Evidence map›Paper›PMID 37349832›Full record

ArticleBMC psychology2023

Development of a digital biomarker and intervention for subclinical depression: study protocol for a longitudinal waitlist control study.

Gisbert W Teepe, Yanick X Lukic, Birgit Kleim, Nicholas C Jacobson, Fabian Schneider, Prabhakaran Santhanam, Elgar Fleisch, Tobias Kowatsch

Open access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in BMC psychology, 2023. 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
0.8field-weighted citation impact, top 26% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
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

8 authors at 4 institutions in 2 countries.

Gisbert W TeepeCentre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006, Zürich, Switzerland. gteepe@ethz.ch.ORCID http://orcid.org/0000-0002-2264-9797
Yanick X LukicCentre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006, Zürich, Switzerland.
Birgit KleimDepartment of Psychology, Experimental Psychopathology and Psychotherapy, Binzmühlestrasse 14, Box 8, 8050, Zürich, Switzerland.
Nicholas C JacobsonDepartments of Biomedical Data Science and Psychiatry, Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, 46 Centerra Parkway, Lebanon, NH, 03766, USA.
Fabian SchneiderCentre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006, Zürich, Switzerland.
Prabhakaran SanthanamCentre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006, Zürich, Switzerland.
Elgar FleischCentre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006, Zürich, Switzerland.
Tobias KowatschCentre for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich, Weinbergstrasse 56/56, 8006, Zürich, Switzerland.
ETH Zurich · CHUniversity of St.Gallen · CHDartmouth College · USUniversity of Zurich · CH

Funding

Treatment Development & Evaluation CoreP30DA029926 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2011 to 2026
$21.5M
NIDA NIH HHS P30 DA029926
6 · The paper itself

Abstract

backgroundDepression remains a global health problem, with its prevalence rising worldwide. Digital biomarkers are increasingly investigated to initiate and tailor scalable interventions targeting depression. Due to the steady influx of new cases, focusing on treatment alone will not suffice; academics and practitioners need to focus on the prevention of depression (i.e., addressing subclinical depression).

aimWith our study, we aim to (i) develop digital biomarkers for subclinical symptoms of depression, (ii) develop digital biomarkers for severity of subclinical depression, and (iii) investigate the efficacy of a digital intervention in reducing symptoms and severity of subclinical depression.

methodParticipants will interact with the digital intervention BEDDA consisting of a scripted conversational agent, the slow-paced breathing training Breeze, and actionable advice for different symptoms. The intervention comprises 30 daily interactions to be completed in less than 45 days. We will collect self-reports regarding mood, agitation, anhedonia (proximal outcomes; first objective), self-reports regarding depression severity (primary distal outcome; second and third objective), anxiety severity (secondary distal outcome; second and third objective), stress (secondary distal outcome; second and third objective), voice, and breathing. A subsample of 25% of the participants will use smartwatches to record physiological data (e.g., heart-rate, heart-rate variability), which will be used in the analyses for all three objectives. DISCUSSION: Digital voice- and breathing-based biomarkers may improve diagnosis, prevention, and care by enabling an unobtrusive and either complementary or alternative assessment to self-reports. Furthermore, our results may advance our understanding of underlying psychophysiological changes in subclinical depression. Our study also provides further evidence regarding the efficacy of standalone digital health interventions to prevent depression. Trial registration Ethics approval was provided by the Ethics Commission of ETH Zurich (EK-2022-N-31) and the study was registered in the ISRCTN registry (Reference number: ISRCTN38841716, Submission date: 20/08/2022).

Indexed as

AnxietyDepressionHumansLongitudinal StudiesSelf ReportAnxietyBreathing trainingConversational agentDepressionDigital biomarkerDigital healthStress

Identifiers

PMID37349832
PMCPMC10288725
OpenAlexW4381683686

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.