This is a three page summary (not review) with an emphasis on methods. The summary is on the following article: Anstey, K.J. & Wood, J. (2011). Chronological age and age-related cognitive deficits are associated with an increase in multiple types of driving errors in late life. Neuropsychology 25(5): 613-621. The summary is on the entire article, but focuses on methods.
Aging and Driving
Anstey, K.J. & Wood, J. (2011). Chronological age and age-related cognitive deficits are associated with an increase in multiple types of driving errors in late life. Neuropsychology 25(5): 613-621.
In "Chronological age and age-related cognitive deficits…" Anstey & Wood (2011) outline the purpose of the research as being to foster greater understanding of the factors involved in driving skills that diminish with age. In particular, the authors are concerned with the cognitive factors that impact driving ability. The authors warn against blanket generalizations about seniors, many of whom retain their ability to drive safely well into old age. The gap in research the authors are filling is related to the specific cognitive changes that take place as a matter of the aging process, and how those changes impact seniors who regularly drive. According to the authors, their research has direct real-world application for the ergonomics of driving experiences in terms of improved road signs and continuing driver education for seniors.
A review of literature reveals that from a neurophysiological standpoint, aging impacts frontal lobe processes and functions more than other brain regions and functions. Decision making and response time are two specific areas that diminish naturally with age. In previous research measuring the driving errors that seniors make, the authors discovered that "the highest rates of errors involved failure to maintain lane posi- tion, errors in approach, blind-spot errors, inappropriate brake / accelerator use, errors in observation, and errors in gap selection," (p. 614). The current research question focuses on common and everyday driving situations. Performance on real-world driving tests is to be compared with performance on laboratory cognitive tests. The researchers hypothesize that laboratory measures of "selective attention, set shifting, and attention" would be associated with "positioning of the vehicle, selecting gaps in traffic, and appropriate planning and preparation in a particular driving situation or maneuver" in the driving test; and that "visual selective attention" would be associated with blind spot checking behaviors (p. 614).
The researchers selected an initial population of 449 Australian persons 70 years and older. They selected from this group 266 participants who claimed that they drive once per week or more, and who met other criteria, to participate in the On Road Driving Test condition. The researchers tested for dementia to rule it out, and administered two hours work of cognitive tests plus a preliminary driving assessment of 50 minutes in length.
Among the cognitive tests used in the study, the Trail Making Tests, Digit-Symbol Matching, Simple Reaction Time, Choice Reaction Time Color, and a Visual Search test were used. During the driving test, an occupational therapist sat in the back seat to monitor and record specific driving behaviors that were being measured for the research. Specific driving behaviors being monitored and coded for the research included general observation and attention; observation of blind spots, appropriate use of directional signals, braking, acceleration, speed, maneuvering, lane positioning, and gap between the car and the car in front. Six situational categories were created for the experiment, including traffic light controlled intersections, one-way traffic, two-way traffic, giving way or yielding, maneuvering, and merging. The dependent variable included the number of occurrences of each type of behavioral error, and each type of situational error.
The same participant underwent the driving test twice, once with navigational support and once without. This helped improve validity, by showing if there was any impact of being instructed vs. driving solo. Statistical analyses used to tabulate the raw data include the Pearson correlation coefficients, Principal Axis Factoring (PFA) analysis and oblimin rotation with Kaiser normalization (p. 616). To determine the central correlations between driving and cognitive test performance, a Poisson distribution linear modeling with logic link function was used. PASW Statistics 18 was used to analyze the raw data (p. 616).
After processing the data, the researchers found that most their hypotheses were substantiated. Some cognitive errors were directly associated with specific driving errors, as predicted. The most commonly reported error was blind spot checking. Blind spot errors are a significant source of car accidents, which is why it is important to isolate the cognitive issues associated with lack of blind spot awareness or checking. Not all cognitive errors were as strongly correlated with driving errors as predicted. For example, reaction time was less predictive of driving errors than was predicted, and than is commonly believed. The results also showed that drivers made more errors in general in the self-navigation condition vs. The guided navigation system. The proposed reason for the difference was that more cognitive faculties were needed when driving solo vs. receiving navigational support.
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