Evidence map›Paper›PMID 37181281›Full record

ArticleTransportation research interdisciplinary perspectives2022

A Naturalistic Study Assessing the Impact of Daytime Running Lights and Vehicle Passing events on Cyclist's Physiological Stress.

Archana Venkatachalapathy, Cara Hamann, Steven Spears, Elizabeth A Shirtcliff, Anuj Sharma

Abstract read
In one paragraph

Article in Transportation research interdisciplinary perspectives, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Archana VenkatachalapathyIowa State University.
Cara HamannUniversity of Iowa.
Steven SpearsUniversity of Iowa.
Elizabeth A ShirtcliffUniversity of Oregon.
Anuj SharmaIowa State University.

Funding

ACL HHS R49CE002108NCIPC CDC HHS R49 CE002108
6 · The paper itself

Abstract

Bicyclists are vulnerable road users who are at a greater risk for injury and fatality during crashes. Additionally, the "near-miss" incidents they experience during regular trips can increase the perceived risk and deter them from riding again. This paper aims to use naturalistic bicycling data collected in Johnson County, Iowa to: 1) study the effect of factors such as road surface type, parked vehicles, pavement markings and car passing events on cyclists' physiological stress and 2) understand the effect of daytime running lights (DRL) as an on-bicycle safety system in providing comfort to cyclists and highlight of their presence on the road to other vehicles. A total of 37 participants were recruited to complete trips over two weekends, one weekend with DRL and the other without DRL. Recruitment was specifically targeted toward cyclists who expressed discomfort riding in traffic. Data were collected using a front forward facing camera, GPS, and a vehicle lateral passing distance sensor mounted on the bicycle and a Empatica E4 wrist band (providing physiological data such as electrodermal activity; EDA) worn by the cyclist. Data from those sources were cleaned, processed, merged, and aggregated into time windows depicting car passing and no car passing events. Mixed effects models were used to study the cyclists' skin conductance response (phasic EDA) and baseline skin conductance level (tonic EDA). Car passing, parked vehicles, and roads with dashed centerline markings were observed to increase the cyclists stress. The use of DRL had negligible impact on cyclist stress on roads.

Indexed as

BicycleCar Passing EventsDaytime Running LightsElectrodermal ActivityPerceived riskSafety

Identifiers

PMID37181281
PMCPMC10174271

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.