Objective tools to assess suicide risk are needed to determine when someone is at imminent risk. This pilot laboratory investigation utilized a within-subjects design to identify patterns in text messaging (SMS) unique to high-risk periods preceding suicide attempts. Individuals reporting a history of suicide attempt (N=33) retrospectively identified past attempts and periods of lower risk (e.g., suicide ideation). Language analysis software scored 189,478 text messages to capture three psychological constructs: self-focus, sentiment, and social engagement. Mixed-effects models tested whether these constructs differed in general (means) and over time (slopes) two weeks before a suicide attempt, relative to lower-risk periods. Regarding mean differences, no language features uniquely differentiated suicide attempts from other episodes. However, when examining patterns over time, anger increased and positive emotion decreased to a greater extent as one approached a suicide attempt. Results suggest private electronic communication has the potential to provide real-time digital markers of suicide risk.
Keywords: Digital Data; Digital Phenotyping; Sentiment Analysis; Suicide; Text Mining.