SmartCriseS - Smartphone Survey of Suicidal Risk

Overview

Sleep and appetite disorders as well as social exclusion, have been linked to the emergence of suicidal ideation (SI) and suicide attempts.This study aims to evaluate the relationship between those factors and suicidal ideation and behaviour. To assess those factors an ecological momentary assessment (EMA) desing will be used. EMA will be carried out using 2 applications integrated into the smartphone of participants (Android or iOS), one to make an explicit data collection with questions and another one for the implicit collection of data from mobile sensors. 1044 suicide attempters will be included in three sites and followed for 6 months. Participants will be evaluated at inclusion and at the end of follow-up. The hypothesis is that sleep, appetite and social exclusion factors collected with the smartphone application will be linked to the intensity of death wish, suicidal ideations and suicidal attempts. An auxiliary study will also be led with 300 patients carrying an actimeter for the 30 first days after inclusion. This will help collecting more accurate data on various sleep parameters.

The proposed study will use ecological momentary assessment (EMA) via smartphone applications (apps) and wearable trackers to examine the relationship between suicidality (wish to die, suicidal ideation and suicide attempt) and changes in sleep quality and disturbed appetite. These behavioral markers, if the hypothesis is proven true, could help predict increased suicidal risk in real-time within a vulnerable population across different cultures. The study aims to: (1) Establish the extent to which quality of sleep is related to suicide ideation and suicide attempts; (2) Establish the extent to which change in appetite is related to suicide ideation and suicide attempts; (3) Determine the emotional impact of the app when suicidality is assessed; (4) Clarify the timeline of the relationship between sleep disturbances and suicidal behavior; (5) Develop personalized algorithms based on EMA protocol and motor activity markers or "signatures" to assess the risk of suicide attempts. The hypothesis is that variations in sleep quality will correlate with increased wish to die, suicide ideation and suicide attempts. It is expected that a decrease in sleep quality will be a suicide risk marker especially among young individuals. This prospective cross-national study will use the infrastructure of an existing network (WORECA). Woreca has defined a common protocol of suicide assessment, data sharing and analysis strategy. 1044 suicide attempters will be included and followed for 6 months. Each participant will be assessed using an EMA protocol via two smartphone apps: (1) One app will ask everyday questions following a dynamic protocol to assess quality of sleep, appetite, suicidal ideation and psychopathology; (2) the other app will record activity using smartphone sensors. Additionally, 300 participants (150 in France and 150 in Spain) will have their sleep phases and other physiological changes during sleep monitored with a wearable armband. Study outcomes include wish to live, wish to die, suicidal ideation, and suicide attempt during the follow-up period. A multi-level logit regression analysis will be used to account for multiple observations per individual, to identify individual-level (sleep, appetite, socio-demographic, clinical data, treatment data) and site-level characteristics associated with death desire, suicidal ideation or suicide attempt (aim 1 and 2). Hazards models will also be used to relate covariate characteristics (sleep, appetite, sociodemographic, clinical data, treatment data) with time to suicide reattempt during the follow-up period (aim 1 and 2). Data mining (machine learning) techniques will be used to examine risk factors, patterns of illness evolution (aim 3 and 4) and patient stratification by level of suicidal risk (aim 5). Identifying surrogate markers of suicidality related with physiological functions, which carry less or no stigma for the patients and are easier to report, or have a lower reporting threshold is an essential task. These markers would allow to predict in real-time an increase in suicidal risk within a vulnerable population and ultimately help to prevent and even personalize treatment.Suicidal behaviours, including suicidal ideation, are preventable but to be efficient, prevention needs to rely on the identication of specific risk factors.