reliability and validity of bioelectrical impedance in determining body composition. J Appl Physiol (1985) 7 Brughelli M, Cronin J, Levin G, et al. 1988;64:529-534. Understanding change of direction ability in sport: a review of resistance training studies. Sports Med 2008;38:1045-1063. 16 Jones RM, Cook CC, Kilduff LP, et al. Relationship between repeated sprint ability and aerobic capacity in professional 8 Chaouachi A, Brughelli M, Chamari K, et soccer players. ScientificWorldJournal al. Lower limb maximal dynamic strength 2013;2013:952350. and agility determinants in elite basketball players. J Strength Cond Res 2009;23:1570-1577. 17 Lemmink KA, Visscher SH. Role of energy systems in two intermittent field

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tests in women field hockey players. J 24 Sassi RH, Dardouri W, Yahmed MH, et Strength Cond Res 2006;20:682-688. al. Relative and absolute reliability of a modified agility T-test and its relationship 18 Meckel Y, Machnai O, Eliakim A. with vertical jump and straight sprint. J Relationship among repeated sprint tests, Strength Cond Res 2009;23:1644-1651. aerobic fitness, and anaerobic fitness in elite adolescent soccer players. J Strength 25 Sheppard JM, Gabbett T, Taylor KL, et al. Cond Res 2009;23:163-169. Development of a repeated-effort test for elite men's volleyball. Int J Sports Physiol 19 Nimphius S, McGuigan MR, Newton RU. Perform 2007;2:292-304. Relationship between strength, power, speed, and change of direction 26 Sheppard JM, Young WB. Agility performance of female softball players. J literature review: classifications, training Strength Cond Res 2010;24:885-895. and testing. J Sports Sci 2006;24:919-932. 2

20 Ostojic SM, Mazic S, Dikic N. Profiling in 27 Spencer M, Bishop D, Dawson B, et al. basketball: physical and physiological Physiological and metabolic responses of characteristics of elite players. J Strength repeated-sprint activities:specific to field- Cond Res 2006;20:740-744. based team sports. Sports Med 2005;35:1025-1044. 21 Reilly T, Bowen T. Exertional Costs of Changes in Directional Modes of Running. 28 Spiteri T, Newton RU, Binetti M, et al. Percept Mot Skills 1984;58:149-150. Mechanical determinants of faster change of direction and agility performance in 22 Ross W, Marfell-Jones M. Physiological female basketball athletes. J Strength Cond testing of the High-Performance Athlete. Res 2015. In: MacDougall J, Wenger H, Green H, eds. Kinanthropometry.: Human Kinetic Books 29 Young WB, Henry BDG. Agility and 1991:223. change-of-direction speed are independent skills: implications for training for agility in 23 Salaj S, Markovic G. Specificity of invasion sports. International Journal of Jumping, Sprinting, and Quick Change-of- Sports Science & Coaching 2014. Direction Motor Abilities. J Strength Cond Res 2011;25:1249-1255.

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506196-L-bw-vd Does Processed on: 17-11-2016 The effect of stress and recovery ‘ϐ‹‡Ž†Ǧ–‡•–’‡”ˆ‘”ƒ ‡ ‹ϐŽ‘‘”„ƒŽŽ

– ’‘”–•‡†ǤʹͲͳͷ —Ǣ͵͸ȋ͸ȌǣͶ͸ͲǦͷǤ †‘‹ǣͳͲǤͳͲͷͷȀ•ǦͲͲ͵ͶǦͳ͵ͻͺͷͺͳǤ 1,2 1,2 1

ǤǤǤ˜ƒ†‡”‘‡• ǡ†”ǤǤ”‹ 1 ǡ’”‘ˆǤ†”ǤǤ‹•• Š‡”2,3,

†”ǤǤǤ Ǥ —‹Œ‰‡ ǡ†”ǤǤǤ Ǥ ”‡ ‡ 1,2, ’”‘ˆǤ†”ǤǤǤǤǤ‡‹ 1 ‹˜‡”•‹–›‘ˆ ”‘‹‰‡ǡ ‹˜‡”•‹–›‡†‹ ƒŽ‡–‡” ”‘‹‰‡ǡ ‡–‡”ˆ‘” —ƒ‘˜‡‡– ‹‡ ‡•ǡ ”‘‹‰‡ǡŠ‡‡–Š‡”Žƒ†• 2  ƒœ‡‹˜‡”•‹–›‘ˆ’’Ž‹‡† ‹‡ ‡•ǡ  Š‘‘Ž‘ˆ’‘”–•–—†‹‡•ǡ ”‘‹‰‡ǡŠ‡‡–Š‡”Žƒ†• 3  ‘‘–„ƒŽŽŽ—„ ”‘‹‰‡ǡ ”‘‹‰‡ǡŠ‡‡–Š‡”Žƒ†•

506196-L-bw-vd Does Processed on: 17-11-2016 Chapter 3

Physical and psychosocial stress and recovery are important performance determinants. A holistic approach that monitors these performance determinants over a longer period of time is lacking. Therefore this study aims to investigate the effect of a player’s physical and psychosocial stress and recovery on field-test performance. In a prospective non- experimental cohort design 10 female Dutch floorball players were monitored over 6 months. To monitor physical and psychosocial stress and recovery, daily training-logs and three-weekly the Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) were filled out respectively. To determine field-test performance 6 Heart rate Interval Monitoring System (HIMS) and 4 Repeated Modified Agility T-test (RMAT) measurements were performed. Multilevel prediction models were applied to account for within-players and between-players field-test performance changes. The results show that more psychosocial stress and less psychosocial recovery over 3 to 6 weeks before –‡•–‹‰†‡ ”‡ƒ•‡ ’‡”ˆ‘”ƒ ‡ȋ’κͶǤͶͻȌǤ‘”‡’Š›•‹ ƒŽ•–”‡••‘˜‡”ͼ™‡‡•„‡ˆ‘”‡ –‡•–‹‰‹’”‘˜‡•’‡”ˆ‘”ƒ ‡ȋ’κͶǤͶͻȌǤ In conclusion, physical and psychosocial stress and recovery affect submaximal interval- based running performance and agility up to 6 weeks before testing. Therefore both physical and psychosocial stress and recovery should be monitored in daily routines to optimize performance.

Keywords: longitudinal study, monitoring, agility, submaximal interval-based running,

physical, psychosocial

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INTRODUCTION

Floorball players need to train 26 hard with sufficient recovery in order to meet the high physical demands of a match . Floorball matches are played indoors and contain

elements of both ice-hockey and field hockey. The match consists of three 28 periods of 20 minutes in which players’ perform 5 or 6 times for 60 to 90 seconds . The match demands are characterized by high-intensity efforts interspersed with recovery-

periods. Activities consist of movements such as sudden accelerations, decelerations, 26,28

twists, turns and changes of direction to anticipate to the ball and other players 26 . This requires well-developed aerobic and anaerobic energy systems and agility . To meet and optimize these physical characteristics an adequate balance between the

physical stress of training and recovery is needed. 12 Physical stress arises from stressors like training frequency and/or duration . However, players also experience

psychosocial stress from stressors like interactions 12,19,20 with other people or an imbalance

between expected and actual performance . Therefore both physical 20 and psychosocial stress and recovery play an important role in performance . 3

Previous research has evaluated the effects of physical and psychosocial

4,5,9,11stress and recovery on field-test performance in high training load or monitor studies

. A decreased field-test performance was shown in most training studies 8-10 as a result of a short period of increased physical stress in terms of training load . After this period of increased physical stress the players completed a taper period with a

reduction in training intensity and frequency, which 8-10 led to an increase in field-test performance due to a super-compensation effect . Monitor studies showed

conflicting results. A one-season monitor study showed improved field-test 4 performance after increased physical stress one week before testing . In contrast,

other monitoring studies found only a pre-season or no relation 14,24 between physical stress and field-test performance 1 to 3 weeks before testing . The contradictions in results may be related to the study design; aforementioned studies had a period of intensified training after which testing was done, whereas other studies monitored a regular training season. In a regular training season physical stress is periodized more smoothly to optimize performance. Monitor studies that evaluated the effects of psychosocial stress and recovery on field-test performance by means of the RESTQ-

Sport questionnaire all showed that more psychosocial stress 9 and less recovery 5,11 resulted in a decreased field-test performance one week and 2 months before testing. The field tests used in these studies mainly focused on aerobic endurance.

However, floorball match demands show 14 that agility is important, next to aerobic endurance. Findings of Gabbett et al. showed a decreased agility as a result of

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increased physical stress in rugby players. However, in most of the aforementioned studies agility-type field tests are not incorporated at all. Moreover, most studies focus on average group-wise performance change and therefore neglect between- player and within-player performance changes. So, to determine the effects of stress and recovery on field-test performance a holistic approach is warranted that includes the individual player’s physical and psychosocial stress and recovery. An individual player experiences both types of stress and recovery, and this may affect their performance. In measuring field-test performance the match demands of floorball should be met properly including both aerobic endurance and agility. Therefore the aim of this study is to investigate the effect of a player’s physical and psychosocial stress and recovery on field-test

performance. METHODS

Subjects

In this study 10 female Dutch floorball players (mean ± SD: age 24.8-1 ± 4.5-1 yr, body 2 mass 64.5 ± 4.9 kg, height 169.9 ± 6.3 cm, VO max 45.2 ± 2.8 Žή‹ ήkg ) participated during 6 months in preparation for the World Cup qualifications. These participants all played at the highest national level and were part of the Dutch national team. The floorball players trained on average 2 times a week and played 1 match a week with their own team. They trained with the Dutch national team one weekend every 6 weeks consisting of 2 training sessions a day and/or a practice

match. A sports physician screened all participants 2 to exclude cardiovascular risks, according to the Lausanne recommendations . The participants signed an informed consent after being fully informed about the study. This study is part of a larger study known as the Groningen Monitoring Athletic Performance Study (MAPS). Approval was granted by the medical ethical committee of the University Medical Center Groningen, the Netherlands conform the declaration of Helsinki and in accordance 16 with the ethical standards of the IJSM . Procedure

A prospective non-experimental cohort design was used to monitor stress, recovery and field-test performance. The study timeline is shown in figure 1. To monitor field- test performance over the course of the season two field tests were administered every 6 weeks. The participants performed both the Heart rate Interval Monitoring System (HIMS), a submaximal interval-based running test, and the Repeated Modified

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Agility T-test (RMAT), an intermittent agility test. These field-tests were 15,21,22 developed for

intermittent team sports and are characterized by an interval profile as well7,15,23 as validated against aerobic or anaerobic laboratory tests or match performance . During the preparation phase the HIMS and RMAT were performed 6 and 4 times respectively. The HIMS was performed twice within one week; once for familiarization and once to obtain baseline measurements. The RMAT was done once for familiarization. Participants were verbally encouraged to evoke maximal effort during the RMAT. During the preparation phase the participants were asked to fill out a daily training-log to measure physical stress and recovery. To assess the psychosocial

stress and recovery the participants completed the 25 Dutch version of the Recovery- Stress Questionnaire for Athletes (RESTQ-Sport) every 3 weeks, referring to their stress and recovery activities in the preceding 3 weeks (figure 1). submax To determine submaximal heart rate (HR ) for the HIMS the maximal max heart rate (HR ) had to be determined. Therefore at the start of the monitoring 3

period a maximal test was done on a treadmill (Valiant, Lode B.V., Groningen, The

17,18Netherlands) using a ramp protocol that was adapted for-1 indoor team sport players

. The-1 participants sta”–‡†ƒ–ƒ•Ž‘’‡‘ˆʹΨƒ–ͺήŠ increasing speed-1 with 0.8 ήŠ per minute, after a warm-—’’‡”‹‘†‘ˆͷ‹—–‡•—–‹ŽͳͺήŠ . Thereafter, the slope increased with 1% a minute. The test was stopped at voluntarily exhaustion of the participant. A breath-by-breath gas analyzer (Cortex Metalyzer 3B, Procare B.V. max Groningen, The Netherlands) was used for the metabolic measurements. HR was determined as the highest HR during the test.

o Figure 1. The longitudinal study design. p=practice session, b=baseline measurement, x=measurement moment, =asking back period.

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Stress and recovery

The training-log consisted 20 of daily recording of the Total Quality of Recovery (TQR) on a scale from 6-20 before each training and match. After every training or match

participants recorded the duration in minutes as well as the session Rating of

Perceived13,20 Exertion (RPE) score on the original 15-point Borg scale ranging from 6-20 . To calculate the load, the session RPE was multiplied by the duration of the training or match as proposed by Foster (1998). The weekly load and duration were calculated as the sum over a week period. For session RPE and TQR the average over

the week was calculated. When 25% or less of a week 4 was missing of the TQR scores, these scores were replaced with the week average . Next to week sums or averages, also the averages over 3 and 6 weeks before the performance tests were calculated. The RESTQ-Sport consists of 77 items, which are rated on a Likert-type scale

from 0: never to 6: always (Figure 2), scoring the frequency of 19 participating in various stress and recovery related activities during the last 3 weeks . The items can be divided into 12 general and 7 sport-specific scales, with 4 questions for each scale and 1 warm-up question (Figure 2). Scores of the RESTQ-Sport were classified in a general stress (GS) score, sport-specific stress (SS) score, general recovery (GR) score and

sport-specific recovery (SR) score; each score was 19 calculated by taking the average of the subscales associated with the specific score . These scores were also calculated for 6 weeks before field-test performance taking the average of the scores of the 2 RESTQ-Sport questionnaires filled out 3 and 6 weeks before testing. The Dutch

version of the RESTQ-Sport 25 shows sufficient reliability and validity for sports practice and science purposes .

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3

Figure 2. Example questions RESTQ-Sport of the 194 main scores: General Stress (GS), Sport Stress (SS), General Recovery (GR) and Sport Recovery (SR) .

‹‡Ž† -test performance

21 The HIMS protocol was performed as described by Lamberts et al. . The protocol

consists of four 2-minute stages of running between 2 lines 20m-1 apart, each stage was

ˆ‘ŽŽ‘™‡†„›ͳ‹—–‡‘ˆ”‡•–Ǥ–ƒ”–‹‰•’‡‡†™ƒ••‡–ƒ–͹Ǥʹή-1 Š and intensity

‹ ”‡ƒ•‡†‘˜‡”–Š‡•–ƒ‰‡•„›ͳǤʹήŠ2 each stage. During the HIMS HR was

monitored (Polar Team , Kempele,th Finland). Field-test performance is defined as the submax max HR at the end -1of the 4 stage, expressed as a percentage of the HR and in

ƒ„•‘Ž—–‡„‡ƒ–•ή‹ . Besides, absoluteth and relative heart rate recovery (HRR and submax HRR%) in the first minute after the 4 stage was determined. Both HR and HRR 21

were calculated as an average over the final 15 seconds of the concerning period th. submax For the lowest day-to-day variation in HR 22 and HRR the HR at the end of the 4 max stage should be between 86-93% of the HR . The participants were allocated to submax either the same,th a slower or faster starting speed depending 22 on their HR at the

end of the 4 stage after the baseline measurements . 15 The RMAT was performed as described by Haj-Sassi et al. (Figure 3). The participants started at the line 55 cm before A (Figure 3) at which the first electronic

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timing gate (TAG Heuer, Marinn, Swiss) was placed. Sensors were mounted on tripods and placed 1.35m above the ground (approximately at shoulder height). After a 3 to 1 countdown the participants ran towards B, shuffled left or right to either C or D, shuffled further to the other side and back to B from which they ran backwards back to A. Participants performed this course 10 times, starting every 30 seconds and were instructed not to cross their feet while shuffling and touch the tape at each mark with

their feet. Field-test performance was determined as15 peak time (PT) and total time (TT). Both variables proved reliability and validity .

15 Figure 3. Repeated Modified Agility T-test (RMAT) modified from Haj-Sassi et al. .

Data analysis

The HIMS and RMAT were completed by 10 and 9 floorball players, respectively. The goalkeeper did not perform the RMAT due to the specific match demands of the goalkeeper. After exclusion of the familiarization and baseline trials 4 HIMS and 3 RMAT measurements remained for the analysis (Figure 1). Means and standard MLwiN deviations were computed for all variables using IBM SPSS Statistics 20 for Windows. The data was analyzed using the Version 2.23 software package. Multi-level modeling allows for repeated measures with missing data, which is inevitable in this longitudinal design, assuming that these are random. Multi-level modeling was

developed to analyze nested data and 3 takes into account the relations within (player’s development) and between players . For the field-test performance parameters of the submax HIMS (HR and HRR) and RMAT (PT and TT), 4 random intercept 2-level models were created. In these 2-level models level 1 represented the measurement occasions

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within individual players and level 2 represented the differences between players. Hereafter predicting variables for physical stress and recovery were added to all four 2-level models. The predicting variables were added one-by-one to quantify the effect of that particular variable on the field-test performance change. The predictive model was evaluated by comparing the -2 Log likelihoods (deviance) of the empty model p (without predicting variables) to the model including predicting variables. The level of statistical significance was set at ζͲǤͲͷǤ RESULTS

During 25 weeks, data of 753 training sessions and matches were collected. The players completed on average 3 training sessions/matches every week. A total of 77 RESTQ-Sport questionnaires were filled out. Descriptive data of HIMS and RMAT field- test performance, training duration, session-RPE, weekload, TQR and RESTQ-Sport are reported in table1. 3

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Duration

sum of 1 week (min) 228.03 ± 229.16 average 3 week (min) 282.46 ± 150.09 RPE average 6 week (min) 266.35 ± 107.39

average 1 week (6-20) 14.63 ± 1.72 average 3 week (6-20) 14.50 ± 1.60 Weekload average 6 week (6-20) 14.36 ± 1.36 (Duration*RPE)

1 week (AU) 3493.95 ± 4854.72 average 3 week (AU) 4308.71 ± 2429.13 TQR average 6 week (AU) 4022.70 ± 1712.45

average 1 week (6-20) 14.39 ± 1.48 average 3 week (6-20) 14.50 ± 1.32 RESTQ-Sport average 6 week(6-20) 14.26 ± 2.65

GS 3 wk (0-6) 1.76 ± 0.69 GS 6 wk (0-6) 1.70 ± 0.59 SS 3 wk (0-6) 1.04 ± 0.57 SS 6 wk (0-6) 1.00 ± 0.52 GR 3 wk (0-6) 3.12 ± 0.74 GR 6 wk (0-6) 3.15 ± 0.62 SR 3 wk (0-6) 2.63 ± 0.79 HIMS SR 6 wk (0-6) 2.57 ± 0.64

Submaximal Heart rate (%) 92.18 ± 3.84 -1 —„ƒš‹ƒŽ ‡ƒ”–”ƒ–‡ȋ„‡ƒ–•ή‹ ) 185.19 ± 11.69 Heart rate Recovery (%) 24.91 ± 6.56 -1 RMAT ‡ƒ”–”ƒ–‡‡ ‘˜‡”›ȋ„‡ƒ–•ή‹ ) 45.76 ± 10.62

Peak Time (sec) 6.40 ± 0.25

Total Time (sec) 66.06 ± 2.61

Table 1. Physical and psychosocial stress and recovery and field test performance in Dutch female Floorball players. Scores are represented as mean ± SD for the Heart rate Interval Monitoring System (HIMS), Repeated Modified Agility Ttest (RMAT), Duration, Rating of Perceived Exertion (RPE), Weekload, Total Quality of Recovery (TQR) and RESTQ-Sport General Stress (GS), Sport Stress(SS), General Recovery (GR), Sport Recovery (SR).

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p

HIMS performance prediction improves significantly ( <0.01) using 2-level models compared to a 1-level model. In this 2-level model, level 1 represents measurement occasion within individual players and level 2 represents differences between players. The 2-level model is stronger in comparison to the 1-level model, which just analyzes the differences between players. In other words individual field- test performance development over time differs between players. For RMAT performance the 2-level models did not improve the prediction of RMAT performance

indicating no differences between individuals in agility development over time. HIMS

submax In Table 2 the results for the 2-level models predicting HR and HRR on the HIMS are shown. Physical stress and recovery show to have no effect on the prediction of HIMS performance. More psychosocial stress 3 weeks before field-test performance in submax terms of GS and SS predicts an increase of HR by 1.81% and 2.50% respectively. submax p Increased GR and SR predicts a decrease in HR by 2.73% and 1.37% for every 3 point on the Likert-scale on average over the score ( ζͲǤͲͳȌ„‘–Šˆ”‘͵–‘͸™‡‡• before field-test performance. In line, over the total 6 weeks before field-test p submax performance more GS and GR predict an increase and a decrease in HR by 1.83% p and 2.43% respectively-1 ( ζͲǤͲͷȌǤ ‘” ǡ‹ ”‡ƒ•‡† ’”‡†‹ –•ƒ‹’”‘˜‡‡–‘ˆ ͹ǤͷͲ„‡ƒ–•ή‹ for every point on the Likert-scale for mean GR ( ζͲǤͲͷȌˆ”‘͵–‘͸

weeks before field-test performance. RMAT

Table 3 shows the results for the 2-level models predicting RMAT performance in p both PT and TT. More physical stress in terms of duration (min) and weekload (AU) predicts faster PT and TT on the RMAT ( ζͲǤͲͷȌ͸™‡‡•’”‹‘”–‘’‡”ˆ‘”ƒ ‡ testing. One hour of training or match play predicts a 0.08 (60*0.0013) and 0.96 (60*0.016) seconds faster PT and TT respectively. Psychosocial stress and recovery show to have no effect on RMAT performance prediction.

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DISCUSSION

This study evaluates the effect of a player’s physical and psychosocial stress and recovery on field-test performance. The first key findings of this study are that submaximal interval-based running (HIMS) performance decreases with more psychosocial stress and less psychosocial recovery in 3 to 6 weeks before performance testing. Second, agility improves after increased physical stress over 6 weeks before performance testing. Our results show that both general and sport specific psychosocial stress and recovery affect HIMS performance. More GS and less GR over the last 6 weeks decreased submaximal performance, while over the last 3 weeks more SS and less SR decreased submaximal performance. This is in line with previous research that

showed an increase in the GS subscales 9,11 and a decrease in GR subscales over 3 days before a decrease in performance . Also the study of Brink et al. showed an increase

in GS and decrease 5 in GR subscales 2 months before decreased submaximal performance . These results indicate that general stress and recovery have a more long-term effect on performance, while sport stress and recovery seem to affect performance in short term. The general stress and recovery scales refer back to conflicts, pressure and successes in daily life. These factors can play a role for a longer period of time. The sport specific stress and recovery scales refer back to physical fitness, injuries and self-regulation during training and matches, these factors might be more dominant on the short term. This supports the importance of monitoring

both general and sport specific psychosocial stress and recovery over the course of a season to be able to respond in time. The effect of psychosocial stress and recovery on HIMS performance is supported by the fact that changes in psychosocial stress and recovery seem to elicit submax meaningful changes -1in HIMS performance. The day-to-day variation-1 in HR and

‹•άʹ„‡ƒ–•ή‹ ȋ‹Ǥ‡Ǥ̱ͳΨ‘ˆƒš‹— Ȍƒ†ά͵„‡ƒ–•ή‹ (i.e. 22 ~5.5% of submax submax HR ) respectively when HR is between 86%-93% at stage 4 . Our players submax submax average HR is 92.18% (table 1) and the changes in both HR and HRR (Table 2) exceed the day-to-day variation. So for example a 1-point increase on a scale from 0 submax to 6 (never – always) in SS over 3 weeks elicits an increase in HR of 2.5% (Table 2). Therefore, a meaningful change of 1% corresponds with an increase in SS of 1% / 2.5% = 0.4. Because the SS scale consists of 12 questions a 1-point increase on (0.4*12=) 5 out of 12 questions is necessary to elicit the required increase of 0.4.

Likewise for HRR-1 an increase of 1 unit on GR over 3 weeks elicits-1 an increase in HRR ‘ˆ͹Ǥͷ„‡ƒ–•ή‹ ȋƒ„Ž‡ʹȌǤ‡ƒ‹‰ˆ—Ž Šƒ‰‡‘ˆ͵„‡ƒ–•ή‹ corresponds with an increase in GR of 3 / 7.5 = 0.4, meaning a 1-point increase on (0.4*20=) 8 out of 20

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questions. These magnitudes of change are realistic, considering the variation in scoring on the RESTQ (Table 1), so changes in psychosocial stress and recovery will submax elicit a meaningful change in HR and HRR on the HIMS. In contrast to psychosocial stress and recovery, physical stress and recovery does not affect HIMS performance. The sensitivity of the TQR, to measure physical

recovery, has not been investigated yet. Similar to our study, physical recovery 4 showed no contribution to field-test performance in the study of Brink et al. . However an advantage of both the RPE and TQR is that they measure perceived physical stress and recovery. Therefore it is assumed that the players take their own capacity into account in the scoring. Nonetheless, a suggestion for future research may be to change the timing of scoring TQR. Players indicated that they rate their recovery more accurately during the warm-up because they are more aware of soreness, while TQR is scored before the warm-up. By filling out the TQR after the warm-up the sensitivity may be improved and may give a clarification of performance change by physical recovery to guide training. 3 More physical stress in terms of training duration and weekload over a 6- week period improves agility indicated by faster times on the RMAT. In literature contrasting results are found in which physical stress both increases and decreases agility. The time in the season and also type of sport may explain these contrasts. In

pre-season an improvement in agility is shown with high levels of stress, while no

change6,14,27 or decrement in agility is shown in early competition and during the season

. It is also known that 6,27 match-related training and match play are important in the

improvement of agility . When looking at type 6,14,27 of sport, improved agility was shown in soccer while decrement was shown in rugby . In soccer, just as in floorball, agility may be a more important match demand in comparison to rugby. In soccer

anaerobic 6 speed training and small-sided games are important components in

training . While in rugby training the emphasis 14 is on the aerobic conditioning, spending less time on agility type training . Based on these studies it would be expected that in our sub-elite floorball players increased sport-specific training would lead to an increase in agility, which is confirmed by our results. Furthermore physical stress appears to elicit meaningful changes in agility.

The smallest worthwhile change 15 is stated to be approximately 0.06 sec for PT and 0.65 sec for TT on the RMAT . In our players agility increases 0.08 sec and 0.96 sec for PT and TT respectively, for each hour of training or match play per week on average over 6 week before testing. So, training duration elicits a meaningful change in agility measured with the RMAT. In this study psychosocial stress and recovery did not affect agility and

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physical stress and recovery had no effect on submaximal interval-based running. Our study was executed during the preparation phase for the World Cup qualifications, which was at the end of their regular season with their own team. Therefore the aerobic capacity of the players was probably at their limit at this time. So, it might be that in this phase physical stress doesn’t affect submaximal interval-based running submax measured by HR and 1 HRR. Besides, only modest changes are shown in aerobic endurance with training . Psychosocial stress and recovery still might influence HR during submaximal interval-based running because psychosocial stress and recovery can change on a day-to-day basis. Physical stress might affect agility due to the high intensity of the training sessions with the national team in comparison to their home team. On the other hand, it can be speculated whether psychosocial stress and recovery affect short explosive agility type of movements. This pioneering study has investigated the effect of physical and psychosocial stress and recovery on both submaximal interval-based running performance and agility. We were able to monitor players of the Dutch national floorball team over a unique 6-month period in preparation to the World Cup. In order to take within- player and between-player differences into account we used an individual approach. The frequency of monitoring psychosocial stress and recovery and field-test performance may be a limitation. Psychosocial stress and recovery can change on a day-to-day basis, so monitoring more often may give better insight in these changes and therefore better training guidance. However when monitoring over an entire season caution is needed to warrant the compliance of the players. Future research should take this into account. This study shows that more psychosocial stress and less psychosocial recovery decreases submaximal interval-based running performance, while more physical stress in terms of training load improves agility both up to 6 weeks before performance testing. This indicates the importance of monitoring stress and recovery throughout the entire season to guide the training program and with that facilitate

successful performances. PRACTICAL APPLICATIONS

Monitoring player’s physical and psychosocial stress and recovery must be incorporated into the daily routine of players, considering the effect on test performance even up to 6 weeks before testing depending on the field-test characteristics. The findings of current study implicate that to optimize aerobic performance more attention should be paid to daily life stressors like work and school and to recovery methods such as social life events on the long term. While on the

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short term more attention should be paid to physical fitness like muscle pain and to recovery methods like self-regulation and giving positive appraisal during training. Besides, changes in agility seem to be dominated by changes in sport-specific training and match play (physical stress). So, coaches can plan specific periods during the season in which agility can be optimized, by increasing physical stress. ACKNOWLEDGEMENTS

The authors would like to thank the players and Jorg Andree, coach of the Dutch female national floorball team for their participation and commitment. We would also like to thank Susan Kok and Janet Toonder for their assistance in data collection. This

study was funded by SIA RAAK-PRO (PRO-2-018).

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REFERENCES

during deliberate overreaching and tapering in rugby league players. Int J 1 Bacon AP, Carter RE, Ogle EA, et al. Sports Med 2007;28:116-124. VO2max trainability and high intensity interval training in humans: a meta- 9 Coutts AJ, Reaburn P. Monitoring changes analysis. PLoS One 2013;8:e73182. in rugby league players' perceived stress and recovery during intensified training. 2 Bille K, Figueiras D, Schamasch P, et al. Percept Mot Skills 2008;106:904-916. Sudden cardiac death in athletes: the Lausanne Recommendations. Eur J 10 Coutts AJ, Reaburn P, Piva TJ, et al. Cardiovasc Prev Rehabil 2006;13:859-875. Monitoring for overreaching in rugby league players. Eur J Appl Physiol 3 Bosker RJ, Snijders TAB. Multilevel 2007;99:313-324. Analysis. An Introduction To Basic And Advanced Multilevel Modeling. : Sage 11 Faude O, Kellmann M, Ammann T, et al. Publications Ltd. 1999. Seasonal changes in stress indicators in high level football. Int J Sports Med 4 Brink MS, Nederhof E, Visscher C, et al. 2011;32:259-265. Monitoring load, recovery, and performance in young elite soccer players. 12 Fletcher D, Hanton S, Mellalieu SD, et al. J Strength Cond Res 2010;24:597-603. A conceptual framework of organizational stressors in sport performers. Scand J Med 5 Brink MS, Visscher C, Coutts AJ, et al. Sci Sports 2012;22:545-557. Changes in perceived stress and recovery in overreached young elite soccer players. 13 Foster C. Monitoring training in athletes Scand J Med Sci Sports 2012;22:285-292. with reference to overtraining syndrome. Med Sci Sports Exerc 1998;30:1164-1168. 6 Caldwell BP, Peters DM. Seasonal variation in physiological fitness of a 14 Gabbett TJ, Domrow N. Relationships semiprofessional soccer team. J Strength between training load, injury, and fitness Cond Res 2009;23:1370-1377. in sub-elite collision sport athletes. J Sports Sci 2007;25:1507-1519. 7 Castagna C, Manzi V, Impellizzeri F, et al. Relationship between endurance field tests 15 Haj-Sassi R, Dardouri W, Gharbi Z, et al. and match performance in young soccer Reliability and validity of a new repeated players. J Strength Cond Res agility test as a measure of anaerobic and 2010;24:3227-3233. explosive power. J Strength Cond Res 2011;25:472-480. 8 Coutts A, Reaburn P, Piva TJ, et al. Changes in selected biochemical, muscular 16 Harriss DJ, Atkinson G. Ethical strength, power, and endurance measures standards in sport and exercise science

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research: 2014 update. Int J Sports Med 23 Lemmink KA, Visscher SH. Role of 2013;34:1025-1028. energy systems in two intermittent field tests in women field hockey players. J 17 Hinrichs T, Franke J, Voss S, et al. Total Strength Cond Res 2006;20:682-688. hemoglobin mass, iron status, and endurance capacity in elite field hockey 24 Meister S, Faude O, Ammann T, et al. players. J Strength Cond Res 2010;24:629- Indicators for high physical strain and 638. overload in elite football players. Scand J Med Sci Sports 2013;23:156-163. 18 Howley ET, Bassett DR,Jr, Welch HG. Criteria for maximal oxygen uptake: 25 Nederhof E, Brink MS, Lemmink KAPM. review and commentary. Med Sci Sports Reliability and validity of the Dutch Exerc 1995;27:1292-1301. Recovery Stress Questionnaire for athletes. International Journal of Sport Psychology 19 Kellmann M, Kallus KW. Recovery- 2008;39:301-311. stress questionnaire for athletes: User 3 manual. Champaign, IL: Human Kinetics 26 Pasanen K, Parkkari J, Pasanen M, et al. 2001. Effect of a neuromuscular warm-up programme on muscle power, balance, 20 Kentta G, Hassmen P. Overtraining and speed and agility: a randomised controlled recovery. A conceptual model. Sports Med study. Br J Sports Med 2009;43:1073-1078. 1998;26:1-16. 27 Silva JR, Magalhaes JF, Ascensao AA, et 21 Lamberts RP, Lemmink KA, Durandt JJ, al. Individual match playing time during et al. Variation in heart rate during the season affects fitness-related submaximal exercise: implications for parameters of male professional soccer monitoring training. J Strength Cond Res players. J Strength Cond Res 2004;18:641-645. 2011;25:2729-2739.

22 Lamberts RP, Maskell S, Borresen J, et 28 Wikstrom J, Andersson C. A prospective al. Adapting workload improves the study of injuries in licensed floorball measurement of heart rate recovery. Int J players. Scand J Med Sci Sports 1997;7:38- Sports Med 2011;32:698-702. 42.

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506196-L-bw-vd Does Processed on: 17-11-2016 Œ—”›”‹•‹•‹ ”‡ƒ•‡†„› Šƒ‰‡• in perceived recovery of team sport players

Ž‹ ’‘”–‡†ǤʹͲͳ͸ƒ”͵Ǥȏ’—„ƒŠ‡ƒ†‘ˆ’”‹–Ȑ 1,2 1,2 1,2

ǤǤǤ˜ƒ†‡”‘‡•ǡ ǡ”ǤǤǤ”‹1 ǡǤǤǤ––‡”ǡ  1,2, ”‘ˆ”ǤǤ‹•• Š‡” ǡ”‘ˆǤ”ǤǤǤǤǤ‡‹ 1 ‹˜‡”•‹–›‘ˆ ”‘‹‰‡ǡ ‹˜‡”•‹–›‡†‹ ƒŽ‡–‡” ”‘‹‰‡ǡ ‡–‡”ˆ‘” —ƒ‘˜‡‡– ‹‡ ‡•ǡ ”‘‹‰‡ǡŠ‡‡–Š‡”Žƒ†• 2  ƒœ‡‹˜‡”•‹–›‘ˆ’’Ž‹‡† ‹‡ ‡•ǡ  Š‘‘Ž‘ˆ’‘”–•–—†‹‡•ǡ ”‘‹‰‡ǡŠ‡‡–Š‡”Žƒ†•

506196-L-bw-vd Does Processed on: 17-11-2016 Chapter 4

The aim of this study is to investigate if changes in perceived stress and recovery over the course of a season are a risk factor for acute and overuse injuries. A prospective non- experimental cohort design was in used in which 86 male and female basketball, volleyball and korfball players participated aged 21.9 ± 3.5 years. In this 10-month ‘„•‡”˜ƒ–‹‘ƒŽ•–—†›–Š‡†ƒ–ƒ™ƒ•‰ƒ–Š‡”‡†ƒ––Š‡’‘”–• ‹‡Ž†ƒ„ ”‘‹‰‡ƒ†ƒ––Š‡ facilities of the participating teams. The Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) was filled out every three weeks throughout the season to assess changes in perceived stress and recovery. Acute and overuse injuries were registered by the teams’ physical therapist. ORs and 95% CI’s were calculated. During one season 66 acute and 62 overuse injuries were registered. Multinomial regression analysis showed that ’‡” ‡‹˜‡† ‡‡”ƒŽ‡ ‘˜‡”›ǡ•Š‘™‹–Š‡• ƒŽ‡•‘ ‹ƒŽ‡ ‘˜‡”›ƒ† ‡‡”ƒŽ‡ŽŽ-Being, decreased in the 6-week period before an acute injury (OR 0.59 and 0.61 respectively, p κͶǤͶͻȌ ‘’ƒ”‡†–‘Š‡ƒŽ–Š›’‡”‹‘†•Ǥ‹•‘ˆ‘˜‡”—•‡‹Œ—”‹‡•‹ ”‡ƒ•‡†™Š‡’‡” ‡‹˜‡† Sport Recovery, shown in the Personal Accomplishment scale, decreased in the 3-week ’‡”‹‘†„‡ˆ‘”‡–Š‡‹Œ—”›ȋͶǤͻͿǡ’κͶǤͶͻȌ ‘’ƒ”‡†–‘Š‡ƒŽ–Š›’‡”‹‘†•ǤŠerefore †‡ ”‡ƒ•‡†’‡” ‡‹˜‡†”‡ ‘˜‡”› ƒ‹†‹ ƒ–‡ƒ‹ ”‡ƒ•‡†‹Œ—”›”‹•Ǥ ‡‡”ƒŽ‡ ‘˜‡”› affects acute injury risk and Sport Recovery affects the risk of an overuse injury. Monitoring perceived recovery over the course of a season could give guidance for recovery enhancing practices to prevent injuries.

Keywords: RESTQ-Sport, acute injury, overuse injury, psychosocial stress and recovery

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INTRODUCTION

It is suggested that psychological factors such as personality characteristics, 22 history of stressors and coping resources can influence injury occurrence . For example, a player with a high trait anxiety who has experienced a recent life event and has poor

coping resources will be more likely to perceive a sport specific situation as 22 stressful. This may result in greater muscle tension and narrowing of the visual field . In team

sports this may cause players to be unable to avoid an opponent quickly 1 or see the opponent in time resulting in a higher risk to sustain an acute injury . This highlights the importance of exploring the role of psychological factors in relation to acute injuries.

Empirical research supports the 10,12,14,16 relation between these psychological factors on injury risk especially acute injuries . In these studies potential psychological

risk factors 8,13,14 were measured at 10 the start of a season with injury follow-up ranging from

3 months up to 2 years . Personality characteristics, history of stressors and coping resources explained 7% up to 24% of the variance in injury occurrence 10,12,14,15 . A more regular monitoring may increase this explained variance since stress levels can change on a day-to-day basis. Previous studies either measured potential

psychological risk factors at the start 12-14 of the season or monitored daily stressors on a weekly basis over a 13-week period . Higher baseline levels in perceived stress as 4

well as a smaller decrease in perceived 13 stress over this period was shown in injured players compared to healthy players . Monitoring perceived stress more regularly over a longer duration, e.g. an entire season, may provide more insight in the

individual changes in stress in relation to 1 acute injury occurrence.

The model 10,12,14,15 of Andersen & Williams and most studies up until now focused on

acute injuries 20,23 , whereas overuse injuries also account for about 14% of the

total injuries and are most predominant 6 in sports involving repetition of

movement 19 patterns like jumping . Based on the theoretical framework of Kenttä and Hassmén it can be assumed that a balance between stress and recovery is also

important in reducing overuse 1 injury risk. It is suggested that stress can result in a

greater muscle tension , while a continuous greater muscle tension reduces 3 the recovery potential and can in turn increase the risk of overuse injuries . Studies differentiating between acute and overuse injuries in relation to perceived stress and

recovery are limited and found no difference 4in changes in perceived stress or

recovery between acute and overuse 18 injuries . This may be due to the monthly administering of the RESTQ-Sport while changes may occur more rapidly. Monitoring changes in perceived stress and recovery more frequently over the course of a season may provide insight in relation to overuse injury occurrence.

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10,12,14,15 Aforementioned studies mainly focused on stressors , more recent

insights show4,5,13,17 the importance of recovery in counterbalancing stress for preventing

injuries . Before an injury players showed less recovery at baseline 4,13 but also a greater decrease in recovery over time in comparison to healthy players . This implies that monitoring recovery in relation to injury occurrence should be included. The Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) is a state oriented

questionnaire and 18 developed to show changes in perceptions of stress and recovery of players over time . This questionnaire is a reliable and valid tool to monitor changes

in both general and 18sport-specific stress and recovery over a period ranging from 3 days up to 4 weeks . Regular monitoring with the RESTQ-Sport may provide insight in the changes in perceived stress and recovery over the course of a season. An increase in stress and/or decrease in recovery can warn for players who are at-risk and proper prevention strategies can be implemented. Up until now research focusing on the role of psychological factors in injury occurrence show limited information about overuse injuries and information about recovery is lacking. The aim of this study is to investigate whether changes in perceived stress and recovery over the course of a season are a risk factor for acute and overuse injuries in team sport players. It is hypothesized that team sport players show an increase in perceived stress and a decrease in perceived recovery before sustaining an injury. Differences between acute and overuse injuries are expected giving the specific mechanisms. METHOD

Subjects

A prospective non-experimental cohort design was used to investigate changes in perceived stress and recovery in relation to injuries. In this study 58 male (mean ± SD: age 22.1 ± 3.8 yr, body mass 89.3 ± 10.9 kg, length 194.0 ± 7.8 cm) and 28 female (mean ± SD: age 21.5 ± 2.5 yr, body mass 71.8 ± 10.9 kg, length 178.1 ± 8.1 cm) indoor team sport players participated. The participants played basketball (26), volleyball (38), or korfball (22) on elite or sub-elite level. Korfball is a mixed-gender team sport

with 8 players on a team: 23 4 males and 4 females. The game has similarities with basketball and netball . Sub-elite level was defined as playing competition at regional level, while elite level players compete at a national or international level. All participants were fully informed about the study after which they signed an informed consent. Institutional approval was received from the medical ethical committee of the University Medical Center Groningen, the Netherlands. This study is part of a

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larger study known as the Groningen Monitoring Athletic Performance Study (Groningen MAPS). ”‘ ‡†—”‡•

‡” ‡‹˜‡†•–”‡••ƒ†”‡ ‘˜‡”›

From the onset of the season 18,21 the players filled out the Dutch version of the RESTQ- 21 Sport every three weeks , which showed sufficient reliability and validity . The

RESTQ-Sport measures the 18 frequency of current stress together with the frequency of recovery-related activities . In this study a period of three weeks was chosen over which this frequency is measured in accordance with the periodization cycle of the

players. 18 The reliability of the RESTQ-Sport was supported for a recall period up to 4 weeks . The questionnaire consists of 77 items, including 1 warm-up question, referring to stress and recovery related activities during the previous 3 weeks. These items are scored on a Likert-type scale ranging from 0 (never) to 6 (always). The items can be divided into 19 scales; 12 general scales and 7 sport-specific scales. Each

scale stconsists of 4 items. A more detailed description 18 of the 19 scales can be found in the 1 chapter of the RESTQ-Sport manual . These scales can be subdivided into 4 main scores for General Stress (GS), Sport Stress (SS), General Recovery (GR), and Sport Recovery (SR). The main scores were calculated by taking the average of the 4 18 scales . Œ—”›”‡‰‹•–”ƒ–‹‘

‡–ƒŽǤ All injuries during the season were recorded by the team’s physical therapist. 9 The data collection system was based on the recommendations of Fuller . They defined an injury as “any physical complaint sustained by a player that results from a

match or training, 9 irrespective of the need for medical attention or time loss from sport activities” . In this study the medical attention injuries were registered by the physical therapist and classified as acute or overuse injuries. An acute injury was defined as “an injury resulting from a specific, identifiable event”. The definition for an

overuse injury was “an injury caused by repeated 9 micro-trauma without a single, identifiable event responsible for the injury” . The acute and overuse medical attention injuries were used for analysis in this study. ƒ–ƒƒƒŽ›•‹•

Out of the 86 team sport players participating in this study 67 players were included in the 2011-2012 season and an additional 19 players were included in the 2012- 2013 season. Players were monitored for a period of 41 weeks. Out of the 933

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possible RESTQ-Sport questionnaires 97 (10.4%) were missing. Despite our efforts to help the players remember to fill out the questionnaires, the missing data was probably primarily due to players who refused or forgot to fill out the questionnaire. This left a total of 836 (89.6%) RESTQ’s for further analysis. The period between two RESTQ’s was marked as ‘healthy’ or ‘before the injury’, according to the injury registration of the physical therapist. Players were injured in a total of 185 RESTQ- periods. These periods were excluded from data-analysis (22.1%), leaving 651 RESTQ’s for final data analysis. Each RESTQ refers to the previous 3-week period. An example is presented in Figure 1. For example, the player became injured in the period between RESTQ 7 and 8. The period before RESTQ 7 is the healthy period right before becoming injured and therefore marked as ‘before the injury’. The periods before RESTQ 4,5, and 6 are marked ‘healthy’. RESTQ 8 and 9 were excluded from the ' analysis. The change scores in perceived stress and recovery for ‘healthy’ and ‘before ' ' injury’ periods were calculated over 2 RESTQ’s administered 3 weeks ( RESTQ3wk) ' 5 and 6 weeks apart ( RESTQ6wk) (Figure 1). For the entire season RESTQ3wk and RESTQ6wk were related to ‘healthy’ or ‘before injury’ periods. These calculations were done for the 19 separate RESTQ-Sport scales.

Figure 1. Example for one player. H=healthy, B=before injury, I=injured. The 3-week periods refer to the period over which the perceived stress and recovery is measured with the RESTQ-Sport.

Statistical analysis

' ' Means and standard deviations were computed for the 4 main scores and 19 scales of the RESTQ-Sport over RESTQ3wk and RESTQ6wk. Data were analyzed using multinomial regression. The dependent variable was the marked period in which ‘healthy’ was set as reference category. Odds ratios (OR) and 95% confidence

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' '

intervals (95%CIs) over RESTQ3wk and RESTQ6wk were calculated for the ‘before ' ' injury’ periods in comparison to the ‘healthy’ periods. Regression models were made separately for acute injuries and overuse injuries with RESTQ3wk and RESTQ6wk p as independent measure. IBM SPSS Statistics 20 for Windows was used for all data analysis. The level of statistical significance was set at ζͲǤͲͷǤ RESULTS

During the 41-week monitoring period 68 players (79%) sustained a total of 128 injuries of which 66 (52%) were acute injuries and 62 (48%) were overuse injuries. The descriptive data of the absolute main scores on the RESTQ-Sport before an injury for players with an acute or overuse injury and healthy players are shown in Table 1. p t No significant differences were found between these groups on the absolute main ' RESTQ scores ( 0.05). The change scores of the 19 RESTQ-Sport scales were on ' average (range) 0.01 (-4.75 - 4.25) over RESTQ3wk for healthy periods, -0.03 (-2.75 ' - 2.75) over RESTQ3wk for before an acute injury, and -0.07 (-2.75 - 2.25) before an overuse injury. Over RESTQ6wk the change scores of the scales were on average (range) -0.02 (-4.75 - 4.5) for healthy periods, -0.03 (-2.5-3) for periods before an acute injury, and -0.07 (-2 - 2) before an overuse injury. 4

Table 1. Descriptives (meanN ± SD) of theGS absolute main scoresSS on the RESTQ-Sport GRof healthy periods and SR periods before an acute or overuse injury.

healthy 559 1.76 ± 0.61 1.72 ± 0.70 3.33 ± 0.72 2.91 ± 0.76 before injury – acute 43 1.60 ± 0.65 1.50 ± 0.59 3.25 ± 0.68 2.86 ± 0.77 before injury - overuse 49 1.59 ± 0.53 1.65 ± 0.67 3.40 ± 0.68 3.00 ± 0.69

N; represents the number of RESTQ’s included to calculate the average over the main score; GS= General Stress; SS= Sport Stress; GR= General Recovery; SR= Sport Recovery.

The results for the multinomial logistic regression analysis for both acute and ' overuse injuries are shown in Table 2. No significant results were found for all main scores of the RESTQ. In RESTQ3wk no differences were shown before sustaining an Social Recovery ‡‡”ƒŽ‡ŽŽ-Being Disturbed Breaks ' acute injury in comparison to the healthy periods. However, a decrease on the scales , and over RESTQ6wk increased

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p ' the risk for acute injuries (OR=0.59, 0.61, 0.55, respectively, ζͲǤͲͷȌǤŠ‡ RESTQ6wk of the 19 RESTQ-Sport scales of periods before sustaining an acute injury Personal Accomplishment in comparison to healthy periods are illustrated in Figure 2. When looking at overuse ' p injuries a decrease in perceived (-1.75 – 1) over ' RESTQ3wk increased the risk to sustain an overuse injury (OR= 0.59, ζͲǤͲͷȌǤ‘ changes over RESTQ6wk were shown in players before an overuse injury in comparison to the healthy players.

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4

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' acute

Figure 2. Average RESTQ6wk on the 19 scales of the RESTQ-Sport of periods before an injury in comparison to healthy periods.

DISCUSSION

In this study changes in perceived stress and recovery over the course of a season were investigated as a potential risk factor for acute and overuse injuries in team sport players. It was hypothesized that players perceive more stress and less recovery before sustaining an injury. Furthermore, differences were expected for acute and overuse injuries given their specific mechanisms. The results show that there was indeed a higher risk with decreased recovery but not with increased stress. More specifically, perceived General Recovery decreased in the 6-week period before an acute injury compared to healthy periods. Risk of overuse injuries increased when perceived Sport Recovery decreased in the 3-week period before the injury compared to healthy periods. This highlights the importance of monitoring recovery in relation to injury risk. As hypothesized the relation between recovery and injury risk differed for Social Recovery acute and overuse injuries. This may be explained by different mechanisms of these ‡‡”ƒŽ‡ŽŽ-being types of injuries. Players scoring high on the General Recovery scales

and are having frequent pleasurable contacts, 18 relaxation and amusement, next to having a good mood and feeling content . When the frequency of these recovery related activities decreases the current stress cannot be

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17 counterbalanced . This could lead to a larger stress response that may cause Personal narrowing of the visual field and increase reaction time that can increase acute injury Accomplishment 1,18 risk . On the contrary decreased Sport Recovery, specifically decreased

, refers to the perception of feeling less integrated in the team, being 18 less able to accomplish worthwhile things in sport, and less enjoying their sport . Questions in the RESTQ-Sport from this scale are more directly related to feeling fit and therefore more related to the development of overuse injuries. In the

development of overuse injuries pain symptoms appear gradually, 6 consequently players will persist in training routines and game playing . Ultimately this can lead to inadequate recovery and result in an overuse injury. However, more research is

needed to clarify these mechanisms. The time periods over which changes in recovery are observed differed between acute and overuse injuries. For acute injury risk General Recovery decreased over a 6-week period before injury, while for overuse injuries Sport Recovery decreased over a 3-week period before injury in comparison to the same healthy periods. The decreased perceived Sport Recovery in overuse injuries may be due to the symptoms appearing gradually and players persisting in their training routine. To the best of our knowledge this is the first study including different time periods before injury in relation to both acute and overuse injuries. This is important since it is not 4

known over what time frame changes are reflected in perceived stress and 6 recovery. This can be important especially for overuse injuries that evolve over time . The lack et al. et al. of studies including different time periods makes8 it hard to compare 13 our results to previous studies. Studies of Fawkner and Ivarsson did show an increase in perceived stress over 2-weeks before injury, but did not include recovery and did not differentiate between acute and overuse injuries. These results together emphasize the importance of monitoring regularly over an entire season and study et al the effect of different time periods in relation to injury risk. Social Recovery ‡‡”ƒŽ‡ŽŽ-Being 13 Personal Accomplishment In line with the study of Ivarsson . our players showed a decrease in perceived , and over 3 and 6 weeks before injury. These scales are all part of the General Recovery main

score. However, 2,22 recovery is not included in the theoretical model of Andersen & Williams . Recovery, in terms of having a good time, being in a good mood, and et al dealing with emotional problems, could be a13 valuable addition to the model based on our results and the results of Ivarsson . . Both perceived stress and recovery et al. change on a day-to-day basis affected by personality, 13 (history of) stressors, and coping. In comparison to the study of Ivarsson our study measured over a longer period and calculated change scores of perceived stress and recovery over 3-

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and 6-week periods. This sheds light on the impact of changes in perceived stress and recovery in relation to acute and overuse injuries over a longer period of time. It may be interesting for future research to focus on changes over the different seasonal phases. One of the strengths of this study is the incorporation of both perceived stress and recovery in relation to acute and overuse injuries. Furthermore, change scores were calculated to get insight in individual changes over time. A possible limitation may be that with the calculation of the 6-week change scores a period of 3 weeks (1 RESTQ) in between isn’t included, however this is one of the first studies including such a method. Since stress and recovery can change on a day-to-day basis another potential limitation is that the questionnaires were administered on a 3-weekly basis. Lack of Energy, Physical Recovery, Disturbed breaks This may affect the reliability especially of the scales that have shown fluctuations in internal consistency such as and 18 Disturbed Breaks . This may also be an explanation for the contradictory finding that decreased perceived increased injury risk in our study. However, with monitoring over an entire season we aimed to minimize the burden for players and optimize compliance. As a result we were able to gather 836 questionnaires, missing only 10%, indicating a high compliance. This illustrates that our approach is suitable to be implemented in sports practice and that 3-weekly monitoring over an entire season can give insight in injury risk. Also a step forward was made in using a more individual approach by assessing changes in perceived stress and recovery. Finally the focus in our study was on players’ perceived stress and recovery before sustaining an

injury. However, other studies have shown that injured players also have more 7,11 perceived stress and less perceived recovery compared to healthy players . Future research should also look at the perceived stress and recovery during an injury, which may give guidance for return to play interventions. To conclude decreased perceived recovery over both 3 and 6 weeks may suggest increased injury risk. Decreased General Recovery over a 6-week period was shown before an acute injury, while decreased Sport Recovery over a 3-weeks period was shown before an overuse injury. This indicates that especially the recovery- enhancing practices, such as time with friends, amusement, and team building can be

important, while the perceived stress of players doesn’t seem to affect injury risk. PRACTICAL IMPLICATIONS

The results from this study indicate that the sports medical staff could carefully monitor changes in perceived recovery of team sport players as a possible tool to guide individual intervention strategies to reduce injury risk. More insight in both

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acute and overuse mechanisms in relation to perceived recovery may give clear guidance for individual or team recovery-related interventions to prevent these injuries. ACKNOWLEDGEMENTS

The authors would like to thank the players, coaches, physical therapists and student team-managers of the volleyball, basketball and korfball teams participating in Groningen MAPS for their participation and commitment during the 2011-2012 and 2012-2013 season. Additionally we would like to thank Marijke Pots, Marit Dopheide and Nienke Schaap for collecting and processing the injury registration from the teams. This study was funded by SIA RAAK-PRO (PRO-2-018). No conflicts of interest are reported by the authors.

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REFERENCES

9 Fuller CW, Ekstrand J, Junge A, et al. Consensus statement on injury definitions and data collection procedures in studies 1 Andersen MB, Williams JM. Athletic of football (soccer) injuries. Br J Sports injury, psychosocial factors and perceptual changes during stress. J Sports Sci Med 2006;40:193-201. 1999;17:735-741. 10 Galambos SA, Terry PC, Moyle GM, et al. 2 Andersen MB, Williams JM. A model of Psychological predictors of injury among elite athletes. Br J Sports Med stress and athletic injury: Prediction and prevention. J Sport Exercise Psychol 2005;39:351-4; discussion 351-4. 1988;10:294-306. 11 Glazer DD. Development and 3 Brenner JS, American Academy of preliminary validation of the Injury- Pediatrics Council on Sports Medicine and Psychological Readiness to Return to Sport Fitness. Overuse injuries, overtraining, and (I-PRRS) scale. J Athl Train 2009;44:185- burnout in child and adolescent athletes. 189. Pediatrics 2007;119:1242-1245. 12 Ivarsson A, Johnson U. Psychological 4 Brink MS, Visscher C, Arends S, et al. factors as predictors of injuries among Monitoring stress and recovery: new senior soccer players. A prospective study. insights for the prevention of injuries and J Sports Sci Med 2010;9:347-352. illnesses in elite youth soccer players. Br J Sports Med 2010;44:809-815. 13 Ivarsson A, Johnson U, Lindwall M, et al. Psychosocial stress as a predictor of injury 5 Brink MS, Visscher C, Coutts AJ, et al. in elite junior soccer: a latent growth curve Changes in perceived stress and recovery analysis. J Sci Med Sport 2014;17:366-370. in overreached young elite soccer players. Scand J Med Sci Sports 2012;22:285-292. 14 Ivarsson A, Johnson U, Podlog L. Psychological Predictors of Injury 6 Clarsen B, Myklebust G, Bahr R. Occurrence: A Prospective Investigation of Development and validation of a new Professional Swedish Soccer Players. J method for the registration of overuse Sport Rehab 2013;22:19-26. injuries in sports injury epidemiology: the Oslo Sports Trauma Research Centre 15 Johnson U, Ivarsson A. Psychological (OSTRC) overuse injury questionnaire. Br J predictors of sport injuries among junior Sports Med 2013;47:495-502. soccer players. Scand J Med Sci Sports 2011;21:129-136. 7 Evans L, Wadey R, Hanton S, et al. Stressors experienced by injured athletes. J 16 Johnson U. Psychosocial antecedents of Sports Sci 2012;30:917-927. sport injury, prevention, and intervention: An overview of theoretical approaches and 8 Fawkner HJ, McMurrary NE, Summers JJ. empirical findings. International Journal of Sport and Exercise Psychology Athletic injury and minor life events: a prospective study. J Sci Med Sport 2007;5:352-369. 1999;2:117-124. 17 Kellmann M. Preventing overtraining in athletes in high-intensity sports and

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stress/recovery monitoring. Scand J Med 21 Nederhof E, Brink MS, Lemmink KAPM. Sci Sports 2010;20 Suppl 2:95-102. Reliability and validity of the Dutch Recovery Stress Questionnaire for athletes. 18 Kellmann M, Kallus KW. Recovery- International Journal of Sport Psychology stress questionnaire for athletes: User 2008;39:301-311. manual. Champaign, IL: Human Kinetics 2001. 22 Williams JM, Andersen MB. Psychosocial antecedents of sport injury: 19 Kentta G, Hassmen P. Overtraining and Review and critique of the stress and recovery. A conceptual model. Sports Med injury model'. Journal of Applied Sport 1998;26:1-16. Psychology 1998;10:5-25.

20 Lian OB, Engebretsen L, Bahr R. 23 Zwerver J, Bredeweg SW, van den Prevalence of jumper's knee among elite Akker-Scheek I. Prevalence of Jumper's athletes from different sports: a cross- knee among nonelite athletes from sectional study. Am J Sports Med different sports: a cross-sectional survey. Am J Sports Med 2011;39:1984-1988. 2005;33:561-567.

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Š›•Š‡”’‘”–ǤʹͲͳ͸ ƒǢͳ͹ǣ͸ͻǦ͹ͷǤ †‘‹ǣͳͲǤͳͲͳ͸ȀŒǤ’–•’ǤʹͲͳͷǤͲͷǤͲͲʹ 1 1,2

ǤǤƒŽŽ‹‰ƒ 1,2 ǡ ǤǤǤ˜ƒ†‡”‘‡• 1,2, Ǥ‡Œƒ‹•‡ ǡ’”‘ˆǤ†”ǤǤǤǤǤ‡‹ 1 ‹˜‡”•‹–›‘ˆ ”‘‹‰‡ǡ ‹˜‡”•‹–›‡†‹ ƒŽ‡–‡” ”‘‹‰‡ǡ ‡–‡”ˆ‘” —ƒ‘˜‡‡– ‹‡ ‡•ǡ ”‘‹‰‡ǡŠ‡‡–Š‡”Žƒ†• 2  ƒœ‡‹˜‡”•‹–›‘ˆ’’Ž‹‡† ‹‡ ‡•ǡ  Š‘‘Ž‘ˆ’‘”–•–—†‹‡•ǡ ”‘‹‰‡ǡŠ‡‡–Š‡”Žƒ†•

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The objectives in this study were to evaluate the dynamic stability index (DSI) differences between males and females for different jump directions. To examine both preseason DSI differences between players with and without a history of ankle sprain, and between players with and without an ankle sprain during the subsequent season. A prospective cohort desigh was used in which 47 male (22.9 ± 3.9y) and 19 female (21.5 ± 2.9y) sub-elite and elite team sport players participated. Ankle sprain history was collected using an injury history questionnaire. The DSI of a single-leg hop-stabilization task measured preseason was collected using force plates and calculated using a Matlab program. Ankle sprains were reported during subsequent season. Male players demonstrated larger DSI than female players on forward medial/lateral stability index (MLSI) and vertical stability index (VSI), diagonal VSI, and lateral anterior/posterior •–ƒ„‹Ž‹–›‹†‡šȋ Ȍƒ† Ǥ ‘”™ƒ”†ǡ†‹ƒ‰‘ƒŽƒ†Žƒ–‡”ƒŽ†›ƒ‹ ’‘•–—”ƒŽ•–ƒ„‹Ž‹–› indices (DPSI) were larger for males (p<0.001). No significant differences were found between players with and without a previous ankle sprain nor between players with and without an ankle sprain during subsequent season. Male players showed larger DSI scores than female players, indicating lower dynamic stability. Sex-specific training sessions or prevention programs should be developed.

Keywords: ankle injuries, dynamic task, lower extremity, postural stability

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INTRODUCTION

Epidemiological studies have reported high incidence of ankle sprains 6,33 in team sports such as basketball, football, soccer, softball, volleyball and baseball . Most literature

has shown that in these indoor and 6 court sports more ankle sprains occur in female players compared to male players . This difference in incidence suggests that mechanisms and risk factors for ankle sprain in males and females should be

examined separately. Ankle sprains may have some 31 debilitating consequences for the

player. For instance, the risk of reinjury is large 4,10,34 and a potential long term consequence is chronic ankle instability (CAI) . CAI was defined as “an

encompassing term used to classify 10 a subject with both mechanical and functional instability of the ankle joint” . Moreover, it has been reported that 10-40% of

players with long term 16,17,29 issues following an ankle sprain still perceive instability and a

feeling 31of giving way , even up to three years after recovering from the ankle 12

sprain . Furthermore, CAI could lead to an increased risk of 31 ankle osteoarthrosis . The greatest risk factor is a history of ankle sprain . One of the explanations

for this 4increased risk may be a decreased neuromuscular control 4following an ankle sprain . Balance deficits are a measure of neuromuscular control . A review has

shown that athletes who sprained 23 their ankle still show balance deficits during a static

balance task after four weeks . These deficits were 23,34 found in the injured ankle, but also in the contralateral ankle that was not injured .

Furthermore, a recent review showed some evidence that 3 postural sway and balance are risk factors for ankle sprains in team sport players . Two studies 5 including male or a combination of male and female 21,32 basketball players found a higher

postural sway being predictive for ankle sprains ,13 however one study including

male volleyball players did not find this relationship . Those three studies used13,21,32 static

balance tasks for measuring postural sway, for instance standing on one leg 21,32. Furthermore, low odds ratios for postural sway were reported in these studies , indicating that ankle sprain risk increased slightly when postural sway increased. Two main limitations can be addressed in current studies examining the relationship between ankle sprain and stability. At first, in most studies static balance tasks were used to measure stability. Two reviews showed that static balance tasks

could not detect stability differences, 23,34 since they might not be sensitive enough to find small differences in postural control . Dynamic balance tests, such as landing and

stabilizing after a single leg jump, may be more capable to better 22,23,34 detect these differences, since they are more challenging and sport specific . The second limitation was that sex differences in stability were not taken into account. For instance, females showed higher dynamic stability scores on a forward jump task

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38

compared to males . These findings contribute to the difference in ankle sprain

incidence5 based on sex; female players presented a higher incidence of ankle sprains . Although, it should be mentioned that one study that examined injury rates for

different age groups 33 found higher ankle sprain occurrence for male players in the age of 15-24 years . In summary, the strategy for dynamic postural stability might be different for male and female players. Dynamic tasks are recommended to measure differences in postural stability between injured and non-injured players.

In this perspective, a single-leg hop-stabilization 41 task was developed to

determine the dynamic stability index (DSI) . The DSI 40 measures the ability of a player to maintain static balance after a dynamic task . A benefit of the single-leg hop-stabilization task is that it includes jumps in different directions, such as forward, diagonal and lateral. This makes it more sport specific than only performing forward

jumps. One of the outcome measures was the dynamic postural stability index 38 (DPSI),

a composite score of the medial/lateral, anterior/posterior and vertical 41 DSI . It was suggested that the DPSI could be used for preseason screenings for CAI . However, to the authors’ knowledge, the relationship between the DPSI and acute ankle sprains has not been examined yet. Compared with other currently used stability measures, the dynamic, challenging and sport specific aspects of the task used to determine DSI could make it more suitable to detect differences in dynamic stability between male and female players with and without a history of an ankle sprain. It might be suitable to detect preseason dynamic stability differences between players with and without ankle sprain during the subsequent season as well. Moreover, the DSI may assist in determining sex differences. Therefore, the first aim was to determine if sex differences in DSI could be detected for different jump directions. The second aim was to examine whether the DSI measured preseason could discriminate (a) between male and female players who had a history of an ankle sprain and players who did not and (b) between male and female players who sustained an ankle sprain during the subsequent season and players who did not. The first hypothesis was that male players would show lower DSI scores than female players for all directions. The second hypothesis was that players with a history of an ankle sprain and players who sprained their ankle during the season would show higher DSI scores compared to their non-injured counterparts.

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METHODS

A prospective cohort design was used to analyze the relationship between the DSI and ankle sprains in male and female team ball players. At the start of the season the DSI was measured during a single-leg hop-stabilization task. In addition, previous injury data were collected in order to provide insight in injury history of players. Ankle sprains were reported during the subsequent season. Written informed consent was obtained from all players and approval was granted in accordance with ethical standards of the local medical ethical committee, conforming to the Helsinki Declaration. Subjects

Two male basketball teams, three volleyball teams (two male and one female) and one korfball team (mixed) playing at elite and sub-elite level participated in this study.

Korfball is a team sport in which 4 males and 4 43 females play in one team, this sport

shares similarities with basketball and netball . More information 43 about this sport can be found in supplementary material provided elsewhere . In total, eighty players were invited to participate in this study. The exclusion criterion was a current injury to the ankle. Eleven players were not able to attend the baseline measurements due to practical reasons. Three players dropped out during the season (2011-2012), one player moved to another city during season, and two players stopped playing at the sub-elite or elite level. Therefore, 66 players (47 male (22 volleyball, 10 korfball, 17 basketball) and 19 female (9 volleyball, 10 korfball)) were included (Table 1). 5

Table 1. Descriptive Statistics of 66 Players (mean ± SD)

Female (n = 19) Male (n = 47)

Age (years) 21.5 ± 2.9 22.9 ± 3.9

Height (cm) 175.9 ± 7.3 193.5 ± 7.9

Mass (kg) 69.0 ± 11.7 87.1 ± 10.6

BMI (kg/m²) 22.2 ± 2.8 23.3 ± 2.5

Fat percentage (%) 20.9 ± 6.0 10.6 ± 4.2

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Procedures

At baseline, players completed an injury history questionnaire about location, severity and type of previous injuries experienced during the whole lifetime, injuries experienced in the last 6 months, and injuries at baseline. To estimate severity of an injury, questions regarding duration of injury and time loss due to the injury were included. Anthropometrics

Prior to the test, mass, height and BMI were measured. Height was measured using a

measuring tape attached to a wall. Dynamic Stability Index

40 The single-leg hop-stabilization task was used to measure DSI . Prior to testing, the maximal vertical leap was calculated, which was the largest difference between

maximal jump height from stance and maximal reaching height out of three trials. 41 A

rope was placed at the reaching height plus 50% of maximal vertical 40 leap height . Therefore, the jump height was 50% of maximal vertical leap . Jumps were performed in three directions, forward, diagonal and lateral and for each direction the jump distance was 70 cm (Figure 1). Players were instructed to jump, touch the rope,

land on one 40 leg and hold their balance for 3 seconds, while keeping their hands at their hips . In contrast to Wikström et al., the player landed on the leg that was most

nearby the force plate instead28,39 of the dominant or non-dominant leg, since this is more specific for team ball sports . The direction and order of trials was randomized. The player was allowed to practice until the task was executed correctly. After practicing, three successful trials for each direction were recorded. A trial was

successful if the player kept balance, touched the rope, did not make 40an additional hop and did not show excessive sway with the other limb, arms, or trunk . Two force plates (Bertec Corporation, Columbus, Ohio) in combination with a custom made Matlab program (The MathWorks Inc., Natick, MA) were used to collect and calculate DSI. Medial/lateral stability index (MLSI), anterior/posterior stability index (APSI),

vertical stability index (VSI) and dynamic postural stability 34,37 index (DPSI) were calculated as described by Wikström and colleagues (Table 2). These indices stand for fluctuations around a zero point. A smaller deviation from zero means better stability. The MLSI includes fluctuations around the frontal axis, whereas the APSI includes fluctuations around the sagittal axis. The VSI was a measure for fluctuation

around the vertical axis and was standardized to body 40 weight. In other words, the VSI includes fluctuations from the subject’s body weight . The reliability of the DSI was

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excellent for the DPSI, APSI and VSI (intraclass correlation (ICC) range: 0.90 – 35 0.97), whereas the reliability of the MLSI was poor (ICC = 0.38, 95% CI 0.08 – 0.66) . The

stability index was corrected for body mass, in order to allow better 34,37 comparison between players and to increase precision of the DPSI measures .

Figure 1. Starting positions for single leg jump landing test. All starting lines were placed 70 cm from the center of the force plate. Right leg landings occurred on center of force plate 1 (A, B, C) and left leg landings on center of force plate 2 (D, E, F). Reproduced and adapted by kind permission of Elsevier from Wikström 40 et al . 5 Injury Report

Injuries were reported during the season by the team physical therapists 8 by using an injury reporting system based on the recommendations of Fuller et al. . The definition of ankle sprain and a previous ankle sprain was “An injury of the ankle ligaments

sustained by an athlete that results from a game or 8 training, irrespective of the need for medical attention or time loss from activities “ . Medical attention injuries were registered by team physical therapists. The number of injuries and percentage of

injured players were reported. Power analysis

Since DSI differences between players with and without an ankle sprain have not been

examined, the difference between healthy subjects and subjects 34,37 with CAI was used to calculate the sample size needed to find relevant differences . Based on these

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differences in DPSI scores, the required sample size would be 20 (10 per group) to

reach an effect size of 1.35 and a power of 0.8 38 with alpha set at 0.05. Based on sex differences in DSI shown in a previous study , a sample size calculation was

performed for an independent t-test. To reach an effect size of 1.00 with a power7 of 0.80 and alpha set at 0.05, the required sample size was 34 (17 per group) . Statistical analyses

Means and standard deviations (SD) were calculated for all outcome variables. Independent t-tests were performed to analyze DSI differences between players who sustained an ankle sprain during the season and players who did not. In addition, independent t-tests were used to calculate differences on the DSI subscales between players with and without a history of an ankle sprain. Furthermore, sex differences on

the subscales of the DSI 38were calculated with independent t-tests. Sex differences in DSI have been reported , therefore the unequal number of injured male and female players would give a distorted picture, that cannot be generalized. Since the male group was the largest group and most injuries occurred in males, this group was included in the comparisons between injured and non-injured players. Cohen’s d values for each of the variables were calculated and reported as a measure of effect

size (ES), where 0.2 ζ d ζ 2 0.5, 0.5 ζ d ζ 0.8 and d η 0.8 represent a small, moderate and large effect, respectively . In addition, a post hoc power analysis was performed in order to examine if pre-set power level (0.80) was reached. SPSS 20.0 Statistical Package (SPSS Inc., Chicago) was used to analyze all data. To adjust for multiple t- tests, a Bonferroni correction of the Ƚ-value was used. The adjusted Ƚ-value was set at .0042 a priori. RESULTS

Body height and mass were significantly higher in males compared to females (p < 0.0001). Female volleyball players were taller than female korfball players (179.62 ± 3.63 vs 172.62 ± 8.26, p = 0.032). Male basketball players were heavier than male korfball players (92.18 ± 11.47 vs 79.99 ± 8.38, p = 0.011) and female volleyball players were heavier than female korfball players (75.04 ± 13.04 vs 63.57 ± 6.72, p = 0.028). However, the DSI was controlled for weight, therefore we do not expect that Sex this has influenced the results.

Figure 2 shows the results of the independent t-tests performed to find differences in DSI between male and female players. Specific results of these analyses (i.e. means and SDs) can be found in the appendix. Males scored significantly higher than females

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on forward MLSI and VSI (p < 0.001, ES = 1.32 and 1.08 respectively), diagonal VSI (p < 0.001, ES = 1.30), lateral APSI and VSI (p < 0.001, ES = 1.14 and 1.21 respectively). In addition, males scored significantly higher on the composite scores: forward (p = 0.001, ES = 1.08), diagonal, and lateral DPSI (p < 0.001, ES = 1.29 and 1.23 respectively). Post-hoc power analysis showed that for all significant findings, the power was higher than 0.992.

5

Figure 2. Results of DSI of males and females during a single-leg hop-stabilization task. APSI = anterior/posterior stability index; DSI = dynamic stability index; DPSI = dynamic postural stability index; MLSI = medial/lateral stability index; VSI = vertical stability index. * significantly greater than females.

History of ankle sprain

Because only four ankle sprains occurred in the last six months before screening, the history of ankle sprains during whole lifetime was included. In total, eight male players (17.4%) and 2 female players (10.5%) reported a history of an ankle sprain. No significant differences in DSI were found between male players with and without a previous ankle sprain (Table 3).

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Ankle sprain during season

Of the male (n = 33) and female players (n = 16) who did not sustain a previous ankle sprain, six male players (18.2%) and two female players (12.5%) sustained an ankle sprain during season (Figure 3). Table 4 shows that no significant differences were reported for preseason DSI scores between male players who developed an ankle sprain during the subsequent season and male players who did not.

Figure 3. Timeline: occurrence of ankle sprains during season 2011/2012. The end of the season is presented per sport.

DISCUSSION

The DSI was originally developed to detect CAI, however the dynamic aspect of the task could make it also suitable for examining the relationship between DSI and acute ankle sprains. To the authors’ knowledge, this is the first study that has analyzed this relationship. The most important finding of this study was that male players demonstrated a larger DSI than female players, indicating that dynamic stability was worse for male players. Moreover, ESs between 1.08 and 1.32 were reported for all significant differences, indicating that the magnitude of the differences was large. These findings showed that the DSI can detect gender differences in dynamic stability. In contrast to

the present findings, in a previous study female players demonstrated a worse 38 composite DSI than their male counterparts while performing a forward jump . Two methodological differences need to be taken into account for the interpretation,

calculation of the DPSI and type of subjects. Wikström et 38 al. calculated a modified DPSI, which was normalized to vertical potential energy . Furthermore, the present

study included elite and sub-elite 38 team sport players, whereas the study of Wikström et al. included healthy subjects . It was not reported if these healthy subjects performed sports. On the other hand, a study including the star excursion balance test

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(SEBT) found a better dynamic stability for females compared 11 to males during anterior, medial and posterior reaches as in the present study . A larger knee flexion

in combination with a better control of the knee while 11 performing the task could have increased the reach distance for the female athletes . Although the SEBT was a measure of dynamic stability, it did not include a landing like the single-leg hop- stabilization task used in the present study. A connection with studies considering anterior cruciate ligament (ACL) injury

prevention may assist in explaining why females demonstrated 24,26,27 a better DSI, since dynamic stability plays a role in ACL injury prevention as well . One study

already tried 27to examine the link between male and female players with CAI and risk

of ACL injury . Literature 19,20 regarding knee injuries has shown sex differences in landing technique . Differences in landing technique may explain why female

players showed lower DSI scores than male players. 1 For instance, vertical ground reaction force might have been lower in females , resulting in a lower DSI. Future studies performing biomechanical analysis of the landing task next to dynamic stability measures might help to gain insight in sex differences. Understanding why females score different compared to males is crucial for coaches and trainers, since that information would allow them to adapt the training programs for each sex more optimally. The second finding was no difference in DSI between male players with and

without a history of an ankle sprain, which was in contrast to the hypothesis. 34 A review has shown that after an ankle sprain, deficits in balance or stability occur . On the

other hand, another study did not find differences 15in postural stability between 5 players with and without a history of ankle sprain . It should be noted that the time

between ankle sprain occurrence and testing was different, 3.6 months for 15 the study of Huurnink et al. versus approximately 17.6 months for the present study . A first

potential explanation for our results is that the severity of an 15 ankle sprain may have influenced dynamic stability, as suggested by Huurnink et al. . In that study, a

diminished dynamic stability after an 15 ankle sprain was found for the players who sustained a severe ankle sprain only . Based on the duration of the previous ankle sprains, no decreased dynamic stability was reported for the more severe sprains (33- 74 days) compared to the less severe ones (21-28 days) in the present study. Unfortunately, the answers to the injury questionnaire did not allow us to collect ankle sprain severity in terms of grade of ankle sprain for each player, but we expect that the grade of the ankle sprain and duration of an ankle sprain are related. A second suggestion that could explain our results is that potentially some of the players with a history of an ankle sprain were able to cope with balance deficits, so called

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‘copers’, whereas other 36 players continued to have problems with ankle stability, so called ‘non-copers’ . In other words, the decreased stability found for the players with more severe ankle sprains may have been washed out by the results for players

with minor ankle sprains without decreased stability. This idea of making a36 distinction between copers and non-copers has been previously proposed . This

distinction was based on measurable factors such as 36 signals of giving way, pain and weakness, return to play and to pre-injury activities . In the present study, these factors were not measured. However, injured players indicated that they have received physical therapy treatment including mobilization of the ankle, balance exercises and functional exercises. Therefore, for future studies it is recommended that questions regarding symptoms after an ankle sprain and return to play after the injury should be added to the injury history questionnaire in order to determine how many of the players with a history of ankle sprain are copers and non-copers. The third finding of this study was that the DSI could not discriminate between players with and without an ankle sprain during the season following the screening, which did not confirm the hypothesis. In contrary, two reviews have shown

some evidence 3,42 that balance or postural sway was related to a higher risk of an ankle sprain . Although no significant differences were found in the present study, it should be noted that moderate ESs were found for differences in four out of twelve subscales and a large ES for four subscales. In addition, injured players demonstrated a trend for higher DSI scores for all subscores except for the MLSI, however these differences did not reach statistical significance. Recent results of our study group

found significant differences in preseason DSI between injured 30 and non-injured players for the diagonal APSI, diagonal VSI and lateral APSI . The results seem promising, since they suggest that the DSI has potential to detect dynamic stability differences between players who will and will not sustain an ankle sprain during the season. But the authors acknowledge that a larger sample size would be necessary to confirm that. Some limitations of this study should be mentioned. The data on previous injuries were collected based on a questionnaire and these injuries had not been confirmed by medical reports. In the present study, athletes were asked to report

previous injuries during the whole lifetime. Because this includes a long recall period, 9 some injuries could have been missed or the diagnosis may have been incorrect .

Nevertheless, 9 injury recall seemed to be higher when less detailed information was asked . In our study, no specific information was asked, the body region and the number of injuries were the most important items. Therefore, the inaccuracy of incidence rate of previous ankle sprains was expected to be low.

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A second limitation of this study was the small sample size. Based on the a priori sample size calculation, we should have included at least 10 players with an ankle sprain during season, while only 8 ankle sprains were reported in our sample. Two of these eight players sustained a previous injury and were therefore removed

from the analysis. A higher injury rate was expected based 13,14,32 on previous studies including basketball and volleyball players (23.8 – 42.9%) . Consequently, the study was underpowered. Still, this study is relevant because of its practical impact and based on the present results new studies can be developed. Based on the current results it is important to keep sex differences in DSI in mind when (preventive) training sessions or prevention programs are being developed for individual players. Potentially for male players more stability exercises after a landing should be included, while for female players other type of exercises might be more helpful. Previous research has shown the benefits of adopting an

external focus of attention, which means directing 18,25 attention to the effect of the movement, for learning a postural control task . Therefore, it might be useful to incorporate externally focused instructions in training sessions. Furthermore, it is recommended that studies considering DSI should conduct separate analyses for males and females. Male players showed higher DSI scores than female players for all jump directions, indicating a worse dynamic stability. Players with an ankle sprain during the season did not show higher preseason DSI scores. Furthermore, players with a history of an ankle sprain did not differ in DSI compared to players with no history of ankle sprain. Further research including larger prospective cohort studies that 5 perform regression analyses are needed to determine if a larger DSI can predict the occurrence of an ankle sprain. ACKNOWLEDGEMENTS

The authors would like to thank the medical staff, coaches and athletes for their participation. In addition, we would like to acknowledge Juha Hijmans for his support

on the data collection and the data reduction.

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17 Kerkhoffs GM, Handoll HH, de Bie R, et control task following an ankle sprain. J al. Surgical versus conservative treatment Orthop Sports Phys Ther 2007;37:564- for acute injuries of the lateral ligament 569. complex of the ankle in adults. Cochrane Database Syst Rev 2007;(2):CD000380. 26 Smith MD, Bell DR. Negative effects on postural control after anterior cruciate 18 Laufer Y, Rotem-Lehrer N, Ronen Z, et ligament reconstruction as measured by al. Effect of attention focus on acquisition the balance error scoring system. J Sport and retention of postural control following Rehabil 2013;22:224-228. ankle sprain. Arch Phys Med Rehabil 2007;88:105-108. 27 Terada M, Pietrosimone B, Gribble PA. Individuals with chronic ankle instability 19 Laughlin WA, Weinhandl JT, Kernozek exhibit altered landing knee kinematics: TW, et al. The effects of single-leg landing potential link with the mechanism of technique on ACL loading. J Biomech loading for the anterior cruciate ligament. 2011;44:1845-1851. Clin Biomech (Bristol, Avon) 2014;29:1125-1130. 20 Lephart SM, Abt JP, Ferris CM. Neuromuscular contributions to anterior 28 Tillman MD, Hass CJ, Brunt D, et al. cruciate ligament injuries in females. Curr Jumping and Landing Techniques in Elite Opin Rheumatol 2002;14:168-173. Women's Volleyball. J Sports Sci Med 2004;3:30-36. 21 McGuine TA, Greene JJ, Best T, et al. Balance as a predictor of ankle injuries in 29 Valderrabano V, Wiewiorski M, Frigg A, high school basketball players. Clin J Sport ‡–ƒŽǤŠ”‘‹• Š‡ •–ƒ„‹Ž‹–ᇻӖ†‡•‘„‡”‡ Med 2000;10:239-244. Sprunggelenks. Unfallchirurg 2007;110:691-700. 22 McKay GD, Goldie PA, Payne WR, et al. Ankle injuries in basketball: injury rate and 30 Van der Does H, Brink M, Lemmink K. A 5 risk factors. Br J Sports Med 2001;35:103- one year prospective study on ankle 108. stability and landing technique: the occurrence of ankle and knee injuries in 23 McKeon PO, Hertel J. Systematic review elite ball team athletes. Br J Sports Med of postural control and lateral ankle 2014;48 (7):586. instability, part I: can deficits be detected with instrumented testing. J Athl Train 31 van Rijn RM, van Os AG, Bernsen RM, et 2008;43:293-304. al. What is the clinical course of acute ankle sprains? A systematic literature 24 Myer GD, Ford KR, Brent JL, et al. The review. Am J Med 2008;121:324-331.e6. effects of plyometric vs. dynamic stabilization and balance training on 32 Wang HK, Chen CH, Shiang TY, et al. power, balance, and landing force in Risk-factor analysis of high school female athletes. J Strength Cond Res basketball-player ankle injuries: a 2006;20:345-353. prospective controlled cohort study evaluating postural sway, ankle strength, 25 Rotem-Lehrer N, Laufer Y. Effect of and flexibility. Arch Phys Med Rehabil focus of attention on transfer of a postural 2006;87:821-825.

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33 Waterman BR, Owens BD, Davey S, et al. 39 Wikstrom EA, Tillman MD, Schenker S, The epidemiology of ankle sprains in the et al. Failed jump landing trials: deficits in United States. J Bone Joint Surg Am neuromuscular control. Scand J Med Sci 2010;92:2279-2284. Sports 2008;18:55-61.

34 Wikstrom EA, Naik S, Lodha N, et al. 40 Wikstrom EA, Tillman MD, Schenker Bilateral balance impairments after lateral SM, et al. Jump-landing direction influences ankle trauma: a systematic review and dynamic postural stability scores. J Sci Med meta-analysis. Gait Posture 2010;31:407- Sport 2008;11:106-111. 414. 41 Wikstrom EA, Tillman MD, Smith AN, et 35 Wikstrom EA, Tillman MD, Borsa PA. al. A new force-plate technology measure Detection of dynamic stability deficits in of dynamic postural stability: the dynamic subjects with functional ankle instability. postural stability index. J Athl Train Med Sci Sports Exerc 2005;37:169-175. 2005;40:305-309.

36 Wikstrom EA, Tillman MD, Chmielewski 42 Witchalls J, Blanch P, Waddington G, et TL, et al. Discriminating between copers al. Intrinsic functional deficits associated and people with chronic ankle instability. J with increased risk of ankle injuries: a Athl Train 2012;47:136-142. systematic review with meta-analysis. Br J Sports Med 2012;46:515-523. 37 Wikstrom EA, Tillman MD, Chmielewski TL, et al. Dynamic postural control but not 43 Zwerver J, Bredeweg SW, van den mechanical stability differs among those Akker-Scheek I. Prevalence of Jumper's with and without chronic ankle instability. knee among nonelite athletes from Scand J Med Sci Sports 2010;20:e137-44. different sports: a cross-sectional survey. Am J Sports Med 2011;39:1984-1988. 38 Wikstrom EA, Tillman MD, Kline KJ, et al. Gender and limb differences in dynamic postural stability during landing. Clin J Sport Med 2006;16:311-315.

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506196-L-bw-vd Does Processed on: 17-11-2016 506196-L-bw-vd Does Processed on: 17-11-2016 Jump landing characteristics predict lower extremity injuries in indoor team sports

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506196-L-bw-vd Does Processed on: 17-11-2016 Chapter 6

The aim of this study is to investigate the predictive value of landing stability and technique to get insight in risk factors for ankle and knee injuries in indoor team sport players. Seventy-five male and female basketball, volleyball or korfball players were screened by measuring landing stability after a single leg jump-landing and landing technique during a repeated counter movement jump by detailed 3-dimensional kinematics and kinetics. During the season 11 acute ankle injuries were reported along with 6 acute and 7 overuse knee injuries by the teams’ physical therapist. Logistic regression analysis showed less landing stability in forward and diagonal jump direction (OR 1.01 – ͷǤͷͶǡ’κͶǤͶͻȌ‹’Žƒ›‡”•™Š‘•—•–ƒ‹‡†ƒƒ —–‡ƒŽ‡‹Œ—”›Ǥ —”–Š‡”‘”‡ landing technique with a greater ankle dorsiflexion moment increased the risk for acute ƒŽ‡‹Œ—”›ȋ͸Ǥͷͼǡ’κͶǤͶͻȌǤ•ƒŽŽ‡”‡‡ˆŽ‡š‹‘‘‡–ƒ†‰”‡ƒ–er vertical ground reaction force increased the risk of an overuse knee injury (OR 0.29 and 1.13 ”‡•’‡ –‹˜‡Ž›ǡ’κͶǤͶͻȌǤ Less one-legged landing stability and suboptimal landing technique was shown in players sustaining an acute ankle and overuse knee injury compared to healthy players. Determining both landing stability and technique may further guide injury prevention programs.

Keywords: overuse, acute, knee, ankle, stability, biomechanics

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INTRODUCTION

In team sports like basketball, volleyball and korfball the loads at the lower

extremities are high due 23,36,38 to the repeated jumps, sudden accelerations, decelerations and directional changes . On average, a basketball player performs 70 jumps in a

game 29,32 and volleyball players jump approximately 60 times during one hour of game

play3,16 . In these sports lower extremity injuries account 3,16,20 for up to 60% of all injuries . Ankle and knee injuries are the most common . Studies up until now mainly

investigated acute injury 30,51 risk factors, although overuse injuries account for about 14% of the injuries .

Currently, 45-86% of the acute ankle 5,6,34 and knee injuries in basketball and volleyball occur after landing from a jump . For ankle injuries landing stability is

used to determine risk factors. A higher variation in postural 33,44 sway when standing on one leg was shown to be a risk factor for an ankle injury . In these studies postural

sway was determined 19 in a static condition, while the conditions in which players get injured are dynamic . Landing stability measured with the dynamic postural stability

index (DPSI) shows 21,48,49 to be more accurate and reliable compared to static measurements , making this a potentially more valid method for landing

stability. Furthermore, the DPSI is able to distinguish 46 between copers and non-copers with ankle instability after an ankle injury . However this tool has not been used prospectively to examine ankle injury risk.

In jump landing 50% of the acute knee injuries result 5,6,34 from landing on another person’s foot and the other 50% from suboptimal landing . This indicates the importance of a proper landing technique. Suboptimal landing technique increases the load on the lower extremities. For example as a result of increased vertical ground

reaction force (vGRF), knee valgus moment, less joint1,9,10,27,37 flexion and less joint range of motion (RoM) resulting in a stiff landing strategy . On the contrary, an optimal landing technique involves soft landing with active muscular control, where energy 1,31 6 absorption is more efficient, reducing the load at the8,11 lower extremities 27,35. To get insight in landing technique, the drop vertical jump and the tuck jump are regularly analyzed. In a prospective study, female players that sustained an anterior

cruciate ligament (ACL) injury showed suboptimal lower extremity biomechanics in 27 terms of more knee valgus and peak vGRF when landing from a drop vertical jump .

In addition, players developing an overuse knee injury showed smaller knee 7,11 extension moments and less ankle and knee flexion angles during jump landing .

Therefore, players with suboptimal jump 7,11,27landing technique have greater risk for acute as well as for overuse knee injuries . Aforementioned studies focusing on landing technique all included one single jump without repetition. A recent report

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35 proposed a protocol with repeated jumping to assess landing technique , being more sport-specific. Unfortunately this is also not yet prospectively examined. When landing, ankle stability is important as well. Up to 45% of landings in

volleyball are one-legged42 with actions like blocking in which landing stability is assumed to be critical . Although research on the role of stability in jump landing is limited, landing patterns are indeed suboptimal, i.e. less knee flexion and less ankle

dorsiflexion, 24,41 in players with chronic ankle instability (CAI) in comparison to without

CAI . In addition, in jump landing10,24,41 a smaller ankle RoM is associated with suboptimal landing technique . These studies indicate similarities in ankle and knee injury risk factors, and the role of stability in landing technique. Up until now there have been no studies that analyzed both landing technique and landing stability in a prospective study design. In addition, landing technique was mainly analyzed from a single jump and not during repeated jumping. Mainly acute injury risk is investigated, while also overuse injury occurrences appear to be important. Both landing technique and ankle stability may give more insight in risk factors for sustaining ankle and knee injuries. Therefore the aim of this study is to investigate the predictive value of dynamic stability and repeated jump landing to get more insight in risk factors for ankle and knee injuries in indoor team sport players. METHODS

Subjects

A total of 75 (male n=49, female n=26) elite or sub-elite level basketball, volleyball or

korfball players participated in this study (age2 21.9 ± 3.5 yr, body mass 82.5 ± 14.3 kg, Ž‡‰–Šͳͺ͹Ǥ͸άͳͳǤͷ ǡ ʹ͵Ǥ͵άʹǤ͸‰ή ). All players signed an informed consent after being fully informed about the study. Institutional approval was received from the medical ethical committee of the University Medical Center Groningen, the

Netherlands conform the26 declaration of Helsinki and in accordance with the ethical standards of the IJSM . This study is part of a larger monitoring study, known as the Groningen Monitoring Athletic Performance Study (Groningen MAPS). Procedures

Prior to testing, general anthropometrics were measured. At the start of the season all players first performed a single leg jump landing (SLJ) followed by a repeated counter movement jump (rCMJ) to measure landing stability and technique, respectively. These tests were performed at the SportsFieldLab Groningen of the Hanze University of Applied Sciences, School of Sportstudies, Groningen,The

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Netherlands. At time of testing, players had no current injury, wore no ankle or knee brace and were free of injury for at least 2 months. Before jumping the players performed a 5-minute warm-up on a cycle ergometer (Excalibur Sport, Lode B.V., Groningen, The Netherlands) where they kept the pedal frequency between 80 and 90 RPM at a power of 70 to 100 watts. After the warm-up, players maximal reaching height was determined and they performed 3 maximal jumps from stance of which the highest jump was taken as the maximal jump height. The maximal vertical jump height was determined by taking the difference between maximal jump height and . maximal reaching height. During 22 the season injuries were registered according to the recommendations of Fuller et al . At the end of the season the predictive value of baseline measurements for ankle and knee injury occurrence was determined. Instrumentation

Kinematic data were collected using an 8-camera motion analysis system at 200 Hz (Vicon Motion Analysis System Inc., Oxford, UK). The motion analysis system was calibrated prior to each session according to guidelines from the manufacturer. For the collection of the ground reaction force data two force plates (Bertec, Corporation, Columbus, OH) collecting data at 1000 Hz were used. Twenty-one reflective markers of 14 mm in diameter were placed according to the Vicon Plug-in-Gait marker set and model to generate the kinematic and kinetic data. In addition, trunk markers were added to the sternum, clavicle, C7, T10 and right scapula. All subjects wore spandex shorts and shirts (for females) and their own athletic shoes during the test session. Landing stability- Single Leg Jump-Landing

. To 48 determine landing stability the SLJ protocol was used as described by Wikstrom et al . Players jumped from diagonal (45°), lateral (180°) and forward (90°) direction to the center of the force plate, which was placed at 70cm distance from the start of 6 the jump (Figure 1). Players were instructed to jump to a rope, placed at 50% of their

maximal vertical 48 jump height, before landing on one leg. In contrast to the protocol of

Wikstrom et al. players landed on the leg 42 most nearby the force plate since this is more specific for ball team sports players . The player practiced until a successful jump met the following criteria; jumping up with hands at the height of the rope, landing on one leg, and keeping balance for three seconds with hands on the hips. A r trial was discarded if balance was kept with touching or leaning on the other leg or r r the ground. After practicing (mean number of practice trials: forward 1.57 0.79, diagonal 1.69 0.97, lateral 1.57 0.75), three successful jumps were counted. If the jump did not meet the before mentioned criteria the trial was discarded and repeated.

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47 The method of Wikstrom et al. was used to calculate medial/lateral stability index (MLSI), anterior/posterior stability index (APSI), vertical stability index (VSI) and an overall DPSI. Each dynamic stability index (DSI) was calculated as an average of landing on the left and right leg from one jump direction; diagonal, lateral or forward, where a higher stability index represents less stability.

48 Figure 1. Starting positions single leg jump landing test modified from Wikstrom et al. . All positions were placed 70 cm from the center of the force plate. Jumps on force plate 1 were landed on the right leg (A,B,C) and jumps on force plate 2 were landed on the left leg (D,E,F) both on the center of the force plate. Landing technique – Repeated Counter Movement Jump

To examine landing technique, players performed a rCMJ, which consisted of 10 series of three maximal CMJs, with a rest period of 20 seconds between series. Trials of three r consecutive jumps were practiced until successful landing on the force plates (mean number of practice trials: 1.18 0.43). Injury registration

Players completed an injury history questionnaire at baseline, which included questions about the location, severity and type of previous injuries over a whole lifetime for severe injuries resulting in time-loss of a month or longer. During the

season injuries were reported by the team’s physical 22 therapist. The reporting system was based on the recommendations by Fuller et al. . An injury was defined as “any

physical complaint sustained by a player that results from a match of training, 22 irrespective of the need for medical attention or time loss from sports activities” . In this study only the medical attention injuries were registered by the physical

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therapist. An acute 22 injury was defined as “an injury resulting from a specific,

identifiable event” . The definition of an overuse injury was “an injury caused by

22repeated micro-trauma without a single, identifiable event responsible for the injury” . Statistical analysis

Customized software using Matlab 6.1 (The MathWorks Inc., Natick, MA) was used to calculate the DSI and hip, knee and ankle joint kinematics and kinetics at the time of peak vGRF. Force plate and kinetic data were filtered using a fourth-order zero-lag Butterworth low-pass filter at 10 Hz. For all outcome variables of the SLJ and rCMJ means and standard deviations were calculated. The outcome variables for landing stability from the SLJ were MLSI, ˜ q APSI, VSI and DPSI. The outcome variables for landing technique of the rCMJ were q -1 -1 peak vGRF(N kg ) sagittal hip, knee and ankle angles ( Ȍƒ†‘‡–•ȋή‰ ), RoM -1 ( Ȍƒ†ˆ”‘–ƒŽ‡‡‘‡–•ȋή‰ ). RoM is expressed as the value at peak vGRF minus the value at initial contact. The moments are expressed as external moments. The values were calculated for the dominant leg, which was determined by asking the 11,18,39 p players which leg they prefer kicking a ball with . Since there were no significant differences found in any of the kinematic and kinetic variables ( >0.05) between the 10 series of three jumps, the average of the 10 series of three jumps was taken for kinematic and kinetic variables. Since no overuse ankle injuries were reported, the injuries were divided in ankle and knee (acute and overuse) injuries. The acute and overuse medical attention injuries were used for analysis in this study. To determine the differences between players with and without an ankle injury an independent t-test was used for each d variable. To compare variables between players with an acute, an overuse or no knee injury an one-way ANOVA was used, with a Bonferroni post-hoc test. Cohen’s effect d d d 6 sizes (ES) were calculated to determine the magnitude of the differences between d t groups. Magnitude of the ES was interpreted as small ( <0.2), moderate (0.2 < 13 0.8) or large ( 0.8) . To determine the predictive value of the dependent variables for both ankle and knee injuries, binomial and multinomial logistic regression was used. The dependent variables were the injuries during the season; an ankle injury, acute knee injury or overuse knee injury. Ankle injuries were predicted with binomial logistic regression because there were only two groups defined: with and without an ankle injury. For knee injuries multinomial logistic regression was used for three groups: no injury, acute injury and overuse injury. Odds ratios (OR) and 95% confidence

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intervals (95%CIs) were calculated for ankle and knee injuries. IBM SPSS Statistics 20 p for Windows was used for all data analysis. The level of statistical significance was set at ζͲǤͲͷƒ’”‹‘”‹Ǥ RESULTS

During the season 11 (14.7%) players sustained an acute ankle injury and no overuse ankle injuries were registered. Thirteen (17.3%) players had a knee injury; 6 acute and 7 overuse. Landing stability - SLJ

Unstable landing increased ankle injury risk. Forward VSI and DPSI and diagonal p APSI, VSI and DPSI were significantly higher at baseline, with large ES (ES=0.8 – 1.0), for players sustaining an ankle injury during the season ( ζͲǤͲͷǡƒ„Ž‡ͳȌǤŠ‡ p binomial logistic regression showed that a higher DSI, representing instability, in the forward and diagonal jump direction increased the risk of an ankle injury ( ζͲǤͲͷȌǤ Landing technique - rCMJ

Landing technique after repeated jumping (rCMJ) was prospectively related to acute p ankle injuries. A landing technique with a greater ankle dorsiflexion moment was shown in players sustaining an acute ankle injury ( ζͲǤͲͷǡαͲǤ͹ǡƒ„Ž‡ʹȌǤ‹‘‹ƒŽ p regression showed a greater ankle dorsiflexion moment increased the risk of an ankle injury ( ζͲǤͲͷȌǤ Besides, landing technique during repeated jumps (rCMJ) was also p prospectively related to overuse knee injuries. A landing with a smaller knee flexion moment and greater vGRF was shown in players sustaining an overuse knee injury ( ζͲǤͲͷǡ=0.3 and ES=0.9 respectively, Table 3). Multinomial regression showed that a p smaller knee flexion moment and a greater vGRF increased the risk of an overuse knee injury ( ζͲǤͲͷȌǤ

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r acute ankle injuriesTable 1. Descriptives (mean SD), Cohen’s effect size (ES) and Binomial Logistic Regression analysis for the dynamic postural stability score of the Single Leg Jump (SLJ). Odds Ratio (OR) and 95% Confidence Intervals (CI) for . No injury Ankle injury

Mean (N=64)SD Mean SD(N=11) ES OR CI 95% Forward MLSI ± ± Forward APSI 0.03 ± 0.01 0.04 ± 0.01 -1.0 Forward VSI 0.10 ± 0.01 0.10 ± 0.01 0.0 Forward DPSI a 0.34 ± 0.05 0.38 ± 0.06* -0.8 1.01* 1.00-1.03 Diagonal MLSI a 0.35 ± 0.05 0.39 ± 0.06* -0.8 1.02* 1.00-1.03 Diagonal APSI 0.08 ± 0.01 0.08 ± 0.01 0.0 Diagonal VSI a 0.07 ± 0.01 0.08 ± 0.01* -1.0 1.10* 1.02-1.19 Diagonal DPSI a 0.33 ± 0.05 0.37 ± 0.05* -0.8 1.02* 1.00-1.04 Lateral MLSI a 0.35 ± 0.05 0.39 ± 0.05* -0.8 1.02* 1.00-1.04 Lateral APSI 0.10 ± 0.01 0.10 ± 0.01 0.0 Lateral VSI 0.05 ± 0.01 0.06 ± 0.02 -0.8 Lateral DPSI 0.32 ± 0.05 0.34 ± 0.06 -0.4

’ 0.20 ± 0.04 0.22 ± 0.04 -0.5

* ζͲǤͲͷǡƒǢ˜ƒŽ—‡••‹‰‹ˆ‹ ƒ–Ž›†‹ˆˆ‡”‡–ˆ”‘players with no injury; MLSI = Medial/Lateral Stability Index, APSI = Anterior/Posterior Stability Index; VSI = Vertical Stability Index; DPSI = Dynamic Postural Stability Index

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DISCUSSION

This study aimed to investigate the predictive value of landing stability and technique to get more insight in risk factors for sustaining ankle and knee injuries in indoor

team sport players. Out of the 28,33 75 players 14.7% sustained an ankle injury, which is

comparable to other studies 17.3% 3,16 of the players. This is lower compared to other more epidemiological type of studies . However, comparison of injury rates is limited by differences in study population and design. The results for the predictive value of landing stability and technique showed that less landing stability is predictive for sustaining acute ankle injuries. A different landing technique, in comparison to healthy players, from a rCMJ was shown in players with both acute ankle and overuse knee injuries. Our study showed that in addition to forward jump landing stability was mainly affected in the diagonal jump direction of players that sustained an acute ankle injury during the season. Therefore, the forward and diagonal DSI (ES=0.8-1.0) can detect higher risk for ankle injuries. This is in accordance with the ankle inversion

motion, which involves a diagonal 4 movement across anatomical planes with ankle plantar flexion and supination . The lateral jump of the SLJ might not have been a replication of the purely lateral directions on the field when receiving an ankle sprain as our movement includes landing from a certain height as well. Still, the used

protocol involves different jump directions, which has shown 48 to be more valid in comparison to just forward jumping for injury prevention . Supporting our findings,

individuals 45 with functionally unstable ankles show to be unstable in forward jump direction . In addition to less landing stability, players sustaining an ankle injury also showed a greater ankle dorsiflexion moment landing from a rCMJ which increased the

risk of sustaining an acute ankle injury. Studies focusing on risk factors for ankle

injuries15,25,41,50 show that less dorsiflexion RoM increases the risk for acute ankle injuries . Despite of being non-significant, our descriptive data showed indeed less ankle dorsiflexion and RoM in players sustaining an acute ankle injury compared to players with no injury (ES=0.2-0.3). In combination with a trend of greater vGRF . (ES=0.3), this may play a role in the significantly increased ankle dorsiflexion moment resulting in stiffer ankle motion and higher loads at the ankle Studies relating double legged landing technique to ankle injuries are limited. Our results reinforce the importance of more research in this area to guide prevention programs. Our results for landing technique showed a smaller knee flexion moment and greater vGRF in players sustaining an overuse knee injury during the following season. Prospective research on overuse knee injuries is limited, however in line with

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our results players with a previous jumpers knee, show a landing technique with 7,8 smaller flexion angles in all joints, smaller knee flexion moment and greater vGRF . Our study also showed that players sustaining an overuse knee injury have non- significant smaller hip, knee and ankle flexion angles, which in combination with the significantly greater vGRF increases the load at the joints. However, in case of overuse injuries it should be taken into consideration that these do not specifically occur from a one time high load at the joints. These types of injuries are mainly a result of a

specific movement 12,14 repeated numerous times creating the same load at the joints over and over again . Especially when this movement is performed in combination with a poor landing technique this might build up the load at the joints resulting in an overuse injury. Demonstrating again the importance of landing technique in sports with frequent jumping. This is the first study looking closely at both DSI and landing technique to get more clear insight in the risk factors for sustaining ankle and knee injuries. In addition, we differentiated between acute and overuse knee injuries to assess risk factors separately. This resulted in rCMJ landing technique being predictive for acute ankle and overuse knee injuries. Furthermore, we incorporated a repeated jump landing protocol that is more sport specific and makes it a more stable measure for landing technique. To get insight in the risk factors for acute and overuse injuries a comprehensive biomechanical protocol was used, consisting of two different jumps at baseline and a detailed prospective injury follow-up across the season. This also resulted in a smaller number of included players compared to other cohort studies. However, one of the unique aspects of this study is the inclusion of elite and sub-elite players, all participating in jump-sports, increasing generalizability of the results. The

players in this study were both male and female. However, 2,17,43it is known that females are more vulnerable to acute ankle as well as knee injuries . Unfortunately due to the relatively small sample size the results of this study could not be presented 6 separately for males and females. Future research should look further into differences between sexes for landing stability and technique. It can be advised to include unanticipated landing from diagonal directions in injury prevention and warming-up programs, based on our results in combination with previous findings on ankle injury mechanism. Future prospective studies should include both landing stability and technique (kinetics and kinematics) relating these to injury occurrence over the season, including all types of lower extremity injuries. It can be concluded that less one-legged landing stability from a forward and diagonal jump and a greater ankle dorsiflexion moment during two-legged repeated jump landing can indicate increased risk of an ankle injury. A landing technique with a

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smaller knee flexion moment and greater vGRF can indicate increased risk of an overuse knee injury. PRACTICAL APPLICATIONS

This study may lead to better and more precise screening at the start of the season for ankle and knee injuries by testing both landing stability and technique. This may guide prevention programs, which should focus on include unanticipated landing from diagonal directions for landing stability and on landing technique in terms of

knee position and joint 40flexion. In these prevention programs the use of feedback seems to be important . ACKNOWLEGDEMENTS

The authors would like to thank the players, coaches, physical therapists and student team-managers of the basketball, volleyball and korfball teams participating in Groningen MAPS for their participation and commitment during the 2011-2012 and 2012-2013 season. Also we would like to thank the students working at the SportsFieldLab Groningen in 2011-2012 and 2012-2013. We thank Juha Hijmans for his support on the data reduction of the SLJ test. Furthermore we thank Bert Otten for

the custom made Matlab script used to calculate the biomechanical variables of the rCMJ and Ruth Ijtsma for her work on the processing and analyzing the data. Lastly we thank Patricia Kelshaw for her valuable contribution to the manuscript.

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The literature on the relation between jump biomechanics and jumper’s knee indicates that a jump with horizontal displacement poses a threat for developing jumper’s knee. Subjects with jumper’s knee have been shown to display a stiff landing pattern characterized by a small range of motion. However, up to now only cross-sectional studies have been conducted. Six teams from sports involving repetitive landing were followed prospectively for two years. At baseline athletes performed the Landing Error Scoring System jump and 3D kinematics and kinetics were obtained. A comparison was made between subjects who developed jumper’s knee and those who did not develop it. Three subjects developed jumper’s knee during the study. Leg stiffness during landing was high compared to the mean of the healthy controls. No common kinematic patterns could be identified in these three subjects. The results suggest that athletes with high leg stiffness during landing might have an increased risk for developing jumper’s knee, yet this conclusion is based on a very small sample. Subjects who develop jumper’s knee do not show a ‘‘Žƒ†‹‰–‡ Š‹“—‡Ǥ —”–Š‡””‡•‡ƒ” Š‹•‡‡†‡†–‘‹˜‡•–‹‰ƒ–‡ whether leg stiffness can be used to identify athletes at risk and as a target variable to be used in prevention.

Keywords: athletic injury, jump-landing, patellar, leg stiffness, tendinopathy

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INTRODUCTION

Patellar tendinopathy is an overuse injury most24 commonly characterized by proximal patellar tendon pain and tendon dysfunction . Especially when no imaging characteristics of patellar tendon structure are available, it is often referred to as

jumper’s knee. Its prevalence is highest in basketball and volleyball players, with12,26 elite players showing a prevalence of 30-45% and recreational players of 10-15% .

Jumper’s knee is an injury with9 variable treatment results, therefore it sometimes leads to long-lasting symptoms . This is why prevention of this injury is important.

Establishing the6,19 etiology of an injury is one of the steps toward developing preventive measures . Overload as a result of high eccentric loads during repeated

jumping2,6 is thought to be the main cause of this injury, hence the name ‘jumper’s

knee’ . However, in a recent review21 it was found that a stiff landing may pose a threat for developing jumper’s knee . This stiff landing was characterized by initial contact with the leg joints in fairly flexed positions, followed by small amounts of leg joint flexion during the landing phase. The results of the review also suggested that compared to take-off, landing may be a main risk factor for jumper’s knee because eccentric forces placed on the knee are high. This is especially the case when landing from a forward jump where ankle range of motion is reduced, which increases the

load on the other joints, and hip flexion is increased,4,5 which places the center of body mass further away from the base of support . All studies identified in the literature

which examined the relation1,5,16,17,19,20 between jumping and jumper’s knee had a cross- sectional design though ; because of this it isn’t clear which occurred first: the landing patterns or the tendon symptoms. The aim of the present study is to prospectively examine the relation between jumping biomechanics and the risk for developing jumper’s knee. As landing from a horizontal jump is thought to be the cause of jumper’s knee, the focus will lie on this movement characteristic. Based on the aforementioned review we hypothesized that

subjects who develop jumper’s21 knee show higher leg stiffness and altered kinematics during landing at baseline . METHODS

Subjects 7

The Groningen Monitoring Athletic Performance Study (MAPS) monitors physical capacity, stress, recovery and injury occurrence in elite and sub-elite team sports athletes. All teams played at the third highest national level or above. Teams were followed during two competitive seasons (2011/2012 and 2012/2013). Athletes of

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the participating sports teams were included in the study only if they were members of the team – either one or two seasons. From the MAPS population only athletes that were involved in basketball (two teams), korfball (one team (this is a mixed-gender team sport with similarities to netball and basketball) and volleyball (three teams) were included in the analyses because these sports involve repetitive jumping. Athletes with an injury at the start of the season that interfered with the execution of the jump test and athletes with a history of knee injury were excluded. All athletes gave written informed consent and were aged 18 years or older. Permission for the study was obtained from the medical

ethical committee of University Medical Center8 Groningen, the Netherlands and the study meets the ethical standards of the IJSM .

Table 1. Characteristics of the study sample.

Male Female

N 32 17

Age (years) 21.8 ± 3.5 21.6 ± 2.7

Height (m) 1.96 ± 0.07 1.78 ± 0.07

Body Mass (kg) 86.2 ± 10.4 68.3 ± 10.7

Sport (Basketball/Korfball/Volleyball) 12/7/13 0/9/8

Seasons (one seasons/two seasons) 21/11 10/7

Procedure

At the start of each season participants performed13 the Landing Error Scoring System (LESS) jump, a jump-landing-rebound task . The LESS jump is a clinical assessment tool used to identify high-risk movement patterns for anterior cruciate ligament injury. The LESS was considered suitable for our purposes because it is standardized, used frequently, well documented, easy to perform and includes a horizontal phase. In the present study clinical assessment was replaced with measuring kinematics and kinetics using a motion analysis system. Three dimensional kinematics were recorded using a motion analysis system with eight cameras (Vicon Motion Systems, Inc.,

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Centennial, CO) at 200 Hz. Reflective markers were placed at the heel, lateral malleolus, second metatarsal head, lateral femoral epicondyle, anterior superior iliac spine and posterior superior iliac spine both bilaterally, and the lateral side of the mid-thigh, mid-calf bilaterally and on the clavicle, sternum, C7, T10 and right shoulder according to the lower body and torso plug-in-gait model. Ground reaction forces were recorded with two force plates (Bertec Corporation, Columbus, Ohio), one for

each foot, at 2000 Hz. Experimental Protocol

The LESS jump started with jumping from a 30-cm high box onto two force plates that were placed at a distance of half the subjects’ height (horizontal phase). Subjects landed with both feet, one on each force plate, and immediately performed a maximal

vertical jump (vertical phase). Subjects were instructed not to gain height during13 the horizontal phase and to jump as high as possible during the vertical phase . Each subject practiced the LESS jump until they performed three satisfactory jumps. A jump was deemed satisfactory if there was no obvious upward movement during the jump and one foot landed on each force plate. The subsequent three jumps were

recorded. Between jumps subjects had time to reposition at a gentle pace. Injury Data

An injury was defined as “any physical complaint sustained by a player that results

from a match or training and needs medical 7 attention”. Registration of these injuries was done as described by Fuller et al. . Medical attention injuries were registered by

the team physical therapists and reported once a month. A clinical diagnosis3,14 of JK was used that included patellar tendon pain during loading and on palpation . No imaging was performed next to the clinical diagnosis. At the end of the study the JK

cases were extracted from the medical database. Data analysis

The landing after the horizontal jump phase was analyzed using Vicon Nexus 1.8 software with Plug-in-Gait lower body and trunk. Kinematic and kinetic data were 7 filtered with the Vicon Nexus Plug-in-Gait Woltring filter with the General Cross

Validation 25 setting and further analyzed using Matlab 8.3 (The Mathworks Inc., Natick MA) . Joint angles of hip, knee and ankle and angle between foot and ground were calculated for the ground contact phase between landing from the horizontal jump and take-off of the vertical jump. A local coordinate system was used to calculate ankle, knee and hip angles. The angle between foot and ground was calculated as the

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angle that the line through heel marker and second metatarsal head marker makes with horizontal. This variable was included because it indicates whether the athletes landed on the heel or more towards the forefoot. Ground contact was defined as the phase at which the vertical component of the ground reaction force exceeded 30N. Leg

stiffness was calculated as18 the quotient of maximum resultant ground reaction force

and change in leg length . Change in leg length15 was the resultant excursion of the hip joint center relative to the second metatarsal . The average value of the three jumps was taken for each person. Data of the athletes (from the six included teams) who did not develop JK were taken as normative data. These normative data were calculated for men and women separately. For athletes who were included for two seasons in the study, only jump data from the first season were included. Data of each athlete that developed JK were compared to gender-specific norms. RESULTS

Forty-nine athletes were included in the study (Figure 1). The characteristics of the athletes are shown for both sexes in Table 1. Eighteen athletes took part in the study for two seasons and 31 athletes for one season.

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Figure 1. Flow of participants in the study.

Three athletes developed JK symptoms during the study resulting in an annual incidence of JK in the studied population of 4.5%. No traumatic events preceding the onset of the JK symptoms were reported. The athletes that developed JK were one woman and two men, and will be referred to as F1, M1 and M2 respectively. F1 (korfball player) and M1 (basketball player) were included for two seasons in the study and M2 (basketball player) for one season. F1 developed JK during the first season and M1 during the second season. The comparisons between the norm group 7 and injured athletes are shown in Figures 2 and 3.

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Figure 2. Sagittal joint angles during the horizontal landing phase of athletes diagnosed with JK (two males: M1 and M2; and one female: F1) compared to the norm groups. (Black line: norm group mean; gray area: two standard deviations of norm group; dotted line: leg diagnosed with JK; dashed line: leg not diagnosed with JK.

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Figure 3. Median leg stiffness (solid line) and interquartile range (dashed lines) for the norm groups (men (top figure) and women (bottom figure)) compared to both legs of athletes diagnosed with JK (two males: M1 and M2; and one female: F1).

Subject M1 showed differences in knee angle, ankle angle and foot-ground angle compared to the male norm group. He landed with a little more extended knee, a more dorsiflexed ankle and on the heel. Later on during the landing phase he showed a plantar flexion pattern whereas the norm group showed an opposite pattern. Towards the point of take off for the vertical jump kinematic patterns were similar to those of the norm group. Leg stiffness of subject M1 was higher in the leg in which no JK was diagnosed during follow-up compared to the leg in which JK was 7 diagnosed. Leg stiffness in the injured leg fell within the second quartile of the norm group whereas leg stiffness of the control leg fell within the highest quartile (Figure 3). Kinematics of subject M2 were more or less similar to those of the norm group. The knee was a little more extended during landing and the ankle a little more

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into plantar flexion. The leg stiffness of both legs of this subject fell within the second highest quartile of the norm group. Subject F1 showed hip kinematics that deviated from those of the female norm group. She landed with a more flexed hip and showed only very little hip flexion after touchdown. Leg stiffness of both legs fell in the highest quartile of the norm group. DISCUSSION

To our knowledge, this is the first study to prospectively assess the relation between landing biomechanics and the risk for developing JK. We aimed to test the specific hypothesis that subjects who develop JK show higher leg stiffness and smaller range

of motion during landing. This hypothesis was based21 on a previous systematic review on the relation between jump biomechanics and JK . Only three of the 49 subjects developed JK during the follow-up; this precludes drawing strong conclusions. Leg stiffness of the athletes diagnosed with JK fell within the highest two quartiles of the norm group. However, these values were not outliers compared to the norm group. No common sagittal plane ankle, knee and or hip kinematic patterns could be identified in these three subjects either. The two subjects with the highest leg stiffness, M1 and F1 showed lower ROM in the lower extremity joints during landing compared to the control group (Figure 3), as hypothesized, but not for all joints. No common kinematic patterns at initial contact could be identified either. As hypothesized, F1 had a large hip flexion angle at IC, which led to a reduced range of

motion towards flexion, a pattern5 that has been described previously in subjects with patellar tendon abnormalities . Similarly, subject M1 had a large dorsiflexion angle

and a heel first landing, also reducing the1 possibility for joint flexion in order to accommodate excessive impact forces . The third subject that developed JK (M2) showed no marked differences in kinematics compared to the control group. An explanation for this may be that landing biomechanics are not the only factor that

influences the onset of JK. JK is thought to have a 22multifactorial etiology and numerous risk factors have been described in the literature . Other intrinsic (genetics, alignment, flexibility, jump height) and extrinsic factors (amount of training, number of jumps performed, playing position) are thought to play a role in the etiology of tendinopathy. It is the interaction of multiple factors, and not the presence or absence of a single factor that determines whether one develops tendinopathy. Previous cross-sectional studies found certain kinematics to be related to JK. In the present study we found no common kinematics patterns in the three JK subjects. A reason for this may be that group level analyses do not show individual

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differences. The present results suggest that there may be various landing patterns

that may have a high5,19 risk for1,19 JK. This is also in line with the literature where

reductions in1 hip , knee , and ankle range of motionall have been suggested as risk factors . What these landing patterns may have in common is reduced joint flexion leading to poor accommodation of impact forces. Although this study has its limitations, strong points are its prospective

design and long-term follow-up. In a recent review only cross-sectional studies 21that assessed the relation between jumping biomechanics and JK could be identified . This study is the first one that has prospectively assessed the relation between jump biomechanics and JK. A limitation of this study is the low incidence of JK in the study population. Only three athletes were diagnosed with this injury during the study period. A previous study shows an annual incidence of 21% in talented male youth

volleyball players,23 which is almost five times the annual incidence reported in the present study . Our study’s low incidence precluded the use of advanced statistical techniques. Because of this we presented only descriptive data, which makes it difficult to draw strong conclusions. The low incidence in this study may be explained by the study population; athletes with a history of knee injury (including 12 with JK) were excluded from the study, which resulted in the inclusion only of athletes that play at the elite/sub-elite level who have remained injury-free, and who are therefore probably less likely to develop new injuries. The previous study by Visnes & Bahr

included youth players, a population23 in which such a drop-out of athletes at a high risk for JK has not taken place yet . Another limitation of the study is that no additional imaging was performed and only a clinical diagnosis of JK was used. This might have led to the inclusion of other conditions that cause anterior knee pain such as patellofemoral pain syndrome,

or infrapatellar bursitis. On the other hand, the relation between tendon 10,11 abnormalities on imaging and experienced tendon pain is not one on one . Ultrasound imaging, for example, can show tendon abnormalities like an increased tendon diameter and hypoechoic areas, but this only increases the likelihood of the diagnosis and does not provide conclusive evidence for a JK diagnosis. Based on the present results there is some evidence for the hypothesis that 7 athletes with high leg stiffness during landing may be at an increased risk for developing JK. However, further research employing large prospective cohort studies to ensure a sufficient amount of JK’s for further analysis is required to study the relation between leg stiffness and the onset of JK. If such a relation is identified, leg stiffness may be used as a screening variable to identify athletes at risk. Also, leg stiffness may be used as a target variable for prevention purposes. Reducing leg

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stiffness can be achieved by changing the anticipatory muscle contractions and/or leg alignment in such a way that it results in an increase in the change in leg length — in other words the range of motion — and a reduction in the peak ground reaction force (the two factors in the equation). Increasing joint ROM during landing influences both these factors; it increases the change in leg length and thereby decreases the peak deceleration of the center of mass, and as a result decreases the peak ground reaction force (by increasing landing time). Peak ground reaction force can also be reduced by landing on two legs, during a sports-specific action such as a block jump, and reducing body weight. This study gives some support for the idea that high leg stiffness during landing from a jump is a risk factor for the development of JK. No common kinematic patterns could be identified in JK cases. Because of the low number of JK cases and the multifactorial etiology of tendinopathy, results should be interpreted with caution. Further research in larger cohorts is therefore required, ideally conducted among a high-risk group to maximize the number of JK cases. The present findings may have

relevance for prevention and treatment as well as for training and rehabilitation. ACKNOWLEGDEMENTS

The authors would like to thank the players, coaches and physical therapists of the teams participating in Groningen MAPS during the 2011-2012 and 2012-2013 season for their participation and commitment. Additionally we would like to thank Marijke Pots, Marit Dopheide and Nienke Schaap for collecting and processing the team injury registration. Finally, we are grateful to the staff and students participating in the movement lab of the SportsFieldLab Groningen in the academic years 2011-2012 and 2012-2013 for their assistance with the data collection. This study was funded by SIA RAAK-PRO (PRO-2-018).

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REFERENCES 9 Kettunen JA, Kvist M, Alanen E, et al. Long-term prognosis for jumper's knee in male athletes. A prospective follow-up 1 Bisseling RW, Hof AL, Bredeweg SW, et study. Am J Sports Med 2002;30:689-692. al. Are the take-off and landing phase dynamics of the volleyball spike jump related to patellar tendinopathy? Br J 10 Khan KM, Cook JL, Maffulli N, et al. Sports Med 2008;42:483-489. Where is the pain coming from in tendinopathy? It may be biochemical, not only structural, in origin. Br J Sports Med 2 Blazina ME, Kerlan RK, Jobe FW, et al. 2000;34:81-83. Jumper's knee. Orthop Clin North Am 1973;4:665-678. 11 Khan K, Cook J. Overuse tendon injuries: Where does the pain come from? Sports 3 Cook JL, Khan KM, Kiss ZS, et al. medicine and arthroscopy review Reproducibility and clinical utility of 2000;8:1-31. tendon palpation to detect patellar tendinopathy in young basketball players. Victorian Institute of Sport tendon study 12 Lian OB, Engebretsen L, Bahr R. group. Br J Sports Med 2001;35:65-69. Prevalence of jumper's knee among elite athletes from different sports: a cross- sectional study. Am J Sports Med 4 Edwards S, Steele JR, Cook JL, et al. 2005;33:561-567. Characterizing patellar tendon loading during the landing phases of a stop-jump task. Scand J Med Sci Sports 2010. 13 Padua DA, Marshall SW, Boling MC, et al. The Landing Error Scoring System (LESS) Is a valid and reliable clinical 5 Edwards S, Steele JR, McGhee DE, et al. assessment tool of jump-landing Landing strategies of athletes with an biomechanics: The JUMP-ACL study. Am J asymptomatic patellar tendon Sports Med 2009;37:1996-2002. abnormality. Med Sci Sports Exerc 2010;42:2072-2080. 14 Ramos LA, Carvalho RT, Garms E, et al. Prevalence of pain on palpation of the 6 Ferretti A, Ippolito E, Mariani P, et al. inferior pole of the patella among patients Jumper's knee. Am J Sports Med with complaints of knee pain. Clinics (Sao 1983;11:58-62. Paulo) 2009;64:199-202.

7 Fuller CW, Ekstrand J, Junge A, et al. 15 Rapoport S, Mizrahi J, Kimmel E, et al. Consensus statement on injury definitions Constant and variable stiffness and and data collection procedures in studies damping of the leg joints in human of football (soccer) injuries. Br J Sports hopping. J Biomech Eng 2003;125:507- Med 2006;40:193-201. 514. 7

8 Harriss DJ, Atkinson G. Ethical standards 16 Richards DP, Ajemian SV, Wiley JP, et al. in sport and exercise science research: Relation between ankle joint dynamics and 2014 update. Int J Sports Med patellar tendinopathy in elite volleyball 2013;34:1025-1028. players. Clin J Sport Med 2002;12:266-272.

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17 Richards DP, Ajemian SV, Wiley JP, et al. 22 van der Worp H, van Ark M, Roerink S, Knee joint dynamics predict patellar et al. Risk factors for patellar tendinitis in elite volleyball players. Am J tendinopathy: a systematic review of the Sports Med 1996;24:676-683. literature. Br J Sports Med 2011;45:446- 452. 18 Serpell BG, Ball NB, Scarvell JM, et al. A review of models of vertical, leg, and knee 23 Visnes H, Bahr R. Training volume and stiffness in adults for running, jumping or body composition as risk factors for hopping tasks. J Sports Sci 2012;30:1347- developing jumper's knee among young 1363. elite volleyball players. Scand J Med Sci Sports 2013;23:607-613. 19 Siegmund JA, Huxel KC, Swanik CB. Compensatory mechanisms in basketball 24 Warden SJ, Brukner P. Patellar players with jumper's knee. J Sport Rehabil tendinopathy. Clin Sports Med 2008;17:358-371. 2003;22:743-759.

20 Sorenson SC, Arya S, Souza RB, et al. 25 Woltring HJ. A Fortran package for Knee extensor dynamics in the volleyball generalized, cross-validatory spline approach jump: the influence of patellar smoothing and differentiation. Advances in tendinopathy. J Orthop Sports Phys Ther Engineering Software (1978) 1986;8:104- 2010;40:568-576. 113.

21 Van der Worp H, de Poel HJ, Diercks RL, 26 Zwerver J, Bredeweg SW, van den et al. Jumper's knee or lander's knee? A Akker-Scheek I. Prevalence of Jumper's systematic review of the relation between knee among nonelite athletes from jump biomechanics and patellar different sports: a cross-sectional survey. tendinopathy. Int J Sports Med Am J Sports Med 2011;39:1984-1988. 2014;35:714-722.

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506196-L-bw-vd Does Processed on: 17-11-2016 General Discussion

506196-L-bw-vd Does Processed on: 17-11-2016 Chapter 8

The aim of this thesis was twofold. First to investigate if changes in training load, recovery and psychosocial stress and recovery are related to (field-test) performance and injury occurrence during the season. Secondly, to provide more insight in the predictive value of movement technique measured at the start of season for injury occurrence during the season. In total 129 sub-elite and elite basketball, volleyball, korfball and floorball players were monitored over the course of two seasons. MONITORING

In general, this thesis showed that more training load during the season was related to better agility. More psychosocial stress and less psychosocial recovery over the course of the season were associated with decreased intermittent endurance (Chapter 3). Furthermore, less psychosocial recovery was also associated with increased acute and overuse injury risk (Chapter 4). To monitor the changes in field test performance over the course of a season a reliable and valid team sport specific field test is required. Game demands of all

included types of 5,16,21sport showed the importance of well-developed energy systems and agile movements . In Chapter 2 no strong relation was found between anaerobic and aerobic capacities and agile movements indicating that agility is an independent (sport specific) quality of players. Studies relating training load and recovery with agility of players are limited. Chapter 3 of this thesis showed that sport specific training was associated with meaningful changes in agility. Although no causal relation was proven, this suggests the importance of sport specific training to improve agility. Psychosocial stress and recovery showed to be related to performance as well as injury risk. More specifically; General Stress and Recovery scales showed to relate to performance over 6 weeks, while for the Sport Stress and Recovery scales this was shown over 3 weeks. Along these lines, a decrease in the General Recovery scales over six weeks was shown before an acute injury while a decrease in the Sport Recovery scales over three weeks was seen before an overuse injury. The fact that both long and short-term psychosocial stress and recovery relate to performance and injury prevalence indicates the importance of monitoring this continuously over the course of a season. This way individual change can be detected and proper interventions can be implemented. Interventions can consist of learning the players a

way of coping to manage the 31 stress and/or enhance recovery like time management,

meditation, relaxation etc. . Tools like mental preparation and the use of routines 31 have shown to be effective in coping with stressors like anxiety but also injuries .

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MOVEMENT TECHNIQUE & INJURY

Players sustaining an ankle injury during the season showed less one-legged landing stability at the start of the season. Furthermore a suboptimal landing technique in terms of greater ankle dorsiflexion moment was present during two-legged jump- landing at baseline (Chapter 6 & 7). For overuse knee injuries a landing technique with smaller knee flexion moment and greater vertical Ground Reaction Force (vGRF) indicated an increased injury risk (Chapter 7). Finally chapter 4 showed some support for high leg stiffness being a risk factor for the development of a Jumpers Knee (JK). Baseline measurements of physical characteristics seem to be important to assess injury risk. More specific landing stability and technique of indoor team sport . players are of interest, since jumping is one of the primary game demands. This risk profile can guide the development of individual intervention programs more precise . 26,27,32 Protocols measuring stability mostly just involve forward jumping , while during a game players jump from different directions The results from this thesis show that using a protocol involving different jump directions is needed to determine a risk profile. In both Chapters 5 and 6 landing stability for the Vertical and Anterior/Posterior Stability Index (VSI and APSI respectively) after a single-leg landing task showed to be less in players sustaining an acute ankle injury, while for

Medial/Lateral Stability Index (MLSI) 27,32 no results were found. These last results are in

accordance with previous 33,34 studies , and may be due to the poor test retest reliability of the MLSI . Furthermore, in our studies jump-landing stability was investigated for different jump directions. The stability index (SI) in diagonal and forward jump direction were less stable in players with an ankle injury during the consecutive season while this was not the case for the lateral jump direction. These

results seem to be contradictive 9,17,29 to the ankle injury mechanism that is most of the time

a lateral inversion of the ankle . However this type of injury often 1 occurs due to a forced inversion, such as hitting of or landing on another players foot . Furthermore the lateral jump direction of the SLJ may not replicate the pure lateral direction of a lateral ankle inversion on the field since the protocol also involves landing from a certain height. Finally, the forward and diagonal jump directions are in accordance

with the ankle inversion motion, involving a diagonal movement 1 across anatomical planes with plantar flexion and supination of the ankle . So, by using a more sport specific jump multi-directional landing protocol as in our study, a more specific risk

profile can be determined to optimize prevention strategies. 8 Next to landing stability, landing technique showed to be a risk factor for lower extremity injuries (Chapter 6 & 7). The results found for high-risk jump-landing

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patterns differ between individuals and studies. In some studies reduced range of

motion (ROM) on the joints 2,10 were shown due to for example already large dorsiflexion

and hip flexion 3 at landing , while others showed normal ROM and at landing a small

knee flexion . Individual landing patterns within and between 13,20 measurement sessions

show to be consistent for both14 kinematics and kinetics . Also a normal range in landing patterns is found . However these normal ranges have a wide variation, which may indicate the natural variability between individuals. This supports the importance to determine individual optimal landing patterns. Inevitable suboptimal landing patterns increase the load on the joints and therefore injury risk. This thesis showed that for overuse injuries in general, and specifically for JK, a suboptimal landing technique with reduced joint flexion indicates increased injury risk (Chapter 6 & 7). In the case of overuse injuries not only landing technique can be a risk factor,

other 30 factors such as number of jumps, playing position and training load play a role . This emphasizes not only the need for baseline measurements of individual physical characteristics and optimal landing patterns but also monitoring of training load over the season. To summarize, baseline measurement of physical characteristics can play an important role in creating an injury risk profile for players and develop prevention programs if necessary. It may be desirable to repeat these measurements after a prevention program or more often during the season to see whether an intervention program is beneficial to decrease the risk, and whether these physical characteristics change over the course of a season. STRENGTHS, LIMITATIONS & FUTURE RESEARCH

This is one of the first studies that included large number of indoor team sport players on a high playing level. Physical characteristics were measured at baseline involving both landing stability and landing-technique. A prospective longitudinal design was used in order to detect changes in training load, stress and psychosocial stress and recovery in relation to injuries or changes in performance. The design and close interaction with the coaches and players makes this study valuable for both science and practice. Next to the unique aspects of this study there are also limitations. The study design presented in this thesis is an observational design. Therefore the results found in Chapter 3 and 4 do not prove causation, but an association between training load, psychosocial stress & recovery, performance and injury occurrence. To get more insight in the cause and effect, experimental studies that manipulate stress and recovery are needed.

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In this study, different indoor team sports were included. The physical game demands of basketball, volleyball, korfball and floorball all involve repeated sprint and change of direction speed (Chapter 2). In general the results found in this study should account for all indoor team sport involving repeated sprinting and quick

changes of direction. As discussed in Chapter 4,11,18 2, 3 and 4 the 12,19 results of these 12,28 studies are

22comparable to 8 results found in soccer , field hockey , volleyball , basketball and rugby . The physical performance tests used in this study are chosen to match the physical demands, however even more sport specific tests may give more detailed information about the sport performance for one type of sport. Landing stability and technique to predict injury occurrence was measured with the use of a motion analysis system and force plates. These systems are very accurate, but not accessible to all coaches. Moreover, measurements and analysis take time and require specific knowledge. The financial recourses are often not available. So, it would be preferable to develop tools to measure landing technique and stability

that are more practical in use and low in costs. A tool that has been developed to 24

evaluate landing technique and is easy to use is the Landing Error Scoring System23 . This tool has shown to be able to identify individuals at risk for ACL injury . To

measure landing stability a potential 25 easy test to use was developed, however this test was purely based on stability and did not include landing from a jump before stabilizing, which is more sport specific. This thesis showed the importance of landing stability measured from different jump directions and also landing technique as risk factor for both acute and overuse injury. Future research may focus on developing more accessible and sport specific tools to create injury risk profiles of players.

The injury registration was done by the physical 15 therapist of the team according to the recommendations of Fuller et al. . The physical therapist is part of the team and has therefore close contact with the players. This makes registration of injuries easier and increases compliance. However, only the medical attention injuries that were seen by the physical therapist were reported. So when a player has pain or a functional limitation but did not go to the physical therapist, this was not reported.

These milder injuries or physical complaints 6 may have been missed and can lead to an underreporting. Recently, Clarsen et al. developed and validated a new method to register overuse injuries and get insight in these milder complaints. This method consists of a short questionnaire that is filled out each week by the players themselves

to gain insight in their physical problems. This method 6,7 showed to be sensitive and valid to register both overuse and acute injuries . Future research could consider 8 using this method to monitor injuries over the course of a season to get a more

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accurate insight in these milder injuries and physical complaints. This method can help to clarify the development and incidence of overuse injuries. In a longitudinal study design the compliance of the participants is important to avoid missing data. The compliance of the coaches and players depends highly on their motivation. One of the factors influencing this motivation is the feedback they receive. However, in our study the main goal was to observe the natural process. Providing feedback too often would interfere with this natural process. So the challenge was to find the right balance in providing feedback that is satisfactory to the coach and players but did not interfere. The importance of motivation was shown in the floorball team who showed high internal motivation and motivation from the coach resulting in an almost complete training log dataset (Chapter 3). Another factor that may influence the compliance is the presence of a member of the research team. In our study the RESTQ-Sport questionnaire was filled out online before the training session every three-weeks. At the training session a member of the research team was present to ask the players that didn’t fill out the questionnaire online to fill it out on paper. As mentioned in Chapter 4 this method led to only 10.4% of the questionnaires missing over a ten-month monitor period. So in future research it is important to take the above mentioned factors for a good compliance into account. One of the key factors seems to be a person who is present at the training sessions to make sure the training logs and questionnaires are filled out adequately. As described earlier the longitudinal design comes with missing data. To handle this adequately multilevel analysis was used assuming that missing data was random. Another advantage of multilevel analyses was that it took into account the relations between and within players. However, the relations in this analysis were assumed to be linear, while this may not be the case. The relations between process and outcome will probably be not as straightforward as assumed in these analyses. Furthermore it is expected that these relations differ for each individual player. So also a more individual approach in analyzing this data would be preferable. Further research is needed to explore the application of both individual approaches and non-

linear approaches.

To conclude, this thesis shows that a higher training load is related to better agility and psychosocial stress and recovery are associated with aerobic intermittent endurance. Players who experience less psychosocial recovery have a higher injury risk. Furthermore, physical characteristics in terms of less landing stability and a suboptimal landing technique measured at the start of the season indicate an increased risk on ankle and knee injuries in indoor team sport players.

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PRACTICAL IMPLICATIONS

Player monitoring systems should include not only the physical load of training and recovery, but also incorporate psychosocial stress and recovery factors. This appeared to be important in relation to both performance and injuries. To enhance agility sport specific training seems to play a role. However, for aerobic intermittent endurance psychosocial stress and recovery also needs to be considered. For the prevention of injuries players are advised to be aware of their recovery and find evidence based intervention strategies if necessary. Movement technique of the players should also be screened at the start of the season. These measurements can include single-leg jump landing from forward and diagonal jump direction and the assessment of the two-legged repeated jump landing technique. More practical tools are still needed to make these measurements more accessible for sports practice. By monitoring changes during the season and asses movement technique at the start of the season, tailor made intervention programs can be developed and applied on time. This can enhance performance and prevent injuries in indoor team sport players.

8

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8 Coutts AJ, Reaburn P. Monitoring changes in rugby league players' perceived stress 1 Andersen TE, Floerenes TW, Arnason A, and recovery during intensified training. et al. Video analysis of the mechanisms for Percept Mot Skills 2008;106:904-916. ankle injuries in football. Am J Sports Med 2004;32:69S-79S. 9 Doherty C, Delahunt E, Caulfield B, et al. The incidence and prevalence of ankle 2 Bisseling RW, Hof AL, Bredeweg SW, et sprain injury: a systematic review and al. Are the take-off and landing phase meta-analysis of prospective dynamics of the volleyball spike jump epidemiological studies. Sports Med related to patellar tendinopathy? Br J 2014;44:123-140. Sports Med 2008;42:483-489. 10 Edwards S, Steele JR, McGhee DE, et al. 3 Bisseling RW, Hof AL, Bredeweg SW, et Landing strategies of athletes with an al. Relationship between landing strategy asymptomatic patellar tendon and patellar tendinopathy in volleyball. Br abnormality. Med Sci Sports Exerc J Sports Med 2007;41:e8. 2010;42:2072-2080.

4 Brink MS, Visscher C, Coutts AJ, et al. 11 Faude O, Kellmann M, Ammann T, et al. Changes in perceived stress and recovery Seasonal changes in stress indicators in in overreached young elite soccer players. high level football. Int J Sports Med Scand J Med Sci Sports 2012;22:285-292. 2011;32:259-265.

5 Chaouachi A, Brughelli M, Chamari K, et 12 Fawkner HJ, McMurrary NE, Summers al. Lower limb maximal dynamic strength JJ. Athletic injury and minor life events: a and agility determinants in elite basketball prospective study. J Sci Med Sport players. J Strength Cond Res 1999;2:117-124. 2009;23:1570-1577. 13 Ford KR, Myer GD, Hewett TE. 6 Clarsen B, Myklebust G, Bahr R. Reliability of landing 3D motion analysis: Development and validation of a new implications for longitudinal analyses. Med method for the registration of overuse Sci Sports Exerc 2007;39:2021-2028. injuries in sports injury epidemiology: the Oslo Sports Trauma Research Centre 14 Fox AS, Bonacci J, McLean SG, et al. (OSTRC) overuse injury questionnaire. Br J What is normal? Female lower limb Sports Med 2013;47:495-502. kinematic profiles during athletic tasks used to examine anterior cruciate ligament 7 Clarsen B, Ronsen O, Myklebust G, et al. injury risk: a systematic review. Sports The Oslo Sports Trauma Research Center Med 2014;44:815-832. questionnaire on health problems: a new approach to prospective monitoring of 15 Fuller CW, Ekstrand J, Junge A, et al. illness and injury in elite athletes. Br J Consensus statement on injury definitions Sports Med 2014;48:754-760. and data collection procedures in studies of football (soccer) injuries. Br J Sports Med 2006;40:193-201.

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16 Gabbett TJ, Kelly JN, Sheppard JM. assessment tool of jump-landing Speed, change of direction speed, and biomechanics: The JUMP-ACL study. Am J reactive agility of rugby league players. J Sports Med 2009;37:1996-2002. Strength Cond Res 2008;22:174-181. 25 Plisky PJ, Rauh MJ, Kaminski TW, et al. 17 Hootman JM, Dick R, Agel J. Star Excursion Balance Test as a predictor Epidemiology of collegiate injuries for 15 of lower extremity injury in high school sports: summary and recommendations basketball players. J Orthop Sports Phys for injury prevention initiatives. J Athl Ther 2006;36:911-919. Train 2007;42:311-319. 26 Ross SE, Guskiewicz KM. Examination of 18 Ivarsson A, Johnson U, Lindwall M, et al. static and dynamic postural stability in Psychosocial stress as a predictor of injury individuals with functionally stable and in elite junior soccer: a latent growth curve unstable ankles. Clin J Sport Med analysis. J Sci Med Sport 2014;17:366-370. 2004;14:332-338.

19 Lemmink KA, Visscher SH. Role of 27 Ross SE, Guskiewicz KM, Yu B. Single- energy systems in two intermittent field leg jump-landing stabilization times in tests in women field hockey players. J subjects with functionally unstable ankles. Strength Cond Res 2006;20:682-688. J Athl Train 2005;40:298-304.

20 Milner CE, Westlake CG, Tate JJ. Test- 28 Sheppard JM, Gabbett T, Taylor KL, et al. retest reliability of knee biomechanics Development of a repeated-effort test for during stop jump landings. J Biomech elite men's volleyball. Int J Sports Physiol 2011;44:1814-1816. Perform 2007;2:292-304.

21 Nimphius S, McGuigan MR, Newton RU. 29 Starkey C. Injuries and illnesses in the Relationship between strength, power, national basketball association: a 10-year speed, and change of direction perspective. J Athl Train 2000;35:161-167. performance of female softball players. J Strength Cond Res 2010;24:885-895. 30 van der Worp H, van Ark M, Roerink S, et al. Risk factors for patellar 22 Ostojic SM, Mazic S, Dikic N. Profiling in tendinopathy: a systematic review of the basketball: physical and physiological literature. Br J Sports Med 2011;45:446- characteristics of elite players. J Strength 452. Cond Res 2006;20:740-744. 31 Weinberg RS, Gould D. Foundations of 23 Padua DA, DiStefano LJ, Beutler AI, et al. Sport and Exercise Psychology, 6E. : The Landing Error Scoring System as a Human Kinetics 2014. Screening Tool for an Anterior Cruciate Ligament Injury-Prevention Program in 32 Wikstrom EA, Tillman MD, Chmielewski Elite-Youth Soccer Athletes. J Athl Train TL, et al. Dynamic postural stability deficits 2015. in subjects with self-reported ankle instability. Med Sci Sports Exerc 8 24 Padua DA, Marshall SW, Boling MC, et 2007;39:397-402. al. The Landing Error Scoring System (LESS) Is a valid and reliable clinical

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33 Wikstrom EA, Tillman MD, Kline KJ, et 34 Wikstrom EA, Tillman MD, Smith AN, et al. Gender and limb differences in dynamic al. A new force-plate technology measure postural stability during landing. Clin J of dynamic postural stability: the dynamic Sport Med 2006;16:311-315. postural stability index. J Athl Train 2005;40:305-309.

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This thesis addresses the daily struggle of coaches and players to find the right balance between what players do (training load), what they are capable of (physical capacities and movement technique) and the psychosocial aspect of the home situation and work which influences this balance. The goal is to eventually push boundaries to optimize performance and prevent players from becoming injured. The first aim was to investigate if changes in training load, recovery and psychosocial stress and recovery over the season are related to (field-test) performance and injury occurrence in indoor team sport players. The second aim was to provide more insight in the predictive value of movement technique measured at the start of season for injury occurrence during the season. Chapter 2 In monitoring performance of indoor team sport, sport specific field-tests are needed that reflect the game demands as close as possible. In it was investigated to what extent anaerobic power and aerobic endurance were related to agility and to what extent this was affected by anthropometrics. Anaerobic power was determined with a repeated Wingate Anaerobic Test, aerobic endurance was 2 measured with a VO max test on the treadmill and agility was measured with the Repeated Modified Agility T-test. Results showed that higher absolute power (Watt) result in faster total times on the agility test in female players, while for male player no significant relations were found. Height explained 22% of the variance of total time on the agility field-test. So even though anaerobic power affects agility in female players, anthropometrics and especially height seems to be more dominant. In 3rd chapter practice this should be taking into account when interpreting agility test results. Thereupon the addressed the effects of training load, recovery and psychosocial stress and recovery on field-test performance in floorball players. In this study ten floorball players were monitored over six months with daily training logs and the Recovery-Stress Questionnaire to give insight in training load and recovery and psychosocial stress and recovery respectively. Furthermore, the Repeated Modified Agility T-test and the Heart rate Interval Monitoring System were used to measure agility and aerobic intermittent performance, respectively. Multilevel modeling, taking into account within-players and between-players variation in performance changes, showed that more training load improved agility up to six weeks before performance testing, while more psychosocial stress and less psychosocial recovery over three to six weeks decreased aerobic intermittent performance. These results imply that more sport specific training load is important to improve agility, while daily stressors such as school and work and also recovery- related activities like social activities are of influence for aerobic intermittent endurance.

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4th chapter

In the changes in psychosocial stress and recovery were related to injury occurrence. In this study 86 male and female players participated, who reported 66 acute and 62 overuse injuries over a period of 41 weeks. Six weeks before sustaining an acute injury a decrease was shown in General Recovery scales, while three weeks before sustaining an overuse injury a decrease in Sport Recovery scales was shown. For practice this implies that it is important to stimulate recovery- enhancing activities. The high game demands of indoor team sports like basketball, volleyball, korfball and floorball include jumping and running movements. Up to 77% of the injuries in these types of sports occur at the lower extremities and mainly to the knee Chapter 5 and ankle. In jump-landing both landing stability and technique are important to decrease the loads at the lower extremities. In the relation between landing stability and the occurrence of ankle sprain was investigated in 47 male and 19 female team sport players. At the start of the season they performed a Single Leg Jump-Landing task to measure landing stability. Ankle injuries were reported during the season. The results showed no differences in landing stability between players with and without an ankle sprain during the season. However, male players showed less landing stability in comparison to female players. It was concluded that sex- specific prevention programs should be developed and larger studies are necessary to Chapter 6 determine whether landing stability is a risk factor for an ankle injury. This was further explored in where the prospective value of both landing stability and landing technique at the start of the season for acute and overuse ankle and knee injuries was investigated. In this study a total of 75 indoor team sport players participated. At the start of the season these players performed the Single Leg Jump-Landing task to measure landing stability. To get insight in landing technique a repeated Counter Movement Jump was performed. Acute and overuse ankle and knee injuries were recorded during the season. Results showed that less landing stability from forward and diagonal direction and a greater ankle dorsiflexion moment during two-legged jump-landing indicate an increased risk of an ankle injury. For an overuse knee injury a landing technique with a smaller knee flexion moment and greater vertical ground reaction force was identified as a risk factor. These outcomes can lead to more precise injury screening at the start of the season and optimization of Chapter 7 prevention programs. The study described in focused on the jumper’s knee. This injury is an overuse injury that has high prevalence in indoor team sports like basketball and volleyball. Forty-nine basketball, volleyball or korfball players were included to examine the relation between jump biomechanics from a horizontal jump and the

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occurrence of a jumper’s knee. At the start of the season the players performed a jump-landing-rebound task from which 3D kinetics and kinematics were determined for the ground contact phase. From the registered injuries the jumper’s knees during the season were extracted for this study. Out of the 49 players there were three players that developed a jumper’s knee. These players showed higher leg stiffness, together with altered kinematics mainly in terms of more extended joint angles during landing and/or smaller range of motion compared to the healthy norm group. These results indicate that high leg stiffness during landing might be a risk factor for Chapter 8 the development of jumper’s knee. In the last chapter ( ) the main outcomes of this thesis are discussed. It is concluded that less landing stability and sub-optimal landing technique can indicate increased injury risk in indoor team sport players. More training load increases agility, sport-specific training and game play seems most important. Furthermore less psychosocial stress and more recovery increase intermittent aerobic endurance performance. When looking at injuries, a decrease in psychosocial recovery over a three or six-week period can indicate a higher injury risk. For coaches it seems that both baseline measurements as well as monitoring over the season are valuable to gain insight in the individual players needs to prevent them from becoming injured and optimize performance.

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Dit proefschrift richt zich op de juiste afstemming tussen wat indoor teamsporters doen (belasting), wat ze aankunnen (belastbaarheid) en de psychosociale aspecten van de thuis en werk situatie die deze balans ook beïnvloeden. Het uiteindelijke doel is om grenzen te verleggen om prestaties te optimaliseren en blessures te voorkomen. De hoofddoelstelling was tweezijdig; 1) te onderzoeken of trainingsbelasting, trainingsherstel en psychosociale stress en herstel gerelateerd zijn aan prestatie en het krijgen van blessures en 2) het verkrijgen van meer inzicht in de voorspellende waarde van de bewegingstechniek aan het begin van het seizoen voor blessures gedurende het seizoen. Hoofdstuk 2 Om prestaties te monitoren is het belangrijk een sport-specifieke veldtest te gebruiken die de wedstrijdeisen zo goed mogelijk reflecteert. In is daarom gekeken in hoeverre anaeroob vermogen en aeroob uithoudingsvermogen gerelateerd zijn aan wendbaarheid en in hoeverre dit beïnvloed wordt door antropometrie. Anaeroob vermogen werd bepaald door middel van een herhaalde 2 Wingate test. Aeroob uithoudingsvermogen werd gemeten met een VO -max test op de loopband en wendbaarheid werd bepaald met behulp van de Repeated Modified Agility T-test. Bij vrouwen resulteerde meer absoluut vermogen (Watt) in een snellere totale tijd op de wendbaarheidstest, terwijl voor mannen geen significante relaties werden gevonden. In de totale groep verklaarde de lengte 22% van de variantie van de totale tijd op de wendbaarheidstest, waarbij langere spelers beter scoorden op de wendbaarheidstest. Hoewel bij vrouwelijke spelers anaeroob vermogen invloed heeft op de wendbaarheid lijkt voor zowel mannen als vrouwen lengte een belangrijkere invloed te hebben. In de praktijk is het belangrijk om hier rekening mee te houden bij Hoofdstuk 3 het interpreteren van de wendbaarheidstest. Vervolgens werd in gekeken naar het effect van trainingsbelasting, trainingsherstel en psychosociale stress en herstel op veldtestprestatie in floorbal spelers. In deze studie werden tien floorbal speelsters gemonitord over een periode van zes maanden met behulp van dagboeken en de Nederlandse versie van de Recovery-Stress Questionnaire om inzicht te krijgen in respectievelijk trainingsbelasting en herstel en psychosociale stress en herstel. Daarnaast zijn de “Repeated Modified Agility T-test” en de “Heart rate Interval Monitoring System” afgenomen om respectievelijk wendbaarheid en het aerobe interval uithoudingsvermogen in kaart te brengen. De multilevel modellen, welke zowel binnen als tussen spelers variatie in prestatie verandering meeneemt, lieten zien dat meer trainingsbelasting tot over zes weken de wendbaarheid verbeterde. Terwijl meer psychosociale stress en minder herstel over drie tot zes weken de aeroob interval uithoudingsvermogen verminderde. Deze resultaten impliceren dat

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sport-specifieke training belangrijk is in het verbeteren van de wendbaarheid, terwijl dagelijkse stress factoren zoals school en werk en daarnaast ook herstel activiteiten Hoofdstuk 4 van invloed zijn op het aeroob interval uithoudingsvermogen. In werden veranderingen in psychosociale stress en herstel gerelateerd aan het krijgen van een blessure. In deze studie participeerden 86 mannelijke en vrouwelijke spelers. Er werden 66 acute en 62 overbelasting blessures gerapporteerd over een periode van 41 weken. Zes weken voor het krijgen van een acute blessure was een daling te zien in de Algemeen Herstel schalen, terwijl drie weken voor het krijgen van een overbelasting blessure een daling was te zien in de Sport Herstel schalen. Dit impliceert dat het belangrijk is om aandacht de besteden aan herstel gerelateerde activiteiten. De fysieke wedstrijdeisen in indoor teamsporten zoals basketbal, volleybal, korfbal en floorbal bestaan met name uit herhaald springen en rennen met veel snelheids- en richtingsveranderingen. In deze typen sport zijn 77% van de blessures aan de onderste extremiteiten en dan met name aan de knie en enkel. Bij het landen Hoofdstuk 5 na een sprong zijn zowel landing stabiliteit als techniek belangrijk om de krachten op de onderste extremiteiten te minimaliseren. In van dit proefschrift werd de relatie tussen landing stabiliteit en het verkrijgen van een enkelblessure onderzocht bij 47 mannelijke en 19 vrouwelijke indoor teamsporters. Aan het begin van het seizoen hebben deze spelers een één benige sprongtaak gedaan om inzicht te krijgen in landing stabiliteit. Daarnaast zijn onder andere enkelblessures gerapporteerd gedurende het seizoen. Er was geen verschil in stabiliteit na landing tussen spelers die wel en geen enkel blessure krijgen. Mannen lieten wel een verminderde stabiliteit zien in vergelijking met vrouwen. Geconcludeerd wordt dat het belangrijk is om preventieve programma’s geslacht specifiek te maken. Daarnaast zijn er studies nodig met grotere aantallen om te bepalen of landing stabiliteit enkel Hoofdstuk 6 blessures kan voorspellen. In is de voorspellende waarde van zowel landing stabiliteit als landingstechniek aan het begin van het seizoen verder onderzocht voor acute en overbelasting blessures aan de enkel en knie. In deze studie hebben 75 indoor teamsporters deelgenomen gedurende twee seizoenen. Aan het begin van het seizoen hebben ze een één benige sprongtaak gedaan voor het meten van landing stabiliteit. Daarnaast hebben ze een herhaalde “Counter Movement” sprong gedaan om inzicht te krijgen in landingstechniek. In deze studie zijn de geregistreerde acute en overbelasting enkel en knie blessures gebruikt voor de analyses. De resultaten lieten zien dat er een verhoogd enkelblessure risico is wanneer spelers minder stabiel zijn na het één-benig landen van een voorwaartse en diagonale sprong en daarnaast was

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ook een groter enkel dorsiflexiemoment na een tweebenige landing een risico factor. Een landingstechniek met een kleiner knie flexie moment en grotere grond reactie kracht bleek het risico op een overbelasting blessure aan de knie te verhogen. Deze resultaten kunnen de basis zijn voor een preciezere blessure screening aan het begin Hoofdstuk 7 van het seizoen en richting geven aan blessure preventie programma’s. In is de jumper’s knee (JK) onderzocht. De JK is een overbelasting blessure die veel voorkomt in indoor teamsporten zoals basketbal en volleybal. In deze studie participeerden 49 basketbal, volleybal en korfbal spelers om de relatie te onderzoeken tussen de sprong biomechanica van een horizontale sprong en het risico om een JK te ontwikkelen. Aan het begin van het seizoen hebben de spelers een sprongtaak gedaan waar op moment van grond contact de 3D kinetica en kinematica van werd bepaald. Uit de blessureregistratie zijn de JK geselecteerd voor deze studie. Van de 49 spelers waren er drie die een JK ontwikkelden. Deze spelers vertoonde een stuggere landing, en daarnaast ook grotere gewrichtshoeken tijdens de landing en/of een kleinere range of motion in vergelijking met de normgroep. Stugger Hoofdstuk 8 landen is dus een risico factor voor het ontwikkelen van een JK. In het laatste hoofdstuk ( ) zijn de belangrijkste resultaten van dit proefschrift bediscussieerd. De metingen aan het begin van het seizoen hebben inzicht gegeven in de fysieke capaciteiten en bewegingstechniek van de teamsporters. Hieruit blijkt dat minder stabiliteit bij het landen en een verminderde landingstechniek kunnen duiden op een verhoogd blessurerisico bij indoor teamsporters. Uit het monitoren van trainingsbelasting, herstel en psychosociale stress en herstel is gebleken dat de wendbaarheid verbeterd door meer te trainen, waarbij sport-specifieke training en wedstrijden het meest belangrijk lijken te zijn. Minder psychosociale stress en meer herstel verbeterd het aerobe interval uithoudingsvermogen. In relatie tot blessures kan een vermindering van psychosociaal herstel duiden op een verhoogd blessure risico. Voor coaches lijkt het belangrijk om zowel aan het begin van het seizoen de bewegingstechniek in kaart te brengen als om over het seizoen de trainingsbelasting, herstel en psychosociale stress en herstel van de spelers te monitoren. Dit kan inzicht geven in de individuele behoeftes van de spelers en kan gebruikt worden om blessures te voorkomen en trainingen te optimaliseren.

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Dan is nu ook voor mij het moment aangekomen. Het schrijven van het dankwoord. Dat deel van het boekje wat ik zelf vaak als eerste lees. Er zijn een hoop mensen die een aandeel hebben gehad in het tot stand komen van dit proefschrift, ik hoop ze hieronder allemaal te noemen. Mocht ik iemand vergeten zijn, het spijt me, maar heel erg bedankt voor je bijdrage!

De afronding van mijn promotie leek voor mij steeds ver weg, maar wat is de tijd gevlogen. Ik kijk met veel plezier terug op de afgelopen 4 à 5 jaar. Er zaten ook moeilijke momenten tussen maar over het algemeen heb ik een super mooie tijd gehad in Groningen. En dat heb ik onder andere te danken aan onderstaande mensen.

Allereerst Prof dr. K. Lemmink en Dr. M. Brink: Bedankt voor jullie begeleiding de afgelopen 5 jaar. Ik heb de tijd die jullie in mij hebben gestoken erg gewaardeerd.

Beste Koen, bedankt voor de begeleiding en het delen van je kennis. Vanaf het begin van het onderzoek was de invulling geheel aan mij, met hier en daar wat subtiele bijsturing, dit zorgde ervoor dat het echt mijn project werd. Die vrijheid bezorgde mij ook wel wat stress, maar ik heb er veel van geleerd. Bedankt voor je vertrouwen in mij.

Beste Michel, ook jij bedankt voor je begeleiding van mijn traject, voor het delen van je eigen ervaring met betrekking tot het monitoren van teamsporters. Daarnaast was je ook altijd bereid om een keer extra af te spreken en mee te kijken met de data, te sparren over de analyse of artikel inhoudelijke zaken. Thanks!

Prof dr. C. Visscher, Beste Chris, in het begin bij het uiteenzetten van de artikelen en vervolgens bij het schrijven van de artikelen had jij altijd weer een frisse blik. Bedankt voor je waardevolle bijdrage aan dit proefschrift.

Lieve Ruby, met jou ben ik aan dit avontuur begonnen. Vanaf dag 1 fulltime samen als collega’s bij het HIS, BW en huisgenootjes aan de Reitdiephaven. Wij kunnen bijna niet meer van elkaar verschillen maar dit uitgegroeid tot een bijzonder goede vriendschap. Bedankt voor al je steun, adviezen, luisterende oor en onze gezellige avondjes thuis op de bank. Ik vond het erg waardevol om iemand zo dichtbij te hebben die 100% begrijpt waar je mee bezig bent. Onze gezamenlijke passie voor koken en (uit) eten. In ons eerste jaar hebben we onze nieuwe baan gevierd bij de Librije. Dit is ondertussen

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uitgegroeid tot een traditioneel jaarlijks etentje en hopelijk zetten we dit nog lang voort. Ik kan mij dan ook niet anders voorstellen dan dat jij naast mij staat op deze belangrijke dag als paranimf. Bedankt voor alles!

e

Wouter Frencken,e jij bent met name betrokken geweest bij mijn 2 artikel welke uiteindelijk als 1 gepubliceerd is. Ik heb jou ervaren als erg betrokken zowel bij schrijven van artikelen als bij alle andere zaken rondom het promoveren. Je hulp bij mijn eerste revisie heb ik erg gewaardeerd! Bedankt hiervoor, maar ook voor de gezellige praatjes op het HIS en bij BW.

Kamergenootjes van het HIS; Adrie en Anne, vanaf het begin met jullie op onze PhD- kamer. Altijd gezellig - tijd voor zowel promotie en onderzoek tips & trucs, als voor de gezellige kletspraatjes. Joan, Ingrid & Cindy jullie sloten later aan in de gezelligste PhD-kamer van het HIS, waar ik met veel plezier werkte en naartoe ging. Bedankt voor jullie gezelligheid en klankbord voor als het allemaal even tegenzat.

Anne Benjaminse, naast kamergenootje ook coördinator van het bewegingslab. Het bewegingslab was onmisbaar in mijn onderzoek om blessurerisico in kaart te brengen. Bedankt voor de tijd die je hebt gestoken in het onderzoek, oa als auteur op 1 van de artikelen.

Steven Doeven, als coördinator van het inspanningslab heb je mij voor de eerste metingen goed op weg geholpen, het uitzoeken van protocollen, het meekijken met geplande metingen en het goed laten verlopen van de eerste metingen. Bedankt voor je hulp! Daarnaast ben je een fijne en behulpzame collega en altijd in voor een gezellig praatje.

Juha Heijmans, zonder jou expertise in het bewegingslab en kennis van matlab waren de meetweken en het verwerken van de data erna een stuk lastiger geweest. Ook was je altijd bereid bij te springen als dit nodig was. Bedankt voor je bijdrage!

Talko Dijkhuis, bedankt voor de tijd die jij in het programmeren hebt gestoken. Vele problemen met opslag en verwerking van grote hoeveelheden data zijn door jou opgelost. Dit heeft veel tijdwinst opgeleverd en daarnaast heeft het mij ook heel wat geleerd over Microsoft Excel.

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ProCare, het feit dat jullie op hetzelfde terrein zitten, jullie service en het beschikbaar stellen van extra materiaal voor de drukke meetweten aan het begin van het seizoen heeft de erg geholpen in een aantal stressvolle meetperiodes. Het is fijn om een goede buur te hebben. Bedankt!

Polar, mijn onderzoek had niet plaats kunnen vinden zonder jullie Team2 systeem, wanneer er problemen waren stonden jullie klaar om te helpen telefonisch of in persoon en ook het aanbieden van een leensysteem was geen probleem. Bedankt voor deze hulp!

Natuurlijk niet te vergeten alle sporters en trainer/coaches van de Flames (huidig: Donar), Lycurgus, Donitas, Nic., Nederlands Floorball team en het Nederlands zaalhockey team die in de seizoenen 2011-2012 en 2012-2013 deelgenomen hebben in het onderzoek. Zonder jullie deelname had dit proefschrift er nu niet gelegen. Super bedankt voor jullie inzet gedurende de 2 seizoenen. Dat wij jullie mochten volgen met dagboeken, vragenlijsten en andere metingen.

Het monitoren, testen en meten van al deze sporters kon ik natuurlijk niet alleen. Daarom wil ik ook alle studenten bedanken die meegeholpen hebben zowel bij de drukke meetweken aan begin van het seizoen als gedurende het seizoen in functie van sportmanager, teammanager of blessuremanager. BEDANKT: Rick Nijland, Joan Dallinga, Marijke Pots, Gesina Bootsma, Gaby Campschroer, Ellen Wolters, Jessica Klunder, Aaltsje Scholte, Reinder Boersma, Xandra Blokzijl, Isabelle Willemse, Cees Smaal, Doortje Ijspeert, Fleur Bosch, Iris Muijsken, Janet Toonder, Marcel Bandringa, Nick de Zeeuw, Rens Wolf, Ruben Prinsen, Susan Kok, Marit Dopheide, Nienke Schaap.

Sportartsen van het UMCG; Bram Bessem, Hans Zwerver, Hans de Vries, Steef Breedeweg, Feikje Riedstra, Stijn de Buijn, Marieke Brinkman. Om alle sporters aan het begin van het seizoen veilig te kunnen testen hebben ze een medische screening gedaan bij jullie. Dank voor jullie hulp tijdens de intensieve meetweken aan het begin van het seizoen en sporters die tijdens het seizoen tussen nog “even” tussendoor moesten.

Henk van der Worp, bedankt voor de fijne samenwerking met als resultaat een mooi artikel (hoofdstuk 7 van dit boekje).

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Niek Benerink en Ruth IJtsema, na 2 jaar volop data verzamelen was er een hele hoop data te verwerken, onder andere de biomechanische data vanuit het bewegingslab. Hierin hebben jullie een grote rol gehad en daarmee enorm geholpen. Bedankt!!

Bert Otten, om deze data van het bewegingslab te kunnen verwerken en analyseren waren jouw Matlab scripts hard nodig. Ook bij problemen kon ik bij jou terecht en was je altijd bereid om biomechanica uitleg te geven. Dank je wel!

HIS collega’s; Ben Moolenaar, bedankt dat je mij in het begin onder je hoede wilde nemen bij het lesgeven. Ik heb veel van je mogen leren op dit gebied. Daarnaast toonde je ook altijd interesse in de voortgang van mijn onderzoek. Ook alle andere HIS collega’s, bedankt voor de praatjes in de koffiekamer, de gezelligheid bij studiedagen en HIS/ALO-uitjes.

BW collega’s & (oud-)PhD-ers; bedankt voor alle gezelligheid op de dagen dat ik bij BW te vinden was. De gezellig lunches, lunchwandelingen, koffie momentjes, voorbereidingen/overleggen voor promotie-stukjes en PhD-uitjes. Ik voelde me altijd

welkom bij jullie!

Lieve Carola, allereerst super bedankt voor het mooie ontwerp van de omslag van dit boekje, en de titelpagina’s in het boekje. Daarnaast bedankt voor je vriendschap. Ik kan altijd en overal mee bij je terecht. Super dat je bij mijn promotie naast me staat als paranimf.

Lieve vriendinnetjes; Irene, Jantien, Ilse, Loes en Anneloes – bedankt voor de gezellige dates die hard nodig zijn voor de afleiding en het herstel ;).

Lieve Peter en Ingrid, sinds het begin van mijn promotie aan de andere kant van de wereld een mooi adresje voor de nodige vakantie. Daarnaast erg betrokken bij mijn promotie traject, altijd bereid tot adviezen bij het schrijven van artikelen en het promoveren. Bedankt voor jullie steun hierin!

Lieve pap en mam, bedankt voor jullie onvoorwaardelijke steun en meegeven van het doorzettingsvermogen wat mij zover heeft gebracht.

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Lieve zusjes, Lisette en Willemijn; de zusjes-dagen en weekendjes hebben gezorgd voor de nodige afleiding. Ondertussen zijn deze een regelmatig terugkerend event, waar ik altijd naar uitkijk. Bedankt dat jullie er altijd zijn.

Last but definitely not least, Lieve Maarten, je steunde mij in mijn keus om naar Groningen te gaan om deze kans te kunnen aangrijpen. Dit betekende wel dat we van samenwonend naar een LAT-relatie gingen. Je stond altijd klaar om te luisteren naar mijn ups & downs tijdens mijn promotie, en nog steeds kan ik met alles bij je terecht. Ondertussen wonen we in het mooie Haarlem, met veel moois in het verschiet. Samen kunnen wij alles aan! Love you!

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506196-L-bw-vd Does Processed on: 17-11-2016 Curriculum Vitae

506196-L-bw-vd Does Processed on: 17-11-2016

Henrike van der Does is geboren op 29 juni 1984 in Eindhoven. Na het behalen van haar gymnasium diploma in Apeldoorn, heeft ze een High School Year gedaan in Clara City, Minnesota, USA. Na dit jaar in het buitenland heeft ze van 2003 tot 2007 gestudeerd aan de Hogeschool van Arnhem en Nijmegen te Nijmegen, waar ze de opleiding Sport, Gezondheid en Management heeft voltooid. Deze gaf haar uiteindelijk toch niet de theoretische diepgang die ze zocht, daarom is ze in 2007 begonnen aan haar pre-master Bewegingswetenschappen aan de VU in Amsterdam om vervolgens in 2009 haar master Bewegingswetenschappen af te ronden. Haar afstudeeronderzoek vond plaats bij de Nationale Zwem Academie in het Sloterparkbad Amsterdam. Na haar afstuderen heeft ze eerst een jaar als onderzoek assistent gewerkt voor een promovendus aan de VU. Daarnaast deed ze werkervaring op als embedded scientist bij het NOC*NSF. Dit heeft er toe geleid dat ze in maart 2011 is aangenomen als promovenda aan de Hanze Hogeschool Instituut voor Sportstudies in samenwerking met de Rijks Universiteit in Groningen bij het Centrum voor Bewegingswetenschappen. Binnen dit onderzoek is ze werkzaam geweest als embedded scientist en heeft gedurende twee seizoenen volleyballers, basketballer, korfballers, floorballers en zaalhockeysters gemonitord. Het onderzoek had als doel inzicht te krijgen in de belasting en belastbaarheid van deze teamsporters in relatie tot de prestatie en het ontstaan van blessures. Dit promotieonderzoek heeft ze in 2016 afgerond. Naast dit promotieonderzoek heeft Henrike gedurende deze periode onderwijs gegeven in onderzoeksvaardigheden en begeleide ze afstudeerders. Ook coördineerde ze activiteiten binnen het inspanningslab van het SportsFieldLab Groningen. Sinds oktober 2015 is Henrike werkzaam als kwaliteitsfunctionaris in het Erasmus Medisch Centrum te Rotterdam op de afdeling Kinderoncologie en - hematologie. Daarnaast is ze parttime werkzaam als onderzoeker bij het Hockey Performance Centre in Eindhoven.

Contact: [email protected]

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List of publications:

Does, H.T.D. van der The effect of stress and recovery to field-test performance in floorball. , Brink, M.S.,Visscher, C., Huijgen, B.C.H., Frencken, W.P.G., Lemmink, K.A.P.M. Int J Sports Med. 2015 Jun;36(6):460-5. doi: 10.1055/s-0034-1398581. Epub 2015 Mar 3.

Does, H.T.D. van der Jump landing predicts lower extremity injuries in indoor team sports. , Brink, M.S., Benjaminse, A., Visscher, C., Lemmink, K.A.P.M. Int J Sports Med. 2016 Mar;37(3):251-6. doi: 10.1055/s-0035-1559688. Epub 2015 Nov 17.

Henrike van der Does. Prospective study of the relation between landing biomechanics and jumper’s knee. Henk van der Worp, , Michel Brink, Johannes Zwerver, Juha Hijmans. Int J Sports Med. 2016 Mar;37(3):245-50. doi: 10.1055/s-0035-1555858. Epub 2015 Dec 23.

Does, H.T.D. van der Monitoring perceived stress and recovery in relation to cycling performance. Otter, R.T.A., Brink, M.S., , Lemmink, K.A.P.M. Int J Sports Med. 2016 Jan;37(1)12-8. doi: 10.1055/s-0035-1555779. Epub 2015 Oct 28.

Dynamic postural stability differences between male and female players with and Does, H.T.D. van der without ankle sprain. Dallinga, J.M., , Benjaminse, A., Lemmink, K.A.P.M. Phys Ther Sport. 2016 Jan;17:69-75. doi: 10.1016/j.ptsp.2015.05.002. Epub 2015 May 29.

Does, H.T.D. van der Injury risk is increased by changes in perceived recovery of team sport players. , Brink, M.S., Otter, R.T.A., Visscher, C., Lemmink, K.A.P.M. Clin J Sport Med. 2016 Mar 3. [Epub ahead of print]

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Does, H.T.D. van der Repeated Modified Agility T-test: role of the energy systems and anthropometrics. , Brink, M.S., Lemmink, K.A.P.M. Submitted Journal of Sport and Health Science Conference presentations:

Changes in perceived stress and recovery relate to changes in submaximal Does, H.T.D van der performance in team sport players. , Brink, M.S. & Lemmink, K.A.P.M.

Annual meeting - European Congress of Sport Science 2015 - Malmo

Does, H.T.D van der Veranderingen in ervaren stress en herstel bij teamsporters: gezond vs. geblesseerd

, Brink M.S.,& Lemmink K.A.P.M.

Dag van het Sportonderzoek 2014 – Nijmegen

Changes in psychosocial stress and recovery and injury occurrence: a one-year Does, H.T.D van der prospective study , Brink M.S.,& Lemmink K.A.P.M.

Annual meeting - European Congress of Sport Science 2014 - Amsterdam

A one year prospective study on ankle stability and landing technique: the occurrence Does, H.T.D van der of ankle and knee injuries in elite ball team athletes. , Brink M.S.,& Lemmink K.A.P.M.

IOC World Conference Prevention of Injury and Illness in Sport 2014 - Monaco

Does, H.T.D van der Recovery Kinetics during a 3-day tournament , Brink M.S.,& Lemmink K.A.P.M.

Annual meeting - European Congress of Sport Science 2013 - Barcelona

Dynamic ankle stability and ankle sprain occurence in elite ball team athletes: a one Does MSc, H. van der season prospective study. , Dallinga MSc, J., Benjaminse MSc, A.,Brink, dr. M., Visscher, prof. dr. C.& Lemmink, dr. K. Groningen Sports Medicine Symposium 2013 – Groningen

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Does MSc, H.T.D. van der Meten van explosiviteit bij top indoor balteamsporters , Brink, dr. M.S., Doeven MSc, S.H, Lemmink, dr. K.A.P.M. Dag van het Sportonderzoek 2012 – Den Haag

Does, H.T.D van der Individual variability in heart rate recovery after standardized sub maximal exercise , Brink M.S.,Visscher,C.& Lemmink K.A.P.M. Annual meeting - European Congress of Sport Science 2012 - Brugge

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506196-L-bw-vd Does Processed on: 17-11-2016 Previous SHARE Dissertations

506196-L-bw-vd Does Processed on: 17-11-2016 Previous SHARE dissertations

Research Institute SHARE

This thesis is published within the (Science in Healthy Ageing and healthcaRE) of the University Medical Center Groningen / University of Groningen. Further information regarding the institute and its research can be obtained from our internetsite: http://www.share.umcg.nl/

More recent theses can be found in the list below. 2016((co-) supervisors are between brackets)

Darvishian M

Real-world(prof E Hak, influenza prof ER van vaccine den Heuvel) effectiveness; new designs and methods to adjust for confounding and bias Berm EJJ

ȋ’”‘ˆ‹Žˆˆ‡”–ǡ’”‘ˆ ƒǡ†” ƒ”‹‰ȌOptimizing treatment with psychotropic agents through precision drug therapy; it is not about the mean Fugel H-J

(prof MJ Postma, dr M Nuijten, dr K Redekop) Economics of stratified medicine Salavati M

(profAssessing CP van gross der motorSchans, function, prof B Steenbergen, functional skills, dr A Waninge, and caregiver dr EAA assistance Rameckers)in children with cerebral palsy (CP) and cerebral palsy impairment (CPI)

Wierike SCM te

‘The’ pathway towards the elite level in Dutch basketball; a (profmultidimensional C Visscher, dr and MT longitudinalElferink- ‡•‡”Ȍ study on the development of talented youth basketball players Jacobs JJWM

(profGeneral R Sanderman, practitioner prof on anT van island. der Molen)How research and innovation help to improve primary care Küpers LK

(prof H Snieder, prof RP Stolk, dr E Corpeleijn) The first 1000 days and beyond

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Kuiper JS

(prof RC Oude Voshaar, prof RP Stolk, dr N Smidt) The importance of social relationships in the process of cognitive ageing Göhner, C

(prof SA Scherjon,prof E SchleuȾ‡”ǡ†” ƒƒ•ǡ†”ŽÚ• ŠȌ Placental particles in pregnancy and preeclampsia Vries AJ de

(prof RL Diercks, dr I van den Akker-Scheek, dr J Zwerver, dr H van der Worp)Patellar tendinopathy; causes, consequences and the use of orthoses

Holland B van

ȋ’”‘ˆ ‡‡ƒǡ’”‘ˆ”‘—™‡”ǡ†”‘‡”ǡ†”†‡‘‡”ȌPromotion of sustainable employment; occupational health in the meat processing industry

Otter13.04.2016 TA EXPAND

(prof KAPM Lemmink, prof RL Diercks, dr MS Brink) Monitoring endurance athletes; a multidisciplinary approach Bielderman JH

ȋ’”‘ˆ˜ƒ†‡” Šƒ•ǡ†” †‡ ”‡‡ˆǡ†”  Š‘—–ȌActive ageing and quality of life; community-dwelling older adults in deprived neighbourhoods Bijlsma MJ

(profAge-period-cohort E ƒǡ’”‘ˆƒ•–‡‡Žƒ†–ǡ†”  ƒ••‡Ȍ methodology; confounding by birth in cardiovascular pharmacoepidemiology Dingemans EAA

(profWorking CJIM after Henkens, retirement; dr ir H determinantsvan Solinge) and conzequences of bridge employment Jonge L de

(profData qualityIM van Langen,and methodology prof LTW inde studiesJong-van on den maternal Berg, dr medication MK Bakker) use in relation to congenital anomalies

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506196-L-bw-vd Does Processed on: 17-11-2016 Financial Support

506196-L-bw-vd Does Processed on: 17-11-2016 Financial Support

This thesis was financially supported by:

NOC*NSF

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