Evidence map›Paper›PMID 31204729›Full record

ArticleJournal of injury & violence research2019

Challenges of establishing a road traffic injury surveillance system: a qualitative study in a middle-income country.

Sakineh Sharifian, Reza Khani Jazani, Homayoun Sadeghi-Bazargani, Davoud Khorasani-Zavareh

Abstract read
In one paragraph

Article in Journal of injury & violence research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

4 authors.

Sakineh Sharifian
Reza Khani Jazani
Homayoun Sadeghi-Bazargani
Davoud Khorasani-ZavarehDepartment of Health in Emergencies and Disasters, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Email:davoud.khorasani@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEstablishing effective road traffic injury surveillance is an important priority for low- and middle-income countries since a large proportion of fatal road traffic injuries occur in these countries. A surveillance system can coordinate the activities and compile the data gathered by all road safety organizations. This study aims to explore the challenges of establishing road traffic injury surveillance based on the stakeholders' experiences.

methodsThis is a qualitative content analysis study that was performed in 2018 in Iran. The study was conducted through interviews with 13 participants and employed purposeful sampling. Data generation was continued until concept saturation.

resultsFive main categories and 17 sub-categories were identified including: policy-making (legal authority, stakeholders, content policy and plan); process (collection and recording, analysis and interpretation, dissemination and feedback); resources and infrastructure (technology, staff, structure, finance); coherence and coordination (communication, dispersion, cooperation, consensus); and context (socio-cultural, political).

conclusionsBy creating a clear structure for a road traffic injury surveillance system, identifying data collection systems and stakeholders in the field of road safety and injury prevention, determining a clear goal for improving road safety, and formulating policies for the dissemination of road traffic crash data among stakeholders, it will be possible to overcome the obstacles to establishing a surveillance system for road traffic injury.

Indexed as

Population SurveillanceAccident PreventionAccidents, TrafficHumansInterviews as TopicIranQualitative Research

Identifiers

PMID31204729
PMCPMC6646822

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.