Wellness Survey Responses and Smartphone App Response Efficiency: Associations With Remote History of Sport-Related Concussion

Concussion history and virtual reality metrics predict core or lower extremity injury occurrence among high school athletes

Introduction

A history of concussion is recognized as a risk factor for musculoskeletal injury, which is likely associated with physiological effects that warrant better understanding. This study aimed to assess the potential of measurements obtained from an immersive virtual reality (VR) test to identify a subtle perceptual-motor impairment that may be prospectively associated with the occurrence of a core or lower extremity sprain or strain.

Methods

A cohort of 68 high school athletes (41 female soccer players and 27 male football players) provided survey responses and completed an immersive VR test several days prior to the initiation of preseason practice sessions. Measurements of eye, neck, arm, and whole-body displacements were obtained during 40 successive lunging/reaching responses to visual stimuli moving horizontally across the VR headset display. Injury occurrences were electronically documented from the initial preseason practice session to the final game of the season.

Results

A statistically significant and intrinsically credible two-factor prediction model for core or lower extremity injury occurrence included an interaction between female sex and a self-reported history of two or more concussions, along with slow response time (RT) for arm reach (OR = 4.67; 95% CI, 1.51-14.43). Follow-up analyses identified sex-specific cut points for arm reach RT associated with elevated injury risk, which were ≥1.385 s for females and ≥1.257 s for males.

Discussion

High school female soccer players who have sustained more than one concussion appear to be highly vulnerable to core or lower extremity sprain or strain, with the risk of injury compounded by a slow arm reach RT. Male football players as a group demonstrated significantly faster arm reach RT than that of female soccer players, but slow perceptual-motor RT for arm reach was also identified as a potentially important injury risk factor for male players. Immersive VR appears to provide precise measurements of behavioral performance characteristics that depend on brain processing efficiency. Given that the speed, accuracy, and consistency of perceptual-motor responses may be modifiable, future research should explore the potential benefits of VR training for reducing the risk of sport-related injuries.

Subtle impairments of perceptual-motor function and well-being are detectable among military cadets and college athletes with self-reported history of concussion

Introduction

A lack of obvious long-term effects of concussion on standard clinical measures of behavioral performance capabilities does not preclude the existence of subtle neural processing impairments that appear to be linked to elevated risk for subsequent concussion occurrence, and which may be associated with greater susceptibility to progressive neurodegenerative processes. The purpose of this observational cohort study was to assess virtual reality motor response variability and survey responses as possible indicators of suboptimal brain function among military cadets and college athletes with self-reported history of concussion (HxC).

Methods

The cohort comprised 75 college students (20.7 ± 2.1 years): 39 Reserve Officer Training Corp (ROTC) military cadets (10 female), 16 football players, and 20 wrestlers; HxC self-reported by 20 (29.2 ± 27.1 months prior, range: 3-96). A virtual reality (VR) test involving 40 lunging/reaching responses to horizontally moving dots (filled/congruent: same direction; open/incongruent: opposite direction) was administered, along with the Sport Fitness and Wellness Index (SFWI) survey. VR Dispersion (standard deviation of 12 T-scores for neck, upper extremity, and lower extremity responses to congruent vs. incongruent stimuli originating from central vs. peripheral locations) and SFWI response patterns were the primary outcomes of interest.

Results

Logistic regression modeling of VR Dispersion (range: 1.5-21.8), SFWI (range: 44-100), and an interaction between them provided 81% HxC classification accuracy (Model χ ²[2] = 26.03, p < .001; Hosmer & Lemeshow χ ²[8] = 1.86, p = .967; Nagelkerke R ²= .427; Area Under Curve = .841, 95% CI: .734, .948). Binary modeling that included VR Dispersion ≥3.2 and SFWI ≤86 demonstrated 75% sensitivity and 86% specificity with both factors positive (Odds Ratio = 17.6, 95% CI: 5.0, 62.1).

Discussion/Conclusion

Detection of subtle indicators of altered brain processes that might otherwise remain unrecognized is clearly important for both short-term and long-term clinical management of concussion. Inconsistency among neck, upper extremity, and lower extremity responses to different types of moving visual stimuli, along with survey responses suggesting suboptimal well-being, merit further investigation as possible clinical indicators of persisting effects of concussion that might prove to be modifiable.

Smartphones dependency risk analysis using machine-learning predictive models

Recent technological advances have changed how people interact, run businesses, learn, and use their free time. The advantages and facilities provided by electronic devices have played a major role. On the other hand, extensive use of such technology also has adverse effects on several aspects of human life (e.g., the development of societal sedentary lifestyles and new addictions). Smartphone dependency is new addiction that primarily affects the young population. The consequences may negatively impact mental and physical health (e.g., lack of attention or local pain). Health professionals rely on self-reported subjective information to assess the dependency level, requiring specialists' opinions to diagnose such a dependency. This study proposes a data-driven prediction model for smartphone dependency based on machine learning techniques using an analytical retrospective case-control approach. Different classification methods were applied, including classical and modern machine learning models. Students from a private university in Cali-Colombia (n = 1228) were tested for (i) smartphone dependency, (ii) musculoskeletal symptoms, and (iii) the Risk Factors Questionnaire. Random forest, logistic regression, and support vector machine-based classifiers exhibited the highest prediction accuracy, 76-77%, for smartphone dependency, estimated through the stratified-k-fold cross-validation technique. Results showed that self-reported information provides insight into predicting smartphone dependency correctly. Such an approach opens doors for future research aiming to include objective measures to increase accuracy and help to reduce the negative consequences of this new addiction form.

Changes in dual-task cognitive performance elicited by physical exertion vary with motor task

Background

Integrated movement and cognitive load paradigms are used to expose impairments associated with concussion and musculoskeletal injury. There is currently little information on the discriminatory nature of dual-task complexity and the relative influence of physical exertion on cognitive outcomes.

Purpose

Assess cognitive performance while under motor conditions of increasing complexity before and after a standardized exercise protocol.

Methods

34 participants were recruited (17 male and 17 female; 24 ± 1.4 yrs). A modified Eriksen flanker test was used to assess cognitive performance under four conditions (seated, single-leg stance, walking, and lateral stepping) before and after a 20-min moderate-to vigorous intensity treadmill protocol. The flanker test consisted of 20 sets of 5-arrow configurations, appearing in random order. To complete the response to cognitive stimulus, participants held a smartphone horizontally and were instructed to respond as quickly and as accurately as possible by tilting the device in the direction corresponding to the orientation of the middle arrow. The metrics used for analysis included average reaction time (ms), inverse efficiency index (average reaction time penalized for incorrect responses), and conflict effect (the average time cost of responding to an incongruent repetition vs. a congruent repetition). Mixed effects (condition by time) RMANOVAs were conducted to examine the effects of motor task complexity and physical exertion on cognitive performance.

Results

There was a condition by time interaction for inverse efficiency index (p < 0.001), in which participants displayed higher cognitive efficiency for the pre-activity lateral stepping condition compared to the other three conditions (Cohen's d = 1.3–1.6). For reaction time and conflict effect, there were main effects for condition (p = 0.004 and 0.006, respectively), in which performance during lateral stepping was improved in relation to the seated condition (reaction time Cohen's d = 0.68; conflict effect Cohen's d = 0.64).

Conclusion

Participants tended to display better dual-task cognitive performance under more stimulating or complex motor tasks before physical exertion, likely associated with the inverted-U arousal-performance relationship. When using dual-task assessments, clinicians should be mindful of the accompanying motor task and baseline exertion levels and their potential to disrupt or optimize cognitive performance.

Sex Moderates the Relationship between Perceptual-Motor Function and Single-Leg Squatting Mechanics

To examine the isolated and combined effects of sex and perceptual-motor function on single-leg squatting mechanics in males and females. We employed a cross-sectional design in a research laboratory. Fifty-eight females (22.2 ± 3.5 yrs, 1.60 ± .07 m, 64.1 ± 13.0 kg) and 35 males (23.5 ± 5.0 yrs, 1.80 ± .06m, 84.7 ± 15.3 kg) free from time-loss injury in the six months prior, vertigo, and vestibular conditions participated in this study. Independent variables were sex, perceptual-motor metrics (reaction time, efficiency index, conflict discrepancy), and interaction effects. Dependent variables were peak frontal plane angles of knee projection, ipsilateral trunk flexion, and contralateral pelvic drop during single-leg squatting. After accounting for the sex-specific variance and perceptual-motor function effects on frontal plane squatting kinematics, female sex amplified the associations of: higher reaction time, lower efficiency index, and higher conflict discrepancy with greater right ipsilateral peak trunk lean (R² = .13; p = .05); higher reaction time, lower efficiency index, and higher conflict discrepancy with decreased right contralateral pelvic drop (R² = .22; p < .001); higher reaction time and lower conflict discrepancy with greater right frontal plane knee projection angle (R² = .12; p = .03); and higher reaction time with greater left frontal plane knee projection angle (R² = .22; p < .001). Female sex amplified the relationship between perceptual-motor function and two-dimensional frontal plane squatting kinematics. Future work should determine the extent to which perceptual-motor improvements translate to safer movement strategies.

A Neuro-Integrative Assessment of Perceptual-Motor Performance and Wellness in ROTC Cadets

Resting heart rate variability (HRV) may be a useful index of both brain-based executive function and general health. Our purpose in this study was to quantify relationships among HRV, perceptual-motor performance metrics, and wellness survey responses. A cohort of 32 male Reserve Officer Training Corp (ROTC) cadets completed a dual-task upper extremity reaction time (UERT) test, two tests of whole-body reactive agility, and a 10-item wellness survey that produced a 0-100 Overall Wellness Index (OWI). We averaged participants' resting HRV measurements twice per week over 10 weeks to derive an intra-individual grand mean (HRV-IIGM) and over a series of days we calculated an intra-individual coefficient of variation (HRV-IICV). We used median values for the two HRV metrics (HRV-IIGM and HRV-IICV) to separate the cadets into equal-sized high and low HRV groups to form the dependent variable for logistic regression analyses. We found a significant inverse relationship between HRV-IIGM and HRV-IICV (r = -0.723, p < .001). Differences in UERT in the left versus right visual hemifields (L-R Diff) and OWI scores were strongly related to both HRV-IIGM ≤ 4.49 and HRV-IICV ≥ 6.95%. Logistic regression models that included L-R Diff and OWI showed 71% classification accuracy for HRV-IIGM (Model χ2 [2] = 12.47, p = .002, Nagelkerke R² = 0.430) and 81% classification accuracy for HRV-IICV (Model χ2 [2] = 14.88, p = .001, Nagelkerke R² = 0.496). These findings suggest that resting HRV, perceptual-motor efficiency, and overall wellness are highly interrelated, supporting a multi-factor biopsychosocial assessment to guide the design and implementation of interventions to maximize operational effectiveness for ROTC cadets and other military personnel.

Whole-Body Reactive Agility Metrics to Identify Football Players With a Core and Lower Extremity Injury Risk

Clinical prediction models are useful in addressing several orthopedic conditions with various cohorts. American football provides a good population for attempting to predict injuries due to their relatively high injury rate. Physical performance can be assessed a variety of ways using an assortment of different tests to assess a diverse set of metrics, which may include reaction time, speed, acceleration, and deceleration. Asymmetry, the difference between right and left performance has been identified as a possible risk factor for injury. The purpose of this study was to determine the whole-body reactive agility metrics that would identify Division I football players who were at elevated risk for core, and lower extremity injuries (CLEI). This cohort study utilized 177 Division I football players with a total of 57 CLEI suffered who were baseline tested prior to the season. Single-task and dual-task whole-body reactive agility movements in lateral and diagonal direction reacting to virtual reality targets were analyzed separately. Receiver operator characteristic (ROC) analyses narrowed the 34 original predictor variables to five variables. Logistic regression analysis determined the three strongest predictors of CLEI for this cohort to be: lateral agility acceleration asymmetry, lateral flanker deceleration asymmetry, and diagonal agility reaction time average. Univariable analysis found odds ratios to range from 1.98 to 2.75 for these predictors of CLEI. ROC analysis had an area under the curve of 0.702 for any combination of two or more risk factors produced an odds ratio of 5.5 for risk of CLEI. These results suggest an asymmetry of 8-15% on two of the identified metrics or a slowed reaction time of ≥0.787 s places someone at increased risk of injury. Sixty-three percent (36/57) of the players who sustained an injury had ≥2 positive predictors In spite of the recognized limitation, these finding support the belief that whole-body reactive agility performance can identify Division I football players who are at elevated risk for CLEI.

Perceptual-Motor Efficiency and Concussion History Are Prospectively Associated With Injury Occurrences Among High School and Collegiate American Football Players

Background:

After a sport-related concussion (SRC), the risk for lower extremity injury is approximately 2 times greater, and the risk for another SRC may be as much as 3 to 5 times greater.

Purpose:

To assess the predictive validity of screening methods for identification of individual athletes who possess an elevated risk of SRC.

Study Design:

Case-control study; Level of evidence, 3.

Methods:

Metrics derived from a smartphone flanker test software application and self-ratings of both musculoskeletal function and overall wellness were acquired from American high school and college football players before study participation. Occurrences of core or lower extremity injury (CLEI) and SRC were documented for all practice sessions and games for 1 season. Receiver operating characteristic and logistic regression analyses were used to identify variables that provided the greatest predictive accuracy for CLEI or SRC occurrence.

Results:

Overall, there were 87 high school and 74 American college football players included in this study. At least 1 CLEI was sustained by 45% (39/87) of high school players and 55% (41/74) of college players. Predictors of CLEI included the flanker test conflict effect ≥69 milliseconds (odds ratio [OR], 2.12; 90% CI, 1.24-3.62) and a self-reported lifetime history of SRC (OR, 1.70; 90% CI, 0.90-3.23). Of players with neither risk factor, only 38% (29/77) sustained CLEI compared with 61% (51/84) of players with 1 or both of the risk factors (OR, 2.56; 90% CI, 1.50-4.36). SRC was sustained by 7 high school players and 3 college players. Predictors of SRC included the Overall Wellness Index score ≤78 (OR, 9.83; 90% CI, 3.17-30.50), number of postconcussion symptoms ≥4 (OR, 8.35; 90% CI, 2.71-25.72), the Sport Fitness Index score ≤78 (OR, 5.16; 90% CI, 1.70-15.65), history of SRC (OR, 4.03; 90% CI, 1.35-12.03), and the flanker test inverse efficiency ratio ≥1.7 (OR, 3.19; 90% CI, 1.08-9.47).

Conclusion:

Survey responses and smartphone flanker test metrics predicted greater injury incidence among individual football players classified as high-risk compared with that for players with a low-risk profile.

A Novel Approach to Assessment of Perceptual-Motor Efficiency and Training-Induced Improvement in the Performance Capabilities of Elite Athletes

Standard clinical assessments of mild traumatic brain injury are inadequate to detect subtle abnormalities that can be revealed by sophisticated diagnostic technology. An association has been observed between sport-related concussion (SRC) and subsequent musculoskeletal injury, but the underlying neurophysiological mechanism is not currently understood. A cohort of 16 elite athletes (10 male, 6 female), which included nine individuals who reported a history of SRC (5 male, 4 female) that occurred between 4 months and 8 years earlier, volunteered to participate in a 12-session program for assessment and training of perceptual-motor efficiency. Performance metrics derived from single- and dual-task whole-body lateral and diagonal reactive movements to virtual reality targets in left and right directions were analyzed separately and combined in various ways to create composite representations of global function. Intra-individual variability across performance domains demonstrated very good SRC history classification accuracy for the earliest 3-session phase of the program (Reaction Time Dispersion AUC = 0.841; Deceleration Dispersion AUC = 0.810; Reaction Time Discrepancy AUC = 0.825, Deceleration Discrepancy AUC = 0.794). Good earliest phase discrimination was also found for Composite Asymmetry between left and right movement directions (AUC = 0.778) and Excursion Average distance beyond the minimal body displacement necessary for virtual target deactivation (AUC = 0.730). Sensitivity derived from Youden's Index for the 6 global factors ranged from 67 to 89% and an identical specificity value of 86% for all of them. Median values demonstrated substantial improvement from the first 3-session phase to the last 3-session phase for Composite Asymmetry and Excursion Average. The results suggest that a Composite Asymmetry value ≥ 0.15 and an Excursion Average value ≥ 7 m, provide reasonable qualitative approximations for clinical identification of suboptimal perceptual-motor performance. Despite acknowledged study limitations, the findings support a hypothesized relationship between whole-body reactive agility performance and functional connectivity among brain networks subserving sensory perception, cognitive decision-making, and motor execution. A complex systems approach appears to perform better than traditional data analysis methods for detection of subtle perceptual-motor impairment, which has the potential to advance both clinical management of SRC and training for performance enhancement.