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Background: Studies have evaluated individual factors associated with persistent postconcussion symptoms (PPCS) in youth concussion, but no study has combined individual elements of common concussion batteries with patient characteristics, comorbidities, and visio-vestibular deficits in assessing an optimal model to predict PPCS. Purpose: To determine the combination of elements from 4 commonly used clinical concussion batteries and known patient characteristics and comorbid risk factors that maximize the ability to predict PPCS. Study Design: Cohort study; Level of evidence, 2. Methods: We enrolled 198 concussed participants—87 developed PPCS and 111 did not—aged 8 to 19 years assessed within 14 days of injury from a suburban high school and the concussion program of a tertiary care academic medical center. We defined PPCS as a Post-Concussion Symptom Inventory (PCSI) score at 28 days from injury of ≥3 points compared with the preinjury PCSI score—scaled for younger children. Predictors included the individual elements of the visio-vestibular examination (VVE), Sport Concussion Assessment Tool, 5th Edition (SCAT-5), King-Devick test, and PCSI, in addition to age, sex, concussion history, and migraine headache history. The individual elements of these tests were grouped into interpretable factors using sparse principal component analysis. The 12 resultant factors were combined into a logistic regression and ranked by frequency of inclusion into the combined optimal model, whose predictive performance was compared with the VVE, initial PCSI, and the current existing predictive model (the Predicting and Prevention Postconcussive Problems in Pediatrics (5P) prediction rule) using the area under the receiver operating characteristic curve (AUC). Results: A cluster of 2 factors (SCAT-5/PCSI symptoms and VVE near point of convergence/accommodation) emerged. A model fit with these factors had an AUC of 0.805 (95% CI, 0.661-0.929). This was a higher AUC point estimate, with overlapping 95% CIs, compared with the PCSI (AUC, 0.773 [95% CI, 0.617-0.912]), VVE (AUC, 0.736 [95% CI, 0.569-0.878]), and 5P Prediction Rule (AUC, 0.728 [95% CI, 0.554-0.870]). Conclusion: Among commonly used clinical assessments for youth concussion, a combination of symptom burden and the vision component of the VVE has the potential to augment predictive power for PPCS over either current risk models or individual batteries. [ABSTRACT FROM AUTHOR]

Background: A validated clinical risk tool has been developed to identify pediatric and adolescent patients at risk of developing persisting symptoms after concussion, but has not been prospectively investigated within a sample of athletes seen after concussion by primary care sports medicine physicians and/or athletic trainers. Purpose: To determine whether a validated clinical risk prediction tool for persistent postconcussive symptoms (PPCSs) predicted which patients would develop PPCSs when obtained within 14 days of concussion among a multicenter sample of adolescent athletes. Study Design: Cohort study; Level of evidence, 2. Methods: Pediatric and adolescent patients (8-18 years of age) from 7 pediatric medical centers and 6 secondary school athletic training facilities who were diagnosed with a concussion and presented ≤14 days after concussion were enrolled as part of the Sport Concussion Outcomes in Pediatrics (SCOPE) study during their initial visit and were followed until symptom resolution. Clinical risk scores (Predicting and Preventing Post-concussive Problems in Pediatrics [5P]) and total symptom severity were obtained using the Post-Concussion Symptom Inventory at the initial visit (mean, 4.9 ± 2.9 days after concussion). Participants were then compared based on symptom resolution time: PPCS group (≥28 days to symptom resolution) and no-PPCS group (<28 days). The authors assessed the odds of developing PPCSs based on the 5P risk score using a binary logistic regression model and the utility of the clinical risk prediction tool to identify total time to symptom resolution using a Cox proportional hazards model. Results: A total of 184 participants enrolled, underwent initial evaluation, and were followed until symptom resolution (mean age, 15.2 ± 2.1 years; 35% female). The mean time to symptom resolution across the entire sample was 17.6 ± 3.7 days; 16% (n = 30) of participants developed PPCS. Those in the PPCS group had significantly greater mean initial total 5P risk scores than those in the no-PPCS group (7.9 ± 1.7 vs 5.9 ± 2.3, respectively; P <.001). After adjustment for initial symptom severity, time to assessment, and assessment setting, a higher initial total 5P risk score was associated with a significantly greater odds of developing PPCSs (adjusted odds ratio, 1.49; 95% CI, 1.07-2.08; P =.019). Furthermore, a higher 5P risk score was significantly associated with longer total symptom resolution time (hazard ratio, 0.80; 95% CI, 0.74-0.88; P <.001). Conclusion: In a multicenter sample of youth athletes seen in different outpatient health care settings, the 5P risk score accurately predicted which athletes may be at risk for developing PPCSs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Although most children report symptom resolution within a month of a concussion, some patients experience persistent postconcussion symptoms (PPCS) that continues for more than 1 month. Identifying patients at risk for PPCS soon after an injury can provide useful clinical information. Purpose: To determine if the Predicting Persistent Post-concussive Problems in Pediatrics (5P) clinical risk score, an emergency department (ED)--derived and validated tool, is associated with developing PPCS when obtained in a primary care sports concussion setting. Study Design: Cohort study; Level of evidence, 3. Methods: We conducted a study of patients seen at a pediatric sports medicine concussion clinic between May 1, 2013, and October 1, 2017, who were <19 years of age and evaluated within 10 days of a concussion. The main outcome was PPCS, defined as symptoms lasting >28 days. Nine variables were used to calculate the 5P clinical risk score, and we assessed the association between the 5P clinical risk score and PPCS occurrence. The secondary outcome was total symptom duration. Results: We examined data from 230 children (mean age, 14.8 6 2.5 years; 50% female; mean time from injury to clinical assessment, 5.6 6 2.7 days). In univariable analyses, a greater proportion of those who developed PPCS reported feeling slowed down (72% vs 44%, respectively; P< .001), headache (94% vs 72%, respectively; P < .001), sensitivity to noise (71% vs 43%, respectively; P< .001), and fatigue (82% vs 51%, respectively; P <.001) and committed ≥4 errors in tandem stance (33%vs 7%, respectively; P< .001) than those who did not. Higher 5P clinical risk scores were associated with increased odds of developing PPCS (adjusted odds ratio [OR], 1.62 [95%CI, 1.30-2.02]) and longer symptom resolution times (β = 8.40 [95%CI, 3.25-13.50]). Among the individual participants who received a high 5P clinical risk score (9-12), the majority (82%) went on to experience PPCS. The area under the curve for the 5P clinical risk score was 0.75 (95% CI, 0.66-0.84). After adjusting for the effect of covariates, fatigue (adjusted OR, 2.93) and ≥4 errors in tandem stance (adjusted OR, 7.40) were independently associated with PPCS. Conclusion: Our findings extend the potential use for an ED-derived clinical risk score for predicting the PPCS risk into the sports concussion clinic setting. While not all 9 predictor variables of the 5P clinical risk score were independently associated with the PPCS risk in univariable or multivariable analyses, the combination of factors used to calculate the 5P clinical risk score was significantly associated with the odds of developing PPCS. Thus, obtaining clinically pragmatic risk scores soon after a concussion may be useful for early treatments or interventions to mitigate the PPCS risk. [ABSTRACT FROM AUTHOR]

Background: Neck pain in a concussion population is an emerging area of study that has been shown to have a negative influence on recovery. This effect has not yet been studied in collegiate athletes., Hypothesis: New or worsened neck pain is common after a concussion (>30%), negatively influences recovery, and is associated with patient sex and level of contact in sport., Study Design: Cohort study; Level of evidence, 2., Methods: Varsity-level athletes from 29 National Collegiate Athletic Association member institutions as well as nonvarsity sport athletes at military service academies were eligible for enrollment. Participants completed a preseason baseline assessment and follow-up assessments at 6 and 24 to 48 hours after a concussion, when they were symptom-free, and when they returned to unrestricted play. Data collection occurred between January 2014 and September 2018., Results: A total of 2163 injuries were studied. New or worsened neck pain was reported with 47.0% of injuries. New or worsened neck pain was associated with patient sex (higher in female athletes), an altered mental status after the injury, the mechanism of injury, and what the athlete collided with. The presence of new/worsened neck pain was associated with delayed recovery. Those with new or worsened neck pain had 11.1 days of symptoms versus 8.8 days in those without ( P < .001). They were also less likely to have a resolution of self-reported symptoms in ≤7 days ( P < .001). However, the mean duration of the return-to-play protocol was not significantly different for those with new or worsened neck pain (7.5 ± 7.7 days) than those without (7.4 ± 8.3 days) ( P = .592)., Conclusion: This novel study shows that neck pain was common in collegiate athletes sustaining a concussion, was influenced by many factors, and negatively affected recovery., Competing Interests: One or more of the authors has declared the following potential conflict of interest or source of funding: This publication was made possible in part by the National Collegiate Athletic Association (NCAA) and the United States DOD. The United States Army Medical Research Acquisition Activity (USAMRAA) is the awarding and administering acquisition office. This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Combat Casualty Care Research Program, endorsed by the DOD, and the Joint Program Committee 6/Combat Casualty Care Research Program–Psychological Health and Traumatic Brain Injury Research Program (W81XWH-14-2-0151). J.A.K. has received research funding from the National Chiropractic Mutual Insurance Company (NCMIC) and speaking honoraria from the Wisconsin Chiropractic Association. L.D.N. has received funding for unrelated research from the National Institute of Neurological Disorders and Stroke (NINDS), the Centers for Disease Control and Prevention (CDC), the DOD, the Medical Technology Enterprise Consortium, and the Medical College of Wisconsin–Advancing a Healthier Wisconsin Endowment and consulting fees for grant reviewing (DOD) and research (NINDS). B.B. has received grants from the National Institute on Aging and the NINDS, travel reimbursements for presenting at conferences, and a $500 honorarium in 1 instance. J.G. has received funding for unrelated research from the NCMIC and consulting fees for chiropractic education accreditation reviewing from the Council on Chiropractic Education. S.P.B. has received research funding from the National Institutes of Health (NIH), the CDC, the DOD-USAMRAA, the NCAA, the National Athletic Trainers’ Association, National Football League (NFL)/Under Armour/GE, Simbex, and ElMindA; has consulted for US Soccer (paid), USA Cycling (unpaid), the University of Calgary SHRed Concussions external advisory board (unpaid), and medicolegal litigation cases; has received speaker honoraria and travel reimbursements for talks given; is a coauthor of Biomechanics of Injury, 3rd Edition; has a patent on “Brain Metabolism Monitoring Through CCO Measurements Using All-Fiber-Integrated Super-Continuum Source” (US 11,529,091 B2); and is/was on the editorial boards (all unpaid) for the Journal of Athletic Training (2015-present), Concussion (2014-present), Athletic Training & Sports Health Care (2008-present), and the British Journal of Sports Medicine (2008-2019). T.W.M. has received research funding from the NCAA and the DOD to complete this work (travel funds to attend scientific conferences and present data were included in the budget of those grants), has received royalties from American Psychiatric Association Publishing for a textbook on traumatic brain injuries that he coedited, and is a member of the concussion scientific advisory committee for the Australian Football League (uncompensated). M.M. has received research funding through the Medical College of Wisconsin from the NIH, the DOD, the Department of Veterans Affairs, the CDC, NFL, the NCAA, and Abbott Laboratories; is a consultant to NeuroTrauma Sciences and a clinical consultant to the Green Bay Packers; and has received honoraria and travel support for professional speaking engagements. T.B. has received funding from the NCAA/DOD Concussion Assessment, Research and Education (CARE) Consortium as part of this study and industry funding from Statespace (no data from this study are related to that funding). J.T.G. has received honoraria from Pacira. H.J.B. has received support for education from Medwest Associates. C.L.M. has received a grant from DJO. A.K. has received book royalties from APA Books and research funding through the University of Pittsburgh from the CDC, the Chuck Noll Foundation for Brain Injury Research, the DOD (Congressionally Directed Medical Research Program, USAMRAA, Uniformed Services University of the Health Sciences), NFL, the NIH (National Institute of Child Health and Human Development, National Institute of Mental Health, NINDS), and private donors. N.P. has received funding from the NCAA/DOD CARE Consortium (W81XWH-14-2-0151), the DOD (W81XWH-20-1-0717), and the Indiana Spinal Cord and Brain Injury Research Fund and unrestricted funds from Statespace. AOSSM checks author disclosures against the Open Payments Database (OPD). AOSSM has not conducted an independent investigation on the OPD and disclaims any liability or responsibility relating thereto.

Background: Few previous studies have investigated how different injury mechanisms leading to sport-related concussion (SRC) in soccer may affect outcomes., Purpose: To describe injury mechanisms and evaluate injury mechanisms as predictors of symptom severity, return to play (RTP) initiation, and unrestricted RTP (URTP) in a cohort of collegiate soccer players., Study Design: Cohort study; Level of evidence, 2., Methods: The Concussion Assessment, Research and Education (CARE) Consortium database was used. The mechanism of injury was categorized into head-to-ball, head-to-head, head-to-body, and head-to-ground/equipment. Baseline/acute injury characteristics-including Sports Concussion Assessment Tool-3 total symptom severity (TSS), loss of consciousness (LOC), and altered mental status (AMS); descriptive data; and recovery (RTP and URTP)-were compared. Multivariable regression and Weibull models were used to assess the predictive value of the mechanism of injury on TSS and RTP/URTP, respectively., Results: Among 391 soccer SRCs, 32.7% were attributed to a head-to-ball mechanism, 27.9% to a head-to-body mechanism, 21.7% to a head-to-head mechanism, and 17.6% to a head-to-ground/equipment mechanism. Event type was significantly associated with injury mechanism [χ 2 (3) = 63; P < .001), such that more head-to-ball concussions occurred in practice sessions (n = 92 [51.1%] vs n = 36 [17.1%]) and more head-to-head (n = 65 [30.8%] vs n = 20 [11.1]) and head-to-body (n = 76 [36%] vs n = 33 [18.3%]) concussions occurred in competition. The primary position was significantly associated with injury mechanism [χ 2 (3) = 24; P < .004], with goalkeepers having no SRCs from the head-to-head mechanism (n = 0 [0%]) and forward players having the least head-to-body mechanism (n = 15 [19.2%]). LOC was also associated with injury mechanism ( P = .034), with LOC being most prevalent in head-to-ground/equipment. Finally, AMS was most prevalent in head-to-ball (n = 54 [34.2%]) and head-to-body (n = 48 [30.4%]) mechanisms [χ 2 (3) = 9; P = .029]. In our multivariable models, the mechanism was not a predictor of TSS or RTP; however, it was associated with URTP ( P = .044), with head-to-equipment/ground injuries resulting in the shortest mean number of days (14 ± 9.1 days) to URTP and the head-to-ball mechanism the longest (18.6 ± 21.6 days)., Conclusion: The mechanism of injury differed by event type and primary position, and LOC and AMS were different across mechanisms. Even though the mechanism of injury was not a significant predictor of acute symptom burden or time until RTP initiation, those with head-to-equipment/ground injuries spent the shortest time until URTP, and those with head-to-ball injuries had the longest time until URTP., Competing Interests: One or more of the authors has declared the following potential conflict of interest or source of funding: This project was supported, in part, by the Grand Alliance Sport-Related Concussion Assessment, Research, and Education (CARE) Consortium, funded, in part by the National Collegiate Athletic Association (NCAA) and the DoD. The U.S. Army Medical Research Acquisition Activity is the awarding and administering acquisition office. This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Psychological Health and Traumatic Brain Injury Program under award No. W81XWH-14-2-0151. A.J.B. has been part of projects that have received funding from the DoD, the National Operating Committee on Standards from Athletic Equipment, the National Athletic Trainer's Association (NATA) Research and Education Foundation, and the NCAA. P.F.P. is an employee of the DoD and has previously received other DoD-related grants. T.W.M. has received research support from the NCAA, the US DoD, and the National Institutes of Health (NIH). He also reports textbook royalties from American Psychiatric Press Publishing Inc and serves on the Concussion Committee Scientific Advisory Board for the Australian Football League. M.A.M. has received research funding from the NIH, the Centers for Disease Control and Prevention (CDC), the DoD, the NCAA, the National Football League (NFL), and Abbott Laboratories. S.P.B. has received research funding from the NIH, the CDC, the DoD-USA Medical Research Acquisition Activity, the NCAA, the NATA Research and Education Foundation, the NFL/Under Armour/GE, Simbex, and ElmindA. He has consulted for US Soccer, US Cycling, the University of Calgary SHRed Concussions external advisory board, and medicolegal litigation. S.L.Z. is a member of the NFL Head, Neck, and Spine Committee. D.P.T. serves as a scientific advisor for HitIQ. He previously consulted for REACT Neuro Inc. He has a consulting practice in forensic neuropsychology, including expert testimony, involving individuals who have sustained mild traumatic brain injury (including former athletes). AOSSM checks author disclosures against the Open Payments Database (OPD). AOSSM has not conducted an independent investigation on the OPD and disclaims any liability or responsibility relating thereto.

Background: Identifying separate dimensions of concussion symptoms may inform a precision medicine approach to treatment. It was previously reported that a bifactor model identified distinct acute postconcussion symptom dimensions., Purpose: To replicate previous findings of a bifactor structure of concussion symptoms in the Concussion Assessment Research and Education (CARE) Consortium sample, examine measurement invariance from pre- to postinjury, and evaluate whether factors are associated with other clinical and biomarker measures., Study Design: Cohort study (Diagnosis); Level of evidence, 2., Methods: Collegiate athletes were prospectively evaluated using the Sport Concussion Assessment Tool-3 (SCAT-3) during preseason (N = 31,557); 2789 were followed at <6 hours and 24 to 48 hours after concussion. Item-level SCAT-3 ratings were analyzed using exploratory and confirmatory factor analyses. Bifactor and higher-order models were compared for their fit and interpretability. Measurement invariance tested the stability of the identified factor structure across time. The association between factors and criterion measures (clinical and blood-based markers of concussion severity, symptom duration) was evaluated., Results: The optimal structure for each time point was a 7-factor bifactor model: a General factor, on which all items loaded, and 6 specific factors-Vestibulo-ocular, Headache, Sensory, Fatigue, Cognitive, and Emotional. The model manifested strict invariance across the 2 postinjury time points but only configural invariance from baseline to postinjury. From <6 to 24-48 hours, some dimensions increased in severity (Sensory, Fatigue, Emotional), while others decreased (General, Headache, Vestibulo-ocular). The factors correlated with differing clinical and biomarker criterion measures and showed differing patterns of association with symptom duration at different time points., Conclusion: Bifactor modeling supported the predominant unidimensionality of concussion symptoms while revealing multidimensional properties, including a large dominant General factor and 6 independent factors: Headache, Vestibulo-ocular, Sensory, Cognitive, Fatigue, and Emotional. Unlike the widely used SCAT-3 symptom severity score, which declines gradually after injury, the bifactor model revealed separable symptom dimensions that have distinct trajectories in the acute postinjury period and different patterns of association with other markers of injury severity and outcome., Clinical Relevance: The SCAT-3 total score remains a valuable, robust index of overall concussion symptom severity, and the specific factors identified may inform management strategies. Because some symptom dimensions continue to worsen in the first 24 to 48 hours after injury (ie, Sensory, Fatigue, Emotional), routine follow-up in this time frame may be valuable to ensure that symptoms are managed effectively.

Background: Organizations recommend that athletes should be asymptomatic or symptom-limited before initiating a graduated return-to-play (GRTP) protocol after sports-related concussion, although asymptomatic or symptom-limited is not well-defined., Hypotheses: (1) There will be a range (ie, beyond zero as indicator of "symptom-free") in symptom severity endorsement when athletes are deemed ready to initiate a GRTP protocol. (2) Baseline symptom severity scores and demographic/preinjury medical history factors influence symptom severity scores at the commencement of the GRTP protocol. (3) Greater symptom severity scores at GRTP protocol initiation will result in longer protocol duration. (4) Symptom severity scores will not differ between those who did and did not sustain a repeat injury within 90 days of their initial injury., Study Design: Cohort study; Level of evidence, 2., Methods: Across 30 universities, athletes (N = 1531) completed assessments at baseline and before beginning the GRTP protocol, as determined by local medical staff. Symptom severity scores were recorded with the symptom checklist of the Sport Concussion Assessment Tool-3rd Edition. Nonparametric comparisons were used to examine the effect of medical, demographic, and injury factors on symptom endorsement at GRTP protocol initiation, as well as differences in symptom severity scores between those who did and did not sustain a repeat injury within 90 days. A Cox regression was used to examine the association between symptom severity scores at GRTP protocol initiation and protocol duration., Results: Symptom severity scores at the time when the GRTP protocol was initiated were as follows: 0 to 5 (n = 1378; 90.0%), 6 to 10 (n = 76; 5.0%), 11 to 20 (n = 42; 3.0%), and ≥21 (n = 35; 2.0%). Demographic (sex and age), medical (psychiatric disorders, attention-deficit/hyperactivity disorder, learning disorder), and other factors (baseline symptom endorsement and sleep) were significantly associated with higher symptom severity scores at the GRTP initiation ( P < .05). The 4 GRTP initiation time point symptom severity score groups did not significantly differ in total time to unrestricted RTP, χ 2 (3) = 1.4; P = .73. When days until the initiation of the GRTP protocol was included as a covariate, symptom severity scores between 11 and 20 ( P = .02; hazard ratio = 1.44; 95% CI, 1.06-1.96) and ≥21 ( P < .001; hazard ratio = 1.88; 95% CI, 1.34-2.63) were significantly associated with a longer GRTP protocol duration as compared with symptom severity scores between 0 and 5. Symptom severity scores at GRTP initiation did not significantly differ between those who sustained a repeat injury within 90 days and those who did not ( U = 29,893.5; P = .75)., Conclusion: A range of symptom severity endorsement was observed at GRTP protocol initiation, with higher endorsement among those with higher baseline symptom endorsement and select demographic and medical history factors. Findings suggest that initiation of a GRTP protocol before an absolute absence of all symptoms is not associated with longer progression of the GRTP protocol, although symptom severity scores >10 were associated with longer duration of a GRTP protocol. Results can be utilized to guide clinicians toward optimal GRTP initiation (ie, balancing active recovery with avoidance of premature return to activity).

Background: A student-athlete's mental state, including history of trait anxiety and depression, or current psychological state may affect baseline concussion assessment performance., Purpose: (1) To determine if mental illness (anxiety, depression, anxiety with depression) influences baseline scores, (2) to determine if psychological state correlates with baseline performance, and (3) to determine if history of concussion affects Brief Symptom Inventory-18 (BSI-18) subscores of state anxiety, depression, and somatization., Study Design: Cross-sectional study; Level of evidence, 3., Methods: A sample of 8652 collegiate student-athletes (54.5% males, 45.5% females) participated in the Concussion Assessment, Research and Education (CARE) Consortium. Baseline assessments included a demographic form, a symptom evaluation, Standardized Assessment of Concussion, Balance Error Scoring System, a psychological state assessment (BSI-18), and Immediate Post-concussion Assessment and Cognitive Test. Baseline scores were compared between individuals with a history of anxiety (n = 59), depression (n = 283), and anxiety with depression (n = 68) and individuals without a history of those conditions (n = 8242). Spearman's rho correlations were conducted to assess the relationship between baseline and psychological state subscores (anxiety, depression, somatization) (α = .05). Psychological state subscores were compared between individuals with a self-reported history of concussions (0, 1, 2, 3, 4+) using Kruskal-Wallis tests (α = .05)., Results: Student-athletes with anxiety, depression, and anxiety with depression demonstrated higher scores in number of symptoms reported (anxiety, 4.3 ± 4.2; depression, 5.2 ± 4.8; anxiety with depression, 5.4 ± 3.9; no anxiety/depression, 2.5 ± 3.4), symptom severity (anxiety, 8.1 ± 9.8; depression, 10.4 ± 12.4; anxiety with depression, 12.4 ± 10.7; no anxiety/depression, 4.1 ± 6.9), and psychological distress in state anxiety (anxiety, 3.7 ± 4.7; depression, 2.5 ± 3.6; anxiety with depression, 3.8 ± 4.2; no anxiety/depression, 0.8 ± 1.8), depression (anxiety, 2.4 ± 4.0; depression, 3.2 ± 4.5; anxiety with depression, 3.8 ± 4.8; no anxiety/depression, 0.8 ± 1.8), and somatization (anxiety, 2.3 ± 2.9; depression, 1.8 ± 2.8; anxiety with depression, 2.2 ± 2.4; no anxiety/depression, 0.9 ± 1.7). A moderate positive relationship existed between all BSI-18 subscores and total symptom number (n = 8377; anxiety: r s = 0.43, P < .001; depression: r s = 0.42, P < .001; somatization: r s = 0.45, P < .001), as well as total symptom severity (anxiety: r s = 0.43, P < .001; depression: r s = 0.41, P < .001; somatization: r s = 0.45, P < .001). Anxiety, depression, and somatization subscores were greater among student-athletes that self-reported more concussions., Conclusion: Clinicians should be cognizant that student-athletes with a history of trait anxiety, depression, and anxiety with depression may report higher symptom score and severity at baseline. Individuals with extensive concussion history may experience greater state anxiety, depression, and somatization.