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Published on: September 15, 2017
Converting the DriveSafe subtest of DriveSafe DriveAware for touchscreen administration
Beth Cheal1,2, Anita Bundy1,3, Ann-Helen Patomella4
1Faculty of Health Sciences, University of Sydney, Sydney, New South Wales, Australia.
Background:
DriveSafe measures awareness of the driving environment. It is one subtest of DriveSafe DriveAware, a cognitive fitness-to-drive screening instrument. We converted DriveSafe to a touchscreen format for ease of administration; this necessitated the development of an automatic data collection and scoring system to reflect the decision that would otherwise have been made by an expert rater. We applied a structured process to determine what constituted 'correct' scores. We then examined the resulting scoring parameters to determine if these discriminated at-risk drivers from a comparison sample.
Methods:
Thirty at-risk older drivers and 30 younger drivers took touchscreen DriveSafe. Following presentation of images containing between one and four objects/hazards for 4 seconds, participants indicated their recall of object/hazard characteristics (type, location and direction of movement) by touching the screen. We analysed responses via descriptive statistics to compare spread, accuracy and consistency; and via a Fisher's exact test to determine whether the set scoring parameters could discriminate between at-risk and comparison drivers.
Results:
Fisher's exact test results indicated 24 of 28 location zones and 18 of 28 direction ranges discriminated at-risk drivers from the comparison group (P < 0.05). Frequency of missed or incorrectly identified hazards was much higher for the at-risk group for all variables. At-risk drivers missed or misidentified significantly (P < 0.00) more object types (34%), directions (47%), and locations (36%) than the comparison group (≤4% for each variable). At-risk drivers entered 31 additional responses for objects/hazards not displayed; the comparison group entered no additional responses.
Conclusion:
The automatic variable data collection and scoring system reflected decisions that would have been made by an expert rater. This systematic process provided automated scoring decisions that enabled us to discriminate at-risk drivers from a comparison group. Psychometric evaluation of data gathered with touchscreen DriveSafe is required prior to use in clinical practice.
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