Treating Depression on a Day-to-day Basis: Development of a Tool for Physicians Based on a Smartphone Application

Overview

Testing and validating an e-health (smartphone application) approach to better understand the determinants of day-to-day symptomatology in depression, medication adherence, and treatment efficacy in the goal of maximizing patient care.

In industrialized countries, depression is the leading cause of disability with a cumulative DALY (disability adjusted life years) that his greater than all the other psychiatric or medical conditions (WHO, 2004). Although the medical treatment is efficient for a large number of patients, two major pitfalls can be highlighted: i). the difficulty to identify and alter risk factors related to therapeutic observance; and ii). the heterogeneous presentation of depression, which may require specific interventions depending on the clinical presentation of the patient. Ecological Momentary Assessment (EMA; also referred to as the Experience Sampling Method) is a method used to gather and interpret real-time data collected in the contexts of daily life through mobile technologies (Stone 1994). It has been used extensively in the field of psychiatry and specifically in mood disorders and it has been shown to be both feasible for patients with depression (Husky 2010, Swendsen 2012) and effective in identifying determinants of mood fluctuations and medication observance (Myin Germeys 2003, Ebner-Primer 2009, Solhan 2009, Silk 2011, Wichers 2010, Rot 2012, Armey 2015, Wenze 2010, Armey 2015). The restitution of the data to patients also has an important added benefit in terms of prognosis, as patients are better integrated in their own care (Wichers 2011, Kramer 2014). Although EMA has been shown to offer promising advantages, it has also been limited by the technical solutions used to gather information on daily life experiences. Rather than using research-dedicated devices which represent the majority of existing tools, the development of an application-based solution could revolutionize the field by creating the first effective and widely-diffusable tool to help clinicians better manage depression with the collaboration of their patients. This application would be designed to help patients monitor their symptoms, while providing regular interventions to increase medication. This is a randomized study in two groups to test and validate an e-health (smartphone application) approach to better understand the determinants of day-to-day symptomatology in depression, medication adherence, and treatment efficacy in the goal of maximizing patient care. In this multicentric study, 200 patients with a DSM-V diagnosis of depression are recruited. Participants will be assessed by: * Hetero-evaluations: diagnostic (MINI), depressive symptomatology (HDRS), clinical impression (CGI). * Auto-evaluations: depressive symptomatology (BDI), medication adherence (MARS), Quality of Life (Q-LES-Q-SF), therapeutic alliance (4PAS). Two groups will be formed by randomization (100 per groups): * Groupe SMART: smartphone (experimental group). This group will performed all clinical evaluations and will download the study application on their smartphone to answer daily questionnaires about symptom severity, medication adherence, during 6 weeks. Participants will be given a smartphone, if the subject does not have one. Clinical visits with psychiatrist will be performed every two weeks, with questionnaires to fill. * Groupe TAU: Treatment as Usual (control group). This group will performed all clinical evaluations and have the same follow-up as the intervention group, but without smartphone application. Expected results Patient benefit: The principle expected benefit for patients concerns their more active participation in their own health care, in the philosophy that the better they understand their disorder and the triggers of symptom expression, the better than can intervene to improve their mental health. Clinician benefit: It can provide high resolution data of depressive symptoms, therapeutic adherence and symptoms fluctuations on his patients, to better follow the remission or to adjust treatment daily dose.