Evidence map›Paper›PMID 40374725›Full record

ArticleScientific reports2025

A pilot study on treatment content in virtual reality-assisted aggression therapy at a maximum-security forensic psychiatric clinic.

Fredrik Sivermo, Fernando Renee González Moraga, Märta Wallinius

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
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.

Fredrik SivermoResearch Department, Regional Forensic Psychiatric Clinic, Växjö, Sweden.
Fernando Renee González MoragaResearch Department, Regional Forensic Psychiatric Clinic, Växjö, Sweden. fernando_renee.gonzalez_moraga@med.lu.se.
Märta WalliniusResearch Department, Regional Forensic Psychiatric Clinic, Växjö, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous findings on results of treatment of aggression in violent offenders show inconsistent results, and implementations of such treatments have demonstrated varying success with sometimes marginal gains in forensic settings. New methods, incorporating virtual reality as a tool for experiential learning, have been put forward yet require deepened investigations concerning both treatment content and effects. The principal objective of this study is to examine the treatment content of the revised VRAPT intervention. Specifically, the study focuses on understanding how the content of the VRAPT intervention is conceptualized from the perspectives of both patients and therapists. Inductive manifest content analysis was applied on content of treatment workbooks (N = 6 + 7), provided by both patients and therapists as part of seven concluded VRAPT treatments at a maximum-security forensic psychiatric clinic in Sweden. Three manifest content categories were identified, relating to treatment content: Skills-training, Tailoring of the intervention, and Self-awareness. While generally quite similar, some potentially important differences between patients' and therapists' perspectives on the VRAPT intervention were apparent. The findings suggest the necessity of further research into optimizing VR-assisted treatments in forensic psychiatry.

Indexed as

AggressionForensic PsychiatryVirtual RealityAdultFemaleHumansMaleMiddle AgedPilot ProjectsSwedenViolenceAggressionContent analysisForensic psychiatryTreatmentVirtual realityVRVRAPT

Identifiers

PMID40374725
PMCPMC12081903

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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.