Evidence map›Paper›PMID 32618577›Full record

ArticleJMIR mental health2020

Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder.

Henning Daus, Timon Bloecher, Ronny Egeler, Richard De Klerk, Wilhelm Stork, Matthias Backenstrass

Abstract read
In one paragraph

Article in JMIR mental health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Observational
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Henning DausInstitute of Clinical Psychology, Centre for Mental Health, Klinikum Stuttgart, Stuttgart, Germany.ORCID https://orcid.org/0000-0002-4411-4363
Timon BloecherEmbedded Systems and Sensors Engineering, Research Center for Information Technology, Karlsruhe, Germany.ORCID https://orcid.org/0000-0002-6155-7529
Ronny EgelerSikom Software GmbH, Heidelberg, Germany.ORCID https://orcid.org/0000-0002-8738-2325
Richard De KlerkITK Engineering GmbH, Ruelzheim, Germany.ORCID https://orcid.org/0000-0002-7362-6245
Wilhelm StorkInstitute for Information Processing Technologies, Karlsruhe Institute of Technology, Karlsruhe, Germany.ORCID https://orcid.org/0000-0003-0579-4615
Matthias BackenstrassInstitute of Clinical Psychology, Centre for Mental Health, Klinikum Stuttgart, Stuttgart, Germany.ORCID https://orcid.org/0000-0002-2361-8271

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Internet- and mobile-based approaches have become increasingly significant to psychological research in the field of bipolar disorders. While research suggests that emotional aspects of bipolar disorders are substantially related to the social and global functioning or the suicidality of patients, these aspects have so far not sufficiently been considered within the context of mobile-based disease management approaches. As a multiprofessional research team, we have developed a new and emotion-sensitive assistance system, which we have adapted to the needs of patients with bipolar disorder. Next to the analysis of self-assessments, third-party assessments, and sensor data, the new assistance system analyzes audio and video data of these patients regarding their emotional content or the presence of emotional cues. In this viewpoint, we describe the theoretical and technological basis of our emotion-sensitive approach and do not present empirical data or a proof of concept. To our knowledge, the new assistance system incorporates the first mobile-based approach to analyze emotional expressions of patients with bipolar disorder. As a next step, the validity and feasibility of our emotion-sensitive approach must be evaluated. In the future, it might benefit diagnostic, prognostic, or even therapeutic purposes and complement existing systems with the help of new and intuitive interaction models.

Indexed as

assistance systembipolar disorderemotion recognitionmHealthmobile appsmonitoringmood recognition

Identifiers

PMID32618577
PMCPMC7367525

What OpenQuestion holds

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Registered trials

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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.