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Texting at the light and other forms of device distraction behind the wheel

Overview of attention for article published in BMC Public Health, September 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)

Mentioned by

news
1 news outlet
twitter
9 tweeters

Citations

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13 Dimensions

Readers on

mendeley
55 Mendeley
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Title
Texting at the light and other forms of device distraction behind the wheel
Published in
BMC Public Health, September 2015
DOI 10.1186/s12889-015-2343-8
Pubmed ID
Authors

James J. Bernstein, Joseph Bernstein

Abstract

Cell phones are a well-known source of distraction for drivers, and owing to the proliferation of text messaging services, web browsers and interactive apps, modern devices provide ever-increasing temptation for drivers to take their eyes off the road. Although it is probably obvious that drivers' manual engagement of a device while their vehicles are in motion is potentially dangerous, it may not be clear that such engagement when the vehicle is at rest (an activity broadly labeled "texting at the light") can also impose risks. For one thing, a distracted driver at rest may fail to respond quickly to sudden changes in road conditions, such as an ambulance passing through. In addition, texting at the light may decrease so-called "situational awareness" and lead to driving errors even after the device is put down. To our knowledge, the direct comparison of the rate of device usage by drivers at rest with the rate of device usage by drivers in motion has not been reported. We collected information on 2000 passenger vehicles by roadside observation. For the first group of 1000 passenger vehicles stopped at a traffic light, device usage ("texting", "talking", "none"), gender of the driver, vehicle type, seatbelt usage and presence of front seat passengers were recorded. For a second set of 1000 vehicles in motion, device usage alone was noted. Statistical significance for differences in rates was assessed with the chi-square test. We found that 3 % of drivers in motion were texting and 5 % were talking. Among the stopped drivers, 14.5 % were texting and 6.3 % were talking. In the stopped-vehicle set, gender and vehicle type were not associated with significant differences in device usage, but having a front seat passenger and using seatbelts were. Device usage is markedly higher among drivers temporarily at rest compared with those in motion, and the presence of a front seat passenger, who may help alleviate boredom or reprimand bad behavior, is associated with lower device usage rates among vehicles stopped at a light. These observations may help identify suitable steps to decrease distracted driving and thereby minimize traffic trauma.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 2%
Unknown 54 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 10 18%
Student > Ph. D. Student 9 16%
Student > Doctoral Student 7 13%
Researcher 5 9%
Student > Master 5 9%
Other 12 22%
Unknown 7 13%
Readers by discipline Count As %
Medicine and Dentistry 10 18%
Engineering 9 16%
Psychology 8 15%
Nursing and Health Professions 7 13%
Social Sciences 5 9%
Other 8 15%
Unknown 8 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 March 2021.
All research outputs
#1,581,820
of 18,846,561 outputs
Outputs from BMC Public Health
#1,757
of 12,465 outputs
Outputs of similar age
#27,289
of 258,968 outputs
Outputs of similar age from BMC Public Health
#1
of 1 outputs
Altmetric has tracked 18,846,561 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,465 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 258,968 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them