eprintid: 10173813
rev_number: 6
eprint_status: archive
userid: 699
dir: disk0/10/17/38/13
datestamp: 2023-07-25 13:59:53
lastmod: 2023-07-25 13:59:53
status_changed: 2023-07-25 13:59:53
type: article
metadata_visibility: show
sword_depositor: 699
creators_name: Whiting, Daniel
creators_name: Mallett, Sue
creators_name: Lennox, Belinda
creators_name: Fazel, Seena
title: Assessing violence risk in first-episode psychosis: external validation, updating and net benefit of a prediction tool (OxMIV)
ispublished: pub
divisions: UCL
divisions: B02
divisions: C10
divisions: D17
divisions: FI6
note: © Author(s) (or their employer[s]) 2023. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).
abstract: BACKGROUND: Violence perpetration is a key outcome to prevent for an important subgroup of individuals presenting to mental health services, including early intervention in psychosis (EIP) services. Needs and risks are typically assessed without structured methods, which could facilitate consistency and accuracy. Prediction tools, such as OxMIV (Oxford Mental Illness and Violence tool), could provide a structured risk stratification approach, but require external validation in clinical settings. OBJECTIVES: We aimed to validate and update OxMIV in first-episode psychosis and consider its benefit as a complement to clinical assessment. METHODS: A retrospective cohort of individuals assessed in two UK EIP services was included. Electronic health records were used to extract predictors and risk judgements made by assessing clinicians. Outcome data involved police and healthcare records for violence perpetration in the 12 months post-assessment. FINDINGS: Of 1145 individuals presenting to EIP services, 131 (11%) perpetrated violence during the 12 month follow-up. OxMIV showed good discrimination (area under the curve 0.75, 95% CI 0.71 to 0.80). Calibration-in-the-large was also good after updating the model constant. Using a 10% cut-off, sensitivity was 71% (95% CI 63% to 80%), specificity 66% (63% to 69%), positive predictive value 22% (19% to 24%) and negative predictive value 95% (93% to 96%). In contrast, clinical judgement sensitivity was 40% and specificity 89%. Decision curve analysis showed net benefit of OxMIV over comparison approaches. CONCLUSIONS: OxMIV performed well in this real-world validation, with improved sensitivity compared with unstructured assessments. CLINICAL IMPLICATIONS: Structured tools to assess violence risk, such as OxMIV, have potential in first-episode psychosis to support a stratified approach to allocating non-harmful interventions to individuals who may benefit from the largest absolute risk reduction.
date: 2023-06
date_type: published
publisher: BMJ
official_url: http://dx.doi.org/10.1136/bmjment-2022-300634
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2031104
doi: 10.1136/bmjment-2022-300634
medium: Print
pii: bmjment-2022-300634
lyricists_name: Mallett, Susan
lyricists_id: SMALL45
actors_name: Flynn, Bernadette
actors_id: BFFLY94
actors_role: owner
funding_acknowledgements: 202836/Z/16/Z [Wellcome Trust]; BRC-1215-20005 [NIHR Oxford Health Biomedical Research Centre]; N/a [UCL/UCLH Biomedical Research Centre]; DRF-2018-11-ST2-069 [National Institute for Health Research (NIHR)]
full_text_status: public
publication: BMJ Ment Health
volume: 26
number: 1
article_number: e300634
event_location: England
citation:        Whiting, Daniel;    Mallett, Sue;    Lennox, Belinda;    Fazel, Seena;      (2023)    Assessing violence risk in first-episode psychosis: external validation, updating and net benefit of a prediction tool (OxMIV).                   BMJ Ment Health , 26  (1)    , Article e300634.  10.1136/bmjment-2022-300634 <https://doi.org/10.1136/bmjment-2022-300634>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10173813/1/e300634.full.pdf