Toi Même, a Mobile Health Platform for Measuring Bipolar Illness Activity: Protocol for a Feasibility Study.

affective response big data, machine learning bipolar disorder cognitive speed digital phenotyping, smartphone app ecological momentary assessment mHealth mood instability

Journal

JMIR research protocols
ISSN: 1929-0748
Titre abrégé: JMIR Res Protoc
Pays: Canada
ID NLM: 101599504

Informations de publication

Date de publication:
18 Aug 2020
Historique:
received: 20 03 2020
accepted: 25 06 2020
revised: 24 06 2020
pubmed: 9 7 2020
medline: 9 7 2020
entrez: 9 7 2020
Statut: epublish

Résumé

The diagnosis and management of bipolar disorder are limited by the absence of available biomarkers. Patients with bipolar disorder frequently present with mood instability even during remission, which is likely associated with the risk of relapse, impaired functioning, and suicidal behavior, indicating that the illness is active. This research protocol aimed to investigate the correlations between clinically rated mood symptoms and mood/behavioral data automatically collected using the Toi Même app in patients with bipolar disorder presenting with different mood episodes. This study also aimed to assess the feasibility of this app for self-monitoring subjective and objective mood/behavior parameters in those patients. This open-label, nonrandomized trial will enroll 93 (31 depressive, 31 euthymic, and 31 hypomanic) adults diagnosed with bipolar disorder type I/II (Diagnostic and Statistical Manual of Mental Disorders, 5th edition criteria) and owning an iPhone. Clinical evaluations will be performed by psychiatrists at the baseline and after 2 weeks, 1 month, 2 months, and 3 months during the follow-up. Rather than only accessing the daily mood symptoms, the Toi Même app also integrates ecological momentary assessments through 2 gamified tests to assess cognition speed (QUiCKBRAIN) and affective responses (PLAYiMOTIONS) in real-life contexts, continuously measures daily motor activities (eg, number of steps, distance) using the smartphone's motion sensors, and performs a comprehensive weekly assessment. Recruitment began in April 2018 and the completion of the study is estimated to be in December 2021. As of April 2019, 25 participants were enrolled in the study. The first results are expected to be submitted for publication in 2020. This project has been funded by the Perception and Memory Unit of the Pasteur Institute (Paris) and it has received the final ethical/research approvals in April 2018 (ID-RCB: 2017-A02450-53). Our results will add to the evidence of exploring other alternatives toward a more integrated approach in the management of bipolar disorder, including digital phenotyping, to develop an ethical and clinically meaningful framework for investigating, diagnosing, and treating individuals at risk of developing bipolar disorder or currently experiencing bipolar disorder. Further prospective studies on the validity of automatically generated smartphone data are needed for better understanding the longitudinal pattern of mood instability in bipolar disorder as well as to establish the reliability, efficacy, and cost-effectiveness of such an app intervention for patients with bipolar disorder. ClinicalTrials.gov NCT03508427; https://clinicaltrials.gov/ct2/show/NCT03508427. DERR1-10.2196/18818.

Sections du résumé

BACKGROUND BACKGROUND
The diagnosis and management of bipolar disorder are limited by the absence of available biomarkers. Patients with bipolar disorder frequently present with mood instability even during remission, which is likely associated with the risk of relapse, impaired functioning, and suicidal behavior, indicating that the illness is active.
OBJECTIVE OBJECTIVE
This research protocol aimed to investigate the correlations between clinically rated mood symptoms and mood/behavioral data automatically collected using the Toi Même app in patients with bipolar disorder presenting with different mood episodes. This study also aimed to assess the feasibility of this app for self-monitoring subjective and objective mood/behavior parameters in those patients.
METHODS METHODS
This open-label, nonrandomized trial will enroll 93 (31 depressive, 31 euthymic, and 31 hypomanic) adults diagnosed with bipolar disorder type I/II (Diagnostic and Statistical Manual of Mental Disorders, 5th edition criteria) and owning an iPhone. Clinical evaluations will be performed by psychiatrists at the baseline and after 2 weeks, 1 month, 2 months, and 3 months during the follow-up. Rather than only accessing the daily mood symptoms, the Toi Même app also integrates ecological momentary assessments through 2 gamified tests to assess cognition speed (QUiCKBRAIN) and affective responses (PLAYiMOTIONS) in real-life contexts, continuously measures daily motor activities (eg, number of steps, distance) using the smartphone's motion sensors, and performs a comprehensive weekly assessment.
RESULTS RESULTS
Recruitment began in April 2018 and the completion of the study is estimated to be in December 2021. As of April 2019, 25 participants were enrolled in the study. The first results are expected to be submitted for publication in 2020. This project has been funded by the Perception and Memory Unit of the Pasteur Institute (Paris) and it has received the final ethical/research approvals in April 2018 (ID-RCB: 2017-A02450-53).
CONCLUSIONS CONCLUSIONS
Our results will add to the evidence of exploring other alternatives toward a more integrated approach in the management of bipolar disorder, including digital phenotyping, to develop an ethical and clinically meaningful framework for investigating, diagnosing, and treating individuals at risk of developing bipolar disorder or currently experiencing bipolar disorder. Further prospective studies on the validity of automatically generated smartphone data are needed for better understanding the longitudinal pattern of mood instability in bipolar disorder as well as to establish the reliability, efficacy, and cost-effectiveness of such an app intervention for patients with bipolar disorder.
TRIAL REGISTRATION BACKGROUND
ClinicalTrials.gov NCT03508427; https://clinicaltrials.gov/ct2/show/NCT03508427.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) UNASSIGNED
DERR1-10.2196/18818.

Identifiants

pubmed: 32638703
pii: v9i8e18818
doi: 10.2196/18818
pmc: PMC7463390
doi:

Banques de données

ClinicalTrials.gov
['NCT03508427']

Types de publication

Journal Article

Langues

eng

Pagination

e18818

Informations de copyright

©Aroldo A Dargél, Elise Mosconi, Marc Masson, Marion Plaze, Fabien Taieb, Cassandra Von Platen, Tan Phuc Buivan, Guillaume Pouleriguen, Marie Sanchez, Stéphane Fournier, Pierre-Marie Lledo, Chantal Henry. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 18.08.2020.

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Auteurs

Aroldo A Dargél (AA)

Perception and Memory Unit, Neuroscience Department, Pasteur Institute, Paris, France.
Unité Mixte de Recherche 3571, Centre National de la Recherche Scientifique (CNRS), Paris, France.
Centre Thérapeutique de Jour (CTPJ) Troubles Bipolaires, Clinique Bellevue, Meudon, France.

Elise Mosconi (E)

Centre Thérapeutique de Jour (CTPJ) Troubles Bipolaires, Clinique Bellevue, Meudon, France.

Marc Masson (M)

Clinique du Château de Garches, Garches, France.

Marion Plaze (M)

Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neuroscience, Paris, France.

Fabien Taieb (F)

Centre of Translational Research, Institut Pasteur, Paris, France.

Cassandra Von Platen (C)

Centre of Translational Research, Institut Pasteur, Paris, France.

Tan Phuc Buivan (TP)

Centre of Translational Research, Institut Pasteur, Paris, France.

Guillaume Pouleriguen (G)

Department of Information Systems, Institut Pasteur, Paris, France.

Marie Sanchez (M)

Department of Information Systems, Institut Pasteur, Paris, France.

Stéphane Fournier (S)

Department of Information Systems, Institut Pasteur, Paris, France.

Pierre-Marie Lledo (PM)

Perception and Memory Unit, Neuroscience Department, Pasteur Institute, Paris, France.
Unité Mixte de Recherche 3571, Centre National de la Recherche Scientifique (CNRS), Paris, France.

Chantal Henry (C)

Perception and Memory Unit, Neuroscience Department, Pasteur Institute, Paris, France.
Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neuroscience, Paris, France.

Classifications MeSH