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Ba, Y; Zhang, W; Peng, Q; Salvendy, G; Crundall, D (2016)
Publisher: Taylor & Francis for the Chartered Institute for Ergonomics and Human Factors
Languages: English
Types: Article
Subjects:

Classified by OpenAIRE into

mesheuropmc: human activities
Objective: Drivers’ risk tendency is a key issue of on-road safety. The purpose of the present study was to explore individual differences in drivers’ decision-making processes, linking external behaviors to internal neural activity, to reveal the cognitive mechanisms of on-road risky behaviors. Methods: Twenty-four male drivers were split into two groups (risky versus safe drivers) by their self-reported risky driving, measured by the Driving Behavior Questionnaire (DBQ). To assess the drivers’ behavioral and neural patterns of decision-making, two psychological paradigms were adopted: the Iowa Gambling Task (IGT) and the Balloon Analogue Risk Task (BART). The performance of each task and corresponding Event Related Potentials (ERPs) evoked by feedback were recorded. Results: In IGT, both driver groups demonstrated similar capacities to realize the advantage choices (decks with larger expected rewards) through long-term selection-feedback process. However, the risky drivers showed higher preference for the risky choices (decks with identical expected rewards but larger variances) than the safe drivers. In BART, the risky drivers demonstrated higher adjusted pumps than that of the safe drivers, especially for the trials following previous negative feedback. More importantly, the risky drivers showed lower amplitudes of Feedback-Related Negativity (FRN) after negative feedbacks, as well as the lower amplitudes of loss-minus-gain FRN, in both paradigms. The significant between-group difference of P300 amplitudes was also reported, which was modified by specific paradigms and according feedbacks. Conclusion: The drivers’ on-road behaviors were determined by the cognitive process, indicated by the behavioral and neural patterns of decision-making. The risky drivers were relatively less error-revised and more reward-motivated, which were associated with the according neural processing of error-detection and reward-evaluation. In this light, it is feasible to quantize divers’ risk tendency in the cognitive stage before actual risky driving or traffic accidents, and intervene accordingly.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • This study was supported jointly by the National Natural Science Foundation of China under grant number 71371103 and 31271100, and the Open Funding Project of National Key Laboratory of Human Factors Engineering, under grant number HF2013-K-04.
    • Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665-683.
    • Arthur, W., Barret, G. V., & Alexander, R. A. (1991). Prediction of vehicular accident involvement: A meta-analysis. Human Performance, 4(2), 89-105.
    • Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50(1-3), 7-15.
    • Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1997). Deciding advantageously before knowing the advantageous strategy. Science, 275(5304), 1293-1295.
    • Bellebaum, C., Polezzi, D., & Daum, I. (2010). It is less than you expected: The feedback-related negativity reflects violations of reward magnitude expectations. Neuropsychologia, 48(11), 3343-3350.
    • Blockey, P. N., & Hartley, L. R. (1995). Aberrant driving behavior - errors and violations. Ergonomics, 38(9), 1759-1771.
    • Carlson, S. M., Zayas, V., & Guthormsen, A. (2009). Neural correlates of decision making on a gambling task. Child development, 80(4), 1076-1096.
    • Conner, M., Lawton, R., Parker, D., Chorlton, K., Manstead, A. S. R., & Stradlings, S. (2007). Application of the theory of planned behaviour to the prediction of objectively assessed breaking of posted speed limits. British Journal of Psychology, 98, 429-453.
    • Crowley, M. J., Wu, J., Crutcher, C., Bailey, C. A., Lejuez, C., & Mayes, L. C. (2009). Risk-taking and the feedback negativity response to loss among at-risk adolescents. Developmental Neuroscience, 31(1-2), 137-148.
    • Elliott, M. A., Armitage, C. J., & Baughan, C. J. (2007). Using the theory of planned behaviour to predict observed driving behaviour. British Journal of Social Psychology, 46, 69-90. doi: 10.1348/14466605x90801
    • Fein, G., & Chang, M. (2008). Smaller feedback ERN amplitudes during the BART are associated with a greater family history density of alcohol problems in treatment-naive alcoholics. Drug and Alcohol Dependence, 92(1-3), 141-148.
    • Frank, M. J., Woroch, B. S., & Curran, T. (2005). Error-related negativity predicts reinforcement learning and conflict biases. Neuron, 47(4), 495-501.
    • Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making Annual Review of Neuroscience (Vol. 30, pp. 535-574). Palo Alto: Annual Reviews.
    • Gully, S. M., Whitney, D. J., & Vanosdall, F. E. (1995). Prediction of police officers' traffic accident involvement using behavioral observations. Accident; analysis and prevention, 27(3), 355-362.
    • Hsu, M., Bhatt, M., Adolphs, R., Tranel, D., & Camerer, C. F. (2005). Neural systems responding to degrees of uncertainty in human decision-making. Science, 310(5754), 1680-1683.
    • Ivers, R., Senserrick, T., Boufous, S., Stevenson, M., Chen, H. Y., Woodward, M., & Norton, R. (2009). Novice Drivers' Risky Driving Behavior, Risk Perception, and Crash Risk: Findings From the DRIVE Study. American Journal of Public Health, 99(9), 1638-1644. doi: 14 10.2105/ajph.2008.150367
    • Iversen, H., & Rundmo, T. (2002). Personality, risky driving and accident involvement among Norwegian drivers. Personality and individual differences, 33(8), 1251-1263.
    • Jonah, B. A. (1986). Accident risk and risk-taking behaviour among young drivers. Accident; analysis and prevention, 18(4), 255-271.
    • Kennerley, S. W., Walton, M. E., Behrens, T. E., Buckley, M. J., & Rushworth, M. F. (2006). Optimal decision making and the anterior cingulate cortex. Nature neuroscience, 9(7), 940-947.
    • Lajunen, T., Parker, D., & Summala, H. (2004). The Manchester Driver Behaviour Questionnaire: a cross-cultural study. Accident Analysis and Prevention, 36(2), 231-238.
    • Lange, S., Leue, A., & Beauducel, A. (2012). Behavioral approach and reward processing: Results on feedback-related negativity and P3 component. Biological Psychology, 89(2), 416-425.
    • Lauriola, M., Panno, A., Levin, I. P., & Lejuez, C. W. (2014). Individual Differences in Risky Decision Making: A Meta-analysis of Sensation Seeking and Impulsivity with the Balloon Analogue Risk Task. Journal of Behavioral Decision Making, 27(1), 20-36.
    • Lejuez, C. W., Aklin, W. M., Jones, H. A., Richards, J. B., Strong, D. R., Kahler, C. W., & Read, J. P. (2003). The Balloon Analogue Risk Task (BART) differentiates smokers and nonsmokers. Experimental and Clinical Psychopharmacology, 11(1), 26-33.
    • Lejuez, C. W., Read, J. P., Kahler, C. W., Richards, J. B., Ramsey, S. E., Stuart, G. L., . . . Brown, R. A. (2002). Evaluation of a behavioral measure of risk taking: The Balloon Analogue Risk Task (BART). Journal of Experimental Psychology-Applied, 8(2), 75-84. doi: 10.1037//1076-898x.8.2.75
    • Nieuwenhuis, S., Gilzenrat, M. S., Holmes, B. D., & Cohen, J. D. (2005). The role of the locus coeruleus in mediating the attentional blink: A neurocomputational theory. Journal of Experimental Psychology-General, 134(3), 291-307.
    • Parker, D., Manstead, A. S., Stradling, S. G., & Reason, J. T. (1992). Determinants of intention to commit driving violations. Accident; analysis and prevention, 24(2), 117-131.
    • Parker, D., McDonald, L., Rabbitt, P., & Sutcliffe, P. (2000). Elderly drivers and their accidents: the Aging Driver Questionnaire. Accident Analysis and Prevention, 32(6), 751-759.
    • Parker, D., Reason, J. T., Manstead, A. S. R., & Stradling, S. G. (1995). Driving errors, driving violations and accident involvement. Ergonomics, 38(5), 1036-1048.
    • Poulter, D. R., Chapman, P., Bibby, P. A., Clarke, D. D., & Crundall, D. (2008). An application of the theory of planned behaviour to truck driving behaviour and compliance with regulations. Accident Analysis and Prevention, 40(6), 2058-2064.
    • Reason, J., Manstead, A., Stradling, S., Baxter, J., & Campbell, K. (1990). Errors and violations on the roads: a real distinction? Ergonomics, 33(10-11), 1315-1332.
    • San Martin, R., Appelbaum, L. G., Pearson, J. M., Huettel, S. A., & Woldorff, M. G. (2013). Rapid Brain Responses Independently Predict Gain Maximization and Loss Minimization during Economic Decision Making. Journal of Neuroscience, 33(16), 7011-7019.
    • Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007). The neural basis of loss aversion in decision-making under risk. Science, 315(5811), 515-518.
    • Turner, C., & McClure, R. (2003). Age and gender differences in risk-taking behaviour as an explanation for high incidence of motor vehicle crashes as a driver in young males. Injury control and safety promotion, 10(3), 123-130.
    • Ulleberg, P., & Rundmo, T. (2003). Personality, attitudes and risk perception as predictors of risky
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