Evidence map›Paper›PMID 37131910›Full record

ReviewCampbell systematic reviews2020

Police programmes that seek to increase community connectedness for reducing violent extremism behaviour, attitudes and beliefs.

Lorraine Mazerolle, Elizabeth Eggins, Adrian Cherney, Lorelei Hine, Angela Higginson, Emma Belton

Abstract readReview
In one paragraph

Review in Campbell systematic reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Lorraine MazerolleFaculty of Humanities and Social Sciences, School of Social Science, St Lucia Campus University of Queensland St Lucia Queensland Australia.
Elizabeth EgginsFaculty of Humanities and Social Sciences, School of Social Science, St Lucia Campus University of Queensland St Lucia Queensland Australia.
Adrian CherneyFaculty of Humanities and Social Sciences, School of Social Science, St Lucia Campus University of Queensland St Lucia Queensland Australia.
Lorelei HineFaculty of Humanities and Social Sciences, School of Social Science, St Lucia Campus University of Queensland St Lucia Queensland Australia.
Angela HigginsonFaculty of Law, School of Justice Research, Gardens Point Campus Queensland University of Technology Brisbane Queensland Australia.
Emma BeltonFaculty of Humanities and Social Sciences, School of Social Science, St Lucia Campus University of Queensland St Lucia Queensland Australia.

Funding

NTP INFORMATION SYSTEMS SUPPORT27305C0011 · NIEHS · Z-TECH CORPORATION · 2007 to 2009
$4.3M
PROVIDE RABBITS, RATS, MICE, HAMSTERS, GERBILS, GUINEA PIGS27307C0011 · NIEHS · PI BOLEN, WAYNE · 2007 to 2007
$500k
NIEHS NIH HHS 27305C0011NIEHS NIH HHS 27307C0011NIEHS NIH HHS 27398C0011
6 · The paper itself

Abstract

Background: Police can play a role in tackling violent extremism through disrupting terrorist plots and by working with communities to identify individuals at risk of radicalisation. Police programmes to tackle violent extremism can involve a range of approaches and partnerships. One approach includes efforts to improve community connectedness by working to address social isolation, belonging, economic opportunities and norms and values that may lead people to endorse or support violent extremist causes and groups. The assumption is that the risk of an individual being radicalised in the community can be reduced when police work in pothe international legal ordersitive ways with community members and groups to mobilise and support activities that help generate a sense of belonging and trust. Police programmes that build a sense of belonging and trust may help ensure individuals are not influenced by activities that violent extremists use to attract support for their cause. Objectives: The review aimed to systematically examine whether or not police programmes that seek to promote community connectedness are effective in reducing violent extremist behaviours, attitudes and beliefs. The review also sought to identify whether effectiveness varied by the intervention type and location. Search Methods: Using terrorism-related terms, we searched the Global Policing Database to identify eligible published and unpublished evaluations between January 2002 and December 2018. We supplemented this with comprehensive searches of relevant terrorism and counter-terrorism websites and research repositories, reference harvesting of eligible and topic-relevant studies, forward citation searches of eligible studies, hand-searches of leading journals and consultations with experts. Selection Criteria: Eligible studies needed to include an initiative that involved the police, either through police initiation, development, leadership or where the police were receivers of the programme (such as a training programme) or where the police delivered or implemented the intervention. The initiative also needed to be some kind of a strategy, technique, approach, activity, campaign, training, programme, directive or funding/organisational change that involved police in some way to promote community connectedness. Community connectedness was defined as being community consultation, partnership or collaboration with citizens and/or organisational entities. Eligible outcomes included violent extremism, along with radicalisation and disengagement which are considered to be attitudinal and belief-based components of violent extremism. These outcomes could be measured via self-report instruments, interviews, observations and/or official data. To be included, studies could utilise individuals, micro- or macroplaces as the participants. Finally, studies needed to provide a quantitative impact evaluation that utilised a randomised or quasi-experimental design with a comparison group that either did not receive the intervention, or that received "business-as-usual" policing, no intervention or an alternative intervention. Data Collection and Analysis: The systematic search identified 2,273 records (after duplicate removal). After systematic screening across two stages (title/abstract and full-text), just one study (reported in two documents) met the review eligibility criteria. Standardised mean differences (SMD) were used to estimate intervention effects for this single study and risk of bias was assessed using the Cochrane Risk of Bias in Non-Randomised Studies-Interventions tool (ROBINS-I). Results: The single eligible study ( Conclusions: The aim of this systematic review was to examine whether or not police programmes that seek to promote community connectedness are effective in reducing violent extremist behaviours, attitudes and beliefs. There is insufficient evidence available to ascertain whether such interventions achieve these outcomes. This finding is the result of the fact that interventions that have been evaluated tend to be characterised by evaluation designs that do not adopt experimental or quasi-experimental approaches or use outcomes that are outside of scope for this review. While the volume of studies identified provide support for the assertion that police can play a role in tackling violent extremism by participating in, and implementing, programmes that promote community connectedness, it is unclear at this time if such approaches work in reducing violent extremism. Whilst we conclude that investment needs to be made in more robust methods of evaluation to test for programme effectiveness, we acknowledge that conducting evaluation and research in the area of counter-terrorism/violent extremism is challenging.

Identifiers

PMID37131910
PMCPMC8356323

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.