Evidence map›Paper›PMID 38245693›Full record

ArticleBMC public health2024

Validity across four common street-crossing distraction indicators to predict pedestrian safety.

Peishan Ning, Cifu Xie, Peixia Cheng, Li Li, David C Schwebel, Yang Yang, Jieyi He, Jie Li, Guoqing Hu

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Peishan NingDepartment of Epidemiology and Health Statistics, Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health, Central South University, Changsha, 410013, China.
Cifu XieChangsha Center for Disease Control and Prevention, Changsha, 410004, China.
Peixia ChengDepartment of Child, Adolescent and Women's Health, School of Public Health, Capital Medical University, Beijing, 100071, China.
Li LiDepartment of Epidemiology and Health Statistics, Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health, Central South University, Changsha, 410013, China.
David C SchwebelDepartment of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, 35233, USA.
Yang YangDepartment of Statistics, Franklin College of Arts and Sciences, University of Georgia, Athens, GA, USA.
Jieyi HeDepartment of Epidemiology and Health Statistics, Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health, Central South University, Changsha, 410013, China.
Jie LiDepartment of Epidemiology and Health Statistics, Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health, Central South University, Changsha, 410013, China.
Guoqing HuDepartment of Epidemiology and Health Statistics, Hunan Provincial Key Laboratory of Clinical Epidemiology, Xiangya School of Public Health, Central South University, Changsha, 410013, China. huguoqing009@gmail.com.

Funding

China Postdoctoral Science Foundation 2021M693551National Natural Science Foundation of China 82073672, 82103950 and 72091514Natural Science Foundation of Hunan Province, China 2021JJ40808Postdoctoral Innovative Talents Program of Hunan Province, China 2021RC2008
6 · The paper itself

Abstract

backgroundMultiple distraction indicators have been applied to measure street-crossing distraction but their validities in predicting pedestrian safety are poorly understood.

methodsBased 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.

resultsHeterogeneous 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.

conclusionsFuture research should consider the pedestrian safety outcomes and type of distractions to select the best distraction indicator.

Indexed as

PedestriansSafetyAccidents, TrafficHumansObservational Studies as TopicRisk-TakingText MessagingVideo RecordingWalkingIndicatorPedestrianPredictive validitySafetyStreet-crossing distraction

Identifiers

PMID38245693
PMCPMC10799455

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.