A Comparison of Youth Flag and Tackle Football Head Impact Biomechanics

An empirical study of the flag rugby game programme to promote gross motor skills and physical fitness in 5-6 year old preschool children

In order to investigate the effects of a flag rugby game programs on the development of gross motor skills and physical fitness in 5-6 year old preschool children. An overall random sampling method was adopted to select 56 preschoolers aged 5-6 years from class A and class B,class A was the ExG (28) implemented a flag rugby games intervention program,and class B was the ConG (28) implemented a regular physical education program,with a 12-week intervention period.The content and requirements of the experimental intervention program were determined through a systematic analysis method, and the subjects' gross motor skills level was tested using the TGMD-3, and their physical fitness level was measured using China's fifth national physical fitness monitoring of early childhood (3-6 years) component.Experimental data were statistically analyzed using independent samples t-test, paired samples t-test, and repeated measures ANOVA test.After 12 weeks of practice, 1）We found that the ExG outperformed the ConG in Skip,One hand stationary dribble, Overhand throw, Underhand throw, Forehand strike of self-bounced,Kick a stationary ball, Total object control subject score, Total gross motor score test results with significant differences (p < 0.05).The ExG differed significantly (p < 0.01) in Grip strength, Stand long jump,Sit forward bend, Continuous jump on both feet,15 m obstacle run,Walk the balance beam, while the ConG differed significantly (p < 0.05) only in Continuous jump on both feet,15 m obstacle run and Stand long jump.2）We also found gender differences in gross motor skills and Physical fitness test results, this difference is manifested in boys outperformed girls in Total object control subject Score, Grip strength and 15 m obstacle run with significant difference (p < 0.05), girls outperformed boys in Sit forward bend with significant difference (p < 0.05).The 12-week flag rugby game programs improved gross motor skills and physical fitness levels of 5-6 year old preschoolers more comprehensively than the regular program, and we recommend the purposeful and organized promotion of a flag rugby game programs in the physical activity curriculum for 5-6 year old preschoolers.

Quantifying head impact biomechanical differences between commonly employed cleaning levels: a critical research interpretation consideration

INTRODUCTION

Wearable accelerometry devices quantify on-field frequency and severity of head impacts to further improve sport safety. Commonly employed post-data collection cleaning techniques may affect these outcomes.

OBJECTIVE

Our purpose was to compare game impact rates and magnitudes between three different cleaning levels (Level-1: impacts recorded within start and end times, Level-2: impacts during pauses/breaks removed, Level-3: video verified) for male youth tackle football.

METHODS

Participants (n = 23, age = 10.9 ± 0.3 yrs, height = 150.0 ± 8.3 cm, mass = 41.6 ± 8.4 kg) wore Triax SIM-G sensors throughout Fall 2019. Impact rates, ratios (IRRs), and 95% confidence intervals (95%CI) were used to compare levels. Random-effects general linear models were used to compare peak linear acceleration (PLA;g) and angular velocity (PAV;rads/s).

RESULTS

Level-1 resulted in higher impact rates (4.57; 95%CI = 4.14-5.05) compared to Level-2 (3.09; 95%CI = 2.80-3.42; IRR = 1.48; 95%CI = 1.34-1.63) and Level-3 datasets (2.56; 95%CI = 2.30-2.85; IRR = 1.78; 95%CI = 1.60-1.98). Level-2 had higher impact rates compared to Level-3 (1.21; 95%CI = 1.08-1.35). Level-1 resulted in higher PAV than Level-2 and Level-3 (p < 0.001) datasets. PLA did not differ across datasets (p = 0.296).

CONCLUSIONS

Head impact data should be filtered of pauses/breaks, and does not substantially differ outcome estimates compared to time-intensive video verification.

Biomechanical characteristics of concussive and sub-concussive impacts in youth sports athletes: A systematic review and meta-analysis

This study aimed to quantitatively investigate and report the biomechanical characteristics of concussive and sub-concussive impacts in youth sports. A systematic search was conducted in September 2022 to identify biomechanical impact studies in athletes ≤18 years of age. Twenty-six studies met the inclusion criteria for quantitative synthesis and analysis. DerSimonian Laird random effects model was used to pool data across the included studies. The pooled estimate of mean peak linear and rotational acceleration of concussive impacts in male youth athletes was 85.56 g (95% CI 69.34-101.79) and 4505.58 rad/s² (95% CI 2870.28-6140.98), respectively. The pooled estimate of mean peak linear and rotational acceleration of sub-concussive impacts in youth athletes was 22.89 g (95% CI 20.69-25.08) and 1290.13 rad/s² (95% CI 1050.71-1529.55), respectively. A male vs female analysis in sub-concussive impacts revealed higher linear and rotational acceleration in males and females, respectively. This is the first study to report on impact data in both sexes of youth athletes. Disparity in kinematic impact values suggests future research should aim for standardised measures to reduce heterogeneity in data. Despite this, the data reveals notable impact data that youth athletes are exposed to, suggesting modifications may be required to reduce long-term neurological risks.

Leveraging football accelerometer data to quantify associations between repetitive head impacts and chronic traumatic encephalopathy in males

Chronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy associated with repetitive head impacts (RHI), but the components of RHI exposure underlying this relationship are unclear. We create a position exposure matrix (PEM), composed of American football helmet sensor data, summarized from literature review by player position and level of play. Using this PEM, we estimate measures of lifetime RHI exposure for a separate cohort of 631 football playing brain donors. Separate models examine the relationship between CTE pathology and players' concussion count, athletic positions, years of football, and PEM-derived measures, including estimated cumulative head impacts, linear accelerations, and rotational accelerations. Only duration of play and PEM-derived measures are significantly associated with CTE pathology. Models incorporating cumulative linear or rotational acceleration have better model fit and are better predictors of CTE pathology than duration of play or cumulative head impacts alone. These findings implicate cumulative head impact intensity in CTE pathogenesis.

Prevention strategies and modifiable risk factors for sport-related concussions and head impacts: a systematic review and meta-analysis

OBJECTIVES

To evaluate prevention strategies, their unintended consequences and modifiable risk factors for sport-related concussion (SRC) and/or head impact risk.

DESIGN

This systematic review and meta-analysis was registered on PROSPERO (CRD42019152982) and conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

DATA SOURCES

Eight databases (MEDLINE, CINAHL, APA PsycINFO, Cochrane (Systematic Review and Controlled Trails Registry), SPORTDiscus, EMBASE, ERIC0 were searched in October 2019 and updated in March 2022, and references searched from any identified systematic review.

ELIGIBILITY CRITERIA

Study inclusion criteria were as follows: (1) original data human research studies, (2) investigated SRC or head impacts, (3) evaluated an SRC prevention intervention, unintended consequence or modifiable risk factor, (4) participants competing in any sport, (5) analytic study design, (6) systematic reviews and meta-analyses were included to identify original data manuscripts in reference search and (7) peer-reviewed. Exclusion criteria were as follows: (1) review articles, pre-experimental, ecological, case series or case studies and (2) not written in English.

RESULTS

In total, 220 studies were eligible for inclusion and 192 studies were included in the results based on methodological criteria as assessed through the Scottish Intercollegiate Guidelines Network high ('++') or acceptable ('+') quality. Evidence was available examining protective gear (eg, helmets, headgear, mouthguards) (n=39), policy and rule changes (n=38), training strategies (n=34), SRC management strategies (n=12), unintended consequences (n=5) and modifiable risk factors (n=64). Meta-analyses demonstrated a protective effect of mouthguards in collision sports (incidence rate ratio, IRR 0.74; 95% CI 0.64 to 0.89). Policy disallowing bodychecking in child and adolescent ice hockey was associated with a 58% lower concussion rate compared with bodychecking leagues (IRR 0.42; 95% CI 0.33 to 0.53), and evidence supports no unintended injury consequences of policy disallowing bodychecking. In American football, strategies limiting contact in practices were associated with a 64% lower practice-related concussion rate (IRR 0.36; 95% CI 0.16 to 0.80). Some evidence also supports up to 60% lower concussion rates with implementation of a neuromuscular training warm-up programme in rugby. More research examining potentially modifiable risk factors (eg, neck strength, optimal tackle technique) are needed to inform concussion prevention strategies.

CONCLUSIONS

Policy and rule modifications, personal protective equipment, and neuromuscular training strategies may help to prevent SRC.

PROSPERO REGISTRATION NUMBER

CRD42019152982.

Youth Tackle Football Head-Impact Estimation by Players and Parents: Is the Perception the Reality?

CONTEXT

With growing concerns surrounding exposure to head impacts in youth tackle football, players and parents must understand the exposure level when assenting and consenting to participate.

OBJECTIVE

To determine whether youth football players and parents could estimate on-field head-impact frequency, severity, and location.

DESIGN

Prospective cohort study.

SETTING

Football field.

PATIENTS OR OTHER PARTICIPANTS

We administered a 10-question head-impact estimation tool to parents (n = 23; mean age = 36.5 years [95% CI = 31.7, 37.3 years]) and players (n = 16 boys; mean age = 11.1 years [95% CI = 10.3, 11.8 years]).

MAIN OUTCOME MEASURE(S)

Player on-field head-impact exposure was captured using the Triax SIM-G system. We determined the accuracy between player and parent estimates relative to on-field head-impact exposures using κ and weighted κ values.

RESULTS

Youth tackle football players and parents did not accurately estimate on-field head-impact frequency (κ range = -0.09 to 0.40), severity (κ range = -0.05 to 0.34), or location (κ range = -0.30 to 0.13). Players and parents overestimated head-impact frequency in practices but underestimated the frequency in games. Both groups overestimated head-impact severity, particularly in games. Most players and parents underestimated the number of head impacts to the top of the head, particularly during practices.

CONCLUSIONS

Underestimations of head-impact frequency in games and to the top of the head suggest that informed consent processes aimed at educating players and parents should be improved. Overestimations of head-impact frequency in practices and severity may explain declining rates of youth tackle football participation.

Relating American Football Age of First Exposure to Patient-Reported Outcomes and Medical Diagnoses Among Former National Football League Players: An NFL-LONG study

BACKGROUND

The age of first exposure (AFE) to American football participation is a growing concern for late-life function. Mixed evidence exists surrounding AFE and may be attributed to varied methods employed across studies.

OBJECTIVE

To examine the associations between AFE to American football participation with measures of cognitive, behavioral, and physical function and brain-related medical diagnoses across age categories among former National Football League players.

METHODS

We conducted a cross-sectional survey of 1784 former players (age: 52.3 ± 16.3 years, AFE: 11.3 ± 2.9 years, years of football: 17.5 ± 4.5 years, 86.9% ≥ one lifetime concussion). Players completed a general health questionnaire recording demographics, football playing history (including AFE), and diagnoses (anxiety, depression, any form of dementia, mild cognitive impairment). Players completed Patient-Reported Outcomes Measurement Information System (PROMIS) measures assessing domains of cognitive and physical function, anxiety, depression, sleep disturbance, pain interference, and emotional-behavioral dyscontrol. Multivariable linear and binomial regression models were used to examine the associations of AFE and age with PROMIS outcomes and diagnoses, respectively.

RESULTS

No significant AFE by age interactions were detected for PROMIS outcomes (p ≥ 0.066) or diagnoses (p ≥ 0.147). Younger AFE associated with higher PROMIS scores of anxiety (B = - 0.22, p = 0.016), depression (B = - 0.22, p = 0.010), sleep disturbances (B = - 0.16, p = 0.007), pain interference (B = - 0.19, p = 0.014), and emotional-behavioral dyscontrol (B = - 0.22, p = 0.019). Age was associated with all PROMIS outcomes (p ≤ 0.042). AFE was not associated with the prevalence of anxiety, depression, dementia, or mild cognitive impairment (p ≥ 0.449), while age was (p ≤ 0.013).

CONCLUSIONS

AFE was significantly associated with PROMIS outcomes, albeit low-strength associations (i.e., effect sizes), but not with diagnoses. Our findings indicate AFE is a significant but minor contributing factor for health-related quality of life in this cohort. Future work should incorporate additional characterizations of cumulative head impacts and related factors when examining long-term outcomes associated with football participation.

A Description of Suspected Concussions in Football-Related Activities among K-12 Students in Utah

The circumstances and nature of concussions among youth who play tackle, flag, or touch football are not well understood. This study used data from Utah's Student Injury Reporting System (SIRS) to explore suspected concussions among K-12 students sustained during participation in football-related activities (tackle, flag, or touch football). Descriptive statistics and chi-square analyses showed that 54.7% of suspected concussions due to football-related activity were among elementary and middle school and 41.3% were among high school students. Most suspected concussions resulted from being struck by or against something (81.9%) and occurred during school-sanctioned games and practices (37.9%), lunch, lunch recess, and recess (34.8%), or physical education class (22.7%). The type of school activity and context for suspected concussions varied by school level. School nurses and others in Utah may use study findings to customize concussion prevention efforts by school level and activity.

Child participation in collision sports and football: what influences parental decisions?

OBJECTIVE

Sport participation promotes health benefits for children. Current media and scientific coverage of sport-related head injury may influence a parent's decision on sports participation. Physicians must understand what influences these decisions to effectively counsel patients and families. This study sought to better understand and quantify the parental decisions to allow/disallow collision sports, including football participation.

METHODS

A 31-question survey related to child/parent demographics, sports history, and influences to allow/disallow sport participation was available to parents in the United States through a national volunteer registry, between November 2016 and September 2019. Pearson's chi-squared and Wilcoxon's signed-rank test were used to analyze categorical and continuous variables, respectively. Multivariate logistic regression was performed to identify the most powerful factors associated with the decision.

RESULTS

Of the 884 responses, 430 (49%) parents would disallow collision sport participation and 334 (38%) would disallow football. Parents who would allow collision sports more commonly cited child desire, while those parents who would disallow cited safety concern as the greatest influence to generally disallow a sport. Those who would disallow reported doctors (35.1% vs 25.3%; P = 0.002), media (12.8% vs 7.3%; P = 0.006) and other parents (11.2% vs 7.3%; P = 0.045) as influences. A child's age (OR 1.039, 95%CI 1.007-1.073; P = 0.018) was independently associated with their parent responding that they would allow collision sports. Parent educational status showed that those with higher than a bachelor's degree would be less likely to allow football participation (OR 0.635, 95%CI 0.443-0.910; P = 0.013).

CONCLUSIONS

Parents incorporate many sources of information into the decision to allow or disallow their child to participate in collision sports. A child's desire to play a sport and child safety are driving factors for parents faced with the decision of whether to allow participation in collision sports. Physician input is more frequently influential to parents than the media, underscoring the responsibility of physicians to engage families on the risks, benefits, and resources available for sport participation.

Neuropsychological Profiles of Athletes and Views of Parents Choosing Flag Versus Tackle Football Participation

Background:

Previous studies have found that injury rates are slightly higher in children who play flag football versus tackle football. It is unclear if this difference is due to the way each type is played or taught or whether there are intrinsic differences in attitudes or neuropsychological characteristics in children and their parents.

Purpose:

To determine whether children who play flag football score differently from those who play tackle football on validated neuropsychological tests.

Study Design:

Cross-sectional study; Level of evidence, 3.

Methods:

Each participating athlete (aged 8-12 years) was recruited in 2018 and 2019 by email through local youth football leagues and the local university. Each athlete was administered a 1-time multidimensional assessment battery. The battery included the Wechsler Abbreviated Scale of Intelligence-2nd Edition, the children’s version of the Trail Making Test, the Integrated Digit Span and Spatial Span subtests of the Wechsler Intelligence Scale for Children-4th Edition (WISC-IV), and the Beck Self-Concept Inventory for Youth. The parent/guardian of each athlete completed the Achenbach Child Behavior Checklist-Parent Report Form, the Behavior Rating Inventory of Executive Function (BRIEF)-Parent Form, and a custom survey. These tests were used to determine IQ estimates and standardized scores, measuring verbal comprehension, matrix reasoning, mental set-shifting, attention, cognitive processing speed, working memory, spatial processing, perception of self-concept, behavioral regulation index, metacognition index, and global executive composite. Scores were compared between flag football and tackle football groups by 2-sample t test, with the Wilcoxon rank-sum test used for nonparametric data.

Results:

A total of 64 athletes (41 tackle football, 23 flag football) were enrolled from youth football leagues (grades 4-6). Flag players scored significantly higher on the WISC-IV Spatial Span-Backward subtest (scaled mean, 12.0 vs 10.6; P = .046), while tackle players had significantly higher BRIEF-Inhibit subscores (mean t-score, 45 vs 42; P = .026). There were no significant differences in any of the other tests, including socioeconomic status and perceived concussion risks.

Conclusion:

Concerns that injury epidemiologic studies comparing flag with tackle football could be confounded by intrinsic differences in the children who choose to play each type seem to be unfounded.

Influence of play type on the magnitude and number of head impacts sustained in youth American football

The magnitude and number of head impacts experienced by young American football players are associated with negative brain health outcomes and may be affected by play-type strategies. The purpose of this research was to examine how play type affects the magnitude and number of head impacts in youth American tackle football. Head impacts were recorded for 30 games in the 5-9 age category and 30 games in the 9-14 age category. Impacts using physical and finite element models were conducted to determine the brain strain. Run plays had a higher head impact frequency in both age groups (p < 0.05). This increase in head impacts was consistent for all positions (p < 0.05), except wide receiver, and offensive line and defensive back in the 9-14 age group (p > 0.05). Both age groups experienced significantly different magnitude proportions with higher numbers of very low and low strain magnitude impacts during run plays (p < 0.05), and a higher proportion of moderate magnitude impacts in the 5-9 age category (p < 0.05). This data can be used to inform and educate teams and coaches and influence decisions around the use of runs and passing plays that may lead to a decrease in head impacts.

Head Impact Research Using Inertial Sensors in Sport: A Systematic Review of Methods, Demographics, and Factors Contributing to Exposure

BACKGROUND

The number and magnitude of head impacts have been assessed in-vivo using inertial sensors to characterise the exposure in various sports and to help understand their potential relationship to concussion.

OBJECTIVES

We aimed to provide a comprehensive review of the field of in-vivo sensor acceleration event research in sports via the summary of data collection and processing methods, population demographics and factors contributing to an athlete's exposure to sensor acceleration events.

METHODS

The systematic search resulted in 185 cohort or cross-sectional studies that recorded sensor acceleration events in-vivo during sport participation.

RESULTS

Approximately 5800 participants were studied in 20 sports using 18 devices that included instrumented helmets, headbands, skin patches, mouthguards and earplugs. Female and youth participants were under-represented and ambiguous results were reported for these populations. The number and magnitude of sensor acceleration events were affected by a variety of contributing factors, suggesting sport-specific analyses are needed. For collision sports, being male, being older, and playing in a game (as opposed to a practice), all contributed to being exposed to more sensor acceleration events.

DISCUSSION

Several issues were identified across the various sensor technologies, and efforts should focus on harmonising research methods and improving the accuracy of kinematic measurements and impact classification. While the research is more mature for high-school and collegiate male American football players, it is still in its early stages in many other sports and for female and youth populations. The information reported in the summarised work has improved our understanding of the exposure to sport-related head impacts and has enabled the development of prevention strategies, such as rule changes.

CONCLUSIONS

Head impact research can help improve our understanding of the acute and chronic effects of head impacts on neurological impairments and brain injury. The field is still growing in many sports, but technological improvements and standardisation of processes are needed.

Comparison of head impact frequency and magnitude in youth tackle football and ice hockey

Repetitive head impacts are a growing concern for youth and adolescent contact sport athletes as they have been linked to long term negative brain health outcomes. Of all contact sports, tackle football and ice hockey have been reported to have the highest incidence of head or brain injury however, each sporting environment is unique with distinct rules and regulations regarding contact and collisions. The purpose of this research was to measure and compare the head impact frequency and estimated magnitude of brain tissue strain, amongst youth tackle football and ice hockey players during game play. Head impact frequency was documented by video analysis of youth tackle football and ice hockey game play. Impact magnitude was determined through physical laboratory reconstructions and finite element modelling to estimate brain tissue strains. Tackle football demonstrated significantly higher impact frequency (P < 0.01) and magnitude of estimated brain tissue strains (P < 0.01) compared to ice hockey. A significantly higher number of higher strain head impacts were documented in tackle football when compared to ice hockey (P < 0.01). These differences suggest that youth football players may experience increased frequency and magnitude of estimated brain tissue strains in comparison to youth hockey.

On-field Characteristics and Head Impact Magnitude in Youth Tackle Football

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/s^2, 95% confidence interval [CI] = 2986 to 3808) had a small effect for higher PRA compared with striking players (3037 rads/s^2, 95% CI = 2713 to 3404, d = 0.251), but negligible effect for simultaneous struck-striking players (3340 rad/s^2, 95% CI = 2945 to 3792, d = 0.018). Fourth quarter impacts (3490 rads/s^2, 95% CI = 3083 to 3951) had a small effect for higher PRA compared with first (2945 rads/s^2, 95% CI = 2596 to 3337, d = 0.404), second (3196 rads/s^2, 95% CI = 2832 to 3604, d = 0.219), and third quarters (3241 rads/s^2, 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.

Head Impact Biomechanics in Youth Flag Football: A Prospective Cohort Study

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.

Differences in Head Impact Exposures Between Youth Tackle and Flag Football Games and Practices: Potential Implications for Prevention Strategies

BACKGROUND

Interventions designed to reduce the risk for head impacts and concussion in youth football have increased over the past decade; however, understanding of the role of regular game play on head impact exposure among youth tackle and flag football athletes is currently limited.

PURPOSE

To explore head impact exposure among youth tackle and flag football athletes (age range, 6-14 years) during both practices and games.

STUDY DESIGN

Cohort study; Level of evidence, 2.

METHODS

Using the Vector MouthGuard sensor, the authors collected head impact data from 524 tackle and flag youth football athletes over the course of a football season. Quantities of interest were estimated from regression models using Bayesian methods.

RESULTS

For impacts ≥10g, a tackle football athlete had an estimated 17.55 (95% CI, 10.78-28.96) times more head impacts per practice compared with a flag football athlete (6.85 [95% CI, 6.05-7.76] and 0.39 [95% CI, 0.24-0.62] head impacts, respectively). Additionally, a tackle football athlete had an estimated 19.48 (95% CI, 12.74-29.98) times more head impacts per game compared with a flag football athlete (13.59 [95% CI, 11.97-15.41] and 0.70 [95% CI, 0.46-1.05] head impacts, respectively). Among tackle football athletes, the estimated average impact rate was 6.51 (95% CI, 5.75-7.37) head impacts during a practice and 12.97 (95% CI, 11.36-14.73) impacts during a game, resulting in 2.00 (95% CI, 1.74-2.29) times more ≥10g head impacts in games versus practices. Tackle football athletes had 2.06 (95% CI, 1.80-2.34) times more high-magnitude head impacts (≥40g) during a game than during a practice. On average, flag football athletes experienced an estimated 0.37 (95% CI, 0.20-0.60) head impacts during a practice and 0.77 (95% CI, 0.53-1.06) impacts during a game, resulting in 2.06 (95% CI, 1.29-3.58) times more ≥10g head impacts in games versus practices. Because of model instability caused by a large number of zero impacts for flag football athletes, a comparison of high-magnitude head impacts is not reported for practices or games.

CONCLUSION

This study provides a characterization of the head impact exposure of practices and games among a large population of youth tackle and flag football athletes aged 6 to 14 years. These findings suggest that a greater focus on game-based interventions, such as fair play interventions and strict officiating, may be beneficial to reduce head impact exposures for youth football athletes.

Head Impact Exposures Among Youth Tackle and Flag American Football Athletes

Background:

Promoted as a safer alternative to tackle football, there has been an increase in flag football participation in recent years. However, examinations of head impact exposure in flag football as compared with tackle football are currently limited.

Hypothesis:

Tackle football athletes will have a greater number and magnitude of head impacts compared with flag football athletes.

Study Design:

Cohort study.

Level of Evidence:

Level 4.

Methods:

Using mouthguard sensors, this observational, prospective cohort study captured data on the number and magnitude of head impacts among 524 male tackle and flag football athletes (6-14 years old) over the course of a single football season. Estimates of interest based on regression models used Bayesian methods to estimate differences between tackle and flag athletes.

Results:

There were 186,239 head impacts recorded during the study. Tackle football athletes sustained 14.67 (95% CI 9.75-21.95) times more head impacts during an athletic exposure (game or practice) compared with flag football athletes. Magnitude of impact for the 50th and 95th percentile was 18.15g (17.95-18.34) and 52.55g (51.06-54.09) for a tackle football athlete and 16.84g (15.57-18.21) and 33.51g (28.23-39.08) for a flag football athlete, respectively. A tackle football athlete sustained 23.00 (13.59-39.55) times more high-magnitude impacts (≥40g) per athletic exposure compared with a flag football athlete.

Conclusion:

This study demonstrates that youth athletes who play tackle football are more likely to experience a greater number of head impacts and are at a markedly increased risk for high-magnitude impacts compared with flag football athletes.

Clinical Relevance:

These results suggest that flag football has fewer head impact exposures, which potentially minimizes concussion risk, making it a safer alternative for 6- to 14-year-old youth football athletes.

Emergency Department Visits From 2014 to 2018 for Head Injuries in Youth Non-Tackle Football Compared With Other Sports

Background

Non-tackle football (ie, flag, touch, 7v7) is purported to be a lower-risk alternative to tackle football, particularly in terms of head injuries. However, data on head injuries in non-tackle football are sparse, particularly among youth participants.

Purpose

To describe the epidemiology of  emergency department visits for head injuries due to non-tackle football among youth players in the United States and compare the data with basketball, soccer, and tackle football.

Study Design

Descriptive epidemiology study.

Methods

Injury data from 2014 to 2018 were obtained from the National Electronic Injury Surveillance System database. Injury reports coded for patients aged 6 to 18 years and associated with basketball, football, or soccer were extracted. Data were filtered to include only injuries to the head region, specifically, the head, ear, eyeball, mouth, or face. Football injuries were manually assigned to "non-tackle" or "tackle" based on the injury narratives. Sports & Fitness Industry Association data were used to estimate annual sport participation and calculate annual injury rates per 100,000 participant-years.

Results

A total of 26,770 incident reports from 2014 to 2018 were analyzed. For head region injuries in non-tackle football, the head was the most commonly injured body part, followed by the face; the most common diagnosis was a laceration, followed by concussion and internal injury (defined as an unspecified head injury or internal head injury [eg, subdural hematoma or cerebral contusion]). The most common contacting object was another player. The projected national rate of head region injuries was lowest for non-tackle football across the 4 sports. In particular, the projected rate of injuries to the head for non-tackle football (78.0 per 100,000 participant-years) was less than one-fourth the rates for basketball (323.5 per 100,000 participant-years) and soccer (318.2 per 100,000 participant-years) and less than one-tenth the rate for tackle football (1478.6 per 100,000 participant-years).

Conclusion

Among youth in the United States aged 6 to 18 years who were treated in the emergency department for injuries related to playing non-tackle football, the most common diagnosis for injuries to the head region was a laceration, followed by a concussion. Head region injuries associated with non-tackle football occurred at a notably lower rate than basketball, soccer, or tackle football.

The Effectiveness of Regulations and Behavioral Interventions on Head Impacts and Concussions in Youth, High-School, and Collegiate Football: A Systematized Review

The purpose of this study was to assess the effectiveness of regulations and behavioral interventions on head impacts and concussions in youth, high-school, and collegiate football, using a systematic search strategy to identify relevant literature. Six databases were searched using key search terms related to three categories: football, head-injuries, and interventions. Studies that met inclusion criteria were included in the study and underwent data extraction. Twenty articles met inclusion criteria and were included in the final systematized review. Of the 20 included studies, 8 studies evaluated interventions in high-school football, 5 studies evaluated interventions in collegiate football, 6 studies evaluated interventions in youth football, and 1 study evaluated interventions in both, high-school and collegiate football. The four categories of interventions and regulations included rule changes, training, education/instruction/coaching tactical changes, and tackle football alternatives. Studies evaluating the effectiveness of interventions and regulations on reducing head impact exposures or head injuries have shown mixed results. Some regulations may be more effective than others, but methodological design and risk of bias pose limitations to generalize effects.

Head Impact Sensor Studies In Sports: A Systematic Review Of Exposure Confirmation Methods

To further the understanding of long-term sequelae as a result of repetitive head impacts in sports, in vivo head impact exposure data are critical to expand on existing evidence from animal model and laboratory studies. Recent technological advances have enabled the development of head impact sensors to estimate the head impact exposure of human subjects in vivo. Previous research has identified the limitations of filtering algorithms to process sensor data. In addition, observer and/or video confirmation of sensor-recorded events is crucial to remove false positives. The purpose of the current study was to conduct a systematic review to determine the proportion of published head impact sensor data studies that used filtering algorithms, observer confirmation and/or video confirmation of sensor-recorded events to remove false positives. Articles were eligible for inclusion if collection of head impact sensor data during live sport was reported in the methods section. Descriptive data, confirmation methods and algorithm use for included articles were coded. The primary objective of each study was reviewed to identify the primary measure of exposure, primary outcome and any additional covariates. A total of 168 articles met the inclusion criteria, the publication of which has increased in recent years. The majority used filtering algorithms (74%). The majority did not use observer and/or video confirmation for all sensor-recorded events (64%), which suggests estimates of head impact exposure from these studies may be imprecise.

Video Confirmation of Head Impact Sensor Data From High School Soccer Players

BACKGROUND

Recent advances in technology have enabled the development of head impact sensors, which provide a unique opportunity for sports medicine researchers to study head kinematics in contact sports. Studies have suggested that video or observer confirmation of head impact sensor data is required to remove false positives. In addition, manufacturer filtering algorithms may be ineffective in identifying true positives and removing true negatives.

PURPOSE

To (1) identify the percentage of video-confirmed events recorded by headband-mounted sensors in high school soccer through video analysis, overall and by sex; (2) compare video-confirmed events with the classification by the manufacturer filtering algorithms; and (3) quantify and compare the kinematics of true- and false-positive events.

STUDY DESIGN

Cohort study; Level of evidence, 2.

METHODS

Adolescent female and male soccer teams were instrumented with headband-mounted impact sensors (SIM-G; Triax Technologies) during games over 2 seasons of suburban high school competition. Sensor data were sequentially reduced to remove events recorded outside of game times, associated with players not on the pitch (ie, field) and players outside the field of view of the camera. With video analysis, the remaining sensor-recorded events were identified as an impact event, trivial event, or nonevent. The mechanisms of impact events were identified. The classifications of sensor-recorded events by the SIM-G algorithm were analyzed.

RESULTS

A total of 6796 sensor events were recorded during scheduled varsity game times, of which 1893 (20%) were sensor-recorded events associated with players on the pitch in the field of view of the camera during verified game times. Most video-confirmed events were impact events (n = 1316, 70%), followed by trivial events (n = 396, 21%) and nonevents (n = 181, 10%). Female athletes had a significantly higher percentage of trivial events and nonevents with a significantly lower percentage of impact events. Most impact events were head-to-ball impacts (n = 1032, 78%), followed by player contact (n = 144, 11%) and falls (n = 129, 10%) with no significant differences between male and female teams. The SIM-G algorithm correctly identified 70%, 52%, and 66% of video-confirmed impact events, trivial events, and nonevents, respectively.

CONCLUSION

Video confirmation is critical to the processing of head impact sensor data. Percentages of video-confirmed impact events, trivial events, and nonevents vary by sex in high school soccer. Current manufacturer filtering algorithms and magnitude thresholds are ineffective at correctly classifying sensor-recorded events and should be used with caution.

Quantitative and qualitative analysis of head and body impacts in American 7v7 non-tackle football

Objectives

Non-tackle American football is growing in popularity, and it has been proposed as a safer alternative for young athletes interested in American football. Little is known about the nature of head contact in the sport, which is necessary to inform the extent to which protective headgear is warranted. The objective of this study was to identify the location, types and frequency of head and body contacts in competitive 7v7 non-tackle American football.

Methods

Video analysis was used to document the type, frequency and mechanism of contacts across a series of under 12, under 14 and high school non-tackle tournament games. A subset of impacts was quantitatively analysed via 3-D model-based image matching to calculate the preimpact and postimpact speed of players’ heads and the change in resultant translational and rotational velocities.

Results

The incidence rate of head contact was found to be low (3.5 contacts per 1000 athlete-plays). Seventy-five per cent of head contacts were caused by a head-to-ground impact. No head-to-head contacts were identified. Most contacts occurred to the rear upper (occiput) or side upper (temporal/parietal) regions. Head-to-ground impact was associated with a maximum preimpact velocity of 5.9±2.2 m/s and a change in velocity of 3.0±1.1 m/s.

Conclusion

Non-tackle football appears to represent a lower contact alternative to tackle football. The distribution of head impact locations, mechanisms and energies found in the present study is different than what has been previously reported for tackle football. The existing tackle football standards are not appropriate to be applied to the sport of non-tackle football, and sport-specific head protection and headgear certification standards must be determined.

Injury Rate in TackleBar Football

Background:

As football comes under greater scrutiny because of concussions and other injuries, many people are searching for safer alternatives, especially for youth athletes. The injury rate in TackleBar football, one such alternative, is not currently known.

Purpose:

To describe TackleBar football and calculate its injury rate over a single season to compare it with both traditional tackle and flag football.

Study Design:

Descriptive epidemiology study.

Methods:

TackleBar football was described, and injuries of male athletes (age range, 9-14 years) participating in TackleBar football were tracked over the course of a season (August 5 through October 27, 2018) and compared with published injury rates for traditional tackle and flag football.

Results:

The overall injury rate of TackleBar football was found to be 0.31 per 1000 athlete-exposures (AEs), which is lower than youth tackle (2.25-2.60/1000 AEs) and flag (5.77/1000 AEs) football.

Conclusion:

TackleBar football may represent a reasonable alternative to tackle and flag football with regard to injuries.