Evidence map›Paper›PMID 34126275›Full record

ArticleAccident; analysis and prevention2021

Reducing distracted pedestrian behavior using Bluetooth beacon technology: A crossover trial.

David C Schwebel, Ragib Hasan, Russell Griffin, Raiful Hasan, Mohammad Aminul Hoque, Md Yasser Karim, Kevin Luo, Anna Johnston

Abstract read
In one paragraph

Article in Accident; analysis and prevention, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

David C SchwebelUniversity of Alabama at Birmingham, USA. Electronic address: schwebel@uab.edu.
Ragib HasanUniversity of Alabama at Birmingham, USA.
Russell GriffinUniversity of Alabama at Birmingham, USA.
Raiful HasanUniversity of Alabama at Birmingham, USA.
Mohammad Aminul HoqueUniversity of Alabama at Birmingham, USA.
Md Yasser KarimUniversity of Alabama at Birmingham, USA.
Kevin LuoUniversity of Alabama at Birmingham, USA.
Anna JohnstonUniversity of Alabama at Birmingham, USA.

Funding

Using Bluetooth Beacon Technology to Reduce Distracted Pedestrian BehaviorR21HD095270 · NICHD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI HASAN, RAGIB, SCHWEBEL, DAVID C · 2018 to 2019
$391k
NICHD NIH HHS R21 HD095270
6 · The paper itself

Abstract

backgroundThe number of fatal pedestrian injuries in the United States has steadily increased over the past decade. Multiple factors likely contribute to this trend, but the growth of pedestrians distracted by mobile devices is widely hypothesized to play a major role. Existing strategies to reduce distracted pedestrian behavior are few and mostly ineffective. The present study evaluated StreetBit, a mostly-passive primary prevention program to reduce distracted pedestrian behavior by alerting distracted pedestrians directly on their smartphone when they approach an intersection, reminding them to attend to traffic as they crossed.

methods385 individuals who regularly crossed a target street corner at an urban university downloaded StreetBit on their phones and participated in a crossover design study whereby the app was inactive for 3 weeks (baseline behavior phase), actively provided alerts for 3 weeks (intervention phase), and then was inactive again for 4 weeks (post-intervention phase). User distraction while crossing the intersection was collected electronically for a total of 34,923 street-crossing events throughout the 10-week study.

resultsIn crude (unadjusted) models, participant distraction was similar across all phases of the research; this result was maintained after adjusting for potential covariates as well as after conducting a sensitivity analysis limited to data from only week 3 of each study intervention phase. In a model stratified by phone/warning type and baseline distraction rates, Android phone users who received a warning that blocked the full screen and had a high baseline distraction rate (≥75% distracted crossings) had a 64% decreased odds of distraction during the alert phase (OR 0.36, 95% CI 0.25-0.51) and a 52% decreased odds of distraction during the post-intervention phase (OR 0.48, 95% CI 0.25-0.94). Users reported positive impressions about the StreetBit app in a post-intervention survey. DISCUSSION: StreetBit, an innovative app designed to prevent distracted pedestrian behavior through a mostly-passive primary prevention strategy relying on intrusive reminders, proved effective among smartphone users who received a warning blocking the full screen and who were frequently distracted at baseline, but not among other users. The results appear to reflect the confluence of two influencing factors. First, due to software development limitations, visually-distracted Android users received a highly intrusive app warning that blocked their smartphone screen whereas iOS users received a less intrusive banner notification blocking a small upper portion of the screen. Second, most users were curious to see if the app was functioning properly, creating artificially-inflated estimates of distraction as users purposefully watched their phones when crossing. Thus, our results indicate promise for StreetBit as an effective intervention and warrant continued software development and empirical testing.

Indexed as

PedestriansAccidents, TrafficAttentionCross-Over StudiesHumansSafetyWalkingBluetooth beaconCrossover trialDistracted pedestrianRoad traffic safety

Identifiers

PMID34126275
PMCPMC8384715

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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.