Objective To evaluate the performance and test–retest reliability obtained when administering a computerized baseline neurocognitive exam to NCAA Division I student-athletes in a controlled laboratory setting versus an uncontrolled remote location. Method A sample of 129 (female = 100) Division I student-athletes completed Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) pre-season assessments for two distinct and respective sports seasons in a controlled laboratory environment and an uncontrolled remote environment. Depending on the environment, participants were given verbal (controlled) or written (uncontrolled) guidelines for taking the test. Results Multivariate repeated-measures ANOVA’s determined that there were no within-subject differences between testing environments on ImPACT composite scores and cognitive efficiency index (CEI). The Chi-square test did not find any significant differences in impulse control or the number of invalid test scores, as determined by ImPACT, between environments. Intraclass correlations found the ImPACT subtest scores to range in test–retest reliability across testing environments, demonstrating moderate (verbal memory composite, r = 0.46; visual memory composite, r = 0.64; reaction time, r = 0.61; impulse control, r = 0.52; and CEI, r = 0.61) and good (visual motor composite, r = 0.77) test–retest reliability. Conclusions Results indicate that ImPACT is reliable between controlled and uncontrolled testing environments. This further suggests that ImPACT can be administered in a remote environment, pending specific adherence to testing instructions, or in the event of social distancing or isolation policies.
incident of lower extremity injury of fencers. Then, athletes were divided into 2 groups according to incident of injury, the I group (I Group,age:22±2years, female=15,male=11) and the noninjury group (N Group,age:22±2years, female=14,male=18): ① The difference between groups was determined to analysis by Student's t test;② The correlation of FMS and incident of injury were determined to analysis by Student's t test Pearson correlation;③ The cut off value of FMS were determined to analysis by Receiver operating characteristic curve, that is calculated by chisquare test. RESULTS:(1)The incident of lower extremity injury accounting for 64.0% of fencers in 2020 world cup season (thigh and calf (20.0%), knee (25.3%), and ankle (8.7%)). ( 2) Compared with N group: total scores of FMS of I group is significantly lower than N group, the diffidence is 5.0% (P<0.05); Besides, individual FMS movements of DS and HS show significant differences between two groups. the differences are 12.1% (P<0.05) and 8.2% (P<0.01) lower than N group respectively; individual FMS movements of SM show significant difference between two groups, the differences is 7.1% (P<0.05) higher than N group.(3) I group's FMS and Injury incidence negative correlation coefficients(r=-0.311*,P<0.05); no correlation between individual FMS and injury.(4) The best cut off value is 17 ( SEN=0.89, 1-SPE=0.36, OR=14.00, P<0.05). when the FMS score of an athlete is lower than 17, the probability of sports injury increases from 63.98% to 74.90%, and the risk of injury increases. CONCLUSION: Injuries of elite Chinese fencers are mainly concentrated in the lower extremity; The FMS total scores, individual FMS (DS, HS, SM) can predict lower extremity sports injury; 17 points might be the cut off value of injury risk prediction for elite fencers.
ranges) were used to describe the sample. Wilcoxon rank sum tests were used to detect group differences in AV symptom endorsement, and SRT (in SRCs with ≥ 1 AV symptom) between HELM and NoHELM SRCs. Ordinal logistic regression models identified differential odds of greater AV symptom count, and longer SRT (categorized as: ≤14, 15-28, >28 days) between SRCs in HELM and NoHELM sports (adjusting for AV symptom count). All models were parametrized to adjust for covariate (sex, class year, event type, and injury mechanism) effects, and effect estimates with 95% CIs excluding 1.0 were deemed statistically significant. RESULTS: Overall, 1,084 SRCs were analyzed, and most were in HELM (67%). Dizziness was the most prevalent AV symptom endorsed in both HELM (60%) and NoHELM (63%) SRCs. We observed no group differences in AV symptom count or SRT between NoHELM and HELM SRCs. SRCs in HELM (compared to NoHELM) were not associated with odds of greater counts of AV symptoms. SRCs (with ≥ 1 AV symptom) in HELM (compared to NoHELM) were associated with higher odds of longer SRT (OR Adj. = 2.1, 95%CI= 1.2-3.9). CONCLUSIONS: The number of AV symptoms endorsed following a SRC was not influenced by sport type (HELM, NoHELM). Adjusting for AV symptoms endorsed, athletes that sustained SRCs in HELM had higher odds of longer SRT.
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