Evidence map›Paper›PMID 41262687›Full record

ArticleFrontiers in psychiatry2025

Attitudes towards a multimodal precision medicine algorithm for predicting treatment response in depression: findings from a large cross-sectional European survey.

Viktor T H Wahner, Johannes C S Zang, Rosa Glaser, Britta Kelch, Inga Stonner, Martina Contu, Mara Dierssen, Ewa Ferensztajn-Rochowiak, Massimo Gennarelli, Dobrochna Kopeć and 16 more

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

26 authors.

Viktor T H WahnerDepartment of Psychiatry, University of Münster, Münster, Germany.
Johannes C S ZangDepartment of General Internal Medicine and Psychosomatic, University Hospital Heidelberg, Heidelberg, Germany.
Rosa GlaserDepartment of Psychiatry, University of Münster, Münster, Germany.
Britta KelchDepartment of Psychiatry, University of Münster, Münster, Germany.
Inga StonnerDepartment of Psychiatry, University of Münster, Münster, Germany.
Martina ContuSection of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
Mara DierssenCentre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
Ewa Ferensztajn-RochowiakDepartment of Adult Psychiatry, Poznan University of Medical Sciences, Poznan, Poland.
Massimo GennarelliDepartment of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.
Dobrochna KopećDepartment of Adult Psychiatry, Poznan University of Medical Sciences, Poznan, Poland.
Mirko ManchiaSection of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
María Martínez de LagránCentre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
Valentina MeneselloDepartment of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.
Oumayma MeskiniParis Brain Institute (ICM), National Centre for Scientific Research (CNRS), Paris, France.
Alessandra MinelliDepartment of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.
Pasquale ParibelloSection of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
Júlia Perera BelResearch Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute (IMIM), Barcelona, Spain.
Giulia PerusiDepartment of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Brescia, Italy.
Marco PinnaSection of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
Claudia PisanuSection of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.
Marie-Claude PotierParis Brain Institute (ICM), National Centre for Scientific Research (CNRS), Paris, France.
Filip RybakowskiDepartment of Adult Psychiatry, Poznan University of Medical Sciences, Poznan, Poland.
Ferran SanzResearch Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute (IMIM), Barcelona, Spain.
Alessio SquassinaSection of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.
Silke JörgensDepartment of Psychiatry, University of Münster, Münster, Germany.
Bernhard T BauneDepartment of Psychiatry, University of Münster, Münster, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Precision medicine aims to facilitate a more individualized treatment selection and a more accurate diagnosis. While there is broad ranging research on precision psychiatry and the corresponding computational tools, its concepts and implementation are underway, little is known about the attitudes towards the actual use of precision psychiatry tools in the management of major psychiatric disorders, such as Major Depressive Disorder (MDD). This study aims to investigate the attitudes of depressive patients, professionals (physicians, psychologists and scientists) and the general population towards a novel, multimodal precision medicine algorithm designed to predict antidepressant treatment response. Methods: 5490 participants from 21 European countries, consisting of three groups of stakeholders, patients with depression (n= 421), professionals (n = 367) and the general population (n = 4702), were polled with a newly developed cross-sectional survey. A hypothetical decision scenario was used to examine the participants' attitudes, in which they were asked for their approval or disapproval for the application of a multimodal precision medicine algorithm to predict treatment response in antidepressant-treatment.3. Results: The general population had an acceptance rate of 78.8%. Overall, 74.6% of patients with MDD would agree to undergo testing using the multimodal algorithm in their current situation and 80.2% reported they would have done so at the time of their first diagnosis. In contrast, the psychiatrist's acceptance rates towards a multimodal algorithm were higher when patients had been in treatment for some time (79.3%) compared to those who had only recently been diagnosed (55.2%). This pattern was present across all other specialties within the professionals group. A considerable number of participants wished to receive more information before deciding, but few declined its application altogether. All groups indicated an openness towards personalized treatment options in general. Conclusion: Overall, participants indicated a large degree of acceptance towards the application of a multimodal precision medicine algorithm. Although limited by the hypothetical nature of the decision scenario, this study provides valuable perspectives from different stakeholders. Future research should move beyond attitudes and address further implementation hurdles that need to be overcome for the successful implementation of novel precision psychiatry approaches in psychiatric care.

Indexed as

algorithmmajor depressive disorder (MDD)personalized medicineprecision medicineprecision psychiatrytreatment resistant depression (TRD)treatment response

Identifiers

PMID41262687
PMCPMC12624457

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