Evidence map›Paper›PMID 22332998›Full record

ArticleBMC medicine2012

A public health approach to understanding and preventing violent radicalization.

Kamaldeep S Bhui, Madelyn H Hicks, Myrna Lashley, Edgar Jones

Abstract read
In one paragraph

Article in BMC medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 3 pooled it
–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

24 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Public Mental Health Approaches to Online Radicalisation: An Empty Systematic Review.International journal of environmental research and public health · 2023
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  16. Moroccan Health Care: A Link to Radicalization and Proposed Solution.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2019
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  18. What should global mental health do about violent extremism?Global mental health (Cambridge, England) · 2019
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  20. And if there were another way out? Questioning the prevalent radicalization models.Canadian journal of public health = Revue canadienne de sante publique · 2018
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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.

Kamaldeep S BhuiWolfson Institute of Preventive Medicine, Queen Mary, University of London, UK. k.s.bhui@qmul.ac.uk
Madelyn H Hicks
Myrna Lashley
Edgar Jones

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVery recent acts of terrorism in the UK were perpetrated by 'homegrown', well educated young people, rather than by foreign Islamist groups; consequently, a process of violent radicalization was proposed to explain how ordinary people were recruited and persuaded to sacrifice their lives. DISCUSSION: Counterterrorism approaches grounded in the criminal justice system have not prevented violent radicalization. Indeed there is some evidence that these approaches may have encouraged membership of radical groups by not recognizing Muslim communities as allies, citizens, victims of terrorism, and victims of discrimination, but only as suspect communities who were then further alienated. Informed by public health research and practice, a new approach is proposed to target populations vulnerable to recruitment, rather than rely only on research of well known terrorist groups and individual perpetrators of terrorist acts.

conclusionsThis paper proposes public health research and practice to guard against violent radicalization.

Indexed as

Knowledge ManagementHumansPopulation GroupsPractice Guidelines as TopicPublic HealthResearch DesignTerrorismUnited KingdomViolence

Identifiers

PMID22332998
PMCPMC3305506

What OpenQuestion holds

Textmetadata
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.