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The use of head kinematic measurement devices has recently proliferated owing to technology advances that make such measurement more feasible. In parallel, demand to understand the biomechanics of head impacts and injury in sports and the military has increased as the burden of such loading on the brain has received focused attention. As a result, the field has matured to the point of needing methodological guidelines to improve the rigor and consistency of research and reduce the risk of scientific bias. To this end, a diverse group of scientists undertook a comprehensive effort to define current best practices in head kinematic measurement, culminating in a series of manuscripts outlining consensus methodologies and companion summary statements. Summary statements were discussed, revised, and voted upon at the Consensus Head Acceleration Measurement Practices (CHAMP) Conference in March 2022. This manuscript summarizes the motivation and methods of the consensus process and introduces recommended reporting checklists to be used to increase transparency and rigor of future experimental design and publication of work in this field. The checklists provide an accessible means for researchers to apply the best practices summarized in the companion manuscripts when reporting studies utilizing head kinematic measurement in sport and military settings.

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This study aimed to 1) develop a consensus (≥70% agreement between experts) on injury risk factors specific to women playing rugby league, 2) establish the importance of the identified injury risk factors and the feasibility of mitigating these risk factors and 3) establish context specific barriers to injury risk management. Aim 1: A Delphi panel, consisting of 12 experts in rugby league and injury (e.g., physiotherapists, research scientists) were asked to identify injury risk factors specific to women playing rugby league. Aim 2: seven coaches of women's rugby league teams were asked to rate each risk factor that achieved consensus by their importance and feasibility to manage. Aim 3: Coaches reported barriers which restrict injury risk factor mitigation. Of the 53 injury risk factors which achieved consensus, the five injury risk factors with the highest combination of importance and feasibility ratings were: "poor tackle technique", "a lack of pre-season intensity", "training session are too short", "the current medical standards", and "limited access to physiotherapists". Following the identification of injury risk factors, their feasibility to manage and context specific barriers, this study proposes three constraint driven, integrated solutions which may reduce the barriers which limit injury risk factor management.

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BACKGROUND: Youth flag football participation has rapidly grown and is a potentially safer alternative to tackle football. However, limited research has quantitatively assessed youth flag football head impact biomechanics. PURPOSE: To describe head impact biomechanics outcomes in youth flag football and explore factors associated with head impact magnitudes. STUDY DESIGN: Cross-sectional study; Level of evidence, 3. METHODS: We monitored 52 player-seasons among 48 male flag football players (mean ± SD; age, 9.4 ± 1.1 years; height, 138.6 ± 9.5 cm; mass, 34.7 ± 9.2 kg) across 3 seasons using head impact sensors during practices and games. Sensors recorded head impact frequencies, peak linear (g) and rotational (rad/s2) acceleration, and estimated impact location. Impact rates (IRs) were calculated as 1 impact per 10 player-exposures; IR ratios (IRRs) were used to compare season, event type, and age group IRs; and 95% CIs were calculated for IRs and IRRs. Weekly and seasonal cumulative head impact frequencies and magnitudes were calculated. Mixed-model regression models examined the association between player characteristics, event type, and seasons and peak linear and rotational accelerations. RESULTS: A total of 429 head impacts from 604 exposures occurred across the study period (IR, 7.10; 95% CI, 4.81-10.50). Weekly and seasonal cumulative median head impact frequencies were 1.00 (range, 0-2.63) and 7.50 (range, 0-21.00), respectively. The most frequent estimated head impact locations were the skull base (n = 96; 22.4%), top of the head (n = 74; 17.2%), and back of the head (n = 66; 15.4%). The combined event type IRs differed among the 3 seasons (IRR range, 1.45-2.68). Games produced greater IRs (IRR, 1.24; 95% CI, 1.01-1.53) and peak linear acceleration (mean difference, 5.69g; P = .008) than did practices. Older players demonstrated greater combined event-type IRs (IRR, 1.46; 95% CI, 1.12-1.90) and increased head impact magnitudes than did younger players, with every 1-year age increase associated with a 3.78g and 602.81-rad/s2 increase in peak linear and rotational acceleration magnitude, respectively (P≤ .005). CONCLUSION: Head IRs and magnitudes varied across seasons, thus highlighting multiple season and cohort data are valuable when providing estimates. Head IRs were relatively low across seasons, while linear and rotational acceleration magnitudes were relatively high.

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BACKGROUND: This study determined the effect of video-verified collision characteristics on head impact magnitudes in male youth tackle football. METHODS: Participants (n = 23, age = 10.9 ± 0.3 years, height = 150.0 ± 8.3 cm, mass = 41.6 ± 8.4 kg) wore Triax Sim-G sensors throughout the fall 2019 season. Ten filmed games were used to identify nine different collision characteristics: mechanism, preparedness, head direction, struck versus striking activity, stance, play type, closing distance, penalty, and quarter. Random-effects general linear models and Cohen d effect sizes were used to examine differences in log-transformed peak linear (PLA; g) and rotational (PRA; rad/s2) accelerations across characteristics. The 10 games produced 533 total video-verified impacts and 23.2 ± 7.2 impacts per athlete. RESULTS: PLA (P range: 0.107 to 0.923) and PRA (P range: 0.057 to 0.768) did not differ across characteristics. Struck players (3370 rads/s2, 95% confidence interval [CI] = 2986 to 3808) had a small effect for higher PRA compared with striking players (3037 rads/s2, 95% CI = 2713 to 3404, d = 0.251), but negligible effect for simultaneous struck-striking players (3340 rad/s2, 95% CI = 2945 to 3792, d = 0.018). Fourth quarter impacts (3490 rads/s2, 95% CI = 3083 to 3951) had a small effect for higher PRA compared with first (2945 rads/s2, 95% CI = 2596 to 3337, d = 0.404), second (3196 rads/s2, 95% CI = 2832 to 3604, d = 0.219), and third quarters (3241 rads/s2, 95% CI = 2841 to 3699, d = 0.144). CONCLUSION: Youth tackle football characteristics did not significantly affect head impact magnitudes during games. More research is needed to explore additional factors that could be modified for sport safety rather than mitigating impact mechanism.

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This study examined the swimming competence of primary school children, and how it was related to swimming activity, non-fatal aquatic events, and demographic factors. Primary school students (N = 4959; female = 2705, male = 2241; age range = 5 to 14 years) across 28 schools in the 15 districts of Hong Kong completed the Swimming Competence Questionnaire, and questions about their swimming experience, non-fatal aquatic events, and demographic variables. Descriptive statistics showed that over 60% of children could swim more than 5m, but less than 50% could swim over 25m. Over 50% of children were able to perform some basic swimming skills (e.g., holding breath underwater, floating, poolside/kickboard kicking, and treading water). Swimming competence was positively predicted by the demographic factors (i.e., age, sex, family income, and parents' highest education level), swimming experience, learning experience, and swimming location. Treading water was the only factor of swimming competence that established asignificant negative association with non-fatal aquatic events. Current results can be used to target key groups to improve children's swimming competence and reduce non-fatal aquatic events; children from lower socio-economic backgrounds and with less swimming experience should be encouraged to participate in more formal learn to swim lessons.

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Sport makes an important contribution to the physical, psychological and emotional well-being of Australians. The economic contribution of sport is equivalent to 2-3% of Gross Domestic Product (GDP). The COVID-19 pandemic has had devastating effects on communities globally, leading to significant restrictions on all sectors of society, including sport. Resumption of sport can significantly contribute to the re-establishment of normality in Australian society. The Australian Institute of Sport (AIS), in consultation with sport partners (National Institute Network (NIN) Directors, NIN Chief Medical Officers (CMOs), National Sporting Organisation (NSO) Presidents, NSO Performance Directors and NSO CMOs), has developed a framework to inform the resumption of sport. National Principles for Resumption of Sport were used as a guide in the development of 'the AIS Framework for Rebooting Sport in a COVID-19 Environment' (the AIS Framework); and based on current best evidence, and guidelines from the Australian Federal Government, extrapolated into the sporting context by specialists in sport and exercise medicine, infectious diseases and public health. The principles outlined in this document apply to high performance/professional, community and individual passive (non-contact) sport. The AIS Framework is a timely tool of minimum baseline of standards, for 'how' reintroduction of sport activity will occur in a cautious and methodical manner, based on the best available evidence to optimise athlete and community safety. Decisions regarding the timing of resumption (the 'when') of sporting activity must be made in close consultation with Federal, State/Territory and/or Local Public Health Authorities. The priority at all times must be to preserve public health, minimising the risk of community transmission.

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CONTEXT: Sudden death in sport at the high school and collegiate levels has been described extensively in the literature. However, few epidemiologic data exist on the incidence of sudden death specifically in American youth sport before secondary school athletics. OBJECTIVE: To describe the epidemiology of sudden death in organized youth sports in the United States from 2007 through 2015. DESIGN: Descriptive epidemiology study. SETTING: Organized American youth sports. PATIENTS OR OTHER PARTICIPANTS: Cases of sudden death that occurred in youth athletes 17 years of age and younger in non-high school organized sports were included. DATA COLLECTION AND ANALYSIS: Information on sudden deaths between August 1, 2007, and December 31, 2015, was obtained via LexisNexis and other publicly available news or media reports. Total youth sport participation rates from 2007 to 2015 were provided by the Sport & Fitness Industry Association. Athlete age, sex, sport, level of play, event type, date of death, setting, and official and speculated causes of death were examined. Data are presented as deaths per year, percentage of total sudden deaths, and deaths per 10 million participants. RESULTS: From 2007 to 2015, 45 sudden deaths were reported in American youth sports. The mean age of patients was 13 ± 2 years. The overall incidence rate was 1.83 deaths/10 million athlete-years. Males experienced a greater number of sudden deaths than females (n = 36/45, 80%). Basketball had the highest number of sudden deaths from 2007 to 2015, with a total of 16 occurrences. The most frequent cause of sudden death was cardiac related (n = 34/45, 76%). Most sudden deaths occurred during practices (n = 32/45, 71%). CONCLUSIONS: Sudden deaths in organized youth sports in the United States from 2007 through 2015 were most often experienced during practices by males, were cardiac related, and occurred while playing basketball. These findings are similar to those in high school and collegiate sports. This study affirms the need for further epidemiologic research into sudden deaths at the organized youth sport level.

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BACKGROUND: Sport specialization has been associated with overuse injuries and is more common in larger high schools, which are often located in more urban/suburban settings. However, sport participation characteristics have not been compared between suburban and rural high schools. PURPOSE/HYPOTHESIS: The purpose of this study was to examine the differences in sport participation characteristics between athletes at suburban and rural high schools. It was hypothesized that suburban high school students would be more likely to be highly specialized, participate in more athletic competitions per year, and play in a league outside of school. We also hypothesized that suburban high school students would start playing their primary sport at a younger age, would have participated in their primary sport for longer, and would play more months per year and hours per week. STUDY DESIGN: Cross-sectional study. METHODS: High school athletes from 4 high schools (2 suburban and 2 rural) participated in this study (N = 354 [222 females]; mean age, 15.7 ± 1.2 years). Athletes were on a school-sponsored athletic team in 1 of 4 sports (volleyball, tennis, basketball, soccer). The suburban schools (study enrollment, n = 226) had total school enrollments of 2271 and 622 students, while the rural schools (study enrollment, n = 128) had total school enrollments of 443 and 297. Participants completed a questionnaire prior to the start of their high school sport season. The questionnaire consisted of demographic information, a sport specialization scale, and sport participation information. Primary sport competition volume in the previous 12 months was classified as high (>60 primary sport competitions), moderate (30-60), or low (<30). Sport specialization status was classified via a 3-point scale as low, moderate, or high. RESULTS: As compared with athletes at rural schools, athletes at suburban schools started playing their primary sport at a younger age (suburban, 7.8 ± 2.9 years; rural, 9.7 ± 3.2 years; P < .001) and participated for more years (suburban, 7.9 ± 3.1 years; rural, 6.1 ± 3.3 years; P < .001), more months per year (suburban, 7.6 ± 3.6 months; rural, 5.6 ± 2.8 months; P < .001), and more hours per week (suburban, 15.2 ± 5.1 hours; rural, 12.9 ± 3.3 hours; P < .001). Athletes at suburban schools were more likely than rural athletes to be classified as highly specialized (χ2 = 52.5, P < .001), participate in more competitions (χ2 = 16.5, P < .001), play in a league outside of school (χ2 = 18.4, P < .001), and train in their primary sport for >8 months per year (χ2 = 27.8, P < .001) and >16 hours per week (χ2 = 15.0, P < .001). CONCLUSION: High school athletes at suburban schools are more likely to exhibit sport participation patterns that are associated with increased risk of overuse injury. These include being classified as highly specialized, playing their primary sport >8 months per year and >16 hours per week, engaging in a high competition volume, and participating in a sport league (eg, club) outside of school. Efforts aimed at safe sport participation should target these groups, as they seem more likely to violate safe sport recommendations.

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OBJECTIVES: The field of sport injury prevention has seen a marked increase in published research in recent years, with concomitant proliferation of lay sport safety resources, such as policies, fact sheets and posters. The aim of this study was to catalogue and categorise the number, type and topic focus of sport safety resources from a representative set of key organisations. DESIGN: Cataloguing and qualitative document analysis of resources available from the websites of six stakeholder organisations in Australia. SETTING: This study was part of a larger investigation, the National Guidance for Australian Football Partnerships and Safety (NoGAPS) project. PARTICIPANTS: The NoGAPS study provided the context for a purposive sampling of six organisations involved in the promotion of safety in Australian football. These partners are recognised as being highly representative of organisations at national and state level that reflect similarly in their goals around sport safety promotion in Australia. RESULTS: The catalogue comprised 284 resources. More of the practical and less prescriptive types of resources, such as fact sheets, than formal policies were found. Resources for the prevention of physical injuries were the predominant sport safety issue addressed, with risk management, environmental issues and social behaviours comprising other categories. Duplication of resources for specific safety issues, within and across organisations, was found. CONCLUSIONS: People working within sport settings have access to a proliferation of resources, which creates a potential rivalry for sourcing of injury prevention information. Important issues that are likely to influence the uptake of safety advice by the general sporting public include the sheer number of resources available, and the overlap and duplication of resources addressing the same issues. The existence of a large number of resources from reputable organisations does not mean that they are necessarily evidence based, fully up to date or even effective in supporting sport safety behaviour change.

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