Predicting suicidal ideation from irregular and incomplete time series of questionnaires in a smartphone-based suicide prevention platform: a pilot study
Résumé
With over 700,000 suicides annually and 20 times that number in suicide attempts, suicidal behavior remains a significant global health issue 1 , which resists efforts in prevention and treatment. Clinicians are still facing the current impossibility to predict the occurrence of suicidal thoughts and behavior in at risk patients 2 . Recently, smartphone-based solutions have emerged to monitor suicide risk 3,4 , with the aim to detect in real time the potential for suicidal gesture within a short period of time. These technologies are widely available and easily leveraged to collect real-time ecological momentary assessment (EMA) data, which refers to actively asking questions via smartphone. When an imminent risk is detected, the patient can be offered an immediate preventive intervention called Just-in-time adaptive interventions 5 . During the suicidal crisis, JITAIs would deliver an intervention such as a safety planning intervention, which has been largely proven to prevent suicidal behavior 6 .
By providing an accurate depiction of the patient's symptoms 7 , EMA enhances understanding of the temporal dynamics of suicide risk 8 . Indeed, in recent years, a growing number of studies provided relevant new findings about the nature and short-term predictors of suicidal thoughts and behavior using smartphone-based EMA 9 . Recent reviews of papers focusing on intensive longitudinal data and suicidal ideation (SI) revealed that suicidal OPEN.
Domaines
Sciences de l'Homme et SociétéOrigine | Fichiers éditeurs autorisés sur une archive ouverte |
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