Evidence map›Paper›PMID 35706482›Full record

ArticleEClinicalMedicine2022

The NEVERMIND e-health system in the treatment of depressive symptoms among patients with severe somatic conditions: A multicentre, pragmatic randomised controlled trial.

Vladimir Carli, Nuhamin Gebrewold Petros, Gergö Hadlaczky, Tereza Vitcheva, Paola Berchialla, Silvia Bianchi, Sara Carletto, Eirini Christinaki, Luca Citi, Sérgio Dinis and 15 more

Open access · goldAbstract read
In one paragraph

Article in EClinicalMedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
2.4field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
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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

25 authors at 9 institutions in 6 countries.

Vladimir CarliNational Centre for Suicide Research and Prevention of Mental Ill-Health, Karolinska Institutet, Stockholm, Sweden.
Nuhamin Gebrewold PetrosNational Centre for Suicide Research and Prevention of Mental Ill-Health, Karolinska Institutet, Stockholm, Sweden.
Gergö HadlaczkyNational Centre for Suicide Research and Prevention of Mental Ill-Health, Karolinska Institutet, Stockholm, Sweden.
Tereza VitchevaNational Centre for Suicide Research and Prevention of Mental Ill-Health, Karolinska Institutet, Stockholm, Sweden.
Paola BerchiallaDepartment of Clinical and Biological Sciences, Università degli Studi di Torino, Turin, Italy.
Silvia BianchiResearch Center "E.Piaggio" and Department of Information Engineering, School of Engineering, Università di Pisa, Pisa, Italy.
Sara CarlettoDepartment of Neuroscience "Rita Levi Montalcini", Università degli Studi di Torino, Turin, Italy.
Eirini ChristinakiSchool of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.
Luca CitiSchool of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.
Sérgio DinisFaculdade de Medicina and CCUL, Universidade de Lisboa, Lisbon, Portugal.
Claudio GentiliGeneral Psychology Department, Università degli Studi di Padova, Padua, Italy.
Vera GeraldesFaculdade de Medicina and CCUL, Universidade de Lisboa, Lisbon, Portugal.
Lorena GiovinazzoDepartment of Clinical and Biological Sciences, Università degli Studi di Torino, Turin, Italy.
Sergio Gonzalez-MartinezLife Supporting Technologies, Universidad Politécnica de Madrid, Madrid, Spain.
Björn MeyerGAIA AG, Hamburg, Germany.
Luca OstacoliDepartment of Clinical and Biological Sciences, Università degli Studi di Torino, Turin, Italy.
Manuel OttavianoLife Supporting Technologies, Universidad Politécnica de Madrid, Madrid, Spain.
Silvia OuakininFaculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.
Tasos PapastylianouSchool of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.
Rita ParadisoSmartex, Pisa, Italy.
Riccardo PoliSchool of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.
Isabel RochaFaculdade de Medicina and CCUL, Universidade de Lisboa, Lisbon, Portugal.
Carmen SettantaDepartment of Clinical and Biological Sciences, Università degli Studi di Torino, Turin, Italy.
Enzo Pasquale ScilingoResearch Center "E.Piaggio" and Department of Information Engineering, School of Engineering, Università di Pisa, Pisa, Italy.
Gaetano ValenzaResearch Center "E.Piaggio" and Department of Information Engineering, School of Engineering, Università di Pisa, Pisa, Italy.
University of Turin · ITKarolinska Institutet · SEUniversity of Essex · GBUniversity of Lisbon · PTUniversity of Pisa · ITUniversidad Politécnica de Madrid · ESGAIA (Germany) · DESmartex (Italy) · ITUniversity of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study assessed the effectiveness of the NEVERMIND e-health system, consisting of a smart shirt and a mobile application with lifestyle behavioural advice, mindfulness-based therapy, and cognitive behavioural therapy, in reducing depressive symptoms among patients diagnosed with severe somatic conditions. Our hypothesis was that the system would significantly decrease the level of depressive symptoms in the intervention group compared to the control group. Methods: This pragmatic, randomised controlled trial included 425 patients diagnosed with myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants were recruited from hospitals in Turin and Pisa (Italy), and Lisbon (Portugal), and were randomly assigned to either the NEVERMIND intervention or to the control group. Clinical interviews and structured questionnaires were administered at baseline, 12 weeks, and 24 weeks. The primary outcome was depressive symptoms at 12 weeks measured by the Beck Depression Inventory II (BDI-II). Intention-to-treat analyses included 425 participants, while the per-protocol analyses included 333 participants. This trial is registered in the German Clinical Trials Register, DRKS00013391. Findings: Patients were recruited between Dec 4, 2017, and Dec 31, 2019, with 213 assigned to the intervention and 212 to the control group. The sample had a mean age of 59·41 years (SD=10·70), with 44·24% women. Those who used the NEVERMIND system had statistically significant lower depressive symptoms at the 12-week follow-up (mean difference=-3·03, Interpretation: The results of this study show that the NEVERMIND system is superior to standard care in reducing and preventing depressive symptoms among patients with the studied somatic conditions. Funding: The NEVERMIND project received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 689691.

Indexed as

Depressione-healthMental healthNEVERMINDRCTSomatic conditions

Identifiers

PMID35706482
PMCPMC9092507
OpenAlexW4229044469

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.