Evidence map›Paper›PMID 33033483›Full record

ArticleFrontiers in psychiatry2020

Victimization of People With Severe Mental Illness Outside and Within the Mental Health Care System: Results on Prevalence and Risk Factors From a Multicenter Study.

Verena Rossa-Roccor, Peter Schmid, Tilman Steinert

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
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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

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

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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

3 authors.

Verena Rossa-RoccorSchool of Population and Public Health, University of British Columbia, Vancouver, BC, Canada.
Peter SchmidDepartment of Psychiatry and Psychotherapy I Weissenau, Ulm University, Ravensburg, Germany.
Tilman SteinertDepartment of Psychiatry and Psychotherapy I Weissenau, Ulm University, Ravensburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We performed a cross-sectional study using a self-reporting survey to assess lifetime violent and non-violent victimization in people with severe mental illness experienced both inside (i.e., any service providing mental health care such as psychiatric hospitals, psychosocial rehabilitative programs, or outpatient care) and outside (i.e., in the personal life of the participants) of the mental health care system. We recruited 170 participants from 20 community mental health facilities. We built logistic regression models to assess potential risk factors for victimization inside the mental health care system. Outside of the mental health care system, the most commonly reported events were theft (n=93, 54.7%), physical violence without use of a weapon (n=87, 51.2%), and sexual harassment (n=82, 50.6%). Within the mental health care system, most commonly reported incidents were theft (n=68, 40.0%), sexual assault (n=18, 10.6%), and physical violence (n=47, 27.7%) by other patients or staff. Significant risk factors for specific victimization events inside the mental health care system were psychotic disorder, victimization in childhood and youth, female gender, number of hospitalizations, and duration of illness. Findings call for increased attention to victimization of people with severe mental illness, especially within the mental health care system as such victimization events may severely impact patients' trajectories.

Indexed as

illegal offences against patientspatients as victimsrisk factors for violence in mental health care systemvictimization in psychiatryviolence in mental health care system

Identifiers

PMID33033483
PMCPMC7509533

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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.