The association of concussion history and mental health in former collegiate athletes

This dissertation aimed to: (1) estimate the association between recurrent concussion and mental health; and (2) compare athlete-recalled and clinically-documented concussion histories during college. Questionnaires were completed by 797 former collegiate athletes who played collegiate sport between 1987-2012. Athlete-recalled concussions from 130 former collegiate athletes were individually linked to previously collected clinical data that tracked medically-diagnosed concussions at the host institution between 1996 and 2012. In Aim 1, binomial regression estimated adjusted prevalence ratios (PR), with depression, impulsivity, and aggression as outcomes. Controlling for alcohol dependence and family history of depression, the prevalence of currently meeting diagnostic criteria for major depression among former collegiate athletes reporting three of more concussions was 2.6 times that of those reporting no concussions [95% Confidence Interval (CI): 1.1, 6.1]. No association was found for impulsivity. Controlling for alcohol dependence, sex, and relationship status, former collegiate athletes reporting three or more concussions had a higher prevalence of high levels of aggression, compared to those reporting no concussions (PR=1.2; 95% CI: 1.0, 1.5). In Aim 2, intraclass correlation coefficients (ICC) assessed agreement between athlete-recalled and clinically-documented concussion histories. Descriptive analyses assessed reasons for disagreement. Agreement between athlete-recalled and clinically-documented concussion histories was low (ICC: 0.21; 95% CI: 0.05, 0.37), but higher for females (ICC=0.65; 95% CI: 0.44, 0.79) and those playing more recently (2005-2012: ICC=0.39; 95% CI: 0.01, 0.67). Of those sustaining college sports-related concussions (40.8%), 39.6% believed they had sustained concussions that went undiagnosed, and 20.8% admitted non-disclosure of suspected concussions. Common reasons for non-disclosure included: did not think injury was serious enough (90.9%); did not know it was a concussion (72.7%); and did not want to leave the game/practice (72.7%). In summary, former collegiate athletes reporting concussions may be at greater risk for major depression and higher levels of aggression. However, current sources of concussion history data apparently fail to capture large proportions of concussions. Methodological research is needed to improve the quality of concussion history assessment tools. The health and well-being of collegiate athletes should continue to be monitored even after transitioning out of collegiate sports.Doctor of Philosoph

Post-Concussion Experiences of Collegiate Student-Athletes

Sports-related concussions are a major public health concern affecting a significant number of collegiate student-athletes. Medical and public health research has addressed every aspect of concussion management processes including concussion education, medical diagnosis, recovery, and returning to sport and classroom. This research has led to several best-practices for concussion management. Since 2010, the NCAA has mandated that its member institutions maintain concussion management policies and procedures. However, the current recommendations, based primarily on medical research, have been found in quantitative studies of the behaviors and practices of athletic trainers, coaches, and student-athletes to be ineffective. To date, no studies have explored the perceptions and experiences of student-athletes post-concussion. The purpose of this study was to understand student-athletes’ experiences post-concussion and how their experiences compared to concussion management policy. A qualitative research design was utilized to allow for an in-depth understanding of the student-athlete’s perspective on concussion management. Data were collected from interviews with seven current and former NCAA student-athletes from five member institutions representing Division I football, lacrosse, men’s soccer, women’s soccer, Division II football, and Division III football; and from publicly obtained concussion management documents. The data were analyzed using Tesch’s (2013) organizing system and Love\u27s (2003) methods for document analysis. Eight major findings emerged from the data: 1) Symptomology and its effects, 2) Pressure to return, 3) Lack of Knowledge, 4) Inadequate support, 5) No rest, 6) No policy, 7) Double-injury, and 8) Inconsistent alignment between student-athletes’ experiences and their institution’s concussion policies. None of the student-athletes’ experiences aligned with the current best-practices in concussion management. Recommendations for cultural change, NCAA practices, and higher education practices include using warning messaging and PSAs, applying effective preseason education, enforcing implementation of concussion management guidelines, leveraging media partnerships, investing in concussion specialists, and creating a team of support

Cognitive and emotional effects of one season of head impact exposure in high school contact sport athletes

Short-term and long-term neurological damage as a result of sports-related brain trauma is a major concern for athletes today. In the last decade, studies of subconcussive repetitive head impacts (RHI) in contact sports have found associations with functional and structural brain changes, even in the absence of diagnosed concussion. Risk and thresholds for brain dysfunction in the setting of sports-related RHI remain poorly understood. This prospective study enrolled 119 athletes (72 contact, 47 noncontact) of both sexes (79 male, 40 female), to explore the effect of one season of subconcussive RHI on brain function in high school football, boys lacrosse, and boys and girls soccer versus a comparison group of noncontact athletes. This study is the first to assess the effects of one season of RHI exposure on traditional and novel cognitive measures as well as self-reported emotion, sleep and headache in high school athletes. Contact sport athletes wore a commercial accelerometer to investigate if there is a dose-response relationship between RHI exposure and brain function. Paired t-test comparisons of all measures revealed contact sport athletes were not different than noncontact athletes in experiencing negative changes over the course of one season on the assessment battery. Given the number of subjects evaluated and the resultant power to detect change, this study had an 82.5% power to detect a Cohenʼs d of 0.66. Regression analysis of multiple measures of RHI among contact sport athletes did not identify a significant relationship between exposure and changes in cognition, emotion, sleep or headache over one season. Secondary analyses found significant relationships between a greater number of total head impacts at postseason assessment and higher scores on NIH Emotion Battery elements Perceived Stress (p=0.0002) and Perceived Hostility (p=0.0004), but it was unrelated to total years of football exposure. Overall, this study showed that there does not appear to be an association between one season of RHI exposure and short-term changes in cognition or self-reported aspects of emotion, sleep, or headache. Results from this study may help in the design of future investigations that will increase our understanding of the short-term consequences of RHI. Future studies should concentrate on the question of a clinically significant threshold at which RHI above a certain magnitude is more likely to cause brain dysfunction

Predictive modelling of football injuries

The goal of this thesis is to investigate the potential of predictive modelling for football injuries. This work was conducted in close collaboration with Tottenham Hotspurs FC (THFC), the PGA European tour and the participation of Wolverhampton Wanderers (WW). Three investigations were conducted: 1. Predicting the recovery time of football injuries using the UEFA injury recordings: The UEFA recordings is a common standard for recording injuries in professional football. For this investigation, three datasets of UEFA injury recordings were available: one from THFC, one from WW and one that was constructed by merging both. Poisson, negative binomial and ordinal regression were used to model the recovery time after an injury and assess the significance of various injury-related covariates. Then, different machine learning algorithms (support vector machines, Gaussian processes, neural networks, random forests, naïve Bayes and k-nearest neighbours) were used in order to build a predictive model. The performance of the machine learning models is then improved by using feature selection conducted through correlation-based subset feature selection and random forests. 2. Predicting injuries in professional football using exposure records: The relationship between exposure (in training hours and match hours) in professional football athletes and injury incidence was studied. A common problem in football is understanding how the training schedule of an athlete can affect the chance of him getting injured. The task was to predict the number of days a player can train before he gets injured. The dataset consisted of the exposure records of professional footballers in Tottenham Hotspur Football Club from the season 2012-2013. The problem was approached by a Gaussian process model equipped with a dynamic time warping kernel that allowed the calculation of the similarity of exposure records of different lengths. 3. Predicting intrinsic injury incidence using in-training GPS measurements: A significant percentage of football injuries can be attributed to overtraining and fatigue. GPS data collected during training sessions might provide indicators of fatigue, or might be used to detect very intense training sessions which can lead to overtraining. This research used GPS data gathered during training sessions of the first team of THFC, in order to predict whether an injury would take place during a week. The data consisted of 69 variables in total. Two different binary classification approaches were followed and a variety of algorithms were applied (supervised principal component analysis, random forests, naïve Bayes, support vector machines, Gaussian process, neural networks, ridge logistic regression and k-nearest neighbours). Supervised principal component analysis shows the best results, while it also allows the extraction of components that reduce the total number of variables to 3 or 4 components which correlate with injury incidence. The first investigation contributes the following to the field: • It provides models based on the UEFA injury recordings, a standard used by many clubs, which makes it easier to replicate and apply the results. • It investigates which variables seem to be more highly related to the prediction of recovery after an injury. • It provides a comparison of models for predicting the time to return to play after injury. The second investigation contributes the following to the field: • It provides a model that can be used to predict the time when the first injury of the season will take place. • It provides a kernel that can be utilized by a Gaussian process in order to measure the similarity of training and match schedules, even if the time series involved are of different lengths. The third investigation contributes the following to the field: • It provides a model to predict injury on a given week based on GPS data gathered from training sessions. • It provides components, extracted through supervised principal component analysis, that correlate with injury incidence and can be used to summarize the large number of GPS variables in a parsimonious way

The Effects of Previous Concussions on the Physiological Complexity of Motor Output During a Continuous Isometric Visual-Motor Tracking Task

The majority of clinical impairments following a concussion resolve within 7-10 days. However, there is limited clarity as to long-term impact of this injury on neurocognitive function, motor control, and particularly integration of these domains. While repetitive head trauma is associated with numerous neurological disorders, the link is not well described. Visual-motor tracking tasks have been used to identify differences in visual processing, error detection, and fine motor control in aging and numerous pathologies. Examining the complexity of motor output from visual-motor tracking provides insight into multiple cognitive and motor function domains, and into fine motor control used for daily living, work, and sport. The purpose of this dissertation was, therefore, to: (1) use multiple regression to determine the extent to which concussion history and symptoms (loss of consciousness and amnesia) influence visual-motor task performance multiscale complexity, and (2) determine whether task performance complexity can distinguish, through logistic regression and prediction, between individuals with and without a history of concussion. In study 1, individuals with (n = 35) and without (n = 15) a history of concussion performed a visual-motor tracking task. Men and women exhibited linear decreases in task performance complexity, as well as midand high-frequency task performance components, with increasing numbers of concussions. However, men and women exhibited differing patterns, as did those with and without a history of concussion-related loss of consciousness. Finally, trial-to-trial complexity variability increased with increasing numbers of concussions. Findings indicate (1) a cumulative reduction in the way in which previously concussed individuals process and integrate visual information to guide behavior and (2) gender is an important consideration in concussion-related visual-motor outcomes. In Study 2, individuals with (n = 85) and without (n = 42) a history of concussion performed a visualmotor tracking task. Linear and nonlinear measures of task performance were used to build gender-specific logistic classification models using 10-fold cross-validation. When ensuring 80% sensitivity, the best models were 75-80% accurate in predicting a history of concussion. Such discrimination has clinical value in identifying individuals who merit further evaluation and observation over time for conditions related to repetitive head traumas

Concussion history among Icelandic female athletes : mental health, cognition and possible concussion biomarkers

Concussion symptoms are complex. They are non-specific to a concussion, and there is no gold standard for diagnosis and evaluation. For most, symptoms will resolve in days or weeks following a concussion. However, symptoms can become more serious, lasting for months or even years, considerably affecting quality of life. Long-lasting concussion symptoms can include worse mental health and cognitive function, impaired sleep, and ocular and vestibular problems. Sports are a significant risk factor for concussions. Previous concussions, medical history and background, age and gender are also factors influencing the prevalence and the sequela of concussion and progression of symptoms. Despite being underrepresented in the concussion literature, many studies have found that women are more at risk of sustaining a concussion and have more severe symptoms. All of the participants in this study were Icelandic female athletes, retired and still active. All had been playing at the highest level in their sport in Iceland. The aims of this Thesis were to 1) examine the usefulness of self-report of concussion history and test if different methods of obtaining self-report would affect the report given and the relationship with an outcome variable; 2) examine concussion history and symptoms among retired and still active female athletes and the relationship with mental health and cognitive abilities; 3) validate self-reported concussion history and symptoms by assessing phycological responses and physical markers in a virtual reality environment. Self-reported history varied according to the method used to elicit concussion history. This change indicates a lack of concussion knowledge and that detailed questioning might be preferable when asking for a self-report of concussion history. This change and how groups were formed depending on concussion count affected the relationship with current symptoms. History of concussion was connected to poorer impulse control, more current post-concussion symptoms and more problems with sleep, as well as more anxiety and depression symptoms. Retired athletes with a concussion history tended to have a worse outcome. When evaluating concussion symptoms and responses in a virtual reality environment, biological signals showed discriminative powers when comparing those with and without a concussion history. This supports their use as possibleiv biomarkers for concussion. The Random forest algorithm predicted concussion history with over 90% accuracy. Overall, the findings support the use of self-report while assessing concussion history and symptoms among female athletes with the appropriate framework. However, the limitations of self-report and how they can affect results are also recognised. In addition, results suggest that concussion history is connected to worse mental health and poorer impulse control. The findings also highlight the use of a multimodal approach to concussion assessment and support the use of several biological measures as possible biomarkers for concussion. Results also underline the importance of including technology from different fields in concussion assessmentEinkenni sem hafa verið kennd við heilahristing eru flókin, þau eru ekki sértæk fyrir heilahristing og það er engin ein algild leið til þess að greina og meta heilahristing. Flestir jafna sig á einkennum á nokkrum dögum eða vikum. Hins vegar, geta einkenni orðið mjög slæm, varað í nokkra mánuði eða ár og haft mikil áhrif á lífsgæði. Langtímaafleiðingar eftir heilahristing geta verið verri líðan og hugræn geta, verri svefn og vandi með augnhreyfingar og jafnvægi. Íþróttir eru einn þeirra áhættuþátta sem hefur mikið vægi þegar kemur að heilahristing, þó ekki fylgi öllum íþróttum jafn mikil áhætta. Fyrri heilahristingssaga, heilsa og bakgrunnur hafa jafnframt áhrif, en einnig aldur og kyn. Allt eru þetta þættir sem hafa áhrif á algengi og afleiðingar heilahristings. Þrátt fyrir að konur eru ekki eins mikið rannsakaðar og karlar gefa margar rannsóknir til kynna að konur séu í meiri hættu á því að fá heilahristing og glími við alvarlegri einkenni. Allir þátttakendur í þessari rannsókn voru íslenskar íþróttakonur sem annað hvort voru enn að æfa og keppa í efstu deildum í sinni íþrótt, eða voru hættar. Markmið þessa verkefnis voru að 1) skoða gagnsemi þess að fá þátttakendur sjálfa til að greina frá heilahristingssögu sinni ásamt því að meta hvort mismunandi aðferðir við að fá fram heilahristingssögu hafi áhrif á það sem er uppgefið og tengsl við fylgibreytur; 2) skoða heilahristingssögu og einkenni meðal íþróttakvenna, sem eru hættar og þeirra sem eru enn virkar, og meta samband við líðan og hugræna getu; 3) staðfesta mat á eigin heilahristingssögu og einkennum með því að skoða svörun og líffræðileg merki sem safnað var í sýndarveruleika. Mat á heilahristingssögu breyttist á milli aðstæðna og var háð því hvaða upplýsingar voru gefnar og hvernig þáttakandi var beðinn um að rifja upp. Þessi breyting bendir til þekkingarleysis á heilahristing og að nákvæmari spurningar um heilahristingssögu séu mikilvægur hluti af gagnasöfnun þegar nota á sjálfsmat. Þessi breyting og það hvernig hópar voru myndaðir út frá fjölda heilahristinga hafði áhrif þegar tengslin við fylgibreytu voru metin. Tengsl voru á milli heilahristingssögu og stýrifærni, núverandi heilahristingseinkenna, meiri svefnvanda, og kvíða-og þunglyndiseinkenna. Þeim íþróttakonum sem áttu sögu um heilahristing og voru hættar keppni gekk í mörgum vi tilvikum verr en öðrum hópum. Merki frá nemum sem mældu líffræðilega svörun við áreiti í sýndarveruleika gáfu ennfremur til kynna að hægt var að greina á milli þeirra sem greindu frá sögu um heilahristing og þeirra sem ekki greindu frá heilahristingssögu. Niðurstöður stiðja því að hægt sé nota þessi merki sem viðmið við mat á heilahristingseinkennum. Með notkun Random forest reikniritsins var hægt að spá fyrir um heilahristingssögu með yfir 90% nákvæmni. Þegar á heildina er litið gefa niðurstöður þessa verkefnis til kynna að hægt sé að styðjast við sjálfsmat á einkennum og heilahristingssögu. Þó er mikilvægt að vera meðvitaður um þær takmarkanir sem kunna að fylgja þessari aðferð og áhrifum á niðurstöður. Að auki benda niðurstöður til þess að tengsl séu á milli heilahristingssögu og verri andlegrar heilsu og að hluta til stýrifærni. Niðurstöður undirstrika einnig mikilvægi þessa að notast við fleiri en eina mælingu við mat á einkennum og mikilvægi þess að nýta aðferðir sem koma úr ólíkum áttum við mat á heilahristing. Með því opnast fleiri möguleikar á mögulegum greiningarviðmiðum fyrir heilahristin

Wearable Technology and Analytics as a Complementary Toolkit to Optimize Workload and to Reduce Injury Burden

Wearable sensors enable the real-time and non-invasive monitoring of biomechanical, physiological, or biochemical parameters pertinent to the performance of athletes. Sports medicine researchers compile datasets involving a multitude of parameters that can often be time consuming to analyze in order to create value in an expeditious and accurate manner. Machine learning and artificial intelligence models may aid in the clinical decision-making process for sports scientists, team physicians, and athletic trainers in translating the data acquired from wearable sensors to accurately and efficiently make decisions regarding the health, safety, and performance of athletes. This narrative review discusses the application of commercial sensors utilized by sports teams today and the emergence of descriptive analytics to monitor the internal and external workload, hydration status, sleep, cardiovascular health, and return-to-sport status of athletes. This review is written for those who are interested in the application of wearable sensor data and data science to enhance performance and reduce injury burden in athletes of all ages

Cognitive Functioning in UK-based Football (Soccer) Players, with emphasis on Social Cognition

Introduction: An area of growing interest, the neuropsychological impact of sporting traumatic brain injuries has received considerable attention. Research has centred on boxing and the National Football League, with associations between sporting concussions and cognitive functioning widely acknowledged. The cumulative effect of mild sporting head injuries remains largely neglected. As the only sport incorporating head impacts (heading) as an integral part of the game, the world’s most popular sport, football (soccer), has received limited research. To date, social cognition remains entirely neglected in the footballing literature, despite recent media attention regarding the potential long-term neuropsychological impacts. Aims: To explore associations between football-related behaviours, cognitive functioning, and the novel addition of social cognition, in a UK-based sample. Method: A quantitative cross-sectional design, enabled twenty-five male footballers to complete a neuropsychological assessment battery of premorbid functioning, cognitive functioning, and social cognition. Results: Weaknesses relative to the norm were revealed for cognitive measures of visual attention, verbal functioning, and verbal memory, and social cognitive measures of theory of mind (ToM) and affective empathy. Results emerged in a highly educated sample, with above average optimal functioning. Associations between football-related behaviours, verbal memory, visual attention, and all measures of social cognition were revealed. Associations between quantified and cumulative career football-related concussions, verbal memory, ToM, and emotion recognition are highlighted. Discussion: Findings indicate precautionary adjustments in assessment, monitoring, and management processes where football head-impacts are apparent. Deficits in verbal memory and social cognition should be held in mind, with future confirmatory research and preventative care recommended