Texting while driving: a discrete choice experiment
Open accessAbstract
Texting while driving is one of the most dangerous types of distracted driving and contributes to a large number of transportation incidents and fatalities each year. Drivers text while driving despite being aware of the risks. Although some factors related to the decision to text while driving have been elucidated, more remains to be investigated in order to better predict and prevent texting while driving. To study decision making involved in reading a text message while driving, we conducted a discrete choice experiment with 345 adult participants recruited from Amazon's Mechanical Turk. Participants were presented with multiple choice sets, each involving two different scenarios, and asked to choose the scenario in which they would be more likely to text while driving. The attributes of the scenarios were the relationship to the text-message sender, the road conditions, and the importance of the message. The attributes varied systematically across the choice sets. Participants were more likely to read a text message while driving if the sender of the message was a significant other, the message was perceived to be very important, and the participant was driving on rural roads. Discrete choice experiments offer a promising approach to studying decision making in drivers and other populations because they allow for an analysis of multiple factors simultaneously and the trade-offs among different choices.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 58 · Cited by 20
Research works printed but not linked: 2
- Chandukala SR, Kim J, Otter T, Rossi PE, Allenby GM, 2008. Choice Models in Marketing: Economic Assumptions, Challenges and Trends, Vol. 2. Now Publishers Inc., Boston, MA.
- Train KE, 2009. Discrete choice methods with simulation. Cambridge university press.
- Authors
- Foreman, A. M., Friedel, J. E., Hayashi, Y., & Wirth, O.
- Affiliations
- National Institute for Occupational Safety and Health (US)
- Pennsylvania State University (US)
- Corresponding author
- Foreman, Anne M.
- Venue
- Accident Analysis & Prevention
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 149
- Pages
- 105823
- ISSN
- 0001-4575 (ISSN-L)
- PMC
- PMC8190565
- OpenAlex
- W3099028922
- Cited by
- 20
- References
- 58
- Citations by year
- 2025: 2 · 2024: 11 · 2023: 4 · 2022: 2 · 2021: 1
- FWCI
- 1.91
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Accident Analysis & Prevention (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Pennsylvania State University
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
- Social Sciences › Decision Sciences › Information Systems and Management › Personal Information Management and User Behavior
- Keywords
- texting while driving, driver distraction, driver decision-making, risk perception, road conditions, rural roads, discrete choice experiment, crash risk
- MeSH terms
- Accidents, Traffic, Distracted Driving, Adult, Automobile Driving, Dangerous Behavior, Humans, Text Messaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review