CONCUSSION CARE seeking is a complex clinical and behavioral issue. Previous work indicates that upward of 50% to 80% of concussions may go unreported across various age groups of participation.1–3 Studies suggest factors associated with care-seeking decisions fit within the socioecological framework, which may indicate that influences exist at multiple levels (eg, intrapersonal, interpersonal, environment, policy) and also that interventions must be cognizant of such influences and their relationships with one another.4,5
Within this framework, the intrapersonal factor of the athlete's concussion knowledge has been raised as an area of importance. Specifically, previous studies suggest that the lack of care seeking may be attributable to not knowing the injury is a concussion and not feeling it was serious enough to report.1,3,6–8 Concussion knowledge is foundational to symptom identification and knowing the steps to take when a concussion occurs. This knowledge may be acquired from a variety of sources including medical professionals, websites, educational programming, and training programs.9 However, the validity of many concussion information sources is unknown.
In addition to the basic provision of foundational knowledge, racial disparities in this knowledge must be addressed. Previous research suggests concussion knowledge differences by race/ethnicity in the high school10 and youth sports settings.11 Specifically, Black high school athletes have a poorer understanding of concussion symptoms than their White peers, and this difference is exacerbated in the absence of an athletic trainer. Recent approaches to interventions posit the need for equitable methodologies to education such that tools and strategies provided do not create or exacerbate disparities in concussion knowledge.12
To develop appropriate concussion educational strategies that not only target concussion knowledge but also provide equitable approaches to knowledge translation and intervention, understanding racial disparities in both knowledge and sources of information used by collegiate-athletes is needed. Therefore, the current study assessed racial differences between Black and White collegiate-athletes in the knowledge of concussion symptoms and the use of concussion information sources.
Study design and participants
This cross-sectional study utilized a convenience sample of National Collegiate Athletic Association (NCAA) collegiate-athletes from 7 institutions (Division I, n = 4; Division II, n = 2; Division III, n = 1) across 3 geographic regions in the United States. Athletes participated in 17 NCAA-sanctioned sports. Eligibility criteria included (1) collegiate-athletes who had participated in their sanctioned sports during the 2017-2018 academic year and (2) aged 18 years or older. Individuals were ineligible for the study if they (1) had sustained a concussion within the previous 3 months or (2) had lingering effects or actively receiving treatment of prolonged issues related to a previous concussion. These exclusion criteria aimed to decrease potential response bias on survey items that could be impacted by a recent injury experience or ongoing issues from previous injuries.
Study variables and instrument
Race was the primary exposure and was assessed using a multiselect item, with options including White/non-Hispanic, Black/non-Hispanic, Hispanic/Latino, Asian, American Indian/Alaskan Native, Native Hawaiian/Pacifier Islander, and Other, with a fill-in option. Any combination of responses noted as White/non-Hispanic and Black/non-Hispanic (hereafter shortened to “White” and “Black,” respectively) was included in analyses. Race is a social construct that can drive poor health outcomes,13 and racial or implicit biases toward non-White or minoritized individuals can produce access and quality-of-care disparities within healthcare.14 Literature has shown that some individuals having Black ancestry often identify, at least under some circumstances, as Black15,16 and may have similar experiences within healthcare.14 As such, responses that indicated mixed-race with Black/non-Hispanic (eg, Black/White) via selection of 2 or more races or using the “other” fill-in option specifying mixed Black/White were also included in the Black collegiate-athlete group (n = 25). White and Black athletes make up 74% of all NCAA athletes, and few athletes selected certain ethnic groups, limiting culturally appropriate comparative analyses.
Additional demographic items included sex, age, year in college, and self-reported diagnosed concussion history (diagnosed by a doctor or athletic trainer). Finally, the questionnaire obtained sports information on the sports played, NCAA division level, and years of experience of playing those sports. Sports were categorized as follows: contact (ie, football, soccer, lacrosse, wrestling, ice hockey, basketball, field hockey, water polo); limited contact (ie, baseball, softball, volleyball); and noncontact (ie, bowling, golf, rowing, tennis, swimming and diving, cross-country, track and field).17,18
The first outcome of interest was concussion symptom knowledge (CSK), which was assessed using methods similar to previous research.2,6 For this study, the original 20-item symptom list was adapted to include symptoms included in the Post-Concussion Symptom Scale, resulting in 34 total items (20 true concussion signs/symptoms and 14 false distractors).19 From this list, participants were instructed to select items they thought were symptoms of a concussion. One point was awarded for each true symptom that was correctly identified and for each false distractor symptom that was not selected (range of 0-34, with higher scores indicating greater CSK). Subscales from the true concussion symptoms were also created for symptoms that were somatic (range, 0-8; eg, nausea, dizziness), sleep (range, 0-3; eg, fatigue, sleep problems), cognitive (range, 0-6; eg, headache, difficulty concentrating), and affective (range, 0-2; ie, irritability, feeling emotional).
The second outcome of interest was the use of concussion information sources. From a list of potential sources, participants indicated those from which they had previously acquired concussion information. The list was compiled by 5 concussion researchers and included 20 potential source options. Two additional items allowed participants to indicate that they had never acquired concussion information from any source or write-in additional sources not listed that they have used. All write-in responses were reviewed and coded into one of the aforementioned potential source options. Most sources were categorized into groups: medical professional (6 options; eg, sports medicine physician, athletic trainer); sport stakeholder (2 options; ie, coach, referee); mass media (6 options; eg, sports news, social media); and policy/organization (4 options; eg, NCAA, youth sports state concussion laws).
The questionnaire consisted of 52 questions and was assessed for face validity by 3 content experts and piloted with a diverse group of 10 undergraduate students not participating in sports. Psychometrics of the knowledge construct used in this study had a Cronbach α of 0.77 compared with the originally developed questionnaire, which had a Cronbach α of 0.72.2 It took participants approximately 15 minutes to complete.
This study was approved by the institutional review board at Duquesne University and met the ethical human subjects research requirements at all participating institutions. To enlist participation, informative emails were sent to the head athletic trainer at each participating college/university. To maximize subject recruitment, the research team collaborated with each institution's sports medicine team to develop an individualized data collection plan based upon available resources and fall athletic activities structure. Data collection occurred during team meetings, before/after practices, and while participants were receiving treatment of an unrelated musculoskeletal injury.
Participants were first presented with an informed consent outlining study details. Those providing informed consent then completed the questionnaire either via pen and paper or electronically on an iPad using the Qualtrics technology (Qualtrics, Provo, Utah). Responses from pen-and-paper questionnaires were manually entered into the Qualtrics platform by research assistants, of which a random sample was checked for data entry accuracy.
Data were analyzed using SAS (version 9.4; SAS Institute Inc, Cary, North Carolina). All analyses were performed with both the full sample and a subsample of football athletes. Descriptive analyses included frequencies, measures of central tendency, and variability. Comparative analyses examined differences in outcome measures between White and Black collegiate-athletes; this included Fisher's exact tests for categorical data (eg, correct/incorrect response for each concussion symptom, use/nonuse of each concussion information source) and Wilcoxon rank-sum tests for quantitative data (eg, CSK score).
Finally, a multivariable Poisson regression model examined the association between race and CSK score while accounting for covariates. Covariates included sex, sports contact level, NCAA division, concussion history, and whether specific concussion information sources were used such as school-based professional, medical professional, mass media, and policy/organization. Robust standard errors were applied to correct for potential issues with over/underdispersion. Resulting incidence rate ratios (IRRs) with 95% CIs excluding 1.00 were deemed statistically significant.
Of the 768 collegiate-athletes who participated, 82.6% identified as White and 17.4% identified as Black (see Table 1). The majority were male (60.5%), from Division II (49.7%), had no concussion history (70.1%), and participated in a contact sport (73.0%). The most represented sport was football (25.5%), followed by lacrosse (13.5%), and soccer (9.0%). Of the athletes who played football (n = 196), 58.7% identified as White and 41.3% identified as Black; the majority were from Division II (60.7%) and had no concussion history (69.4%).
TABLE 1 -
Characteristics of sample of collegiate athletes
|All sports (N = 768)
||Football-only (n = 196)
||All sports (N = 768)
||Football-only (n = 196)
Years playing sportsa
Sports contact level
Year in college
||Swim and dive
||Track and field
Abbreviation: NCAA, National Collegiate Athletic Association.
aOnly considers sports that participant play in college.
bIncludes individuals who self-identified as Black/mixed race.
Concussion symptom knowledge
CSK score distributions were skewed left, with more participants reporting higher scores. The median (IQR) scores for all athletes and football-only athletes were 28 (25-30) and 27 (24-29), respectively (see Table 2). Results of the Wilcoxon rank-sum tests suggest that White athletes had higher CSK scores than Black athletes among all athletes and football-only athletes (both Ps < .001). Findings were similar when examined with CSK subscales.
TABLE 2 -
Concussion symptom knowledge descriptive statistics for collegiate athletes
|Scales (potential range)
||Mean (SD); Median (IQR)
|All CA (N = 768)
||White CA (n = 634)
||Black CA (n = 134)
||All football CA (N = 196)
||White football CA (n = 115)
||Black football CA (n = 81)
|Total symptoms (0-34)b
||27.4 (3.8); 28 (25-30)
||27.7 (3.6); 28 (26-30)
||25.9 (4.1); 26 (23-29)
||26.1 (4.1); 27 (24-29)
||26.9 (4.0); 28 (24-30)
||25.1 (4.1); 25 (23-28)
|Somatic symptoms (0-8)
||6.3 (1.6); 7 (6-7)
||6.4 (1.6); 7 (6-8)
||5.7 (1.8); 6 (5-7)
||5.9 (1.9); 6 (5-7)
||6.2 (1.8); 7 (5-7)
||5.4 (1.9); 6 (4-7)
|Sleep symptoms (0-3)
||2.3 (0.9); 3 (2-3)
||2.4 (0.9); 3 (2-3)
||2.0 (0.9); 2 (1-3)
||2.0 (1.0); 2 (1-3)
||2.2 (0.9); 3 (2-3)
||1.8 (0.9); 2 (1-2)
|Cognitive symptoms (0-6)
||5.1 (1.4); 6 (5-6)
||5.3 (1.2); 6 (5-6)
||4.4 (1.6); 5 (4-6)
||4.6 (1.6); 5 (4-6)
||4.9 (1.6); 6 (4-6)
||4.1 (1.7); 4 (3-5)
|Affective symptoms (0-2)
||1.1 (0.9); 1 (0-2)
||1.1 (0.9); 1 (0-2)
||0.8 (0.9); 0.5 (0-2)
||0.9 (0.9); 1 (0-2)
||1.1 (0.9); 1 (0-2)
||0.7 (0.8); 0 (0-1)
Abbreviation: CA, collegiate athletes.
aWilcoxon rank-sum test compares distributions of White versus Black collegiate athletesʼ concussion symptom knowledge scale scores.
bTotal symptom scale includes items from Somatic, Sleep, Cognitive, and Affective subscales, as well as loss of consciousness AND 14 reverse-coded false distractors.
Among all athletes, common concussion symptoms identified correctly included sensitivity to light (96.9%), headache (95.6%), dizziness (90.4%), and difficulty concentrating (89.6%; see Supplemental Digital Content Table 3, available at: https://links.lww.com/JHTR/A430). Concussion symptoms less commonly identified included feeling more irritable/angry (53.3%), feeling more emotional (53.3%), and drowsiness (72.5%). When examining distributions of correctly identified individual concussion symptoms, the percentage of correct answers among White athletes was significantly higher than among Black athletes for 16 of the 20 true concussion symptoms. Symptoms with the largest differences for White compared with Black athletes included the following: feeling like “in a fog” (83.1% vs 54.5%); nausea or vomiting (82% vs 60.4%); and feeling more irritable/angry (56.8% vs 36.6%). The 4 symptoms without statistically significant findings were all somatic symptoms. Of the 14 false distractor symptoms, 3 had statistically significant differences that were noted, with Black athletes being more likely to correctly identify these distractors as nonsymptoms. Findings were nearly similar when restricted to the football-athletes subsample. Findings that were significant among all athletes but no longer significant among football-only athletes included symptoms of dizziness, memory loss, confusion, sleep problems, fatigue/low energy, and feeling more emotional.
TABLE 3 -
Multivariable Poisson regression for models predicting higher concussion symptom knowledge score among collegiate athletes
||Incidence rate ratio (95%CI)
|All collegiate-athletes (N = 768)
||Football collegiate-athletes only (n = 196)
|Black vs White
|Female vs Male
|Sports contact level
|Limited contact vs Noncontact
|Contact vs Noncontact
|Contact vs Limited contact
|Division II vs Division I
|Division III vs Division I
|Division III vs Division II
|Yes vs No
|Concussion information sources used
|Family member (Yes vs No)
|School-based professional (Yes vs No)
|Medical professional (Yes vs No)
|Coach (Yes vs No)
|Mass media (Yes vs No)
|Policy/organization (Yes vs No)
Abbreviation: NCAA, National Collegiate Athletic Association.
aDenotes statistical significance (ie, 95% CI does not include 1.00 for incidence rate ratios or 0.00 for mean difference).
Sources of concussion information
Overall, 87.6% of the sample noted using at least one of the 20 provided sources of concussion information (see Supplemental Digital Content Table 4, available at: https://links.lww.com/JHTR/A431). Common sources included athletic trainer (73.0%), school-based professional (69.3%), coach (57.9%), and the NCAA (47.1%). When examining distributions of using each source of concussion information, the percentage of use among White athletes was significantly higher than among Black athletes for 4 of the 20 sources. School-based professional was the source with the largest difference (72.1% vs 56.0%), followed by the NCAA (49.4% vs 36.6%). In addition, Black athletes noted use of the referee as a source of concussion information (8.2% vs 3.6%) more than White athletes. Findings were mostly similar when restricted to the football-only subsample, although the only statistically significant difference was for the NCAA (54.8% vs 37.0%).
Multivariable Poisson regression model to predict concussion symptom knowledge
Controlling for covariates, Black athletes were estimated to have a lower CSK score than White athletes among the entire sample (IRR = 0.97; 95% CI, 0.94-0.997) and football-only subsample (IRR = 0.96; 95% CI, 0.92-0.996) (see Table 3). Notably, in both models, having a concussion history and using mass media as a source of concussion information were also associated with higher CSK scores. In the model for all athletes, being female versus male and from Division III versus Division II were also associated with higher CSK scores.
Findings from this study suggest a disparity in CSK between Black and White collegiate-athletes, with Black athletes having lower CSK than White athletes. Athletic trainers were reported as a main source of concussion information for the majority of Black and White collegiate-athletes. Approximately 16% fewer Black athletes gained concussion knowledge from school-based professionals including a teacher, school nurse, or gym/health teacher than White athletes, and roughly 13% fewer Black athletes gained concussion knowledge from the NCAA than White athletes. Despite NCAA mandates requiring concussion education for athletes, the differences in CSK and information seeking highlight the need for equitable strategies to disseminate concussion information to diverse populations.
CONCUSSION SYMPTOM KNOWLEDGE
The NCAA mandates that all institutions have concussion safety procedures to better protect the health and safety of collegiate-athletes20; thus, all athletes, regardless of institution, gender, sport, or race, should have access to and receive concussion education. The current findings suggest that despite this, varying levels of knowledge exist between Black and White athletes. First, Black athletes recognized concussion symptoms to a lesser degree than their White peers. These results parallel prior research in the high school setting.10 Even for more common signs and symptoms of concussion that are frequently discussed, including dizziness, memory loss, difficulty concentrating, drowsiness, and feeling in a “fog,” considerable differences were noted between Black and White athletes, with Black athletes less frequently identifying them. Athletes who have an inability to recognize concussion symptoms may put their health at risk because it could potentially lead to not seeking medical care when needed. Immediate symptom recognition is pertinent to allied healthcare professionals providing appropriate, time-sensitive care for a concussion-related injury.3–5,7,21 Thus, it is essential that clinicians and scholars aim to understand the probable underlying mechanisms and causes of CSK disparities between Black and White collegiate-athletes.
Contextualizing how race may impact an athlete's capability to identify and recognize concussion symptoms may help better serve athletes from diverse backgrounds, including Black athletes and other minorities. Historically, in the United States, race has been a social and political classification that has stratified people, and this social stratification has consequently produced social inequalities and social inequities.13,22 Black communities are often marginalized within the US social context and are not typically provided the same equitable resources in healthcare access, standard of healthcare, and quality of healthcare afforded to White communities,22,23 which could lead to adverse health information–seeking behaviors, decreased confidence and trust in the healthcare system, and lower health literacy in this population. In addition, as noted in the socioecological framework, levels of influence are not independent and isolated but rather can interact with one another. In the context of concussion, community-level inequities have been linked to reduced access to concussion information and education among coaches and parents in communities with higher percentages of poverty and/or lower English fluency.12,24 Socioeconomic status (SES) intersects with race as research has shown that racial minorities are predominately inhabitants of lower socioeconomic areas and that Black individuals are more likely to have lower SES than White people.25,26 Therefore, Black collegiate-athletes have a higher probability of experiencing health-related inequities throughout their life than their White counterparts, which may contribute to the previous findings concerning racial disparities around concussion.10,27,28
All of these contributing factors of inequity and disparity at the community level, youth sports level, and high school sports level could impact exposure and/or receptiveness to concussion education materials that may ultimately explain the lower CSK of Black collegiate-athletes. To support this, Wallace et al6,10 found that Black high school athletes lacking access to an athletic trainer yielded the lowest CSK and that high school athletes attending lower SES urban schools also had a poorer understanding of concussion. Furthermore, biased and/or inequitable policies and practices within healthcare and resources provided prior to athletes' arrival at college may explain the disparities between Black and White athletes when identifying concussion symptoms. Thus, the disparity in CSK noted among Black collegiate-athletes could be continued from high school. In addition, specific to concussion-related resources and policies, Black parents have been shown to have lower concussion knowledge than White parents,29 lower resourced communities are less likely to have access to an athletic trainer,30 and urban schools are less likely to have defined concussion education policies and practices.31 Earlier exposure to concussion education, or a repetitive concussion education model, may improve concussion symptom identification, similar to the sentiments of Register-Mihalik et al,2 who indicated that improving concussion knowledge can have a positive influence on reporting behaviors and symptom recognition.
SOURCES OF CONCUSSION INFORMATION
The resources to which Black and White athletes have access to as collegiate-athletes could affect their abilities to correctly identify concussion symptoms. Furthermore, both the biased allocation of healthcare resources and the frequency of exposure to concussion information before being a collegiate-athlete may be the driving factor of the racial disparities seen in concussion symptom recognition. The current study did not collect information on prior sources of knowledge specific to previous settings but did examine sources of concussion information across various segments of the socioecological framework, such as interpersonal (family members, school-based professionals, sports stakeholders), social environment (mass media), and policy (organizations such as the NCAA). Although 4 of the 20 sources from which participants selected suggested higher use among White athletes than among Black athletes, the majority showed similar trending results. It can be assumed that Black individuals may obtain their health information through avenues that are different from those of White individuals. The current data support this theory, with White athletes reporting having gained concussion information from a school-based professional (ie, school nurse, teacher, gym/health teacher), other physician (ie, family doctor, pediatrician, etc), online media sources, and NCAA policy to a greater extent than Black athletes. These observed differences may again be linked to resource access limitations, the skepticism and mistrust Black individuals have with the healthcare system as a whole, or the lack of rapport Black athletes may have with their healthcare providers.
Racial distrust in medical resources and healthcare overall may be linked to historical instances of Black individuals being treated inferiorly in hospitals, given detrimental treatment/care with or without their consent (ie, Tuskegee experiments), and denied treatment and care altogether.22,32–34 Black individuals are also more likely to be uninsured, have Medicaid or Medicare, and have less exposure to routine scheduled visits with a healthcare provider that supports genuine relationship development.32,35 Some research has highlighted that Black individuals often have negative perceptions of their interactions with healthcare professionals compared with the more positive feelings expressed by White individuals.35 These negative experiences could be caused by lower representation of Black healthcare providers or Black patients having lower levels of health literacy or just a poorer understanding of medical jargon.35,36 Presently, racial differences in concussion information sources could be tied to how concussion information is directed or messaged, including poorer representation of Black or ethnic minorities, or linguistic partialities toward White hegemonic standards and pedagogies. Specific to potential issues with medical jargon on the concussion symptom checklist, “fatigue” and “nausea” are medical terms that may be more challenging for those with lesser medical familiarity to identify, of which these 2 symptoms displayed vast differences between Black and White athletes. Not being able to understand medical jargon as terms and expressions, while having a lack of familiarity navigating medical spaces, may also contribute to increased health disparities in concussion symptom identification.
FINDINGS SPECIFIC TO FOOTBALL ATHLETES
Lower CSK among racial minorities has now been identified at every level of sports.10,11,29 Adding to this, the current study also stratified CSK results among all athletes and football-only athletes. It could be presumed that the CSK differences within this study were the result of a large percentage of Black collegiate-athletes who participated in football as they have frequent exposure to concussion materials; however, when considering this subsample of collegiate-athletes, racial differences did not drastically sway from the overall sample findings. There were less statistically significant findings, which is likely due to the lower statistical power yielded from a smaller sample size.
These findings provide perspective for stakeholders to create effective targeted interventions that incorporate equitable methods to disseminate educational content to diverse athletic populations across all sports. To accomplish this, there must be an acknowledgment of underlying mechanisms and factors that could be contributing to racial differences. Furthermore, there must be a willingness to investigate where and how athletes are obtaining and retaining concussion-related information in order to create better patient-centered educational content aimed at enhancing concussion identification and disclosure.
Findings may not be generalizable to nonrespondents from participating institutions or other institutions that did not participate in this study. Of importance, this study was limited to Black and White athletes, and combining those who identified as mixed Black/White with those who identified as Black may not fully capture the potential unique experiences of these individuals. Moreover, fewer data from participants from other racial/ethnic groups (eg, n = 7 identified as Asian), limiting our ability to make other ethnic or culturally justified comparisons. Furthermore, this study utilized a newly adapted symptom checklist. Although use of the symptom checklist has been ongoing in concussion research, future studies should expand symptom knowledge exploration to more comprehensive metrics. Also, the list of concussion information sources utilized had limited psychometrics and may not be exhaustive; however, it encompasses multiple levels from the socioecological framework. Future studies aiming to address concussion health literacy, including knowledge, symptom identification, attitudes, and reporting behaviors, would benefit from contextualizing targeted communities and the demographic makeup of athletes and families. Such acknowledgment of community needs is warranted, particularly within lower socioeconomic communities where there may be a larger percentage of racial/ethnic minorities and poorer resources for concussion education.
Racial differences in CSK and the use of concussion information sources were found between Black and White collegiate-athletes. Specific differences were noted for a variety of sleep, affective, somatic, and cognitive symptoms. Also, Black and White athletes varied in the specific concussion information sources used. Such racial differences observed in this study underline an unacceptable disparity worthy of attention and underscore the need to identify strategies to ensure equitable access to concussion education and prevention. Moving forward, a conscious attempt is needed to redevelop concussion education initiatives as racially, culturally, and linguistically inclusive, addressing the needs of all collegiate-athletes equally and equitably.
1. McCrea M, Hammeke T, Olsen G, Leo P, Guskiewicz K. Unreported concussion in high school football players: implications for prevention. Clin J Sport Med. 2004;14(1):13–17. doi:10.1097/00042752-200401000-00003
2. Register-Mihalik JK, Guskiewicz KM, McLeod TC, Linnan LA, Mueller FO, Marshall SW. Knowledge, attitude, and concussion-reporting behaviors among high school athletes: a preliminary study. J Athl Train. 2013;48(5):645–653. doi:10.4085/1062-6050-48.3.20
3. Wallace J, Covassin T, Nogle S, Gould D, Kovan J. Knowledge of concussion and reporting behaviors in high school athletes with or without access to an athletic trainer. J Athl Train. 2017;52(3):228–235. doi:10.4085/1062-6050-52.1.07
4. Register-Mihalik J, Baugh C, Kroshus E, Zachary YK, Valovich McLeod TC. A Multifactorial approach to sport-related concussion prevention and education: application of the socioecological framework. J Athl Train. 2017;52(3):195–205. doi:10.4085/1062-6050-51.12.02
5. Kerr ZY, Register-Mihalik JK, Marshall SW, Evenson KR, Mihalik JP, Guskiewicz KM. Disclosure and non-disclosure of concussion and concussion symptoms in athletes: review and application of the socio-ecological framework. Brain Inj. 2014;28(8):1009–1021. doi:10.3109/02699052.2014.904049
6. Wallace J, Covassin T, Nogle S, Gould D, Kovan J. Concussion knowledge and reporting behavior differences between high school athletes at urban and suburban high schools. J Sch Health. 2017;87(9):665–674. doi:10.1111/josh.12543
7. Asken BM, McCrea MA, Clugston JR, Snyder AR, Houck ZM, Bauer RM. “Playing through it”: delayed reporting and removal from athletic activity after concussion predicts prolonged recovery. J Athl Train. 2016;51(4):329–335. doi:10.4085/1062-6050-51.5.02
8. Chrisman SP, Quitiquit C, Rivara FP. Qualitative study of barriers to concussive symptom reporting in high school athletics. J Adolesc Health. 2013;52(3):330–335.e333. doi:10.1016/j.jadohealth.2012.10.271
9. Kerr ZY, Chandran A, Nedimyer AK, et al. Use of sport-related concussion information sources among parents of United States middle school children. J Sport Health Sci. 2020;S2095-2546(20):30055–30057. doi:10.1016/j.jshs.2020.04.008
10. Wallace J, Covassin T, Moran R. Racial disparities in concussion knowledge and symptom recognition in American adolescent athletes. J Racial Ethn Health Disparities. 2018;5(1):221–228. doi:10.1007/s40615-017-0361-1
11. Kroshus E, Gillard D, Haarbauer-Krupa J, Goldman RE, Bickham DS. Talking with young children about concussions: an exploratory study. Child Care Health Dev. 2017;43(5):758–767. doi:10.1111/cch.12433
12. Kroshus E, Kerr ZY, Lee JGL. Community-level inequalities in concussion education of youth football coaches. Am J Prev Med. 2017;52(4):476–482. doi:10.1016/j.amepre.2016.12.021
13. Bailey ZD, Krieger N, Agenor M, Graves J, Linos N, Bassett MT. Structural racism and health inequities in the USA: evidence and interventions. Lancet. 2017;389(10077):1453–1463. doi:10.1016/S0140-6736(17)30569-X
14. Williams DR, Wyatt R. Racial bias in health care and health: challenges and opportunities. JAMA. 2015;314(6):555–556. doi:10.1001/jama.2015.9260
15. Doyle JM, Kao G. Are racial identities of multiracials stable? Changing self-identification among single and multiple race individuals. Soc Psychol Q. 2007;70(4):405–423.
16. Hitlin S, Scott Brown J, Elder GH Jr. Racial self-categorization in adolescence: multiracial development and social pathways. Child Dev. 2006;77(5):1298–1308. doi:10.1111/j.1467-8624.2006.00935.x
17. Rice SG; the Council on Sports Medicine and Fitness. Medical conditions affecting sports participation. Pediatrics. 2008;121(4):841–848. doi:10.1542/peds.2008-0080
18. Katz BP, Kudela M, Harezlak J, et al. Baseline performance of NCAA athletes on a concussion assessment battery: a report from the CARE Consortium. Sports Med. 2018;48(8):1971–1985. doi:10.1007/s40279-018-0875-7
19. Kontos AP, Elbin RJ, Schatz P, et al. A revised factor structure for the Post-Concussion Symptom Scale: baseline and postconcussion factors. Am J Sports Med. 2012;40(10):2375–2384. doi:10.1177/0363546512455400
20. Buckley TA, Baugh CM, Meehan WP 3rd, DiFabio MS. Concussion management plan compliance: a study of NCAA Power 5 Conference Schools. Orthop J Sports Med. 2017;5(4):2325967117702606. doi:10.1177/2325967117702606
21. Holmes L Jr, Tworig J, Casini J, et al. Implication of socio-demographics on cognitive-related symptoms in sports concussion among children. Sports Med Open. 2016;2(1):38. doi:10.1186/s40798-016-0058-8
22. Feagin J, Bennefield Z. Systemic racism and U.S. health care. Soc Sci Med. 2014;103:7–14. doi:10.1016/j.socscimed.2013.09.006
23. Benkert R, Peters RM, Clark R, Keves-Foster K. Effects of perceived racism, cultural mistrust and trust in providers on satisfaction with care. J Natl Med Assoc. 2006;98(9):1532–1540.
24. Kroshus E, Gonzalez LA, Chrisman SPD, Jimenez N. Availability of concussion information in Spanish for parents of youth athletes. Health Promot Pract. 2019;20(3):372–380. doi:10.1177/1524839918790231
25. Thurman WA, Johnson KE, Sumpter DF. Words matter: an integrative review of institutionalized racism in nursing literature. ANS Adv Nurs Sci. 2019;42(2):89–108. doi:10.1097/ANS.0000000000000265
26. Smedley BD, Stith AY, Nelson AR, eds. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. National Academies Press; 2003.
27. Wallace J, Covassin T, Moran R, Deitrick JM. Factors contributing to disparities in baseline neurocognitive performance and concussion symptom scores between Black and White collegiate athletes. J Racial Ethn Health Disparities. 2018;5(4):894–900. doi:10.1007/s40615-017-0437-y
28. Houck Z, Asken B, Clugston J, Perlstein W, Bauer R. Socioeconomic status and race outperform concussion history and sport participation in predicting collegiate athlete baseline neurocognitive scores. J Int Neuropsychol Soc. 2018;24(1):1–10. doi:10.1017/S1355617717000716
29. Bloodgood B, Inokuchi D, Shawver W, et al. Exploration of awareness, knowledge, and perceptions of traumatic brain injury among American youth athletes and their parents. J Adolesc Health. 2013;53(1):34–39. doi:10.1016/j.jadohealth.2013.01.022
30. Kroshus E, Rivara FP, Whitlock KB, Herring SA, Chrisman SPD. Disparities in athletic trainer staffing in secondary school sport: implications for concussion identification. Clin J Sport Med. 2017;27(6):542–547. doi:10.1097/JSM.0000000000000409
31. DePadilla L, Miller GF, Everett Jones JS. Characteristics of schools with youth sports concussion-related educational policies and practices. J Sch Health. 2020;90(7):520–526. doi:10.1111/josh.12900
32. Dickman SL, Himmelstein DU, Woolhandler S. Inequality and the health-care system in the USA. Lancet. 2017;389(10077):1431–1441. doi:10.1016/S0140-6736(17)30398-7
33. Armstrong K, McMurphy S, Dean LT, et al. Differences in the patterns of health care system distrust between blacks and whites. J Gen Intern Med. 2008;23(6):827–833. doi:10.1007/s11606-008-0561-9
34. Strekalova YA. When trust is not enough: a serial mediation model explaining the effect of race identity, eHealth information efficacy, and information behavior on intention to participate in clinical research. Health Educ Behav. 2018;45(6):1036–1042. doi:10.1177/1090198118757822
35. Shepherd SM, Willis-Esqueda C, Paradies Y, Sivasubramaniam D, Sherwood J, Brockie T. Racial and cultural minority experiences and perceptions of health care provision in a Mid-western region. Int J Equity Health. 2018;17(1):33. doi:10.1186/s12939-018-0744-x
36. Spiegel JM, Breilh J, Yassi A. Why language matters: insights and challenges in applying a social determination of health approach in a North-South collaborative research program. Global Health. 2015;11:9. doi:10.1186/s12992-015-0091-2