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Background: Growing evidence indicates early exercise may improve symptoms and reduce clinical recovery time after concussion, but research examining collegiate student-athletes is scarce. Objective: The aim of this study was to compare symptom recovery time, clinical recovery time, and persisting post-concussion symptom (i.e., symptoms ≥ 28 days) prevalence by the timing of light exercise initiation before the graded return to play (RTP) protocol among concussed participants. Methods: Collegiate student-athletes (n = 1228; age 18.4 ± 0.9 years; 56.5% male, 76.3% division I; 33.7% ≥ 1 prior concussion) across 30 institutions enrolled in the CARE Consortium completed post-concussion assessments and were monitored over time. Symptom recovery (days from injury to symptom resolution) and clinical recovery (days from injury to return to play protocol completion) was determined by the student-athletes' clinicians. Student-athletes were categorized by timing of light exercise initiation. Early (< 2 days post-concussion; n = 161), typical (3–7 days post-concussion; n = 281), and late exercise (≥ 8 days post-concussion; n = 169) groups were compared with the no-exercise group (n = 617; i.e., did not exercise prior to beginning the RTP protocol) for all analyses. Multivariable Cox regression models with hazard ratios (HR) and survival curves and a multivariable binomial regression model with prevalence ratios (PR) compared recovery outcomes between exercise groups while accounting for covariates. Results: Compared to the no-exercise group, the early exercise group was 92% more probable to experience symptom recovery (HR 1.92; 95% CI 1.57–2.36), 88% more probable to reach clinical recovery (HR 1.88; 95% CI 1.55–2.28) and took a median of 2.4 and 3.2 days less to recover, respectively. The late exercise group relative to the no-exercise group was 57% less probable to reach symptom recovery (HR 0.43; 95% CI 0.35–0.53), 46% less probable to achieve clinical recovery (HR 0.54; 95% CI 0.45–0.66) and took 5.3 days and 5.7 days more to recover, respectively. The typical exercise group did not differ in hazard for symptom or clinical recovery (p ≥ 0.329) compared with the no-exercise group. The prevalence of persisting post-concussion symptoms in the combined sample was 6.6%. Early exercise had 4% lower prevalence (PR 0.96, 95% CI 0.94–0.99) and typical exercise had 3% lower prevalence (PR 0.97, 95% CI 0.94–0.99) of persisting post-concussion symptoms, while the late exercise group had an elevated prevalence (PR 1.11, 95% CI 1.04–1.18) compared with the no-exercise group. Conclusion: Exercise < 2 days post-concussion was associated with more probable and faster symptom and clinical recovery, and lower persisting post-concussion symptom prevalence. When considering our findings and existing literature, qualified clinicians may implement early exercise into their clinical practice to provide therapeutic treatment and improve student-athlete recovery. [ABSTRACT FROM AUTHOR]

Background: Concussion pre-injury (i.e., baseline) assessments serve as a benchmark comparison point in the event an individual sustains a concussion and allows clinicians to compare to post-injury measures. However, baseline assessments must reflect the individual's true and most optimized performance to serve as a useful comparison. Mental fatigue and motivation throughout baseline testing may alter individual assessment performance, indicating an order of administration (OoA) may play an influential role in assessment outcomes. Objective: To examine the influence concussion baseline battery OoA has on symptom, postural stability, cognitive screening, and computerized neurocognitive test outcomes. Methods: We employed a retrospective observational cohort study to examine healthy collegiate student-athletes and military cadets (n = 2898, 19.0 ± 1.4 years, 66.1% male, 75.6% white, 54.4% Division-I) baseline assessment performance on the Sport Concussion Assessment Tool (SCAT; total symptom number and severity), Balance Error Scoring System (BESS; total error scores), Standardized Assessment of Concussion (SAC; total score), and Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) domain scores (verbal and visual memory, visual-motor speed, reaction time). Assessments were binned to beginning, middle, or end tertiles based upon OoA. We used one-way ANOVAs with Tukey post-hoc t tests, 95% confidence intervals (CI), and Cohen's d effect sizes for significant models (α = 0.05). Results: SCAT total symptom number (mean difference = 2.23; 95% CI 1.76–2.70; d = 0.49, p < 0.001) and severity (mean difference = 5.58; 95% CI 4.42–6.74; d = 0.50; p < 0.001) were lower when completed at the end of baseline testing compared to the middle. Total BESS errors were 1.06 lower when completed at the middle relative to the end (95% CI 0.43–1.69; d = 0.17; p = 0.001). Total SAC scores were better at the beginning relative to middle (mean difference = 0.58; 95% CI 0.25–0.90; d = 0.33; p < 0.001) and end (mean difference = 0.44; 95% CI 0.16–0.73; d = 0.24; p = 0.001). Verbal memory, visual memory, and reaction time performance were highest at the beginning (p ≤ 0.002), while visual-motor speed performance was highest at the middle (p = 0.001). Conclusion: Completing baseline assessments in the order of (1) ImPACT, (2) SAC, (3) BESS, and (4) SCAT symptom checklist may improve performance across assessments collectively. Clinicians and researchers should consider completing baseline assessments in this order when possible to potentially aid in optimizing concussion baseline assessment performance and maximize post-concussion comparisons. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In the recently published article "Mental Health in the Young Athlete" the following author name was inadvertently misspelled as Christine L. Master. The correct spelling of the author's name is: Christina L. Master as shown above. [ABSTRACT FROM AUTHOR]

Purpose Of Review: The goal of the present paper is to provide a comprehensive overview of mental health concerns in young athletes, with a focus on common disorders, as well as population-specific risk factors.Recent Findings: Athletes experience similar mental health concerns as non-athlete peers, such as anxiety, depression and suicidal ideation, ADHD, eating disorders, and substance abuse. However, they also experience unique stressors that put them at risk for the development or exacerbation of mental health disorders. Student athletes have to balance academics with rigorous training regimens while focusing on optimal performance and managing high expectations. Physical injuries, overtraining, concussion, sleep disorders, and social identity are some of the factors that also impact the mental health of student athletes. Existing literature highlights the need to develop proactive mental health and wellness education for young athletes, and to develop services that recognize the unique needs of this population. [ABSTRACT FROM AUTHOR]