El aprendizaje dialógico: ¿camino para una escuela feliz?

Concerns relating to driving safety are difficult to address for health professionals who frequently consider it an issue on or beyond the fringes of their clinical expertise (Brook and Southward, 2007; Frampton, 2007; Hawley et al, 2010). In an early but influential study Gillespie et al (1999) investigated the depth of knowledge and attitudes of

geriatricians towards their responsibilities regarding the fitness to drive of their patients. The research was completed using a postal survey only of over 700 geriatricians practicing in the UK. The response to the study questionnaire was high, exceeding sixty percent, strengthening the results and reducing the likelihood of skew. The high response rate also perhaps reflected the relevance of this topic to practicing clinicians. The results of the study demonstrated that geriatricians are commonly reluctant to confront the issue of fitness to drive with individuals with a diagnosis of dementia owing to a lack of expertise

31 and suitable information. The study identified that a significant proportion of the

respondents advised individuals with a mild dementia to cease driving. Subsequent research has demonstrated however, that drivers with in the mild to moderate phase of dementia may remain safe when driving (Berndt et al, 2008; Brown and Ott, 2004). Although the study exposed widespread uncertainty of geriatricians in dealing with driving, the nature of the survey did not provide an opportunity for further exploration of the issues. In a later, large scale study constructed from a number of smaller studies, Hawley et al (2010) employed a mixed methods approach that included focus groups and semi structured interviews to investigate the attitudes towards fitness to drive with a variety of medical practitioners and medical students. This provided far richer evidence about attitudes of health professionals than was contained in Gillespie et al’s (1999) study. The study sought to evaluate knowledge and attitudes of health professionals regarding driving and investigate how advice was provided. The key findings of the research mirrored those of Gillespie et al’s study but further identified that medical practitioners received little or no training regarding driving and many did not routinely consider the issue of driving safety during consultations with their patients. Of those clinicians who provided advice regarding driving, a sizable proportion described uncertainty of procedural requirements and lack of available resources to enable effective decision making.

Instruments designed to detect decrements in cognitive function are used in many clinical settings. A variety of screening tools are available and used in the UK specifically to inform and support decisions regarding driving (Appendix B). Screening tools are designed to detect the presence or absence of a particular factor or to include or exclude a condition (British Psychological Society, 2001). Tools created to evaluate behaviours vary in their ability to act as reliable predictors to behaviour and there are no universally

32 accepted clinical guidelines for what may constitute an effective assessment battery. To date, a number of driver screening tools are available but the development of a screening tool capable of reliably predicting driving safety has so far proved elusive (Kortling and Kaptein, 1996; McCarthy and Mann, 2006). Reasons for this are unclear but may be related to their over-reliance on cognitive testing. As discussed earlier, the components of cognition are largely conceptual and the manner of their organisation remains the subject of conjecture. Salthouse (2007) in an initial pilot study and second large scale study of healthy volunteers administered 16 different cognitive tests, not related to driving, on three separate occasions. The sample was grouped according to three age bands; young adult, middle and older aged. The results of the study found wide variation in an individual’s test performance results over a relatively short period. The results also appear to demonstrate significant differences in cognitive testing performance across all age ranges tested. These findings emphasise the difficulties of identifying true changes from short term fluctuations and underline the need for evaluation tools to capture a more representative picture of an individual’s function.

General Cognitive Screening Tools Used in Driver Evaluation

Testing tools designed to measure cognitive elements are frequently used to evaluate cognitive impairments upon driving. An example of this is the Trail-Making Test A & B (TMT-A&B) which was originally used by the American military to test general

intelligence as part of the Army Individual Test of General Ability (Tombaugh, 2004). In the mid 1950’s Reitan (1955) further developed the TMT to assess cognitive impairment of individuals with a brain injury. The TMT has been used to evaluate a range of cognitive elements such as general intelligence, memory and motor speed (Corrigan and Hinkldey, 1987), visual perception, “fine motor abilities” (Groff and Hubble 1981), cognitive

33 flexibility (Lamberty et al 1994) and visual scanning and attention (O’Donnel et al, 2010). More recently the TMT has been used to predict the safety of driving of those with a cognitive impairment. In a meta-analysis of a number of small scale studies Silva et al (2009) illustrated that the test was not entirely predictive but demonstrated reasonable agreement with the performance of drivers on the on-road test.

The Mini Mental State Examination (MMSE) is one of the most frequently administered general cognitive screening tools used to provide an indication of the driving safety of older drivers with cognitive decline in both in the UK and the USA. The large proportion of research evidence agrees however that the MMSE may fail to predict driving

competence in older people with a cognitive decline (Silva et al, 2009). In studies where MMSE test results were compared to both simulator and on road driving performance the predictive value of the MMSE was found to be poor (Adler et al, 2005). This may result from the MMSE’s focus upon gross cognitive impairment, limiting its sensitivity to much milder impairments that can impact driving. It may also reflect the fact that the MMSE focuses upon language, orientation, and memory omitting other components of cognitive function such as executive processes that are important for safe driving.

Similar to the TMT and the MMSE, the Clock Drawing Test (CDT) is an established test and was originally used to identify visuo-constructional disorders associated with lesions sustained to the parietal lobe (Shulman, 2000). More recently however the clock drawing test has attracted attention for its role in the screening of early dementia and in particular Alzheimer’s disease (Sunderland, Hill, Mellow, 1989). The test is reported to evaluate many of the cognitive components that are impaired in early cognitive decline such as memory, understanding of verbal instruction, spatial orientation, abstract thinking, executive and visuospatial skills (Aprahamian, et al, 2011). It has also demonstrated

34 reasonable success in identifying drivers who are unsafe to drive but has had less success in predicting safe drivers correctly (Freund et al, 2005).

Specific Driver Screening Tools

It has not been possible to evaluate all testing tools employed to assess driving capacity and therefore I have chosen to concentrate on tools that are in regular use in UK driving assessment centres (Inwood, 2007). A brief description of specific and non-specific driver testing tools has been provided (Appendix B). The Physicians Guide to Assessing and Counselling Older Drivers, (Carr et al, 2010) recommends the use of the Assessing

Driving Related Skills (ADReS), (McCarthy, 2005), the clock drawing test (Sunderland et al 1989) and Trail Making Test. The ADReS tool has been designed for use specifically with older drivers. The tool is largely made up of cognitive tests but does include a vision and motor-function element. In an evaluation of the sensitivity and specificity of the ADReS screening tool, data were measured for levels of agreement with an on-road assessment. The study included 50 healthy volunteers sampled from a motoring club. The justification of the sample size was not outlined. Criteria for inclusion in the study did not require specific clinical diagnoses and although the research sample excluded individuals below the age of 65 only one person was included with a diagnosis of dementia.

Participants were informed that licensing authorities would be notified in the events of concerns regarding driving safety during the research and that this may result in loss of licensing entitlement. Perhaps as an effect of this and the sampling method used, very few participants were found unsafe to drive from the on-road assessment. Consequently, the results of the study must be treated with some degree of caution. Nevertheless, these results demonstrated that even with only a small proportion (16%) of the sample failing the in-car assessment, the ability of the tool to correctly screen safe drivers was questionable.

35 The specificity, or the true negative results of the screening tool, was demonstrated to have a high degree of accuracy in identifying all those found to be unsafe on the road however the sensitivity, or true positives results of the screening tool, was extremely poor,

incorrectly identifying 54% of participants as unsafe who subsequently passed the on-road evaluation (McCarthy and Mann, 2006).

Similar difficulties associated with sensitivity and specificity exists with driver screening tools developed and in clinical use across the UK. The Rookwood Driving Battery was originally developed by staff engaged in driving assessment, to provide an indication of driving safety and is used widely with a range of clinical diagnoses. It is now the primary screening tool used in driver screening across all diagnoses in the UK and for this reason I have considered its development and evidence for its use in greater detail. Three studies by the screening tool’s principle developer have been published to evaluate and validate its use in assessing driving ability (McKenna et al, 2004; McKenna et al, 2007; Rees et al, 2007). These studies included participants totalling 735 participants although it is not clear whether these studies included the same participants or their data. The original research design used a sample of 142 participants with a wide variety of clinical diagnoses (McKenna et al, 2004). Sampling methods and inclusion criteria were not detailed. Participants were included if their medical condition “affected brain functioning”. 43 participants were included over the age of 70 years and only 17 participants with a diagnosis of dementia. The participants were tested using the testing battery and then undertook an on-road driving evaluation. The on-road assessments were conducted by a driving instructor and the researcher. The driving instructor was informed of the cognitive battery performance before commencing the on-road assessment, weakening the study findings. The results of this study illustrated that the testing tool demonstrated good levels

36 of sensitivity and specificity in relation to the on-road assessment when evaluating

individuals with a traumatic brain injury, although statistical analysis was not used in calculating the level of agreement. When the results of participants with a diagnosis of dementia are taken in isolation however, the efficacy of the test is extremely poor. The sensitivity was calculated to be 0.54 and specificity, calculated to be 0.67. The positive predictive value, or the likelihood that the screening tool is able to identify unsafe drivers, was found to be 0.85 in individuals diagnosed with dementia and the negative predictive value, or the likelihood that the tools will identify safe drivers was 0.30. These results mean that the total predictive value for the Rookwood Driving Battery for individuals diagnosed with dementia in the four studies was little over 50%. Similarly poor results were obtained for those research participants over the age of 70 years. Results of testing also suggest poor outcomes in providing an accurate predictive indication for those individuals less than 6 months post brain injury or stroke. Finally, the nature of the testing tool, in particular the problem solving subtest makes the testing battery designed to be used on one occasion only. Retesting data has not been produced and no suitable resolution to the problem has yet been offered.

Explanations for the poor efficacy of screening tools to predict outcomes of on-road driving assessments are complex. The reliance upon measures of cognitive performance presents a number of difficulties. These include the lack of a full understanding of

cognitive processes, their relationship with each other in normal function, the uncertainty of what specific functions cognitive testing tools are measuring and not least, their uncertain relationship with the driving task. The poor outcomes most testing tools

experience with people diagnosed with dementia and those over the age of 70 years cannot be described simply in terms of the research processes used, although this cannot be

37 discounted. Almost all studies calculate levels of agreement of the testing tool with the on-road assessment. The use of the on-road assessment as a gold standard against which to measure testing tools should however be treated with caution. Many on-road assessments employ standard protocols but uncontrollable factors such as weather and lighting

conditions, other road users and traffic volume may act as confounding factors limiting their use as an entirely reliable measure. Although practical alternatives to the on-road assessment may not exist, studies such as those conducted by Berndt et al (2008) have attempted to strengthen results by driving standardised routes, avoiding periods of heavy traffic volume and driving at similar times of the day.