Skip to main content

[]

Intended for healthcare professionals
Skip to main content
Restricted access
Research article
First published online February 28, 2018

Voluntary- and Involuntary-Distraction Engagement: An Exploratory Study of Individual Differences

Abstract

Objective

The aim of this study was to explore individual differences in voluntary and involuntary driver-distraction engagement.

Background

Distractions may stem from intentional engagement in secondary tasks (voluntary) or failing to suppress non-driving-related stimuli or information (involuntary). A wealth of literature has examined voluntary distraction; involuntary distraction is not particularly well understood. Individual factors, such as age, are known to play a role in how drivers engage in distractions. However, it is unclear which individual factors are associated with voluntary- versus involuntary-distraction engagement and whether there is a relation between how drivers engage in these two distraction types.

Method

Thirty-six participants, ages 25 to 39, drove in a simulator under three conditions: voluntary distraction with a self-paced visual-manual task on a secondary display, involuntary distraction with abrupt onset of irrelevant visual-audio stimuli on the secondary display, and no distraction.

Results

The number of glances toward the secondary display under voluntary distraction was not correlated to that under involuntary distraction. The former was associated with gender, age, annual mileage, and self-reported distraction engagement; such associations were not observed for the latter. Accelerator release time in response to lead-vehicle braking was delayed similarly under both conditions.

Conclusion

Propensity to engage in voluntary distractions appears to be not related to the inability of suppressing involuntary distractions. Further, voluntary and involuntary distraction both affect braking response. These findings have implications for design of in-vehicle technologies, which may be sources of both distraction types.

Get full access to this article

View all access and purchase options for this article.

References

Anderson B. A., Laurent P. A., Yantis S. (2011). Value-driven attentional capture. Proceedings of the National Academy of Sciences, 108, 10367–10371.
Arnett J. (1994). Sensation seeking: A new conceptualization and a new scale. Personality and Individual Differences, 16, 289–296.
Arthur W., Doverspike D. (1992). Locus of control and auditory selective attention as predictors of driving accident involvement: A comparative longitudinal investigation. Journal of Safety Research, 23, 73–80.
Beanland V., Fitzharris M., Young K. L., Lenné M. G. (2013). Driver inattention and driver distraction in serious casualty crashes: Data from the Australian National Crash In-Depth Study. Accident Analysis & Prevention, 54, 99–107.
Bendak S., Al-Saleh K. (2010). The role of roadside advertising signs in distracting drivers. International Journal of Industrial Ergonomics, 40, 233–236.
Bugg J. M., DeLosh E. L., Davalos D. B., Davis H. P. (2007). Age differences in Stroop interference: Contributions of general slowing and task-specific deficits. Aging, Neuropsychology, and Cognition, 14, 155–167.
Carter P. M., Bingham C. R., Zakrajsek J. S., Shope J. T., Sayer T. B. (2014). Social norms and risk perception: Predictors of distracted driving behavior among novice adolescent drivers. Journal of Adolescent Health, 54(5, Suppl.), S32–S41.
Chattington M., Reed N., Basacik D., Flint A., Parkes A. (2009). Investigating Driver Distraction: The Effects of Video and Static Advertising (No. PPR409). Wokingham, UK: Transport Research Laboratory.
Chen H.-Y. W., Donmez B. (2016). What drives technology-based distractions? A Structural Equation Model of social and psychological factors related to technology-based driver distraction engagement. Accident Analysis & Prevention, 91, 166–174.
Chen H.-Y. W., Donmez B., Hoekstra-Atwood L., Marulanda S. (2016). Self-reported engagement in driver distraction: An application of the theory of planned behaviour. Transportation Research F: Traffic Psychology and Behaviour, 38, 151–163.
Crundall D., Underwood G. (2011). Visual attention while driving: Measures of eye movements used in driving research. In Porter B. E. (Ed.), Handbook of traffic psychology (pp. 137–148). San Diego, CA: Academic Press.
Dingus T. A., Guo F., Lee S., Antin J. F., Perez M., Buchanan-King M., Hankey J. (2016). Driver crash risk factors and prevalence evaluation using naturalistic driving data. Proceedings of the National Academy of Sciences of the United States of America, 113, 2636–2641.
Dingus T. A., Klauer S. G., Neale V. L., Petersen A., Lee S. E., Sudweeks J. D., … Gupta S. (2006). The 100-Car Naturalistic Driving Study, Phase II: Results of the 100-car field experiment (No. DOT HS 810 593). Washington, DC: National Highway Traffic Safety Administration.
Donmez B., Boyle L. N., Lee J. D. (2007). Safety implications of providing real-time feedback to distracted drivers. Accident Analysis & Prevention, 39, 581–590.
Drews F. A., Yazdani H., Godfrey C. N., Cooper J. M., Strayer D. L. (2009). Text messaging during simulated driving. Human Factors, 51, 762–770.
Feng J., Marulanda S., Donmez B. (2014). Susceptibility to driver distraction questionnaire: Development and relation to relevant self-reported measures. Transportation Research Record: Journal of the Transportation Research Board, 2434, 26–34.
Fitch G. M., Soccolich S. A., Guo F., McClafferty J., Fang Y., Olson R. L., … Dingus T. A. (2013). The impact of hand-held and hands-free cell phone use on driving performance and safety-critical event risk (No. DOT HS 811 757). Washington, DC: National Highway Traffic Safety Administration.
Fukuda K., Vogel E. K. (2011). Individual differences in recovery time from attentional capture. Psychological Science, 22(3), 361–368.
Green P. (2002). Where do drivers look while driving (and for how long)? In Olson P. L., Dewar R. E. (Eds.), Human factors in traffic safety (2nd ed., pp. 77–110). Tucson, AZ: Lawyers & Judges.
Hartley A. A. (1993). Evidence of the selective preservation of spatial selective attention in old age. Psychology and Aging, 8, 371–379.
Hoekstra-Atwood L., Chen H.-Y. W., Donmez B. (2017). Simulator study of involuntary driver distraction under different perceptual loads. Transportation Research Record: Journal of the Transportation Research Board, 2663, 12–19.
Horberry T., Anderson J., Regan M. A., Triggs T. J., Brown J. (2006). Driver distraction: The effects of concurrent in-vehicle tasks, road environment complexity and age on driving performance. Accident Analysis & Prevention, 38, 185–191.
Horrey W. J., Lesch M. F. (2008). Factors related to drivers’ self-reported willingness to engage in distracting in-vehicle activities. In Proceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting (pp. 1546–1550). Santa Monica, CA: Human Factors and Ergonomics Society.
Hughes P. K., Cole B. L. (1986). What attracts attention when driving? Ergonomics, 29, 377–391.
International Organization for Standardization. (2007). Road vehicles—Ergonomic aspects of transport information and control systems—Occlusion method to assess visual demand due to the use of in-vehicle systems (ISO Report No. 16673:2007). Geneva, Switzerland: International Organization for Standardization.
Irwin D. E., Colcombe A. M., Kramer A. F., Hahn S. (2000). Attentional and oculomotor capture by onset, luminance and color singletons. Vision Research, 40, 1443–1458.
Lansdown T. C. (2012). Individual differences and propensity to engage with in-vehicle distractions: A self-report survey. Transportation Research Part F: Traffic Psychology and Behaviour, 15, 1–8.
Lee J. D., Young K. L., Regan M. A. (2008). Defining driver distraction. In Regan M. A., Lee J. D., Young K. L. (Eds.), Driver distraction: Theory, effects, and mitigation (pp. 31–40). Boca Raton, FL: CRC Press.
Li W., Gkritza K., Albrecht C. (2014). The culture of distracted driving: Evidence from a public opinion survey in Iowa. Transportation Research Part F: Traffic Psychology and Behaviour, 26, Part B, 337–347.
Lucas M. (2012). 89-A. Retrieved from http://www.89a.co.uk/archive
Marulanda S., Chen H.-Y. W., Donmez B. (2015). Test–retest reliability of the susceptibility to driver distraction questionnaire. Transportation Research Record: Journal of the Transportation Research Board, 2518, 54–59.
Maylor E. A., Lavie N. (1998). The influence of perceptual load on age differences in selective attention. Psychology and Aging, 13, 563–573.
Merritt P., Hirshman E., Wharton W., Stangl B., Devlin J., Lenz A. (2007). Evidence for gender differences in visual selective attention. Personality and Individual Differences, 43, 597–609.
Murphy P. (2002). Inhibitory control in adults with attention-deficit/hyperactivity disorder. Journal of Attention Disorders, 6, 1–4.
National Highway Traffic Safety Administration. (2017). Distracted driving 2015 (DOT HS 812 381). Washington, DC: Author.
Pinheiro J., Bates D., DebRoy S., Sarkar D., & R Core Team. (2015). nlme: Linear and nonlinear mixed effects models. R package version 3.1-122 [Computer software]. Retrieved from https://CRAN.R-project.org/package=nlme
Pöysti L., Rajalin S., Summala H. (2005). Factors influencing the use of cellular (mobile) phone during driving and hazards while using it. Accident Analysis & Prevention, 37, 47–51.
Stoet G. (2010). Sex differences in the processing of flankers. Quarterly Journal of Experimental Psychology, 63, 633–638.
Theeuwes J. (1992). Perceptual selectivity for color and form. Perception & Psychophysics, 51, 599–606.
Theeuwes J., Atchley P., Kramer A. F. (2000). On the time course of top-down and bottom-up control of visual attention. In Driver J. (Ed.), Attention and performance XVIII: Control of cognitive processes (pp. 105–124). Cambridge, MA: MIT Press.
Theeuwes J., Belopolsky A. V. (2012). Reward grabs the eye: Oculomotor capture by rewarding stimuli. Vision Research, 74, 80–85.
Theeuwes J., Godijn R. (2001). Attentional and oculomotor capture. In Folk C. I., Gibson B. S. (Eds.), Attraction, distraction and action: Multiple perspectives on attentional capture (pp. 121–150). Amsterdam, Netherlands: Elsevier.
Trick L. M., Enns J. T. (2009). A two-dimensional framework for understanding the role of attentional selection in driving. In Castro C. (Ed.), Human factors of visual and cognitive performance in driving (pp. 63–73). Boca Raton, FL: CRC Press.
Victor T., Dozza M., Bärgman J., Boda C.-N., Engström J., Markkula G. (2015). Analysis of naturalistic driving study data: Safer glances, driver inattention, and crash risk (No. SHRP2 Report S2-S08A-RW-1). Washington, DC: National Academy of Sciences.
Wallace B. (2003). Driver distraction by advertising: Genuine risk or urban myth? In Proceedings of the Institution of Civil Engineers—Municipal Engineer 156 (pp. 185–190). London: Institution of Civil Engineers.
Weir C., Bruun C., Barber T. (1997). Are backward words special for older adults? Psychology and Aging, 12, 145–149.
Xu R. (2003). Measuring explained variation in linear mixed effects models. Statistics in Medicine, 22, 3527–3541.

Biographies

Huei-Yen Winnie Chen is an assistant professor at the University at Buffalo, State University of New York, Department of Industrial and Systems Engineering. She received her PhD in industrial engineering from the University of Toronto.
Liberty Hoekstra-Atwood is a human factors researcher at Battelle Memorial Institute. She received her MASc in industrial engineering at the University of Toronto, where she worked in the Human Factors and Applied Statistics Laboratory.
Birsen Donmez is an associate professor at the University of Toronto, Department of Mechanical and Industrial Engineering. She received her PhD in industrial engineering from the University of Iowa in 2007.

Cite article

Cite article

Cite article

OR

Download to reference manager

If you have citation software installed, you can download article citation data to the citation manager of your choice

Share options

Share

Share this article

Share with email
Email Article Link
Share on social media

Share access to this article

Sharing links are not relevant where the article is open access and not available if you do not have a subscription.

For more information view the Sage Journals article sharing page.

Information, rights and permissions

Information

Published In

Article first published online: February 28, 2018
Issue published: June 2018

Keywords

  1. driver distraction
  2. driving simulator
  3. voluntary distraction
  4. involuntary distraction
  5. individual differences

Rights and permissions

© 2018, Human Factors and Ergonomics Society.
Request permissions for this article.
PubMed: 29489421

Authors

Affiliations

Huei-Yen Winnie Chen
University at Buffalo, Buffalo, New York
Liberty Hoekstra-Atwood
Birsen Donmez
University of Toronto, Toronto, Canada

Notes

Birsen Donmez, Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Rd., Toronto, ON M5S 3G8, Canada; e-mail: [email protected].

Metrics and citations

Metrics

Journals metrics

This article was published in Human Factors: The Journal of the Human Factors and Ergonomics Society.

View All Journal Metrics

Article usage*

Total views and downloads: 2038

*Article usage tracking started in December 2016


Altmetric

See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores



Articles citing this one

Receive email alerts when this article is cited

Web of Science: 15 view articles Opens in new tab

Crossref: 19

  1. Do automation and digitalization distract drivers? A systematic review
    Go to citationCrossrefGoogle Scholar
  2. Susceptibility to distracted driving: The role of personality and individual factors
    Go to citationCrossrefGoogle Scholar
  3. Training benefits driver behaviour while using automation with an attention monitoring system
    Go to citationCrossrefGoogle Scholar
  4. When Do Users Prefer Voice Control Systems in Vehicles? A Survey of Chinese Drivers
    Go to citationCrossrefGoogle Scholar
  5. Gamification of Driver Distraction Feedback: A Simulator Study With Younger Drivers
    Go to citationCrossrefGoogle Scholar
  6. Handbook of Human‐Machine Systems
    Go to citationCrossrefGoogle Scholar
  7. Risk Assessment of Distracted Driving Behavior Based on Visual Stability Coefficient
    Go to citationCrossrefGoogle Scholar
  8. The Effects of ADAS on Driving Behavior: A Case Study
    Go to citationCrossrefGoogle Scholar
  9. The Role of ADAS While Driving in Complex Road Contexts: Support or Overload for Drivers?
    Go to citationCrossrefGoogle Scholar
  10. Distracted when Using Driving Automation: A Quantile Regression Analysis of Driver Glances Considering the Effects of Road Alignment and Driving Experience
    Go to citationCrossrefGoogle Scholar
  11. View More

Figures and tables

Figures & Media

Tables

View Options

Access options

If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:

HFES members can access this journal content using society membership credentials.

HFES members can access this journal content using society membership credentials.


Alternatively, view purchase options below:

Purchase 24 hour online access to view and download content.

Access journal content via a DeepDyve subscription or find out more about this option.

View options

PDF/EPUB

View PDF/EPUB

Full Text

View Full Text