Using non-linear methods to investigate the criterion validity of traffic-psychological test batteries

Risser, Ralf; Chaloupka, Ch; Grundler, Wolfgang; Sommer, Markus; Häusler, Joachim; Kaufmann, Caroline L.

doi:10.1016/j.aap.2006.12.018

Cited by 41 publications

(35 citation statements)

References 19 publications

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“…The analysis encompassed measures N and E, as well as age, while the dependent variables were the basic dimensions of cognitive processing, which we established as the quickness and lability of the response time and the cooperation of peripheral and central pro cesses of attention. Obviously, the question which cognitive functioning as pects should be recognized as key factors in driving [34] could make the topic of a separate article. Quickness, vari ability and precision of response are identified amongst many other factors as key aspects of cognitive process ing [1].…”

Section: Discussionmentioning

confidence: 99%

The effect of age and personality on the main cognitive processes in drivers

Biernacki

Tarnowski

2011

International Journal of Occupational Medicine and Environmental Health

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Objectives: The purpose of this study is the evaluation of how the decline of cognitive abilities caused by aging is mode rated by biologically determined personality dimensions: Neuroticism (N) and Extraversion (E). Materials and Methods:The research was conducted with the participation of 160 men in good physical health, professional drivers, aged 20-70 (Mean = 40, SD = 11). Personality traits were measured using Eysenck's Personality Questionnaire -Revised (EPQR), while Ravens Progressive Matrices, Go/noGo Task and Peripheral Perception Test were used to evaluate cognitive pro cesses. The score of Ravens Progressive Matrices was treated as a control variable. Results: The results of the study, based on a Hierarchical Multiple Regression Analysis, indicate that besides the intelligence level, age is the best predictor of cognitive functioning level and that this influence is additionally moderated by the N trait level as well as, less frequently, by the interaction of age and E. Conclusion: This means that high N trait level increases the influence of age on cognitive functions decline. When the N trait level was low, the age differences in measures of cognitive performance were not sig nificant. Thus, the level of N trait may play an important role in the process of cognitive aging. The results are discussed in the context of a driving safety research.

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Section: Discussionmentioning

confidence: 99%

The effect of age and personality on the main cognitive processes in drivers

Biernacki

Tarnowski

2011

International Journal of Occupational Medicine and Environmental Health

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“…They validated their model using leave-one-out cross-validation. Risser et al (2008) recruited a mixed-age sample of 222 people and constructed a neural network model to predict on-road driving performance. They validated their model using jack-knife, bootstrapping, and testing on a new sample.…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of driving ability: Are we building valid models?

Hoggarth

Innes

Dalrymple‐Alford

et al. 2015

Accident Analysis & Prevention

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“…Previous researches have shown that the test results contribute significantly to the prediction of fitness to drive, in a standardized driving test (23)(24)(25)(26). The following five tests of VTS were used in this study:…”

Section: Computerized Traffic Psychological Testmentioning

confidence: 99%

“…All the measurements were done using the Vienna test system (VTS), which is an objective and reliable tool to measure the cognitive abilities of drivers (23,24). This study measured score changes of simple and choice reaction time, selective attention, visual orientation, and visual memory as a result of HFPC.…”

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confidence: 99%

Do Hands-Free Cell Phone Conversation While Driving Increase the Risk of Cognitive Distraction Among Drivers? A Cross-Over Quasi-Experimental Study

Sadeghian

Karbakhsh

Saremi

et al. 2018

Iran Red Crescent Med J

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Background: Background: Conversation over the cell phone while driving is a known risk factor for road traffic crash. Using handsfree to talk on the cell phone may remove visual and manual distraction yet not the cognitive distraction. Objectives: The purpose of this study was to better understand the mechanisms of cognitive distraction due to hands-free cell phone conversation (HFPC) while driving. Methods: Twelve male and 12 female University students in Tehran, Iran, were selected via the consecutive convenient sampling method, and randomly assigned to one of the following administrations of cross-over quasi-experimental study design, during year 2016: Administration 1, participants performed the tests while involved in HFPC, took rest for 60 minute, and then performed the tests another time without HFPC; Administration 2, participants performed the tests without HFPC, took rest, and then performed the tests another time with HFPC. Each participant moved to the other administration after 7 to 10 days. The Vienna test system (VTS) was used to measure simple and choice reaction time, selective attention, visual orientation, and visual memory. Linear regression analysis was used to study the change in test scores due to HFPC.

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Using non-linear methods to investigate the criterion validity of traffic-psychological test batteries

Cited by 41 publications

References 19 publications

The effect of age and personality on the main cognitive processes in drivers

The effect of age and personality on the main cognitive processes in drivers

Prediction of driving ability: Are we building valid models?

Do Hands-Free Cell Phone Conversation While Driving Increase the Risk of Cognitive Distraction Among Drivers? A Cross-Over Quasi-Experimental Study

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