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Driving Skills Training for Older Adults: An Assessment of DriveSharp

Published online by Cambridge University Press:  09 December 2015

Katherine A. Johnston ,
David Borkenhagen  and
Charles T. Scialfa
Katherine A. Johnston
Affiliation:
Department of Psychology, University of Calgary
David Borkenhagen
Affiliation:
Department of Psychology, University of Calgary
Charles T. Scialfa*
Affiliation:
Department of Psychology, University of Calgary
*
†La correspondance et les demandes de tirés-à-part doivent être adressées à: / Correspondence and requests for reprints should be sent to: Charles T. Scialfa, Ph.D. Department of Psychology University of Calgary Calgary, AB T2N 1N4 (scialfa@ucalgary.ca)
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Abstract

Computer-based, cognitive training procedures aim to increase safety by improving skills related to driving, such as speed-of-processing and the Useful Field of View. The current study assessed the effectiveness of DriveSharp in training older drivers in a naturalistic class setting. Participants (n = 24) attended 10 hours of DriveSharp classes over 5 weeks. Pre- and post-testing sessions assessed improvements on a dynamic hazard perception test, Trails A and Trails B. A control group (n = 18) completed only pre- and post-testing sessions. In-class training times were lower than expected. Participants’ improvement in the games leveled off after the first assessment and the DriveSharp group did not demonstrate a significant improvement in performance compared to the control group. Among several usability issues, the most problematic were misunderstanding task goals and the difference between training and evaluation. There are several implications for those using DriveSharp to enhance older drivers’ safety.

Résumé

Les procédures de formation cognitive informatique visent à augmenter la sécurité en améliorant les compétences relatives à la conduite, comme la vitesse-de-traitement et le Useful Field of View. L'étude actuelle a évalué l'efficacité du DriveSharp dans la formation des conducteurs âgés dans un cadre de classe réaliste. Les participants (n = 24) ont assisté à 10 heures de cours de DriveSharp pendant 5 semaines. Les séances pré- et post-test ont evalués améliorations sur un essai dynamique de la perception du risque, Trails A et Trails B. Un groupe de contrôle (n = 18) a terminé seulement les séances pré- et post-test. En classe, les temps de formation étaient plus bas que prévus. L'amélioration des participants aux jeux ont stabilisée après la première évaluation, et le groupe de DriveSharp n'a pas démontré une amélioration significative des performances sur les tests, par rapport au groupe de contrôle. Parmi plusieurs questions relatives à la facilité d'utilisation, les plus problématiques étaient le malentendudes objectifs de la tâche et la différence entre la formation et l'évaluation. Il y a plusieurs implications pour ceux qui utilisent DriveSharp pour améliorer la sécurité des conducteurs âgés.

Keywords

agingcognitive trainingDriveSharpdriving skillshazard perceptionvieillissmentformation cognitiveDriveSharpcompetences de conduiteperception des risques
Type
Articles
Information
Canadian Journal on Aging / La Revue canadienne du vieillissement , Volume 34 , Issue 4 , December 2015 , pp. 532 - 544
Copyright
Copyright © Canadian Association on Gerontology 2015 

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References

Ball, K., Berch, D. B., Helmers, K. F., Jobe, J. B., Leveck, M. D., Marsiske, M., et al. (2002). Effects of cognitive training interventions with older adults. A randomized controlled study. The Journal of the American Medical Association, 288, 2271–2281.CrossRefGoogle Scholar
Ball, K., & Owsley, C. (1993). The useful field of view test: A new technique for evaluating age-related declines in visual function. Journal of the American Optometry Association, 64, 71–79.Google Scholar
Ball, K., Owsley, C., Sloane, M. E., Roenker, D. L., & Bruni, J. R. (1993). Visual attention problems as a predictor of vehicle crashes in older drivers. Investigative Ophthalmology and Visual Science, 34, 3110–3123.Google Scholar
Ball, K., Roenker, D., Bruni, J., Owsley, C., Sloane, M., Ball, D., et al. (1991). Driving and visual search: Expanding the useful field of view. Investigative Ophthalmology and Visual Science (Suppl. 32), 1041.Google Scholar
Ball, K. K., Edwards, J. D., Ross, L. A., & McGwin, G. (2010). Cognitive training decreases motor vehicle collision involvement among older drivers. Journal of the American Geriatrics Society, 58, 2107–2113.CrossRefGoogle ScholarPubMed
Ball, K. K, Roenker, D. L., Wadley, V. G., Edwards, J. D., Roth, D. L., McGwin, G., et al. (2006). Can high-risk older drivers be identified through performance-based measures in a Department of Motor Vehicles setting? Journal of American Geriatric Society, 54, 77–84.Google Scholar
Bowers, A. R., Anastasio, R. J., Sheldon, S. S., O’Connor, M. G., Hollis, A. M., Howe, P. D., et al. (2013). Can we improve clinical prediction of at-risk older drivers? Accident Analysis and Prevention, 59, 537–547.Google Scholar
Chapman, P., Underwood, G., & Roberts, K. (2002).Visual search patterns in trained and untrained novice drivers. Transportation Research Part F, Traffic Psychology and Behavior, 5, 157–167.Google Scholar
Chipman, M., MacGregor, C., Smiley, A., & Lee-Gosselin, M. (1992). Time vs. distance as measures of exposure in driving surveys. Accident Analysis & Prevention, 24(6), 679–684.Google Scholar
Dobbs, B., & Schopflocher, D. (2010). The introduction of a new screening tool for the identification of cognitively impaired medically at-risk drivers: The SIMARD A modification of the DemTect. Journal of Primary Care and Community Health, 1, 119–127.Google Scholar
Dobres, J., Potter, A., Reimer, B., Mehler, B, Mehler, A. & Coughlin, J. (2013). Assessing the impact of “Brain Training” on driving performance, visual behavior, and neuropsychological measures. Proceedings of the Seventh International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design, Bolton Landing NY, June 17–20. Ames, IA: Public Policy Center of the University of Iowa (pp. 50–56). Available at http://drivingassessment.uiowa.edu/2013/proceedings Google Scholar
Edwards, J. D., Delahunt, P. B., & Mahncke, H. W. (2009). Cognitive speed of processing training delays driving cessation. Journal of Gerontology A Biological Science Medical Science, 64, 1262–1267.CrossRefGoogle ScholarPubMed
Edwards, K. J., Leonard, K., Lunsman, M., Dodson, J., Bradley, S., Myers, C., et al. (2008). Acceptability and validity of older driver screening with the driving health inventory. Accident Analysis and Prevention, 40, 1157–1163.Google Scholar
Evans, L., (2004). Traffic Safety. Bloomfield Hills, MI: Science Serving Society.Google Scholar
Fisher, D., Pollatsek, A., & Pradhan, A. (2006). Can novice drivers be trained to scan for information that will reduce their likelihood of a crash? Injury Prevention, 12, 25–29.Google Scholar
Folstein, M., Folstein, S., & McHugh, P. (1975). Mini-mental state: A practical method for grading the cognitive status of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.Google Scholar
Goode, K. T., Ball, K., Sloane, M., Roenker, D. L., Roth, D. L., Myers, R. S., et al. (1998). Useful field of view and other neurocognitive indicators of crash risk in older adults. Journal of Clinical Psychology in Medical Settings, 5, 425–440.Google Scholar
Hakamies-Blomqvist, L., Raitanen, T., & O’Neill, D. (2002). Driver ageing does not cause higher accidents per km. Transportation Research Part F: Traffic Psychology and Behavior, 5, 271–274.Google Scholar
Horswill, M. S., Anstey, K. J., Hatherly, C. G., & Wood, J. (2010). The crash involvement of older drivers is associated with their hazard perception latencies. Journal of the International Neuropsychological Society, 16, 939–944.Google Scholar
Horswill, M. S., Kemala, C. N., Wetton, M., Scialfa, C. T., & Pachana, N. A. (2010). Improving older drivers’ hazard perception ability. Psychology and Aging, 25, 464–469.Google Scholar
Horswill, M. S., Mannington, S., McCullough, C., Wood, J., Pachana, N., McWilliam, J., et al. (2008). The hazard perception ability of older drivers. Journal of Gerontology: Psychological Sciences, 63B, P212–P218.Google Scholar
Horswill, M. S., & McKenna, F. (2004). Drivers’ hazard perception ability: Situation awareness on the road. In Banbury, S., & Tremblay, S. (Eds.), A cognitive approach to situation awareness (pp. 155–175). Aldershot, UK: Ashgate.Google Scholar
Horswill, M. S., & Taylor, K., Newnam, S., Wetton, M., & Hill, A. (2013). Even highly experienced drivers benefit from a brief hazard perception training intervention. Accident Analysis and Prevention, 52, 100–110.Google Scholar
Li, G., Braver, E. R., & Chen, L. H. (2003). Fragility versus excessive crash involvement as determinants of high death rates per mile driven in older drivers. Accident Analysis and Prevention, 35, 227–235.Google Scholar
Lochner, M., & Trick, L. M. (2011). Attentional tracking of multiple vehicles in a highway driving scenario. Proceedings for 6th International Symposium on Human Factors in Driving Assessment, Training, and Vehicle Design.Google Scholar
Marrington, S. A., Horswill, M. S., & Wood, J. M. (2008). The effect of simulated cataracts on drivers’ hazard perception ability. Ophthalmology Vision Science, 85, 1121–1127.Google Scholar
McKenna, F. P., & Crick, J. L. (1991). Hazard perception in drivers: A methodology for testing and training. Final Report, Behavioural Studies Unit, Crowthorne, UK: Transport and Road Research Laboratory.Google Scholar
Meuleners, L. B., Harding, A., Lee, A. H., & Legge, M. (2006). Fragility and crash over-representation among older drivers in Western Australia. Accident Analysis and Prevention, 38, 1006–1010.Google Scholar
Nielsen, J. (2013). Seniors as web users. Neilsen Norman Group. Retrieved September 27, 2015 from http://www.nngroup.com/articles/usability-for-senior-citizens/ Google Scholar
Owsley, C., Ball, K., Sloane, M. E., Roenker, D. L., & Bruni, J. R. (1991).Visual/cognitive correlates of vehicle accidents in older drivers. Psychology of Aging, 6, 403–415.Google Scholar
Posit Science. (2010). DriveSharp overview and installation. Retrieved September 27, 2015 from http://www.brainhq.com/sites/default/files/pdfs/ds_install.pdf Google Scholar
Roenker, D. L., Cissell, G. M., Ball, K. K., Wadley, V. G., & Edwards, J. D. (2003). Speed-of-processing and driving simulator training result in improved driving performance. Human Factors, 45, 218–233.CrossRefGoogle ScholarPubMed
Ross, R., Cordazzo, S., & Scialfa, C. (2014). Predicting on-road driving performance and safety in healthy older adults. Journal of Safety Research, 51, 73–80.Google Scholar
Rubin, G. S., Ng, E. S., Bandeen-Roche, K., Keyl, P. M., Freeman, E. E., & West, S. K. (2007). A prospective, population-based study of the role of visual impairment in motor vehicle crashes among older drivers: The SEE study. Investigative Ophthalmology and Vision Science, 48, 1483–1491.Google Scholar
Scialfa, C., Borkenhagen, D., Lyon, J., Deschênes, M., Horswill, M., & Wetton, M. (2012a). The effects of driving experience on responses to a static hazard perception test. Accident Analysis and Prevention, 45, 547–553.CrossRefGoogle ScholarPubMed
Scialfa, C., Deschênes, M., Ference, J., Boone, J., Horswill, M., & Wetton, M. (2012b). Hazard perception in older drivers. International Journal of Human Factors and Ergonomics, 1, 221–233.Google Scholar
Sekuler, R., McLaughlin, C., & Yotsumoto, Y. (2008). Age-related changes in attentional tracking of multiple moving objects. Perception, 37, 867–876.Google Scholar
Sims, R. V., McGwin, G., Allman, R. M., Ball, K., & Owsley, C. (2000). Exploratory study of incident vehicle crashes among older drivers. Journal of Gerontology, 55, M22–M27.Google Scholar
Tombaugh, T. (2004). Trail making test A and B: Normative data stratified by age and education. Archives of Clinical Neuropsychology, 19, 204–213.Google Scholar
Trick, L. M., Perl, T., & Sethi, N. (2005). Age-related differences in multiple-object tracking. Journal of Gerontology: Series B: Psychological Sciences and Social Sciences, 60B, 102–105.Google Scholar
Willis, S. L., Tennstedt, S. L., Marsiske, M., Ball, K., Elias, J., Koepke, K. M., et al. (2006). Long-term effects of cognitive training on everyday functional outcomes in older adults. The Journal of the American Medical Association, 296, 2805–2814.CrossRefGoogle ScholarPubMed
Wood, J. M., Horswill, M. S., Lacherez, P. F., & Anstey, K. J. (2013). Evaluation of screening tests for predicting older driver performance and safety assessed by an on-road test. Accident Analysis and Prevention, 50, 1161–1168.Google Scholar