Evidence map›Paper›PMID 27294182›Full record

ArticleData in brief2016

Naturalistic speeding data: Drivers aged 75 years and older.

Anna Chevalier, Aran John Chevalier, Elizabeth Clarke, John Wall, Kristy Coxon, Julie Brown, Rebecca Ivers, Lisa Keay

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Data in brief, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Anna ChevalierThe George Institute for Global Health, Sydney Medical School, The University of Sydney, GPO Box 5389, Sydney, NSW 2001, Australia.
Aran John ChevalierSafer Roads Consulting, 53 Lachlan St, Thirroul, NSW 2515, Australia.
Elizabeth ClarkeKolling Institute of Medical Research, Sydney Medical School, The University of Sydney, Level 10, Kolling Building 6, Royal North Shore Hospital, St Leonards, NSW 2065, Australia.
John WallThe Centre for Road Safety, Transport for NSW, Level 3, 84 Crown St, Wollongong, NSW 2500, Australia.
Kristy CoxonThe George Institute for Global Health, Sydney Medical School, The University of Sydney, GPO Box 5389, Sydney, NSW 2001, Australia; School of Science and Health, Western Sydney University, Narellan Road Campbelltown, NSW 2560, Australia.
Julie BrownNeuroscience Research Australia (NeuRA), Margarete Ainsworth Building, Barker St, Randwick, NSW 2031, Australia.
Rebecca IversThe George Institute for Global Health, Sydney Medical School, The University of Sydney, GPO Box 5389, Sydney, NSW 2001, Australia.
Lisa KeayThe George Institute for Global Health, Sydney Medical School, The University of Sydney, GPO Box 5389, Sydney, NSW 2001, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The data presented in this article are related to the research article entitled "A longitudinal investigation of the predictors of older drivers׳ speeding behavior" (Chevalier et al., 2016) [1], wherein these speed events were used to investigate older drivers speeding behavior and the influence of cognition, vision, functional decline, and self-reported citations and crashes on speeding behavior over a year of driving. Naturalistic speeding behavior data were collected for up to 52 weeks from volunteer drivers aged 75-94 years (median 80 years, 52% male) living in the suburban outskirts of Sydney. Driving data were collected using an in-vehicle monitoring device. Global Positioning System (GPS) data were recorded at each second and determined driving speed through triangulation of satellite collected location data. Driving speed data were linked with mapped speed zone data based on a service-provider database. To measure speeding behavior, speed events were defined as driving 1 km/h or more, with a 3% tolerance, above a single speed limit, averaged over 30 s. The data contains a row per 124,374 speed events. This article contains information about data processing and quality control.

Indexed as

DeviceIn-vehicle monitoringNaturalisticOlder driversRoad safetySpeed

Identifiers

PMID27294182
PMCPMC4889889

What OpenQuestion holds

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LicenceCC BY
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.