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On average, 1.4 million traumatic brain injuries (TBI) occur annually; 75%–90% of which are mild TBI or concussions (Chrisman & Richardson, 2014). Until recent years, the standard of no outward as physical evidence of damage due to mild TBI, has been a significant component contributing to the low emphasis on research (McKee & Robinson, 2014). Previously it was thought that those with concussions recovered quickly, but now studies indicate that symptoms may last throughout months, years, or possibly a lifetime. One symptom that is frequently reported by subjects after mild TBI is a depressed mood (Chen, Johnston, Petrides, & Ptito, 2008). One population, in particular, has a great concussion risk. Adolescents involved in sports have a 0.23% chance of concussion overall (Pfister, Pfister, Hagel, Ghali, & Ronksley, 2015). The goal of this study is to explore the relationship between concussions and the rates of major depressive disorder in adolescent athletes ages 14-18.
The general populace now recognizes major depressive disorder as a common mental disorder with a lifetime prevalence of 16.2% (Sun, Niu, You, Zhou, & Tang, 2017). In the period of life known as adolescence, the development of depression has been linked by studies to co-morbidities such as decreased school performance, substance abuse, unhealthy weight gain, and suicide (Chrisman & Richardson, 2014). Into adulthood decline in physical health and increased risk of suicide persist (Sun et al., 2017). Following a concussion, victims observe the following list of symptoms: irritability, anxiety, poor concentration, fatigue, depression, and decreased coordination all which are a part of post-concussion syndrome (Trahan, Ross, & Trahan, 2001). Full recovery from symptoms may be within 7-10 days for most bodies, but others experience symptoms for a more extended period (Maruta et al., 2016).
A concussion consists of fast acceleration and deceleration of the brain that causes it to change shape momentarily (McKee & Robinson, 2014). When the brain gets deformed, it affects the shape of blood vessels, axons, and can impact membranes (McKee & Robinson, 2014). The forces cause the release of neurotransmitters, and the stretching of blood vessels disrupts the balance of the blood-brain barrier (McKee & Robinson, 2014). This process also causes entire areas to become affected by but also individual cells like axons (McKee & Robinson, 2014). Studies show that there can be lasting microscopic effects on axons and the severity of the injury to the axons in proportional to the severity of the concussion (McKee & Robinson, 2014).
The Post-Concussion Syndrome Checklist is a standardized way to have subjects rate the magnitude, regularity, and length of typical symptoms related to post-concussion syndrome (Trahan et al., 2001). The test is usually performed directly following the mild TBI. Following the concussion researchers also perform the Beaumont Post Concussional Index (BPCI) (Trahan et al., 2001). The BPCI is a 55-item survey with 33 questions about regular post-concussion symptoms. The scales on the BPCI are designed to measure frequency, intensity, or duration of these symptoms. Most of the items allow one to rate frequency or intensity on a 5-point scale. The 33 items together form a total score known as the Post Concussional Index (Trahan et al., 2001).
Studies measuring the impact of traumatic brain injury (TBI) have criteria in which subjects are selected and rejected. In a study by Moore, Sauve, & Ellemberg, researchers excluded patients with TBI if they had drug or alcohol abuse, mental retardation, or other neurological symptoms in their history that were not results of the mild TBI (2016). A similar study on concussion measured the effects of the concussion on attention. In this study, the researchers excluded those who had histories of brain injury and ADHD (Wu et al., 2018). In the study by Wu and his fellow researchers, the criteria for selection in the study on attention were young adults with diagnosed sports-related concussions (2018). Some studies benefit from having more variability in their subjects. By having subjects that are post-concussion with symptoms, and subjects post-concussion with no symptoms allows researchers to see the relationship between control and concussion and also within different degrees of TBI (Moore et al., 2016).
In post-TBI studies using various measurement techniques can lead a researcher to different insights into the brain. By using functional MRI, researchers could observe activation in areas related to working memory such as the prefrontal cortex (Moore et al., 2016). Other techniques were valuable because they had flexibility and decreased sensitivity to head motion. In a study related to this, the researcher used functional near-infrared spectroscopy (fNIRS) to visualize the absorption of oxygen in the brain (Wu et al., 2018). In tests studying attention, such as the one by Wu and his colleagues, the VSAT can be used (2018). The VSAT, which design by researchers in a previous study, was made to look at a subject’s capacity for continued attention and brain activation patterns (Wu et al., 2018).
Researchers use subject, self- report measures to asses major depressive disorder in individuals who have suffered from concussions. One measure used by Horn and his associates was the Hospital Anxiety and Depression Scale (van der Horn et al., 2016). A more common measure for depression by researchers is the Beck Depression Inventory II (BDI II). The BDI II is considered one of the most prominent measures globally for determining the existence and severity of depression traits (de Sá Junior, de Andrade, Andrade, Gorenstein, & Wang, 2018). Researchers used both brain scanning techniques and self-report measures to see depression in concussed individuals and also differences between sexes.
Researchers in some studies did not look into age and sex differences but noted that they might affect the occurrence of depression. In a study by Kontos, Covassin, Elbin, & Parker, the researchers noted that sex differences and age differences in depression after concussion from high school to college were not yet studied (2012). The researchers noted it was surprising because females were found in other studies to have higher risk factors for depression and have more severe neurocognitive effects following concussion compared to males (Kontos, Covassin, Elbin, & Parker, 2012). Another group of researchers did study the role of sex in depression after a concussion and found that the sex of the participant was not correlated to a diagnosis of depression (Chrisman, & Richardson, 2014). The same research study also found that the older age range of 15-17 year old compared to the age range of 12-14 years old was significantly correlated with the increased diagnosis of depression after concussion (Chrisman, & Richardson, 2014).
Another study by Yang, Peek-Asa, Covassin, & Torner showed that baseline depression level was a strong predictor of levels of depression and anxiety after concussion (2015). This studying indicates that professionals should have baseline screenings done on those at risk for concussion. A baseline screening for and depression would mean that that the subject would have a higher risk of post-concussion depression and anxiety (Yang, Peek-Asa, Covassin, & Torner, 2015).
Concussions affect many areas of the brain and the brain’s processing function. Recent research studies have yielded some results on the effect of mild TBI on the areas of subjects’ brain related to psychological processes such as attention and working memory (Wu et al., 2018). In one post-concussion study, the subjects showed abnormal activation in a specific area of the brain, the left middle frontal gyrus (Wu et al., 2018). Abnormal activation in this area during visual stimuli and processing suggests attention deficits in those that have had mild TBI (Wu et al., 2018). In the study by Moore, Sauve, & Ellemberg, TBI subjects showed lower activation in the medial prefrontal cortex compared with control subjects (2016). This area of the brain is related to working memory and is considered crucial for higher-order cognitive functioning (Moore et al., 2016). In another study, researchers noted a behavioral response during a working memory task. Unlike the previous study, the response accuracy and response speed was not different between mild TBI and control groups (Chen, Johnston, Petrides, & Ptito, 2008). When researchers looked at the blood-oxygen level results of the fMRI they did see a difference. The subjects who had depression and were athletes post-concussion showed lower activity in the dorsolateral prefrontal cortex and deactivation in the temporal and frontal regions of the brain (Chen et al., 2008). Chen and his collogues also used structural imaging called voxel-based morphometry to look at the concentration of gray matter in those areas (2008). Researchers concluded that the higher severity of the depression symptoms in the subject, the more gray matter loss in the areas associated in major depressive disorder (Chen et al., 2008).
Studies also used the mentioned Post-concussional Index (PCI) and compared it to the BDI II for subjects. Trahan, Ross, & Trahan analyzed the data and found high correlations between a high score on the PCI and high scores of the BDI II (2001). High self-reported BDI II score was correlated with alterations in frontal-alpha asymmetry measured by an EEG (Moore et al., 2016). A previous study found that the difference in power between the left and right front brain hemispheres is a maker of emotional reaction (Moore et al., 2016). The results of the alterations were only statistically significant for athletes that were post-concussion but no other group of subjects (Moore et al., 2016). Even after athletes in the study were asymptomatic for common symptoms and returned to play still the study found to have effects in the EEG scan (Moore et al., 2016). Researchers state that this is an example how the effects of mild TBI can be long-term and should be monitored for additional periods of time even after the resolution common of common symptoms (Moore et al., 2016). The EEG device may be a device that can prevent serious progression of neurological disorders (Moore et al., 2016).
In a study looking at the immediate effects of concussion, researchers sampled high school and collegiate athletes before the concussion, two days after the concussion, seven days after the concussion, and 14 days after concussion (Kontos et al., 2012). The athletes showed increased depression levels from their baseline at all of the 2, 7, and 14-day timeline (Kontos et al., 2012). The researcher also found that collegiate athletes had a more considerable increase in depression levels 14 days post-concussion over the high schoolers (Kontos et al., 2012). Subjects showed slower reaction time and less visual memory at 14 days post-concussion, and slower reaction at the 7-day mark also (Kontos et al., 2012).
This study is based on the studies performed by Kontos, Covassin, Elbin, & Parker in 2013 and Moore, Sauve, & Ellemberg in 2016. We will examine the effect of concussion on BDI II score and frontal alpha asymmetry using baseline, 7-day post-concussion, 14-day post-concussion, and 30 post-concussion measurements. We hypothesize that subjects will exhibit higher levels of BDI-II and decreased levels frontal alpha asymmetry compared to baseline in all stages of the post-concussion testing.
The study will be a 2-year sample of high school males ages 14-18 in the Cedar Falls/ Waterloo area. The participants must be involved in at least one sport. There will be 60 subjects total in the experimental group. Subjects will be recruited by first contacting the athletic director of an area high school. With cooperation from the athletic director, male athletes will be sent home with a note that describes the study which will take place at an area hospital. Parents or guardians of students under the age of 18 will need to provide written consent at the time of the baseline study. The students will have an excused absence from school for the baseline study, and the student will continue to be excused if they meet the criteria. Exclusion factors for all participants will be the following: a history of drug or alcohol abuse, special education, ADHD, diagnosed psychiatric disorder(s), prior brain injury, and a baseline BDI II score of over 20. Subjects that have a BDI score of over 20 will be referred to a psychiatric resource. The experimental group examining sport-related concussions will be required to provide documentation that their concussion was diagnosed by a medical professional.
Letter sent out to participants will read “You are a potential subject for a research study involving high school athletes. You will be excused from school on this date to undergo approximately 30 minutes of testing at your nearest hospital. The testing will include a survey and a non-invasive medical scan. Follow up screening will be involved in the future at researcher discretion. If interested, please notify your athletic director and email [email protected] with further questions. Parent/guardian presence and permission are required at the time of the study.”
Participants will visit the hospital for the first time and learn about the procedure with their parents/legal guardian. They will be shown the room where the BDI II will be performed and the room and set up of the EEG machine. They will be told that they can leave at any during the study. After the parents and guardians grant consent, the baseline testing will occur.
The Beck Depression Inventory-II will be on a computer screen for subjects to fill out. The subjects will be alone in the room to fill out the inventory and will ring a bell when finished. After completion of the inventory, a trained research assistant will lead the subject into a Faraday Chamber. The subject will be fitted with an EEG net on their head. The research assistant will instruct the subject to sit relaxed in the chair for five minutes with their eyes closed. During this time spontaneous EEG information will be recorded.
Participants scheduled for evaluation after a concussion will be prompted to be transported to the hospital by a parent/ legal guardian if still experiencing symptoms. Subjects returning for post-concussion analysis will be asked for documentation of their concussion. Researchers will perform evaluations at three separate occasions seven days post-concussion, 14 days post-concussion, and 30 days post-concussion. At each evaluation, The Beck Depression Inventory II will be on a computer screen for subjects to fill out. The subjects will be alone in the room to fill out the inventory and will ring a bell when finished. After completion of the inventory, a trained research assistant will lead the subject into a Faraday Chamber. The subject will be fitted with an EEG net on their head. The research assistant will instruct the subject to sit relaxed in the chair for five minutes with their eyes closed. During this time spontaneous EEG information will be recorded
Diagnosis of concussion by health care provider will need to meet three criteria. The criteria increase for base level in post-concussion symptoms, decrease from base level in a neurocognitive score and presence of concussion signs on the field or court (Kontos et al., 2013).
The BDI II is considered one of the most prominent measures globally for determining the existence and severity of depression traits (de Sá Junior, de Andrade, Andrade, Gorenstein, & Wang, 2018). This consist of 21 self-reported topic which subjects rate on a scale of 0-3 (Kontos et al., 2013). The scores for the BDI range from 0-63 with minimal depression scoring 0-13 mild depression scoring 14-19 moderate depression scoring 20-28 and severe depression scoring above 28 (Kontos et al., 2013). An example BDI II question would be to rate oneself on a scale of 0 indicating no feelings to 3 meaning extreme emotional feelings for the following statement:
I blame myself for everything bad that happens.
The Faraday Chamber used will be soundproof and electromagnetically shielded (Moore et al., 2016). There will be 30 sensors on the EEG net that will be placed on the skull and the measured impedance between electrodes will be below 40 k also the first 30 seconds of the EEG collection will be disregarded to account for outside stimuli (Moore et al., 2016). Data compilation from the EEG will follow Moore’s experiment exactly. It will be performed “offline via Brain Vision Analyzer version 1.05 (Brain Products GmbH, Munich, Germany)” (Moore et al., 2016, p.4). This program will indicate regions of interest in the EEG in both the left and right frontal regions and give a numerical value for them (Moore et al., 2016). These numbers in the datasets will give off readings of alpha waves, and the differences between the two sides will be compared to assess frontal alpha asymmetry (Moore et al., 2016).
- Chen, J.-K., Johnston, K. M., Petrides, M., & Ptito, A. (2008). Neural substrates of symptoms of depression following concussion in male athletes with persisting postconcussion symptoms. Archives of General Psychiatry, 65(1), 81–89. https://doiorg.proxy.lib.uni.edu/10.1001/archgenpsychiatry.2007.8
- Chrisman, S. P. D., & Richardson, L. P. (2014). Prevalence of diagnosed depression in adolescents with history of concussion. Journal of Adolescent Health, 54(5), 582–586. https://doi-org.proxy.lib.uni.edu/10.1016/j.jadohealth.2013.10.006
- de Sá Junior, A. R., de Andrade, A. G., Andrade, L. H., Gorenstein, C., & Wang, Y.-P. (2018). Response pattern of depressive symptoms among college students: What lies behind items of the Beck Depression Inventory-II? Journal of Affective Disorders, 234, 124–130. https://doi-org.proxy.lib.uni.edu/10.1016/j.jad.2018.02.064
- Kontos, A. P., Covassin, T., Elbin, R., & Parker, T. (2012). Depression and Neurocognitive Performance After Concussion Among Male and Female High School and Collegiate Athletes. Archives of Physical Medicine and Rehabilitation, 93(10), 1751-1756. doi:10.1016/j.apmr.2012.03.032
- Maruta, J., Spielman, L. A., Yarusi, B. B., Wang, Y., Silver, J. M., & Ghajar, J. (2016). Chronic post-concussion neurocognitive deficits II Relationship with persistent symptoms. Frontiers in Human Neuroscience, 10. Retrieved from https://login.proxy.lib.uni.edu/login?url=http://search.ebscohost.com/login.aspx?direct=t ue&db=psyh&AN=2016-45752-001&site=ehost-live
- McKee, A. C., & Robinson, M. E. (2014). Military-related traumatic brain injury and neurodegeneration. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 10(3, Suppl), S242–S253. https://doi org.proxy.lib.uni.edu/10.1016/j.jalz.2014.04.003
- Moore, R. D., Sauve, W., & Ellemberg, D. (2016). Neurophysiological correlates of persistent psycho-affective alterations in athletes with a history of concussion. Brain Imaging and Behavior, 10(4), 1108–1116. https://doi-org.proxy.lib.uni.edu/10.1007/s11682-015-9473 6
- Pfister, T., Pfister, K., Hagel, B., Ghali, W. A., & Ronksley, P. E. (2015). The incidence of concussion in youth sports: A systematic review and meta-analysis. British Journal of Sports Medicine, 50(5), 292-297. doi:10.1136/bjsports-2015-094978
- Sun, X., Niu, G., You, Z., Zhou, Z., & Tang, Y. (2017). “Gender, negative life events and coping on different stages of depression severity: A cross-sectional study among Chinese university students”: Corrigendum. Journal of Affective Disorders, 215, 102. https://doi org.proxy.lib.uni.edu/10.1016/j.jad.2017.02.032
- Trahan, D. E., Ross, C. E., & Trahan, S. L. (2001). Relationships among postconcussional-type symptoms, depression, and anxiety in neurologically normal young adults and victims of mild brain injury. Archives of Clinical Neuropsychology, 16(5), 435–445. https://doi org.proxy.lib.uni.edu/10.1016/S0887-6177(00)00051-2
- van der Horn, H. J., Liemburg, E. J., Scheenen, M. E., de Koning, M. E., Spikman, J. M., & vander Naalt, J. (2016). Post-concussive complaints after mild traumatic brain injury associated with altered brain networks during working memory performance. Brain Imaging and Behavior, 10(4), 1243–1253. https://doi org.proxy.lib.uni.edu/10.1007/s11682-015-9489-y
- Wu, Z., Mazzola, C. A., Catania, L., Owoeye, O., Yaramothu, C., Alvarez, T., … Li, X. (2018). Altered cortical activation and connectivity patterns for visual attention processing in young adults post‐traumatic brain injury: A functional near infrared spectroscopy study. CNS Neuroscience & Therapeutics, 24(6), 539–548. https://doi org.proxy.lib.uni.edu/10.1111/cns.12811
- Yang, J., Peek-Asa, C., Covassin, T., & Torner, J. C. (2015). Post-concussion symptoms of depression and anxiety in Division I collegiate athletes. Developmental Neuropsychology, 40(1), 18–23. https://doi org.proxy.lib.uni.edu/10.1080/87565641.2014.973499
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