From e-Health to i-Health: Prospective Reflexions on the Use of Intelligent Systems in Mental Health Care

Briffault, Xavier; Morgiève, Margot; Courtet, Philippe

doi:10.3390/brainsci8060098

Cited by 19 publications

(9 citation statements)

References 71 publications

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“…In addition, the potential harm of these interventions is not well understood (Ebert et al, 2017). New technological elements potentially applicable to online interventions to prevent depression are being developed: use of sensors through smartphones (Boonstra et al, 2018), virtual and augmented reality (Quero et al, 2019), machine learning and artificial intelligence (Briffault, Morgiève, & Courtet, 2018;Fulmer, Joerin, Gentile, Lakerink, & Rauws, 2018). Unfortunately, RCTs on their effectiveness in preventing depression are not yet available.…”

Section: Practical Implicationsmentioning

confidence: 99%

Effectiveness of online psychological and psychoeducational interventions to prevent depression: Systematic review and meta-analysis of randomized controlled trials

Rigabert

Motrico

Moreno-Peral

et al. 2020

Clinical Psychology Review

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Section: Practical Implicationsmentioning

confidence: 99%

Effectiveness of online psychological and psychoeducational interventions to prevent depression: Systematic review and meta-analysis of randomized controlled trials

Rigabert

Motrico

Moreno-Peral

et al. 2020

Clinical Psychology Review

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show abstract

“…We hope that this digital tool will lead to scientific and clinical advances, and will allow identifying high-risk periods, and predicting the imminent risk, which is extremely challenging at the moment [27]. These fine-grained digital assessments and predictive mHealth-based interventions are promising tools for suicide prevention [57], because they represent an unprecedented opportunity to act at multiple levels through targeted, scalable and contextualized micro-interventions [98]. They might allow proposing just-in-time adaptive interventions (JITAI), defined by Nahum-Shani [99] as the right support (e.g., type, intensity) at the right time [26].…”

Section: Resultsmentioning

confidence: 99%

A digital companion for ecological momentary assessment and prevention of suicide: A case series on the use of the emma app

Margot¹,

Genty²,

Dubois³

et al. 2020

Preprint

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Background: Many suicide risk factors have been identified, but traditional clinical methods do not allow the accurate prediction of suicide behaviors. To face this challenge, we developed emma, an app for Ecological Momentary Assessment/Intervention (EMA/EMI) and prediction of suicide risk in high risk patients.Objective: We wanted to test the feasibility of implementing this mHealth-based suicide risk assessment and prevention tool and its impact in subjects at high risk of suicide in real world conditions.Methods: The EMMA Study is an ongoing longitudinal interventional multicenter trial in which patients at high-risk for suicide (n=100) use emma for 6 months. During this period, they complete four EMA types (daily, weekly, monthly, spontaneous) and may use EMI modules. Participants undergo clinical assessment at month 0, 1, 3 and 6 after inclusion.Results: Among the 43 patients already recruited in the EMMA Study, 14 participants had completed the follow-up. Their data were analyzed to evaluate emma implementation and impact on suicide risk management. EMA completion rates were extremely heterogeneous among the 14 participants with a sharp decrease over time. The completion rates of the weekly EMA (25% to 87.5%) were higher than for the daily EMA (0% to 53.3%). Most patients (n=10/14) answered the EMA questionnaires spontaneously. Similarly, the Safety Plan Modules use was very heterogeneous (2 to 75 times). Specifically, 11 patients used the Call Module (1 to 29 times), designed by our team to help them to get in touch with healthcare professionals and/or relatives during a crisis. All patients used the Breathing Space Module and 8 the Emotion Regulation Module (1 to 46 times). The diversity of patient profiles and use of the EMA and EMI modules proposed by emma was highlighted by three case reports.Conclusions: These preliminary results suggest that it is possible and acceptable to collect longitudinal fine-grained contextualized data (EMA) and to offer personalized intervention (EMI) in real time to people at high risk of suicide. Patients have different clinical and digital profiles and needs that require a highly scalable, interactive and customizable app. To become a complementary tool for suicide prevention, emma should be integrated in the existing emergency procedures.

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“…Hopefully, this digital tool might lead to scientific and clinical advances and will allow for the identification of high-risk periods and prediction of imminent risk, which are extremely challenging at the moment [ 71 ]. These fine-grained digital assessments and predictive mHealth-based interventions are promising tools for suicide prevention [ 55 ], because they represent an unprecedented opportunity to act at multiple levels through targeted, scalable, and contextualized micro-interventions [ 72 ]. They might allow for the proposal of just-in-time adaptive interventions, defined by Nahum-Shani et al [ 73 ] as the right support (eg, type and intensity) at the right time [ 31 ].…”

Section: Discussionmentioning

confidence: 99%

A Digital Companion, the Emma App, for Ecological Momentary Assessment and Prevention of Suicide: Quantitative Case Series Study

Morgiève¹,

Genty²,

Azé³

et al. 2020

JMIR Mhealth Uhealth

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Background Many suicide risk factors have been identified, but traditional clinical methods do not allow for the accurate prediction of suicide behaviors. To face this challenge, emma, an app for ecological momentary assessment (EMA), ecological momentary intervention (EMI), and prediction of suicide risk in high-risk patients, was developed. Objective The aim of this case report study was to describe how subjects at high risk of suicide use the emma app in real-world conditions. Methods The Ecological Mental Momentary Assessment (EMMA) study is an ongoing, longitudinal, interventional, multicenter trial in which patients at high risk for suicide are recruited to test emma, an app designed to be used as a self-help tool for suicidal crisis management. Participants undergo clinical assessment at months 0, 1, 3, and 6 after inclusion, mainly to assess and characterize the presence of mental disorders and suicidal thoughts and behaviors. Patient recruitment is still ongoing. Some data from the first 14 participants who already completed the 6-month follow-up were selected for this case report study, which evaluated the following: (1) data collected by emma (ie, responses to EMAs), (2) metadata on emma use, (3) clinical data, and (4) qualitative assessment of the participants' experiences. Results EMA completion rates were extremely heterogeneous with a sharp decrease over time. The completion rates of the weekly EMAs (25%-87%) were higher than those of the daily EMAs (0%-53%). Most patients (10/14, 71%) answered the EMA questionnaires spontaneously. Similarly, the use of the Safety Plan Modules was very heterogeneous (2-75 times). Specifically, 11 patients out of 14 (79%) used the Call Module (1-29 times), which was designed by our team to help them get in touch with health care professionals and/or relatives during a crisis. The diversity of patient profiles and use of the EMA and EMI modules proposed by emma were highlighted by three case reports. Conclusions These preliminary results indicate that patients have different clinical and digital profiles and needs that require a highly scalable, interactive, and customizable app. They also suggest that it is possible and acceptable to collect longitudinal, fine-grained, contextualized data (ie, EMA) and to offer personalized intervention (ie, EMI) in real time to people at high risk of suicide. To become a complementary tool for suicide prevention, emma should be integrated into existing emergency procedures. Trial Registration ClinicalTrials.gov NCT03410381; https://clinicaltrials.gov/ct2/show/NCT03410381

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From e-Health to i-Health: Prospective Reflexions on the Use of Intelligent Systems in Mental Health Care

Cited by 19 publications

References 71 publications

Effectiveness of online psychological and psychoeducational interventions to prevent depression: Systematic review and meta-analysis of randomized controlled trials

Effectiveness of online psychological and psychoeducational interventions to prevent depression: Systematic review and meta-analysis of randomized controlled trials

A digital companion for ecological momentary assessment and prevention of suicide: A case series on the use of the emma app

A Digital Companion, the Emma App, for Ecological Momentary Assessment and Prevention of Suicide: Quantitative Case Series Study

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