Disclaimer: This dissertation has been written by a student and is not an example of our professional work, which you can see examples of here.

Any opinions, findings, conclusions, or recommendations expressed in this dissertation are those of the authors and do not necessarily reflect the views of UKDiss.com.

Effect of Prior Head Impacts on Neurocognitive Performance in Youth Athletes

Info: 10129 words (41 pages) Dissertation
Published: 11th Nov 2021

Reference this

Tagged: MedicalSportsNeurology


Hypothesis: Youth athletes with an increased frequency of previous concussions and subconcussive impacts will display poorer neurocognitive performance in tasks related to memory (compared to those without a history of concussion and fewer subconcussive impacts).

Methods: A literature search was conducted using PubMed and Google Scholar. Using certain exclusion criteria, several cross-sectional, retrospective cohort and case-control studies deemed to have an evidence level of 2 or 3 were chosen and evaluated. Neurocognition measured by computerized testing was compared across youth athletes with and without a history of concussion.

Results: The majority of the studies reviewed suggested that there is no effect of prior concussion on memory-related neurocognitive performance. However, two studies found subtle differences in the Verbal Memory composite score of the ImPACT battery in athletes with previous concussions. One study found that athletes with repetitive subconcussive impacts displayed poorer ImPACT composite scores for Visual Motor Speed and Reaction Time, both of which comprise tasks involving working memory. Other studies demonstrated athletes with previous concussions reporting more severe post-concussion symptoms.

Conclusions: These findings, although inconclusive, are consistent with previous studies that show subtle but not definitive evidence that multiple concussions can play a role in neurocognitive deficits in youth athletes. Potential future studies should utilize multiple modalities of neurocognitive testing to account for different cognitive domains. This would include more multiply concussed athletes who are often underrepresented, and define the severity and temporality of prior concussions. Further longitudinal research is required to determine the extent to which multiple brain traumas affect post-concussion symptoms.

Keywords: traumatic brain injury, brain concussion, multiple concussions, athletic injuries, adolescent, child, neurocognition, cognitive function, attention, memory

Ultramini Abstract: This paper determined the effect of prior subconcussive and concussive impacts on neurocognitive performance in youth athletes by reviewing current literature. It was found that most assessments via ImPACT and ANAM showed no difference in performance, while some demonstrated an association between increased frequency of impacts and poorer cognitive performance involving memory.


Traumatic brain injury (TBI) is defined by the Centers for Disease Control and Prevention (CDC) as “a disruption in the normal function of the brain that can be caused by a bump, blow, or jolt to the head, or penetrating head injury” (CDC, 2017). Sports-related TBI is increasingly becoming an important public health concern and has been described as an epidemic by the CDC. The exact incidence is unknown and quite often underreported, but it has recently been estimated that 1.6 million to 3.8 million sports-related TBIs occur in the United States annually (Daneshvar, Nowinski, McKee, & Cantu, 2011; Yue et al., 2016; Langlois, Rutland-Brown, & Wald, 2006), leading to over 500,000 emergency department (ED) visits and more than 60,000 hospitalizations (Yue et al., 2016). While the majority of the focus in the media has been on collegiate or professional athletes, the pediatric population contributes the most participants to contact and collision sports. Over 44 million youth participate in sports annually, who now begin at earlier ages and play multiple sports throughout the year. This increases the potential risk for TBIs, concussions, a type of mild TBI, and subconcussive injury, a term used to describe neural dysfunction after sport exposure in the absence of symptoms (Giza et al., 2013). About 60-80% of sports-related TBI ED visits are by pediatric patients, primarily adolescents (Kannan, Ramaiah, & Vavilala, 2014), and it is estimated that high school sports alone are responsible for at least 250,000 concussions per year (Kimbler, Murphy, & Dhandapani, 2011).

Most youth athletic activities involve some risk for concussion, the highest risk sports being those that engage in interpersonal contact and collisions such as rugby, hockey and American football (Pfister, T., Pfister, K., Hagel, Ghali, & Ronksley, 2016). There is substantial concern surrounding the short and long-term effects of concussions, particularly in children who suffer repetitive and subconcussive injuries. Some experimental models and clinical studies have suggested that multiple injuries may have cumulative and enduring impacts (Mannix et al., 2013; Meehan, Zhang, Mannix, & Whalen, 2012; Guskiewicz et al., 2003; Prins & Hovda, 2003). However, many of these studies pertain to the effects in collegiate and professional athletes, who likely sustain a higher number and severity of injuries than high school and younger athletes. It is inappropriate and insufficient to apply findings from adults to children due to the difference in injury mechanisms, and also the differences in age that determine biomechanical properties, intracranial water content, intracranial blood volume, and overall myelination within the CNS (Giza, Mink, & Madikians, 2007; Bauer, Fritz, & Harald, 2004; Gefen, A., Gefen, N., Zhu, Raghupathi, & Margulies, 2003). Therefore, there is a need for more studies focused on pediatric sports-related TBI.

The neurocognitive effects after suffering a sports-related concussion have been well studied in adults, but again there is a lack of studies documenting these effects in children and adolescents. An additional problem is the lack of standardized measures of specific cognitive domains. Approximately 40% of US high schools with athletic trainers use a computerized test battery to assess neurocognitive function after concussions in pediatric athletes (Meehan, d’Hemecourt, Pollins, Taylor, & Comstock, 2012). Of those using computerized testing, the majority used the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT Inc., Pittsburgh, PA) battery, although the Automated Neuropsychological Assessment Metrics (ANAM developed by the US Department of Defense), CogSport (CogState Ltd, Melbourne, Australia) and HeadMinder (ImPACT Applications, Inc., Axon Sports, LLC) tests are also used (Echemendia et al., 2013).

The ImPACT battery is a web-based computer-administered neurocognitive test developed to assess sport-related concussion in youth, collegiate and professional athletes. It includes six tests/modules that yield five composite/domain scores for visual memory, verbal memory, visual motor processing speed, reaction time, and impulse control, as well as a total symptom score based on 22 common post-concussion symptoms (ex. headache, dizziness) rated from 0 (none) to 6 (severe) on the Post-Concussion Scale (PCS) (ImPACT Applications, Inc., 2017). Details regarding the specific modules and composite scores are provided in the Appendix in Tables 1 and 2, and the Post-Concussion Scale is shown in Table 3.

The ANAM test is a collection of computerized test batteries designed for serial testing of cognitive functions including speed and accuracy of attention, memory, and thinking abilities. It includes 31 test modules testing Simple Reaction Time, Code Substitution, Code-Substitution Delayed, Continuous Performance Test, Mathematical Processing, Matching to Sample, Spatial Processing, Sternberg Memory Procedure, and Procedural Reaction Time (Cernich, Reeves, Sun, & Bleiberg, 2007).

There is also a paucity of research on the effects of sustaining repetitive subconcussive injuries or previous concussions on neurocognitive function in children and adolescents, resulting in conflicting results from the literature that does exist. Multiple concussions have been associated with risk of future concussions, and prolonged symptoms and recovery time in adolescents (Eisenberg, Andrea, Meehan, & Mannix, 2013; Terwilliger, Pratson, Vaughan, & Gioia, 2016; Miller et al., 2016). Re-injury to the brain before full recovery has occurred has been hypothesized to increase impairment and prolong neurometabolic recovery, as shown in animal models (Prins, Hles, Reger, Giza, & Hovda, 2010) and in a small sample of three adult male athletes (Vagnozzi et al., 2008). High school athletes with a history of two or more concussions have shown higher ratings of cognitive, physical and sleep symptoms than athletes with a history of one or no previous concussions (Schatz, Moser, Covassin, & Karpf 2011). Moser, Schatz, & Jordan (2005) found that high school athletes with recent concussions performed significantly worse on measures of attention and concentration than youth athletes with no concussion, especially those with a history of two or more concussions. However, it is unclear if a consistent quantifiable negative impact on neurocognition is seen with a history of concussion, particularly in the pediatric population.

The purpose of this review was to determine whether a history of sports-related TBI has an effect on neurocognitive performance in children and adolescents. The hypothesis was that youth athletes with previous concussions or subconcussive injuries would display poorer neurocognitive performance on tasks relating to memory compared to those without previous injury.


All of the referenced literature included in this review was identified using two databases, PubMed and Google Scholar. Medline medical subject headings (MeSH) and search terms included combinations of “traumatic brain injury/brain concussion”, “multiple concussions” “child/pediatric/adolescent”, “neurocognition”, “cognitive function”, “attention” and “memory”. Studies were included if they were original research on the neurocognitive effects of sports-related TBI or concussion in children published in English within the last five years. Studies were restricted to only sports-related TBIs rather than including more general studies of TBIs, as the latter involve various mechanisms and injuries. Due to the focus on the pediatric population in sports, studies only included research on children ages 5 to 22 years and were excluded if they included mixed age cohorts and did not report child data separately from adult data. Studies that did not involve testing neurocognitive performance relating to memory were excluded. Publications that compared computerized testing of neurocognitive performance of previously concussed with not previously concussed children were included. Review articles, case reports, and meta-analyses were excluded, as well as studies containing less than 15 subjects.


Six of the eight studies chosen were cohort studies, three of which were cross-sectional, three of which were retrospective in design. The other two studies were matched case-control studies. Seven of the studies used ImPACT to assess neurocognitive performance, six of which compared preseason baseline scores of previously concussed and non-concussed groups, while the last examined the subconcussive effects of high and low contact sports. The remaining study used different compared pre- and post-season neurocognitive function with ANAM.

In assessing the validity and reliability of ImPACT in a sample of symptomatic concussed high school and collegiate athletes, a study by Schatz and Sandel (2013) reported the online version of ImPACT showed 91% sensitivity and 69% specificity. Within that same sample, the measure possessed 95% sensitivity and 97% specificity for athletes suspected of denying their symptoms (Schatz & Sandel, 2013).

Mannix et al. (2014) retrospectively evaluated the association of prior concussion on baseline computerized neurocognitive testing with ImPACT. The study sample consisted of 6005 male and female high school athletes from Maine, with a mean age of 16. Subjects who reported a concussion within 26 weeks of testing, history of epilepsy, or history of brain surgery were excluded. The athletes completed baseline preseason testing with ImPACT and were divided into groups based on the number of previously sustained concussions. The sports represented included football, soccer, basketball, ice hockey, lacrosse, track and field, wrestling, baseball, field hockey, cheerleading, volleyball, swimming and softball. 85.3% of the athletes had never sustained a concussion, 10% reported a history of 1 concussion, 2.9% sustained 2 concussions, 1.1% reported 3 prior concussions, and 0.6% sustained 4 or more concussions. Simple linear regression showed that increasing frequency of previous concussions was associated with decreased baseline composite scores in Verbal memory (p = 0.039), increased scores on Impulse control (p = 0.002), and increased total scores on the PCS (p < 0.001).  However, with multivariate modeling accounting for predictors such as age, gender, history of attention-deficit/hyperactivity disorder (ADHD) or learning difficulties, history of headache or migraine treatment, and history of psychiatric condition, only the relationship between Impulse Control and number of prior concussions remained. Therefore, the number of previous concussions is not a strong predictor of ImPACT scores.
The paper entitled “Effects of two concussions on the neuropsychological functioning and symptom reporting of high school athletes” by Tsushima, Geling, Arnold, & Oshiro (2016) used a retrospective archival search to select 483 high school athletes aged 14-18 who were administered ImPACT during preseason baseline testing. Excluded from the study were participants whose primary language was not English, those with a history of learning disability or special education, those who were tested less than seven days after a concussion, and those with three or more prior concussions (Tsushima et al., 2014). Athletes were divided into three groups based on number of self-reported previous concussions: no concussion (84.7%), 1 concussion (12%) and 2 concussions (3.3%). The sports represented included football, soccer, wrestling, basketball, baseball, judo, cheerleading, volleyball, track, softball, field hockey, boxing and paddling. There were no significant differences in ImPACT composite scores (p > 0.25) or the Total Symptom score (p = 0.195) between the three groups, even when adjusted for age. It was found that athletes with a history of two concussions were on average older compared to those without a history of only one previous concussion.

Brooks et al. (2017) conducted a cross-sectional cohort study to determine whether or not measureable differences in cognitive functioning or symptom reporting exist in high school football players with a history of multiple concussions. A total of 5232 male adolescent football players age 14 to 18 from Maine were assessed using the ImPACT battery and symptom ratings were obtained from the PCS. Athletes were excluded if they had a concussion within 6 months before baseline testing, history of meningitis, epilepsy or brain surgery, and testing completed in a language other than English. Based on the number of self-reported injury history, the athletes were stratified into 0 (80%), 1 (14%), 2 (4.1%), 3 (1.3%), or ≥4 (0.6%) prior concussions. There were no significant differences in ImPACT performance across the 5 groups when examining the independent contribution of concussion history (p = 0.396).  However, there was an association between greater symptom scores and a higher number of prior concussions across all of the symptom score subdomains: cognitive-sensory, sleep-arousal, vestibular-somatic, and affective (p < 0.001).

A report by Brooks et al. (2013) investigated the potential cumulative effects of prior concussions on neurocognitive functioning. In this study 643 male and female Bantam and Midget ice hockey players, ages 13 to 17.9 years old, were recruited from the most elite divisions of hockey leagues in Edmonton, Alberta, Canada. Exclusion criteria consisted of having English as a second language, having had a concussion within the past six months, attention or learning problems, and an injury or chronic illness that prevented return to play at the beginning of the season. All athletes completed ImPACT baseline testing as part of a larger study on outcome from concussion (Brooks et al., 2013). Previous concussions were self-reported by the athlete and parent/guardian using a pre-season questionnaire (PSQ). Groups were made for those with no (62%), one (30.8%), and two or more (7.2%) previous concussions. The number of previous concussions as rated on the PSQ was significantly correlated with higher levels of PCS symptom ratings (p = 0.002), but not with cognitive abilities measured by ImPACT (p > 0.05) (Brooks et al., 2013).

Barker et al. (2017) performed a matched case-control analysis to determine the effects of multiple concussions on neurocognitive scores and symptoms using ImPACT. From the Nova Southeastern Sports Medicine Clinic database, exclusion criteria and case matching was applied to a pool of 26,240 male and female athletes, leaving 204 participants aged 10-19. Each concussion group contained 68 participants to equally represent those with 0, 1, and 2 prior concussions. Exclusion criteria included a self-reported history of treatment for substance abuse, psychiatric disorder, special education enrollment, repeated years of schooling, diagnosis of ADHD, learning disability, autism, speech therapy; different first language than test administered; and history of brain surgery (Barker et al., 2017). A variety of sports were represented, including football, lacrosse, soccer, wrestling, gymnastics, swimming, cheerleading, basketball, baseball, and tennis. Comparisons of the groups’ ImPACT composite scores showed no difference for Verbal Memory, Visual Memory, Visual Motor, Reaction Time, or Impulse Control. There was, however, a significant difference in the PCS total symptom score between those who had no previous concussions and those with two previous concussions, with the total symptom score of the two-previous concussion group being more than twice the score of the zero-concussion group (p < 0.05). Those with one prior concussion did not significantly differ from the other groups in symptom reporting.

The report by Iverson, Echemendia, LaMarre, Brooks, & Gaetz (2012) examined whether a history of three or more concussions is associated with poorer performance on neurocognitive testing or with greater reporting of subjective symptoms during athletes’ baseline preseason evaluation. From an archival database containing 786 male athletes who had undergone baseline ImPACT testing, 26 athletes aged 17 to 22 with a self-reported history of three or more concussions were identified. These athletes were matched to controls who had not sustained a prior concussion on age, education, self-reported learning problems, special education, and repeated grades. Most athletes were also matched based on the sport they played, the position played if possible, and the school or organization attended (Iverson et al. 2012). The sports included football, soccer, ice hockey, lacrosse, wrestling, and water polo. The compared ImPACT scores showed no difference between the groups except for the Verbal Memory composite, in which athletes with three or more prior concussions performed more poorly than those without concussion history (p = 0.028). The PCS symptom score differences were not significant (p = 0.13).

Another study by Tsushima, Geling, Arnold, & Oshiro (2016) explored the neuropsychological effects of repetitive, subconcussive impacts in youth sports that do not result in a diagnosable concussion. In this study 282 non-concussed male high school athletes (grades 8 to 12) from public schools were divided into two groups based on the known rates of concussions among various sports: the high contact sport group, consisting of football players and the low-contact sport group, including wrestling, soccer, baseball, judo and baseball. The assumption was made that more subconcussive head traumas occur in sports in which more concussions are reported (Tsushima et al., 2016). This increased frequency of injury can be likened to having a history of more previous concussions, while the lower frequency of injury can be likened to having fewer or no previous concussions. Baseline testing using ImPACT composite scores and symptom reporting using PCS was completed prior to the start of the athletes’ respective seasons and compared to testing after the season was finished. Analyses using t tests comparing the high-contact and low-contact groups showed lower scores in Visual Motor Speed (p < 0.001) and Reaction Time (p < 0.001) in the football players, but no differences in Verbal Memory, Visual Memory, and no significant differences in PCS total symptom scores (p = 0.069).

The study entitled “Examining neurocognitive function in previously concussed interscholastic female soccer players” by Forbes, Glutting, & Kaminski (2014) conducted a cross-sectional assessment of neurocognitive performance as related to repetitive subconcussive blows from purposeful heading. A total of 210 interscholastic female soccer players were recruited from four metropolitan U.S. high schools and equally split into two groups: never-been concussed (control) and previously concussed (experimental) prior to the beginning of the season. The Automated Neuropsychological Assessment Metrics (ANAM) version 1.0 was used to measure pre- and post-season neurocognitive function and a Concussion Symptom Checklist was completed to assess number and severity of 17 symptoms rated from 0 to 6. The ANAM test consists of five subset components: simple reaction time, continuous performance test, math processing, matching to sample, and Sternberg memory. These components are further explained in Table 4 of the Appendix. The number of headers was also recorded for each player during each competitive game. The average number of headers was approximately 24 for both the control and experimental groups. The average number of previous concussions in the experimental group was 1.3. There were no significant differences found in neurocognitive performance in any component of the ANAM between the two groups or in reported symptoms (all p values > 0.05). Therefore, the authors concluded that purposeful heading in soccer is more than likely not detrimental in terms of neurocognitive performance and long-term persistent concussion-related symptoms, even when players had a previous history of concussion (Forbes et al., 2014).


Overall, the results of this review do not strongly support the hypothesis that sustaining prior concussions negatively impacts objective neurocognitive function in adolescents that undergo computerized testing. However, it is premature to definitively conclude that there is no association, as two studies suggested a negative impact on Verbal Memory composite scores (Mannix et al., 2014; Iverson et al., 2012), and one study demonstrated lower scores for Visual Motor Speed and Reaction Time, both of which contain tasks involving working memory (Tsushima, Geling, Arnold & Oshiro, 2016).

The varying absence and presence of differences amongst neurocognitive function seen in these studies is not necessarily unprecedented, as past studies have also reported mixed results. Earlier studies containing high school athletes proposed that a history of two or more prior concussions display greater impairment on neuropsychological and memory tests than athletes with a history of only one concussion (Collins et al., 1999; Collins et al., 2002). Other studies containing high school and collegiate athletes have suggested measureable cognitive deficits from multiple prior concussions (Gaetz, Goodman, & Weinberg, 2000; Iverson, Gaetz, & Collins, 2004; Moser, Schatz, & Jordan, 2005; Schatz, Moser, Covassin, & Karpf, 2011), yet still others suggest no effects (Broglio, Ferrara, Piland, & Anderson, 2006; Bruce & Echemendia, 2009; Collie, McCrory & Makdissi, 2006; Iverson, Brooks, Lovell & Collins, 2006; Thornton, Cox, Whitfield, & Fouladi, 2008).

There are several speculated explanations for the apparent lack of association between concussion history and obvious testable neurocognitive deficits despite this association being proven in adults. Due to the focus on a younger population, it is possible that these results could represent recovery and neuroplasticity, a shorter duration of overall exposure to concussions and repetitive head trauma, less intense exposure (e.g. fewer hits, lesser force of impact, slower ball velocities) than in professional and collegiate athletes, or a combination of those factors (Brooks et al., 2016).

The study by Tsushima, Geling, Arnold, & Oshiro (2016) suggested that participating in high-contact sports such as football may affect neurocognitive functioning in youth athletes due to repetitive subconcussive head trauma. This may be due to incomplete neurological development, as animal and clinical research has shown that immature adolescent brains are more predisposed to head injury (Field, Collins, Lovell & Maroon, 2003). Additionally, it is possible that athletes who experience subconcussive impacts were actually concussed. The concept of a concussion spectrum calls into question the diagnostic approach to concussions, which mainly involves symptom analysis instead of concrete brain imaging (Forbes, Glutting & Kaminski, 2014).

The finding that different neurocognitive deficits were observed in different cognitive domains across studies makes test standardization both necessary yet problematic. Any type of testing must be standardized in order to compare results between individuals, but perhaps the computerized tests currently being used do not encompass all aspects of the neurocognitive domains tested. It is difficult to pinpoint specific domains as they often involve overlapping subdomains, some of which are not always tested. There are many ways to test “memory”, and it appears as though that may be key to ascertaining the effect multiple concussions have on specific aspects of memory. Every reviewed study used computerized testing of neurocognition, either ImPACT or ANAM for the purpose of standardizing performance assessment. ImPACT is relatively easy to administer, and research in the past decade has shown that it is a reliable, valid and practical approach to the neurocognitive assessment of mild TBI in high school and collegiate athletes (Schatz & Ferris, 2013; Maerlender et al, 2013).

ANAM is not as widely used as ImPACT, but has proven suitable for concussion surveillance and demonstrated validity, reliability as well as sensitivity to mild TBI (Cernich, Reeves, Sun, & Bleiberg, 2007).

There are many advantages of computerized testing, such as easy and rapid administration to large groups (and in different languages if needed), inclusion of adaptive test procedures, provision of more accurate and precise measurement of time-based responses (e.g. reaction time, response latency); consistent administration across various settings; immediate results relating to clinical diagnosis and prognosis, and finally easy collection, storage, access and sharing of data (De Marco & Broshek, 2016). Even with these advantages, the findings of this review support the need for future studies to use different testing modalities, as the neuropsychological test measures in this research only account for a handful of neurocognitive functions related to memory (visual memory, working memory) contained in the ImPACT battery and ANAM battery.

For example, Moore et al. (2015) investigated the effects of concussion history on children’s neurocognitive processing, with an emphasis on attention and cognitive control, during flanker performance. Cognitive control is associated with a wide range of processes and cannot be restricted to a particular cognitive domain, but the core functions that constitute cognitive control are working memory, inhibition and cognitive flexibility (Diamond, 2013). The presence of impairments in cognitive control may be attributed to deficits in attention, memory, language comprehension and emotional processing (Mackie, Van Dam & Fan, 2013).

It is worth noting that the ImPACT and ANAM test batteries are screening tools designed to assess cognitive symptoms to help diagnose concussions in an acute setting. These tests might not possess the sensitivity and specificity to allow for detection of chronic changes in cognition (Lovell, Collins, Iverson, Johnston & Bradley, 2004).

An important finding in four of the seven studies that used ImPACT testing is that adolescents with a history of prior concussions or repetitive subconcussive trauma had more self-reported symptoms (such as dizziness, fatigue, trouble falling asleep, difficulty concentrating, difficulty remembering) as assessed by the Post-Concussion Scale symptom portion of ImPACT, even when more than six months post-injury. Whether a true causal relationship exists between previous concussions and more severe symptoms needs to be further explored in adolescents and should be considered when monitoring recovery and determining the risk of sustaining a subsequent concussion.Unexpectedly, the number of symptoms reported did not correlate with testable neurocognitive abilities, suggesting that the current screening tools used are not able to accurately measure the subjective effects experienced by those with multiple concussions, and that perhaps multiple testing modalities should be included in future studies.

There were certain limitations and weaknesses in the reviewed studies that may have led to the inconclusive results of this review. First, although most studies had a large number of participants in total, all studies had small sample sizes of previously concussed athletes. As the number of previous concussions increased, the corresponding number of athletes decreased. For example, in the study by Iverson et al. (2012), their database of 786 subjects only contained 26 individuals with a history of three or more injuries. This limitation is and has been difficult to overcome due to the lack of a large cohort of multiply concussed athletes. Future studies would benefit from representing more previously concussed athletes to match the high number of controls to increase the statistical power of the studies.

Second, none of the studies defined the injury severity characteristics of prior concussions, age at which the prior concussions occurred, or the time interval between multiple concussions.Consequently, the severity of concussions was unknown. Though most studies only included athletes if they had not sustained a concussion within the past six months, the average time since last concussion and time between concussions was unaccounted for. This is important to know due to the concept of a vulnerable window, during which repeat concussion results in worse outcomes and prolonged recovery in children (Eisenberg, Andrea, Meehan & Mannix, 2013). There is preliminary evidence for a potential association between a second blow to the head sustained within 24 hours of an initial concussion and more significant and persistent post-concussion symptoms in adolescent student-athletes (Terwilliger, Pratson, Vaughan, Gioia, 2016).

Third, the primary outcome of all of the studies reviewed was a rapid computerized screen of neurocognitive abilities (either ImPACT or ANAM) and does not represent a more complex or comprehensive evaluation of neurocognitive functioning, such as paper and pencil testing from a battery of neuropsychological tests. Computerized testing is useful for standardized scores yet is in itself limiting, as it does not approach neurocognitive deficit detection from all angles. There is a general lack of studies assessing post-concussion neurocognition in children in other ways, and it is possible that a different test battery would lead to results that differ from those of this review. Furthermore, studies did not include other methods of investigation such as functional magnetic resonance imaging (fMRI) that may reveal persistent neurological effects from prior multiple concussions through the detection of hemodynamic changes associated with neuronal activity. Researchers have documented fMRI changes in athletes with persistent post-concussion symptoms but no difference in neurocognitive task performance compared to controls. (Chen et al., 2014). This suggests that regional brain activation shown by fMRI during a task may be more sensitive to cumulative concussive injuries than test performance. Thus, the conclusions from this review are limited to an absence of neurocognitive effects based solely on the computerized batteries that were administered.
Fourth, each individual tested could have a myriad of psychological, biological, and social factors that could either intensify or reduce the severity or onset of serious head injury consequences. Some of these were accounted for, but the same inclusion and exclusion criteria did not apply to all of the studies.

Fifth, the studies were not able to account for variables that may have affected neuropsychological functioning such as test effort and school aptitude. Some athletes tend to “tank” or “sandbag” their baseline performances in a way that makes post-concussion return-to-play easier to pass (Erdal, 2012). No studies reviewed contained effort tests to assess test motivation in the participants.

Lastly, the studies’ common use of cross-sectional design renders them less powerful and convincing than a longitudinal study. In addition, the retrospective reporting of concussions can be influenced by normal human biases, especially if concussions occurred many years prior.

Going forward, studies would benefit from recruiting larger samples of concussed athletes and using multiple investigative techniques of neurocognitive testing to assess a broader set of measures and domains. For example, the concurrent use of multiple batteries of computerized tests with imaging to view brain activity during task performance could add another dimension to the studies performed thus far. Future studies should be longitudinal in nature, wherein athletes are followed over several years to monitor recovery, repeat testing, document additional injuries, and identify those who stop playing sports due to injuries. Certain studies in this review indirectly attributed the group differences in reporting more symptoms to a history of concussions, but a longitudinal study might establish whether there is a direct relationship, or if there are factors that mediate that relationship. Prospective studies are also required to determine whether the lack of adverse cognitive effects found here is carried throughout an athlete’s lifetime, or if the cumulative effects of concussions show up as even longer-term symptom sequelae. Of particular importance is the potential association between playing high school football and the increased risk of neurodegenerative disorders such as chronic traumatic encephalopathy and Alzheimer’s disease later in life. Another area for further research is exploring the plausible relationship between increased subjective symptom scores and long-term development of depression, anxiety, or other mental health problems.

In conclusion, there are still inconsistencies regarding the effects of multiple prior concussions on computerized neurocognitive performance in youth athletes, though the evidence shows that prior concussive and subconcussive history being a very weak predictor of lower neurocognitive scores for tasks relating to memory. Although these results are somewhat reassuring given the current concern over possible long-term cognitive effects, they still highlight the need for more studies using different modalities of neurocognitive testing in pediatric athletes and designing studies to be longitudinal in nature. The implications of these findings are important not only for the management of youth athletes with a history of multiple concussions, but also for the diagnosis of concussions, monitoring recovery, return-to-play guidelines, and implementing new policies regarding rules of youth sports to minimize the amount of traumatic brain injuries.


Barker, T., Russo, S. A., Barker, G., Rice, M. A., Jeffery M. G., Broderick, G., & Craddock, T. J. (2017). A case matched study examining the reliability of using ImPACT to assess the effects of multiple concussions. BMC psychology 5(1), 14. 

Bauer, R., & Fritz, H. (2004). Pathophysiology of traumatic injury in the developing brain: an introduction and short update. Experimental and ToxicologicPathology56(1), 65-73.

Broglio, S. P., Ferrara, M. S., Piland, S. G., & Anderson, R. B. (2006). Concussion history is not a predictor of computerised neurocognitive performance. British Journal of Sports Medicine40(9), 802-805.

Brooks, B. L., Mannix, R., Maxwell, B., Zafonte, R., Berkner, P. D., & Iverson, G. L. (2016). Multiple past concussions in high school football players: are there differences in cognitive functioning and symptom reporting?. The American journal of sports medicine44(12), 3243-3251.

Brooks, B. L., McKay, C. D., Mrazik, M., Barlow, K. M., Meeuwisse, W. H., & Emery, C. A. (2013). Subjective, but not objective, lingering effects of multiple past concussions in adolescents. Journal of neurotrauma30(17), 1469-1475.

Bruce, J. M., & Echemendia, R. J. (2009). History of multiple self-reported concussions is not associated with reduced cognitive abilities. Neurosurgery64(1), 100-106.

Centers for Disease Control and Prevention. (2017). Traumatic Brain Injury & Concussion. Retrieved from https://www.cdc.gov/traumaticbraininjury/index.html

Cernich, A., Reeves, D., Sun, W., & Bleiberg, J. (2007). Automated neuropsychological assessment metrics sports medicine battery. Archives of Clinical Neuropsychology22, 101-114.

Collie, A., McCrory, P., & Makdissi, M. (2006). Does history of concussion affect current cognitive status?. British Journal of Sports Medicine40(6), 550-551.

Collins, M. W., Grindel, S. H., Lovell, M. R., Dede, D. E., Moser, D. J., Phalin, B. R.,… & Sears, S. F. (1999). Relationship between concussion and neuropsychological performance in college football players. Jama282(10), 964-970.

Collins, M. W., Lovell, M. R., Iverson, G. L., Cantu, R. C., Maroon, J. C., & Field, M. (2002). Cumulative effects of concussion in high school athletes. Neurosurgery51(5), 1175-1181.

Daneshvar, D. H., Nowinski, C. J., McKee, A. C., & Cantu, R. C. (2011). The epidemiology of sport-related concussion. Clinics in sports medicine30(1), 1-17.

De Marco, A. P., & Broshek, D. K. (2016). Computerized cognitive testing in the management of youth sports-related concussion. Journal of childneurology31(1), 68-75.

Echemendia, R. J., Iverson, G. L., McCrea, M., Macciocchi, S. N., Gioia, G. A., Putukian, M., & Comper, P. (2013). Advances in neuropsychological assessment of sport-related concussion. Br J Sports Med47(5), 294-298.

Eisenberg, M. A., Andrea, J., Meehan, W., & Mannix, R. (2013). Time interval between concussions and symptom duration. Pediatrics, peds-2013.

Erdal, K. (2012). Neuropsychological testing for sports-related concussion: how athletes can sandbag their baseline testing without detection. Archives of clinical neuropsychology27(5), 473-479.

Field, M., Collins, M. W., Lovell, M. R., & Maroon, J. (2003). Does age play a role in recovery from sports-related concussion? A comparison of high school and collegiate athletes. The Journal of pediatrics142(5), 546-553.

Forbes, C. R., Glutting, J. J., & Kaminski, T. W. (2016). Examining neurocognitive function in previously concussed interscholastic female soccer players. Applied Neuropsychology: Child5(1), 14-24.

Gaetz, M., Goodman, D., & Weinberg, H. (2000). Electrophysiological evidence for the cumulative effects of concussion. Brain Injury14(12), 1077-1088.

Gefen, A., Gefen, N., Zhu, Q., Raghupathi, R., & Margulies, S. S. (2003). Age dependent changes in material properties of the brain and braincase of the rat. Journal of neurotrauma20(11), 1163-1177.

Giza, C. C., Kutcher, J. S., Ashwal, S., Barth, J., Getchius, T. S., Gioia, G. A., … & McKeag, D. B. (2013). Summary of evidence-based guideline update: Evaluation              and management of concussion in sports Report of the Guideline Development              Subcommittee of the American Academy of Neurology. Neurology80(24), 2250              2257.

Giza, C. C., Mink, R. B., & Madikians, A. (2007). Pediatric traumatic brain injury: not just little adults. Current opinion in critical care13(2), 143-152.

Guskiewicz, K. M., McCrea, M., Marshall, S. W., Cantu, R. C., Randolph, C., Barr, W., … & Kelly, J. P. (2003). Cumulative effects associated with recurrent concussion in collegiate football players: the NCAA Concussion Study. Jama290(19), 2549-2555.

ImPACT Applications, Inc. (2017). ImPACT version 2.0: Clinical user’s manual. Retrieved from https://www.impacttest.com/dload/ImPACT21_usermanual.pdf

Iverson, G. L., Brooks, B. L., Lovell, M. R., & Collins, M. W. (2006). No cumulative effects for one or two previous concussions. British Journal of SportsMedicine40(1), 72-75.

Iverson, G. L., Echemendia, R. J., LaMarre, A. K., Brooks, B. L., & Gaetz, M. B. (2012). Possible lingering effects of multiple past concussions. Rehabilitation research and practice2012.

Iverson, G. L., Gaetz, M., Lovell, M. R., & Collins, M. W. (2004). Cumulative effects of concussion in amateur athletes. Brain injury18(5), 433-443.

Kannan, N., Ramaiah, R., & Vavilala, M. S. (2014). Pediatric neurotrauma. International journal of critical illness and injury science4(2), 131.

Kimbler, D. E., Murphy, M., & Dhandapani, K. M. (2011). Concussion and the Adolescent Athlete. The Journal of Neuroscience Nursing: Journal of theAmerican Association of Neuroscience Nurses43(6), 10.

Langlois, J. A., Rutland-Brown, W., & Wald, M. M. (2006). The epidemiology and impact of traumatic brain injury: a brief overview. The Journal of head trauma rehabilitation21(5), 375-378.

Lovell, M. R., Collins, M. W., Iverson, G. L., Johnston, K. M., & Bradley, J. P. (2004). Grade 1 or “ding” concussions in high school athletes. The American journal ofsports medicine32(1), 47-54.

Mackie, M. A., Van Dam, N. T., & Fan, J. (2013). Cognitive control and attentional functions. Brain and Cognition, 82(3), 301–312.

Mannix, R., Iverson, G. L., Maxwell, B., Atkins, J. E., Zafonte, R., & Berkner, P. D. (2014). Multiple prior concussions are associated with symptoms in high school athletes. Annals of clinical and translational neurology1(6), 433-438.

Mannix, R., Meehan, W. P., Mandeville, J., Grant, P. E., Gray, T., Berglass, J., … & Peters, N. V. (2013). Clinical correlates in an experimental model of repetitive mild brain injury. Annals of neurology74(1), 65-75.

Meehan III, W. P., Zhang, J., Mannix, R., & Whalen, M. J. (2012). Increasing recovery time between injuries improves cognitive outcome after repetitive mild concussive brain injuries in mice. Neurosurgery71(4), 885-892.

Meehan, W. P., d’Hemecourt, P., Collins, C. L., Taylor, A. M., & Comstock, R. D. (2012). Computerized neurocognitive testing for the management of sport-related concussions. Pediatrics129(1), 38-44.

Miller, J. H., Gill, C., Kuhn, E. N., Rocque, B. G., Menendez, J. Y., O’Neill, J. A., … & Ferguson, D. (2016). Predictors of delayed recovery following pediatric sports related concussion: a case-control study. Journal of Neurosurgery:Pediatrics17(4), 491-496.

Moore, R. D., Pindus, D. M., Drolette, E. S., Scudder, M. R., Raine, L. B., & Hillman, C. H. (2015). The persistent influence of pediatric concussion on attention and cognitive control during flanker performance. Biologicalpsychology109, 93-102.

Moser, R. S., Schatz, P., & Jordan, B. D. (2005). Prolonged effects of concussion in high school athletes. Neurosurgery57(2), 300-306.

Pfister, T., Pfister, K., Hagel, B., Ghali, W. A., & Ronksley, P. E. (2016). The incidence of concussion in youth sports: a systematic review and meta-analysis. Br J Sports Med50(5), 292-297.

Prins, M. L., & Hovda, D. A. (2003). Developing experimental models to address traumatic brain injury in children. Journal of neurotrauma20(2), 123-137.

Prins, M., Hales, A., Reger, M., Giza, C., & Hovda, D.(2010).Repeat traumatic brain injury in the juvenile rat is associated with increased axonal injury and cognitive impairments. Dev. Neurosci. 32, 510.

Schatz, P., & Sandel, N. (2013). Sensitivity and specificity of the online version of ImPACT in high school and collegiate athletes. The American Journal of SportsMedicine41(2), 321-326.

Schatz, P., Moser, R. S., Covassin, T., & Karpf, R. (2011). Early indicators of enduring symptoms in high school athletes with multiple previous concussions. Neurosurgery68(6), 1562-1567.

Terwilliger, V. K., Pratson, L., Vaughan, C. G., & Gioia, G. A. (2016). Additional post-concussion impact exposure may affect recovery in adolescent athletes. Journal of neurotrauma33(8), 761-765.

Thornton, A. E., Cox, D. N., Whitfield, K., & Fouladi, R. T. (2008). Cumulative concussion exposure in rugby players: neurocognitive and symptomatic outcomes. Journal of Clinical and Experimental Neuropsychology30(4), 398-409.

Tsushima, W. T., Geling, O., Arnold, M., & Oshiro, R. (2016). Are there subconcussive neuropsychological effects in youth sports? An exploratory study of high-and low-contact sports. Applied Neuropsychology: Child5(2), 149-155.

Tsushima, W. T., Geling, O., Arnold, M., & Oshiro, R. (2016). Effects of two concussions on the neuropsychological functioning and symptom reporting of high school athletes. Applied Neuropsychology: Child5(1), 9-13.

Vagnozzi, R., Signoretti, S., Tavazzi, B., Floris, R., Ludovici, A., Marziali, S., … & Lazzarino, G. (2008). Temporal window of metabolic brain vulnerability to concussion: a pilot 1H-magnetic resonance spectroscopic study in concussed athletes—part III. Neurosurgery62(6), 1286-1296.

Yue, J. K., Winkler, E. A., Burke, J. F., Chan, A. K., Dhall, S. S., Berger, M. S., … & Tarapore, P. E. (2016). Pediatric sports-related traumatic brain injury in United States trauma centers. Neurosurgical focus40(4), E3


Table 1. ImPACT Neuropsychological Test Modules (ImPACT Applications Inc., 2017).

Test Module & Description Ability Areas Tested
  1. Word Discrimination

-Twelve target words presented twice
-Recall is tested for a 24-word list with 12 target words and 12 non-target words from the same semantic category as the target word

Immediate and delayed memory for words
  1. Design Memory

-Twelve target designs presented twice
-Recall is tested for 24 designs, 12 target and 12 non-target designs

Immediate and delayed memory for designs
  1. X’s and O’s

-First is a distractor task: subject is asked to click the left mouse button if a blue square is presented and the right mouse button if a red circle is presented

– Then subject is presented with a random assortment of illuminated X’s and O’s and tested for memory of their location after the distractor task re-appears

Attention, concentration, working memory, reaction time
  1. Symbol Match

-Recall of 9 common symbols matched to a number

Visual processing speed, learning and memory
  1. Color Match

-First, the subject clicks a red, blue or green button as they are presented on the screen to avoid effects of color blindness

-Then a word is displayed on the screen in the same colored ink as the word or in a different colored ink

-Subject is instructed to click in the box as quickly as possible only if the word is presented in the matching ink

Focused attention, response inhibition, reaction time
  1. Three Letters

-Subject clicks on numbered buttons in backward order starting with 25, then is asked to remember three consonant letters displayed on the screen

-Numbered grid re-appears and subject clicks the numbered buttons in backward order again

-After 18 seconds, the numbered grid disappears and subject recalls the three letters using the keyboard

Attention, concentration, working memory, visual-motor speed

Table 2. ImPACT Composite Scores Composition (ImPACT Applications Inc., 2017)

Composite Score Comprised of:
Verbal Memory (higher score = better performance)
  • Total % correct score from Module 1
  • Total correct hidden symbols from Module 4
  • % total letters correct from Module 6
Visual Memory (higher score = better performance)
  • Total % correct score from Module 2
  • Total correct memory score from Module 3
Visual Motor Speed (higher score = better performance)
  • Total number correct /4 during interference of Module 3
  • Average counted correctly x3 from countdown phase of Module 6
Reaction Time (lower score = better performance)
  • Average correct RT of interference stage of Module 3
  • Average Correct RT /3 of Module 4
  • Average Correct RT of Module 5
Impulse Control (lower score = better performance)


*Used as a measure of test validity

  • Total errors on the interference phase of Module 3
  • Total commissions from Module 5

Table 3. Post-Concussion Symptom Scale (ImPACT Applications Inc., 2017).

Symptom Minor Moderate Severe
Headache 1 2 3 4 5 6
Nausea 1 2 3 4 5 6
Vomiting 1 2 3 4 5 6
Balance Problems 1 2 3 4 5 6
Dizziness 1 2 3 4 5 6
Fatigue 1 2 3 4 5 6
Trouble Falling Asleep 1 2 3 4 5 6
Sleeping More Than Usual 1 2 3 4 5 6
Sleeping Less Than Usual 1 2 3 4 5 6
Drowsiness 1 2 3 4 5 6
Sensitivity to Light 1 2 3 4 5 6
Sensitivity to Noise 1 2 3 4 5 6
Irritability 1 2 3 4 5 6
Sadness 1 2 3 4 5 6
Nervousness 1 2 3 4 5 6
Feeling More Emotional 1 2 3 4 5 6
Numbness or Tingling 1 2 3 4 5 6
Feeling Slowed Down 1 2 3 4 5 6
Feeling Mentally Foggy 1 2 3 4 5 6
Difficulty Concentrating 1 2 3 4 5 6
Difficulty Remembering 1 2 3 4 5 6
Visual Problems 1 2 3 4 5 6

Instead of zero, subjects check a box indicating they are not experiencing the symptom.

Table 4. Subset components of ANAM used by Forbes, Glutting & Kaminski (2016).

Component Description
Simple reaction time (SRT) -Measures response time (ms) to a stimulus presented at various time intervals
Continuous performance test (CPT) -Measures attention and concentration


-Participant must continuously monitor letters and identify whether the current letter displayed is the same or different from the immediately preceding letter

Math processing (MTH) -Measures mental processing speed and mental efficiency


-Participants solve a three-step simple addition or subtraction equation and identify whether the solution is greater than or less than 5

Matching to sample (MSP) -Measures visual memory


-Participants recall a checkerboard matrix after 5s and match it to the original matrix design

Sternberg memory (STN) -Measures working memory


-Participants memorize a string of 6 letters and subsequently recall whether or not a presented letter belongs to that six-letter string

Table 5. Summary of the reviewed studies reporting findings in previously concussed groups compared to non-concussed groups.

Study Authors Testing Modality Cognitive Domains Affected No. of Post-Concussion Symptoms Significance
(p value)
“Multiple prior concussions are associated with symptoms in high school athletes” Mannix et al. ImPACT -Verbal Memory (decreased)


-Impulse Control (increased)

Increased -Verbal Memory
(p = 0.039)


-Impulse Control
(p = 0.002)
-Symptoms (p < 0.001)

“Effects of two concussions on the neuropsychological functioning and symptom reporting in high school athletes” Tsushima, Geling, Arnold & Oshiro ImPACT None Same -ImPACT Scores
(p > 0.25)
-Symptoms (p = 0.195)
“Multiple past concussions in high school football players: are there differences in cognitive functioning and symptom reporting?” Brooks et al. ImPACT None Increased -ImPACT Scores
(p = 0.396)
-Symptoms (p < 0.001)
“Subjective but not objective, lingering effects of multiple past concussions in adolescents” Brooks et al. ImPACT None Increased -ImPACT Scores
(p > 0.05)
-Symptoms (p = 0.002)
“A case matched study examining the reliability of using ImPACT to assess the effects of multiple concussions” Barker et al. ImPACT None Increased -ImPACT Scores
(all p > 0.16)


-Symptoms (p = 0.01)

“Possible lingering effects of multiple past concussions” Iverson et al. ImPACT Verbal Memory Same -Verbal Memory
(p = 0.028)
-Symptoms (p = 0.13)
“Are there subconcussive neuropsychological effects in youth sports? An exploratory study of high-and low-contact sports” Tsushima, Geling, Arnold & Oshiro ImPACT -Visual Motor Speed (increased)
-Reaction Time (increased)
Same -Visual Motor Speed, Reaction Time
(p < 0.001)
-Symptoms (p = 0.69)
“Examining neurocognitive function in previously concussed interscholastic female soccer players Forbes, Glutting & Kaminski ANAM None Same p > 0.05

Cite This Work

To export a reference to this article please select a referencing stye below:

Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.

Related Services

View all

Related Content

All Tags

Content relating to: "Neurology"

Neurology is the specialist branch of medicine that deals with the treatment of disorders of the nervous system. This means that neurologists concern themselves with issues affecting the brain, the nerves, and the spinal cord.

Related Articles

DMCA / Removal Request

If you are the original writer of this dissertation and no longer wish to have your work published on the UKDiss.com website then please: