Related Experiment Video
Updated: Oct 23, 2025

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research
Published on: December 18, 2020
"Like it's wrong, but it's not that wrong:" Exploring the normalization of risk-compensatory strategies among young
Fareed Kaviani1, Kristie L Young2, Brady Robards3
1Monash Sustainable Development Institute, Monash University, Australia.
Introduction:
Young drivers are the most vulnerable road users and most likely to use a smartphone illegally while driving. Although when compared with drink-driving, attitudes to illegal smartphone risk are nearly identical, smartphone use among young drivers continues to increase.
Method:
Four in-depth focus groups were conducted with 13 young (18-25 years) drivers to gain insight into their perceptions of the risks associated with the behavior. Our aim was to determine how drivers navigate that risk and if their behavior shapes and informs perceptions of norms.
Results:
Three key themes emerged: (a) participants perceived illegal smartphone use as commonplace, easy, and benign; (b) self-regulatory behaviors that compensate for risk are pervasive among illegal smartphone users; and (c) risk-compensation strategies rationalize risks and perceived norms, reducing the seriousness of transgression when compared with drink-driving. Young drivers rationalized their own use by comparing their selfregulatory smartphone and driving skills with those of "bad drivers," not law abiders. Practical Applications: These findings suggest that smartphone behaviors shape attitudes to risk, highlighting the importance for any countermeasure aimed at reducing illegal use to acknowledge how a young person's continued engagement in illegal smartphone use is justified by the dynamic composition of use, risk assessment and the perceived norms.
Related Concept Videos
Schemas
Bullying
Social Traps
The Anchoring-and-Adjustment Heuristic
Determination of Expected Frequency
Guidelines and Strategies for Safe Computer Charting
Maintain Confidentiality and Security:

