Evidence map›Paper›PMID 41451066›Full record

ArticleIndian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine

Road Traffic Accidents in the Northern Border Region of Saudi Arabia: A Retrospective Cross-Sectional Study Using Secondary Data.

Fatima Alnoor, Ebtesam Babeker, Ehssan Ahmed, Alaa Mustafa

Abstract read
In one paragraph

Article in Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine. 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

4 authors.

Fatima AlnoorDepartment of Mathematics, College of Science, Northern Border University, Arar, Saudi Arabia.
Ebtesam BabekerDepartment of Mathematics, College of Science, Northern Border University, Arar, Saudi Arabia.
Ehssan AhmedDepartment of Mathematics, College of Science, Northern Border University, Arar, Saudi Arabia.
Alaa MustafaDepartment of Mathematics, College of Science, Northern Border University, Arar, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Road traffic accidents (RTAs) are a global public health concern and a major concern in developing countries such as Saudi Arabia. Objective: To describe the characteristics, patterns, and contributing factors of RTAs in the Northern Border area of Saudi Arabia for the time period from 2016 to 2018. Methods: The data used for this retrospective cross-sectional study were obtained from the Saudi Open Data Platform. Variables included the frequency, type, cause, driver age, and license status of the accidents. The data were analyzed using SPSS v25 (IBM Corp., Armonk, NY, USA), and descriptive statistics were calculated, and chi-square tests were used to determine significance ( Results: Out of 34,311 RTAs recorded, 96.81% were damage only, 2.31% were injury, and 0.88% were fatal (statistically significant). Speeding was the major cause (54.6% - 60.75%). Young drivers 18-30 represented the majority (52.98%). Most had an expired or no license, and a significant association was found between age group and accident outcome ( Conclusions: The high incidence of RTAs involving young drivers with expired or no license, the prevalence of speeding as a cause of accidents, and the global prevalence of RTAs emphasize the need for more effective enforcement of traffic law with targeted educational interventions.

Indexed as

Fatalitiesinjuriestraffic accidentsvehicle

Identifiers

PMID41451066
PMCPMC12735399

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.