Smartphone-Measured Sleep Health Risk Factors Detect Suicidal Thoughts and Behaviors Among Adolescents.

OBJECTIVE

Suicide deaths and poor sleep health in adolescents have significantly increased. Smartphone sensors (eg, accelerometry) provide an unobtrusive and scalable way to monitor sleep health over extended time periods. We hypothesized that poor weekly sleep health (ie, shorter and variable time in bed; late and variable bedtime) assessed through smartphone sensors would associate with weekly suicidal thoughts and behaviors (STB).

METHOD: High-risk adolescents (N = 145, 13-18 years of age, 112 female) oversampled for STB (n = 114) installed the Effortless Assessment Research System application on their smartphones, allowing access to motion data over 6 months. Simultaneously, the app measured weekly suicidal ideation. Clinical interviews measured suicidal events (ie, attempts, specifc psychiatric hospitalizations, and emergency department events related to suicide risk) at 1-, 3-, and 6-month follow-up assessments. Mixed-effects logistic regression models tested whether the weekly average and variability of time in bed and bedtime related to next-week STB.

RESULTS

A 1-SD in weekly time in bed, relative to one's typical weekly time in bed, related to a near 2-fold greater odds of a next-week suicidal event (odds ratio [OR] = 1.85, 95% CI = 1.01, 3.28, p = .045). This was driven by time in bed on weekdays (OR = 2.39, 95% CI = 1.19, 4.44, p = .013). Greater variability of bedtimes (ie, lower bedtime consistency) within a weekend, relative to one's own typical weekend bedtime variability, predicted next-week suicidal ideation (OR = 1.91, 95% CI = 1.28, 2.69, p = .001).

CONCLUSION

Results reveal proximal associations between smartphone-derived sleep measures and STB, highlighting the possibility of developing just-in-time interventions, focusing on which sleep behaviors to modify and when to intervene to reduce suicide risk.