Evidence map›Paper›PMID 37876721›Full record

ReviewFrontiers in public health2023

Differences of corruption types in selected Western and central-eastern health systems during the COVID-19 pandemic: a rapid review.

Alejandro Gonzalez-Aquines, Adolfo C Cordero-Perez, Iwona Kowalska-Bobko

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in public health, 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
–field-weighted citation impact, top 79% 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, 0 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

3 authors at 3 institutions in 3 countries.

Alejandro Gonzalez-AquinesInstitute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, Kraków, Poland.
Adolfo C Cordero-PerezIndependent Researcher, Zurich, Switzerland.
Iwona Kowalska-BobkoInstitute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, Kraków, Poland.
Institute for Independent Studies Zürich · CHJagiellonian University · PLUniversity of Bradford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To identify, describe, and classify the cases of health corruption present in selected Western [the Netherlands and the United Kingdom (UK)] and Central-Eastern European (Poland and Slovakia) countries during the COVID-19 pandemic. Methods: A rapid review of the literature was conducted, evaluating data from 11 March 2020 to 15 April 2021. Information sources included MEDLINE via WoS, IBSS via ProQuest, Scopus, and gray literature. Results: Thirteen cases were identified across the four countries. The primary type of health corruption in Western European countries was procurement corruption, while misuse of (high) level positions was the most prevalent in Central-Eastern European countries. Actors from central governments were most involved in cases. The rule of law and anti-corruption watchdogs reported most cases in the United Kingdom and the Netherlands, while the media reported cases in Poland and Slovakia. Conclusion: The differences in types of corruption in WE and CEE countries emphasize the need to contextualize the approach to tackle corruption. Thus, further research in preventing and tackling corruption is a vital and necessary undertaking despite the inherent of conducting health corruption research.

Indexed as

COVID-19EuropeHumansNetherlandsPandemicsPolandCentral-Eastern EuropeCOVID-19health corruptionpublic health crisisWestern Europe

Identifiers

PMID37876721
PMCPMC10590903
OpenAlexW4387435860

What OpenQuestion holds

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LicenceCC BY
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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.