Evidence map›Paper›PMID 31344670›Full record

ArticleJMIR mental health2019

Unraveling the Black Box: Exploring Usage Patterns of a Blended Treatment for Depression in a Multicenter Study.

Lise L Kemmeren, Anneke van Schaik, Johannes H Smit, Jeroen Ruwaard, Artur Rocha, Mário Henriques, David Daniel Ebert, Ingrid Titzler, Jean-Baptiste Hazo, Maya Dorsey and 2 more

Open access · goldAbstract read
In one paragraph

Article in JMIR mental health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
2.8field-weighted citation impact, top 9% 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.

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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

12 authors at 6 institutions in 6 countries.

Lise L KemmerenDepartment of Research and Innovation, GGZ inGeest Specialized Mental Health Care, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-5386-3112
Anneke van SchaikDepartment of Research and Innovation, GGZ inGeest Specialized Mental Health Care, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-7169-9600
Johannes H SmitDepartment of Research and Innovation, GGZ inGeest Specialized Mental Health Care, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-2062-8378
Jeroen RuwaardDepartment of Research and Innovation, GGZ inGeest Specialized Mental Health Care, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-4510-997X
Artur RochaCentre for Information Systems and Computer Graphics, Institute for Systems Engineering and Computers, Technology and Science, Porto, Portugal.ORCID http://orcid.org/0000-0002-5637-1041
Mário HenriquesCentre for Information Systems and Computer Graphics, Institute for Systems Engineering and Computers, Technology and Science, Porto, Portugal.ORCID http://orcid.org/0000-0003-0058-7596
David Daniel EbertDepartment of Clinical Psychology and Psychotherapy, Friedrich-Alexander University of Erlangen-Nürnberg, Erlangen, Germany.ORCID http://orcid.org/0000-0001-6820-0146
Ingrid TitzlerDepartment of Clinical Psychology and Psychotherapy, Friedrich-Alexander University of Erlangen-Nürnberg, Erlangen, Germany.ORCID http://orcid.org/0000-0002-8963-2324
Jean-Baptiste HazoEceve, Unit 1123, Inserm, Université de Paris, Paris, France.ORCID http://orcid.org/0000-0002-1834-4413
Maya DorseyEceve, Unit 1123, Inserm, Université de Paris, Paris, France.ORCID http://orcid.org/0000-0002-9744-7575
Katarzyna ZukowskaFaculty of Psychology, SWPS University of Social Sciences and Humanities, Warsaw, Poland.ORCID http://orcid.org/0000-0002-7653-2033
Heleen RiperDepartment of Research and Innovation, GGZ inGeest Specialized Mental Health Care, Amsterdam, Netherlands.ORCID http://orcid.org/0000-0002-8144-8901
GGZ inGeest · NLFriedrich-Alexander-Universität Erlangen-Nürnberg · DEInserm · FRInstitute for Systems Engineering and Computers · PTUniversity of Southern Denmark · DKUniwersytet SWPS · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBlended treatments, combining digital components with face-to-face (FTF) therapy, are starting to find their way into mental health care. Knowledge on how blended treatments should be set up is, however, still limited. To further explore and optimize blended treatment protocols, it is important to obtain a full picture of what actually happens during treatments when applied in routine mental health care.

objectiveThe aims of this study were to gain insight into the usage of the different components of a blended cognitive behavioral therapy (bCBT) for depression and reflect on actual engagement as compared with intended application, compare bCBT usage between primary and specialized care, and explore different usage patterns.

methodsData used were collected from participants of the European Comparative Effectiveness Research on Internet-Based Depression Treatment project, a European multisite randomized controlled trial comparing bCBT with regular care for depression. Patients were recruited in primary and specialized routine mental health care settings between February 2015 and December 2017. Analyses were performed on the group of participants allocated to the bCBT condition who made use of the Moodbuster platform and for whom data from all blended components were available (n=200). Included patients were from Germany, Poland, the Netherlands, and France; 64.5% (129/200) were female and the average age was 42 years (range 18-74 years).

resultsOverall, there was a large variability in the usage of the blended treatment. A clear distinction between care settings was observed, with longer treatment duration and more FTF sessions in specialized care and a more active and intensive usage of the Web-based component by the patients in primary care. Of the patients who started the bCBT, 89.5% (179/200) also continued with this treatment format. Treatment preference, educational level, and the number of comorbid disorders were associated with bCBT engagement.

conclusionsBlended treatments can be applied to a group of patients being treated for depression in routine mental health care. Rather than striving for an optimal blend, a more personalized blended care approach seems to be the most suitable. The next step is to gain more insight into the clinical and cost-effectiveness of blended treatments and to further facilitate uptake in routine mental health care.

Indexed as

cognitive behavior therapycombined modality therapydepressioninternetlogfile analysisroutine mental healthcaretreatment compliance

Identifiers

PMID31344670
PMCPMC6686640
OpenAlexW2963013780

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.