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. 2023 Jan;53(2):590-596.
doi: 10.1017/S0033291721002063. Epub 2021 May 24.

Modifiable risk factors for inpatient violence in psychiatric hospital: prospective study and prediction model

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Modifiable risk factors for inpatient violence in psychiatric hospital: prospective study and prediction model

Seena Fazel et al. Psychol Med. 2023 Jan.

Abstract

Background: Violence perpetrated by psychiatric inpatients is associated with modifiable factors. Current structured approaches to assess inpatient violence risk lack predictive validity and linkage to interventions.

Methods: Adult psychiatric inpatients on forensic and general wards in three psychiatric hospitals were recruited and followed up prospectively for 6 months. Information on modifiable (dynamic) risk factors were collected every 1-4 weeks, and baseline background factors. Data were transferred to a web-based monitoring system (FOxWeb) to calculate a total dynamic risk score. Outcomes were extracted from an incident-reporting system recording aggression and interpersonal violence. The association between total dynamic score and violent incidents was assessed by multilevel logistic regression and compared with dynamic score excluded.

Results: We recruited 89 patients and conducted 624 separate assessments (median 5/patient). Mean age was 39 (s.d. 12.5) years with 20% (n = 18) female. Common diagnoses were schizophrenia-spectrum disorders (70%, n = 62) and personality disorders (20%, n = 18). There were 93 violent incidents. Factors contributing to violence risk were a total dynamic score of ⩾1 (OR 3.39, 95% CI 1.25-9.20), 10-year increase in age (OR 0.67, 0.47-0.96), and female sex (OR 2.78, 1.04-7.40). Non-significant associations with schizophrenia-spectrum disorder were found (OR 0.50, 0.20-1.21). In a fixed-effect model using all covariates, AUC was 0.77 (0.72-0.82) and 0.75 (0.70-0.80) when the dynamic score was excluded.

Conclusions: In predicting violence risk in individuals with psychiatric disorders, modifiable factors added little incremental value beyond static ones in a psychiatric inpatient setting. Future work should make a clear distinction between risk factors that assist in prediction and those linked to needs.

Keywords: Inpatients; prediction; psychosis; risk assessment; violence.

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Figures

Fig. 1.
Fig. 1.
ROC curve of the main model predicting inpatient violence: predictions incorporating random effects. Note: AUC 0.87 (95% CI 0.84–0.91).
Fig. 2.
Fig. 2.
ROC curve of the main model predicting inpatient violence: predictions not incorporating random effects. Note: AUC 0.77 (95% CI 0.72–0.91).

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