M107. EXPLORING REAL-TIME VARIABILITY IN PSYCHOLOGICAL, PSYCHOPHYSIOLOGICAL, AND BEHAVIOURAL RISK FACTORS FOR AGGRESSION: A NOVEL APPROACH COMBINING ACTIVE AND PASSIVE REMOTE MONITORING. (18th May 2020) - Greer, Ben
Abstract: Background: Most service users diagnosed with a schizophrenia-spectrum disorder are not aggressive, but this behaviour does occur in inpatient mental health services worldwide. Aggression is difficult to predict and is influenced by a combination of changeable psychological, psychophysiological, and behavioural factors. Current assessment methods are limited to observable behaviours, conducted relatively infrequently, and demonstrate poor predictive accuracy. Advances in active (experience sampling methodology) and passive (wearable psychophysiological sensors) remote monitoring enable monitoring of psychological, psychophysiological, and behavioural parameters in real-time. Monitoring real-time variability in these parameters could identify concerning changes earlier than is currently possible and enable support to be provided sooner. This study aimed to examine real-time variability psychological, psychophysiological, and behavioural factors among an inpatient sample, and relationship with behavioural incidents. Methods: Service users (N=40) with a diagnosis of schizophrenia-spectrum disorder and/or antisocial personality disorder were recruited from a medium-secure inpatient forensic mental health service in the UK. Participants completed a blended active and passive remote monitoring study for seven consecutive days. Participants rated 20 psychological and behavioural items at random periods seven times per day, while wearing a passive remote monitoring device which simultaneously collected measurements of electrodermal activity, heart rate variability, and physical activity. Behavioural incidents occurring during the study were recorded from staff-completed behaviour rating scales, and participants' electronic hospital records. Multi-level models were constructed to examine the role of psychophysiological, psychological, and behavioural factors in predicting behavioural incidents, controlling for covariates such as physical movement and medication. Results: The findings demonstrate the within- and between-participant variability in psychological, psychophysiological, and behavioural parameters occurring in real-time, with high ecological validity. Multi-level modelling enabled the predictive ability of these changes in relation to behavioural incidents to be examined, in addition to the timeframe over which this predictive relationship exists. Discussion: To our knowledge this is the first study to examine real-time change in psychological, psychophysiological, and behavioural parameters in relation to behavioural incidents. This blended active and passive remote monitoring approach can offer a temporally precise method of assessing change in these parameters, which participants regarded as acceptable. This novel method could assist in identifying concerning change in these parameters earlier and delivering timely support for service users experiencing difficulties, which could be explored in future research.