Cited by 195Digital Mental Health InterventionsMental Health Research TopicsEmotion and Mood Recognition

The DOI matches its Crossref record; 99 of the 99 references it cites were found in a registry or an index; none of the 137 sources its claims cite is checked for support yet.

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

Open access
Colombo, Desirée, Fernández-Álvarez, Javier, Patané, Andrea, Semonella, Michelle, Kwiatkowska, Marta, García-Palacios, Azucena, Cipresso, Pietro, Riva, Giuseppe, Botella, Cristina·2019·Journal of Clinical Medicine

Abstract

Ecological momentary assessment (EMA) and ecological momentary intervention (EMI) are alternative approaches to retrospective self-reports and face-to-face treatments, and they make it possible to repeatedly assess patients in naturalistic settings and extend psychological support into real life. The increase in smartphone applications and the availability of low-cost wearable biosensors have further improved the potential of EMA and EMI, which, however, have not yet been applied in clinical practice. Here, we conducted a systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, to explore the state of the art of technology-based EMA and EMI for major depressive disorder (MDD). A total of 33 articles were included (EMA = 26; EMI = 7). First, we provide a detailed analysis of the included studies from technical (sampling methods, duration, prompts), clinical (fields of application, adherence rates, dropouts, intervention effectiveness), and technological (adopted devices) perspectives. Then, we identify the advantages of using information and communications technologies (ICTs) to extend the potential of these approaches to the understanding, assessment, and intervention in depression. Furthermore, we point out the relevant issues that still need to be addressed within this field, and we discuss how EMA and EMI could benefit from the use of sensors and biosensors, along with recent advances in machine learning for affective modelling.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This systematic review maps technology-based ecological momentary assessment (EMA) and ecological momentary intervention (EMI) for major depressive disorder (MDD), covering technical, clinical, and technological dimensions. It finds growing feasibility and preliminary efficacy, but limited clinical implementation, compliance challenges, and few EMI trials.

Key findings

  • The review included 33 articles (EMA = 26; EMI = 7) per the abstract, though the Results section reports 32 EMA studies and 8 EMI studies.
  • EMA compliance was generally encouraging: 16 studies reported >85% compliance, 5 reported 70–84%, and 4 reported 65%.
  • Four EMIs were identified: Psymate, Mobylize, Help4Mood, and Medlink. Psymate was tested in 102 depressed patients in a three-arm RCT; Mobylize in 7 MDD patients; Help4Mood in 28 depressed patients randomized to Help4Mood or TAU; Medlink in 8 MDD patients.
  • Psymate reduced depressive symptoms in the experimental group with maintenance at follow-up; Mobylize reduced depressive and anxiety symptoms but had low mood-prediction accuracy; Help4Mood showed reduced symptoms in both groups but greater clinical improvement in TAU; Medlink showed 84% medication adherence and significant depressive symptom decrease over 4 weeks.

Methods

  • Systematic review following PRISMA guidelines, searching PubMed and Web of Science in March 2019 with a broad EMA/EMI/mHealth/depression string.
  • Search produced 4,993 articles; after duplicate removal and title/abstract screening, 401 were retrieved, 40 papers selected, and 33 articles included.
  • Inclusion required adults with primary current or past MDD using DSM/ICD criteria and hand-held technology-based EMA or EMI; paper-and-pencil diaries were excluded. EMA studies had no risk-of-bias assessment; EMI studies used the Downs and Black quality index.

Limitations

  • The paper states that EMA/EMI are time-consuming, may be perceived as invasive, require repeated assessments over weeks, raise privacy concerns, and reduce experimental control because data are collected in naturalistic settings.
  • The paper states there are no standard validated EMA item sets, compliance and dropout remain problematic, few EMIs exist, only two were tested in RCTs, and more high-quality trials are needed.
  • Evident from the text: the abstract and Results report inconsistent included-study counts (33 vs. 32 EMA/8 EMI), and the search was limited to English-language publications in two databases as of March 2019.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.3390/jcm8040465

Cites

99 of 99 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 137 cited sources checked · 0 supported · 0 flagged

Show all 106 claims

  • It may state two separate claims as one. 70
  • Probably not a substantial claim. 45
  • The quote only partly states this claim. 2
104 of 104
  • The paper relies on this without support.

    Technology-based EMA and EMI have not yet been applied in clinical practice.

    “The increase in smartphone applications and the availability of low-cost wearable biosensors have further improved the potential of EMA and EMI, which, however, have not yet been applied in clinical practice.”
  • The paper relies on this without support.

    The findings from the included EMA and EMI studies are valid and comparable enough to support the review's conclusions about EMA and EMI for MDD.

    “As pointed out in this review, the widespread adoption of EMA for the investigation of depression has led to novel insights into different aspects of the disease, including emotion reactivity, cortisol patterns, or daily rumination.”
  • The paper relies on this without support.

    Electrodermal activity and heart rate variability are valid correlates of users' affective state.

    “electrodermal activity (EDA) and heart rate variability (HRV) have been extensively investigated as correlates of users’ affective state, and they are considered non-invasive”
3 of 3

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • EMA study count changes

    Major

    The abstract reports 26 EMA articles, but the results report 32 EMA studies after applying the inclusion criteria.

  • Medlink participant count changes

    Minor

    The efficacy study is described as involving eight MDD patients, but the compliance section counts nine users.

  • EMI study count changes

    Minor

    The abstract reports seven EMI articles, but the results report eight EMI studies.

3 of 3

Citations

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Metadata

Authors
Colombo, D., Fernández-Álvarez, J., Patané, A., Semonella, M., Kwiatkowska, M., García-Palacios, A., Cipresso, P., Riva, G., & Botella, C.
Affiliations
  • Universitat Jaume I (ES)
  • Department of Psychology, Università Cattolica del Sacro Cuore, Largo Gemelli, 1, 20100 Milan, Italy
  • Department of Computer Science, University of Oxford, Wolfson Building, Parks Rd, Oxford OX1 3QD, UK
  • IRCCS Istituto Auxologico Italiano (IT)
  • University of Oxford (GB)
  • Department of Basic Psychology, Clinic and Psychobiology, Universitat Jaume I, Av. Sos Baynat, s/n, 12071 Castellón, Spain
  • Università Cattolica del Sacro Cuore (IT)
Corresponding author
Colombo, Desirée
Venue
Journal of Clinical Medicine
Publisher
MDPI AG
Published
2019-04-05
Volume
8
Issue
4
Pages
465
ISSN
2077-0383 (ISSN-L)
OpenAlex
W2905222826
Cited by
194
References
99
Citations by year
2026: 19 · 2025: 28 · 2024: 42 · 2023: 22 · 2022: 33 · 2021: 23 · 2020: 26 · 2019: 1
FWCI
2.94
Type
journal article
Language
en
Open access
Locations
  • Journal of Clinical Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, other-oa)
  • Repositori UJI (Universitat Jaume I) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • PubliCatt (Università Cattolica del Sacro Cuore) (submittedVersion, other-oa)
Funders
H2020 Marie Skłodowska-Curie Actions (722022)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Keywords
ecological momentary assessment, ecological momentary intervention, major depressive disorder, mobile application, wearable biosensors, information and communication technologies, machine learning, naturalistic assessment, medication adherence, digital mental health

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