Police and public perspectives on the use and impacts of technology that expose enforcement locations for phone use while driving

Journal Article (2023)
Author(s)

Verity Truelove (USC – University of the Sunshine Coast)

Kayla Stefanidis (USC – University of the Sunshine Coast)

Laura Mills (USC – University of the Sunshine Coast)

Oscar Oviedo-Trespalacios (Queensland University of Technology, TU Delft - Safety and Security Science)

DOI related publication
https://doi.org/10.1016/j.ssci.2023.106155 Final published version
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Publication Year
2023
Language
English
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Journal title
Safety Science
Volume number
164
Article number
106155
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Abstract

Avoiding being caught and punished has consistently been demonstrated to be a key predictor of continued engagement in risky and illegal phone use while driving. This is a large concern, as the presence of applications such as Google Maps, Apple Maps, Waze, and social media pages/groups that share the location of enforcement activities related to phone use while driving has increased. The present investigation aimed to understand the impact of these technologies on phone use while driving using a mixed-methods approach. First, to obtain an enforcement perspective, 15 police officers from Queensland (Australia) were interviewed. Three main themes were identified, suggesting that the use of the technologies 1) can encourage dangerous driving and allow drivers to avoid punishment more often, 2) do not impact police enforcement of the phone use while driving law and 3) can promote exposure to enforcement. Next, a quantitative survey was implemented with Queensland drivers (n = 622, 58.7% females). A cluster analysis was initially conducted to categorise the different types of phone offenders (acknowledging differential deterrability). Two clusters (high-frequency and low-frequency phone offenders) were created. A hierarchal binary logistic regression indicated that using Apple maps, Facebook police location sites and checking these Facebook sites predicted membership in the high-frequency phone offender group (Waze and Google maps were not significant). After controlling for the use of these technologies, avoiding being caught and punished predicted being in the high-frequency phone offender group. The results confirmed the impact of these technologies on phone use while driving behaviour.

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