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Context: Race has been shown to influence computerized neurocognitive test scores, motor function test scores, and reported symptomology following sport-related concussion (SRC). However, the effect race may have on recovery time following SRC remains unknown. The objective of this study was to determine the influence of race on days until symptom free from SRC in NCAA Division 1 collegiate athletes. Design: Prospective cohort study. Methods: Participants were Black (n = 53 [28% female]) and White (n = 150 [43.3% female]) who were on average 19.0 (1.21) and 20.2 (1.3) years of age, respectively. Data were collected from the 2015–2016 to 2020–2021 collegiate sport seasons. Participants were evaluated before and after an SRC at empirically derived time points. The primary outcome measure was time until symptom free (days). Additional outcomes included baseline and postinjury Immediate Postconcussion Assessment and Cognitive Test and Sensory Organization Test (SOT) scores. A Mann–Whitney U test compared days to symptom free between groups. Immediate Postconcussion Assessment and Cognitive Test and SOT outcome scores were analyzed using a 2 (group) × 2 (time) analysis of variance. Results: White participants had a longer median recovery time (9 d) to symptom free compared with Black participants (6 d [P = .04]). Statistically significant differences were observed between Black 87.3 (9.84) and White 90.4 (8.30) groups for Immediate Postconcussion Assessment and Cognitive Test’s verbal memory composite score (P = .03). Postinjury, White participants scored significantly higher 44.5 (5.63) on visual motor speed compared with Black participants (42.4 (5.90) [P = .02]). Within-group SOT differences between baseline and postinjury testing were observed in both groups (all P < .001). Conclusions: Black collegiate athletes achieved symptom resolution sooner than White athletes. We did not explore underlying sociocultural factors such as socioeconomic status or previous concussion education, which may have influenced our results. Future studies should explore factors that may contextualize these findings.

Suicide and contributing mental health conditions in athletes are shared concerns within health care and society at large. This commentary focuses on suicide risk among athletes and the role of sports medicine professionals in preventing suicide and promoting mental health. In this commentary, we draw on the scientific literature and our clinical experiences to pose and answer these questions: Does suicide risk among athletes vary by sociodemographic factors (eg, sex, gender, race/ethnicity, family income, sexual orientation) or if injured? Do sociodemographic differences influence access to and benefits from services among athletes? How do I know my athletes are at risk for suicide? What do I do if one of my athletes shares with me that they have considered suicide? Within our commentary, we review the current literature and clinical practices regarding these questions and close with actionable suggestions and recommendations for future directions.

Context: While increasing telehealth use throughout sports medicine has improved patients’ access to health care, some communities may not have the same opportunities to connect with a provider. Barriers to telehealth implementation can be influenced by internal (eg, provider’s digital health literacy and resources) and external (eg, community’s social determinants of health or “SDOH”) factors. This study aimed to assess the impact of internal and external factors on telehealth use by athletic trainers (ATs). Design: Cross-sectional survey. Methods: In total, 767 ATs participated in the study. Participants (age = 39 [13] y) completed a survey containing the electronic health literacy scale and digital health literacy instrument, reported professional use of telehealth as a provider (yes/no), provided resources at their clinical site, and provided the zip code for the community they served. After data collection, the researchers extracted SDOH information using the zip code data from 2 US databases, including population density, median household income, poverty index, education level, and technology access. Chi-square or independent samples t tests were conducted to compare telehealth use by each SDOH factor. Results: In total, 62.3% (n = 478/767) of ATs reported using telehealth, and 81.6% of ATs (n = 626) had a dedicated facility to offer health care services. We identified a significant difference in digital health literacy scores between users and nonusers of telehealth (P = .013). We did not identify any significant differences between telehealth users by community type (P = .957), population density (P = .053), income (P = .462), poverty index (P = .073), and computer (P = .211) or broadband internet access (P = .295). Conclusions: Our data suggest that internal factors such as digital health literacy and clinical site resources may have contributed to an AT’s previous telehealth use in clinical practice. However, the SDOH data extracted from the community zip code where the AT provided clinical services were similar for those with and without previous telehealth use.

Context: Collegiate athletes who are deaf or hard-of-hearing (D/HoH) are diagnosed with concussions at a similar rate as athletes who are hearing; however, little evidence exists on knowledge and attitudes of athletes who are D/HoH toward concussions. This study aimed to examine differences in knowledge of and attitudes toward concussions between athletes who are D/HoH and athletes who are hearing. Design: Cross-sectional research design. Methods: Of the 310 athletes who are D/HoH and 430 athletes who are hearing that were invited to participate, 90 athletes who are D/HoH, and 72 athletes who are hearing completed the survey. The Rosenbaum Concussion Knowledge and Attitudes Survey was used to quantify knowledge of and attitude toward concussions. The Rosenbaum Concussion Knowledge and Attitudes Survey consists of the concussion knowledge index (CKI) and the concussion attitudes index (CAI) subscales. Linear regressions were run to test the association of hearing status with CKI and CAI scores. Pearson correlations were performed to determine relationships between CKI and CAI for athletes who are D/HoH and athletes who are hearing. Alpha level was set a priori at P ≤ .05. Results: Athletes who are hearing demonstrated a higher CKI component score (19.58 [2.19]) compared to athletes who are D/HoH (16.14 [3.31]; P < .001). There were no statistical differences in CAI between hearing groups (hearing: 57.18 [8.73], D/HoH: 55.97 [9.92]; P = .41). There was a moderate positive correlation between CKI and CAI (r = .58) for athletes who are D/HoH, while a weak positive correlation (r = .30) for athletes who are hearing was observed. Conclusions: Athletes who are D/HoH have poorer knowledge of concussions but similar attitudes toward concussion as that of athletes who are hearing. Current concussion educational interventions are in written or spoken form which may not be inclusive to athletes who are D/HoH. Health care professionals should consider an athlete’s preferred communication mode to improve the efficiency and effectiveness of education.