Current state and future directions of technology-based ecological momentary assessments and interventions for major depressive disorder: protocol for a systematic review

Abstract

BackgroundEcological momentary assessments (EMAs) and ecological momentary interventions (EMIs) represent a novel approach for the assessment and delivery of psychological support to depressed patients in daily life. Beyond the classical paper-and-pencil daily diaries, the more recent progresses in Information and Communication Technologies (ICT) enabled researchers to bring all the needed processes together in only one device, i.e., response signaling, repeated symptom collection, information storage, secure data transfer, and psychological support delivery. Despite evidence showing the feasibility and acceptability of these techniques, EMAs are only beginning to be applied in real clinical practice, whether the development of EMIs for clinically depressed patients is still very limited. The objective of this systematic review is to provide the state of the art of technology-based EMAs and EMIs for major depressive disorder (MDD), with the aim of leading the way to possible future directions for the clinical practice.MethodsWe will conduct a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Data sources will include two bibliographic databases, PubMed and Web of Science (Web of Knowledge), supplemented by searches for unpublished or ongoing studies. Eligible studies will report data for adult (≥ 18 years old) with a primary (both current and past) diagnosis of MDD, defined by a valid criterion standard. We will consider studies adopting technology-based EMAs and EMIs for the investigation and/or assessment of depression and for the delivery of a psychological intervention. We will exclude studies adopting paper-and-pencil tools.DiscussionThe proposed systematic review will provide new insights on the advantages and benefits of adopting technology-based EMAs and EMIs for MDD in the traditional clinical practice, taking into consideration both clinical and technological issues. The potential of using sensors and biosensors along with machine learning for affective modeling will also be discussed.Electronic supplementary materialThe online version of this article (10.1186/s13643-018-0899-y) contains supplementary material, which is available to authorized users.

Addiction, Anhedonia, and Comorbid Mood Disorder. A Narrative Review

“…It was questioned how much pleasure the participants experienced during the day on three domains (social, recreation, and performance/accomplishment). EMA might be a promising methodology providing data better covering the actual evolution of symptoms than (retrospective) self-report and is increasingly used in both depression and addiction research (52, 53). However, as yet, no validated set of EMA-implementable questions on anhedonia have been developed.…”

Current State and Future Directions of Technology-Based Ecological Momentary Assessment and Intervention for Major Depressive Disorder: A Systematic Review

“…Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria [27] were followed. For the systematic review protocol, see [28].…”

Compliance and Retention With the Experience Sampling Method Over the Continuum of Severe Mental Disorders: Meta-Analysis and Recommendations

“…As such, ESM is of particular interest in clinical psychology where patients are affected by memory problems [3,4], unstable affective states [5,6], and by a heightened sensitivity to contextual factors [17‑19]. ESM has, therefore, been extensively used in this field of research over the past 30 years [7,8], particularly in populations with depressive disorders [7,9] and psychosis [8,10].…”