Validity across four common street-crossing distraction indicators to predict pedestrian safety
-
Published:2024-01-20
Issue:1
Volume:24
Page:
-
ISSN:1471-2458
-
Container-title:BMC Public Health
-
language:en
-
Short-container-title:BMC Public Health
Author:
Ning Peishan,Xie Cifu,Cheng Peixia,Li Li,Schwebel David C.,Yang Yang,He Jieyi,Li Jie,Hu Guoqing
Abstract
Abstract
Background
Multiple distraction indicators have been applied to measure street-crossing distraction but their validities in predicting pedestrian safety are poorly understood.
Methods
Based on a video-based observational study, we compared the validity of four commonly used distraction indicators (total duration of distraction while crossing a street, proportion of distracted time over total street-crossing time, duration of the longest distraction time, and total number of distractions) in predicting three pedestrian safety outcomes (near-crash incidence, frequency of looking left and right, and speed crossing the street) across three types of distraction (mobile phone use, talking to other pedestrians, eating/drinking/smoking). Change in Harrell’s C statistic was calculated to assess the validity of each distraction indicator based on multivariable regression models including only covariates and including both covariates and the distraction indicator.
Results
Heterogeneous capacities in predicting the three safety outcomes across the four distraction indicators were observed: 1) duration of the longest distraction time was most predictive for the occurrence of near-crashes and looks left and right among pedestrians with all three types of distraction combined and talking with other pedestrians (Harrell’s C statistic changes ranged from 0.0310 to 0.0335, P < 0.05), and for the occurrence of near-crashes for pedestrians involving mobile phone use (Harrell’s C statistic change: 0.0053); 2) total duration of distraction was most predictive for speed crossing the street among pedestrians with the combination and each of the three types of distraction (Harrell’s C statistic changes ranged from 0.0037 to 0.0111, P < 0.05), frequency of looking left and right among pedestrians distracted by mobile phone use (Harrell’s C statistic change: 0.0115), and the occurrence of near-crash among pedestrians eating, drinking, or smoking (Harrell’s C statistic change: 0.0119); and 3) the total number of distractions was the most predictive indicator of frequency of looking left and right among pedestrians eating, drinking, or smoking (Harrell’s C statistic change: 0.0013). Sensitivity analyses showed the results were robust to change in grouping criteria of the four distraction indicators.
Conclusions
Future research should consider the pedestrian safety outcomes and type of distractions to select the best distraction indicator.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hunan Province, China
China Postdoctoral Science Foundation
Postdoctoral Innovative Talents Program of Hunan Province, China
Publisher
Springer Science and Business Media LLC
Reference26 articles.
1. Hamann C, Dulf D, Baragan-Andrada E, Price M, Peek-Asa C. Contributors to pedestrian distraction and risky behaviours during road crossings in Romania. Inj Prev. 2017;23(6):370–6.
2. Nasar J, Hecht P, Wener R. Mobile telephones, distracted attention, and pedestrian safety. Accid Anal Prev. 2008;40(1):69–75.
3. Ning PS, Hu GQ. Progress on epidemiological characteristics and interventions of pedestrian distraction. Zhonghua Liu Xing Bing Xue Za Zhi. 2022;43(2):277–81. Chinese.
4. National Highway Traffic Safety Administration. Fatality Analysis Reporting System (FARS). https://www-fars.nhtsa.dot.gov/People/PeoplePedestrians.aspx. Accessed 24 Aug 2023.
5. Regan MA, Lee JD, Young KL. Driver distraction: theory, effects, and mitigation. Florida: CRC Press; 2009.