Evidence map›Paper›PMID 36689265›Full record

ReviewJMIR mental health2023

Digital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review.

Eric Ettore, Philipp Müller, Jonas Hinze, Matthias Riemenschneider, Michel Benoit, Bruno Giordana, Rene Hurlemann, Danilo Postin, Amandine Lecomte, Michel Musiol and 3 more

Erratum issuedOpen access · goldAbstract readReview
In one paragraph

Review in JMIR mental health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
5.9field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  20. Asynchronous Technologies in Mental Health Care and Education.Current treatment options in psychiatry · 2023
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 7 institutions in 2 countries.

Eric EttoreDepartment of Psychiatry and Memory Clinic, University Hospital of Nice, Nice, France.ORCID 0000-0002-9686-5951
Philipp MüllerResearch Department Cognitive Assistants, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Saarbrücken, Germany.ORCID 0000-0001-7037-7100
Jonas HinzeDepartment of Psychiatry and Psychotherapy, Saarland University Medical Center, Hombourg, Germany.ORCID 0000-0001-8124-7213
Matthias RiemenschneiderDepartment of Psychiatry and Psychotherapy, Saarland University Medical Center, Hombourg, Germany.ORCID 0000-0001-7658-1022
Michel BenoitDepartment of Psychiatry, Hopital Pasteur, University Hospital of Nice, Nice, France.ORCID 0000-0001-6568-6689
Bruno GiordanaDepartment of Psychiatry, Hopital Pasteur, University Hospital of Nice, Nice, France.ORCID 0000-0001-7293-6607
Rene HurlemannDepartment of Psychiatry, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Bad Zwischenahn, Germany.ORCID 0000-0003-2628-565X
Danilo PostinDepartment of Psychiatry, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Bad Zwischenahn, Germany.ORCID 0000-0001-9580-9117
Amandine LecomteResearch Department Sémagramme Team, Institut national de recherche en informatique et en automatique, Nancy, France.ORCID 0000-0002-4289-4271
Michel MusiolResearch Department Sémagramme Team, Institut national de recherche en informatique et en automatique, Nancy, France.ORCID 0000-0001-7659-777X
Hali LindsayResearch Department Cognitive Assistants, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Saarbrücken, Germany.ORCID 0000-0002-0646-3749
Philippe RobertResearch Department, Cognition-Behaviour-Technology Lab, University Côte d'Azur, Nice, France.ORCID 0000-0002-0963-1728
Alexandra KönigResearch Department Stars Team, Institut national de recherche en informatique et en automatique, Sophia Antipolis - Valbonne, France.ORCID 0000-0001-9960-9657
Institut national de recherche en sciences et technologies du numérique · FRCarl von Ossietzky Universität Oldenburg · DEDeutsches Forschungsnetz · DEHôpital Pasteur · FRSaarland University · DECentre Hospitalier Universitaire de Nice · FRCognition Behaviour Technology · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMajor depressive episode (MDE) is a common clinical syndrome. It can be found in different pathologies such as major depressive disorder (MDD), bipolar disorder (BD), posttraumatic stress disorder (PTSD), or even occur in the context of psychological trauma. However, only 1 syndrome is described in international classifications (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [DSM-5]/International Classification of Diseases 11th Revision [ICD-11]), which do not take into account the underlying pathology at the origin of the MDE. Clinical interviews are currently the best source of information to obtain the etiological diagnosis of MDE. Nevertheless, it does not allow an early diagnosis and there are no objective measures of extracted clinical information. To remedy this, the use of digital tools and their correlation with clinical symptomatology could be useful.

objectiveWe aimed to review the current application of digital tools for MDE diagnosis while highlighting shortcomings for further research. In addition, our work was focused on digital devices easy to use during clinical interview and mental health issues where depression is common.

methodsWe conducted a narrative review of the use of digital tools during clinical interviews for MDE by searching papers published in PubMed/MEDLINE, Web of Science, and Google Scholar databases since February 2010. The search was conducted from June to September 2021. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) automated voice analysis, behavior analysis by (2) video and physiological measures, (3) heart rate variability (HRV), and (4) electrodermal activity (EDA). For this purpose, we were interested in 4 frequently found clinical conditions in which MDE can occur: (1) MDD, (2) BD, (3) PTSD, and (4) psychological trauma.

resultsA total of 74 relevant papers on the subject were qualitatively analyzed and the information was synthesized. Thus, a digital phenotype of MDE seems to emerge consisting of modifications in speech features (namely, temporal, prosodic, spectral, source, and formants) and in speech content, modifications in nonverbal behavior (head, hand, body and eyes movement, facial expressivity, and gaze), and a decrease in physiological measurements (HRV and EDA). We not only found similarities but also differences when MDE occurs in MDD, BD, PTSD, or psychological trauma. However, comparative studies were rare in BD or PTSD conditions, which does not allow us to identify clear and distinct digital phenotypes.

conclusionsOur search identified markers from several modalities that hold promise for helping with a more objective diagnosis of MDE. To validate their potential, further longitudinal and prospective studies are needed.

Indexed as

bipolar disorderclinical interviewdepressiondiagnosisdifferential diagnosisdigitaldigital healthdigital phenotypinginformationinterviewmental disordermental healthnonverbal behaviorphysiological measuresposttraumatic stress disorderpsychotraumaspeech analysis

Identifiers

PMID36689265
PMCPMC9903183
OpenAlexW4312803688

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.