Background: The multiplicities of factors, which may contribute to injury from sporting activity, and the complexity of the relations among them, indicate that identifying causal mechanisms poses a challenge to epidemiologists. The identification of risk factors associated with the effect of the injury on subsequent participation may be as important in understanding how to reduce the burden of injuries on sports participants, as identifying factors associated with the injury incidence rate. Aim: The aim of this study was to develop a biomechanical, antbropometrical, physical, motor and injury epidemiology profile for elite U/19 rugby players. Design: A prospective cohort study. Subiects: In this study 77 elite rugby players were used during the first testing episode (October 2005). These players had just completed their school career and were selected to form part of the Rugby Institute of the University of North West. The U/19 first team members were (n = 31) tested again in July 2006. Two different profiles were established. Method: Once approval had been granted by both the players and by the Rugby Institute of the North West University, the players were submitted to a test battery. Anthropometric, Physical and Motor tests were done at the beginning of the season and the players re-tested at the end of the season. A Biomechanical and Postural Evaluation was done once-off at the beginning of the season. The necessary steps were taken to address existing shortcomings identified in the test subjects. After the results had been analysed, individual programmes were formulated, explained and implemented. The aim was to minimize the possible risk areas indicated by screening. Results: The results were statistically processed, recorded and compared with previous literature studies, according to both the total group and the different player positions - these are the tight five, the loose forwards, the halfbacks and the backs. The Anthropometrical, Physical and Motor testings showed a low or nil practical significant difference for the total group after a season of professional training and coaching, with slight differences between the player groups. The Biomechanical and Postural Evaluation proved the group to be dynamically overloaded with poor regional stability and musculature as far as the upper and lower limbs were concerned, with asymmetry and weak core stability of the spinal and pelvic region. A total of 184 injuries were reported over the season, with the lower limbs (58%) and upper limbs (23%) as the most commonly injured body parts; and sprains (22%) and strains (17%) the type of injury which occurred most often. The tight five (32%) had the highest injury rate, with the flanker (13%) the least injured player position. Conclusion: A profile for elite U/19 rugby players has been determined. This profile can be implemented in conjunction with similar findings in existing literature for future guidelines by coaches and the management to select a better team, to ensure a higher quality of performance and to prevent injuries. / Thesis (M.Ed.)--North-West University, Potchefstroom Campus, 2007.

Thesis (M.A.(Clinical Psychology)) -- University of Limpopo, 2015. / The effect of Cumulative Mild Head Injury (CMHI) in contact sports, such as rugby, is seen increasingly at school level where more and more injuries are reported. Research on CMHI in contact sport is needed specifically amongst previously disadvantaged groups where little or no research has taken place. The research is thus intended to seek a better understanding of CMHI in the contact sport of rugby specifically amongst amateur players. A quantitative research approach was utilised with a quasi-experimental research design. A sample of 18 student rugby players and 18 volleyball (non-contact sport) controls was used. In terms of mean performances the tests did not reveal a consistent pattern of deficits which is typically associated with the effects of Cumulative Mild Head Injuries. There were significant results however, in terms of variability that suggests potential deficits in attention among the rugby group. The results are therefore indicative of a poorer overall cognitive profile for the rugby playing group. It is concluded that the increased variability may be displayed in individuals who suffer CMHI at an earlier age.

Over the past 25 years, the role of motivation in sport has increasingly received attention in scientific research. A model that is central to this research, is Ryan and Deci’s (2000b) Self–determination Theory (SDT), which is based on the assumption that human behaviour is motivated by the extent to which it satisfies the needs for autonomy, competence and relatedness. Surprisingly little research has been done to date on the relation between self–determination and performance among South African rugby players. An improved understanding of the role of motivation in performance among university rugby players, as well as the role of bursary awards, can generate better knowledge and may help to identify, manage and motivate players better at an early stage. The goal of this study was to explore the relation between self–determination and performance among a group of university rugby players. The first objective was to establish whether there are performance differences between players who are intrinsically motivated (IM), extrinsically motivated (EM) and amotivated. A second objective was to establish whether players who receive bursaries are more intrinsically motivated, extrinsically motivated or amotivated, and how this relates to their performance. Participants were an availability sample of 51 u/19 and u/21 university rugby players of the North–West University Rugby Institute who completed the Behavioural Regulation in Sport Questionnaire (BRSQ) (Lonsdale et al., 2008) and who were assessed in terms of performance by themselves, the principal researcher, a sport scientist and the coach. Data was analysed by means of the Spearman ranking correlation coefficient, cluster analyses, the t–test and Chi Square test, to determine the differences in terms of performance between the intrinsically motivated, extrinsically motivated and amotivated participants, and also between bursary holders and non–bursary holders. Because an availability sample was used, the meaningfulness of results according to effect sizes and their guiding values were determined for practical meaningfulness, rather than focusing on statistical inference and p values. Firstly, it was found that IM correlates positively and practically meaningful with autonomous EM and that it correlates negatively (small to practically visible) with controlled EM and amotivation. Autonomous and controlled EM correlate negatively, and with a small effect. These correlations in general fit appropriately in with Ryan and Deci’s (2000b) self–determination continuum. It was found that IM, autonomous EM and bursary awards correlate positively with performance, in contrast with controlled EM and amotivation. It was indicated that both IM and autonomous EM could possibly contribute to a feeling of agency and subsequently to better performance. However, it is important to note that no cause–effect deductions can be made, and that the results cannot necessarily be generalised to other rugby players. The contribution of this study is that it indicates that all forms of EM are not necessarily bad for performance, and that autonomous EM and discerning bursary awards can appropriately motivate rugby players towards performance. The exact nature and mechanism according to which autonomous EM influences performance should, however, be investigated by means of larger random samples in future research. / Thesis (M.A. (Research Psychology))--North-West University, Potchefstroom Campus, 2011.

Over the past 25 years, the role of motivation in sport has increasingly received attention in scientific research. A model that is central to this research, is Ryan and Deci’s (2000b) Self–determination Theory (SDT), which is based on the assumption that human behaviour is motivated by the extent to which it satisfies the needs for autonomy, competence and relatedness. Surprisingly little research has been done to date on the relation between self–determination and performance among South African rugby players. An improved understanding of the role of motivation in performance among university rugby players, as well as the role of bursary awards, can generate better knowledge and may help to identify, manage and motivate players better at an early stage. The goal of this study was to explore the relation between self–determination and performance among a group of university rugby players. The first objective was to establish whether there are performance differences between players who are intrinsically motivated (IM), extrinsically motivated (EM) and amotivated. A second objective was to establish whether players who receive bursaries are more intrinsically motivated, extrinsically motivated or amotivated, and how this relates to their performance. Participants were an availability sample of 51 u/19 and u/21 university rugby players of the North–West University Rugby Institute who completed the Behavioural Regulation in Sport Questionnaire (BRSQ) (Lonsdale et al., 2008) and who were assessed in terms of performance by themselves, the principal researcher, a sport scientist and the coach. Data was analysed by means of the Spearman ranking correlation coefficient, cluster analyses, the t–test and Chi Square test, to determine the differences in terms of performance between the intrinsically motivated, extrinsically motivated and amotivated participants, and also between bursary holders and non–bursary holders. Because an availability sample was used, the meaningfulness of results according to effect sizes and their guiding values were determined for practical meaningfulness, rather than focusing on statistical inference and p values. Firstly, it was found that IM correlates positively and practically meaningful with autonomous EM and that it correlates negatively (small to practically visible) with controlled EM and amotivation. Autonomous and controlled EM correlate negatively, and with a small effect. These correlations in general fit appropriately in with Ryan and Deci’s (2000b) self–determination continuum. It was found that IM, autonomous EM and bursary awards correlate positively with performance, in contrast with controlled EM and amotivation. It was indicated that both IM and autonomous EM could possibly contribute to a feeling of agency and subsequently to better performance. However, it is important to note that no cause–effect deductions can be made, and that the results cannot necessarily be generalised to other rugby players. The contribution of this study is that it indicates that all forms of EM are not necessarily bad for performance, and that autonomous EM and discerning bursary awards can appropriately motivate rugby players towards performance. The exact nature and mechanism according to which autonomous EM influences performance should, however, be investigated by means of larger random samples in future research. / Thesis (M.A. (Research Psychology))--North-West University, Potchefstroom Campus, 2011.

M.A. / South Africans are known for their love of sports and rugby is one of the most popular sports in the country. Due to this nationwide love of rugby children are often exposed to the game from a very young age. However, children’s participation in competitive rugby is a complex matter. It is unclear whether children participate in rugby for the simple love of the game or because of the competitive culture that is dominant within South Africa. Numerous studies have expressed concerns about children’s participation in rugby due to the physical risks, the psychological stress that accompanies competitive sports, the emphasis on winning (pressure to perform) and the resultant disappointment of losing. Research has also demonstrated that elevated anxiety levels are an integral part of competitive sport participation and impact physiological and psychological behavioural responses. However, previous research has not focused on anxiety in relation to competitive sport participation in the South African context or on the impact that participation in competitive rugby has on children in South Africa. This study thus aimed to investigate the anxiety experienced by high school rugby players and determine the extent to which their involvement in competitive rugby contributes to this anxiety. A within-and-between, quasi-experimental design study was conducted to address this primary aim. Twenty (20) children participated in the study; 10 of the participants played high school rugby, while the remaining 10 participants were not involved in any sport.

The potential to track changes in training status and fitness levels of especially team sport participants by making use of more time efficient and accessible methods such as heart rate variability (HRV) and heart rate recovery (HRR) cannot be overlooked and needs to be considered. However, studies that have investigated this aspect in team sport participants are scarce. It is against this background that the main objectives of this study were firstly, to determine the relationships between HRV and HRR as well as the fitness levels of a cohort of university-level rugby players. The second objective was to determine the validity of the BioForce Heart Rate Variability System to determine the HRV of a cohort of university-level rugby players. Twenty-four university-level rugby players (age: 20.1 ± 0.41 years; body stature: 182.7 ± 6.2 cm; body mass: 89.7 ± 12.7 kg) of a South African university’s Rugby Institute participated in the first part of the study. During the test day players’ fasting baseline HRV (baseline HRV) values were taken. This was followed by the measurement of the post-breakfast HRV (Pre-Yo-Yo IR1 HRV). Players were then required to perform the Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1) while they were fitted with a portable Cosmed K4b2 gas analyser apparatus and a Fix Polar Heart Rate Transmitter Belt. After completion of the test, HRR was taken on 1 and 3 minutes and followed by the measurement of HRV (Post-Yo-Yo IR1 HRV). For the second part of the study a group of twenty u/21 university-level rugby players (age: 20.06 ± 0.40 years; body stature: 181.8 ± 5.5 cm; body mass: 91.1 ± 10.7 kg) of a South African university’s Rugby Institute were recruited to participate in this study. HRV was measured simultaneously by the Actiheart monitor system as well as the BioForce Heart Rate Variability System over three times periods: during the morning in a fasting state just after players had woken up (baseline); in the morning just after the players ate breakfast (pre-anaerobic); after completion of a high-intensity anaerobic training session (post-anaerobic) and after completion of a 20 min recovery session (post-recovery). Significant correlations (p ≤ 0.05) were found between Pre-Yo-Yo IR1 HRV and heart rate (HR) at the respiratory compensation point (RCP-HR (bpm)) (r = -0.468) as well as oxygen uptake at the RCP (RCP- 2max VO (% of 2max VO )) (r = 0.476), respectively. A forward stepwise regression analysis showed that HR at ventilatory threshold 1 (VT1-HR (bpm)) contributed significantly (p ≤ 0.05) to the post-Yo-Yo IR1 HRV with a variance of 39.8%. Final Yo-Yo IR1 level also contributed significantly (p ≤ 0.05) to 3 minute post-Yo-Yo IR1 HRR with a variance of 16.5%. For the second part of the study the majority of significant relationships (p < 0.05) between the Actiheart and Bioforce obtained HRV results were observed for the post-recovery period (Mean RR, SDNN, RMSSD and Peak LF power), followed by the pre-anaerobic period (Mean R-R and SDNN) and the baseline period (LF:HF ratio). No significant relationships were observed between the HRV results of the two apparatuses during the post-anaerobic period. In conclusion, HRV and HRR may have the potential to act as affordable and easy measurement tools of team sport participants’ fitness levels. However, the study results suggested that the BioForce Heart Rate Variability System that is used to obtain team sport participants’ HRV is especially valid to determine HRV after recovery periods that follow hard training sessions. The results do however cast a shadow of doubt over the accuracy of this apparatus when used directly after hard training sessions. / MSc (Sport Science), North-West University, Potchefstroom Campus, 2014

The potential to track changes in training status and fitness levels of especially team sport participants by making use of more time efficient and accessible methods such as heart rate variability (HRV) and heart rate recovery (HRR) cannot be overlooked and needs to be considered. However, studies that have investigated this aspect in team sport participants are scarce. It is against this background that the main objectives of this study were firstly, to determine the relationships between HRV and HRR as well as the fitness levels of a cohort of university-level rugby players. The second objective was to determine the validity of the BioForce Heart Rate Variability System to determine the HRV of a cohort of university-level rugby players. Twenty-four university-level rugby players (age: 20.1 ± 0.41 years; body stature: 182.7 ± 6.2 cm; body mass: 89.7 ± 12.7 kg) of a South African university’s Rugby Institute participated in the first part of the study. During the test day players’ fasting baseline HRV (baseline HRV) values were taken. This was followed by the measurement of the post-breakfast HRV (Pre-Yo-Yo IR1 HRV). Players were then required to perform the Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1) while they were fitted with a portable Cosmed K4b2 gas analyser apparatus and a Fix Polar Heart Rate Transmitter Belt. After completion of the test, HRR was taken on 1 and 3 minutes and followed by the measurement of HRV (Post-Yo-Yo IR1 HRV). For the second part of the study a group of twenty u/21 university-level rugby players (age: 20.06 ± 0.40 years; body stature: 181.8 ± 5.5 cm; body mass: 91.1 ± 10.7 kg) of a South African university’s Rugby Institute were recruited to participate in this study. HRV was measured simultaneously by the Actiheart monitor system as well as the BioForce Heart Rate Variability System over three times periods: during the morning in a fasting state just after players had woken up (baseline); in the morning just after the players ate breakfast (pre-anaerobic); after completion of a high-intensity anaerobic training session (post-anaerobic) and after completion of a 20 min recovery session (post-recovery). Significant correlations (p ≤ 0.05) were found between Pre-Yo-Yo IR1 HRV and heart rate (HR) at the respiratory compensation point (RCP-HR (bpm)) (r = -0.468) as well as oxygen uptake at the RCP (RCP- 2max VO (% of 2max VO )) (r = 0.476), respectively. A forward stepwise regression analysis showed that HR at ventilatory threshold 1 (VT1-HR (bpm)) contributed significantly (p ≤ 0.05) to the post-Yo-Yo IR1 HRV with a variance of 39.8%. Final Yo-Yo IR1 level also contributed significantly (p ≤ 0.05) to 3 minute post-Yo-Yo IR1 HRR with a variance of 16.5%. For the second part of the study the majority of significant relationships (p < 0.05) between the Actiheart and Bioforce obtained HRV results were observed for the post-recovery period (Mean RR, SDNN, RMSSD and Peak LF power), followed by the pre-anaerobic period (Mean R-R and SDNN) and the baseline period (LF:HF ratio). No significant relationships were observed between the HRV results of the two apparatuses during the post-anaerobic period. In conclusion, HRV and HRR may have the potential to act as affordable and easy measurement tools of team sport participants’ fitness levels. However, the study results suggested that the BioForce Heart Rate Variability System that is used to obtain team sport participants’ HRV is especially valid to determine HRV after recovery periods that follow hard training sessions. The results do however cast a shadow of doubt over the accuracy of this apparatus when used directly after hard training sessions. / MSc (Sport Science), North-West University, Potchefstroom Campus, 2014