Article Text

The BokSmart intervention programme is associated with improvements in injury prevention behaviours of rugby union players: an ecological cross-sectional study
  1. James C Brown1,2,
  2. Sugnet Gardner-Lubbe3,
  3. Michael Ian Lambert1,
  4. Willem Van Mechelen1,2,
  5. Evert Verhagen2
  1. 1UCT/MRC Research Unit for Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
  2. 2Department of Public & Occupational Health and EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
  3. 3Department of Statistical Sciences, Faculty of Science, University of Cape Town, Cape Town, South Africa
  1. Correspondence to Mr James C Brown, UCT/MRC Research Unit for Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences. University of Cape Town, Cape Town, South Africa; jamesbrown06{at}


Background/aim Participants of rugby union (‘rugby’) have an above-average risk of injury compared with other popular sports. Thus, BokSmart, a nationwide injury prevention programme for rugby, was introduced in South Africa in 2009. Improvements in injury-preventing behaviour of players are critical to the success of an intervention. The aim of this study was to assess whether BokSmart has been associated with improvements in rugby player behaviour.

Methods An anonymous knowledge, attitude and self-reported behaviour questionnaire was completed by junior (under-18) and senior (adult) tournament players who attended merit-based tournaments (2008–2012). The questionnaire was completed by 2279 junior players (99% of total estimated population) from 111 teams and 1642 senior players (96% of population) from 81 teams. A generalised linear model assessed behavioural changes over this time period.

Results Nine (50%) of the behaviours improved significantly (p<0.005) between 2008 and 2012 and the remaining behaviours remained unchanged. Improved behaviours included the targeted, catastrophic injury-preventing behaviours of the intervention: practising of tackling (adjusted overall improvement in odds: 56%) and scrummaging, in forwards only (58%), techniques. Other behaviours that improved significantly were postinjury compression and elevation as well as alcohol avoidance, mouthguard use (training and matches) and cooling down (training and matches). Practising of safe rucking techniques; warming up before training/matches; ice use; heat, massage and alcohol avoidance postinjury; and preseason and off-season conditioning remained unchanged.

Conclusions BokSmart is associated with improvements in targeted injury-preventing behaviours in players. Future research should ascertain whether self-reported behaviours reflect actual behaviour and whether the observed improvements translate into changes in injury rates.

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Rugby union (henceforth ‘rugby’) is one of the most popular team sports globally.1 In comparison to other popular team sports, rugby carries a relatively high risk of injury.2 ,3 As a result, there are numerous examples of injury prevention efforts that have been evaluated for their effectiveness at reducing this injury risk and include protective equipment trials,4 law changes5 ,6 and nationwide injury prevention programmes such as RugbySmart of New Zealand.7

Player behaviour has been identified as the ‘key factor’ underlying the success of injury prevention in sport.8 However, there is only one example of an injury prevention programme for rugby where the behaviour of the intervention target has been assessed.7 In that study, the RugbySmart programme was associated with improvements in self-reported injury-preventing behaviours, concomitant with the reduction in injury rates in the same group of players.7

Thus, the South African Rugby Union (SARU) adapted and launched BokSmart as a nationwide injury prevention programme in July 2009.9 The programme aims to educate all rugby coaches and referees in safe and effective injury prevention methods for rugby.9 SARU achieved this by teaching BokSmart educators who then disseminate the BokSmart content to all rugby coaches and referees. Through ongoing injury surveillance by SARU, the content focuses on high-risk areas for catastrophic injuries.9 Based on the results of this surveillance, the scrum and tackle (ball carrying and tackling) phases are discussed in depth during the BokSmart course. The other content ranges from hydration and nutrition strategies through to the identification and management of catastrophic injuries (including concussion). Since January 2010, it has been compulsory for all South African coaches and referees to attend a biennial BokSmart course. Coaches and referees are considered key role-players for injury prevention in rugby.7 By educating these key role-players in South Africa, it was the expectation of BokSmart that the injury prevention behaviour of the players under the control of these coaches and referees would improve, as observed in the New Zealand evaluation.7

Therefore, the aim of this study was to assess whether player behaviour has improved over a period of 5 years since the launch of the BokSmart nationwide injury prevention programme.


Study design and population

Data for this ecological study were collected through the BokSmart programme (, which is a joint initiative between SARU ( and the Chris Burger/Petro Jackson Player's Fund (CBPJPF) ( CBPJPF is a non-profit public benefit organisation, developed to aid players who have been permanently disabled while playing rugby in South Africa. Permission to analyse the data was obtained, with SARU's permission, from the UCT Human Research Ethics Committee.

Between 2008 and 2012, SARU administered a ‘knowledge, attitude and behaviour (KAB)’ questionnaire (see online supplementary appendix II) annually to players at a junior and senior SARU tournament. Both tournaments were attended by teams representing each of the 14 rugby unions in South Africa. As attendance at a BokSmart course has been a mandatory prerequisite for coaching since January 2010, it can be assumed that by 2011 and 2012 all coaches of the surveyed players had attended a course.

The questionnaire was administered at a pretournament meeting and completed anonymously by the players. The players were high-level amateur players competing at a provincial tournament in their respective age groups: under-18 (junior) and open/adult (senior). It is important to note that the same group of players was not followed up each year, but rather the players attending these two tournaments between 2008 and 2012 were measured at each time point.

Between 2008 and 2012, a total of 112 junior and 84 senior teams attended these tournaments and were asked to complete the KAB questionnaire. Of these teams, 111 (99%) and 81 (96%) completed them in those age groups, respectively. On average, a team squad comprised 22 players, providing an estimated 4224 players from the 192 compliant teams. In reality, there were 2279 junior and 1642 senior players that completed the KAB questionnaire between 2008 and 2012, providing a total of 3921 completed questionnaires (93% of total estimated population). No information was available for those players at the tournament who did not attend the meeting at which the questionnaires were completed.

KAB questionnaire

Although the KAB questionnaire was not validated prior to use in this study, it was developed through use in the RugbySmart evaluation in New Zealand over a 10-year period, which was considered sufficient piloting by SARU for the BokSmart evaluation (see online supplementary appendix II).7 The players were not asked to disclose their identity when they completed the questionnaire to improve the integrity of answers by eliminating fear of consequential action based on their answers. Thus, it is possible that some of the same players could be in the dataset more than once if they had competed in the tournament in consecutive years. There is however no way to assess this.

While it is termed a ‘KAB’ questionnaire, the majority of questions actually investigate knowledge, self-reported behaviour (henceforth ‘behaviour’) and perceptions (not attitude) of injury prevention (primary and secondary) practices of the players. All questions of the KAB questionnaire (see online supplementary appendix I) were grouped into five categories: demographics, behaviour, perceptions, education and knowledge (see online supplementary appendix II). For example, the ‘demographics’ category included questions on age, ethnicity and year of completion; ‘behaviour’ included questions on how players managed their previous injuries; and ‘perceptions/attitudes’ included questions on which injury prevention practices were perceived to be important in reducing injury. The possible answers for each question of the KAB questionnaire (see online supplementary appendix I) are also provided in online supplementary appendix II.

The 18 injury-preventing behaviours of the KAB questionnaire were subsequently coded as ‘correct’ or ‘incorrect’ behaviours, based on the respondent's answers and what BokSmart programme implementers (SARU) deemed as ‘correct’. Besides those who were subsequently coded to have behaved incorrectly, the ‘incorrect’ category also included respondents who had not answered a particular question (‘no answer’). This decision was made in conjunction with SARU prior to the analyses. The rationale for this categorisation was that the current research question focused on ‘correct’ (as determined by SARU) answers: thus all other options were deemed ‘incorrect’. If a particular questionnaire comprised mainly (>90%) ‘no answer’ answers, such a questionnaire was removed from the analyses. The 18 ‘specific’ behaviours (indicated in parentheses) were grouped based on expert opinion under five ‘summary’ behaviours (see online supplementary appendix II): injury management (ice, elevation and compression use; and alcohol, heat, massage and exercise avoidance, postinjury), mouthguard use (at training and matches), stretching (warming up and cooling down at training and matches), safe techniques (tackling, rucking, scrummaging) and conditioning (preseason and off-season). Besides this grouping, the BokSmart programme also identified 2 of these 18 behaviours as ‘targeted behaviours’ due to their potential relationship with catastrophic head, neck and spine injuries: that is, practising of safe tackling and scrummaging techniques.


Although analyses have been performed on knowledge and perception components of these data, it was not possible to include these results in this article. A subsequent article will describe the relationships between these knowledge and perception components.

As all behaviour questions had either a ‘correct’ (=1) or ‘incorrect’ (=0) outcome, they were therefore modelled with a Bernoulli distribution.10 A logistic regression model was then fitted for each behaviour to assess whether the proportion of correct behaviours had changed over the time period: 2008–2012. Although the analyses could have been conducted as ‘before/after’ the launch of the intervention, it was decided that using ‘year’ as a continuous predictor might be more informative for providing feedback on the intervention.

Besides ‘year’ (2008–2012), five other potential predictors were considered: age group, ‘age’ (junior, senior); ethnicity, as questioned by SARU (Caucasian, African, mixed ancestry, other); Rugby Provincial Union, ‘union’ (n=14); position (back, forward, back/forward); perception of whether or not coaches should take a safety course, ‘safety’; and perception of who was important to preventing injuries, ‘role’ (‘coach’, ‘referee’, ‘player’ or a combination of these options). The predictor ‘role’ was a combination of the three questions for coach, referee and player as the answers were virtually identical for these three questions (data not shown).

A stepwise model selection approach was applied where Akaike's information criterion11 was used to select the predictors to include in each model to obtain the most parsimonious model for each of the 23 behaviours (18 behaviours and their 5 summary behaviours).

Once this behavioural model was established, a χ2 test was used to assess which of the predictors were contributing statistically significantly (p<0.05) to the behaviour. At this point, any non-significant predictors/confounders (p>0.05) were removed from the model and the model was refitted to produce a final parsimonious and statistically robust model. Therefore, whenever a behaviour is stated to be ‘significantly different’ over the 2008–2012 time period, this statement is made at the 95% significance level (p<0.05). All ‘significantly different’ findings had 95% CI lower bounds larger than one: these data are also shown for interpretation.

In summary, the proportion change in correct behaviour that is described in the ‘Results’ section has accounted for these other five factors if they were discovered to be significant confounders of the behaviour's relationship with year. The specific effects of these other five factors are not described here.

Both unadjusted and adjusted (taking into account confounders described previously) correct behaviour proportions are reported for the time period (2008–2012) of interest. Note that the adjusted change over time is shown as an average annual change as the magnitude of absolute year-to-year proportional change was different depending on the relative proportions of the confounders for each particular behaviour. The overall change for the 5 years is calculated by extrapolating this average annual change.


Study population

The average age of junior players was 17±1 years (mean±SD), while senior players were 25±4 years of age (table 1). At the senior tournament, the majority of players were Caucasian (64%), while this ethnicity comprised just less than half of the respondents at the junior tournament. African players comprised 34%/15%; ‘mixed ancestry’ players comprised 19%/21% and ‘other’ comprised 1% at the junior/senior tournaments.

Table 1

Details of the junior and senior sample, including average age and proportions of white players, forward positions and those who had never had a sprain, previously

Player behaviour: 2008–2012

Overall, 9 of the 18 (50%) specific behaviours and 4 of the 5 (80%) summary behaviours improved significantly, after adjustment (table 2 and figure 1), while the remaining behaviours did not change significantly.

Table 2

Summarised and specific correct behaviour proportions in 2008 and 2012

Figure 1

Changes in odds of correct behaviour proportions for injury management, mouthguard use, training of safe techniques (safe techniques), stretching and conditioning.

Injury management

Although the unadjusted proportion of correct behaviours deteriorated by −4% (88% to 84%), the adjusted OR improved significantly between 2008 and 2012 (annual change in odds: 1.07 times (1.04 to 1.11)) (table 2). This was due, in part, to significant improvements in the adjusted odds of compression of an injured limb (annual change of 1.09 times (1.00 to 1.18)), elevation of an injured limb (annual change of 1.13 (1.03 to 1.21)) and alcohol avoidance postinjury (annual change of 1.13 (1.03 to 1.23)) (figure 1). The alcohol avoidance was very high in juniors. All other adjusted injury management behaviours—ice use on the injured limb and heat and exercise avoidance postinjury—did not change significantly between 2008 and 2012.

Mouthguard use

The unadjusted proportion of correct behaviours for the summary behaviour improved by 2% (47% to 49%) and indicates that mouthguards were being used by less than half of all players at both training and matches between 2008 and 2012 (table 2 and figure 1). However, the adjusted OR of the summary behaviour improved significantly (annual change in odds: 1.08 times (1.05 to 1.12)) from 2008 to 2012 (table 1). This was due to large significant improvements in the adjusted OR of mouthguard use at both training (annual change: 1.10 times (1.04 to 1.16)) and matches (annual change: 1.08 times (1.03 to 1.13)).


While the unadjusted proportion of correct summary behaviour only improved by 0.5% (98.9% to 99.4%) the adjusted OR improved significantly (annual change in odds: 1.03 times (1.00 to 1.06)) from 2008 to 2012 (table 2 and figure 1). This improvement in the adjusted summary behaviour was due to significant improvements in the adjusted odds of cooling down after training (annual change: 1.05 times (1.00 to 1.11)) and matches (annual change: 1.08 (1.02 to 1.13)). The adjusted odds of warming-up behaviours did not change significantly at training or matches between 2008 and 2012 (table 2 and figure 1).

Safe techniques

The unadjusted proportion of correct summary behaviours improved by 2% (78% to 80%) and the adjusted odds improved significantly (annual change in odds: 1.06 (1.02 to 1.09)) from 2008 to 2012. This was due to significant improvements in adjusted behaviours of practising of safe tackle techniques in all players (annual change: 1.09 times (1.03 to 1.14)) and safe scrummaging techniques in forwards (OR 58% larger in 2012 than 2008, annual change: 1.08 (1.00 to 1.17)), but not safe rucking techniques in all players (not significantly different over the same time period).

Physical conditioning

The unadjusted summary behaviour deteriorated by 14% between 2008 and 2012, although the adjusted change was not significantly different over this time period. Both off-season and preseason physical conditioning adjusted odds also decreased, although not significantly, between 2008 and 2012 (table 2 and figure 1).


The main finding of this study was that the implementation of the BokSmart programme has been associated with improvements in targeted catastrophic injury-preventing behaviours (practising safe tackling and scrummaging techniques) of players between 2008 and 2012. These two behaviours were identified as ‘targeted’ by SARU based on the focus of the content included in their BokSmart programme.9 The evaluation of RugbySmart7 also observed improvements in the proportion of these two correct behaviours (safe tackling and scrummaging) in players over a 10-year period: these two behaviours were linked to the concomitant reduction in injury rates observed over the same study period.7 Subsequent to this evaluation, improvements in behaviour of the intervention target have been identified as critical to the success of any injury prevention programme, not just rugby.8

In total, the New Zealand RugbySmart programme evaluated 5 of the 18 behaviours from their KAB questionnaire: (1) training of safe rucking techniques, (2) training of safe tackling techniques, (3) training of safe scrummaging techniques (forwards only), (4) warming up and (5) cooling down. Of these five, only warming up did not improve over the 10-year evaluation (1996–2005) in New Zealand. However, this lack of a finding for warming up was ascribed to the high proportion of players already performing this behaviour correctly at the start of the evaluation (table 3).

Table 3

Summary of whether adjusted change in odds of correct behaviours improved or remained unchanged in players between 2008 and 2012

Importantly, the KAB questionnaire (see online supplementary appendix I) was designed based upon the assumption that 18 behaviours are potentially capable of affecting injury risk in rugby players. While it is well supported in the literature that behaviour does underpin injury prevention interventions,8 it is possible that not all 18 of these 18 behaviours are equally important for injury prevention in rugby. Of the non-targeted behaviours, only mouthguard use has evidence for, but not against, its relationship with the prevention of injury (dental claims) in rugby.12 The adjusted odds of mouthguard use for training/matches improved significantly in this evaluation, although the unadjusted proportions were still <50% in 2012 (training: 32.1%; matches: 46.7%). This should be a concern for BokSmart implementers. Similarly, the finding that just more than half of all players warm-up before matches should also be of concern for implementers, despite this behaviour having equivocal evidence for its relationship with injury prevention.13

Other adjusted odds of correct behaviour that did not improve in this 5-year evaluation were ice use; heat, alcohol, exercise and massage avoidance; warming up before matches and training; and preseason and off-season conditioning. Of these, only preseason and off-season conditioning, and warming up before training had a possible explanation for a lack of a finding with high proportions of correct behaviour at baseline (2008). It is unclear whether these behaviours are related to injury rates, and thus whether BokSmart should be concerned with this finding. However, future BokSmart content should focus on those that are clearly associated with injury prevention evidence in the most recent literature.

The present study has a number of limitations. The behaviour measure was self-reported, which means that the measure was not reflective of actual behaviour. This study was also not longitudinal in design—the improvement in behaviour was only at a population, and not individual, level. Also, the improvements may not only be as a result of BokSmart. However, nationwide interventions such as the BokSmart programme are concerned with effectiveness rather than efficacy and thus a population-based improvement is important to the success of the intervention.14 Another limitation was the possibility that the same players were included in more than 1 year of assessment: due to the questionnaires being anonymous (to increase integrity of answers), this factor would be impossible to assess. However, due to the age-based and merit-based selection criteria for these tournaments, it is unlikely that this was applicable to a large proportion. Also, due to the unspecific wording of the question (see online supplementary appendix II), the possible confounding effect of a previous injury on a behavioural outcome could not be accounted for statistically. Possibly the most important limitation of this study is that it is not known whether an improvement in correct behaviour can cause a reduction in injury rates. Although this causal link was implied by the comparable evaluation of RugbySmart, the effect may be different in South Africa. Through the concomitant injury surveillance project that SARU began at these tournaments in 2011, it is anticipated that the causal link can be investigated by 2015. A particular strength of the present data was the high response rates of the questionnaire: 99% and 96% of the estimated total populations in junior and senior players, respectively. By comparison, the RugbySmart evaluation had response rates between 57% and 83%.7

‘Helmets for Kids’ in Viet Nam

Nearly 3000 helmets were donated to primary school children in Quang Nam Province through the Asia Injury Prevention (AIP) Foundation's Helmet for Kids programme, sponsored by Johnson & Johnson. The programme targets 44 primary schools in 4 provinces that have agreed to implement the National Child Helmet Action Plan. The Action Plan coordinated by AIP aims to achieve a 80% child helmet-wearing rate by 2016. (Noted by IBP)

Injury prevention programmes unpopular with high school coaches

Fewer than 10% of high school coaches implement injury prevention programmes as designed. Only half were aware of the programmes, but many believe they are too complex or do not work. Source: J Sci Med Sport 2015. (Noted by IBP)

Police arrest road rage suspect

A woman in Las Vegas was shot after an episode of road rage. Apparently the victim and her armed 22-year-old son followed a car she believed had been involved in a road rage incident earlier that night. Later, they were they were shot at by someone inside the car and the son returned fire ‘to protect my family’. (Noted by IBP)

Road rage Montreal-style

Not to be outdone, a Montreal driver with family aboard chased after a driver who had cut him off and blocked his path. The offender threatened his opponent with a running chainsaw. (Noted by IBP)

In conclusion, the BokSmart programme was found to be associated with improvements in targeted injury prevention behaviour in players: practising of safe tackling and scrummaging (forwards only) techniques. Future research needs to establish whether these behavioural improvements are truly longitudinal and consistent with the player’s coaches and referees. Furthermore, future research should also assess whether these improvements in targeted injury-preventing behaviours translate into reductions in injury rates in these players.

What is already knownon the subject?

  • The RugbySmart nationwide injury prevention programme was able to reduce general and catastrophic injury rates.

  • According to programme implementers, the ability of RugbySmart to improve targeted injury prevention behaviours in players was critical to the success of the programme.

  • RugbySmart was developed for and evaluated in New Zealand—a developed, first-world country with suitable infrastructure to support such an intervention.

What this study adds?

  • BokSmart, an adapted version of RugbySmart, was adapted for South Africa—a developing country with enormous socioeconomic disparities among rugby-playing populations.

  • Despite these challenges, the implementation of BokSmart was associated with improvements in players’ targeted behaviours (training of safe scrummaging and tackling techniques) between 2008 and 2012.

  • Improvement in players’ behaviour is vital to the overall success of BokSmart, which is to reduce catastrophic injuries in players.


The authors thank Dr Wayne Viljoen (BokSmart manager) and Mr Clint Readhead (SARU medical manager) for the collection and permission to analyse these data. Furthermore, the authors would like to thank Dr Simon Gianotti, Dr Ken Quarrie and Mr Richard Skelly for their advice, based on their involvement in the RugbySmart programme.


Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

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  • Contributors SG-L provided all the statistical analyses, based on the research question that was decided upon by MIL, WVM and EV. JCB wrote the article. All other authors made edits to the manuscript.

  • Funding JCB receives PhD funding from the SAVUSA/NRF Desmond Tutu Doctoral Programme.

  • Competing interests None.

  • Ethics approval UCT Human Research Ethics Committee.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Access to depersonalised data, which are stored by SARU, may be applied for through JB and ML.