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Development of a Behind-the-Wheel Driving Performance Assessment for Older Adults

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Title:
Development of a Behind-the-Wheel Driving Performance Assessment for Older Adults
Creator:
JUSTISS, MICHAEL DANFORTH ( Author, Primary )
Copyright Date:
2008

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Subjects / Keywords:
Aircraft maneuvers ( jstor )
High speed vehicles ( jstor )
Left turns ( jstor )
Older adults ( jstor )
Research studies ( jstor )
Right turns ( jstor )
Road maintenance ( jstor )
Speed ( jstor )
Speed control ( jstor )
Vehicles ( jstor )

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University of Florida
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University of Florida
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Copyright Michael Danforth Justiss. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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12/31/2007

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DEVELOPMENT OF A BEHIND-THE-WHEEL DRIVING PERFORMANCE ASSESSMENT FOR OLDER ADULTS By MICHAEL DANFORTH JUSTISS A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2005

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Copyright 2005 by Michael Danforth Justiss

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To my parents and Grandmom

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iv ACKNOWLEDGMENTS I would first like to thank my family fo r all their love and support during these trying times I experienced as a graduate stude nt. I would especially like to thank my doctoral committee: Dr. William Mann, Dr. Craig Velozo, Dr. Wendy Stav, Dr. Pat Kricos, and Dr. Ken Brummel-Smith. Wit hout the support of these individuals, I certainly would have never made it this far. Without the financial support of a research assistantship, I would not have been able to advance my career to this level. The assistantship has also offered a unique and challenging perspective to graduate school and without it, I could not have succeeded and th rived in this research environment. I must personally acknowledge my prim ary mentor, Dr. Mann, as “whip master” who kept me on track, despite unavoidable obst acles and challenges. He taught me ways to overcome adversity that I did not think myse lf capable of. I mentioned family in the first sentence; this would, of course, incl ude my RSD family of graduate students, especially the PhDemons. Who would have thought that three people thrown into a broom closet on the first day of graduate sc hool would have surviv ed each other this long, let alone develop a truly la sting friendship? Michael, De nnis, and Arlene were for a long time, affectionately known as the “thr ee amigos”and always will be. Without their love and support, I would have qu it a long time ago. I thank you, Dennis and Arlene. And to the rest of the family: Ri ck, Michelle, Patricia, Bagwandt, Milap, Inga, Leigh, Jamie, Matt, Jai wa, Pei Shen, Sande, Roxanna, Megan, Jessica, and Christina. I thank you all.

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v I also have to thank the driving folks fo r all of their support in helping me to complete my data collection. Desiree and Diana, you were a joy to work with, and I thank you for your efforts and friendship. F unding for my dissertation was provided by The Centers for Disease Control and Prevention, and The Federal Highway Administration.

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vi TABLE OF CONTENTS Page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES...........................................................................................................viii LIST OF FIGURES...........................................................................................................ix ABSTRACT....................................................................................................................... ..x CHAPTER 1 INTRODUCTION AND BACKGROUND.................................................................1 Specific Aims and Hypotheses.....................................................................................1 Background and Significance.......................................................................................2 Driving Cessation and Psychosocial Impact.................................................................4 Older Drivers and the ICF............................................................................................7 Introduction to the ICF..........................................................................................7 The ICF Conceptual Framework...........................................................................9 Driving and the Elderly.........................................................................................9 The ICF and Rehabilitation.................................................................................12 The ICF and Community Mobility......................................................................14 The ICF and Driver Assessment..........................................................................15 Summary.....................................................................................................................15 2 LITERATURE REVIEW...........................................................................................17 Washington University Road Test (WURT)..............................................................17 New Haven Study.......................................................................................................19 Performance-Based Driving Evaluation (PBDE).......................................................20 Comparative Study-Cognition and Age......................................................................21 Behind-the-Wheel Evaluation (BTWE).....................................................................24 Summary.....................................................................................................................25 3 EXPERIMENT I: RELIABILITY AND VALIDITY OF A BEHIND-THEWHEEL DRIVING PERFORMANCE ASSESSMENT FOR OLDER ADULTS...29 Methods......................................................................................................................34 Participant Selection............................................................................................34

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vii Inclusion and Exclusion Criteria................................................................................34 Inclusion Criteria.................................................................................................34 Exclusion Criteria................................................................................................34 Reliability and Validity.......................................................................................36 Results........................................................................................................................ .37 Reliability and Validity...............................................................................................39 Discussion...................................................................................................................40 4 EXPERIMENT II: GEOGRAPHIC GENERA LIZABILITY OF A BEHIND-THE-WHEEL DRIVING PERFORMANCE ASSESSMENT FOR OLDER ADULTS......................................................................................................43 Methods......................................................................................................................44 Results........................................................................................................................ .46 Discussion...................................................................................................................49 5 EXPERIMENT III: ITEM RESPONSE ANALYSIS OF A BEHIND-THE-WHEEL PERF ORMANCE ASSESSMENT....................................50 Methods......................................................................................................................52 Instrument............................................................................................................52 Reliability............................................................................................................53 Data Collection....................................................................................................54 Sample.................................................................................................................54 Analysis...............................................................................................................55 Results........................................................................................................................ .56 Rating Scale.........................................................................................................56 Unidimensionality...............................................................................................60 Principal Components Analysis..........................................................................65 Discussion...................................................................................................................67 6 CONCLUSION...........................................................................................................71 APPENDIX A ROAD PERFORMANCE FORM..............................................................................74 B ROAD PERFORMANCE FORM II..........................................................................92 C INFORMED CONSENT TO PA RTICIPATE IN RESEARCH..............................113 D RASCH CONTROL FILE........................................................................................125 E PRINCIPAL COMPONENT ANALYSI S AND FACTOR (3) LOADINGS.........129 LIST OF REFERENCES.................................................................................................143 BIOGRAPHICAL SKETCH...........................................................................................149

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viii LIST OF TABLES Table page 2-1 Reliability and validity summar y for behind-the-wheel assessments......................27 3-1 Demographic information for elderl y persons completing behind-the-wheel assessment................................................................................................................37 3-2 Cognitive, functional, and psychosocial characteristics for elderly persons completing behind-the-wheel assessment................................................................39 3-3 Reliability of the behind-th e-wheel performance assessment..................................40 3-4 Correlation of global rating and be hind-the-wheel performance scores..................40 4-1 Demographic information for elderly persons completing two separate behindthe-wheel assessments..............................................................................................47 4-2 Cognitive, functional, and psychosocial characteristics for elderly persons completing two separate behind-the-wheel assessments..........................................48 4-3 Summary table for repeated measures analysis of variance with one facet: geographic location..................................................................................................49 5-1 Demographic information for elderl y persons completing behind-the-wheel assessment................................................................................................................55 5-2 Summary of category stru cture characteristics for the JustDrive item scale...........57 5-3 Summary of category st ructure for the JustDrive item scale (collapsed).................58 5-4 Hypothesized hierar chy of item-difficulty...............................................................61 5-5 Infit statistics in difficulty order...............................................................................62 5-5 Exploratory principal co mponent analysis (eigenvalu es > 1) with cumulative percent variance........................................................................................................66

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ix LIST OF FIGURES Figure page 1-1 The International Classification of F unctioning, Disability and Health (ICF)..........7 5-1 Graphical representation for the probabil ity of using levels of the rating scale.......57 5-2 Graphical representation for the probab ility of using levels of the collapsed rating scale................................................................................................................59 5-4 Person ability/item difficulty....................................................................................64 5-5 Scree plot of JustDrive assessment items.................................................................67

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x Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy DEVELOPMENT OF A BEHIND-THE-WHEEL DRIVING PERFORMANCE ASSESSMENT FOR OLDER ADULTS By Michael Danforth Justiss December 2005 Chair: William C. Mann Cochair: Craig Velozo Major Department: Rehabilitation Science The assessment of older adu lts’ driving ability is of important interest for rehabilitation scientists. Driving is an importa nt activity of daily living that is often taken for granted. Loss of freedom associated with the driving cessation, can lead to social isolation or depression. The accepted method of determining driving competence is the behind-the-wheel driving assessm ent, but there has been grea t difficulty with establishing a standardized and objective process. In or der to provide a reliab le and valid outcome measure of driving performance for resear ch being conducted at the University of Florida’s National Older Driver Research and Training Center (NODRTC), several experiments were devised. Experiment I established the criterion va lidity of an evaluator’s Global Rating of driving ability and established the reliability of a behind-the-wheel driving performance assessment. Intraclass correlation coefficients were used to assess inter-rater reliability

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xi and test-retest reliability of the measuremen t procedures. Internal consistency of the measure was high (.94) and determin ed using Chronbach’s alpha. Experiment II was performed to test the standardized methods of road course development and to determine the generali zability of the drivi ng performance score across different locations. A complete repeat ed measures design was utilized to test 42 older adults on two different road courses that met the sa me design guidelines. There was a high generalizability coefficient ( .89), and there was no significant difference between the performance scores on the separate road courses. Experiment III utilized a 1-parameter item response analysis (Rasch) to evaluate the scale structure, item-person fit, and unidimensionality of the behind-the-wheel performance assessment. The results from th e Rasch analysis suggest collapsing the four point scale used for the scoring of driving ma neuvers into three categories. The internal consistency of the collapsed scale remained high (.93). Person-item fit statistics were within acceptable limits (MnSq < 1.7) for most of the items being scored. Information from this study provides ev idence for the reliability, validity, and generalizability of standardized methods to measure the behind-the-wheel driving performance for older adults. There is a n eed for consistency in measurement methods utilized in driving rehabilitation. These methods also provide a reliable and valid outcome measure for driving research.

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1 CHAPTER 1 INTRODUCTION AND BACKGROUND Many driving rehabilitation specialists and researchers have emphasized the “onroad” driving exam as the most appropriate method to determine driving performance and is widely accepted as the criterion standa rd for driving competence (Hunt et al., 1997; Odenheimer et al., 1994). Difficulty arises with consensus surrounding the standardization of the clinical assessment and on-road assess ment protocols. Multiple sites around the United States and other countri es have developed st andardized on-road assessments but still have difficulty with qua ntifying driving behavi ors associated with age-related decline. Many of the on-road assessments used in both licensing settings and clinical rehabilitation facilities have a scor ing system for drivi ng performance but the final decision of a pass/fail outcome is often left to the expert judgment of the evaluator. Specific Aims and Hypotheses Aim #1: To establish the reliability and validity of a behind-the-wheel driving performance assessment for older adults Hypotheses (a) The behind-the-wheel driver performa nce score will demonstrate good interrater reliability, using two raters during the same measurement period. (b) The behind-the-wheel driver performa nce score will demonstrate good testretest reliability (temporal stability), assessing the same participant on the same fixed driving route, within one week of the first assessment. (c) The assessment tool will demonstrate good internal consistency. (d) The behind-the-wheel driver performan ce score will be highly correlated with the global rating (evaluator judgment) of driver competence (criterion validity). Aim #2: To establish the geographic generalizabi lity of a standardized behind-the-wheel driving performance assessment of older adults

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2 Hypothesis: The behind-the-wheel driver performance scores will not vary significantly, assessing the same particip ant on two different driving courses, within one week of th e initial assessment. Aim #3: Using item response analysis, examine th e unidimensionality and item-difficulty hierarchy of a standardized assessment for be hind-the-wheel performa nce of older adults Hypotheses: (a) Items will show good fit statistics demons trating adequate internal consistency. (b) The items will be grouped according to the three theoretical levels of driving complexity used when designing the ro ad course progressi on of complexity. Background and Significance The older population (>65) in the United States was estimated at 35.6 million in the year 2002, a 10.2% increase over the previous decade. Older adults represent 12.3% of the entire population or approximately one in eight Americans. The very old (>85) are the fastest growing age cohort. Over the pa st century, the >85 age group (currently 4.6 million) has grown 38 times larger. The averag e life expectancy has also increased. For those who reach age 65, they can expect an average additiona l 18.1 years of life (NHTSA, 2002). By the year 2030, there will be an es timated 71.5 million older adults. The percentage of seniors at that time will represent approximately 20% of the U.S. population. Those over 85 years will increas e from 4.6 to approximately 9.6 million and represent 13% of the older adult population. With the increasing number of older a dults comes the increased propensity for disability due to age-related decline and associated diseases . Over half (54.5%) the older adult population in 1997 reported at least one type of impairme nt. Seventy four percent of the very old (>85) reported at least one type of impairment or disability (Ficke, 2003).

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3 Driving is considered an important inst rumental activity of daily living. The ability to drive affords an individual a high level of personal and so cietal independence. In 2001, there were an estimated 19.1 million olde r licensed drivers in the United States. This was a 31% increase from the previous decade. Older drivers make up approximately 10% of the tota l driving population in America. The number of licensed elderly and frail elderly drivers is projected to increase. The older adult population accounted for over 150,000 injuries associated with vehicle crashes during 2002. These traffic-related injuries accounted for 5% of a ll people injured in cras hes. Older adults comprised 12% of all driver and occupant fata lities and 17% of all pedestrian fatalities (NHTSA, 2002). These statistics suggest that older driver safety and mobility should be considered an emerging public health issue. There is an impending crisis over av ailability of funds for health care costs related to the rising inju ry and fatality risks among this group as well as the funds available to support mobility following driving cessation. Because of the inherent variability in age-related declines of function experienced by elders, simple agebased approaches to identify those at risk will not work (Staplin, Lococo, Byington, & Harkey, 2001a). A longitudinal study of older drivers (n= 338) estimated male drivers between 70-74 had an approximate total life e xpectancy of 18 years and a driv ing life expectancy of only 11 years. For women in this age group, thei r approximate life expectancy was 21 years, while their driving life expectancy remained similar to men at 11 years. Men will have approximately seven years, and women ten year s when they will not have the ability to

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4 operate a vehicle, and must depend on a lternative modes of transportation (Foley, Heimovitz, Guralnik, & Brock, 2002). Driving Cessation and Psychosocial Impact There are many reasons why older adults cease driving. Dellinger and colleagues conducted a cross-sectional st udy of community dwelling elder in California (n=1950) and asked for information on why they st opped driving (Dellinger, Sehgal, Sleet, & Barret-Connor, 2001). Six categories for ma in reason for driving cessation were identified: medical problems (41%), age-re lated changes (19.4%), licensing or licensingrenewal problems (12.2%), “other” (12.1%), so meone else can drive (10.8%), and vehicle maintenance costs (4.3%). Vision, slow react ion-time, cardiovascular disease, arthritis, Parkinson’s Disease, and accidents were listed subjectively by the study participants for specific reasons they stopped driving. A pproximately 65% of these older adults, who stopped driving within the past five years, were female with a mean age of 85.5 years. Driving cessation by decade showed 2% stopping in their 60s, 18% in their 70s, 63% in their 80s, and 17% in their 90s. A large number of factors were analyzed for association with driving cessation among a cohort of older adults (n=309) (Mar ottoli et al., 1993). Medical conditions associated with driving cessation were: Parkinso n’s Disease, stroke, ar thritis, hip fracture, cataract, glaucoma, vision, and depression. Other factors include d availability of alternative transportation, being married, inab ility to perform one or more basic activity of daily living (BADL), decrea sed physical and social activ ities, and no longer working. A study of 108 older adults in the United Kingdom reported reasons for giving up their driving privileges as: health reasons (28.6%) and loss of confidence or other psychological reason (17.9%) (Brayne et al., 2000) . In a rural environment, a group of 75

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5 older adults (mean age of 83.6 years) indica ted prior accidents, lack of confidence, diminished health, and availability of social support as their reas ons to cease driving. Driving performance has been described as being 90% reliant on visual function. A group of researchers analyzed the relationship of driving cessation to psychosocial factors among a cohort of visually impaired elders (n=604). Psycholog ical well-being was assessed with measures for depression, envi ronmental mastery, and vision specific wellbeing. Driving cessation was associated w ith poor adaptation to visual impairment, increased depression, and decreased environmenta l mastery. The majority of older adults who ceased driving reported lower health st atus, increased functi onal disability, poorer vision, and decreased social support (Hor owitz, Boerner, & Reinhardt, 2002). Marottoli and colleagues’ longitudinal st udy of older drivers (n=1316) showed an association between driving ce ssation and decreased social activity outside of the home (2000). Studies have demonstrated a relatio nship with decreased out-of-home activities and personal well-being among older adults wi th arthritis (Mor et al., 1989; Slattery, Jacobs, & Nichaman, 1989; Zimmer, Hickey, & Searle, 1995). In creased risk for disability and decline in cognitive status ha ve also been associated with disengagement from social activity outside the home (Bassuk, Glass, & Berkman, 1999; Hubert, Bloch, & Fries, 1993). A multidimensional analysis , using a life satisfaction index showed a relationship between activity level and psychosocial outcom es (Hoyt, Kaiser, Peters, & Babchuk, 1980). Social and productive activit ies were shown to have survival advantages among a group of older adults in Connecticut (Glass, de Leon, Marottoli, & Berkman, 1999). Social activities were identified as going to church, cinemas, restaurants, or sporting even ts; taking a day or overnigh t trip; playing cards, bingo, or

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6 other games; and participation in social gr oups. Productive activities were identified as gardening, preparing meals, shopping, community work, and paid employment. After controlling for health-related factors related to survival and controlling for physical activity (fitness), Social and productive activities showed sign ificant survival advantages, with the strongest benefits seen among the least physically active. Depression is strongly as sociated with driving ce ssation. A longitudinal study was conducted with older adults from three driving categories: ac tive drivers (n=502), those who stopped driving by 1982 (n=92), a nd those who never drove or had stopped prior to 1982 (n=722). The active driver group was predominantly young elderly (mean age 69.9), had higher education, fewer medical conditions, ADL deficits, or cognitive impairments. After adjusting for sociodem ographic and health-related factors, driving cessation was independently associated with an increase in depressive symptoms (Marottoli et al., 1997). Drivi ng cessation is commonly identifi ed as a stressful life event for older people. Another longitudinal study (n=1962) analyzed perceived stressful life events and depressive symptoms measured w ith the Center for Epidemiological Studies Depression scale (CESD). A study using a re gression analysis model showed predictive change for driving cessation on depressive sy mptoms among older adults (Glass, Kasl, & Berkman, 1997). A longitudinal study of an elderly cohort monitored depressive symptoms over three to five years post-dri ving cessation and showed a greater risk for worsening depressive symptoms over this extended timeframe (Fonda, Wallace, & Herzog, 2001). The literature illustrates the psychosocial impact that driving cessation can have on the elderly and how active participation in a variety of roles may be dependent upon

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7 the activity of driving. The psychosocial factor s and interactions therein, can be put into perspective by using a conceptual model recognized in rehab ilitation science. Figure 1-1. Conceptual framework for the World Health Organization’s International Classification of Functioning, Disability and Health (ICF) Older Drivers and the ICF Introduction to the ICF The International Classification of Func tioning, Disability and Health (ICF) was developed by the World Health Organization (WHO), in an attempt to standardize the language and terminology used to describe factors related to human functioning and health. A conceptual framework was develope d to describe the interactions or potential interactions between and among these factors. The body of the ICF model is divided into two parts: 1) Functioning and Disability and 2) Contextual Factors. E ach part consists of two components. The functioning and disabi lity portion is compos ed of body-function and structure, as well as activ ities and participation component s. The contextual factors

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8 portion is composed of envir onmental factors and personal factors. These components can be identified as either positive or nega tive denoting a level of function or impairment. The components are categori zed into domains and constr ucts in order to provide units of classification or codes. The organizational structure of the coding is hierarchical. Body Functions contains a “b” prefix, Body St ructure contains an “s”, Activities and Participation has “d”, and Environmental Fa ctors has an “e” for a prefix. The first number position after the prefix represents the respective chapter (first level item-one digit) then increases based upon required levels. The following example is for the classification of driving within th e ICF coding guidelines (2001, page 147): Driving has been identified under the Functi oning and Disability portion and within the activities and participation component . Therefore, it is identified by a “d” prefix. The fourth chapter within the activity and participation section where driving is identified is “Mobility” (d4). Mobility is defined as “moving by changing body position or location, or by tr ansferring from one place to another, by using various forms of transportati on.” Moving around using transportation is grouped under the codes d470-d489. Drivi ng is identified as d475 and driving a motorized vehicle is d4751. There are tw o qualifiers within the activities and participation component: performance a nd capacity. The performance qualifier denotes active life-participation, while the capacity qualifier reflects the individual’s ability to carry out the task identified. The qualifiers are used for assessment of the individual for the level of difficulty in performance or capacity on a scale from 0 (no difficulty) to 4 (com plete difficulty). A number of 8 or 9 indicate “not specified” or “not applicable” respectiv ely. As an example: d4751.02 could identify an individual with no restri ction in performance of driving a car in their current environment but a moderate cap acity limitation in turning the vehicle. Further coding of d4751.021 denotes no di fficulty driving in their current environment (0=first qualifier), modera te limitation in “st eering” (2=second qualifier), but mild limitation in “steering” (1=third qualifier) with the use of an assistive device. There have been numerous versions of th e ICF during the evolu tion to the present model. A previous version, the International Classification of Impair ments, Disabilities, and Handicaps (ICIDH), was limited in its scope for providing adequate representation of environmental influences on disability (WHO, 2001). These earlier versions followed

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9 more of a medical model where the main fo cus for intervention was on the individual. There are often circumstances where barri ers to independence for persons with disabilities are part of the soci al structure and environment. A task force was established in 1995 to address environmental influences, which were incorporated into the current ICF and covers the physical, social and att itudinal environment (Contextual Factors) (Schneidert, Hurst, Miller, & Ustun, 2003). The current ICF follows a universal model instead of a minority model. A minority m odel identifies certain impairment groups, is unidimensional or has a unidirect ional flow of concepts, and is categorical. The universal scheme views everyone as having the potential for disability, is on a continuum, and is multidimensional or multidirectional. The negative terminology from the ICIDH has been changed from a disablement model to a more positive enabling or functional model. Impairment has been changed to body-stru cture and function, disa bility changed to activity, and handicap change d to participation. The ICF Conceptual Framework Driving and the Elderly This review of the ICF related to elde rly drivers will begin with the activity identification of driving a motor vehicle (d4571). To reduce overlap between the components of activity and participation, driv ing will be recognized as an activity: an execution of a task or action by an individua l. The review will address body structure and function’s influence on an individual's abili ty or capacity to safely operate a motor vehicle and how diminished capac ity interacts with participation and contextual factors to reflect psychosocial impact. Driving is identified as an instrumental activity of daily livi ng. Driving involves the incorporation of multiple sensory and motor skills to perform the activity safely. One

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10 of the most important sensory functions re quired for driving is vision. Approximately 90% of the information processed for driv ing is visual (b210b229) (Owsley & McGwin, 1999). In addition to vision, cognition or ment al functions also play a major role in vehicle operation. Visual attention, processi ng speed, dynamic and sta tic acuity, contrast sensitivity, memory function, useful field of view, simple and complex reaction times, and divided attention are examples of body function/structure com ponents necessary for the activity of driving (b110-189, b710-789, s1 10-s299). The ICF can be used in research as a guide for development of screening and assessment tools to identify functional limitations related to driving performance and to provide direction for intervention strategies to promote safer and longer mobility for the frail elders. Age-related decline could contribute to decr eased capacity to drive safely. As age increases, so does the prevalence of certain diseases or conditions that can adversely affect the necessary skills or structures required for driving. Cataract, macular degeneration, diabetes, demen tia, cerebral vascular accident, and arthritis, can all influence body function and structures needed for driving. The conc eptual framework of the ICF allows for multidirecti onal interaction between constructs and components. The activity of driving can intera ct or influence body structur es and function, especially regarding the frail elderly. The increase in the number of older dr ivers combined with increased frailty associated with age related changes in bone and inte rnal organ strength, makes this population more susceptible to in jury or death, even in the presence of vehicle-safety measures, like seat belts and air bags (Bra ver & Trempel, 2004). Older drivers are statistically more likely to su stain a severe upper-ex tremity injury during vehicle crashes when an air bag deploys compared to a non-deployment situation

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11 (Jernigan, 2003). Normal age-related cha nges among the elderly put them in a higher risk category for sustaining injury. Safety a dvantages of seat belts and air bags diminish as we age and air bags may be detrimental to older drivers due to frailty issues. The decreased safety benefit has b een attributed to the change in collision type among this population. It is suggested that the safety benefits of seat belts and air bags are more suited for front-impact collisions. Older driver s have fewer front-end collisions and more left-side impact collisions, compared to younger drivers (Bedard, Stones, Guyatt, & Hirdes, 2001). Changes in both driving expos ure and driving behavi or are changing for seniors. Results from the 2001 National H ousehold Travel Survey (NHTS) showed a marked increase (50%) in the total miles traveled for da y trips among older Americans (75+). Fatalities associated with side-imp act collisions with tw o vehicles accounted for 25% of total occupant deaths for th is age group (Austin & Faigin, 2003). Driver positioning is an impor tant factor in reducing the risk for injury associated with air-bag deployment and improper seat belt use. Women who are less than five-andhalf feet have an increased risk for air bag related injury due to improper positioning. Age-related postural changes that result in slumped driving positi on toward the steering wheel can increase risk for injury, even with lo w-velocity impact. The high level of force exerted by air-bag deployment, when a person is positioned too close to the airbag module, can cause abdominal and thoracic da mage, which can include pulmonary artery tears and aortic laceration (Shkrum, 2002). A distance of at least 25cm from the air bag is recommended to decrease risk of associat ed injury with air bag deployment (Ferguson, 1998).

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12 The influence of driving on participation is very important for older persons. The perception of one’s quality of lif e is often closely related to one’s level of independence. Independence for older persons is often equa ted with the ability to drive. Driving provides the opportunity for in creased interaction (partici pation) within the social environment. Visiting family and friends, acce ssing health care and food, and attending services from community organizations and pl aces of worship are a few examples of how driving can provide an importa nt opportunity for increased mobility and independence as well as social interaction. In contrast, driving cessation has been attributed to an increased incidence of depression and a more rapid decline in health status among older adults. Environmental influences are also impor tant factors. The driving environment can greatly influence a driver’s ability on the road. Age-rela ted declines in the required component functions (vision, cognition, se nsorimotor) for driving may often be “overloaded” in certain cont extual situations. Some state licensing agencies advocate graduated licensing to restrict driving for those deemed “at-risk”(Brayne et al., 2000; McKnight & Peck, 2003). Some studies indi cate that many older adults already selfrestrict (personal factors) when they are awar e of driving performan ce deficits (Brayne et al., 2000). Examples of changes in driving behaviors include driv ing only during the day, avoiding congested or challenging road ways, and avoiding inclement weather. The ICF and Rehabilitation The evaluation process determines if older drivers are identified as safe, unsafe, or have the potential for rehabil itation. Safe drivers may require some general education or recommendations for continued safety with no need for further intervention (personal factors). These older drivers who require remediation/rehabi litation can be targeted for

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13 intervention from multiple directions in th e ICF model. First, the roads could be designed to be more elder-friendly. This falls under the contextual arm of the ICF model and involves societal factors such as govern ment procedures and policy changes. A recently developed guideline to help make road ways friendlier to older drivers is already being implemented across the United Stat es (Staplin, Lococo, Byington, & Harkey, 2001b). The Highway Design Handbook for Ol der Drivers and Pedestrians was developed to provide highway designers and engineers with practical information they can use to address the declining abilities of older adults. Funding through the Federal Highway Administration (FHWA) is being applied to study the use of these elderfriendly road designs and safety features. The National Older Driver Research and Training Center (NODRTC), at the University of Florida, will compare older driver performance in conditions that are comp liant and non-compliant with the design handbook in both an on-road and simulated environment. Another intervention point for a frail elder population is body function/structureactivity-environment inter action level. As an example: An individual who is cognitively intact and does not exhibit any visual field neglect following a stroke may be identified for rehabilitation. Targeting th e body: Remediation of component function such as range of motion, strength, visual processing speed, et c. can be provided to enhance component function to thereby increase independence with driving (activity). With the same deficit example: If remediation of component sk ills is not a viable option, rehabilitation techniques may be applied to enable the pe rson to perform the activity by environmental modification (e120.). Adaptive or assistive te chnology may be applied to the vehicle to enable the driver to operate the vehicle safely despite body fu nction/structure limitations.

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14 Examples of vehicle modifications (environmen t) include left foot accelerator controls for right CVA, hand controls when lower ex tremity function is in adequate, wider view mirrors to increase range of vision, spinne r knobs for upper extremity dysfunction, etc. Another possible area for in tervention is screening for adverse reactions with medication. Many frail elders take multiple medications that can by alone or in combination, negatively impact driving performance.(O'Hanlon, 1992; Ray, Gurwitz, Decker, & Kennedy, 1992) Review of medicati ons for these potential negative effects may identify older adults who ma y need to restrict driving or be able to modify their regimen under physician guidance in orde r to continue to drive safely. The ICF and Community Mobility These intervention strategies have the potential to increase the driving life expectancy of frail elders. Th e majority of negative psychos ocial factors that impact the frail elderly arise from driv ing cessation. Within the ICF framework one can see how limiting an activity can provide a barrier to participation and contextual factors. Challenging avenues of intervention to a ddress psychosocial impact for this rapidly growing cohort are alternative sources of transportation and/or social support networks. Socioeconomic status and stigma often play a role in elderly access to alternative transportation services.(Bur khardt, 1998) The frail elderly may have higher demands from their transportation alternatives. So me elders may require highly individualized service that may include door-to-door, paratr ansit, and wheelchair access with caregiver assistance. The time schedules and routes of traditional transportation service providers may not be conducive with timeframe and loca tions required for medical appointments. The ICF model can guide research efforts to a ddress: the psychosocia l impact of driving cessation, the effects of altern ative transportation strategi es, the role of counseling

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15 services to decrease barriers to elder mobility, and the affects of social interaction on quality of life for older adults. These areas of research need to also include the development of reliable and valid mob ility-related quality of life measures. The ICF and Driver Assessment The holistic nature of a rehabilitation science approach using the conceptual framework of the ICF targets a ll areas of the model. Driver rehabilitation specialists are trained to identify deficits in body function and structures (screening) resulting from disease, injury, or normal age-related declin e that may impede safe driving performance (activity). A battery of sta ndardized component measures is often used to determine the potential risks for unsafe driv ing or crash risk. The behi nd-the-wheel exam involves a more comprehensive assessment of the ve hicle (environment), person-vehicle fit (personal factors-environmen t), and onor off-road pe rformance (interaction of body function/structure-activity-envi ronment-personal factors). Summary Driving is considered an important instru mental activity of daily living. As the older adult population continues to grow, ne w methods are needed to more accurately, fairly, and efficiently identify at-risk driv ers. Research is being conducted at the University of Florida’s National Older Driv er Research and Trai ning Center (NODRTC) to develop a state of the scie nce assessment model to identify these drivers. Tests of vision, cognition, and sensorimotor function are being studied to best predict behind-thewheel (BTW) driving performance. The outco me measure is the primary focus of this study. This study will evaluate BTW driving performance as a reliable and valid outcome measure to be used for determini ng the predictive validity of screening and

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16 assessment tools of measur ing driving-related skills of vision, cognition, and sensorimotor processing.

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17 CHAPTER 2 LITERATURE REVIEW This review focuses on behind-the-wheel dr iving assessment of older drivers. The different methods utilized to assess driv ing performance are discussed and summary reports of psychometric properties of the m easurement tools provided. A recurring theme for these methods to objectify driver perf ormance is the focus on driving behaviors related to specific tasks under certain environmental conditio ns. These studies provide information for reliable and valid scoring mechanisms to identify or differentiate safe from unsafe drivers. Washington University Road Test (WURT) The Washington University Road Test (W URT) is a performance-based assessment that was developed to assess older drivers wi th dementia (n=123) (L. A. Hunt et al., 1997). Thirty-six subjects were identified w ith very mild dementia of the Alzheimer’s type (DAT), 29 with mild DAT and 58 c ontrols as assessed by the Washington University Clinical Dementia Rating (CDR). Upon completion of an off-road test to verify familiarization with vehicle controls, a licensed driving instructor (>15 years of experience) who was blinded to the CD R scores took the subjects on a fixed, standardized road course. The road c ourse was designed to evenly distribute performance difficulty. The licensed instru ctor sat in the front seat while a study investigator (occupational therapist) sat in the rear seat and was also blinded to the subjects CDR score. Driving behaviors dem onstrating increased risk for crashes among older adults were identified through pilot data (Hunt, Morr is, Edwards, & Wilson, 1993)

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18 and literature review. These behaviors were scored on 2-3 point scales (e.g. 0 = moderate to severe impairment, 1 = mild impairment, 2 = no impairment) depending upon the behavior (e.g. signaling, left tu rns, merging). Fifty-four beha viors were scored for a total possible score of 108. A subjective or “global” score (“safe”, “marginal”, and “unsafe”) was given to represent an ove rall interpretation of drivi ng performance for the entire evaluation process. Three different investigators were used to determine interrater reliability using this scoring method. After the investigators were trained using these methods, they each scored behaviors (quantitative score) and gave overall (global) rati ngs for ten road tests simultaneously. Interrater reliability for th ese investigators for the global rating was r = 0.96. Interrater reliability for the global rating between the investigator and the instructor was k = 0.85. Test-retest reliability (stabi lity) was accomplished by retesting subjects (n=63) one month later using the same inves tigator-instructor team (global rating, k=.53). The quantitative score test-ret est reliability was k=0.76. The global rating was used as the “gold standard” to test validity. The quantitative score was validated against the global rating with a high correlation (u sing Kendall Tau-b=0.60) with p<.001. Concurrent validity was addressed by includ ing items from the local Department of Motor Vehicles (DMV) road exam. The 54 items were grouped into nine components (signals, speed control, reacts to others, etc.) and were correlated with the global rating. All nine component subscores were significant ly correlated (p<.01). There are strengths with this study of driving a ssessment. A particular strengt h for this study is the large sample size with use of a cont rol group, which adds statistica l power to the results. The overall correlation between the driving instru ctor rating (criterion standard) and the total

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19 quantitative score from the investigators was high, demonstrating that safer global ratings were positively associated with higher quantitative scores of dr iving behaviors or tasks. A limitation for this study is the sample sel ection based solely on cognitive status, which limits generalization to other se nior populations with other agi ng related deficits that may influence driving performance. The inclusion criteria were based on a cognitive assessment that is not widely recognized a nd developed by the investigating university (Washington University Clinical Dementia Rating). New Haven Study An approach to quantify driving behavior s and increase external and concurrent validity was taken by Richardson and Marotoll i (Richardson & Marottoli, 2003). They standardized an on-road exam based on the ex isting state department of motor vehicles exam. The assessment consisted of 36 standa rd driving behaviors, which were assessed on a pass/fail basis. These researchers modifi ed the scoring to a three-point scale where 0 represented major errors or unsafe, 1 repres ented minor errors, and 2 represented good or no errors. Chronbach’s alpha for internal consistency was 0.88. They used two driving evaluators who assessed over 350 separate ol der drivers and demonstrated inter-rater reliability with an intra-cla ss correlation coefficient of 0.99. To assess rater agreement, weighted kappas were calculated and 26/ 36 items yielded .911-.998, and the remaining ten were >.80. Partial correlations were run on the 36 items in the exam with clinical/cognitive assessments. Significant correlations (p<.05) were seen between total driving performance score and tests for visu al attention (letter cancellation), visual memory (visual reproduction task), and ex ecutive functioning (T rails B). Visual attention was associated with 25/36 of the driving behaviors, 15/36 for visual memory, and 17/36 for executive function. After contro lling for visual acuity, visual attention

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20 accounted for approximately 18% of the variance for the on-road exam and was associated with >50% of the driving behavi ors scored. Even though this study quantifies the items on the road test and demonstrates moderate to strong correlations to visual memory, visual attention, and executive func tioning, there is no globa l rating (pass/fail) to compare the overall driving performance dete rmined by the professional experience of the evaluator. This study has a small sample size and did not consist of clinically referred subjects. Performance-Based Driving Evaluation (PBDE) Odenheimer and Colleagues (1994) devel oped a road test, which identified individual driving tasks and scored corresponding driving be haviors (n=30) (Odenheimer et al., 1994). Experts were consulted in areas of drivi ng, functional assessment and cognitive assessment to develop a list of ite ms and behaviors deemed appropriate to determine safe driving ability (content valid ity). The road course was on a fixed route with a driving instructor in the passenger seat, and two researchers in the backseat. A battery of clinical assessments was administ ered for cognition (Mini Mental State Exam), verbal and visual memory (Wechsler Memo ry Scale), executive functioning (Trails A), and traffic sign recognition (self-created). Simple and complex reaction times were recorded using a Neurobehavioral Evaluation Sy stem (NES). The driving instructor was blinded to the clinical assessment results. The instructor provided a global rating of driving performance on a four-point scale (0 = unsafe in any situation, 1 = safe under optimal conditions, 2=generally safe with mode rate driving difficulty, and 3 = safe in any situation.) The scoring of the on-road performance wa s sectioned into a closed route and an in-traffic route. The closed course consisted of items related to general familiarity with

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21 vehicle features and controls (e.g. seat belts, signals, ignition, peda ls) and was scored for seven maneuvering tasks (e.g. driv ing straight, turni ng, parking). The in-traffic course was scored on 68 driving tasks (e.g. turning, me rging, driving straight ), which progressed in difficulty from residential up to freeway dr iving. Each task is scored for errors in behavior (e.g. scanning, speed, signaling, lane po sitioning) that may be related to a task. An error in any corresponding behavior result s in a “fail” for that driving task. Interrater reliability for the researchers wa s reported a correlation of 0.84 for the closed course and .74 for the in-traffic course. The closed driving course revealed an internal consistency rating of .78 while the in-traffi c rating was .89. Validity was demonstrated with correlation between the global rating and the in-traffic score (r=.74; p<.01) as well as the closed course score (r=.44; p<.05). C onstruct validity was demonstrated for the intraffic scores with all clinical assessments except simple reaction time. The significant age-adjusted correlation coefficients ra nged from .33-.72 with cognition, traffic sign recognition, and complex reaction time as th e three strongest associations. The difference in correlation strength between the closed course and in-traffic course to the global rating suggests that the closed course is inadequate by itself to determine driving competency. Comparative Study-Cognition and Age Dobbs and colleagues (1998) set out to id entify driving errors across three groups of experienced drivers: the cognitively im paired, “normal” older and “normal’ younger drivers (Dobbs, Heller, & Schopflocher, 1998) . Participants underwent six hours of neuropsychological exams, which assesse d memory, attention, language, and other mental functions (specific assessments not id entified). The purpose was to analyze the discrepancy between on-road scoring of driv er errors and expert opinion of driver

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22 performance (Dobbs et al., 1998). The on-road course was designed in two segments, a closed course and an open-road course. The cl osed course (results not reported in this study) was a residential-type of road de sign but was undeveloped and closed to the public. The open-road course consisted of 37 driving maneuv ers that had been identified as problematic for older drivers (turns, yields , etc.) and graded for difficulty (residentialhighway driving). Scoring of the maneuvers was based on short description of error types with no restriction on not ations (open-ended descriptio n). Each error was scored with a 5, 10, or 51 ranking graded by subjective interpretation of severity. Total scores >50 resulted in failing the exam. A multivariate approach (MANOVA) was used to compare the global driver rating scores for defensive driving, accident risk, and driving abilit y. Defensive driving was scored on a 5-point scale (1=no problems, 5=very severe problems), accident risk was on a 10-point scale (1=highest, 10=no risk ), and driving ability on a 4-point scale (1=very poor, 4=excellent). Significant diffe rences were seen for all three groups. An alarming result was seen with a proportion anal ysis of pass/fail using the North American scoring criteria. The North American scori ng method follows the tenets of most driver licensing bureaus across the United States. Th is protocol involves a demerit scoring method for rules of the road and emphasize driving maneuvers that could result in a violation or citation and as well as behaviors judged to be “uns afe”. Error scores are used to make a subjective, global interpretation of driving performance (pa ss/fail). There were an expected high number of cognitively impaired subjects who failed (.71) but a disproportionately high number of “normals” who failed (~.40 for both groups). T-tests for within group comparisons of the global crit eria indicated subject s who failed the road

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23 test were rated differently from those w ho passed in the areas of defensive driving (p<.0001), accident risk (p<.0001), and driver skill (p<.0001). Those who were rated as good drivers, having good defensive driving ski lls, and at lower risk for accidents were failed using this scoring prot ocol. After controlling for errors common to all three groups, the cognitively impaired subjects who failed the road te st remained high at 68%. For the older “normal” group, only 25% failed and only 3% of the young “normals” failed using the North American scoring method. The results of this analysis show the im portance of adjusting for common errors across groups in order to detect those errors specific to declines in driving competence (performance). This also demonstrates the shortcomings of existing scoring procedures utilized by many on road driving assessment protoc ols that don’t control for these factors. The large sample size and use of controls (also seen in the WURT study) adds to the statistical power of these me thods. Another positive approa ch is seen with the openended method of error identification. Thr ough the use of multivariate analysis methods for item reduction, the authors were able to in terpret distinct classi fications of errors, which could then be compared between groups for determining group designation (referral, healthy old and healthy young). Of pa rticular interest are the results concerning “hazardous errors” which are identified as any maneuver that required intervention by the evaluator to take control of th e vehicle or situations in whic h other drivers had to adjust for the error. This category of errors was th e best predictor for inclusion into the referral or cognitively impaired group. Similar results we re seen in other studies of driving errors using similar multivariate methods (Di Stefano & MacDonald, 2003).

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24 DriveAble is an established driver eval uation program used widely in Canada and more recently in select location across the United States with se veral locations in Florida. It is composed of a competence screening and an on-road exam. The computerized competence screening is administered to check reflexes, judgment, decision-making, attention, and memory. The on-road portion of the exam is scored on 34 driving maneuvers on a course graded for difficulty from residential to highway driving. Score values are sent electronically to Dr iveAble headquarters where a pass/fail recommendation is returned the evaluation center. The competence screen has been reported to have a 94% accu racy rate for predicting failure of the road course (sensitivity), and 98% percent accuracy to pr edict passing the road course (specificity) (Dobbs et al., 1998). A limitation for the use of DriveAble is that it does not assess drivers with severely disabling physical c onditions requiring vehicle modifications and primarily focused on cognitive impairment. DriveAble requires specialized assessor training, proprietary software, and standardized proprietary road c ourses which limits its applicability for driving research. Behind-the-Wheel Evaluation (BTWE) Galski and colleagues developed an on-ro ad evaluation procedure to test the driving performance of subjects having su stained a traumatic brain injury (n=35) (Thomas Galski, Bruno, & Ehle, 1992). Subj ects were given a clinical assessment battery of cognitive exams for executive functioning (Trails A), complex figure test (Roy-Osterreith), visual form discrimination, letter cancellation, block design (WAIS-R), and a maze test (Porteus). A simulated evaluation was conducted to assess threat recognition, crash avoidance and evasive actions. The BTWE consists of a “lot” index and a “street” index. The lot index reflects those driving behaviors assessed off-road

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25 (familiarity with vehicle controls). The stre et index consisted of 13 driving activities or maneuvers that were hierarchically ranked by th e driving instructor in order of difficulty. Items were dichotomously scored as pass= 1 and fail=0.The individual scores were multiplied by rank and summed. A constant for the street index and lot index was added to give a maximum possible score of 100 for each. Construct validity was demonstrated betw een the street index and eight cognitive measures, simulator performance for signali ng and threat recogn ition, and several lot index items (See table 2-1). The significant cognitive measures accounted for 64% of the variability in the street index. Adding the two significant simulator items to the regression model increased the variability to 84% and when the lot items were added, the explained variability of the street index increased to 93% (T. Galski, Bruno, & Ehle, 1993). Summary Overall the on-road evaluation methods de scribed above were well designed and reported good reliability and validity for both item rating (driving behaviors) and clinical criteria (cognition, vision, etc.) where appli cable (see table below). They all captured important aspects of driving performance iden tified as problematic for older adults. The WURT study incorporated a high degree of c ontrol with a large sample and control groups, as did the comparative study by Dobbs et al. The smaller sample size and lack of control sample limited the power of the PBDE, but it does use a precise method of scoring of driving tasks and related behavi ors. PBDE does include a more commonly used cognitive assessment (MMSE) for rati ng impairment. The PBDE also included vision and attention evaluati ons in their clinical ba ttery, which showed strong associations with the on-road test results. Despite the positive attributes of these studies,

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26 the quantitative scoring methods for these assessments were course dependent which limits their ability to generalize use in othe r geographic locations or environments. The New Haven study (Richardson & Maroto lli) and the BTWE (Galski et al) both used standardized road courses but scor ed driving performance on a scale that was dependent of the road course. The New Haven method also utilized an existing DMV testing form to quantify driving behaviors. This established external validity, which is one of the most important concerns for ev aluation of driving competence. The BTWE takes an extra step by ranking item importanc e to establish indexed scores for driving behaviors. This is important with in strument development because not every performance item scored has e qual contribution to “safe driv ing performance.” The New Haven study had very strong rater reliability but focused primarily on the associations between the individual driving behaviors and visual attenti on processing rather than how these behaviors contributed individua lly to the criterion standard. An individual assessment protocol cannot be identified as uniquely qualified to provide the “best” prediction or classification of safe vs. unsafe driving performance. Further development and testing of these types of on-road assessment protocols is needed. Design elements from these studies provide insight into the development of a universally accepted, standardized road assessm ent. Of these elements, independence of the measurement tool from who is tested (youn g vs. old) and where the testing occurs is paramount. Due to the dynamic and multi-cont extual attributes of driving competence, item-response analysis (e.g. Rasch analysis , principle component analysis) should be utilized to capture the associations both individually or in combination that may contribute to the construct of driving competence. Establishing an item hierarchy may

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27 provide evidence for applying empirically deri ved weights to items to more accurately identify competent vs. non-competent drivers. Table 2-1. Reliability and validity summa ry for behind-the-wheel assessments Study Description Reliability Validity Washington University Road Test (WURT) Hunt et al (1997) Standardized on-road test (n=123). Subjects with dementia (mild, very mild, control) Interrater reliability Global rating b/w investigators (OT) k=0.96; Global rating b/w investigator and instructor k =0.85; Test-retest reliability Quantitative score k=.76; Global rating k=.53 High correlation between quantitative score and global rating (r=.60; p<.001) Concurrent validity Inclusion of DMV road test items New Haven Study Richardson and Marotolli (2003) Standardized on-road test (n=35). Quantified road performance scores Internal Consistency Chronbach’s alpha=0.88 Interrater reliability Intraclass correlation coefficient(ICC=.99) Construct Validity Moderate correlation with visual attention (r=.43), visual memory (r=.40, and executive functioning (r=-.38) Concurrent validity Use of existing DMV road test PerformanceBased Driving Evaluation Odenheimer et al (1994) Standardized performance – based road test (n=30). Closed and in-traffic road scores Interrater reliability r =.84 ; in-traffic r =.74 Internal Consistency closed course=.78; intraffic=.89 Correlation between driving score and global rating, in-traffic (r=.74,p<.01); closed course (r=.44,p<.05) Construct Validity Correlation with MMSE (r=.72), Traffic signs (r=.69), Visual memory (r=.50), verbal memory (r=.37), Trails A (r=.33), Complex reaction time (r=.58); all age-adjusted.

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28 Table 2-1 continued DriveAble Dobbs et al (1998) Computer screen followed by an on-road exam Predictive Validity (road test) 68% pass/fail outcome for cognitively impaired elderly Predictive Validity (screen) Sensitivity 94% accuracy for predicting failure of road test Specificity 98% accuracy for predicting failure of road test BTWE Galski et al (1992) Study comparing onroad performance to cognitive function, simulated driving. (n=35) Correlation of Street Index to: Cognition: Trails A, (r=.42, p<.05), figure test change score (r=.44, p<.01), maze test (r=.43, p<.05), visual form discrimination (r=-.56, p<.001), Double letter cancellation (r=-.57, p<.001), Block design (r=.60, p<.001), Simulator: signal errors (r=-.64, p<.001), threat recognition (r=.69, p<.001) Lot behaviors: following directions (r=-.59), slow response (r=-.68), inattention (r=-.71), distractibility (r=-.72); all p<.001

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29 CHAPTER 3 EXPERIMENT I: RELIABILITY A ND VALIDITY OF A BEHIND-THE-WHEEL DRIVING PERFORMANCE ASSESSMENT FOR OLDER ADULTS The behind-the-wheel (BTW) driving assessm ent has been identified as the most appropriate method to determine driving co mpetence (Hunt et al., 1997; Odenheimer et al., 1994). Inconsistent scor ing methods for behind-the-wh eel assessment and lack of standardized procedures to quantify driving performance has prompted researchers to develop tools to more objectively measure this dynamic task (De Raedt & PonjaertKristoffersen, 2000; Di Stefano & Macdona ld, 2003; Dobbs, Heller, & Schopflocher, 1998; Galski, Bruno, & Ehle, 1993; Hunt et al., 1997; Janke & Eberhard, 1998; McKnight & McKnight, 1999; Odenheimer et al., 1994; Richardson & Marottoli, 2003). Despite attempts to quantify driving perfor mance, the accepted global criterion outcome (pass/fail) is determined by evaluator judgment rather than a quantifiable driving score. Both the measurement tool and the environm ent used to assess driving performance has been reviewed by driving experts from nati onal and international consensus conferences on older driver assessment (Stephens et al., 2004). Groups were unable to recommend a standardized method of BTW performance measurement. Many driving rehabilitation specialists recommended all individuals refe rred for a driving assessment should be given the opportunity to complete an “on-road” se gment. Off-road and on-road BTW testing was explored with the on-road testing identifi ed as the most ecologically valid method to assess “true” driving performance.

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30 Different quantitative methods to assess driving performa nce have been explored. Some studies use methods to count driving “errors” (Mazer et al., 2003; Roenker, Cissell, Ball, Wadley, & Edwards, 2003) while others utilize more elaborate scoring mechanisms that scale individual drivi ng components (Galski et al ., 1993; Hunt et al., 1997; Odenheimer et al., 1994). A well recognized dr iving behavior model describes driving as a complex task that is hier archically controll ed through three leve ls of progression: strategic, tactical and operational (M ichon, 1985; Ranney, 1994). The strategic or planning level reflects general goal forma tion which may involves trip planning and selecting a route and its alte rnatives. The tactical leve l reflects the navigational influences of the selected route, such as tu rns, curves and traffic. The operational level involves the ability to control the vehicl e given the environmental or situational influences (Ranney, 1994). Researchers using this hierarchical m odel have focused on the tactical and operational levels of driving in an attempt to more objectively measure performance. Types of driving maneuvers can be identified on a fixed course and represent the tactical level of driving. Left turns, right turns, and straight driving are examples of these driving maneuvers. Each driving maneuver will have ce rtain behaviors associated with them and reflect the ability to control the vehicle dur ing a maneuver (operational). By identifying errors at the operational level, evaluators can objectively score driving performance during select maneuvers (tactical). Because of geographic variability in c ourse design, information gathered from expert consensus was utilized when deve loping the on-road por tion of the driving assessment. Recommendations were given fo r a fixed-route with a gradual progression

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31 of driving difficulty for total driving tim e of approximately one hour. The scoring mechanism for this study is based on behavior al errors used to score driving maneuvers (Mallon & Wood, 2004; Odenheimer et al., 1994). The differen ce in scoring compared to previous research is that maneuvers are scaled for severity of error. A total performance score is then calculated. This score will be validated against the Global Outcome Rating determined by the evaluator. Rather than a pass/fail outcome, a modified outcome scale is used to reflect a more realistic interpre tation of driving competence commonly seen in driving rehabilitation. The outcome rating is based on evaluator judgment (criterion standard) and has four levels: Safe (3), Safe with restric tions or recommendations (2), Unsafe Remediable (1), Unsafe not remediable (0). Driving Behaviors : The following driving behaviors were modi fied and/or collapsed in order to control for environmental variation and capture as much objective driving behavior by a single evaluator, compared to similar scor ing items and/or met hods (Hunt et al., 1997; Mallon & Wood, 2004; Odenheimer et al ., 1994; Richardson & Marottoli, 2003): Vehicle position (anterior/posterior) (movi ng or stopped): Vehicle po sition refers to the position of the vehicle forward and backward (anterior posterior) in relation to other vehicles and/or objects and pavement marki ngs. This captures following distance during forward movement and vehicle spacing during lane changes and merges. Examples of errors: Traveling too closely (tailgating), in adequate space cushion during merge or lane change, stopping across a crossw alk or too far back from e ither pavement markings or other vehicles.

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32 Lane Maintenance : Refers to the lateral (side to side) positioning of the vehicle during driving maneuvers (turns, straight drivi ng, lane changes, etc.) and while stopped. Reflects ability to maintain steering control. Examples of errors: Drifting out of driving lane, encroachments on perpendicular traffic or wide turns, park ing outside designated space markings. Commonly referr ed to as lane keeping. Speed Regulation : Reflects ability to follow and maintain speed limits and having adequate control of acceleration and braking features of the ve hicle. Example of errors: not coming to a complete stop at stop sign, tr aveling too slow/fast, inadequate merging speed, abrupt or inappropriate braking or acceleration. Yielding : Giving right-of-way when appropriate . Yielding refers to the ability to recognize common rules of road safety. Yiel ding is assessed at four-way or two-way stop intersections (when other vehicles ar e present), right turns on red, and merges. Signaling : Proper use of turn signals. Errors in signal use consist of leaving the turn signal on, not using the turn signal when turn ing, using the turn si gnal inappropriately (wrong signal for given turn, sign aling too short until maneuver). Visual scanning : Demonstrating visual scanning of driving environment. Examples of errors: Not checking blind spot, not l ooking through rearview mirror, not looking left/right before proceeding through intersection. Adjustment to stimuli/traffic signs : Ability to appropriately re spond to driving situations. This captures ability to adju st appropriately to changing road sign information, other vehicle movements, pedestrian movements a nd ability to recognize potential hazards. Errors would consist of not adjusting speed for posted limits, not following proper

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33 directions given by evaluator, choosing impr oper lane from posted signage, improper response to traffic or pedest rian (or cyclist) movement. Gap acceptance : Choosing an appropriately safe time and or spacing distance to cross in front of oncoming traffic (unprotected left turn). Errors in gap acceptance are based on evaluator judgment given the sp eed of oncoming traffic a number of lanes to be crossed. Errors in gap acceptance consis t of driver estimates that are both too short and too long. Scoring of Maneuvers: Each maneuver is scored on a scale of 0-3 and based on behavior errors for the given maneuver. The road course is has a fi xed route and allows for low, moderate, and high grades of complexity for each maneuve r. Low complexity maneuvers are those performed in a low speed, low traffic volume, and single-lane environment, such as a residential neighborhood with speed limits <30mph. Moderate complexity maneuvers are those performed at speeds > 30mph. and < 45mph., can consist of two lanes, and higher traffic volumes. High complexity driv ing is identified by tr avel speeds >50 mph (highway driving), and higher density traffi c volumes at moderate speeds (35-50mph). Multiple left turns, right turns, lane changes and straight driving are evaluated at each level of complexity. The high-speed merge is located in a typical freeway environment with speed in excess of 55mph. Each maneuver has a number of associated behaviors from which to derive a score. A score of ” is given for a ma neuver where there are zero errors for any associated behaviors. A score of ” is given for any errors in any behavior for the given maneuver. A score of ” is given if the ev aluator has to use verbal cues or repeat instructions (not hearing relate d) in order to modify or cha nge behavior. A score of ”

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34 is given if physical intervention (grabbing the steering wheel, using the auxiliary brake, etc.) is required or if warran ted by the situation. The cumu lative score is divided by the total number of maneuvers to yi eld a percentage score. An example of a road course scoring form can be seen in appendix A. This study will analyze the crite rion validity, inter-rate r reliability, internal consistency, and test-retest reliability of this measurement tool. Methods Participant Selection A convenience sample of 95 older adults with a mean age of 75.3 (SD = 6.4) years met the following inclusion/exclusion criteria: Inclusion and Exclusion Criteria Inclusion Criteria Adult volunteers over age 65 (participants) and those referred for driving evaluation from Gainesville area physicia ns, law enforcement, and family. Participants with a minimal Snellen acuity of 20/40 with corrected vision Participants who are seizur e free in the past year Participants possessing a valid driver’s license Exclusion Criteria Participants who do not meet th e above listed in clusion criteria Participants requiring adap tive driving equipment (e.g. left-sided pedals, onehanded devices) Participants were recruited through ongoing aging and driving research being conducted at the University of Florida’s Driving Rehabilitation Services Program: Independence Drive . The road course was designed using liter ature review and ex pert peer support attained from driving and assessment experts who attended the International Older Driver Consensus Conference on Assessment, Remedi ation, and Counseling held in Arlington

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35 VA, December, 2003. The course began with a “warm-up” period with our dual brake program vehicle in a parking lot (2005 Buic k Century). The evaluator pointed out the general controls for mirrors, seats and automa tic transmission shift. The drivers made simple maneuvers and practiced perpendicular or angled parking for approximately 5-10 minutes. The course was designe d to progress from simple to moderate and then through high complexity environments. The parking lo t or “off-road” area wa s selected to empty directly into a residential or simple driving environment. The course gradually progre ssed in difficulty by entering roadways with higher speeds, more traffic lights/signals, and hi gher traffic/pedestrian volume including a high speed merge onto a highway or expressway. To control for adequate exposure within each level of difficulty, the course was designed to contain at least three examples of each type of maneuver within each level of difficulty. The scored maneuvers were left turns, right turns, lane changes, st raight driving, and one high speed merge. Lane changes were excluded from the simple driving envir onment and only one high speed merge was required. The total length of the course was approximately 15 miles in length with a mean run time of 51.9 minutes (SD = 7.4). The BTW assessments were given during daylight hours of mid-morning through late afternoon. Cancellation of the BTW assessment due to unsafe driving, inclement weather or unsafe road conditions was left to the discretion of the driving evaluator and documented. The course structure and the dr iving performance form were piloted with 10 volunteers for the purposes of training by the Certified Driving Rehabilitation Specialist and with the scor ing procedures. The comple ted course consisted of 91 maneuvers through Gainesville, Florida. Th e driving performance form was designed so

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36 a lone evaluator would be able to documen t observed driving errors adequately and remain attentive to the driver and surroundi ng conditions. The fixed route ensured all participants were given the same maneuvers a nd navigational instructi ons were scripted. The evaluator would check observed errors from a list of behaviors under each maneuver. For example: During a left turn (maneuver) fa ilure to signal and swing wide into the perpendicular lane would warrant a check in lane maintenance and signaling. Verbal cues given to modify behavior outside th e scripted navigationa l directions were documented as were any evaluator interventions or violations of law for each maneuver. The scores utilized for statistical anal ysis are the Global Rating and the Driving Performance Score. The Global Rating desc ribed above is the evaluator’s overall judgment. The Driving Performance Score is the total number of points accumulated over the set number of maneuvers divided by the total possible number of points (91 maneuvers x 3 = 273 possible points) Reliability and Validity Inter-rater reliability of the driving performance score was estimated using an Intra-class correlation coefficient (ICC). This statistic was chosen as it reflects both the level of association and agreement between raters (Portney & Watkins, 2000). By following assessment methods used in previous BTW studies using multiple raters of the same participant, we identified a primary rate r as the front seat evaluator and a secondary rater as a backseat evaluator (located dire ctly behind the front passenger) (Hunt et al., 1997; Mazer et al., 2003; Odenheimer et al., 1994). Thirty-three participants were evaluated using multiple raters. The raters alternated between primary and secondary positions for this sub-sample. Temporal stability (test-retest reliability) was also estimated using an ICC with a sample of 10 participants. The participants agreed to

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37 return within one week of th eir first road test. Internal consistency (homogeneity) was estimated using Chronbach’s alpha. The cr iterion validity was es timated by correlating the evaluator’s global rating against the dr iving performance score using Pearson’s r coefficient. Results Ninety-five participants completed behind-the-wheel assessments using standardized methods. The mean age was 75.3 years of age (ranging from 65-89 years). Fifty-four percent were male while 46% were female. Most of the sample (92%) was White, 1% African-American, 3% Hispanic or Latino, and 4% Asian. Almost 40% of the sample had a graduate level education or higher and 14% gr aduating high school. Twenty-two percent completed some college or an associate degree. Table 3-1. Demographic information for el derly persons completing behind-the-wheel assessment N=95 Frequency (%) Age Mean = 75.3 (SD = 6.4) Gender Male Female 51 (53.7%) 44 (46.3%) Race White African-American Hispanic or Latino Asian 87 (91.6%) 1 (1.1%) 3 (3.2%) 4 (4.2%) Level of Education High school or below Some college Bachelors Post professional Masters Doctorate 15 (15.8%) 21 (22.1%) 16 (16.8%) 4 (4.2%) 18 (18.9%) 21 (22.1%)

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38 Cognitive status of the sample was assessed using the Mini Mental Status Exam which ranges from 0-30 with 30 being the best score. A score of 24 is an accepted cutoff for mild cognitive ability (Kantor, Mauger, Richardson, & Unroe, 2004). The scores ranged from 21-30 with a mean of 27.2 (SD = 2.3). Seven percent of the sample scored below 24 for mild cognitive impairment. A well recognized assessment of visual attention processing is the Usef ul Field of View Analyzer. This computer-based test categorized participants into five groups based on risk for crashes ranging from 1-5. Category one represents very low risk while category 5 represents a very high risk for vehicle crashes. The sample average was 2.1 (SD = 1.2). Forty-three percent of the sample scored within category one while 16% scored more than category three. The functional status of the sample was based on values from the F unctional Independence Measure (FIM) and the OARS IADL scale. The FIM, which ranges from 0-126, identifies the level of assistance needed to complete basic activitie s of daily living (e.g. bathing, dressing toileting, etc.). A score of 126 represents complete independence. The FIM was given by telephone and the self-repo rted scores ranged from 111-126 with a mean of 125.1 (SD = 2.3). The OARS is also a self-reported scale to assess the level of assistance needed to complete instrumental ac tivities of daily livi ng (e.g. using the phone, money management, etc.). The scale range s from 0-14 with 14 representing complete independence. Scores ranged from 10 -14 with a mean of 13.8 (SD = 0.1).

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39 Table 3-2. Cognitive, functional, and psychosocial characteristics for elderly persons completing behind-the-wheel assessment Assessment N=95 Mean (SD) MMSE 27.2 (2.3) FIM 125.1 (2.3) OARS IADL 13.8 (0.6) UFOV 2.1 (1.2) Number of Meds 7.0 (4.2) GDS 2.8 (2.8) Pain 11.0 (1.5) Other health-related characteristics of the sample included pain, level of depression, and number of medications. Pain was assessed using the Jette Pain Scale which ranges from 1040 with 10 representing no pain. The sample’s pain scores ranged from 10-17 with a mean of 11.0 (SD = 1.5). The level of depression was assessed using the Geriatric Depression Scale (GDS) which ranges from 030 with scores between 10 and 19 representing mild depression and scores between 20 and 30 as severe depression. Scores ranged from 0-14 with a mean of 2.8 (SD = 2.8). The mean number of medications taken by the sample was 7.1 (SD = 4.2). Reliability and Validity The thirty-three participants used for the inter-rater reliability analysis were 89% White, 1% African American, 1% Hispanic or Latino, and 1% Asian. Fifty-six percent were male and 44% female. The in ter-rater reliability (ICC) using dichotomous scoring of maneuver items (OD) (Odenheimer et al ., 1994) was .88 and the ICC for the modified scoring of items accounting for severity of e rror (PS) was .94. The in ter-rater reliability for the Global Rating was .98. The test-ret est (temporal stability) ICC was .90 (OD score) and .95 (PS score). Internal consistency for the items for the PS yielded a

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40 Chronbach’s alpha of .94. The correlation fo r Global Rating and PS (criterion validity) was r = .84, p < .001. Table 3-3. Reliability of the behi nd-the-wheel performance assessment Measure Inter-rater Reliability (n=33) Temporal Stability (test-retest) (n=10) Internal Consistency (Chronbach’s alpha) N=95 Global Rating ICC = .98 Kappa = 1.0 Performance Score (PS) ICC = .94 ICC = .95 = .94 Dichotomous Score (OD) ICC = .88 ICC = .91 = .95 Table 3-4. Correlation of global rating a nd behind-the-wheel performance scores Measure n Global Rating Performance Score (PS) 95 r = .84, p < .001 Dichotomous Score (OD) 95 r = .75, p < .001 Discussion Standardized methods for assessing be hind-the-wheel drivin g performance can provide a valid and reliable outcome measure for determining older driver competence. The Global Rating, which reflects the evaluators overall judgme nt of driving performance is widely accepted as the criterion standard by both driving rehabil itation specialists and driver licensing institutions (Hunt et al., 1997; Mallon & Wo od, 2004; Odenheimer et al., 1994). The very significant and strong asso ciation between the Global Rating and the quantitative driving performance score supports the validity of this outcome measure of “real time” driving performance. The quantitative scoring method (errors to score maneuvers) has been demonstrated to be a reliable and valid mechanism to estim ate the driving performance of older adults. By expanding the scale to include severity of error, a stronger correlation indicates greater sensitivity for this modified scor ing method compared to dichotomous pass/fail

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41 criteria for each performance item/maneuve r. The high internal consistency of the measure indicates we are measuring a high de gree of the trait of interest, driving performance. The driving performance form used to score the errors/maneuvers was designed with substantial feedback by drivi ng rehabilitation specia lists who had a major concern over their ability to adequately score the participant and remain attentive to the driver and his or her surroundings . The inter-rater reliability scores demonstrate a safe and consistent method of accurately quan tifying driving performance. The high correlation coefficient suggests the primary ev aluator (front seat) can remain attentive and still adequately and cons istently identify driving e rrors. The fixed number of maneuvers ensured consistency of exposure to probable events throughout the course. The course design to progress gradually th rough three distinct levels of driving complexity provided adequate exposure to novel and challenging driving events during the approximately one hour duration. Some driving rehabilitation specialists and researchers debate whether a fixed route with scripted navigational directions is an appropriate method for evaluation. The major ity of older drivers will self-regulate or restrict their driving frequency when they ar e aware of declining ability. Many will only drive to the store, bank, or doctor’s offi ce and avoid difficult maneuvers and unfamiliar areas. Having and older driver drive to th eir store is a very occupationally centered approach to assess driving within their accepte d environment. This type of evaluation would be of benefit in states where graduate d licensing or geographi c restrictions can be imposed. Most states do not have these opt ions and they are diffi cult to enforce. A structured research design to study the difference between the fixed route evaluation and

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42 the “personalized” evaluation would provide valuable information toward refining the behind-the-wheel assessment process. The convenience sampling yielded a skew ed distribution of older driver’s performance ability. There were more “safe” drivers than those identified as dangerous “failing”. One problem with the sampling sc hema was the issue over reporting of “atrisk” drivers to the state (Florida). After careful review of both state and professional (Occupational Therapy) re porting requirements, it was decided that we were professionally obligated to inform the state and report dangerous drivers. Even though this “risk” was explicitly described during our informed consent process, very few (2%) withdrew from the study because they feared to lose their license. This aspect of the study would naturally attract t hose older adults who are more competent drivers. There is still further measurement development required before a quantitative “cutoff” score can be determined. An even more pressing and demanding task is determining the generalizability of the road course design and scoring mechanism across different locations. This research question wi ll be addressed in the second experiment of this study.

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43 CHAPTER 4 EXPERIMENT II: GEOGRAPHIC GENERALIZABILITY OF A BEHIND-THE-WHEEL DRIVING PERFORMANCE ASSESSMENT FOR OLDER ADULTS The driving performance measurements obt ained from the previous experiment have been demonstrated to be reliable and va lid outcomes. Questions arise as to whether generalizations can be made about these meas urements of driving performance. This reliability evidence provides a f oundation for making generalizations. The BTW driving assessment has been identified as the accepted method for measuring driving performance. The naturalis tic setting provides ecological validity to the assessment process. Expe rimental control of the driving environment has proven to be difficult for driving researchers. Studies to assess driving performance have been designed in simulated and off-road or clos ed-course environments in an attempt to control for environmental variance that might influe nce performance. Although experimentally sound, performance in these environments do not generalize to driving in the “real world” which is the accepted envi ronment for determining driving competence by driver licensing agencies and rehabilitation settings. The theory behind the validity of th e BTW assessment is that throughout a hierarchically structured, fixe d-route driving course, a par ticipant will be adequately exposed to enough driving experiences for th e evaluator to make an objective decision about their overall driving performance. These same elements that strengthen the experimental nature of the BTW assessment, also confounds the gene ralizability of this method to other areas or driving environments . Driving rehabilita tion specialists from

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44 driving consensus conferences voiced opinions concerning th e fixed-route design of the driving course. Roadway conditions can vary form street to street as we ll as from city to city. The design guidelines described have been used to develop road courses at several data collection sites throughout th e state of Florida. Pilot an alyses revealed similar interrater reliability and validity data compared to those in Experiment I. Currently, there is an insufficient sample size which restricts ge neralizability of thes e performance scores across different location usi ng parallel arm designs. Experiment II was designed to study th e generalizability of the BTW assessment across different locations. The hypothesis is there should not be a significant difference in driving performance scores between two different road courses when following the fixed-route design recommendations. This study is identified as single facet generalizability study with the facet being geographic location. Methods A clinical trial, employing a complete re peated measures crossover design, was used to address this research objective. By definition of this study design, each experimental unit (hereafter referred to as a participant) will be tested at both factor levels. To control for possible change in pe rformance status over time, the factor level will be given within 1-4 weeks of each other. The accuracy of the response variable measurement will be maximized in several ways. Each trial for all participants will ta ke place at the same location, around the same time of day, and during similar weather and li ghting conditions (no rain, daylight hours). Evaluators will be trained by a registered occupational therapist (OTR) certified in driving rehabilitation (CDRS). Each participant will be given scripted instruction during both courses.

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45 All participants were selected from volunteer and referral sources (see inclusion criteria) in the Gainesville, Florida area. Since the chance of selection of each experimental unit in the universe is not known, this is not a probabi lity sampling scheme. To understand why this method of assignment is superior to others, it must first be emphasized that the list from which assignment will occur is based on a convenience sample . Therefore the list itself may introduce potential selection bias, both geographical (since the inclusion criteria will limit responde rs to those residing w ithin the Gainesville area). Geographical bias is not one that can be controlled within a convenience sample design. In this manner the convenience sample will be transformed into a representative sample, in which the extraneous factor of ag e has been controlled. Cluster sampling was not applicable to this study, since the individuals do not exis t in clusters, and geographical distance betw een groups of individuals was not an issue. To control for any residual effects that may yet exist inherently in the study, the order of factor level assignment (Course 1 or 2) will be randomi zed by SPSS statistical software. A total of 21 participants will be assigned to course one and 21 to course 2. An experimental design was chosen to allo w control of factor level assignments. An observational study would not afford this opt ion. The prospective (a priori) nature of an experimental design also affords better cont rol of extraneous factors, which increases the accuracy and validity of the results. Retr ospective studies (cohor t, cross-sectional, case control) are inferior with respect to the level of control of both extraneous and experimental factors. A repeated measures design was chosen over a parallel arm design since, by nature, repeated measures designs require smaller sample sizes and therefore less time, as well as fewer resources. Importa ntly, complete repeated measures designs

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46 also afford the opportunity to test individuals under all (in this study, both) factor levels. This inherently increases th e gain in information relati ve to a parallel arm design, assuming residual effects are identified and balanced. Results Road course 1 consisted of 91 scored ma neuvers while course 2 consisted of 113 scored maneuvers. Each course had at least three left turns , right turns and straight driving segments represented in each of the three levels of drivi ng complexity. There was one high speed merge per course and a minimum of three lane changes represented in the moderate and high complexity levels (See appendices A and B). Forty-two subjects were given both BT W assessments. The mean age was 75.7 years of age (ranging from 65-87 years). Fift y-four percent were male while 46% were female. The majority of the sample ( 93%) was White, 2% African-American, and 5% Asian. Over half (55%) of the sample had a graduate level education or higher and 17% graduating high school.

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47 Table 4-1. Demographic information for elderly persons completing two separate behind-the-wheel assessments N=42 Frequency (%) Age Mean = 75.7 (SD = 6.0) Gender Male Female 20 (47.6%) 22 (52.4%) Race White African-American Hispanic or Latino Asian 39 (92.9%) 1 (2.4%) 0 (0.0%) 2 (4.8%) Level of Education High school or below Some college Bachelors Post professional Masters Doctorate 7 (16.7%) 4 (9.5%) 7 (16.7%) 1 (2.4%) 12 (28.6%) 11 (26.2%) Cognitive status of the sample was assessed using the Mini Mental Status Exam which ranges from 0-30 with 30 being the best score. A score of 24 is an accepted cutoff for mild cognitive ability. The scores range d from 21-30 with a mean of 27. (SD = 2.1). Seven percent of the sample scored belo w 24 for mild cognitive impairment. A well recognized assessment of visual attention processing is the Useful Field of View Analyzer. This computer-based test categori zed participants into five groups based on risk for crashes ranging from 1-5. Category on e represents very low risk while category 5 represents a very high risk for vehicle cras hes. The sample average was 2.0 (SD = 1.1). Forty-five percent of the sample scored with in category one while 17% scored more than category three. The functional status of the sample wa s based on values from the Functional Independence Measure (FIM) and the OARS IA DL scale. The FIM, which ranges from

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48 0-126, identifies the level of assistance needed to complete basic ac tivities of daily living (e.g. bathing, dressing toileting, et c.). A score of 126 represen ts complete independence. The FIM was given by telephone and the self-re ported scores ranged from 111-126 with a mean of 125.5 (SD = 1.1). The OARS is also a self-reported scale to assess the level of assistance needed to complete instrumental ac tivities of daily livi ng (e.g. using the phone, money management, etc.). The scale range s from 0-14 with 14 representing complete independence. Scores ranged from 10 -14 with a mean of 13.9 (SD = 0.3). Table 4-2. Cognitive, functional, and psychosocial characteristics for elderly persons completing two separate behind-the-wheel assessments N=42 Mean (SD) MMSE 27.6 (2.1) FIM 125.5 (1.1) OARS IADL 13.9 (0.3) UFOV 2. (1.1) Number of Meds 7.0 (4.1) GDS 2.9 (2.8) Pain 10.9 (1.6) Other health-related characteristics of the sample included pain, level of depression, and number of medications. Pain was assessed using the Jette Pain Scale which ranges from 1040 with 10 representing no pain. The sample’s pain scores ranged from 10-17 with a mean of 10.9 (SD = 1.6). The level of depression was assessed using the Geriatric Depression Scale (GDS) which ranges from 030 with scores between 10 and 19 representing mild depression and scores between 20 and 30 as severe depression. Scores ranged from 0-14 with a mean of 2.9 (SD = 2.8). The mean number of medications taken by the sample was 7.1 (SD = 4.1). The mean performance score for course 1 was .84 (SD = .08) and the mean performance score for course 2 was .85 (SD = .07). The generalizability coefficient was

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49 .89. The F statistic was 2.34, (p = .134) representing the diffe rence in driving performance between the two courses. Table 4-3. Summary Table for Repeated Measur es Analysis of Variance with One Facet: Geographic Location. ANOVA Sum of Squares df Mean Square F Sig Between People 0.436 41 0.011 Within People Between Items 0.003 1 0.003 2.335 0.134 Residual(a) 0.048 41 0.001 Total 0.051 42 0.001 Total 0.487 83 0.006 Discussion Based on the G study results, there is a rela tively small proportion or error that is attributable to the course lo cation. The expected hypothesis that there is no significant difference at an alpha level of .05 between the performance scores of this sample of older adults is retained. Despite the higher number of overall maneuvers in the second course compared to the first, the performance scores did not differ significantly between assessments. This information supports the design structure of th e fixed-route driving course as a reliable method to evaluate older driver performa nce across different locations. To the knowledge of the author, there have been no reported studies that compare the driving performance of the same pa rticipants across two different locations. Participants were asked following the completion of their second road test “Did you find one road course more difficult than th e other?” Only two participants felt the second course was more difficult than the first. The rest felt they we re “about the same.” Both raters identified the second road course as “slightly more challengi ng” than the first. Reasons noted by the raters were the increa sed overall driving time (55 minutes SD = 12.4), and increased driving time in higher complexity areas.

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50 CHAPTER 5 EXPERIMENT III: ITEM RESPONSE ANALYSIS OF A BEHIND-THE-WHEEL PERFORMANCE ASSESSMENT The reliability and validity of the Just Drive performance measure was established using classical test theory psychometrics (see experiment I). To further assess the measurement characteristics of th is tool, modern test theory methods were applied. Item response analysis and more sp ecifically the Rasc h measurement model, is becoming a popular method to examine the psychometric properties of func tional performance measures (Velozo, Kielhofner, & Lai, 1999). While the first experiment focused on the JustDrive performance measure as a whole (classical test theory), the Rasch model will analyze the test items within the tool. Modern measurement theories suggest the measurement of a construct be separate fr om the tool being utilized (McHorney, 1997). An overarching goal of this dissertation is to increase the objective measurement of behind-the-wheel driving pe rformance. The definiti on of objective measurement according to the Institute for Objective Measurement: “Objective measurement is the repetition of a unit that maintains its size, within an allowable range of error, no matter which instrument is used to measure the variable of interest (test free) and no matter who or what relevant person or thing is measured (sample free)”. These criteria for a scientific measure make the development of objective measures in the social and rehabilitation sciences a daunti ng task. The scientific development of a measurement tool begins with the idea or c onstruct we intend to measure which in this case is driving performance. Items are select ed for a tool based upon their ability to bring

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51 out the characteristics of th e intended construct through the behaviors of those being measured (Bond & Fox, 2001). The Rasch model is a single parameter, item response model used to construct measures from the ordinal scaling of observations (L inacre, 2002). The Rasch analysis is based upon the following formula (Velozo et al., 1999): In [Pnijk/Pnijk-1] = Bn – Di – Fk Where Pnijk = probability of person n being rate d at step k on domain i by rater j Pnijk-1 = probability of person n being rate d at step k-1 on domain i by rater j Bn = ability of person n Di = difficulty of item i Fk = difficulty of rating step k relative to step k-1 By taking the log of the raw scores, the ordina l values are transformed into equal interval values. This aspect of the Rasch analysis is of great importance because all rating scales used for clinical observations are consid ered ordinal (Velozo et al., 1999). The mathematical operations used in classical test theory models improperly treat ordinal data as interval data. The right side of the formula contains the component Bn – Di which represents the person’s ability given the difficulty of a partic ular item. The concept of person to item-difficulty is a component of in terest when designing a driving course. The Rasch formula provides empirical evidence of the difficulty or complexity of the driving items selected when designing the road course. The recommended progression from simple through more complex or difficult driving tasks has not been adequately investigated. Selecting and accurately identify ing the different levels of driving difficulty or complexity increases the precision for m easuring the construct of driving performance across a range of for this ability.

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52 Methods Instrument The behind-the-wheel performance assessm ent was developed through literature and peer review. Certified Driving Rehabilitation Specialis ts (CDRS) and expert panel members from The International Older Driv er Consensus Conference and The Canadian Older Driver Consensus Conference were cons ulted during the review and selection of driving assessment methods. To increase the objectivity of th e behind-the-wheel assessment and increase the level of experiment al control given the dynamic nature of the driving activity, the road cour se and scoring procedures were designed with specific criteria. The scoring procedure chosen was based on previous driving performance research conducted by Odenheimer et al. ( 1994). Participants were given performance scores (pass/fail) for each driving maneuve r which was based on whether errors among specific driving behaviors were observed duri ng the given maneuver. This enables the evaluator to assess performance within the environmental context. A total performance score was calculated as a percentage of “passed” maneuvers recorded during the assessment. A modified version (JustDrive) of this sc oring procedure was used in an attempt to account for severity of error during the observed maneuver and to control for environmental variation in driving complex ity. A scaled measure of performance on each maneuver was used. A four point scal e (0-3) was chosen where 3 = no observed errors, 2 = one or more errors observed, 1 = one or more observed errors with verbal cueing required to modify or change drivi ng behavior, and 0 = one or more observed errors with physical intervention required or warranted (grabbing wh eel or using safety brake), including violation of la w (Florida Statutes). The maneuvers scored were left and

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53 right turns, lane changes, straight driving segments, and a high speed merge. The observed driving behaviors were vehicle positioning (anterio r/posterior), lane maintenance, speed regulation, yielding, signaling, visual scanning, gap acceptance, and adjustment to stimuli/traffic signs and conditions (see Appendix A, pg. 18). For the road course design, maneuvers were grouped into three levels of driving complexity: low, moderate, and high. The course was also on a fixed-route to contro l for the total number of maneuvers being scored. The course wa s structured with a gradual progression in driving complexity or difficulty. Reliability The scoring forms were designed with the purpose for clinical utility. The goal to create a more objective measure of driving pe rformance can interfere with safety during the assessment procedure. The primary eval uator must remain attentive throughout the course to observe both the driver and the driv ing environment and intervene if necessary. Two-evaluator models have been used widely in the driving literature and some states require this method for their driving assessmen ts. From a clinical perspective, the twoevaluator model is not feasible for typical driving rehabilita tion programs. Inter-rater and test-retest reliability were established for the instrument. An intra-class correlation coefficient (ICC) which accounts for both association and agreement (Portney & Watkins, 2000), was .94 using the JustDrive scor ing procedure. The two evaluators were trained driving rehabilitation specialists (occupational therapists) and certified driving instructors in the state of Florida. The ev aluators alternated between a primary (front seat) and a secondary (right rear seat) rater position during when es tablishing inter-rater reliability on a sub-sample of 28 participants. Temporal stability (test-retest reliability) was .95 and was evaluated within a period of one week of the initial assessment.

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54 Data Collection The behind-the-wheel asse ssment of driving performance (JustDrive) was designed for the purpose of establishing a reliable and valid outcome measure for investigating the model clin ical assessment protocol de veloped through the National Older Driver Research and Trai ning Center (NODRTC) at the Un iversity of Florida. The clinical assessment protocol is a battery of cognitive, visual , and sensorimotor tests used to measure driving related skills. A drivi ng rehabilitation service facility (Independence Drive) was established through the University of Florida. A convenience sample was recruited through this facil ity and from advertisements sent to the surrounding Gainesville, Florida area. In an attempt to recru it participants with decreased function, a recruitment core database from a frail elder st udy was also used. Participants were given the clinical assessment battery followed by the behind-the-wheel assessment. Sample Ninety five participants completed the fixed-route, behind-the-wheel driving assessment. The mean age was 75.3 years of age (ranging from 65-89 y ears). Fifty-four percent were male while 46% were female. The majority of the sample (92%) was White, 1% African-American, 3% Hispanic or Latino, and 4% Asian. Almost 40% of the sample had a graduate level education or higher and 14% gr aduating high school. Twenty-two percent completed some college or an associate degree.

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55 Table 5-1. Demographic information for el derly persons completing behind-the-wheel assessment N=95 Frequency (%) Age Mean = 75.3 (SD = 6.4) Gender Male Female 51 (53.7%) 44 (46.3%) Race White African-American Hispanic or Latino Asian 87 (91.6%) 1 (1.1%) 3 (3.2%) 4 (4.2%) Level of Education High school or below Some college Bachelors Post professional Masters Doctorate 15 (15.8%) 21 (22.1%) 16 (16.8%) 4 (4.2%) 18 (18.9%) 21 (22.1%) Analysis The item response analysis for the Just Drive instrument was conducted using Winsteps computer software. The mean square (MnSq) standard residuals were used to determine how well the items fit the construct. MnSq infit values for persons or items between 0.6 and 1.4 are deemed acceptable for s caled data (survey t ype). An acceptable range for clinical observations MnSq inf it values are between 0.5 and 1.7. The 1.7 value was used to review the acceptabi lity of the person and item fit. This provides evidence of the unidimensionality for the construct of driving performance. The Rasch analysis provides also provides a hierarchical order of item difficulty. Item and person measures are presented in the form of interval-level logits which represent log odds ratios. The higher the logit value, the more challenging the associated item or more able the person. A factor analysis was performed using SAS (version 8.2) statistical software.

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56 Results Rating Scale Three essential criteria have been identified for rating scale development (Linacre, 2002). The first cr iterion requires a minimum of 10 observations within each scale category. Low counts within a categor y can lead to imprecise estimations or instability in the step calibra tions. The second criterion re quires a progression (direction) in the average measures for each category. These average values represent empirically derived markers within the context of the categ ories being used (magnitude). In simple terms, a positive vector of average category measures (magnitude and direction). This enables us to discern “lower” from “higher” values and what relate d differences imply. The third criterion requires an Out-fit MnSq value less than 2.0. An Out-fit MnSq above 2.0 reflects a large amount of “noise” which suggests the rating category is providing little or improper information. Previous dr iving performance research using observed driving behaviors to score maneuvers (Mal lon & Wood, 2004; Odenhe imer et al., 1994) utilized a dichotomous rating scal e (pass/fail) for item scores. The utility of scaling the maneuver score to account for severity of driving error (4-points) was explored. The Rasch analysis reports the probability of rating a 0, 1, 2, or 3 depending on what is observed during a give n maneuver. It would be expected that participants with good driving ability would be rated wit hout driving errors (3) and drivers with lesser ability or dangerous driving behavior would require cueing or intervention (1 or 0). A gra phical representation of these rating probabilitie s is seen in figure 5-1. The probability is high that a participant dem onstrating poor or dangerous driving ability will be rated ” for a maneuve r and the probability is also high that a participant demonstrating good or excellent dr iving performance would be rated .”

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57 The probability of selecting a rating category (0, 1, 2, or 3) changes as a participant displays less or more driving ability. Fo r example, as driving performance increases (from -3 to +3 logits along th e x-axis), the probability of be ing rated ” decreases to 0% at a logit score of approximately +1.0. In c ontrast, as a participan t’s driving performance decreases, the probability of being rated ” drops to 0% at a logit score of approximately -1.0. P ++---------+---------+---------+---------+---------+---------++ R 1.0 + + O | | B |00000 | A | 0000 3| B .8 + 00 333 + I | 00 333 | L | 00 33 | I | 0 33 | T .6 + 00 222 33 + Y | 0 2222 2222 33 | .5 + 0 22 22233 + O | 00 22 33222 | F .4 + 0 22 3 22 + | * 33 22 | R | 22 00 33 222 | E | 111*11111*1 33 222 | S .2 + 11111 22 0*111 33 222 + P | 1111 222 0*3*111 2| O | 111111 222 333 000 1111 | N |11 222222 333333 00000 11111111 | S .0 +******333333333333333 000000000*************+ E ++---------+---------+---------+---------+---------+---------++ -3 -2 -1 0 1 2 3 PERSON [MINUS] ITEM MEASURE (LOGITS) Figure 5-1: Graphical represen tation for the probability of utilizing each level of the item (maneuver) rating scale. The y-ax is represents the probability of rating one of these categories (0 to 1.0) and th e x-axis represents the person measure minus the item measure in logits. Table 5-2 Summary of category structure ch aracteristics for the JustDrive item scale Category Observed Count Observed Average InFit MnSq OutFit MnSq Category Measure 0 247 .38 1.60 2.27 -2.07 1 394 .29 .87 0.91 -0.79 2 2976 1.38 .95 0.82 0.49 3 5938 2.75 .91 0.95 2.54 Poor driving performance Good driving performance 3 = no observed errors 2 = one or more errors observed 1 = one or more observed errors with verbal cueing required to modify or change driving behavior, and 0 = one or more observed errors with

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58 As the graphical representation shows in figure 5-1, the probability of using a rating of ” (verbal cueing) is not distinctly higher than receivi ng other ratings on the scale. A participant’s drivi ng ability of approximately -0.6 logits has approximately the same probability of being ra ted a 0, 1, or 2. After revi ew of the collapsed scale characteristics (table 5-2) and review of a ll 91 item category summar ies, the scale did not meet all of the required elements to retain all 4 points: 1. An inadequate number (<10) of observations for the first two levels of the ra ting scale, 2. For the collapsed scale (ratings collapsed across all 91 items), the observed average for each rating did not increase incrementally, and 3. The Out-fit MnSq is > 2.0 (Linacre, 2002). Figure 5-1 shows a nondistinct, probabilistic emergence for category ,” compared to the other levels of the scale. The decision was made to collapse ca tegory ” into category .” Table 5-3 and Figure 5-2 report the scale characteristic re sults following the merging of category ” with category .” Table 5-3 Summary of category structure fo r the JustDrive item scale (collapsed) Category Observed Count Observed Average InFit MnSq OutFit MnSq Category Measure 0 641 -0.14 1.28 1.74 -1.48 1 0 0.00 0.00 -0.62 2 2976 .92 1.02 0.85 0.49 3 5938 2.15 .86 0.93 1.99

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59 P ++--------------+--------------+--------------+--------------++ R 1.0 + + O |00000 | B | 0000 | A | 000 | B .8 + 00 + I | 00 333| L | 0 333 | I | 00 3333 | T .6 + 0 33 + Y | 00 22222222222 333 | .5 + 0 222 222*33 + O | *22 333 222 | F .4 + 22 00 33 2222 + | 22 0 333 222 | R | 22 00 33 2222 | E | 22 0*33 222| S .2 + 22 33 00 + P | 222 3333 00 | O | 22222 3333 0000 | N |22222 3333333 0000000 | S .0 +*************111111111111111111111111111111111***************+ E ++--------------+--------------+--------------+--------------++ -2 -1 0 1 2 PERSON [MINUS] ITEM MEASURE Figure 5-2: Graphical represen tation for the probability after merging the first two rating categories. After merging the first two rating categories, the resultant Infit MnSq values fall within the even more of 0.6-1.4. An acceptable Outfit MnSq value is < 2.0. The merged rating of ” now has an acceptable Outfit MnSq of 1.74. The criteria for incrementally observed averages and category measures are now acceptable. (Table 5-3). Two of the three scale criteria are within acceptable limits: 2) Category measures and observed averages advance incrementally and 3) Outfit MnSq value for each rating category is < 2.0. The first criteria requiri ng 10 observations per rating category was not satisfied. One reason could be the small sample size re lative to the overall number of items. The lack of adequate observations within each category is a product of incidental rather than structural “zero” (Linacre, 2002). Structur al “zeros” represent categories that would never be observed while incident al “zeros” simply reflect th e lack of observations of a 3 = no observed errors 2 = one or more errors observed 1 = one or more observed errors with verbal cueing required to modify or change driving behavior, and 0 = one or more observed errors with physical intervention required or warranted Poor driving performance Good driving performance

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60 particular category with this particular data set. The new graphical representation for the probability of utilizing each level of the rating scale is shown in Figure 5-2. The collapsed category of ” into ” results in the emergence of three distinct probability curves for each level of the scale. As driving ability increases, the probability of receiving a rating of ” for an item decrea ses and the probability of scoring a ” increases. As a person’s driving ability c ontinues to increase the probability of being rated a ” decreases, and at a logit of approximately 1.0 the probability of receiving a ” increases beyond that of category .” The remaining analyses utilized the restructured performance rating scale. Unidimensionality The unidimensionality of the construct is reflected in the overall mean infit score (MnSq = 1.09, ZSTD = 0.3) for the measur ement tool. Approximately 20% of the individual item MnSq values were higher th an the 1.4 cutoff established for rating scale (survey) data. There was no discernable pattern observed as to why th ese particular items displayed higher variable noise compared to other maneuvers of the same type and complexity. An acceptable cutoff criteria of 1.7 MnSq was identified for rating scales for clinical observations (Sabari et al., 2005; Wright & Linacre, 1994). When the conservative cutoff for individual item-noise wa s relaxed to 1.7 approximately 5% of the total number of items fall above this score. Approximately 5% of items and persons are expected to misfit based on probability alone . Because there was no obvious pattern of misfit noted, all items were retained (see table 5-5). The mean item infit summary was acceptable (MnSq = 1.12; ZSTD = 0.3) as was the mean person infit (MnSq = 1.09, ZSTD = 0.3).

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61 Table 5-4 Hypothesized hier archy of item-difficulty Items (level of complexity) It em abbreviation (# observed) High Speed Merge (High) HSM (1) Lane Change (High) LCH (6) Left Turn (High) LTH (3) Right Turn (High) RTH (3) Straight Drive (High) SDH (8) Lane Change (Moderate) LCM (7) Left Turn (Moderate) LTM (4) Right Turn (Moderate) RTM (5) Straight Drive (Moderate) SDM (18) Left Turn (Simple) LTS (7) Right Turn (Simple) RTS (8) Straight Drive (Simple) SDS (21) Total items 91

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62 Table 5-5 Infit statistics in di fficulty order. Highlighted it ems denote high Infit values. Item Measure (Logits) Error Infit MnSq Z STD Item Measure (Logits) Error Infit MnSq Z STD 1 SDS1 2.81 .12 1.23 1.5 47SDM2 .11 .16 1.14 0.7 2 RTS1 2.73 .11 1.58 3.6 48HSM .11 .16 1.55 2.3 3 LCH4 1.23 .11 0.98 -0.1 49SDM10.08 .17 1.39 1.7 4 RTM2 1.19 .11 0.76 -1.8 50 SDH3 .08 .17 1.76 3.0 5 LCH2 1.15 .12 0.62 -3.0 51LTS1 .06 .17 1.15 0.8 6 RTH2 1.11 .12 2.11 5.8 52SDM17.03 .17 1.12 0.6 7 SDM12 1.07 .12 0.72 -2.0 53LTM2 .00 .17 1.12 0.6 8 SDH1 1.03 .12 1.55 3.2 54 RTS8 .00 .17 1.96 3.6 9 LCM1 .99 .12 0.64 -2.7 55SDH2 -.06 .17 1.20 1.0 10 LTM3 .93 .12 0.80 -1.4 56SDH4 -.06 .17 1.27 1.2 11 SDM9 .90 .12 0.68 -2.2 57SDS19 -.09 .18 0.67 -1.6 12 LCH5 .87 .12 1.03 0.2 58SDM8 -.09 .18 1.49 2.0 13 SDM7 .79 .13 1.47 2.6 59LTH1 -.12 .18 1.00 0.1 14 LCH6 .77 .13 1.03 0.3 60 SDH5 -.22 .19 1.83 3.0 15 LTH2 .74 .13 0.83 -1.1 61SDH8 -.26 .19 1.26 1.1 16 SDM6 .72 .13 0.68 -2.1 62SDM5 -.33 .19 1.60 2.3 17 RTH1 .72 .13 0.80 -1.3 63SDM13-.37 .20 1.80 2.8 18 RTM3 .70 .13 0.58 -2.9 64LCM5 -.41 .20 1.21 0.9 19 SDM18 .67 .13 0.85 -0.9 65 LTH3 -.41 .20 1.73 2.6 20 SDM3 .65 .13 1.28 1.6 66LTS4 -.49 .21 1.21 0.9 21 SDH7 .65 .13 1.10 0.6 67 SDS16 -.54| .21 1.01 0.1 22 SDS2 .63 .13 0.67 -2.1 68LTS5 -.58 .21 0.85 -0.6 23 LCM3 .61 .14 0.57 -2.9 69SDS20 -.58 .21 1.36 1.4 24 SDH6 .60 .14 1.05 0.4 70 RTS6 -.63 .22 1.93 3.1 25 SDM14 .60 .14 1.12 0.7 71SDS17 -.63 .22 1.55 2.0 26 LCH3 .56 .14 1.00 0.1 72RTM5 -.63 .22 0.99 0.0 27 RTM4 .52 .14 1.53 2.6 73RTS3 -.73 .23 0.89 -0.4 28 SDM11 .52 .14 0.88 -0.7 74SDS18 -.73 .23 0.86 -0.5 29 LCM2 .50 .14 0.59 -2.6 75SDM1 -.95 .25 0.97 0.0 30 RTH3 .50 .14 1.52 2.6 76 SDS21 -.95 .25 1.93 3.0 31 LTS2 .48 .14 0.79 -1.2 77SDS5 -1.08 .26 1.03 0.2 32 LTS6 .48 .14 0.49 -3.4 78SDS4 -1.15 .27 0.88 -0.4 33 LTS7 .48 .14 0.62 -2.4 79 SDS14 -1.15 .27 1.90 2.8 34 RTS7 .48 .14 0.57 -2.7 80RTS2 -1.22 .27 0.83 -0.6 35 SDM16 .46 .14 1.58 2.7 81 SDM4 -1.22 .27 1.24 0.9 36 LTM4 .46 .14 1.00 0.0 82 LCH1 -1.38 .29 1.41 1.4 37 RTS4 .44 .14 0.64 -2.1 83SDS6 -1.56 .31 1.64 2.0 38 LCM6 .40 .15 1.06 0.4 84 RTS5 -1.66 .32 0.97 0.0 39 SDS3 .38 .15 1.21 1.1 85SDS11 -1.66 .32 0.92 -0.2 40 LCM4 .35 .15 0.89 -.5 86SDS7 -1.77 .34 0.88 -0.3 41 SDS15 .33 .15 0.85 -.8 87SDS8 -1.89 .36 0.91 -0.2 42 SDM15 .33 .15 1.72 3.1 88SDS9 -1.89 .36 1.65 1.9 43 LCM7 .31 .15 1.17 0.9 89 SDS12 -1.89 .36 0.91 -0.2 44 LTM1 .26 .15 0.91 -0.4 90SDS10 -2.17 .40 0.79 -0.5 45 LTS3 .16 .16 1.20 1.0 91 SDS13 -2.34 .43 0.93 -0.1 46 RTM1 .16 .16 0.65 -1.9

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63 Table 5-5 lists the items in order of difficulty for this sample with person measures of driving ability and average measur es of driving challenge on the same scale. Compared to the hypothetical order (Table 54) the most challenging item was expected to be the high speed merge. Based on the responses, the high speed merge is approximately in the middle of the hierarchy ranking (Figure 5-4, highl ighted pink). The most challenging items were the first two mane uvers of the driving course. Most of the high and moderate complexity maneuvers were ranked in the top 50%. Figure 5-4 illustrates the person-item ranking. The simp le complexity maneuvers (highlighted green) group toward the bottom of the difficulty hierarchy and the moderate (yellow) and high (red) complexity maneuvers groups toward the top of the scale. The summary infit statistics for the partic ipants were also in an acceptable range (MnSq = 1.09; ZSTD = 0.3). Less than three percent of the person MnSq infit values were outside the acceptable li mit of 1.7. Rasch analysis ca lculates a person-separation reliability which is analogous to Chronbach’s alpha. With the scale collapsed across the first two ratings, the separation reliability wa s (.93). A person-separa tion index is also calculated and represents th e number of statistically di stinct strata of driving performance. The person-separation index wa s 3.54. This index is used to calculate a separation ratio (SR = 5.1) which means there ar e approximately five distinct levels of driving performance being represented by th is sample (Velozo & Peterson, 2001). The mean of the sample measure (M to the left of the vertical axis) was 1.61 logits higher than the mean of the item calibrations (M to the right of the vertical axis).

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64 Figure 5-4 Person ability/item difficulty. The le ft side of the figure represents participant performance and the right side represents item difficulty (L ogits). Each “X” on the left represents an individual participant with th e Xs lower on the scale showing lesser driving performance than those Xs toward the top. PERSONS MAP OF ITEMS | 4 + X | | X | | T| XXX | 3 XX + X | SDS1 XXX | RTS1 XX | XXX S| XXXXX | XXXXXXXXXXX | 2 XXXXXXXXX + XX |T XXXXXXXX | XXXX M| XXXXXXXXXXX | XXXXXXXX | LCH4 XXXXXXX | LCH2 RTH2 RTM2 SDM12 1 XX +S LCM1 SDH1 XXXX S| LCH5 LTM3 SDM7 SDM9 XXX | LCH6 LTH2 RTH1 RTM3 SDH7 SDM18 SDM3 SDM6 XXXXXX | LCH3 LCM2 LCM3 RTH3 RTM4 SDH6 SDM11 SDM14 SDS2 X | LCM6 LTM4 LTS2 LTS6 LTS7 RTS4 RTS7 SDM16 SDS3 XXXX | LCM4 LCM7 LTM1 SDM15 SDS15 X | HSM LTS3 RTM1 SDH3 SDM10 SDM2 0 X T+M LTM2 LTS1 RTS8 SDH2 SDH4 SDM17 X | LTH1 SDM8 SDS19 | SDH5 SDH8 SDM5 X | LCM5 LTH3 LTS4 SDM13 | LTS5 RTM5 RTS6 SDS16 SDS17 SDS20 | RTS3 SDS18 | -1 +S SDM1 SDS21 | SDS14 SDS4 SDS5 | RTS2 SDM4 | LCH1 | SDS6 | RTS5 SDS11 SDS7 |T SDS12 SDS8 SDS9 -2 + | SDS10 | SDS13 | | | | -3 + | Green = Simple complexity Yellow = Moderate complexity Red = High complexity Pink = High speed merge

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65 Principal Components Analysis An exploratory principal component analysis was run to determine the unidimensionality of the construct. Acco rding to the Kaiser rule for retaining components with an eigenvalue > 1.0, we woul d retain 27 principle components (Table 55) (Portney & Watkins, 2000). According to th e scree plot (Figure 55) we would make a visual estimate to retain thos e components just to the left of where the curve starts to level out (~3-4). The theoretical design stru cture of the road c ourse involved three operationally defined levels of driving comp lexity. For this reason, an oblique factor rotation was chosen with a three factor so lution. This accounted for approximately 33% of instrument variance. Analysis of the fact or loadings across all 91 items did not reveal any interpretable maneuver patterns or gr oupings. The cumulative variance for the 21 initial components was approximately 80%.

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66 Table 5-5 Exploratory Principal Component An alysis (Eigenvalues > 1) with Cumulative Percent Variance Eigenvalue Cumulative Percent 1 21.54 23.7% 2 4.66 28.8% 3 3.90 33.1% 4 3.11 36.5% 5 2.75 39.5% 6 2.65 42.5% 7 2.50 45.2% 8 2.41 47.8% 9 2.20 50.3% 10 2.17 52.6% 11 2.13 55.0% 12 2.01 57.2% 13 1.94 59.3% 14 1.81 61.3% 15 1.70 63.2% 16 1.63 65.0% 17 1.50 66.6% 18 1.46 68.2% 19 1.42 69.8% 20 1.34 71.2% 21 1.28 72.7% 22 1.19 74.0% 23 1.16 75.2% 24 1.10 76.4% 25 1.06 77.6% 26 1.05 78.8% 27 1.02 79.9%

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67 9 1 8 9 8 7 8 5 8 3 8 1 7 9 7 7 7 5 7 3 7 1 6 9 6 7 6 5 6 3 6 1 5 9 5 7 5 5 5 3 5 1 4 9 4 7 4 5 4 3 4 1 3 9 3 7 3 5 3 3 3 1 2 9 2 7 2 5 2 3 2 1 1 9 1 7 1 5 1 3 1 1 9 7 5 3 1 Component Number 12 10 8 6 4 2 0 Eigenvalue Scree Plot Figure 5-5 Scree plot of JustDrive assessment items Discussion The first experiment of this dissertati on sought to establish the reliability and validity of a behind-the-wheel performance measure (JustDri ve). Through the use of item response theory techniques using Rasch an alysis, provided valuable information for the development of this measurement tool. We derived useful information about this measure of driving performance by: 1) re fining the rating scale, 2) exploring the unidimensionality of the items used for the construct of driving performance, and 3) verifying the expected hierarchy of item di fficulty used in road course design. The rating scale of no errors, some errors, verbal cueing required, and intervention required or warranted was not s upported empirically using all four points based on MnSq and summary characteristics. The scale was collapsed because the probability of rating a participant with a scor e of ” was not distinctly different from rating them a .” The intention of a rating scale instead of a dic hotomous pass/fail was

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68 to add more information in order to increase the precision and accuracy of the measurement tool (Linacre, 2002). Although di chotomous rating does provide a reliable method of driving assessment (Mallon & Wood, 2004; Odenheimer et al., 1994), this study provides empirical evidence that more in formation can be attained by scaling the items. The unidimensionality of a measure represen ts construct validity. A difficult task in driving assessment is providing objective m easurement of performance. This is due largely to the dynamic nature of the activity in relation to the environment. The environment, which provides the ecological or naturalistic validity necessary for accurate assessment, also challenges objectivity and expe rimental control. Ni nety percent of the items and 97% of the persons fit the Rasch model based on the MnSq inclusion/exclusion cutoff of 1.7. By analyzing individual item s and persons, we were able to determine those items that would be better left out or identify persons who may represent a different or distinct sample. The choice to include or exclude items based on their infit scores often depends on the type of test (clinical obser vation or survey) or is often left up to the decision of the researcher. We chose to relax our item and pers on calibration guidelines to reflect clinical observation rather th an conventional survey scale criteria. The intended use of the instrument also in fluences our decision to retain items. The construction of the driving assessment wa s designed in an incr emental fashion based on a hypothetical hierarchy of item or maneuver difficulty. Part of the course design recommendations is for an overall driving time of ~45-60 minutes to provide ample opportunity of environmental exposure for the evaluator to make a decision about driving competence. Based on the empirical evidence from the item-difficulty hierarchy, there

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69 was no discernable pattern of erratic fit to warrant exclusion of the driving maneuvers. However, the simple or residential area warrant s further investigation. At least for this sample, the first two maneuvers (simple right turn and simple straight driving segment) proved to be the most challenging for all driv ers regardless of drivi ng ability. Despite the acclimation or warm-up period in a parking lo t to familiarize the participants with the vehicle, these first maneuvers were the most challenging. The acclimation period may be inadequate and it’s not until they start to dr ive on open roadways that the “get used to” the car and their abiliti es to control it. The findings are suggestive that these two or possibly the first several “simple” driving mane uvers should not be counted or scored for this measure. The overall range of items is adequate to differentiate driving performance and there were no ceiling or floor effects noted with this sample. The principal component analysis did not support a unidimensional constr uct for driving performance. This could be due to the small sample (105) relative to the high number of items (91) or the dynamic nature of the activity of driving. The length of the test could have contributed to the high reliability coefficient, but the ratio of samp le per item may have hindered the reliability of the components analysis. According to the Spearman-Brown formula, the longer the test the more reliable it will be (Anastasi & Urbina, 1997). Driving can be described as the synergistic functioning of multiple systems involving vision, cognition, and sensorimotor pr ocessing. The Rasch analysis provided some insight regarding the proposed hierarchy of driving complexity used to design the road course and hence “selection” of items. This information can assist future road course design and maneuver sequencing base d on the empirically de rived ranking of item

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70 complexity or challenge. The separation ratio which identifies five distinct strata within our sample warrants further investigation. The Global Rating (cri terion) of overall driving performance is based on evaluator j udgment and divided into four levels: (3) Safe, (2) Safe with restricti ons or recommendations, (1) Un safe but remediable and (0) Unsafe not remediable (see experiment I). After reviewing the outcome scale with the driving evaluators, suggesti ons were given to expand th e second rating category to further differentiate restricti ons from to recommendations. Sample characteristics within the empirically derived strata should be compared on the Global Rating scores and driving related skills of vision, cognition, a nd sensorimotor function to provide more information about the functional driv ing abilities of those persons within these groups.

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71 CHAPTER 6 CONCLUSION The assessment of driving ability for olde r adults is of important interest for rehabilitation scientists. Driving is an importa nt activity of daily living that is often taken for granted. Loss of freedom associated with the driving cessation can lead to social isolation or depression. The accepted method of determining driving competence is the behind-the-wheel driving assessm ent, but there has been grea t difficulty with establishing a standardized and objective process. In or der to provide a reliab le and valid outcome measure of driving performance for resear ch being conducted at the University of Florida’s National Older Driver Research and Training Center (NODRTC), several experiments were devised. Experiment I established the criterion validity of an evaluator’s Global Rating Score of driving ability and established the reliability of a behind-the-wheel driving performance assessment. Intraclass correlati on coefficients were used to assess interrater reliability and test-retest reliability of the measurement procedures. Internal consistency of the measure was very high ( .94) and was determined using Chronbach’s alpha, which was comparable to the dic hotomous scoring method (.95) which is commonly used in performance measures. Experiment II was performed to test the standardized methods of road course development and determine the generalizabilit y of the driving performance score across different locations. A complete repeated m easures design was utili zed to test 42 older adults on two different road courses that me t the same design guidelines. There was a

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72 high generalizability coefficient (.89) and th ere was no significant difference between the performance scores on the sepa rate road courses. This exploratory analysis using a single-facet generalizability theory design is limited to Gainesville, FL during daylight hours, and in a southern climate with minima l rain. Inclusion of these factors into a larger sample, multi-site experiment woul d provide valuable information about the abilities of older drivers to drive during in clement weather, temper atures, and variable lighting situations. Experiment III was conducted to explore the scale structure used to score the items (maneuvers) in the JustDrive assessmen t and the unidemensionality of the construct of driving performance. Although the scal ed method provides more information about the severity of error occurring during the maneuver, all four levels were not adequately represented. By collapsing th e scale into three levels, the internal consistency was maintained (.93) and the measurement tool disp layed better fit statis tics (MnSq) for both items and persons using the Rasch model. Th e levels of “verbal cu es required” (1) and “intervention required” (0) were combined to identify “hazardous e rrors” (0) (Di Stefano & Macdonald, 2003; Dobbs, Heller, & Schopflo cher, 1998). The principal component analysis showed the construct of driving performance to be multi-dimensional. There is a limitation with the small sample size used for this analysis. The structure of the road course results in repetition of items (e.g. left turns, right turns, stra ight driving, etc.). Item response analysis combining these maneuvers into individual item scores is needed. Information from this study provides ev idence for the reliability, validity, and generalizability of a standardized met hod to measure behind-the-wheel driving performance of older adults. There is a n eed for consistency in measurement methods

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73 utilized in driving rehabilitation. These methods also provide a reliable and valid outcome measure for driving research with olde r adults. Future res earch to refine the measurement of behind-the-wheel driving performance should include item response analysis to determine the ability of individual items to discriminate the driving ability of older adults. Item reduction research should be done in an atte mpt the streamline the assessment process to more efficiently iden tify at-risk drivers which would be very advantageous in light of the growing nu mber of older adults in our society.

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74 APPENDIX A ROAD PERFORMANCE FORM Start Time______ Date of Assessment___/__/___ Weather Condition______End Time_______ Participant #_______ Road Performance Form Off Road Course Done Score Intervene VC Comments Winn Dixie LotNorthwood Village 0123 Acceleration Intervene VC Braking Intervene VC L turn Intervene VC Visual scanning Speed Regulation Lane maintenance Signaling R turn Intervene VC Visual scanning Speed Regulation Lane maintenance Signaling Parking Intervene VC Visual scanning Speed Regulation Lane maintenance Signaling Vehicle positioning Backing up Intervene VC Visual scanning Speed Regulation Lane maintenance Vehicle positioning OffRoad Low complexity < 30mph Moderate complexity ~30-45mph High complexity > 45mph VC = Verbal Cues Rater # _____ 1 2 Course# ____ 1st 2nd

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75 Understands Shifter Y/N Turn car on/off Y/N Understands Mirror controls Y/N Seatbelt use Y/N Exit lot from behind buildings Turn R onto NW 62nd Ave R turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight at NW 28th Terr. After 2 Speed Regulation humps Turn Left onto NW 31st Terrace *** Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning L onto NW 31st Terr.*** Left turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Right turn (into 57th Place) no stop***

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76 R turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning R at onto NW 33rd Street*** R turn (Simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning L onto NW 58th Place*** Left turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning R onto 33rd Terrace*** R turn (Simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation

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77 Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Right onto 62nd AVE*** R turn (Simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Left onto 33rd St.*** Left turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Right onto 63rd Place R turn (Simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling

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78 Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Left onto 32nd St.*** Left turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Left onto 67th Place*** Left turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Left onto 33rd St.*** Left turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli

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79 Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Left onto 62nd Ave.*** Left turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning R at onto NW 23rd St.*** R turn (Simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Lane Change! I want you to change lanes to Left*** Lane Change Left (moderate) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning

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80 Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning I want you to change lanes to Right* Lane Change Right (moderate) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (simple) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning R onto NW 34th St.*** R turn (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Left on 53rd Ave. Left turn (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Gap acceptance (if no arrow)

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81 Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Right on 24th Blvd.*** R turn (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Straight past NW 45th Ave** (marker) Straight Driving (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Right onto 39th Ave.*** R turn (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli change lanes to left After the light, change lanes to left when safe***

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82 Lane Change Left (moderate) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (moderate) 0123Intervene VC Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning At the next light turn Left onto 34th St.*** Left turn (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Gap acceptance (if no arrow) Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Past Rock Creek*** (marker) Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli R onto NW 16th Ave*** R turn (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning

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83 Speed Regulation Lane maintenance Adjustment to stimuli Lane Change Left (moderate) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Left turn into Publix Lot (past light)*** Left turn (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Gap acceptance Straight Driving (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Right at stop in front of store*** R turn (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (simple) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance

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84 Adjustment to stimuli Right onto 43rd St.***Far Left ahead R turn (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Get into the far left lane*** Lane Change Far Left (High) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Turn left at light onto NW 23rd Ave*** Left turn (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Gap acceptance (if no arrow) Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Left onto 55th St.*** Left onto 55th St.*** Left turn (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance

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85 Signaling Yielding Adjustment to stimuli Gap acceptance (if no arrow) Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Past NW 16th Ave.*** (marker) Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli R onto Newberry Rd. R turn (signalized with yield High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli When safe change lanes to Left*** Lane Change Left (High) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli After NW 62nd St.***

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86 When safe change lanes to Right Lane Change Right (High) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli R onto I-75 North*** R turn (High yield) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Merge onto 75*** Merge (High) 0123Intervene VC Vehicle positioning Signaling Visual scanning Speed Regulation Lane maintenance Yielding Adjustment to stimuli Straight Driving (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli

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87 Lane Change Left (High) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Lane change Lane Change Right (High) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Take the next Exit*** Straight Driving (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Over Lane change to exit Lane Change Right to exit (High) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (High) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Right 39th Ave.(Stay Right) Right onto 39th Ave.***(Stay Right) R turn (signalized moderate) 0123Intervene VC

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88 Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli After NW 75th St.*** When safe change lanes to Left Lane Change Left (moderate) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Straight through 51strd St.** (marker) When safe change lanes to Right*** Lane Change Right (moderate) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli after 43rd St change lanes to Left Immediately after 43rd St.***

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89 change lanes Left turn onto 34th St. Lane Change Left (moderate) 0123Intervene VC Signaling Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Vehicle positioning Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Left onto NW 34th St.*** Left turn (moderate protected) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Gap acceptance (if no arrow) Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Road curves to right***(marker) Straight Driving (moderate) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Adjustment to stimuli Left into Northwood Plaza*** Left turn (High unprotected) 0123Intervene VC Vehicle positioning Visual scanning Speed Regulation Lane maintenance Signaling Yielding Adjustment to stimuli Gap acceptance Park car in front of Ind. Drive*** General Comments and observations:

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90 Name of Evaluator _____________________________ Signature _____________________________ Global Rating:_______( 3) Safe under any condition (2) Safe with restrictions or recommendations (1) Unsafe Remediable (0) Unsafe not remediable Driving Behaviors : Vehicle position (anterior/posterior) (moving or sto pped): Vehicle position refers to the position of the vehicle forward and backward ( anterior posterior) in relation to other vehicles and/or objects and pavement markings. This captures following distance during forward movement and vehicle spacing during lane changes and merges. Examples of errors: Traveling too closely (tailgating), inadequate space cushion during merge or lane cha nge, stopping across a crosswalk or too far back from either pavement markings or other vehicles. Lane Maintenance: Refers to the lateral (side to side) positioning of the vehicle during driving maneuvers (turns, straight drivi ng, lane changes, etc.) and while stopped. Reflects ability to maintain steering control. Examples of errors: Drifting out of driving lane, encroachments on perpendicular traffic or wide turns, parking outside designated space markings. Commonly referred to as lane keeping. Speed Regulation: Reflects ability to follow and maintain Speed Regulation limits and having adequate control of acceleration and braking features of the vehicle. Example of errors: not coming to a complete stop at stop sign, traveling too slow/fast, inadequate merging Speed Regulation, abrupt or inappropriate braking or acceleration. Yielding: Giving right-of-way when appropriate. Yielding refers to the ability to recognize common rules of road safety. Yielding is assess ed at four-way or two-way stop intersections (when other vehicles are present), right turns on red, and merges. Signaling: Proper use of turn signals. Errors in signal use consist of leaving the turn signal on, not using the turn signal when turning, using t he turn signal inappropriately (wrong signal for given turn, signaling too short until maneuver). Visual scanning: Demonstrating visual scanning of driving environment. Examples of errors: Not checking blind spot, not looking through rearview or side mirrors during lane changes, not looking left/right before proceeding through intersection. Eye check mirrors help determine proper scanning. Adjustment to stimuli/traffic signs: Ability to appropriately respond to driving situations. This captures ability to adjust appropriately to changing road sign information, other vehicle

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91 movements, pedestrian movements and ability to recognize potential hazards. Errors would consist of not adjusting Speed Regulation for posted limits, not following proper directions given by evaluator, choosing improper lane from posted signage, improper response to traffic or pedestrian (or cyclist) movement. Gap acceptance: Choosing an appropriately safe time and or spacing distance to cross in front of oncoming traffic (unprotected left turn). Errors in gap acceptance are based on evaluator judgment given the Speed Regulation of oncoming traffic and number of lanes to be crossed. Errors in gap acceptance consist of driver es timates that are both too short and too long for the given Speed Regulation and distance to be traveled. Global Rating (Criterion Standard): Safe (3), Safe wi th restrictions or recommendations (2), Unsafe Remediable (1), Unsafe not remediable (0). Maneuver scores 3 = No Errors 2 = One or more errors without verbal cue or intervention required 1 = Requires verbal cues to modify behavior or maneuver 0 = Situation warrants physical interv ention or illegal (violation) occurs No errors for a given behavior or maneuver result s in score of “three.” Any error in a behavior results in a maximum possible score of “two” for that maneuver. Verbal cueing to complete a task or modify a behavior results in a maximum score of “one” for the given maneuver. Extreme errors (intervention required or warranted) and violations resu lt in a “zero” for that maneuver. A “zero” is also given if another vehicle has to modify their behavior to avoid you.

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92 APPENDIX B ROAD PERFORMANCE FORM II Start T ime______ Date of Assessment___/__/___ Weather Condition_______EndTime_______ Participant #_______ Road Performance Sheet Off Road Course Done Score Intervene VC Comments 19th St. Park Lot 0123 Acceleration Intervene VC Braking Intervene VC L turn Intervene VC Visual scanning Speed Lane maintenance Signaling R turn Intervene VC Visual scanning Speed Lane maintenance Signaling Parking Intervene VC Visual scanning Speed Lane maintenance Signaling Vehicle positioning Backing up Intervene VC Visual scanning Speed Lane maintenance Vehicle positioning Off Road Low complexity ~<30mph Moderate complexity ~30-45mph High complexity > 45mph VC = Verbal Cues Rater # _____ 1 2 Course# _____1st 2nd

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93 Understands Shifter Y/N Turn car on/off Y/N Understands Mirror controls Y/N Seatbelt use Y/N Right out of Parking Lot onto 19th St. Right Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right at Stop onto NW 36th Ave.*** Right Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Left onto NW 21st St.*** Left Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed

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94 Visual scanning Adjustment to stimuli Left onto NW 34th Ave. After speed hump Left onto NW 34th Ave*** Left Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right a stop onto NW 20th St.*** Right Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Take 2nd Right onto NW 32nd Place Right Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli

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95 Right onto NW 21st St. Right at stop onto NW 21st St.*** Right Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right after hump onto NW35th Ave.* Right Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Cross 19th St.*** Left onto NW 18th Terrace*** Left Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli

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96 Left into NW 37th Ave. Left into NW 37th Ave. Left Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Left onto NW 19th St.*** Left Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Left at stop onto NW 31st Place*** Left Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right at Traffic Circle

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97 Right at Traffic Circle*** Right Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right at light onto NW 13th St.*** Right Turn (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Left (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Left at light onto 23rd Ave. Left at light onto 23rd Ave.*** Left Turn (moderate) 0123Intervene VC Signaling

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98 Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Gap Acceptance Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Right (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right at next signal onto NW 6th St.** Right Turn (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Left turn on 8th Lane Change Left (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance

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99 Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Left at 3rd light onto NW 8th Ave.*** Left Turn (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Gap Acceptance Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Right (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli At next signal Right onto Main Street Right onto Main Street *** Right Turn (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation

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100 Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Left (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Right (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Past Depot Ave. Past Depot Ave.*** (marker) Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right at light onto SW 16th Ave.*** Right Turn (moderate) 0123Intervene VC Signaling

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101 Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right at Light onto SW 13th St.*** Right Turn (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Immediate Lane Change Left*** Lane Change Left (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Left at light onto Archer*** Left Turn (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Gap Acceptance

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102 Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Right (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Left (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Left (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Far left turning lane for 34th St.** Left turn onto SW 34th St*** Left Turn (High) 0123Intervene VC Signaling

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103 Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Gap Acceptance Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Right (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lange change Right Lane Change Right (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right at second light onto 39th Blvd** Right Turn (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation

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104 Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Left at light onto Archer*** Left Turn (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Gap Acceptance Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli 2 lane changes to right for 75 Lane Change Right (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Right (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC

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105 Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right turn onto I-75*** Right Turn (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli High Speed Merge 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Left (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning

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106 Adjustment to stimuli Lane Change Right (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Right to Exit (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Keep right for Newberry Rd.*** Right Turn (High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Keep Right past 8th Ave. (marker)*** Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli After 8th Ave. change lanes left*** Lane Change Left (High) 0123Intervene VC Signaling

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107 Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (High) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Left at light onto 43rd St.*** Left at light onto 43rd St.*** Left Turn (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Gap Acceptance Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Lane Change Right (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Past 23rd/16th *** Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed

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108 Visual scanning Adjustment to stimuli Past 39th*** Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Change lanes left for Millhopper Lane Change Left (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Turn left into McDonalds entrance*** Left Turn (UPL)(High) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Gap Acceptance Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right turn in front of store*** Right Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding

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109 Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Left turn at end of storefront*** Left Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (simple) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right Turn (simple) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Right turn onto 53rd Ave*** Right Turn (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Past Appletree*** Straight Driving (moderate) 0123Intervene VC Lane maintenance

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110 Vehicle positioning Speed Visual scanning Adjustment to stimuli Right onto 34th St. Right onto 34th St.*** Right Turn (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli Straight Driving (moderate) 0123Intervene VC Lane maintenance Vehicle positioning Speed Visual scanning Adjustment to stimuli Right turn into Northwood Plaza*** Right Turn (moderate) 0123Intervene VC Signaling Visual Scanning Vehicle Positioning Lane Maintenance Speed Regulation Yielding Adjustment to Stimuli END COURSE General Comments and observations: Name of Evaluator _____________________________ Signature _____________________________

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111 Global Rating:_______ (3) Safe under any condition (2) Safe with restrictions or recommendations (2) Unsafe Remediable (1) Unsafe not remediable Driving Behaviors : Vehicle position (anterior/posterior) (moving or sto pped): Vehicle position refers to the position of the vehicle forward and backward ( anterior posterior) in relation to other vehicles and/or objects and pavement markings. This captures following distance during forward movement and vehicle spacing during lane changes and merges. Examples of errors: Traveling too closely (tailgating), inadequate space cushion during merge or lane cha nge, stopping across a crosswalk or too far back from either pavement markings or other vehicles. Lane Maintenance: Refers to the lateral (side to side) positioning of the vehicle during driving maneuvers (turns, straight drivi ng, lane changes, etc.) and while stopped. Reflects ability to maintain steering control. Examples of errors: Drifting out of driving lane, encroachments on perpendicular traffic or wide turns, parking outside designated space markings. Commonly referred to as lane keeping. Speed: Reflects ability to follow and maintain speed limits and having adequate control of acceleration and braking features of the vehicle. Example of errors: not coming to a complete stop at stop sign, traveling too slow/fast, i nadequate merging speed, abrupt or inappropriate braking or acceleration. Yielding: Giving right-of-way when appropriate. Yielding refers to the ability to recognize common rules of road safety. Yielding is assess ed at four-way or two-way stop intersections (when other vehicles are present), right turns on red, and merges. Signaling: Proper use of turn signals. Errors in signal use consist of leaving the turn signal on, not using the turn signal when turning, using t he turn signal inappropriately (wrong signal for given turn, signaling too short until maneuver). Visual scanning: Demonstrating visual scanning of driving environment. Examples of errors: Not checking blind spot, not looking through rearview or side mirrors during lane changes, not looking left/right before proceeding through intersection. Eye check mirrors help determine proper scanning. Adjustment to stimuli/traffic signs: Ability to appropriately respond to driving situations. This captures ability to adjust appropriately to changing road sign information, other vehicle movements, pedestrian movements and ability to recognize potential hazards. Errors would consist of not adjusting speed for posted limits, not following proper directions given by evaluator, choosing improper lane from posted signage, improper response to traffic or pedestrian (or cyclist) movement. Gap acceptance: Choosing an appropriately safe time and or spacing distance to cross in front of oncoming traffic (unprotected left turn). Errors in gap acceptance are based on evaluator judgment given the speed of oncoming traffic and number of lanes to be crossed. Errors in gap acceptance consist of driver estimates that are both too short and too long for the given speed and distance to be traveled. Global Rating (Criterion Standard): Safe (3), Safe wi th restrictions or recommendations (2), Unsafe Remediable (1), Unsafe not remediable (0).

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112 Maneuver scores 3 = No Errors 2 = One or more errors without verbal cue or intervention required 1 = Requires verbal cues to modify behavior or maneuver 0 = Situation warrants physical interv ention or illegal (violation) occurs No errors for a given behavior or maneuver result s in score of “three.” Any error in a behavior results in a maximum possible score of “two” for that maneuver. Verbal cueing to complete a task or modify a behavior results in a maximum score of “one” for the given maneuver. Extreme errors (intervention required or warranted) and violations resu lt in a “zero” for that maneuver. A “zero” is also given if another vehicle has to modify their behavior to avoid you.

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113 APPENDIX C INFORMED CONSENT TO PARTICIPATE IN RESEARCH IRB# 625-2004 Informed Consent to Pa rticipate in Research and Authorization for Collection, Use, and Disclosure of Protected Health Information You are being asked to take part in a res earch study. This form provides you with information about the study and seeks your authorization for the collection, use and disclosure of your protected health informa tion necessary for the study. The Principal Investigator (the person in charge of this research) or a representative of the Principal Investigator will also describe this study to you an d answer all of your questions. Your participation is entirely voluntar y. Before you decide whether or not to take part, read the information below and ask questions about a nything you do not unders tand. If you choose not to participate in this study you will not be penalized or lose any benefits to which you would otherwise be entitled. 1. Name of Participant ("Study Subject") _____________________________________________________________________ 2. Title of Research Study Reliability and Validity of Behind-the-Wheel Driving Asse ssment of Older Adults

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114 3. Principal Investigator and Telephone Number(s) Michael D. Justiss, PhD(c), MOT, OTR/L, CDI University of Florida Department of Occupational Therapy College of Public Hea lth and Health Professions P.O Box 100164 Gainesville, FL 32610 352-273-6620 4. Source of Funding or Other Material Support University of Florida, Centers for Dis ease Control and Prevention (CDC), and the Federal Highway Administration (FHWA) 5. What is the purpose of this research study? The purpose of this study is to determin e if there is a difference in driving performance scores between two separate road courses. 6. What will be done if you ta ke part in this research study? You have been selected for participation in this research project by seeking services from the University of Florida’s I ndependence Drive driving assessment and rehabilitation center in Gainesville or from participation in an existing research project through the University of Florida’s National Older Driver Research and Training Center (NODRTC) (IRB#445-2003). For those NOT Participating in the National Older Driver Research Project (IRB#4452003): If you agree to take part in this research project, you’ll ha ve to take a few extra tests during the office portion of your drivi ng evaluation, before you take any on-road tests. For those Participating in the National Older Driver Research Project (IRB#4452003): If you agree to take part in this research project, no additio nal tests are needed during the office portion of your driving evaluation. The normal procedure when going to Indepe ndence Drive for a co mprehensive driving evaluation includes going to the Independence Dr ive office to take a series of tests and then going out, in the test car, for an on-road test. When the office appointment is scheduled, the driving rehabilitation specialist recommends that you do not drive to the evaluation and have an alternative method of transportation until after the evaluation

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115 has been completed and results reviewed. The normal office visit starts out with one of the Independence Drive staff members or a University of Florida research assistan t taking information about your driver’s license, driving history, medical and health history, the medications you are currently taking, and other personal information such as your address, date of birth, and phone number. Then you will undergo vision test s, a computer-based test, and paper-andpencil tests. These tests look at different t ypes of memory, how y ou think, the ability to pay attention, and knowledge of road rules. The evaluator will then test your strength, flexibility, and coordination. After the normal office visit is completed, you’ll take the on-road driving test. This starts out with the driving rehabilitation speci alist driving you in the test car to the beginning of the test course. The road test takes about an hour to complete. After completion of both the office and road test , the driving rehabilitation specialist or research assistant will schedule a second road test to be give n on a different day but within one week (preferably the next day). The second road test will be conducted like the first, except in a differ ent location still in the Gainesv ille area. After completion of the second road test the driving rehabilita tion specialist will discuss your performance and provide written recommendations that ma y improve your ability to travel safely. The difference from the normal office visit at Independence Drive, if you agree to participate in this research st udy, are a few extra tests in the office prior to the first road test, and the addition of a second road test on a different day. There are no tests given in the office before the second road test. Ag ain, the extra tests in the office apply only to those NOT Participating in the existing National Older Driver Research Project. 6.a. What procedures would be done as part of your normal clinical care (even if you did not participate in this research)? The normal procedure when going to I ndependence Drive for a comprehensive driving evaluation includes going to the Inde pendence Drive office to take a series of tests and then going out, in th e test car, for an on-road test. 6.b. What procedures will be done only because you ar e participating in this research study? If you agree to participate in this research project, the extra office tests include those called the Functional Independence Measure, the Instrumental Activities of Daily Living Scale, the Jette Pain Scale, and th e Geriatric Depression Sc ale. All of these tests are questionnaires asked by the research assistant in the office, before any road tests. The second road test is given only to those who agree to participate in this research study. The Functional Independence M easure asks you how well you are able to complete

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116 basic self-care tasks by yourself such as dressing, bathin g, and eating. The Instrumental Activities of Daily Living Sc ale asks you how well you are able to complete more complex tasks by yourself such as managi ng your checkbook or going shopping. The Jette Pain Scale asks ho w much pain you may experience while completing everyday tasks and the Geriatric Depression Scale asks you how you have been feeling. For those Participating in the National Older Driv er Research Project (IRB#4452003): These extra office tests have alrea dy been collected by telephone and will be accessed for the purposes of this study. A diagram has been provided to help explai n the overall procedure when you come for an evaluation: Arrive at Independence Drive Center Road Test 1 hour Office Tests Given 1.5 hours Those participating in Older Driver Pro j ect Those NOT participating in Older Driver Pro j ect Written consent for Older Driver Written consent for Road Test Written consent for Road Test Not participating in Research Extra Tests Given 20 minutes Second Road Test 1 hour Office Tests Given 1.5 hours Office Tests Given 1.5 hours Road Test 1 hour Road Test 1 hour Second Road Test 1 hour Office Tests Given 1.5 hours Road Test 1 hour Feedback Provided Feedback Provided Feedback Provided Feedback Provided

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117 If you have any questions now or at any time during the study, you may contact the Principal Investigator lis ted in #3 of this form. 7. If you choose to participate in this study, how long will yo u be expected to participate in the research? The procedure for a complete driving evaluation takes about 2.5 hours. For those NOT Participating in the National Older Driver Research Project (IRB#4452003): Participation in the Ro ad Test Study will ta ke about an additional 1 hour 20 minutes (total time of about 4 hours). For those Participating in the National Older Driver Research Project (IRB#4452003): Participation in the Road Test Study will take about an additional 1 hour (total time of about 3.5 hours). 8. How many people are expected to participate in this research? We expect to enroll 50 subjects to participate in this project. 9. What are the possible discomforts and risks? You may become fatigued by the additional tests added to the normal procedure. You may feel uncomfortable disclosing pers onal information. If you are found to be unsafe to drive by the driving rehabilitation sp ecialist, the state in which your driver’s license was issued has to be notified. Th is report may result in state action, which could result in forfeiture of your license. However, this procedure is no different for someone who does not participat e in this research study. This study may include risks th at are unknown at this time. Participation in more than one research st udy or project may furthe r increase the risks to you. Please inform the Principal Investigat or (listed in #3 of this consent form) or the person reviewing this consent with you before enrolling in this or any other research study or project. Throughout the study, the researchers will notify you of new in formation that may become available and might affect your decision to remain in the study.

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118 If you wish to discuss the information a bove or any discomforts you may experience, you may ask questions now or call the Principa l Investigator or contact person listed on the front page of this form. 10a. What are the possible benefits to you? You will have the opportunity to have a driving rehabilitation specialist examine those things that are important for driving safely. If the driving specialist finds things that may affect your driving, the driving specia list may be able to provide services, or refer you to someone else, who can assist wi th driving safely. If you are not able to continue driving safely, the driving speci alist can inform you on ways of getting around without driving yourself. 10b. What are the possible benefits to others? Findings from this research may be used to find out the things that make driving unsafe for some older people. This study may provide the researchers with tools that can be used to identify those who are safe drivers and those w ho are unsafe drivers, which could make driving safer for everyone . This research may be able to show what types of roadway conditions may be be tter for older drivers and affect the way roadways are constructed in the future. This research may show th at identification of those that are unsafe to drive, or roadwa y conditions that are unsafe, may reduce the amount of accidents in whic h older people are involved. 11. If you choose to take pa rt in this research study, will it cost you anything? No. Costs for routine medical care proce dures that are not being done only for the study will be charged to you or your insurance. 12. Will you receive compensation for taking part in this research study? Participants will be compensated $15 total for completing the additional on-road evaluation and clinical assessments.

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119 13. What if you are injure d because of the study? If you experience an injury that is dire ctly caused by this study, only professional consultative care that you receive at the Univ ersity of Florida Health Science Center will be provided without charge. However, hospital expenses will have to be paid by you or your insurance provider. No other co mpensation is offered. Please contact the Principal Investigator listed in Item 3 of this form if you e xperience an injury or have any questions about any discomforts that yo u experience while participating in this study. 14. What other options or trea tments are available if you do not want to be in this study? The option to taking part in this study is doi ng nothing. If you do not want to take part in this study, tell the Principal Investigat or or his/her assistan t and do not sign this Informed Consent Form. 15a. Can you withdraw from this research study? You are free to withdraw your consent and to st op participating in this research study at any time. If you do withdraw your consent, there will be no penalty, and you will not lose any benefits you are entitled to. If you decide to withdraw y our consent to participate in this research study for any reason, you should contact Michael D. Justiss at (352) 273-6620. If you have any questions regarding your ri ghts as a research su bject, you may phone the Institutional Review Board (IR B) office at (352) 846-1494. 15b. If you withdraw, can information abou t you still be used and/or collected? No. If you withdraw from th is study, all of the informa tion previously collected will be destroyed and no further information will be collected about you. 15c. Can the Principal Investigator wit hdraw you from this research study? You may be withdrawn from the study w ithout your consent for the following reasons: You do not qualify to be in the study becau se you do not meet the study requirements: ask the Principal Investigator if you w ould like more information about this.

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120 16. If you agree to participate in this res earch study, the Princi pal Investigator will create, collect, and use private information about you and your health. Once this information is collected, how w ill it be kept secret (confide ntial) in order to protect your privacy? Information collected about y ou and your health (called prot ected health information), will be stored in locked fili ng cabinets or in comp uters with security passwords. Only certain people have the legal right to revi ew these research re cords, and they will protect the secrecy (confidentiality) of these re cords as much as th e law allows. These people include the researchers fo r this study, certain University of Florida officials, the hospital or clinic (if any) involved in this research, and the Institutional Review Board (IRB; an IRB is a group of people who are re sponsible for looking af ter the rights and welfare of people taking part in research). Otherwise your research records will not be released without your permission unl ess required by law or a court order. If you participate in this research study, th e researchers will collect , use, and share your protected health information with others. Items 17 to 26 below describe how this information will be collect ed, used, and shared. 17. If you agree to participate in this research study, what protected health information about you may be collect ed, used and shared with others? Your protected health inform ation may be collected, used, and shared with others to determine if you can participate in the study, and then as part of your participation in the study. This information can be gathered from you or your past, current or future health records, from procedur es such as physical examina tions, x-rays, blood or urine tests or from other procedures or tests. This informatio n will be created by receiving study treatments or participating in study pr ocedures, or from your study visits and telephone calls. More specifically, the follo wing information may be collected, used, and shared with others: Demographic information, including age and date of birth, gender, driver license number, education, income, co mplete medical history, current medical conditions, and medication. Tests of vision, hearing, the ability to pay attention to two things that are happening at the same time, and alertness. Outcome data collected from your participation in this study. If you agree to be in this research study, it is possible that some of the information collected might be copied into a "limited da ta set" to be used for other research purposes. If so, the limited data set ma y only include information that does not directly identify you. For ex ample, the limited data set cannot include your name, address, telephone number, social secu rity number, or any other photographs,

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121 numbers, codes, or so forth that link you to th e information in the li mited data set. If used, limited data sets have legal agr eements to protect your identity and confidentiality and privacy. 18. For what study-related purposes will your protected health information be collected, used, and sh ared with others? Your protected health inform ation may be collected, used, and shared with others to make sure you can participate in the re search, through your participation in the research, and to evaluate the results of th e research study. Mo re specifically, your protected health information may be collect ed, used, and shared with others for the following study-related purpose(s): To make sure you are eligible to participate in the study To find methods that can help determ ine if a driver is safe or not To see what affects medical conditio ns and medications have on driving and driving-related abilities 19. Who will be allowed to coll ect, use, and share your protected health information? Your protected health inform ation may be collected, used, and shared with others by: the study Principal Investigator Michae l D. Justiss, MOT, OTR/L, CDI and required staff at the National Older Dr iver Research and Training Center other professionals at the University of Florida or Shands Hospital that provide study-related treatment or procedures the University of Florida Institutional Review Board 20. Once collected or used, who may your pr otected health information be shared with? Your protected health inform ation may be shared with: related study sponsors: the Centers fo r Disease Control and Prevention, and the Federal Highwa y Administration. United States and foreign governmental agencies who are responsible for overseeing research, such as the Food and Drug Administration, the Department of Health and Human Se rvices, and the Office of Human Research Protections Government agencies wh o are responsible for ove rseeing public health concerns such as the Centers for Di sease Control and Federal, State and local health departments

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122 21. If you agree to participate in this resea rch, how long will you r protected health information be used and shared with others? Protected health information will be us ed and disclosed until 09/30/2015. If you withdraw your permission for the use a nd disclosure of your protected health information, then your information will be removed from the database. 22. Why are you being asked to allow the colle ction, use and sharing of your protected health information? Under a new Federal Law, researchers cannot collect, use, or share with others any of your protected health informa tion for research unless you a llow them to by signing this consent and authorization. 23. Are you required to sign th is consent and authorizatio n and allow the researchers to collect, use and share with others your protected health information? No, and your refusal to sign will not affect your treatment , payment, enrollment, or eligibility for any benefits out side this research study. However, you cannot participate in this research unless you allow the coll ection, use and sharing of your protected health information by signing this consent/authorization. 24. Can you review or co py your protected health inform ation that has been collected, used or shared with others under this authorization? You have the right to review and copy your protected health information. However, you will not be allowed to do so until after the study is finished. 25. Is there a risk that your protected health information could be given to others beyond your authorization? Yes. There is a risk that information recei ved by authorized persons could be given to others beyond your authorizati on and not covered by the law.

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123 26. Can you revoke (cancel) your authorizatio n for collection, use and sharing with others of your protected health information? Yes. You can revoke your authorization at any time before, during, or after your participation in the research. If you revoke, no new information will be collected about you. However, information th at was already collected ma y still be used and shared with others if the researchers have relied on it to complete and protect the validity of the research. You can revoke your authoriza tion by giving a written request with your signature on it to the Principal Investigator. 27. How will the researcher(s) benefi t from your being in this study? In general, presenting research results helps the career of a scien tist. Therefore, the Principal Investigator may benefit if the results of this study are presented at scientific meetings or in scientific journals.

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124 28. Signatures As a representative of this study, I have ex plained to the participant the purpose, the procedures, the possible benefits, and the risks of this research study; the alternatives to being in the study; and how the participan t’s protected health information will be collected, used, and shared with others: ____________________ _________________________ ______________ _______ Signature of Person Obtaining Consent and Aut horization Date You have been informed about this study’s purpose, procedures, possible benefits, and risks; the alternatives to being in the st udy; and how your protected health information will be collected, used and shar ed with others. You have re ceived a copy of this Form. You have been given the opportunity to ask questions before you sign, and you have been told that you can ask other questions at any time. You voluntarily agree to participate in this study. You hereby authorize the collection, use and sharing of your protected health in formation as described in sections 17-26 above. By signing this fo rm, you are not waiving a ny of your legal rights. ____________________ _________________________ ______________ _______ Signature of Person Consenting and Authorizing Date Would you be willing to be c ontacted in the future to hear about more opportunities to participate in research? YES NO _____________________________________________ ____________________ Signature of Person Consenting a nd Authorizing Date

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125 APPENDIX D RASCH CONTROL FILE Title="Item Response Analysis of a Driving Performance Assessment for Older Adults" CODES=0 1 2 3 NEWSCORE=0 0 2 3 NAME1=1 NAMELEN=3 NI=91 ITEM1=6 DISCRIM=YES TABLES=111111111111111111111 &END RTS1 SDS1 SDS2 LTS1 SDS3 RTS2 SDS4 RTS3 SDS5 LTS2 SDS6 RTS4 SDS7 RTS5 SDS8 LTS3 SDS9 RTS6 SDS10 LTS4 SDS11 LTS5 SDS12 LTS6 SDS13 LTS7 SDS14 RTS7 SDS15 LCM1 SDS16 LCM2 SDS17 RTM1 SDM1 LTM1 SDM2 RTM2 SDS18 SDS19 RTM3 SDM3 LCM3 SDM4 LTM2 SDM5

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126 SDM6 RTM4 SDM7 LCM4 SDM8 LTH1 SDS20 RTS8 SDS21 RTH1 LCH1 SDM9 LTH2 SDM10 LTM3 SDM11 SDM12 RTH2 SDH1 LCH2 SDH2 LCH3 SDH3 RTH3 SDH4 HSM SDH5 LCH4 SDH6 LCH5 SDH7 LCH6 SDH8 RTM5 SDM13 LCM5 SDM14 LCM6 SDM15 LCM7 SDM16 LTM4 SDM17 SDM18 LTH3 END NAMES 1 3223233333333333333333333333333333333323333333323333332333223233332223333323333333223322333333 2 2213233333232333232323232323232323233223323333323023333323222232002323333323233323333233333333 3 1212313333333333232313232331322321232222322331112230322333333222322222222111111221203012123321 4 1112323333332333233323332323232311233213322221122222223323223322321333322111111223322222123322 6 3223223333332333333333333323332333333323333333323333333323223331033333333333333333333333332333 7 2222323333222223233323322223222323332322323233222223222333222222321223330323323332332232332332 8 1222222323233333231333322333222222233313323133313222231323223220332221122311010322302222322330 9 0222223222332323133223332323222222223323321202020023322323122122220201022222202122202320121220 10 2112223322323232333323333332323233333323221233333232222323211112322223303333333333333233333332 11 1112232323232232332322222322222323222222232233220023301322222212121233333320313331302332232033 12 1212223323233332333333232323222332222222222232020022231323222222000320222222202232102332232000 13 3223223332333333333333323323232233332323322333330332331323333333333333333333333333303333333333 14 2213323333232333233323332323232323333223233233330323333323223232322223222311113333332320232333 15 2113223233332333333323233333323323333222323232332230233323223322223322332323222331322033303333 16 2112222223232222222232222323323223223222222222222222223222122122222112221112000222322222233221 17 2222333333333333133322233333232333232323233332322323233313321222332323123323332332333221223333 18 2112333233232333333333332323232223332313322233322222333322223322002122333332233233231332332231 19 2213233333332333232333332323232323333313322233323322333323333222001320333323323233222333333231 20 2123223222232333332333232333322333333323222322332233333333223222332322333322333333333333332333 21 3122233332333333333333232333222233232333333233333332333323233333222333333323333333333333332332 22 3122333333232333233333332323232323332323323333332223333323222332332333333333333333332233332333 23 3123333333222333333332332323233333333223222333333333333322223332332333233322223333233233232233 24 3223333333232333333333332333333333333333333333333333333323233232333333333323333333333233333333 25 2112333333333333333333232333232323222323323231333323332123200212132120322322223333223313232331

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127 26 3213333333233333333333333333332233333323333232220033233333323222023233333323333333333330322333 27 3222233333323333333333332323232333333333333232332333233323223332332333233323333333333323333333 28 3112333323233333333333333323332323332323322233223223333333223232322333333332222233323322332333 29 3212333333233333333333333323322322333223320333333333233333333222222333333333333333323332332333 30 2122332333232333232323332323232322232223322232322233233323223222322322333323232323222323332333 31 3213333333232333333333333323232333333322323233223333331323333322233333333323333333332323322333 32 3223123233323323333333333333333333333323323332333333333333333333332333333333233333333333333333 33 2222333332333333133333333333322222233223323232323233222323332222233332332312121333222312121231 34 3112333333232333332333332333232323232323333233323323323323223232021323233322222333232330332332 35 3112332333232333232323232323232323232323333333323323333333223232022232333322333333333022233333 36 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129 APPENDIX E PRINCIPAL COMPONENT ANALYSI S AND FACTOR (3) LOADINGS The SAS System 1 The FACTOR Procedure Initial Factor Method: Principal Components Prior Communality Estimates: ONE Eigenvalues of the Correlation Matrix: Total = 91 Average = 1 Eigenvalue Difference Proportion Cumulative 1 21.5425964 16.8789038 0.2367 0.2367 2 4.6636926 0.7622490 0.0512 0.2880 3 3.9014436 0.7925048 0.0429 0.3309 4 3.1089388 0.3544599 0.0342 0.3650 5 2.7544790 0.0994917 0.0303 0.3953 6 2.6549873 0.1551376 0.0292 0.4245 7 2.4998497 0.0874215 0.0275 0.4519 8 2.4124282 0.2138549 0.0265 0.4784 9 2.1985733 0.0313474 0.0242 0.5026 10 2.1672259 0.0405502 0.0238 0.5264 11 2.1266756 0.1166194 0.0234 0.5498 12 2.0100562 0.0726798 0.0221 0.5719 13 1.9373764 0.1320869 0.0213 0.5932 14 1.8052895 0.1080030 0.0198 0.6130 15 1.6972865 0.0719261 0.0187 0.6317 16 1.6253604 0.1244523 0.0179 0.6495 17 1.5009081 0.0414687 0.0165 0.6660 18 1.4594394 0.0368476 0.0160 0.6821 19 1.4225918 0.0798137 0.0156 0.6977 20 1.3427781 0.0669182 0.0148 0.7124 21 1.2758599 0.0846328 0.0140 0.7265 22 1.1912272 0.0282123 0.0131 0.7396 23 1.1630149 0.0618766 0.0128 0.7523 24 1.1011383 0.0403185 0.0121 0.7644 25 1.0608197 0.0138139 0.0117 0.7761 26 1.0470059 0.0241865 0.0115 0.7876 27 1.0228193 0.1197738 0.0112 0.7988 28 0.9030456 0.0619895 0.0099 0.8088 29 0.8410561 0.0200226 0.0092 0.8180 30 0.8210335 0.0087666 0.0090 0.8270 31 0.8122669 0.0225305 0.0089 0.8359 32 0.7897364 0.0512709 0.0087 0.8446 33 0.7384655 0.0172065 0.0081 0.8527 34 0.7212590 0.0599786 0.0079 0.8607 35 0.6612804 0.0117757 0.0073 0.8679 36 0.6495047 0.0260152 0.0071 0.8751 37 0.6234895 0.0257716 0.0069 0.8819

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130 38 0.5977179 0.0149955 0.0066 0.8885 39 0.5827223 0.0263216 0.0064 0.8949 40 0.5564007 0.0362740 0.0061 0.9010 41 0.5201267 0.0132295 0.0057 0.9067 42 0.5068972 0.0151442 0.0056 0.9123 43 0.4917531 0.0263286 0.0054 0.9177 44 0.4654245 0.0233634 0.0051 0.9228 45 0.4420611 0.0148891 0.0049 0.9277 46 0.4271720 0.0157788 0.0047 0.9324 47 0.4113932 0.0236575 0.0045 0.9369 48 0.3877357 0.0321559 0.0043 0.9411 49 0.3555798 0.0123314 0.0039 0.9451 50 0.3432484 0.0074008 0.0038 0.9488 51 0.3358476 0.0326001 0.0037 0.9525 52 0.3032475 0.0104689 0.0033 0.9558 53 0.2927786 0.0436270 0.0032 0.9591 54 0.2491516 0.0052143 0.0027 0.9618 55 0.2439373 0.0093955 0.0027 0.9645 56 0.2345418 0.0061817 0.0026 0.9671 57 0.2283601 0.0042318 0.0025 0.9696 58 0.2241283 0.0248109 0.0025 0.9720 59 0.1993174 0.0080439 0.0022 0.9742 60 0.1912735 0.0060055 0.0021 0.9763 61 0.1852680 0.0184970 0.0020 0.9784 62 0.1667710 0.0084795 0.0018 0.9802 63 0.1582915 0.0061890 0.0017 0.9819 64 0.1521025 0.0051297 0.0017 0.9836 65 0.1469728 0.0189385 0.0016 0.9852 66 0.1280343 0.0091876 0.0014 0.9866 67 0.1188467 0.0055884 0.0013 0.9879 68 0.1132583 0.0064853 0.0012 0.9892 69 0.1067730 0.0089641 0.0012 0.9904 70 0.0978089 0.0109922 0.0011 0.9914 71 0.0868168 0.0032888 0.0010 0.9924 72 0.0835280 0.0124755 0.0009 0.9933 73 0.0710524 0.0033797 0.0008 0.9941 74 0.0676727 0.0038698 0.0007 0.9948 75 0.0638029 0.0092958 0.0007 0.9955 76 0.0545071 0.0010946 0.0006 0.9961 77 0.0534126 0.0066457 0.0006 0.9967 78 0.0467669 0.0035944 0.0005 0.9972 79 0.0431725 0.0064967 0.0005 0.9977 80 0.0366758 0.0058302 0.0004 0.9981 81 0.0308456 0.0025896 0.0003 0.9984 82 0.0282560 0.0051061 0.0003 0.9988 83 0.0231499 0.0023366 0.0003 0.9990 84 0.0208133 0.0044021 0.0002 0.9992 85 0.0164112 0.0018867 0.0002 0.9994 86 0.0145245 0.0028386 0.0002 0.9996 87 0.0116859 0.0009223 0.0001 0.9997 88 0.0107636 0.0036524 0.0001 0.9998 89 0.0071112 0.0014751 0.0001 0.9999 90 0.0056361 0.0021837 0.0001 1.0000 91 0.0034524 0.0000 1.0000 3 factors will be retained by the NFACTOR criterion.

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131 The FACTOR Procedure Initial Factor Method: Principal Components Factor Pattern Factor1 Factor2 Factor3 i78 LCH6 0.75259 -0.04705 -0.01622 i88 LTM4 0.72652 -0.14096 -0.05664 i80 RTM5 0.71407 -0.25254 -0.06086 i77 SDH7 0.70803 -0.23187 -0.08393 i75 SDH6 0.70238 -0.09306 0.03872 i76 LCH5 0.70112 -0.03041 0.06009 i79 SDH8 0.69260 -0.29714 -0.12206 i19 SDS10 0.68215 -0.08486 -0.18763 i66 LCH2 0.66984 -0.12361 0.08108 i35 SDM1 0.66142 -0.10261 0.10516 i73 SDH5 0.63586 -0.28739 -0.19566 i74 LCH4 0.63564 -0.17110 -0.06639 i70 RTH3 0.63348 -0.20053 -0.12685 i91 LTH3 0.61736 -0.18113 0.03896 i67 SDH2 0.59833 -0.32241 0.05425 i8 RTS3 0.59546 0.19422 -0.23081 i43 LCM3 0.59388 0.13954 0.20636 i83 SDM14 0.58390 -0.27220 -0.19273 i84 LCM6 0.57680 -0.15178 0.19535 i36 LTM1 0.56821 0.00201 0.23332 i37 SDM2 0.56695 0.26743 0.02443 i86 LCM7 0.56501 -0.28336 -0.08814 i5 SDS3 0.54740 -0.00332 -0.01175 i40 SDS19 0.54555 0.04627 -0.03988 i68 LCH3 0.54399 -0.04725 0.08602 i29 SDS15 0.54336 0.20439 -0.07490 i69 SDH3 0.54259 -0.36598 -0.00914 i82 LCM5 0.54165 -0.41434 -0.01622 i61 LTM3 0.54164 0.12740 0.08462 i81 SDM13 0.53845 -0.29955 -0.22814 i72 HSM 0.53813 -0.28583 -0.06069 i58 SDM9 0.53777 0.27340 0.26261 i71 SDH4 0.53668 -0.33862 -0.03952 i89 SDM17 0.53177 -0.25781 -0.03884 i54 RTS8 0.53033 0.11002 -0.28575 i47 SDM6 0.52330 -0.18360 -0.03621 i34 RTM1 0.51582 0.04149 0.18556 i90 SDM18 0.49910 -0.11090 0.23420 i46 SDM5 0.49675 -0.01221 -0.16354 i59 LTH2 0.48884 0.28588 0.12336 i32 LCM2 0.48194 0.07331 0.26503 i62 SDM11 0.48124 0.13923 -0.07050 i87 SDM16 0.47481 -0.32705 -0.03468 i42 SDM3 0.47433 0.32653 -0.03280 i27 SDS14 0.47418 0.12888 -0.24368 i38 RTM2 0.47350 -0.20704 0.19707 i24 LTS6 0.46553 0.20485 0.33934 i6 RTS2 0.46523 -0.01660 0.20933 i13 SDS7 0.46466 0.28121 -0.16930 i44 SDM4 0.45817 0.05247 -0.19349 i49 SDM7 0.45476 0.21297 -0.15659 i16 LTS3 0.45241 -0.15836 -0.06598

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132 i56 RTH1 0.43319 0.12115 0.27441 i48 RTM4 0.42674 0.29093 -0.23109 i4 LTS1 0.41718 0.24454 -0.28979 i60 SDM10 0.41564 0.26351 -0.06012 i51 SDM8 0.41563 0.18608 -0.19285 i63 SDM12 0.41556 -0.16627 0.29647 i23 SDS12 0.40468 0.25602 -0.28653 i50 LCM4 0.39183 0.07462 0.37396 i85 SDM15 0.39166 -0.26086 -0.01076 i7 SDS4 0.38498 0.23747 -0.16734 i65 SDH1 0.38382 -0.17007 0.21919 i33 SDS17 0.38306 -0.18227 -0.17084 i31 SDS16 0.38264 0.12946 -0.11623 i17 SDS9 0.37939 0.37924 -0.12872 i3 SDS2 0.37581 0.24138 0.22275 i20 LTS4 0.36997 -0.06867 -0.19386 i21 SDS11 0.36929 0.27841 -0.17512 i41 RTM3 0.36514 0.18370 0.20147 i39 SDS18 0.33700 0.26456 -0.21654 i22 LTS5 0.32290 0.16292 -0.09476 i57 LCH1 0.30903 0.30662 0.01096 i55 SDS21 0.29451 0.11633 0.01051 i53 SDS20 0.29168 0.21748 -0.16235 i18 RTS6 0.28997 0.11647 0.05809 i14 RTS5 0.28312 0.26085 -0.14865 i25 SDS13 0.35048 0.47940 -0.02399 i15 SDS8 0.39155 0.44875 -0.16105 i9 SDS5 0.12132 0.42445 -0.18484 i52 LTH1 0.23766 0.36616 -0.32628 i12 RTS4 0.30132 0.20332 0.54791 i10 LTS2 0.31729 0.19006 0.50730 i26 LTS7 0.31583 0.30480 0.42283 i1 RTS1 0.11997 0.27355 0.40827 i28 RTS7 0.36351 0.17579 0.38889 i30 LCM1 0.33256 0.02564 0.35307 i64 RTH2 0.21266 -0.20751 0.33254 i2 SDS1 0.31026 0.19752 0.31544 i11 SDS6 0.03092 0.21481 -0.26677 i45 LTM2 0.35828 0.04596 -0.36173 Variance Explained by Each Factor Factor1 Factor2 Factor3 21.542596 4.663693 3.901444

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133 The SAS System 5 The FACTOR Procedure Initial Factor Method: Principal Components Final Communality Estimates: Total = 30.107733 i1 i2 i3 i4 i5 i6 0.25590374 0.23478035 0.24911731 0.31781409 0.29979333 0.26053961 i7 i8 i9 i10 i11 i12 0.23260114 0.44556402 0.22904575 0.39415125 0.11826578 0.43234082 i13 i14 i15 i16 i17 i18 0.32364764 0.17029727 0.38062469 0.23410559 0.30432859 0.10102411 i19 i20 i21 i22 i23 i24 0.50772797 0.17917696 0.24455731 0.13978862 0.31141350 0.37383300 i25 i26 i27 i28 i29 i30 0.35323744 0.37143445 0.30083537 0.31427746 0.34262376 0.23591404 i31 i32 i33 i34 i35 i36 0.17668774 0.30787709 0.20914345 0.30222072 0.45905995 0.37730483 i37 i38 i39 i40 i41 i42 0.39354984 0.30590076 0.23045317 0.30135485 0.20766482 0.33268811 i43 i44 i45 i46 i47 i48 0.41474715 0.25011527 0.26132525 0.27365878 0.30885968 0.32015250 i49 i50 i51 i52 i53 i54 0.27667941 0.29894005 0.24456621 0.29701504 0.15872974 0.37500355

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134 i55 i56 i57 i58 i59 i60 0.10037764 0.27762888 0.18963427 0.43290583 0.33590352 0.24581405 i61 i62 i63 i64 i65 i66 0.31676113 0.25594861 0.28823069 0.19886970 0.22428246 0.47054414 i67 i68 i69 i70 i71 i72 0.46488722 0.30555382 0.42843529 0.45759535 0.40424751 0.37496615 i73 i74 i75 i76 i77 i78 0.52518967 0.43771627 0.50349045 0.49611062 0.56210543 0.56886518 i79 i80 i81 i82 i83 i84 0.58288940 0.57737105 0.43171441 0.46532888 0.45217701 0.39389826 i85 i86 i87 i88 i89 i90 0.22156274 0.40729806 0.33360305 0.55090576 0.35075280 0.31624693 i91 0.41545746

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135 The SAS System 7 The FACTOR Procedure Rotation Method: Oblique Varimax Oblique Transformation Matrix 1 2 3 1 0.60305 0.36829 0.37791 2 -0.86443 0.75643 0.34694 3 -0.27428 -0.65160 0.95341 Inter-Factor Correlations Factor1 Factor2 Factor3 Factor1 1.00000 0.28916 0.33869 Factor2 0.28916 1.00000 0.26964 Factor3 0.33869 0.26964 1.00000 Rotated Factor Pattern (Standardized Regression Coefficients) Factor1 Factor2 Factor3 i79 SDH8 0.70801 0.10985 0.04228 i82 LCM5 0.68926 -0.10336 0.04548 i73 SDH5 0.68554 0.14428 -0.04595 i80 RTM5 0.66561 0.11161 0.12422 i77 SDH7 0.65042 0.14005 0.10711 i81 SDM13 0.64623 0.12037 -0.11795 i69 SDH3 0.64608 -0.07106 0.06937 i83 SDM14 0.64028 0.13473 -0.05752 i71 SDH4 0.62719 -0.03273 0.04766 i67 SDH2 0.62464 -0.05887 0.16598 i86 LCM7 0.60985 0.05118 0.03118 i70 RTH3 0.59016 0.16427 0.04889 i72 HSM 0.58825 0.02152 0.04634 i87 SDM16 0.57855 -0.04992 0.03291 i88 LTM4 0.57551 0.19784 0.17166 i89 SDM17 0.55420 0.02614 0.07448 i74 LCH4 0.54943 0.14794 0.11756 i19 SDS10 0.53618 0.30930 0.04947 i91 LTH3 0.51818 0.06497 0.20762 i78 LCH6 0.49897 0.25215 0.25263 i75 SDH6 0.49339 0.16305 0.27007 i66 LCH2 0.48856 0.10037 0.28756 i47 SDM6 0.48421 0.07744 0.09954 i85 SDM15 0.46463 -0.04606 0.04726 i35 SDM1 0.45872 0.09745 0.31462 i33 SDS17 0.43542 0.11452 -0.08135 i76 LCH5 0.43262 0.19605 0.31170 i16 LTS3 0.42781 0.08983 0.05312 i84 LCM6 0.42546 -0.02967 0.35157 i38 RTM2 0.41046 -0.11064 0.29499 i46 SDM5 0.35498 0.28027 0.02757 i68 LCH3 0.34530 0.10856 0.27120 i5 SDS3 0.33620 0.20675 0.19451 i20 LTS4 0.33564 0.21063 -0.06884 i65 SDH1 0.31835 -0.13011 0.29502 i40 SDS19 0.29993 0.26191 0.18420

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136 i15 SDS8 -0.10762 0.58859 0.15012 i52 LTH1 -0.08371 0.57710 -0.09423 i23 SDS12 0.10132 0.52940 -0.03142 i48 RTM4 0.06924 0.52781 0.04189 i4 LTS1 0.11967 0.52744 -0.03379 i8 RTS3 0.25450 0.51661 0.07236 i17 SDS9 -0.06372 0.51046 0.15223 i25 SDS13 -0.19647 0.50734 0.27590 i13 SDS7 0.08356 0.49416 0.11174 i9 SDS5 -0.24304 0.48619 0.01688 i39 SDS18 0.03393 0.46533 0.01270 i54 RTS8 0.30308 0.46473 -0.03384 i21 SDS11 0.03007 0.46071 0.06919 i42 SDM3 0.01278 0.44306 0.26127 i27 SDS14 0.24138 0.43090 -0.00841 i49 SDM7 0.13309 0.43061 0.09645 i7 SDS4 0.07278 0.43045 0.06834 i51 SDM8 0.14269 0.41949 0.03776 i29 SDS15 0.17154 0.40352 0.20484 i45 LTM2 0.27555 0.40241 -0.19353 i14 RTS5 -0.01398 0.39845 0.05577 i37 SDM2 0.10402 0.39518 0.33033 i60 SDM10 0.03936 0.39158 0.19118 i53 SDS20 0.03243 0.37771 0.03089 i11 SDS6 -0.09387 0.34770 -0.16812 i57 LCH1 -0.08170 0.33861 0.23361 i44 SDM4 0.28401 0.33451 0.00688 i62 SDM11 0.18919 0.32849 0.16296 i31 SDS16 0.15072 0.31459 0.07870 i22 LTS5 0.07989 0.30390 0.08820 i55 SDS21 0.07417 0.18961 0.16168 i12 RTS4 -0.14432 -0.09225 0.70680 i10 LTS2 -0.11209 -0.06993 0.66951 i26 LTS7 -0.18899 0.07136 0.62823 i24 LTS6 0.01058 0.10529 0.57053 i28 RTS7 -0.03941 0.01344 0.56914 i58 SDM9 0.01594 0.23374 0.54846 i50 LCM4 0.06922 -0.04292 0.53050 i1 RTS1 -0.27609 -0.01492 0.52949 i2 SDS1 -0.07015 0.05813 0.48652 i30 LCM1 0.08154 -0.08818 0.47120 i43 LCM3 0.18092 0.18981 0.46959 i56 RTH1 0.08125 0.07237 0.46736 i32 LCM2 0.15457 0.06025 0.46025 i3 SDS2 -0.04312 0.17585 0.43814 i36 LTM1 0.27692 0.05876 0.43788 i59 LTH2 0.01384 0.31590 0.40153 i41 RTM3 0.00614 0.14216 0.39381 i34 RTM1 0.22430 0.10045 0.38624 i63 SDM12 0.31301 -0.16591 0.38202 i90 SDM18 0.33261 -0.05268 0.37343 i6 RTS2 0.23749 0.02239 0.36964 i61 LTM3 0.19329 0.24071 0.32957 i64 RTH2 0.21641 -0.29533 0.32542 i18 RTS6 0.05826 0.15704 0.20537

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137 Reference Axis Correlations Factor1 Factor2 Factor3 Factor1 1.00000 -0.21835 -0.28284 Factor2 -0.21835 1.00000 -0.19063 Factor3 -0.28284 -0.19063 1.00000 Reference Structure (Semipartial Correlations) Factor1 Factor2 Factor3 i79 SDH8 0.65009 0.10323 0.03905 i82 LCM5 0.63287 -0.09713 0.04201 i73 SDH5 0.62946 0.13559 -0.04244 i80 RTM5 0.61116 0.10488 0.11474 i77 SDH7 0.59722 0.13161 0.09893 i81 SDM13 0.59337 0.11312 -0.10895 i69 SDH3 0.59323 -0.06677 0.06407 i83 SDM14 0.58790 0.12661 -0.05313 i71 SDH4 0.57588 -0.03076 0.04402 i67 SDH2 0.57354 -0.05532 0.15331 i86 LCM7 0.55996 0.04810 0.02880 i70 RTH3 0.54188 0.15437 0.04515 i72 HSM 0.54012 0.02022 0.04280 i87 SDM16 0.53122 -0.04691 0.03039 i88 LTM4 0.52843 0.18592 0.15855 i89 SDM17 0.50886 0.02456 0.06880 i74 LCH4 0.50448 0.13902 0.10858 i19 SDS10 0.49232 0.29065 0.04569 i91 LTH3 0.47579 0.06105 0.19176 i78 LCH6 0.45815 0.23695 0.23334 i75 SDH6 0.45303 0.15322 0.24944 i66 LCH2 0.44859 0.09432 0.26560 i47 SDM6 0.44460 0.07278 0.09194 i85 SDM15 0.42662 -0.04329 0.04365 i35 SDM1 0.42120 0.09158 0.29060 i33 SDS17 0.39980 0.10762 -0.07514 i76 LCH5 0.39723 0.18424 0.28790 i16 LTS3 0.39281 0.08441 0.04907 i84 LCM6 0.39066 -0.02788 0.32473 i38 RTM2 0.37689 -0.10397 0.27247 i46 SDM5 0.32594 0.26338 0.02546 i68 LCH3 0.31705 0.10201 0.25049 i5 SDS3 0.30870 0.19428 0.17966 i20 LTS4 0.30819 0.19794 -0.06358 i65 SDH1 0.29231 -0.12227 0.27250 i40 SDS19 0.27540 0.24612 0.17013 i15 SDS8 -0.09881 0.55311 0.13865 i52 LTH1 -0.07686 0.54232 -0.08703 i23 SDS12 0.09303 0.49749 -0.02902 i48 RTM4 0.06357 0.49600 0.03869 i4 LTS1 0.10988 0.49565 -0.03121 i8 RTS3 0.23368 0.48547 0.06684 i17 SDS9 -0.05851 0.47969 0.14061 i25 SDS13 -0.18040 0.47676 0.25483 i13 SDS7 0.07673 0.46437 0.10321 i9 SDS5 -0.22316 0.45689 0.01559 i39 SDS18 0.03115 0.43728 0.01173

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138 i54 RTS8 0.27829 0.43672 -0.03126 i21 SDS11 0.02761 0.43294 0.06391 i42 SDM3 0.01174 0.41635 0.24132 i27 SDS14 0.22163 0.40493 -0.00777 i49 SDM7 0.12220 0.40466 0.08909 i7 SDS4 0.06683 0.40450 0.06312 i51 SDM8 0.13101 0.39421 0.03488 i29 SDS15 0.15751 0.37920 0.18920 i45 LTM2 0.25301 0.37816 -0.17876 i14 RTS5 -0.01284 0.37443 0.05151 i37 SDM2 0.09551 0.37136 0.30511 i60 SDM10 0.03614 0.36798 0.17658 i53 SDS20 0.02978 0.35495 0.02854 i11 SDS6 -0.08619 0.32675 -0.15529 i57 LCH1 -0.07501 0.31820 0.21577 i44 SDM4 0.26078 0.31435 0.00635 i62 SDM11 0.17372 0.30869 0.15052 i31 SDS16 0.13839 0.29563 0.07269 i22 LTS5 0.07335 0.28559 0.08147 i55 SDS21 0.06810 0.17818 0.14933 i12 RTS4 -0.13252 -0.08669 0.65283 i10 LTS2 -0.10292 -0.06572 0.61839 i26 LTS7 -0.17353 0.06706 0.58026 i24 LTS6 0.00972 0.09894 0.52697 i28 RTS7 -0.03618 0.01263 0.52568 i58 SDM9 0.01463 0.21965 0.50658 i50 LCM4 0.06356 -0.04033 0.48999 i1 RTS1 -0.25350 -0.01403 0.48906 i2 SDS1 -0.06441 0.05463 0.44938 i30 LCM1 0.07487 -0.08287 0.43522 i43 LCM3 0.16612 0.17837 0.43373 i56 RTH1 0.07460 0.06801 0.43168 i32 LCM2 0.14192 0.05662 0.42510 i3 SDS2 -0.03959 0.16525 0.40469 i36 LTM1 0.25427 0.05522 0.40445 i59 LTH2 0.01271 0.29686 0.37087 i41 RTM3 0.00564 0.13359 0.36374 i34 RTM1 0.20595 0.09439 0.35675 i63 SDM12 0.28741 -0.15591 0.35285 i90 SDM18 0.30540 -0.04950 0.34491 i6 RTS2 0.21806 0.02104 0.34142 i61 LTM3 0.17748 0.22620 0.30440 i64 RTH2 0.19871 -0.27753 0.30058 i18 RTS6 0.05349 0.14758 0.18969 Variance Explained by Each Factor Eliminating Other Factors Factor1 Factor2 Factor3 9.7904405 6.3996302 6.1291283

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139 Factor Structure (Correlations) Factor1 Factor2 Factor3 i79 SDH8 0.75409 0.32598 0.31170 i82 LCM5 0.67477 0.10821 0.25106 i73 SDH5 0.71170 0.33012 0.22514 i80 RTM5 0.73996 0.33757 0.37975 i77 SDH7 0.72720 0.35701 0.36517 i81 SDM13 0.64109 0.27543 0.13338 i69 SDH3 0.64903 0.13447 0.26903 i83 SDM14 0.65975 0.30436 0.19566 i71 SDH4 0.63387 0.16148 0.25126 i67 SDH2 0.66384 0.16651 0.36167 i86 LCM7 0.63521 0.23593 0.25153 i70 RTH3 0.65421 0.34810 0.29306 i72 HSM 0.61016 0.20411 0.25137 i87 SDM16 0.57526 0.12624 0.21540 i88 LTM4 0.69086 0.41054 0.41992 i89 SDM17 0.58698 0.20647 0.26923 i74 LCH4 0.63202 0.33851 0.34353 i19 SDS10 0.64237 0.47768 0.31447 i91 LTH3 0.60729 0.27079 0.40064 i78 LCH6 0.65744 0.46455 0.48961 i75 SDH6 0.63201 0.37854 0.48114 i66 LCH2 0.61498 0.31917 0.48010 i47 SDM6 0.54032 0.24430 0.28442 i85 SDM15 0.46732 0.10103 0.19221 i35 SDM1 0.59346 0.31493 0.49627 i33 SDS17 0.44098 0.21849 0.09700 i76 LCH5 0.59488 0.40520 0.51109 i16 LTS3 0.47178 0.22786 0.22224 i84 LCM6 0.53596 0.18815 0.48767 i38 RTM2 0.47839 0.08759 0.40418 i46 SDM5 0.44536 0.39035 0.22337 i68 LCH3 0.46855 0.28153 0.41742 i5 SDS3 0.46187 0.35641 0.36413 i20 LTS4 0.37324 0.28913 0.10164 i65 SDH1 0.38065 0.04149 0.36776 i40 SDS19 0.43805 0.39830 0.35640 i15 SDS8 0.11342 0.59795 0.27237 i52 LTH1 0.05125 0.52749 0.03303 i23 SDS12 0.24376 0.55023 0.14564 i48 RTM4 0.23605 0.55912 0.20765 i4 LTS1 0.26074 0.55294 0.14896 i8 RTS3 0.42840 0.60971 0.29786 i17 SDS9 0.13544 0.53308 0.26829 i25 SDS13 0.04368 0.52492 0.34615 i13 SDS7 0.26430 0.54845 0.27329 i9 SDS5 -0.09674 0.42046 0.06565 i39 SDS18 0.17278 0.47856 0.14966 i54 RTS8 0.42600 0.54324 0.19412 i21 SDS11 0.18672 0.48806 0.20360 i42 SDM3 0.22939 0.51720 0.38506 i27 SDS14 0.36313 0.49843 0.18953 i49 SDM7 0.29028 0.49510 0.25764 i7 SDS4 0.22039 0.46992 0.20905

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140 i51 SDM8 0.27678 0.47093 0.19920 i29 SDS15 0.35760 0.50836 0.37174 i45 LTM2 0.32636 0.42991 0.00830 i14 RTS5 0.12012 0.40944 0.15847 i37 SDM2 0.33017 0.51432 0.47212 i60 SDM10 0.21734 0.45451 0.31009 i53 SDS20 0.15212 0.39542 0.14372 i11 SDS6 -0.05027 0.27523 -0.10616 i57 LCH1 0.09534 0.37797 0.29724 i44 SDM4 0.38307 0.41849 0.19327 i62 SDM11 0.33937 0.42714 0.31561 i31 SDS16 0.26835 0.37939 0.21458 i22 LTS5 0.19764 0.35079 0.19721 i55 SDS21 0.18375 0.25465 0.23792 i12 RTS4 0.06839 0.05660 0.63304 i10 LTS2 0.09445 0.07818 0.61269 i26 LTS7 0.04442 0.18610 0.58346 i24 LTS6 0.23426 0.26218 0.60251 i28 RTS7 0.15724 0.15551 0.55941 i58 SDM9 0.26929 0.38624 0.61688 i50 LCM4 0.23649 0.12014 0.54237 i1 RTS1 -0.10107 0.04801 0.43196 i2 SDS1 0.11144 0.16903 0.47844 i30 LCM1 0.21563 0.06245 0.47504 i43 LCM3 0.39485 0.36874 0.58204 i56 RTH1 0.26047 0.22188 0.51439 i32 LCM2 0.32787 0.22905 0.52884 i3 SDS2 0.15612 0.28152 0.47095 i36 LTM1 0.44222 0.25690 0.54752 i59 LTH2 0.24118 0.42817 0.49139 i41 RTM3 0.18063 0.25012 0.43422 i34 RTM1 0.38416 0.26945 0.48930 i63 SDM12 0.39443 0.02761 0.44330 i90 SDM18 0.44386 0.14419 0.47188 i6 RTS2 0.36916 0.19073 0.45611 i61 LTM3 0.37452 0.38547 0.45994 i64 RTH2 0.24123 -0.14500 0.31909 i18 RTS6 0.17323 0.22927 0.26745 Variance Explained by Each Factor Ignoring Other Factors Factor1 Factor2 Factor3 16.488916 11.505151 12.144716

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141 Final Communality Estimates: Total = 30.107733 i1 i2 i3 i4 i5 i6 0.25590374 0.23478035 0.24911731 0.31781409 0.29979333 0.26053961 i7 i8 i9 i10 i11 i12 0.23260114 0.44556402 0.22904575 0.39415125 0.11826578 0.43234082 i13 i14 i15 i16 i17 i18 0.32364764 0.17029727 0.38062469 0.23410559 0.30432859 0.10102411 i19 i20 i21 i22 i23 i24 0.50772797 0.17917696 0.24455731 0.13978862 0.31141350 0.37383300 i25 i26 i27 i28 i29 i30 0.35323744 0.37143445 0.30083537 0.31427746 0.34262376 0.23591404 i31 i32 i33 i34 i35 i36 0.17668774 0.30787709 0.20914345 0.30222072 0.45905995 0.37730483 i37 i38 i39 i40 i41 i42 0.39354984 0.30590076 0.23045317 0.30135485 0.20766482 0.33268811 i43 i44 i45 i46 i47 i48 0.41474715 0.25011527 0.26132525 0.27365878 0.30885968 0.32015250 i49 i50 i51 i52 i53 i54 0.27667941 0.29894005 0.24456621 0.29701504 0.15872974 0.37500355 i55 i56 i57 i58 i59 i60 0.10037764 0.27762888 0.18963427 0.43290583 0.33590352 0.24581405 i61 i62 i63 i64 i65 i66 0.31676113 0.25594861 0.28823069 0.19886970 0.22428246 0.47054414 i67 i68 i69 i70 i71 i72 0.46488722 0.30555382 0.42843529 0.45759535 0.40424751 0.37496615 i73 i74 i75 i76 i77 i78 0.52518967 0.43771627 0.50349045 0.49611062 0.56210543 0.56886518 i79 i80 i81 i82 i83 i84 0.58288940 0.57737105 0.43171441 0.46532888 0.45217701 0.39389826

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142 i85 i86 i87 i88 i89 i90 0.22156274 0.40729806 0.33360305 0.55090576 0.35075280 0.31624693 i91 0.41545746

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BIOGRAPHICAL SKETCH Michael D. Justiss began his aging resear ch as a Rehabilitation Science Doctoral student with the University of Florida’s Rehabilitation Engi neering Research Center on Technology for Successful Aging (RERC-Tech-A ging). During his first two years, he conducted research with smart technology appl ications to enhance elder independence. He was the RERC-Tech-Aging project leader for a collaborative research study with Honeywell’s Independent LifeSt yle Assistant (ILSA), used to remotely monitor elder activity in a home environm ent. He has also done research with the Veteran Administration’s Low ADL Monitoring Project (LAMP), which uses smart technology to enhance care-coordinator activity. More recentl y, he functions as a re search assistant for the National Older Driver Research and Trai ning Center, which rece ived congressional funding under the Centers for Disease Control and the Federal Highway Administration. He has served as a University of Florida representative on the Florida At-Risk Drivers Council and served as an E xpert Panel member of the International Older Driver Consensus Conference. Michael has served as adjunct faculty in the Department of Occupational Therapy teaching Applied Research and has shared authorship on severa l journal articles published in Occupation, Participation and Healt h, Assistive Technology, Occupational Therapy Journal of Research, and Technology and Disability. He has also presented for national and international conf erences on issues pertaining to technology and aging, elder mobility, and older drivers. 149