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1 THE RELATIONSHIP BETWEEN PREDEPLOYMENT INTELLIGENCE AND PTSD IN OEF OIF VETERANS WITH MILD TRAUMATIC BRAIN INJURY By JOSEPH M. GULLETT A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2013
2 2013 Joseph M. Gullett
3 To my loving and beautiful wife, Alice
4 ACKNOWLEDGMENTS I thank my mother, my father, and my G randmother Loretta for my life and my education. I also thank my mentors Dr. Russell Bauer and Dr. David B. FitzGerald for their continued support.
5 TABLE OF CONTENTS P age ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 6 LIST OF ABBREVIATIONS ............................................................................................. 7 ABSTRACT ..................................................................................................................... 8 CHAPTER 1 INTRODUCTION .................................................................................................... 10 Overview ................................................................................................................. 10 PTSD Risk Factors ................................................................................................. 11 Cognitive Theories of PTSD ................................................................................... 12 Cognitive Reserve ................................................................................................... 14 The Relati onship between Intelligence and PTSD .................................................. 16 The Occurrence of Co morbid Depression & PTSD Post deployment .................... 17 Co occurring PTSD and mTBI ................................................................................ 18 Time Since Injury and Age at Injury ........................................................................ 19 Military Rank, Military Occupation Specialty, & Loss of Cons ciousness ................. 19 2 METHODS .............................................................................................................. 21 Participants ............................................................................................................. 21 Cognitive Measures ................................................................................................ 22 Self Report Measures ............................................................................................. 25 Procedur e ............................................................................................................... 26 3 RESULTS ............................................................................................................... 30 4 DISCUSSION ......................................................................................................... 37 LIST OF REFERENCES ............................................................................................... 42 BIOGRAPHICAL SKETCH ............................................................................................ 51
6 LIST OF TABLES Table P age 2 1 P articipant demographics ................................................................................... 29 3 1 Intercorrelations between cognitive and emotional functioning measures for veterans .............................................................................................................. 34 3 2 Summary of regression analysis for IQ change score pred icting P TSD reporting in veterans ........................................................................................... 35 3 3 Summary of r egression analysis for AFQT p redicting PTS D reporting in veterans .............................................................................................................. 35 3 4 Analysis of covariance for differences in exec utive functioning by AFQT ........... 36 3 5 Summary of regression analysis for executive functioning composite predicting P TSD reporting in veterans ................................................................ 36
7 LIST OF ABBREVIATIONS AOC Alteration of Consciousness ANCOVA Analysis of Covariance BDI II Beck Depression Inventory, 2nd edition CAPS Clinician Administered PTSD Scale DoD Department of Defense EF Executive Functioning EOD Explosive Ordinance and Disposal FSIQ Full Scale Intelligence Quotient GED General Education Development test GLM General Linear Model IQ Intelligence Quotient LOC Loss of Consciousness MOS Military Occupat ion Specialty mTBI Mild Traumatic Brain Injury OEF Operation Enduring Freedom OIF Operation Iraqi Freedom PCL M Posttraumatic Checklist, military version PCS Postconcussive Symptoms PTSD Posttraumatic Stress Disorder TICV Total Intracranial Volume TSI Time Since Injury VA Veterans Administration
8 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science THE RELATIONSHIP BETWEEN PREDEPLOYMENT INTELLIG ENCE AND PTSD IN OEF OIF VETERANS WITH MILD TRAUMATIC BRAIN INJURY By Joseph M. Gullett May 2013 Chair: Russell M. Bauer Major: Psychology Posttraumatic Stress Disorder (PTSD) is a significant mental health concern for soldiers ret urning from the wars in Iraq and Afghanistan. There are several known risk factors for the development of PTSD in veterans, such a history of brain injury, younger age at deployment, and a low level of intelligence. Theories of cognitive reserve hypothesiz e that individuals with lower education and intelligence levels are at greater risk for clinical manifestations of dysfunction following brain injury. To evaluate this hypothesis, p re deployment military aptitude test results and post deployment cognitive and mood measures were obtained for 4 4 male veterans of Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) with a history of mild Traumatic Brain Injury (mTBI). We examined whether predeployment intellectual ability influenced the developm ent of post deployment PTSD. L ower predeployment intellectual ability was significantly associated with higher reported levels of post deployment PTSD after controlling for age, head injury frequency, time since injury, and depressive symptom reporting. U tilizing similar control s, low and high pre deployment intelligence groups differed significantly in their post deployment executive functioning performance, but increased PTSD reporting was not significantly related to post combat executive
9 functioning. However, veterans who experienced a decrease in intellectual functioning performance after deployment reported significantly higher levels of PTSD. These results suggest that lower predeployment intelligence can be a risk factor for the development of PT SD in this population, and that coping resources associated with higher order executive functioning may lead to an increased ability to manage the effects of trauma.
10 CHAPTER 1 INTRODUCTION Overview The American Psychiatric Association defines Posttraumatic Stress Disorder (PTSD) as the presence of unwanted intrusive thoughts of a traumatic event, the avoidance of stimuli associated with or numbing of memories from that event, and increased hyper arousal subsequent to the li fe threatening trauma ( American Psychiatric Association, 2000) The hostile environment to which deployed soldiers of Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) are exposed can be described as a hotbed for the development of PTSD symptoms. Prevalence rates of combat related PTSD in returning OEF/OIF veterans are estimated to fall between 5 and 20% ( Hoge et al., 2004; Milliken, Auchterlonie, & Hoge, 2007; Seal, Bertenthal, Miner, Sen, & Marmar, 2007) After returning from foreign wars, veterans with a diagnosis of PTSD are statistically more likely to be unemployed, to experience marital and familial discord, suicidal ideation, substance abuse and dependence, and to encounter problems learning in educational settings ( Karney, Ramchand, Osilla, Caldarone, & Burns, 2008) However, not all individuals develop psychological disorders following trauma. There are many risk factors for the development of PTSD, including childhood history of abuse or trauma, family hi story of psychiatric illness, a lower level of intelligence, and lack of education ( Brewin, A ndrews, & Valentine, 2000; Charuvastra & Cloitre, 2008; King, King, & Foy, 1996; Macklin et al., 19 98) An i ndividuals susceptibility to develop PTSD may be increased in those who have experienced direct combat exposure, or who have experienced a mild Traumatic Brain Injury during combat (mTBI; Brenner et al., 2010; Carlson et al., 2010;
11 Schneiderman, Braver, & Kang, 2008) The prevalence of mTBI (as opposed to death or more severe injury) has increased in recent wars as a result of improved body armor and advanced medical care, which has led to an increase in the woundedto killed ratio. In response to this increase in prevalence researchers have sought to determine factors which protect an individual from the longlasting effects of brain injury. This protective factor is often referred to as c ognitive r eserve, or the capacity of an individua l s brain to resist or overcome the effects of trauma and reduce the presence of dysfunction following an injury. Many studies have supported the theory of cognitive reserve, which hypothesizes that a combination of intellectual ability and level of education serve as a protective factor against the development of cognitive dysfunction subsequent to neurologic disease or injury ( Fay et al., 2010; Helmstaedter & Kockelmann, 2006; Kesler, Adams, Blasey, & Bigler, 2003; Scarmeas et al., 2003) PTSD Risk Factors PTSD is a major public health concern, and understanding the factors that influence its development is crucial for prevention and treatment efforts. It is estimated that the lifetime prevalence of PTSD in trauma exposed individuals is as high as 24%, and as high as 9% in the general population ( Feeny & Foa, 2005) The prevalence rate of PTSD in OIF/OEF veterans has been estimated to fall between 5 % and 20%, which is rough ly three to four times the prevalence in the general U.S. population ( Hoge et al., 2004; Seal et al., 2007) Furthermore, a recent large scale study of OIF/OEF veterans showed that incurring a mTBI doubles the risk for the development of PTSD ( Schneiderman et al., 2008) Several factors intrinsic to the individual and their home environment can i ncrease the risk of developing PTSD as a result of exposure to combat in a wartime situation, such as a family history of psychiatric illness, childhood
12 abuse and/or adversity, previous trauma history, lower intelligence, lack of education, and younger age at traumatic exposure ( Brewin et al., 2000; Charuv astra & Cloitre, 2008; King et al., 1996; Macklin et al., 1998 ) However, the factors present at the time of the trauma, or even afterward, are better predictors of the development of PTSD. These factors include concomitant life stressors, lack of social support, intelligence level, and trauma severity ( Brewin et al., 2000 ; McNally & Shin, 1995) There may even be a selection bias that predisposes military populations to develop psychiatric conditions at an increased rate after deployment, as one report found higher rates of reported childhood physical and sexual abuse in military populations ( Seifert, Polusny, & Murdoch, 2011) In military veterans exposed to wartime atrocities such as the death of comrades, brutal killing of men, women, and children, and the constant threat of attack resulting in bodily injury; the presence of risk factors predeployment can significantly increase the likelihood of developing PTSD. Therefore, the identification of known risk factors in military populations is a critical step in prevention efforts Cognitive Theories of PTSD Cognitive theories of emotion propose that a persons interpretation of a lifethreatening event is more important than the event itself in determining th e persons emotional and behavioral reaction ( Feeny & Foa, 2005 ) One recent study examined the cognitive factors related to preparedness for war and the perception of threat in 207 OEF/OIF veterans. The author found that the effect of a soldiers combat experience on the development of PTSD was highly dependent upon how that individual perceived threats in their environment ( Renshaw, 2011 ) Interestingly, some soldier s received specialized training prior to deployment which was intended to prepare them for the combat experiences they might encounter. This study found that this level of
13 preparedness for war was a significant moderator for how perceptions of threat related to PTSD levels. In other words, those veterans who reported being more psychologically prepared for war had levels of threat perception which matched their actual level of combat experience, whereas those soldiers who reported being unprepared for war had high levels of threat perception regardless of their combat experience. This suggests that there may be a need for a predeployment psychological intervention to better prepare soldiers for wartime combat situations. It also raises the question as to whether soldiers with more limited cognitive capaci ty prior to deployment are at increased risk for the development of PTSD due to decreased coping abilities. Another cognit ive theory of stress reaction has sought to integrate the effect that environmental and cognitive variables have on emotional outcomes in response to stress. Hobfoll proposed that the threat of the loss of one s resources is the main factor that drives the development of stress disorders ( Hobfoll, 1989) The author defines resources as personal characteristics (e.g. self esteem), objects (e.g. a home or car ), energies (e.g. time and money) and conditions (e.g. marriage) that a person obtains over their lifetime. Those individuals who are exposed to stressors or experience a trauma perceive that this event has threatened their cache of resources result ing in a negative psychological reaction. When conceptualizing the development of PTSD in this context, it becomes clear how individuals who are deployed to war, thousands of miles from nearly all of their resources, are at an increased susceptibility to develop ing stress reactions in response to their perceived loss of resources. Because ones intellectual ability is a general factor representative of the collective of experiences and resources obtained over the course of the lifespan, those with fewer resources upon deployment
14 to war (i.e. those with lower pre deployment intelligence) are likely to be susceptible to the development of a stress disorder such as PTSD. Cognitive R eserve Much like the theory of conservation of resources proposed, several theorists and researchers sought to describe cognitive reserve as a resource which can bolster an individual against the effects of a trauma. In the passive model of brain reserve capacity proposed by Satz, the cognitive sequelae of a brain injury would be manifested in an individual once the magnitude of injury reached that individuals inherent threshold ( Satz, 1993 ) Using a more active, neurobehavioral model of cognitive reserve, Stern postulated that the brain of an individual w ith high levels of education and IQ actively attempts to compensate for injury in a greater, more efficient manner than that of an individual with lower levels of education and IQ. This theory suggests that through reorganization of damaged neural networks the brain is able to recruit networks previously unused for that particular cognitive process prior to injury ( Stern, 2002) Whether cognitive reserve exists as an active or passive process has yet to be definitively proven through research. The common threads tying investigations of such theories together, however, appear to be that the experiences (education) and abilities (intelligence) of affected individuals are consis tently associated with cognitive performance and pathology following injury. A hallmark study in 1968 first proposed the concept of a cognitive reserve threshold in aging humans with dementia ( Blessed, Tomlinson, & Roth, 1968 ) The se researchers found that objective evidence of neurocognitive dementia symptom onset was not present in elderly individuals until damage to the brain reached 50100cc of volume, as measured by the sum of brain infarctions present on post mortem
15 histological examination. In the years to follow, many research studies have tested and supported the cognitive reserve hypothesis with brain injured populations Kesler and colleagues examined education and pre injury IQ as factors related to Total Intracranial (brain) Volume (TICV) and change in IQ following brain injury in a civilian population. The authors found that TICV was highly correlated with IQ, suggesting that those with higher TICV measurements had a higher level of brain reserve. They also found that decreases in post inj ury IQ from pre injury IQ were significantly greater for the low IQ group (FSIQ <90), suggesting that loss of function was greater in those with lower preinjury reserve ( Kesler et al., 2003 ) More recently, a longitudinal study of children and adolescents with mTBI confirmed the hypothesis that higher cognitive reserve, as measured by cognitive testi ng, is related to the presence of fewer Postconcussive Symptoms (PCS) following injury ( Fay et al., 2010 ) In the most technologically sophisticated investigation of cognitive reserve to date, Haute and colleagues investigated how Cognitive Capacity related to the organizational quality of white matter in the brains of young persons. The authors defined Cogni tive Capacity as a composite of WASI III FSIQ, achievement testing scores, and years of education. The structural quality of brain white matter was measured using Diffusion Tensor Imaging (DTI). They found that directional organization of white matter fibe rs was positively correlated with Cognitive Capacity after correcting for multiple comparisons, once again implicating the existence of a brain reserve related to an individuals intelligence and education levels ( Haut et al., 2007) Many researchers and theorists have suggested that an individuals acquired years of education is a meaningful and easily obtained proxy for Cognitive Reserve
16 ( Katzman, 1993) However, in a military population such as the one in the present study, this postulate may prove difficult as the overwhelming majority of individuals were deployed to combat with a high school diploma or GED equiv alent, and thus exhibit little variability in their level of education as a group. Therefore, a premorbid measure of intelligence would serve as the most appropriate measure of cognitive r eserve in this population. The R elationship b etween Intelligence an d PTSD Given the fact that an individuals experiences throughout their lifespan influence the level of intelligence they possess, it seems likely that the mental qualities afforded to persons with higher intelligence, such as coping skills, can assist in diffusing the effects of trauma. A recent metaanalysis found a small mean effect size (r=.18) for the relationship between intelligence and PTSD based on six studies with 1,149 participants ( Brewin et al., 2000) The relationship of intelligence as a protective factor for PTSD has been supported in numerous studies ( Gale et al., 2008 ; Gil, Calev, Greenberg, Kugelmass, & et al., 1990; Gilbertson, Gurvits, Lasko, Orr, & Pitman, 2001; Kr emen et al., 2007; Pitman, Orr, Lowenhagen, Macklin, & Altman, 1991; Vasterling, Brailey, Constans, Borges, & et al., 1997; Vasterling et al., 2002) and even in some studies after controlling for combat exposure ( Macklin et al., 1998; McNally & Shin, 1995; Wright, Cabrera, Eckford, Adler, & Bliese, 2012 ) Despite this abundance of research, little is known about specific cognitive factors that influence the relationship between predeployment intelligence as protective for post deployment emotional dysfunction after the occurrence of blast related mTBI. Individuals with lower global intelligence as measured by currently available intelligence measures may also exhibit weaker performance on tests of executive
17 functioning. E xecutive function ing refers to a set of complex, higher order, goal driven mental processes, including inhibition, planning, problem solving, initiation, cognitive flexibility, and self monitoring ( Lezak, Howieson, Loring, Hannay, & Fischer, 2004; Stuss & Alexander, 2000) One could reason that individuals with impairment in their ability to self monitor and problem solve as a result of lowered executive functioning ability may be at an increased risk for the development of psychological di sorders. Therefore, evaluating this component of mental functioning may provide important insight to the source of psychological dysfunction, as well as a potential area of intervention in those who are identified as being at risk. The Occurrence of Co morbid De pression & PTSD Post deployment Individuals diagnosed with PTSD in the general population are at an increased risk of developing co morbid conditions, such as depression. In fact, the National Comorbidity Study found that 88 percent of men and 79 percent of women who were diagnosed with PTSD had also been given another psychiatric diagnosis at some point in their lifetime ( Kessler, Sonnega, Bromet, Hughes, & et al., 1995 ) More germane to the current study, one investigation found that two thir ds of soldiers returning from the wars in Iraq and Afghanistan have been found to have co morbid PTSD and depression ( Karney et al., 2008) while other studies report comorbidit ies between 3.6% and 6.3% ( Grieger et al., 2006 ; Schell & Marshall, 2008 ) The diagnostic criteria for the two diagnoses are similar, with both requiring the presence of some combination of vegetative symptoms (increased or decreased sleep), numbing of emotions, loss of interest, anhedonia, restricted range of affect, irritability, anger, and difficulty concentrating. Wi th this in mind, some degree of comorbidity in research studies involving combat exposed populations is inevitable. Therefore, in studies which seek to
18 examine the effect of various factors on the development of PTSD, the presence of depressive symptoms is a factor that must be strongly considered before making theoretical or statistical conclusions. Co o ccurring PTSD and mTBI Evidence that PTSD and mTBI can exist jointly is becoming increasingly abundant. A diagnosis of PTSD requires that a lifethreatening trauma (or the perception thereof) must have been experienced, and the reexperiencing of that event is a central component of the disorder. According to the Veterans Administration (VA) and Department of Defense (DoD), a diagnosis of mTBI is based upon the experience of a traumaevent significant enough to produce a Loss of Consciousness (LOC) less than 30 minutes, Alteration of Consciousness (AOC; i.e., feeling dazed, seeing stars, or becoming momentarily disoriented) less than 24 hours, with posttraumatic amnesia for the event equaling less than 24 hours in duration ( VA/DoD, 2009 ) In light of these diagnostic criteria, some have argued that if a person is rendered unconscious and has amnesia for the event, they cannot truly develop PTSD. However, soldiers in the current wars in Iraq and Afghanistan often experience several instances of mTBI in theater, many of which are characterized strictly by AOC, means that the two disorders can be produced simultaneously. Furthermore, many of the experiences of these soldiers, such as the loss of a close friend in combat, occur independently of the events that produced mTBI in combat. As such, the veterans returning from these wars are at an increased risk for both PTSD and mTBI. Delineating the factors that affect the two phenomena is crucial to understanding their development.
19 Time Since Injury and Age at Injury In an extensive review of the neuropsychological sequelae of PTSD and TBI in OEF/OIF veterans, Dolan argued that accounting for Time Since Injury (TSI) and severity of TBI is crucial for researchers in who wish to make assumptions regarding the presence of neuropsychological and emotional dysfunction in brain injured veteran populations ( Dolan et al., 2012 ) One study suggests there may be evidence th at a younger age at injury is a factor that interacts with increased TSI to produce higher rates of post injury psychological symptom reporting ( Senathi Raja, Ponsford, & Schonberger, 2010) Another study determined that longer TSI in soldiers with PTSD was associated with reduced attentional abilities on neuropsychological investigation, and that age at injury was not a factor which affected the cognitive outcomes ( Marx et al., 2009 ) In light of the mixed findings in this area, considerable attention will be paid to TSI in the present study in order to account for the effects it may have on the generalizability of findings to the entire veteran population. Military Rank, Military Occupation Specialty & Loss of Consciousness Several research studies have determined that combat exposure is significantly related to PTSD symptom reporting and experiencing mTBI in veterans returning from Iraq and Afghanistan ( Karney et al., 2008 ; Tanielian, Jaycox, Schell, Marshall, & Vaiana, 2008 ) A soldiers combat exposure may possibly be related to their Military Operation Specialty (MOS). As one might exp ect, an Information Technology s pecialist is likely to have less combat exposure than an Explosive Ordinance and Disposal (EOD) technician, and in turn, fewer instances of LOC and AOC Due to the complexity of the MOS system and the wide variability present in this sample, MOS was not included as a possible confounding variable in the current study. As mentioned
20 previously, soldiers who experience mTBI develop PTSD at nearly double the rate of those who did not report experiencing mild TBI ( Schneiderman et al., 2008) Therefore, the number of reported LOC or AOC would serve as an appropriate proxy for combat exposure in this population. While research demonstrat es a clear association between pre deployment ability and post deployment psychological outcomes, little is known about the applicability of these findings to individuals deployed to the Iraq and Afghanistan conflicts. T he soldiers returning from these war s are experiencing unprecedented rates of survival after brain injury as a result of recent technological advances (e.g. Kevlar body armor), and as a result, a neuropsychologically unique population has arisen. Little is known about how the pre deployment experiences of these soldiers affect their post deployment cognitive and emotional outcomes, and whether or not there exists a component of cognitive functioning that can be altered to reduce psychological dysfunction post war. We hypothesize that the nega tive association between predeployment intellectual ability and post deployment psychological dysfunction seen in previous research will hold true in the current population. Additionally, we aim to identify a cognitive construct which can not only explain the variability between individuals with and without dysfunction post war, but which can also be a source of intervention for those who are at risk for the development of such dysfunction.
21 CHAPTER 2 METHODS Participants Participants were recruited as par t of a larger neuroimaging study of the effects of blast related mTBI on the white matter of the brain (VA RR&D Grant # B6698W). To be included in the imaging study, participants must have experienced an alteration or loss of consciousness as a direct resu lt of a blast while on active duty in Iraq or Afghanistan. Participants were excluded if they had a self reported or medically documented history of substance abuse (e.g. alcohol) neurological conditions (e.g. epilepsy), and brain abnormalities (e.g. tumor, stroke, visible white matter abnormalities). The presence of these criteria was established first through self report, neurological examination by the attending study physician (DBF), followed by medical record confirmation of known conditions. Participant accounts of their blast history were also confirmed through medical record review, where possible. All participants were required to be MRI safe, and must have passed the impl icit or embedded effort measures given as part of a full length neuropsychological battery administered by a trained psychometrician according to a standardized protocol. As the neuropsychological tests em ployed in this study utilize native English speaking normative samples, participants must also have been native English speakers. This requirement avoid ed the possibility of confounding results of the neuropsychological test interpretation, especially on language and verbal memory based tests. Those who w ere included in the study were retrospectively contacted after their initial participation by the primary author (JMG) in order to obtain written consent to collect ASVAB scores (which serve as a proxy for general intellectual ability; see below)
22 from the Department of Defense. Of the 54 eligible participants in the larger study, 44 respondents gave written consent to collect ASVAB data, and were included in the final analysis for the current study. The participant population was comprised of 44 enlisted m ale OEF/OIF veterans with an age range of 24 to 49 (m: 32.02, SD : 5.77) and an average education level of 12.11 years (SD : .935). Females were not specifically excluded; however those few who did qualify and participated in the study were later disqualifi ed as a result of exclusionary criteria discoveries (e.g. brain abnormalities, failed effort testing). A breakdown of all demographic variables is included in Table 21. Cognitive Measures The A rmed S ervices V ocational A ptitude B attery (ASVAB) is administered to all military personnel prior to enlistment either in pencil and paper fashion, or as a Computerized Adaptive Test (CAT). As such, it is not administered to those who enter the military as officers. The results of the ASVAB are used, in conjunction with other criteria for the selection of applicants for enlistment into the Armed Forces and the classification of those accepted as recruits ( Brannick, 1990, p. 16 ) The ASVAB is comprised of several subtests that are combined to create composite scores, such as the Armed Forces Qualification Test ( AFQT ) and the General Technical (GT) score. The AFQT composite is a percentile score that is used by all four main branches of the U.S. military to provide a measure of general trainability of applicants accepted f or enlistment ( Brannick 1990, p. 24) Because of the academic nature of the subtests comprising the AFQT, including Arithmetic Reasoning, Paragraph Comprehension, Word Knowledge, and Mathematics Knowledge; its utility as a measure of IQ has been evaluated by several researc hers. The AFQT has been determined to be as psychometrically sound as any widely
23 available IQ measure at predicting general factors of intelligence, and in most cases, it performs better ( Herrnstein & Murray, 1994 ) Herrnstein and Murray (1994) demonstrated that in multivariate analyses of bot h military populations and participants from the National Longitudinal Survey of Youth (NLSY), the AFQT consistently correlated higher with other measures of intelligence more than those other measures of intelligence did with one another. Other researcher s have found that the AFQT was strongly associated with crystallized measures of intelligence predicting as much as 32% of the variance in WAISIII Vocabulary and Informat ion scores, WRAT 3 Reading ability and N A ART Full Scale IQ. Additionally, the AFQT was partially associated with several fluid measures of intelligence (WAIS III Digit Symbol Coding and Block Design, Trails B; Kennedy, Kupke, & Smith, 2000; Poppen & Southwell, 2003) which explained 20% of the variance in AFQT scores Another group of researchers a lso found the AFQT subscale of the ASVAB to correlate very highly (r=.92) with the Multidimensional Aptitude Battery (MAB), an instrument used to measure intelligence very similar to the WAIS. The authors created a regression equation that allowed them to reliably predict a persons MAB Full Scale IQ from their ASVAB AFQT score ( Orme, Brehm, & Ree, 2001) Thus, several research investigations have determined that the AFQT serves very well as a measure of premorbid intelligence in s oldiers needing to undergo a neuropsychological evaluation in the Veterans Affairs system. Several neuropsychological measures were administered to participants as part of the larger study. The National Adult Reading Test ( NART; Nelson, 1982) is a 50 item word list widely used in practice and research in order to estimate premorbid intellectual ability. It has been found to correlate highly with traditional
24 neuropsychological measures of IQ, such as the WAIS III and WAIS R ( Crawford, Parker, Stewart, & Besson, 1989 ; Mathias, Bowden, & Barrett Woodbridge, 2007; Willshire, Kinsella, & Prior, 1991) and has even been shown to accurately predict pre injury IQ after head injury ( Moss & Dowd, 1991) As this test is predominantly based upon verbal sk ills, its ability to predict pre morbid intelligence may be limited to instances in which it is compared to a measure with a verbal component, such as the AFQT. Another test which participants in the larger study received was the Adaptive Digit Ordering T est (DOT A). This test requires participants to organize a list of seven randomly presented digits into increasing order. Research on the DOT A has determined that this test is sensitive to frontal lobe dysfunction in patients with Parkinsons disease as w ell as frontal lobe damage ( Werheid et al., 2002) Additionally, participants were administered the Trail Making Tests ( TMT A, TMT B; Reitan, 1958) according to standard administration procedures. Of particular interest for the current study was TMT B, which has been found to be particularly sensitive to frontal executive dysfunction in a wide variety of populations ( Arbuthnott & Frank, 2000; Periez et al., 2007; Stuss et al., 2001) Lastly, the Controlled Oral Word Association Test ( Benton, 1967) was administered to participants in standardized fashion. While the test was originally designed to assess verbal fluency in aphasia, research has determined that frontal lobe functioning play s a large role in the ability of patients to perform this task ( Brooks, Fos, Greve, & Hammond, 1999; Raskin, Mateer, & Tweeten, 1998; Raskin & Rearick, 1996)
25 Self Report Measures The Posttraumatic Checklist Military (PCL M) is a 17item self report measure used by researchers and clinicians to assess the likelihood in which problems and complaints associated with PTSD are present in military populations. The PCL M has been validated with the Structured Clinical Interview for the DSM IV TR (SCID), and has been reported to have high test retest reliability, internal consistency, and convergent and discriminant validity ( Bliese et al., 2008; Pratt, Brief, & Keane, 2006) The PCLM is based on the criteria for diagnosing PTSD set forth in the DSM IV ( Weathers, Huska, & Keane, 1991 ) however the specific scoring method for diagnosing PTSD with this instrument varies across research studies Using the symptom cluster method of scoring the PCLM ( Brewin, 2005 ) a diagnosis of PTSD may be warranted in participants who endorse a symptom rating of 3 out of 5 on at least one re experiencing symptom, two arousal symptoms, and three avoidance symptoms ( Weathers & Ford, 1996) This particular scoring method has produces a sensitivity of 1.00 and specificity of 0.92, signifying that all cases of PTSD we re correctly identified and eight percent of cases were misdiagnosed as having the disorder ( Manne, Du Hamel, Gallelli, Sorgen, & Redd, 1998 ) Another method used to identify cases of PTSD using the PCLM involves totaling the responses for all 17 items, and identifying cases of PTSD as those who scored over 50 ( Andrykowski, Cordova, Studts, & Miller, 1998; Weathers & Ford, 1996). This scoring method, while less involved than the method previously described, has slightly higher specificity (0.99) but lower sensitivity (0.60) and tends to lack the PTSD identification ability of the symptom cluster method. All participants in the current study had been given a clinical diagnosis of PTSD in the Veterans Affairs system prior to inclusion. For the purposes of regression analyses in this study, the PCLM total score
26 was utilized as a continuous variable, with no cut off scores or individual r esponse criteri a being applied. When performing group based comparisons, various methods were examined for their ability to classify participants with PTSD. In the current study, the PCLM possessed high internal consistency with Cronbachs alpha equal to 0.94. The Beck Depression Inventory, 2nd Edition (BDI II), is a selfreport measure used to assess depressive symptoms in adults ( Beck, Steer, & Brown, 1996 ) T he BDI II is comprised of 21 items related to depressive symptoms that correspond to the diagnostic criteria for depression listed in the DSM IV. The BDI II has been validated with the Structured Clinical Interview for DSM IV ( SCID; Sprinkle et al., 2002) and has been shown to have strong reliability in clinical populations ( Ambrosini, Metz, Bianchi, & Rabinovich, 1991; Storch, Roberti, & Roth, 2004) High levels of PTSD and depressive symptoms have been reported in populations returning from Iraq and Afghanistan ( Ramchand, Karney, Osilla, Burns, & Caldarone, 2008 ) therefore this measure has been included to determine the extent to which the two psychological phenomena can be independently accounted for in the current study. In this study, the BDI II demonstrated high internal consistency with Cronbachs alpha of 0.94. Procedure Statistical analyses were perf ormed using IBM SPSS Statistics v20.0 statistical software A linear regression was performed to determine the amount of variance in PTSD symptom reporting that could be accounted for by predeployment intellectual ability as measured by the AFQT percentile score, controlling for age and frequency of head injury during combat. As the AFQT score is highly correlated to general intellectual ability, education was not cont rolled for as it is presumed to be a proxy of intelligence. Furthermore, given that the acquired level of education in this sample had a highly
27 modal distribution (12 years); this variable was proven in a cursory analysis to be statistically unsuitable as a controlling variable due to its highly kurtotic nature. Composite variables have been found to be more stable and reliable representations of a cognitive construct, specifically Executive Functioning ( EF; Salthouse, Atkinson, & Berish, 2003 ) According to Salthouse and colleagues, the creation of a composite variable serves to simplify analyses by allowing variables with different units of measurement to be analyzed simultaneously. This procedure additionally allows for the reduction of variables introduced into the statistical model, which is import ant in studies with a relatively small number of participants. In the current study, three cognitive variables (TMT B, COWAT, and DOT A) designed to measure EF performance were highly correlated with one another, thus suggesting they measured the same cognitive construct. An EF composite score was created in SPSS by computing zscores for each participant on each of the three tests, and averaging these z scores. For the purposes of psychometric consistency within this composite creation procedure, TMT B elapsed time scores were inverted so that the participant with the longest elapsed time to completion in this sample had the lowest score, and vice versa. High and low intelligence groups were created using a meansplit procedure in which veterans with AFQT percentile scores at or above the mean for the sample were assigned a value of 1, and those with AFQT percentile scores below the mean were assigned a value of 0. For the participants in the study who had complete data, this procedure resulted in one group of 22 veterans at or above the mean, and another group of 22 veterans below the mean of the entire sample. Utilizing the EF composite variable, Analysis of Covariance (ANCOVA) was performed to determine whether
28 participants with high versus low AFQT scores varied in their EF performance after controlling for demographic variables thought to affect EF, such as age and the presence of LOC It should be not ed that two veterans in the sample did not have complete data for the neuropsychological battery and were therefore excluded from analyses involving the EF composite. Statistical investigation of these two participants revealed that they were Missing Compl etely at Random (MCAR), meaning their missingness was not related to a statistically identifiable factor (Littles MCAR chi square = 2.537, df = 1, p = .11) Therefore, the se missing participants exclusion was not likely to affect the validity of analyses.
29 Table 2 1 Participant demographics (N = 44) Mean Standard Deviation Age a 32.02 5.77 Time since Injury b 4.60 2.07 Education c 12.11 .935 LOC d 1.11 1.21 AOC d 3.33 3.24 AFQT 61.17 20.00 PCL M e 56.50 15.89 BDI II 23.31 12.58 EF Composite f 0.00 0 80 Note. All participants were classified as incurring at least one mild Traumatic Brain Injury (AOC or LOC). a Current. b Years. c Completed years at deployment. d Frequency. e Percentile. f N = 42
30 CHAPTER 3 RESULTS All examined variables in the current dataset met General Linear Model (GLM) normality requirements for skewness and kurtosis. For all ANCOVA analyses, Levenes test for the inequality of variances was non significant, confirming that the GLM assumption he ld true. Additionally, factor interaction models were tested for each GLM based analysis to confirm the homogeneity of regression assumption. In order to determine whether the AFQT could be used as a valid measure of premorbid intellectual ability in this sample, Pearson correlations were performed to compare participants predeployment intelligence (AFQT) to their post deployment premorbid intelligence estimate ( NART ) Results indicate that the AFQT was highly correlated with post deployment NART scores (r = 0.67, p<.01; Table 3 1). Given that the psychometric properties of these two intelligence tests are very distinct, this strong positive relationship should not be over interpreted to imply the absence or presence of change in intelligence post de ployment. To evaluate such changes a difference score was created by putting the scores from these two intelligence estimates into a common z score metric and subtracting post deployment from predeployment z scores. This procedure results in an IQ change score, which could in turn be used to examine the hypothesis of whether reported PTSD symptoms are associated with a decline in intellectual ability ( Macklin et al., 1998) A linear regression was employed to examine whether a relationship existed between IQ change scores and PTSD reporting. Careful consideration of correlational analyses revealed a strong positive statistical relationship between reported levels of PTSD on the PCLM and depression on the BDI I I (r = 0.64, p<.01; Table 31). By
31 controlling for depressive symptoms in this r egression model, the unique contribution of IQ change to PTSD beyond that of reported depression was examined. A proxy of combat exposure (LOC) was also included as a controlling variable in this model as combat exposure was thought to have a positive line ar relationship to the presence of PTSD. Additionally, age and Time Since Injury were controlled for in this analysis. Results indicate a strong relationship between IQ change scores and PTSD symptom reporting [F( 5,43)=7. 89, p < .001 ], with the overall model accounting for 51. 0 % of the variance in symptoms. The direction of this relationship was such that those veterans who reported higher levels of PTSD experienced larger declines in IQ score. More specifically, for each standard deviation reduction in the IQ change z score, veterans scored 5 07 points higher on the PCLM. The results of this analysis suggest that the prolonged presence of PTSD post combat was related to a relative reduction in intellectual functioning as measured by these two IQ estimates (See Table 32). An additional linear regression examined whether the AFQT could be used to account for post deployment PTSD reporting on the PCLM. As previously mentioned, a strong positive relationship exist ed between PTSD and depressive symptom repor ting in the current sample data, and the unique contribution of PTSD beyond that of depression was examined in this regression model. Results indicate that the AFQT account ed for an additional 12% of unique variance in PTSD reporting after controlling for age, TSI, LOC frequency, and depressive symptom reporting. The addition of the AFQT in step three of the regression model resulted in a highly significant F change over step two [ F ( 1,38) = 10.89, p = .002]. The full model exceeded the specified .05 significance level, F (5,38) = 10.1, p = .000, and explained 57% of the total variance in
32 PTSD reporting on the PCLM in this sample. It was found that the AFQT significantly predicted repo rted levels of PTSD such that those with lower AFQT scores tended to report higher levels of PTSD ( = .38, p<.01). Examination of unstandardized beta coefficients revealed that for each percentile decrease in AFQT score, a three point increase in PTSD was reported on the PCLM after accounting for controlling variables. Additionally, BDI II depression reporting significantly predicted PTSD such that those reporting higher depression also reported higher PTSD ( = .70, p<.01). For each one point increase i n PTSD reported, nearly a full point increase in BDI II depression reporting was observed upon examination of beta coeffici ents in this model (See Table 3 3). Full factorial ANCOVA was employed to determine whether veterans with below average pre deployment intelligence differed from those with above average predeployment intelligence in their post deployment EF composite scores. By controlling for the variables age and frequency of LOC, the ability of the AFQT to predict unique variance in PTSD reporting was examined in the context of participants EF performance. The results described in Table 3 4 show that low and high intelligence groups significantly differed in the EF composite scores, indicating a significant main effect for pre deployment intelligence level after controlling for age and frequency of 2 = .10]. The age covariate was not significantly related to 2 = .05], nor was frequency of LOC [ F (1,39) = 0.01, p>.05, 2 = .00]. Planned cont rasts further confirmed that veterans having below mean intelligence had significantly lower EF composite scores [p=.045, 95% CI ( 1.20, 0.01)] compared to veterans with above mean intelligence. Consideration of post hoc ANOVA
33 results revealed that the EF composite scores of the below average intelligence group (M = 0.32, SD = 0.86) were significantly lower than the above average intelligence group (M = 0.31, SD = 1.05). It is important to note that the EF composite correlated significantly with the pre d eployment IQ estimate ( AFQT; r=.41, p=.008) and with the post deployment premorbid IQ estimate ( NART; r=.54, p=.000), and this relationship was stronger than th at of the individual components o f the EF composite (See Table 31). This suggests that the EF composite may represent a strong cognitive construct which is a b i product of intellectual functioning itself. Given the association between EF and predeployment intelligence on the AFQT, a linear regression was performed to determine whether current EF performance is associated with PTSD above and beyond that which can be attributed to pre deployment intelligence. By controlling for pre morbid intellectual ability on the AFQT, the association between current EF and PTSD was examined to determine if prolonged exposure to PTSD symptoms was related to EF performance. The full model exceeded the .05 significance level, F( 6 41) = 8 45, p < 001 and explained 59.2 % of the total variance in PTSD symptom reporting. However, the significance of this model can be solely attributed to the association between the AFQT and PTSD reporting, as EF did not provide a significant contribution in explained varianc e in PTSD symptoms above and beyond that of the AFQT. T he results of this analysis suggest that prolonged presence of PTSD symptoms post combat is not related to EF performance (See Table 3 5) .
34 Table 3 1 Intercorrelations between cognitive and emotional f unctioning m easures for veterans (N = 44) Measure 1 2 3 4 5 6 7 8 1. PCL M .64** .38* .12 .10 .09 .10 .14 2. BDI II .64** .10 .12 .28 .03 .16 .26 3. AFQT .38* .10 .28 .34* .67** .32* .41** 4. COWA a .12 .12 .28 .38* .32* .37* .74** 5. DOT A a .10 .28 .34* .38* .49** .47** .79** 6. NART a .09 .03 .67** .32* .49** .46** .54** 7. TMT B ab .10 .16 .32* .37* .47** .46** .79** 8. EF composite a .14 .26 .41** .74** .79** .54** .79** a N=42, b Scores recorded as total time elapsed to completion. *p < .05. **p < .01.
3 5 Table 3 2 Summary of regression analysis for IQ change score predicting PTSD reporting in v eterans (N=44) Variable B SE B Step 1 Age 0.06 0.38 0.02 Time Since Injury 0.25 0.94 0.03 LOC 2.41 1 65 0.18 BDI II 0.7 8 0.1 6 0.6 2 ** Step 2 Age 0.00 0.37 0.00 Time Since Injury 0.70 0.92 0.09 LOC 2.05 1. 59 0.16 BDI II 0.74 0.1 6 0.59** IQ Change 5 07 2. 31 0.2 6 Note. R2 2 = .51 for Step 2 (ps < .05). IQ Change is the NART z score subtracted from the AFQT z score. *p < .05. **p < .01. Table 3 3 Summary of regression analysis for AFQT p redicting PT SD reporting in veterans (N = 44) Variable B SE B Step 1 Age a 0.76 0.44 0.27 LOC b 4.07 2.01 0.31* Time since Injury c 0.44 1.17 0.06 Step 2 Age a 0.06 0.38 0.02 LOC b 2.41 1.65 0.18 Time since Injury c 0.25 0.94 0.03 BDI II .784 .164 0.62** Step 3 Age a 0.99 0.34 0.04 LOC b 2.22 1.48 0.17 Time since Injury c 1.18 0.89 0.16 BDI II 0.77 0.15 0.70** AFQT 0.30 0.09 0.38** Note. R2 2 = .32 for Step 2 (ps < .02 = .12 for Step 3 (ps < .05). a Current. b Frequency. c Years *p < .05. **p < .01.
36 Table 3 4 Analysis of covariance for d ifferences in executive f unctioning by AFQT (N=44) Executive Functioning Composite Score Variable df F 2 p Age a 1 1.85 0.05 .18 LOC b 1 0.00 0.00 .96 AFQT 1 4.28* 0.10 .04 Error 39 (36.04) a Current, b Frequency Table 3 5 Summary of regression analysis for executive f unctioning c omposite predicting PTSD reporting in v eterans (N=42) Variable B SE B Step 1 Age 0.07 0.40 0.02 Time Since Injury a 0.22 0.99 0.03 LOC b 2.3 7 1. 71 0.1 8 BDI II 0. 79 0.1 7 0.62 ** Step 2 Age 0.08 0.35 0.03 Time Since Injury a 1.09 0.93 0.14 LOC b 1.99 1. 51 0.15 BDI II 0.8 1 0.1 5 0.64 ** AFQT 0.35 0.10 0.44** EF Composite 2.44 1.98 0.15 Note. R2 2 = .5 9 for Step 2 (ps < .01 ). EF composite is for TMT B, COWAT, and DOT A a Years. b Frequency. *p < .05. **p < .01.
37 CHAPTER 4 DISCUSSION Although a large proportion of combat exposed veterans do not develop PTSD, it is important from a prevention and intervention standpoint to identify the psychological and cognitive variables that are associated with an increased risk of developing PTSD. The current study sheds light on several factors that influence the development of PTSD after deployment to war, specifical ly pre morbid intellectual ability. Results of this study indicate a strong negative relationship between veterans pre deployment intellectual functioning and their post deployment emotional functioning such that those veterans with lower intellectual functioning reported higher levels of post deployment PTSD. This relationship remained after controlling for several salient individual factors, and appeared to be minimally affected by the experience of combat incurred m TBI. While mTBI cannot be ruled out as a factor influencing the development of PTSD, the current study suggests that cognitive functioning at the time of deployment has a strong influence on the development of emotional and cognitive functioning in the context of mTBI. These findings are consi stent with the Cognitive Reserve hypothesis, which has been demonstrated in past studies by which intelligence had a strong negative relationship to emotional ( Brewin et al., 2000 ; Gale et al., 2008; Gil et al., 1990 ; Gilbertson et al., 2001 ; Kremen et al., 2007; Macklin et al., 1998; McNally & Shin, 1995; Pitman et al., 1991; Vasterling et al., 1997; Vasterling et al., 2002; Wright et al., 2012) and cognitive functioning ( Haut et al., 2007; Kesler et al., 2003 ) This relationship between intelligence and emotional functioning after war points to the need for the clarification of the modifiable components of intellectual functioning that are involved with protection against psychological dysfunction post trauma.
38 One of the possible modifiable components of intellectual ability after trauma is E xecutive F unctioning ( EF; Cicerone, Levin, Malec, Stuss, & Whyte, 2006 ) w hich refers broadly to the functions associated with the frontal lobe systems of the brain. These functions include self monitoring and awareness, initiation and susta ined attention, inhibition, cognitive flexibility, and problem solving ( Stuss & Alexander, 2000 ) Many of these functions can be adversely affected by both mTBI and PTSD, and are therefore a viable target for intervention efforts. The results of the current study suggest that individuals with AFQT scores above the mean for the sample had higher post co mbat EF performance than those with AFQT scores below the mean of the sample. However, this finding may indicate that EF is simply a product of intellectual ability and general brain function itself, as further analysis determined that EF did not explain a dditional variance in PTSD symptoms above and beyond that of the pre deployment intelligence estimate (AFQT). While EF performance was not associated with PTSD beyond its relationship with general intelligence, it is possible that veterans who have a hist ory of mTBI experience a decrease in general intellectual functioning post deployment. To test this hypothesis we created an IQ change score, which was simply the difference in standardized z scores between pre and post deployment IQ estimates. This allowed us to determine which veterans had a reduction in performance on the IQ estimates from preto post deployment. Statistical analysis determined that the re was a significant relationship between IQ change and severity of PTSD such that those veterans who h ad decreased intellectual functioning (NART) compared to the precombat AFQT reported significantly higher symptoms of PTSD These results suggest the possibility
39 that certain individuals possess cognitive attributes which allow them to better withstand tr auma than others. Thus, the Cognitive Reserve hypothesis hold s true in this veteran population, and higher intelligence prior to exposure to combat appears to be associated with better cogn itive and emotional functioning post combat. Limitations, considerations, and future d irections : Previous comparisons of the PCLM and the BDI II in their ability to identify PTSD suggest that both instruments may be tapping generalized distress rather than specific aspects of the disorder ( Arbisi et al., 2012 ) Some authors note that reported depressive and PTSD s ymptoms often overlap in military populations in the acute readjustment period after deployment ( Arbisi et al., 201 2 ; Tsai, Pietrzak, Southwick, & Harpaz Rotem, 2011) We believe that in this study we were able to distinguish reported PTSD symptoms from reported depressive symptoms due to the fact that our participants were seen in a time period, on average, beyond the acute post deployment period than participants in these previous studies (M = 55.2 months) In previous research ( Grieger et al., 2006; Karney et al., 2008; Schell & Marshall, 2008) as well as in the current study, depressive symptom reporting was h ighly correlated with PTSD symptom reporting. In this study, the association between change in intellectual functioning from preto post combat and PTSD was examined. It was found that post combat PTSD was significantly related to a pre to post combat reduction in measured intellectual functioning. This general relationship was found when utilizing a wordlist estimate of IQ (NART) as the post combat outcome measure. Additionally, accounting for age, Time Since Injury, depressive symptoms and a proxy of com bat exposure (LOC) reduced the unexplained variance in PTSD symptom
40 reporting, resulting in a significant negative association between PTSD and measured intelligence change. A significant proportion of the lowered performance on neuropsychological testing measured in the current study can be attributed to the presence of increased levels of prolonged post combat PTSD. In a similar investigation, Macklin and colleagues found that after controlling for combat exposure, no significant association existed between intelligence change and PTSD ( Macklin et al ., 1998 ) It is possible that this 1998 study failed to find a significant association between pre to post deployment intelligence change and PTSD as a result of a failure to account for concurrent depressive symptoms in participants with PTSD. Alternat ively, it is also possible that the self report measure of PTSD employed in the present study had reduced diagnostic accuracy compared to the Clinician Administered PTSD Scale (CAPS) used in the Macklin study. Some authors have found that factors such as s ocial support and psychological resilience protect against the development of PTSD in OEF/OIF veterans ( Pietrzak, Johnson, Goldstein, Malley, & Southwick, 2009) It is possible that including these factors in the prediction model woul d have mitigated t he ability of the AFQT to pr edict PTSD symptom reporting. However, due to the fact that cognitive reserve and intelligence tend to be higher in those with home environments with strong familial bonds and social support, it is possible tha t the pre deployment AFQT accounts for much of the same variance that psychological resilience accounted for in the 2009 Pietrzak study. Individuals of higher intelligence may possess certain strengths which allow them to earn higher military rank or obtai n a more desirable MOS during their time in service.
41 As such, it is possible that military rank and MOS are factor s which can affect the results of research in this field. Because of the limited sample size of this study, military rank and MOS were not ex amined as possible influencing factor s for or against the development of cognitive or emotional dysfunction and may be a limiting factor to the current findings Preliminary investigation suggested that rank and MOS may be associated with combat exposure (LOC), which in turn may affect the development of cognitive and emotional dysfunction post deployment. Future studies in this area of research should more directly evaluate the possibility that these factors are associated with post deployment cognitive and emotional outcomes A final implication of the current results is that, if predeployment intelligence is a risk factor for development of PTSD, it may serve as a basis for targeting particular troops for predeployment preventative interventions designed to build resistance, increase psychological preparedness for war, and provide stress inoculation with the goal of reducing or preventing the development of combat related PTSD in this population. The viabilit y of such a preventative approach has not been investigated but would be a fruitful avenue for future research.
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51 BIOGRAPHICAL SKETCH Joseph Gullett received his Bachelor of Science degree in p sychology (Cum Laude) from the University of Florida in 2008. As an undergraduate, he worked as a research assistant under the guidance of Dr. Michael Marsiske in the D epartment of Clinical and Health Psychology. He maintained a relationship with the CHP faculty after earning his degree when he began endeavors with clinical populations as a psychometrician at the University of Florida Psychology Clinic. During the time since his undergraduate study Joseph has presented several independent research projects at international conferences, and has also written a first author publication on the clinical utility of a modified neuropsychological test for use in Parkinsons disease patients. A short time later, h is research focus evolved into the study of Diffusion Tensor Imaging of brain injured veterans at the Malcom Randall VA under the mentorship of neurologist David B. FitzGerald, MD. It was during the development and implementation of this research stu dy while also continuing clinical work at the Psychology Clinic that Mr. Gullett received an offer to begin work as a graduate student in the D epartment of Clinical and Health Psychology under the mentorship of Dr. Russell Bauer.