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Abstract
There has been growing interest in using wearable physiological monitors to passively detect the signals of distress (i.e., increases in autonomic arousal measured through increased electrodermal activity [EDA]) that may be imminently associated with suicidal thoughts. Before using these monitors in advanced applications such as creating suicide risk detection algorithms or just-in-time interventions, several preliminary questions must be answered. Specifically, we lack information about whether: (1) EDA concurrently and prospectively predicts suicidal thinking and (2) data on EDA adds to the ability to predict the presence and severity of suicidal thinking over and above self-reports of emotional distress. Participants were suicidal psychiatric inpatients (n = 25, 56% female, M age = 33.48 years) who completed six daily assessments of negative affect and suicidal thinking duration of their psychiatric inpatient stay and 28 days post-discharge, and wore on their wrist a physiological monitor (Empatica Embrace) that passively detects autonomic activity. We found that physiological data alone both concurrently and prospectively predicted periods of suicidal thinking, but models with physiological data alone had the poorest fit. Adding physiological data to self-report models improved fit when the outcome variable was severity of suicidal thinking, but worsened model fit when the outcome was presence of suicidal thinking. When predicting severity of suicidal thinking, physiological data improved model fit more for models with non-overlapping self-report data (i.e., low arousal negative affect) than for overlapping self-report data (i.e., high arousal negative affect). These findings suggest that physiological data, under certain contexts (e.g., when combined with self-report data), may be useful in better predicting—and ultimately, preventing—acute increases in suicide risk. However, some cautious optimism is warranted since physiological data do not always improve our ability to predict suicidal thinking.
Highlights
In recent years, there has been increased interest in using wearable devices to study psychological constructs of interest in the real world, such as detecting signals of distress that may predict the onset of suicidal thoughts [1,2,3]
There is optimism about the possibility of using wearable monitors to identify periods of risk for suicidal thoughts among those who are at risk for suicide, there are important questions that must be answered about the predictive ability of autonomic arousal before developing interventions that rely on wearable passive sensing
Autonomic events marginally improved the fit of contemporaneous model with high arousal negative affect
Summary
There has been increased interest in using wearable devices (e.g., smartwatches) to study psychological constructs of interest in the real world, such as detecting signals of distress that may predict the onset of suicidal thoughts [1,2,3]. If a wearable monitor could passively detect this distressing state, it would provide opportunities for the deployment of just-in-time adaptive interventions [7]. Such interventions would be useful for groups of individuals at elevated risk for suicide [8], such as those who have recently discharged from inpatient psychiatric care for suicide risk (the focus of this study). The psychological experience of distress is reliably associated with sympathetic autonomic activity This activity can be indirectly detected by observing the small increases in perspiration that occur during an autonomic event [9, 10]. Because sweat is a good conductor of electricity, changes in skin conductance ( called electrodermal activity; EDA) [11]
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