Evidence map›Paper›PMID 42516988›Full record

ArticleForensic science international. Synergy2026

Enhancing quality assurance in forensic medicolegal opinions: A standardized training and auditing framework for Arab countries.

Mamdouh Kamal Zaki, Zahraa Khalifa Sobh

Abstract read
In one paragraph

Article in Forensic science international. Synergy, 2026. 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

2 authors.

Mamdouh Kamal ZakiSenior Consultant of Forensic Medicine, Egypt.
Zahraa Khalifa SobhForensic Medicine and Clinical Toxicology Department, Faculty of Medicine, Alexandria University, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quality assurance in medicolegal (ML) reporting is essential to ensure accuracy, consistency, and compliance with legal and scientific standards. Since forensic opinions significantly influence judicial decisions, it is crucial to uphold high standards. In the Arab region, there are notable differences in forensic medicine practices among countries, emphasizing the urgent need for unified standards. Therefore, this initiative aims to improve the quality of ML reporting by proposing a standardized training and auditing framework based on international best practices, tailored to the realities of Arab forensic institutions. A key part of this article is developing a training framework grounded in best practices to unify forensic medical examiner competencies and reduce variability. At the same time, a specialized auditing framework has been created for senior forensic leaders to improve institutional accountability. This includes implementing a structured auditing protocol that uses newly adopted standardized checklists to assess report quality and detect non-conformities. Additionally, institutional leaders are encouraged to systematically investigate the root causes of substandard opinions within their organizations using Root Cause Analysis (RCA) methodology. Identifying these root causes offers opportunities for improvement. We recommend implementing this initiative through a Training of Trainers (TOT) model. This method enables institutional leaders and senior practitioners to disseminate standardized practices across all levels effectively. The multiplying effects of this initiative are vital for enhancing quality assurance and promoting continuous improvement within forensic practice across Arab countries.

Indexed as

Arab countriesAuditingForensic medicolegal opinionQuality assuranceStandardized training

Identifiers

PMID42516988
PMCPMC13404065

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.