ArticleJournal of affective disorders2026
Predicting next-day suicidal urges, depression, and PTSD symptoms using ecological momentary assessments and passive sensing of sleep among military service members and veterans.
Article in Journal of affective disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundsSuicide risk fluctuates rapidly, highlighting the importance of identifying risk factors for acute suicidal urges. This study examined whether nightly sleep measured actively via self-report ecological momentary assessment (EMA) and passively via wearable sensors predicted next-day suicidal urges, depression, and PTSD symptoms among military service members and veterans.
methodsMilitary service members and veterans with current suicidal ideation or a suicide attempt in the past month (N = 86) completed seven EMA surveys per day and wore a wearable device (Fitbit) for 28 days. Using multilevel models, we examined sleep assessed by EMA-only, wearable-only, and EMA + wearable as predictors of next-day suicidal urges, depression, and PTSD symptoms, and compared the predictive utility of the three approaches.
resultsParticipants completed 7898 EMA observations (48.9% adherence) and wore a wearable device (Fitbit) for 79.43% of the study period. More severe nightmares and poorer sleep quality assessed by EMA predicted next next-day suicidal urges (maximum and average), suicidal beliefs, depression, and PTSD symptoms. Wearable-assessed sleep duration deviation significantly predicted next-day maximum suicidal urges. Wearable-assessed sleep regularity index predicted next-day depression. EMA-only models consistently outperformed wearable-only models in predicting next-day suicide risks and mental health outcomes, and combining EMA and wearable demonstrated best model fit.
conclusionOur findings suggest that self-reported sleep via EMA has strong utility in predicting near-term suicidal risk, depression, and PTSD, while wearable devices can provide low-burden, supplemental information. Integrating wearables and EMA may enhance the prediction and inform just-in-time suicide interventions.
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