Occupational Therapy In Health Care, 28(2):127–131, 2014 C 2014 by Informa Healthcare USA, Inc. Available online at http://informahealthcare.com/othc DOI: 10.3109/07380577.2014.903017
CONSENSUS STATEMENTS WITH BACKGROUND PAPERS
Consensus Statements for Screening and Assessment Tools Michel B´edard1,2,3 & Anne E. Dickerson4 1
Centre for Research on Safe Driving, Lakehead University, Thunder Bay, Ontario, Canada, 2 St. Joseph’s Care Group, Thunder Bay, Ontario, Canada, 3 Northern Ontario School of Medicine, Thunder Bay, Ontario, Canada, 4 Department of Occupational Therapy, East Carolina University, Greenville, North Carolina, USA
ABSTRACT. Occupational therapists, both generalists and specialists, have a critical role in providing services to senior drivers. These services include evaluating fitnessto-drive, developing interventions to support community mobility, and facilitating the transition from driving to non-driving when necessary for personal and community safety. The evaluation component and decision-making process about fitness-to-drive are highly dependent on the use of screening and assessment tools. The purpose of this paper is to briefly present the rationale and context for 12 consensus statements about the usefulness and appropriateness of screening and assessment tools to determine fitness-to-drive, within the occupational therapy clinical setting, and their implications on community mobility. KEYWORDS. Assessment, consensus statements, driving, screening
There is a paucity of well-documented, well-validated screening and assessment tools to determine fitness-to-drive. “Screening”1 refers to short, easy-to-administer tests that allow the quick identification of drivers who are clearly without impairment and those who need a more in-depth assessment to determine fitnessto-drive—this helps reduce the number of drivers requiring more comprehensive and longer testing. However, both screening and comprehensive assessment approaches, as they currently stand, are imperfect, to a large extent because the current tools used have several limitations. First, the statistical associations between performance on the screening and assessment tools and results on the outcome measure of interest (often an on-road ´ driving test) are limited in most research studies (Bedard et al., 2008). The low magnitude of these associations indicates that important other factors are at play 1 The term “screening” is used here to denote the preliminary assessment of fitness-to-drive and is not meant
in the Public Health sense of identifying an underlying condition before it starts manifesting itself. Address correspondence to: Dr. Michel Bedard, Department of Health Sciences, Lakehead University, 955 Oliver Road, Thunder Bay, Ontario P7B 5E1, Canada (E-mail: [email protected]). (Received 28 February 2014; accepted 6 March 2014)
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in explaining the results obtained on the gold standard. Second, it is reasonable to assume that in “real-world” driving (outside the more controlled setting of a research study) the associations would be even weaker. While modest statistical associations may enable researchers to quantify the relative risk of an outcome for one group versus another, these associations are not sufficiently strong to determine the risk for any given individual with sufficient precision. From a testing perspective, this means that there will be an inevitable tradeoff between test “sensitivity” and test “specificity,” such that if one of these indicators is strong, the other will be weak. Sensitivity is the ability of a tool to identify an underlying condition when it truly exists (in our context it refers to the ability of the tool to accurately label as “unfit” those drivers who are truly unfit to drive). Specificity is the ability of a tool to rule out a condition when it really does not exist (here it refers to the ability of the tool to accurately label as “fit” those drivers who are truly fit to drive). The most useful tool is one that has both high sensitivity ´ and specificity (Weaver & Bedard, 2012). It is possible, using two cut points rather than one, to achieve higher sensitivity and specificity. However, this results in a very large “gray area,” necessitating that a large number of drivers undergo com´ prehensive testing (Bedard et al., 2013). Hence, there is not, at present, a single tool that provides sufficient precision to make decisions regarding fitness-to-drive (Gamache, 2010). The following consensus statement was affirmed by a panel of experts (see Dickerson and Schold-Davis in this issue) at the highest level (i.e., evidence is strong and allows for an evidence-based consensus statement—Level 1): Statement 1: A decision about continued, restricted, or cessation of driving should never be made on the results of one tool in isolation, as there is not enough evidence provided by any one tool to make a decision. In addition to the challenges of applying the results of research studies to predict individual performance, the limited predictive accuracy of present tools arises from a number of issues related to instrument development. First, while driving is a complex task requiring the involvement and integration of multiple sensory/perceptual, cognitive, and motor skills, a brief screening tool may only address one discrete skill or ability (e.g., visual scanning, reaction time). Hence, it is unreasonable to expect that a simple tool will capture the full range of variables underlying fitness-to-drive. Second, candidate tools for screening and assessment often have limitations related to their administration. For example, many tools take a long time to administer (problematic because screening tools should be brief). Computer-based tasks may disadvantage seniors who are less efficient and demonstrate more performance errors (missing steps or adding steps) and motor control errors (mouse control and clicking errors) when using a computer (Kim, 2014). Many tools also lack face validity, that is, the tool does not appear to measure what it is supposed to measure (e.g., it is not readily apparent to a senior how generating a number of grocery items on a test relates to fitness-to-drive). The ecological validity (how well the test situation approximates the real-life situation) of the tool can also be an issue. For example, seniors have reported that operating a driving simulator is not “like driving a car”
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(Schwarga et al., 2014). Third, and importantly, tool properties apply only to the research conditions under which they were tested (Streiner & Norman, 2008). For example, results obtained with a sample of people with Alzheimer disease cannot be generalized to different diagnostic groups such as people with Parkinson disease and results obtained with one outcome measure may not be similar with a different outcome measure (i.e., the accuracy of a tool in predicting performance on a simulator may differ from its accuracy in predicting performance on the road). After a thorough review of these issues, the expert panel affirmed the following statements at the highest level of evidence (i.e., evidence is strong and allows for an evidence-based consensus statement—Level 1): Statement 2: Measurement tools must be administered according to the protocol under which they were tested in order to use the norms and/or evidence. Statement 3: Measurement tools that are developed specifically for a diagnostic group should be interpreted carefully when used with other diagnostic groups unless there is sufficient evidence supporting the use of the tool with another group. Statement 4: Results from measurement tools that are developed based upon specific outcomes (e.g., crashes) should be interpreted carefully when used to predict another outcome (e.g., driving performance). Ultimately, it is important that occupational therapists continue to apply an evidence-based framework to the determination of fitness-to-drive for seniors. An evidence-based framework implies that the proper research activities, from the in´ dividual studies to the development of the tool, have taken place (Bedard et al., 2011). The tools currently used by driver rehabilitation specialists to determine fitness-to-drive vary greatly (Dickerson, 2013) and not all tools were developed with the same amount of rigor. Occupational therapists can rely on guidelines to ´ help them select the tools appropriate to their practice (Weaver & Bedard, 2012; Weaver et al., 2014) and all determinations of fitness-to-drive must rely on the combination of full assessment results (triangulation) and using the clinical reasoning process. With this in mind, the expert panel affirmed the following statements (Statement 5 was affirmed at Level 2—the evidence is suggestive and allows for a consensus statement; Statements 6–9 were affirmed at Level 3—based on clinical judgment and theory): Statement 5: The ethical application of research knowledge depends on the critical appraisal of the research, its replication, and adequate synthesis. Statement 6: Some screening tools appear to hold more promise than others. Therapists should use evidence-based tools in making decisions. Statement 7: Occupational Therapists need to apply a framework to identify the criteria required to select the tools best suited to their needs and practices. Statement 8: In the hands of a general practice occupational therapist, results from screening/assessment tools serve as criteria for referral and action. In the hands of the driver rehabilitation specialist, the same tools can contribute to a decision for fitness-to-drive. Statement 9: Processes should be followed for occupational therapy generalists to start the driving discussions with sufficient clinically related evidence.
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Statement 9 highlights the need to discuss transportation needs regardless of driving status. The typical senior’s life expectancy exceeds the expected years of safe driving and for some seniors, transitioning to non-driving may be inevitable, potentially resulting in adverse effects (Silverstein, 2008). Hence, planning for continued community mobility in the event of driving cessation is an important role for occupational therapists. It is also imperative to note that in some situations seniors have modifiable conditions that may improve with time, treatment, and/or adaptive equipment (e.g., stroke, amputation). Hence, recommendations should carefully address the potential for improvement and/or other solutions to enhance fitness-to-drive. Based on the importance of community engagement through mobility, the expert panel affirmed the following three statements (Statement 10 was affirmed at level 2—the evidence is suggestive and allows for a consensus statement; Statements 11–12 were affirmed at level 3—based on clinical judgment and theory): Statement 10: If the client is determined to be unfit to drive, the occupational therapist should provide intervention or an appropriate referral for intervention and planning to address transportation options and community mobility. Statement 11: Occupational therapy generalists should consider the multi-factorial nature of someone’s condition and potential for improvement. Statement 12: If the client is determined to be fit to drive the occupational therapist needs to address future community mobility issues including enhancing safe driving as well as transitioning to non-driver status over time. The determination of fitness-to-drive is one of the most challenging tasks facing occupational therapists. Nonetheless, by combining the careful selection and use of currently available evidence-based tools and using clinical judgment, occupational therapists can play an important role in supporting the safe mobility of seniors. SUMMARY Community mobility allows people to fully engage in life activities and for most adults, driving is the preferred means to achieve community mobility. Therefore, as a highly valued activity of daily living, occupational therapists must ensure driving is addressed as part of occupational therapy evaluations and that they consider intervention plans to support community mobility. The consensus statements provided in this paper are meant to support occupational therapists in achieving these objectives. ACKNOWLEDGEMENTS ´ Michel Bedard acknowledges financial support from AUTO21-Network of Cen´ tres of Excellence and the Ontario Neurotrauma Foundation. Michel Bedard is a member of Candrive, a Canadian Institutes of Health Research-funded research team to support safe driving in older adults, and acknowledges their support. We also thank three anonymous reviewers for their thoughtful and constructive suggestions.
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Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article. ABOUT THE AUTHORS ´ Dr. Michel Bedard is a Professor of Health Sciences, and Medicine, and the Director of the Centre for Research on Safe Driving, at Lakehead University. He is also the Scientific Director for St. Joseph’s Care Group, a large health care organization providing services in the areas of complex care and physical rehabilitation, longterm care, and mental health and addictions. Dr. Anne E. Dickerson is a Professor in the Department of Occupational Therapy and the Director of the “Research for the Older Adult Driving Initiative” (ROADI) at East Carolina University. Dr. Dickerson is also the Editor of Occupational Therapy in Health Care.
REFERENCES ´ Bedard M, Marshall S, Man-Son-Hing M, Weaver B, Gelinas I, Korner-Bitensky N, et al. (2013). It is premature to test older drivers with the SIMARD-MD. Accident; Analysis and Prevention, 61, 317–321. ´ Bedard M, Riendeau J, Weaver B, & Clarkson A. (2011). Roadwise review has limited congruence with actual driving performance of aging drivers. Accident Analysis and Prevention, 43, 2209–2214. ´ Bedard M, Weaver B, Darzins P, & Porter MM. (2008). Predicting driving performance in older adults: We are not there yet! Traffic Injury Prevention, 9, 336–341. Dickerson AE. (2013). Driving assessment tools used by driver rehabilitation specialists: Survey of use and implications for practice. American Journal of Occupational Therapy, 67, 564–573. Gamache PL. (2010). Alternative avenues in the assessment of driving capacities in older drivers and implications for training. Current Directions in Psychological Science, 19, 370–374. Kim YS. (2014). Reviewing and critiquing computer learning and usage among older adults. Educational Gerontology, 34, 709–735. Schwarga A, Wetherington C., & Dickerson A. (2014). Evaluating the use of an interactive driving simulator from the perspective of occupational therapy practitioners and older adults. Presented at the Annual Meetings of the American Occupational Therapy Association, Maryland, MD. Silverstein NM. (2008). When life exceeds safe driving expectancy: Implications for gerontology and geriatrics education. Gerontology & Geriatrics Education, 29, 305–309. Streiner DL, & Norman GR. (2008). Health measurement scales (4th ed.). Oxford; New York: Oxford University Press. ´ Weaver B, & Bedard M. (2012). Assessing fitness-to-drive: Practical tips on choosing the right screening tools for your practice. Canadian Geriatrics Society Journal of CME, 2, 5–9. Weaver B, Walter SD, & Bedard M. (2014). How to report and interpret screening test properties: Guidelines for driving researchers. Traffic Injury Prevention, 15, 252–261.
Copyright of Occupational Therapy in Health Care is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
CONSENSUS STATEMENTS WITH BACKGROUND PAPERS
Consensus Statements for Screening and Assessment Tools Michel B´edard1,2,3 & Anne E. Dickerson4 1
Centre for Research on Safe Driving, Lakehead University, Thunder Bay, Ontario, Canada, 2 St. Joseph’s Care Group, Thunder Bay, Ontario, Canada, 3 Northern Ontario School of Medicine, Thunder Bay, Ontario, Canada, 4 Department of Occupational Therapy, East Carolina University, Greenville, North Carolina, USA
ABSTRACT. Occupational therapists, both generalists and specialists, have a critical role in providing services to senior drivers. These services include evaluating fitnessto-drive, developing interventions to support community mobility, and facilitating the transition from driving to non-driving when necessary for personal and community safety. The evaluation component and decision-making process about fitness-to-drive are highly dependent on the use of screening and assessment tools. The purpose of this paper is to briefly present the rationale and context for 12 consensus statements about the usefulness and appropriateness of screening and assessment tools to determine fitness-to-drive, within the occupational therapy clinical setting, and their implications on community mobility. KEYWORDS. Assessment, consensus statements, driving, screening
There is a paucity of well-documented, well-validated screening and assessment tools to determine fitness-to-drive. “Screening”1 refers to short, easy-to-administer tests that allow the quick identification of drivers who are clearly without impairment and those who need a more in-depth assessment to determine fitnessto-drive—this helps reduce the number of drivers requiring more comprehensive and longer testing. However, both screening and comprehensive assessment approaches, as they currently stand, are imperfect, to a large extent because the current tools used have several limitations. First, the statistical associations between performance on the screening and assessment tools and results on the outcome measure of interest (often an on-road ´ driving test) are limited in most research studies (Bedard et al., 2008). The low magnitude of these associations indicates that important other factors are at play 1 The term “screening” is used here to denote the preliminary assessment of fitness-to-drive and is not meant
in the Public Health sense of identifying an underlying condition before it starts manifesting itself. Address correspondence to: Dr. Michel Bedard, Department of Health Sciences, Lakehead University, 955 Oliver Road, Thunder Bay, Ontario P7B 5E1, Canada (E-mail: [email protected]). (Received 28 February 2014; accepted 6 March 2014)
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in explaining the results obtained on the gold standard. Second, it is reasonable to assume that in “real-world” driving (outside the more controlled setting of a research study) the associations would be even weaker. While modest statistical associations may enable researchers to quantify the relative risk of an outcome for one group versus another, these associations are not sufficiently strong to determine the risk for any given individual with sufficient precision. From a testing perspective, this means that there will be an inevitable tradeoff between test “sensitivity” and test “specificity,” such that if one of these indicators is strong, the other will be weak. Sensitivity is the ability of a tool to identify an underlying condition when it truly exists (in our context it refers to the ability of the tool to accurately label as “unfit” those drivers who are truly unfit to drive). Specificity is the ability of a tool to rule out a condition when it really does not exist (here it refers to the ability of the tool to accurately label as “fit” those drivers who are truly fit to drive). The most useful tool is one that has both high sensitivity ´ and specificity (Weaver & Bedard, 2012). It is possible, using two cut points rather than one, to achieve higher sensitivity and specificity. However, this results in a very large “gray area,” necessitating that a large number of drivers undergo com´ prehensive testing (Bedard et al., 2013). Hence, there is not, at present, a single tool that provides sufficient precision to make decisions regarding fitness-to-drive (Gamache, 2010). The following consensus statement was affirmed by a panel of experts (see Dickerson and Schold-Davis in this issue) at the highest level (i.e., evidence is strong and allows for an evidence-based consensus statement—Level 1): Statement 1: A decision about continued, restricted, or cessation of driving should never be made on the results of one tool in isolation, as there is not enough evidence provided by any one tool to make a decision. In addition to the challenges of applying the results of research studies to predict individual performance, the limited predictive accuracy of present tools arises from a number of issues related to instrument development. First, while driving is a complex task requiring the involvement and integration of multiple sensory/perceptual, cognitive, and motor skills, a brief screening tool may only address one discrete skill or ability (e.g., visual scanning, reaction time). Hence, it is unreasonable to expect that a simple tool will capture the full range of variables underlying fitness-to-drive. Second, candidate tools for screening and assessment often have limitations related to their administration. For example, many tools take a long time to administer (problematic because screening tools should be brief). Computer-based tasks may disadvantage seniors who are less efficient and demonstrate more performance errors (missing steps or adding steps) and motor control errors (mouse control and clicking errors) when using a computer (Kim, 2014). Many tools also lack face validity, that is, the tool does not appear to measure what it is supposed to measure (e.g., it is not readily apparent to a senior how generating a number of grocery items on a test relates to fitness-to-drive). The ecological validity (how well the test situation approximates the real-life situation) of the tool can also be an issue. For example, seniors have reported that operating a driving simulator is not “like driving a car”
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(Schwarga et al., 2014). Third, and importantly, tool properties apply only to the research conditions under which they were tested (Streiner & Norman, 2008). For example, results obtained with a sample of people with Alzheimer disease cannot be generalized to different diagnostic groups such as people with Parkinson disease and results obtained with one outcome measure may not be similar with a different outcome measure (i.e., the accuracy of a tool in predicting performance on a simulator may differ from its accuracy in predicting performance on the road). After a thorough review of these issues, the expert panel affirmed the following statements at the highest level of evidence (i.e., evidence is strong and allows for an evidence-based consensus statement—Level 1): Statement 2: Measurement tools must be administered according to the protocol under which they were tested in order to use the norms and/or evidence. Statement 3: Measurement tools that are developed specifically for a diagnostic group should be interpreted carefully when used with other diagnostic groups unless there is sufficient evidence supporting the use of the tool with another group. Statement 4: Results from measurement tools that are developed based upon specific outcomes (e.g., crashes) should be interpreted carefully when used to predict another outcome (e.g., driving performance). Ultimately, it is important that occupational therapists continue to apply an evidence-based framework to the determination of fitness-to-drive for seniors. An evidence-based framework implies that the proper research activities, from the in´ dividual studies to the development of the tool, have taken place (Bedard et al., 2011). The tools currently used by driver rehabilitation specialists to determine fitness-to-drive vary greatly (Dickerson, 2013) and not all tools were developed with the same amount of rigor. Occupational therapists can rely on guidelines to ´ help them select the tools appropriate to their practice (Weaver & Bedard, 2012; Weaver et al., 2014) and all determinations of fitness-to-drive must rely on the combination of full assessment results (triangulation) and using the clinical reasoning process. With this in mind, the expert panel affirmed the following statements (Statement 5 was affirmed at Level 2—the evidence is suggestive and allows for a consensus statement; Statements 6–9 were affirmed at Level 3—based on clinical judgment and theory): Statement 5: The ethical application of research knowledge depends on the critical appraisal of the research, its replication, and adequate synthesis. Statement 6: Some screening tools appear to hold more promise than others. Therapists should use evidence-based tools in making decisions. Statement 7: Occupational Therapists need to apply a framework to identify the criteria required to select the tools best suited to their needs and practices. Statement 8: In the hands of a general practice occupational therapist, results from screening/assessment tools serve as criteria for referral and action. In the hands of the driver rehabilitation specialist, the same tools can contribute to a decision for fitness-to-drive. Statement 9: Processes should be followed for occupational therapy generalists to start the driving discussions with sufficient clinically related evidence.
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Statement 9 highlights the need to discuss transportation needs regardless of driving status. The typical senior’s life expectancy exceeds the expected years of safe driving and for some seniors, transitioning to non-driving may be inevitable, potentially resulting in adverse effects (Silverstein, 2008). Hence, planning for continued community mobility in the event of driving cessation is an important role for occupational therapists. It is also imperative to note that in some situations seniors have modifiable conditions that may improve with time, treatment, and/or adaptive equipment (e.g., stroke, amputation). Hence, recommendations should carefully address the potential for improvement and/or other solutions to enhance fitness-to-drive. Based on the importance of community engagement through mobility, the expert panel affirmed the following three statements (Statement 10 was affirmed at level 2—the evidence is suggestive and allows for a consensus statement; Statements 11–12 were affirmed at level 3—based on clinical judgment and theory): Statement 10: If the client is determined to be unfit to drive, the occupational therapist should provide intervention or an appropriate referral for intervention and planning to address transportation options and community mobility. Statement 11: Occupational therapy generalists should consider the multi-factorial nature of someone’s condition and potential for improvement. Statement 12: If the client is determined to be fit to drive the occupational therapist needs to address future community mobility issues including enhancing safe driving as well as transitioning to non-driver status over time. The determination of fitness-to-drive is one of the most challenging tasks facing occupational therapists. Nonetheless, by combining the careful selection and use of currently available evidence-based tools and using clinical judgment, occupational therapists can play an important role in supporting the safe mobility of seniors. SUMMARY Community mobility allows people to fully engage in life activities and for most adults, driving is the preferred means to achieve community mobility. Therefore, as a highly valued activity of daily living, occupational therapists must ensure driving is addressed as part of occupational therapy evaluations and that they consider intervention plans to support community mobility. The consensus statements provided in this paper are meant to support occupational therapists in achieving these objectives. ACKNOWLEDGEMENTS ´ Michel Bedard acknowledges financial support from AUTO21-Network of Cen´ tres of Excellence and the Ontario Neurotrauma Foundation. Michel Bedard is a member of Candrive, a Canadian Institutes of Health Research-funded research team to support safe driving in older adults, and acknowledges their support. We also thank three anonymous reviewers for their thoughtful and constructive suggestions.
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Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article. ABOUT THE AUTHORS ´ Dr. Michel Bedard is a Professor of Health Sciences, and Medicine, and the Director of the Centre for Research on Safe Driving, at Lakehead University. He is also the Scientific Director for St. Joseph’s Care Group, a large health care organization providing services in the areas of complex care and physical rehabilitation, longterm care, and mental health and addictions. Dr. Anne E. Dickerson is a Professor in the Department of Occupational Therapy and the Director of the “Research for the Older Adult Driving Initiative” (ROADI) at East Carolina University. Dr. Dickerson is also the Editor of Occupational Therapy in Health Care.
REFERENCES ´ Bedard M, Marshall S, Man-Son-Hing M, Weaver B, Gelinas I, Korner-Bitensky N, et al. (2013). It is premature to test older drivers with the SIMARD-MD. Accident; Analysis and Prevention, 61, 317–321. ´ Bedard M, Riendeau J, Weaver B, & Clarkson A. (2011). Roadwise review has limited congruence with actual driving performance of aging drivers. Accident Analysis and Prevention, 43, 2209–2214. ´ Bedard M, Weaver B, Darzins P, & Porter MM. (2008). Predicting driving performance in older adults: We are not there yet! Traffic Injury Prevention, 9, 336–341. Dickerson AE. (2013). Driving assessment tools used by driver rehabilitation specialists: Survey of use and implications for practice. American Journal of Occupational Therapy, 67, 564–573. Gamache PL. (2010). Alternative avenues in the assessment of driving capacities in older drivers and implications for training. Current Directions in Psychological Science, 19, 370–374. Kim YS. (2014). Reviewing and critiquing computer learning and usage among older adults. Educational Gerontology, 34, 709–735. Schwarga A, Wetherington C., & Dickerson A. (2014). Evaluating the use of an interactive driving simulator from the perspective of occupational therapy practitioners and older adults. Presented at the Annual Meetings of the American Occupational Therapy Association, Maryland, MD. Silverstein NM. (2008). When life exceeds safe driving expectancy: Implications for gerontology and geriatrics education. Gerontology & Geriatrics Education, 29, 305–309. Streiner DL, & Norman GR. (2008). Health measurement scales (4th ed.). Oxford; New York: Oxford University Press. ´ Weaver B, & Bedard M. (2012). Assessing fitness-to-drive: Practical tips on choosing the right screening tools for your practice. Canadian Geriatrics Society Journal of CME, 2, 5–9. Weaver B, Walter SD, & Bedard M. (2014). How to report and interpret screening test properties: Guidelines for driving researchers. Traffic Injury Prevention, 15, 252–261.
Copyright of Occupational Therapy in Health Care is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
