The study goal is to determine the feasbility and interest of monitoring mental health and non mental health related simptoms in Outpatients in order to prevent suicide.
Taking into account the strengths and pitfalls of existing suicide risk assessment methods, we have designed a system capable to combine EMA and continuous monitoring of patients using the smartphone's and/or wearable's sensors and data entry in order to monitor and predict suicide risk. For example, both poor sleep quality and disturbed appetite are clinical markers of depression, with a bidirectional relationship. Their changes could precede the increase of suicidal behavior as sleep and appetite are both influenced by mood state and regulated by the serotonergic system. Our hypothesis is that tracking mental health simptoms regularly through self-report could serve as a consistent and non-biased shortcut to assess mood state, its biological underpinnings and could potentially predict suicidal behavior.
Study Type
OBSERVATIONAL
Enrollment
30
CHRU de Brest
Brest, France
Evaluate the feasibility of this intensive data capture technology in patients in real world without economical incentives.
acceptability assessed by the AES scale
Time frame: 2 month
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