Assessment and Treatment Units (ATUs) require accurate, consistent and longitudinal monitoring of behavioural states to inform formulation, evaluate treatment effects and support safe discharge planning. However, existing ward documentation often relies on variable qualitative descriptions and commonly used incident-based tools fail to capture the temporal context or patterns of escalation occurring outside recorded events. This paper aims to develop an assessment tool that can generate data-drive insights regarding behavioural states.
This study reports on the development and piloting of a Positive Behaviour Support (PBS) informed Behavioural State Monitoring Form (BSMF) designed to provide hourly, longitudinal data on observable behavioural states, sleep and community access within an ATU setting. The BSMF was developed using PBS and Time Intensity Model principles, operationalising behavioural states into clearly defined, observable categories. Hourly ratings were collected prospectively at a single ATU between November 2023 and March 2026 and one semi-structured interview with ward staff was thematically analysed to explore usability and clinical utility. Quantitative data were analysed descriptively to identify temporal patterns and two illustrative case studies were examined in depth.
The BSMF generated high-frequency behavioural data with an 84.7% completion rate. Case studies demonstrated clinically meaningful patterns, including associations between sleep and behavioural stability, identification of “vulnerability windows,” and improved alignment of medication review with observed presentation. Staff reported that the BSMF enhanced pattern recognition, reduced ambiguity in documentation and supported more accurate PBS informed formulation, while also noting challenges related to workload, interpretation variability and rapid behavioural state fluctuation.
Overall, the BSMF offers a feasible, rights based and clinically meaningful method for capturing longitudinal behavioural state patterns in ATUs.
Early findings suggest that the tool supports more consistent formulation, enhances multidisciplinary decision-making and strengthens proactive and preventative care. Further, work is needed to formally validate the tool, refine implementation processes and evaluate its impact on clinical outcomes and staff practice.
