Citation

Kang L, Vij A, Hubbard A, Shaw D. J. Saf. Res. 2021; 79: 135-147.

Copyright

(Copyright © 2021, U.S. National Safety Council, Publisher Elsevier Publishing)

DOI

10.1016/j.jsr.2021.08.014

PMID

34847997

Abstract

INTRODUCTION: Safety is a critical factor in promoting sustainable urban non-motorized travel modes like bicycles. Helmets have shown to be effective in reducing injury severity in bicycle crashes, however, their effects on bicyclists' behaviors still requires deeper understanding, especially amid the emerging trend of using shared bicycles. Risk compensation effects suggest that bicyclists may offset perceived gains in safety from wearing a helmet by increasing risk-taking behaviors. A better understanding of these compensation effects can be useful in assessing various bicycle safety related programs.

METHOD: Using a sample of 131 bicyclists from the San Francisco Bay area, this research studies how bicyclists respond with respect to risk-taking behaviors under various urban-street conditions, as a function of helmet use. Study participants were each shown 12 videos, shot in Berkeley, California, from the perspective of a bicyclist riding behind another bicyclist. A fractional factorial experiment design was used to systematically vary contextual attributes (e.g., speed, bike lane facilities, on-street parking, passing vehicles) across the videos. After each video, participants were asked to indicate if they would overtake the bicyclist in the video. With the help of data adaptive estimation techniques, targeted maximum likelihood estimation (TMLE) was applied to estimate the average risk difference between helmeted users and non-users, controlling for self-selection effects. Individual-based nonparametric bootstrap was performed to assess the uncertainty associated with the estimator.

RESULTS: Our findings suggest, on average, individuals more likely to wear a helmet are 15.6% more likely to undertake a risky overtaking maneuver.

Practical Applications: This study doesn't try to oppose mandatory helmet laws, but rather serves as a cautionary warning that road safety programs may need to consider strategies in which unintended impact of bicycle helmet use can be mitigated. Moreover, our findings also provide additional evaluation component when it comes to the cost-benefit assessment of helmet-related laws.

Keywords: Risk Compensation

Language: en

Keywords

Bicycle helmet; Data adaptive estimation; Risk compensation effects; Risk-taking behavior; Targeted maximum likelihood estimation