Evidence map›Paper›PMID 41743485›Full record

ArticleFrontiers in public health2026

Child centred policing: supporting trauma informed front line police practices with girls who have lived experiences of child sexual exploitation in the United Kingdom.

Tracee Green, Aravinda Kosaraju, Emma Soutar

Abstract read
In one paragraph

Article in Frontiers in public health, 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

3 authors.

Tracee GreenCentre for Child Protection, School of Social Sciences, University of Kent, Gillingham, United Kingdom.
Aravinda KosarajuCentre for Child Protection, School of Social Sciences, University of Kent, Gillingham, United Kingdom.
Emma SoutarCentre for Child Protection, School of Social Sciences, University of Kent, Gillingham, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Child sexual exploitation (CSE) continues to present significant challenges for policing, with longstanding concerns about inconsistent recognition of risk, victim-blaming narratives, and uneven application of trauma-informed approaches. Methods: This study reports on the co-design, delivery, and evaluation of a pilot simulation-based training tool developed by the University of Kent's Centre for Child Protection in partnership with Kent Police. Guided by a participatory action research framework, a mixed-methods evaluation was conducted, including pre-, mid-, and post-training questionnaires, live polling, and independent observation. Results: Quantitative findings demonstrated improvements in officers' self-reported confidence, knowledge, and practice skills. Qualitative feedback indicated reductions in victim-blaming language and greater use of trauma-informed framing. Observations reinforced these shifts, highlighting enhanced officer engagement with contextual safeguarding and recognition of trauma responses. Discussion: Although limited to a single police force and reliant on self-reported data, the pilot suggests that simulation-based learning is a promising approach to embedding trauma-informed practice in frontline policing. The findings underline the value of experiential training for disrupting entrenched biases and supporting culture change in sensitive areas of practice.

Indexed as

child sexual exploitation (CSE)evaluationpolicingsimulationtrainingtrauma-informed approachviolence against women and girls (VAWG)

Identifiers

PMID41743485
PMCPMC12931523

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.