Harvard Study Predicts 75% of Suicide Attempts a Week in Advance

Suicide, the second-leading cause of death for Americans aged 10 to 34, remains notoriously difficult to predict. However, recent research from Harvard University indicates that a significant majority of suicide attempts could be forecast within a much shorter timeframe, potentially allowing for earlier intervention.

The study, set to be published in the October issue of the Journal of Psychopathology and Clinical Science, found that 75% of suicide attempts and 87% of suicide-related events were predicted in the week before they occurred. This research built upon previous work that showed around 50% of individuals who died by suicide had seen a clinician in the month prior to their death, though much of that data relied on self-reporting.

Matthew Nock, a Harvard psychology professor and the study's lead author, pioneered a technique for surveying individuals in real time. His multiyear study involved over 600 high-risk adults and adolescents who had sought hospital treatment for suicidal thoughts or behaviors. Participants received smartphone-based surveys multiple times a day for the first three months and daily for the subsequent three months. These surveys asked about suicidal ideation, intent, resistance to urges, and emotional states such as hopelessness, isolation, anger, worry, energy levels, and positivity.

The findings highlighted the significant role of emotional states in predicting suicide risk. The study revealed that for every one-point increase on an agitation scale, an individual's odds of attempting suicide increased by 11%, making agitation a stronger predictor than depression. This aligns with earlier research by Nock, which found that 90% of suicide attempt survivors reported experiencing a temporary urge to alleviate psychological agitation and pain.

Beyond self-reported emotions, Nock's team also analyzed metadata related to survey engagement, such as the time taken to start and complete surveys. The study also incorporated a real-time alert system designed to trigger interventions if an individual showed intent to attempt suicide.

"We need to understand what puts people at risk, and the ebb and flow of suicidal thoughts — how to better measure them when they occur, and how to better predict increases in risk," Nock stated, emphasizing the goal of creating a scalable, reproducible, and accurate system for intervention.

This research is part of a broader initiative by Nock's lab to enhance real-time suicide risk monitoring, exploring methods such as wearable sensors to track physiological data like sleep patterns, heart rate, and voice signatures. Potential interventions stemming from this technology could include reminders of coping mechanisms learned in therapy or encouragement to connect with support networks.

Nock expressed optimism about the potential for delivering care directly into individuals' environments, while also acknowledging the critical need for robust privacy safeguards and collaboration with clinicians and patients.