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Driving Impairments Associated with Depressive Symptomatology DRIVING IMPAIRMENTS ASSOCIATED WITH DEPRESSIVE SYMPTOMATOLOGY A thesis submitted to Kent State University in partial fulfillment of the requirements for the degree of Master of Arts by Vivek Venugopal August, 2009 Thesis written by Vivek Venugopal B. A., Ohio Wesleyan University, 2004 M. A., Kent State University, 2009 Approved by Jeffrey A. Ciesla, Ph.D. Advisor Douglas L. Delahanty, Ph.D. Interim Chair, Department of Psychology Timothy Moerland, Ph.D. Dean, College of Arts and Sciences ii TABLE OF CONTENTS LIST OF TABLES iv LIST OF FIGURES vi ACKNOWLEDGMENTS vii INTRODUCTION…………………………………………………………….. 1 METHOD………………………………………………………………........... 13 Participants…………………………………………................. 13 Procedures………………………………………….................. 13 Measures…………………………………………..................... 14 Neuropsychological Tests.…………………............................. 16 Driving Task……………..…………………............................. 17 RESULTS……………………………………………………………………... 21 DISCUSSION………………………………………………………………… 45 REFERENCES………………………………………………………………... 52 iii LIST OF TABLES TABLE 1………..……………………………………………………………….. 6 THE FOUR MODES OF ATTENTIONAL PROCESSING OUTLINED IN TRICK ET AL. (2004) TABLE 2………………………………………………………………............... 12 HYPOTHESES TESTED IN THE PRESENT STUDY TABLE 3………………………………………………………………………... 14 SAMPLE CHARACTERISTICS TABLE 4………………………………………………………………………… 18 A DESCRIPTION OF THE EVENTS/OBSTACLES A DRIVER ENCOUNTERS IN THE K-MADS TABLE 5………………………………………………………………………… 22 DEPRESSION, RUMINATION, SLEEP QUALITY, AND NEUROPSYCHOLOGICAL TESTS TABLE 6………………………………………………………………………… 24 CORRELATIONS AMONG DEPRESSION, SLEEP QUALITY, RUMINATION, AND NEUROPSYCHOLOGICAL TESTS TABLE 7………………………………………………………………………… 25 CESD SCORES PREDICTING PERFORMANCE ON THE TMT-B AND LNS (OLS REGRESSION) TABLE 8………………………………………………………………………… 26 CESD SCORES PREDICTING PERFORMANCE ON THE TMT-A, GPT-A, AND GPT-B (OLS REGRESSION) TABLE 9………………………………………………………………………… 28 RSQ SCORES PREDICTING PERFORMANCE ON THE TMT-B AND LNS (OLS REGRESSION) iv TABLE 10………………………………………………………………………… 29 RSQ SCORES PREDICTING PERFORMANCE ON THE TMT-A, GPT-A, AND GPT-B (OLS REGRESSION) TABLE 11………………………………………………………………………… 30 DRIVING PERFORMANCE TABLE 12………………………………………………………………………… 31 CORRELATIONS AMONG THE VARIOUS DRIVING VARIABLES AND NEUROPSYCHOLOGICAL TESTS TABLE 13………………………………………………………………………… 32 PREDICTING REACTION TIME BASED ON NEUROPSYCHOLOGICAL ABILITIES (OLS REGRESSION) TABLE 14………………………………………………………………………… 34 PREDICTING AVERAGE LANE DEVIATION BASED ON NEUROPSYCHOLOGICAL ABILITIES (OLS REGRESSION) TABLE 15………………………………………………………………………… 36 PREDICTING AVERAGE SPEED DEVIATION BASED ON NEUROPSYCHOLOGICAL ABILITIES (OLS REGRESSION) TABLE 16………………………………………………………………………… 43 PREDICTING NUMBER OF CRASHES BASED ON NEUROPSYCHOLOGICAL ABILITIES (GzLM REGRESSION) TABLE 17………………………………………………………………………… 44 PREDICTING DRIVING PERFORMANCE BASED ON RSQ SCORES TABLE 18………………………………………………………………………… 47 NEUROPSYCHOLOGICAL TEST SCORES AND AGE-REFERENCED NORMS v LIST OF FIGURES FIGURE 1………………………………………………………………............... 39 HISTOGRAM OF THE NUMBER OF CRASHES VARIABLE FIGURE 2………………………………………………………………............... 40 THE NUMBER OF CRASHES VARIABLE AND EXAMPLES OF POISSON DISTRIBUTIONS vi Acknowledgments The love, support, and guidance of many parties have contributed to the successful completion of this project. First and foremost, I thank my supervisor, Dr. Hughes, for granting me the opportunity to participate in such an innovative and exciting research endeavor. The levity and optimism of his mentorship provided all the encouragement and reassurance I needed to overcome the many practical and technical challenges of this study. I also extend my gratitude to my advisor, Dr. Ciesla, under whose warm and able tutelage, I discovered my love for scientific inquiry. Our numerous meetings and discussions equipped me not only with many tools for research, but also a fond and intricate appreciation of their utility. Hearty thanks are due to Dr. Gunstad for sharing his wealth of technology with our team; his generosity afforded this project a new and competitive edge. I have learnt from all three of these distinguished researchers, but far less than I could have. I must also acknowledge my lab-mates, Katie Horsey, David Kalmbach, and Laura Reilly, for their kind review of this manuscript. Finally, I wish to express my eternal gratitude to my parents, Rajee Venugopal and V. G. Pillai. Their love gave me the courage to dream. vii INTRODUCTION Over six million motor vehicle accidents and over 40,000 fatalities have occurred in the U.S. every year since 1993 (Research and Innovative Technology Administration, 2008). A majority of these accidents are caused by human factors such as failure to attend to appropriate stimuli while driving (Trick, Enns, Mills, & Vavrik, 2004; Recarte & Nunes, 2000; Rumar, 1990). A government report based on police records, baseline data, general population surveys, and onsite technician reports of over 2000 accidents concluded that human factors such as inattention and internal distraction were the direct cause of accidents in at least 64% of the cases, and the probable cause in 90 – 93% of the cases (Treat et al., 1979). Given that depression causes impairments in neuropsychological abilities such as attention, individuals with depression have received research consideration in recent years as a potential risk group for motor vehicle accidents. However, the extant literature on depression-related driving impairment is limited not only in volume but also in scope. Most studies do not focus on the independent effects of depression on driving capability, but instead on the effects of anti-depressant medication on driving (Brunnauer et al., 2006; Wingen, Ramaekers, & Schmitt, 2006; Wingen, Bothmer, Langer, & Ramaekers, 2005; Ramaekers, 2003; Gerhard & Hobi, 1984). Other studies identify individuals with depression as a high risk group for motor vehicle accidents based on epidemiological data or survey methods (Wilson & Jonah, 1988; Donovan & Marlatt, 1982; Schmidt, Shaffer, 1 2 Zlotowitz, & Fisher, 1977; Selzer, Rogers, & Kern, 1968), though most of these studies are either dated or fail to extricate driving impairments on account of depression-related neurological deficits from confounds such as suicidal intent or comorbid alcoholism. To the best of my knowledge, only one study (Bulmash et al., 2006) has examined actual driving performance among unmedicated individuals with depression. Bulmash and colleagues (2006) found that a clinically depressed out-patient group performed significantly more poorly than a non-clinical control group on a simulated driving task, and attributed this effect to psychomotor disturbances among the depressed group. Although their results convincingly indicate disproportionate levels of driving impairment among their depressed sample, psychomotor disturbances may not be the only explanation for this impairment. Firstly, because they did not obtain an objective measure of psychomotor ability for their participants, they lacked the empirical basis to suggest that their depressed sample exhibited psychomotor deficits or that these deficits had caused the observed driving impairments. Secondly, since depression is typically accompanied by a decline in cognitive abilities such as attention in addition to psychomotor functioning (Hammar, Lund, & Kayumov, 2003; Veiel, 1997), the driving impairments Bulmash and colleagues found in their depressed sample could just as reasonably be attributed to a decline in global cognitive abilities. Research in the area of depression-related driving impairments should endeavor not only to replicate the association between depressive symptomatology and driving impairments, but also to identify the specific neuropsychological deficits responsible for these impairments. Hence, it is important to assess, first and foremost, the various 3 neuropsychological capacities utilized while driving and, secondly, whether and to what extent these capacities are diminished in individuals with depressive symptomatology. The role of psychomotor functions in driving Although safe driving entails complex psychomotor responses (Groeger, 2000), attributing driving impairments among individuals with depression to psychomotor disturbances is problematic for a number of reasons. Psychomotor disturbances, observable either in the form of retardation (slowed speech and body movements) or agitation (inability to sit still, pacing etc.), are one of the signs of depression enumerated in the Diagnostic and statistical manual of mental disorders, fourth edition, text revision (American Psychological Association, 2000) . However, the evidence for the prevalence of psychomotor changes among individuals with depression remains scarce due to contradictory findings and lack of replication. While some research (Sabbe et al., 1999; Hartlage, Alloy, Vazquez, & Dykmna, 1993; Cornell, Suarez, & Berent, 1984) indicates that nearly all individuals with depression exhibit some degree of psychomotor disturbances, other studies (Parker et al., 1993; Austin et al., 1992) conclude that psychomotor changes are only observable in a proportion of this population. Moreover, recent reviews of the research on depression-related neuropsychological deficits identify psychomotor ability as the neuropsychological domain least affected by depression (Airaksinen, Larsson, Lundberg, & Forsell, 2004; Zakzanis et al., 1999). Finally, there exists little to no empirical evidence linking deficits in psychomotor
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