Boruta algorithm coercion mental health services predictors psychiatric nursing random forests
Minimising formal coercion, such as seclusion, physical restraint, and forced medication, remains a global priority in acute mental health units. However, key drivers beyond individual-level features are poorly understood. This exploratory analysis was intended to identify the top functional, contextual, and interventional features linked to formal coercion in three Australian acute adult mental health inpatient units. Nested within a mixed concurrent control study, this feature analysis examined nurses' reports of 2955 de-escalation events over 324days, from March 2024 to April 2025, including nurses' commentaries on the behavioural functions that triggered de-escalations. Fifteen inductively coded functional features were analysed alongside 15 contextual and 16 interventional features. Studied target variables included seclusion and physical restraint events and their durations, as-needed intramuscular psychotropic events, physical injury events, and Code Black activations. Features were analysed using bivariate statistics and machine learning techniques, including the Boruta algorithm for feature selection and random forest regressions for predictive modelling. Top drivers for the use of formal coercion included behavioural ‘Responses to Challenging, Physical and External Stimuli,’ incidents of self-harm, incidents directed towards nurses, and the application of specific deescalation techniques. A hierarchy of behavioural functions is proposed as a by-product of this analysis. These findings provide
nuanced insights into the drivers of formal coercion and the underlying value arrangements, as well as elevate the merit of ecological, bottom-up approaches in early warning signs work.
Details
Title
Functional, Contextual, and Interventional Drivers of Formal Coercion in Acute Mental Health Units: A Feature Analysis
Creators
Esario IV Daguman - Southern Cross University
Marie Hutchinson - Southern Cross University
Jacqui Yoxall - Southern Cross University
Richard Lakeman - Southern Cross University
Publication Details
International Journal of Mental Health Nursing, Vol.35(1), pp.1-17
Publisher
Wiley; HOBOKEN
Grant note
This feature analysis is part of a larger research project funded by Southern Cross University and the Translational Research Grant Scheme from the NSW Office for Health and Medical Research.