Evidence map›Paper›PMID 37520998›Full record

ArticleHeliyon2023

Saen Fanai, Masoud Mohammadnezhad

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. 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
0.4field-weighted citation impact, top 41% of its field
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, 2 citations in OpenAlex.

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

2 authors at 2 institutions in 3 countries.

Saen FanaiDepartment of Public Health, Ministry of Health, Port Vila, Vanuatu.
Masoud MohammadnezhadSchool of Nursing and Healthcare Leadership, University of Bradford, Bradford, West Yorkshire, United Kingdom.
University of Bradford · GBVanuatu Cultural Centre · VU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Around 1.35 million deaths are caused by Road Traffic Injuries (RTIs) each year. This study aimed to explore the perceptions of Vanuatu's Health Care Workers (HCWs) regarding the existing preventative strategies for RTI. Materials and methods: In 2020, this study used qualitative approaches to collect data from HCWs using Focus Group Discussions (FGDs). Study participants were self-identified Ni-Vanuatu HCWs who had been serving for more than 6 months in three main hospitals where the study was conducted and purposive sampling was used to gather the study participants. To guide the FGDs, a semi-structured open-ended questionnaire was created. Thematic analysis was used to processed the data obtained, based on predetermined themes that were based on theory while also enabling the data to determine new themes. Result: From 5 FGDs with 22 HCWs who were emergency nurses, doctors and public health officers, data saturation was reached. The study yielded five main themes and sixteen subthemes. The relevance and trends of RTI, barriers to effective care, pre-hospital management capacity, barriers to pre-hospital care and addressing RTI were among the key subjects. The findings suggest that addressing health institutional leadership and resources will improve prevention of RTIs. Conclusion: Prevention of RTIs is hindered by the lack of health institutional capacities in terms of leadership and resources that include emergency equipment, financial and trained human resources. The health sector should consider developing stronger leadership in road safety to be an essential part of its core business.

Indexed as

Health care workersPerceptionRisk factorsRoad traffic injuryVanuatu

Identifiers

PMID37520998
PMCPMC10374962
OpenAlexW4384945610

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.