Attitudes towards a Multimodal Precision Medicine Algorithm for Predicting Treatment Response in Depression: Findings from a large cross-sectional European Survey

Viktor T. H. Wahner¹Johannes C. S. Zang²Rosa Glaser¹Britta Kelch¹Inga Stonner¹Martina Contu³Mara Dierssen⁴Ewa Ferensztajn-Rochowiak⁵Massimo Gennarelli⁶Dobrochna Kopeć⁵Mirko Manchia^3,7Maria Martínez De Lagran⁴Valentina Menesello⁶Oumayma Meskini⁸Alessandra Minelli⁶Pasquale Paribello³Júlia Perera Bel⁹Giulia Perusi⁶Marco Pinna³Claudia Pisanu¹⁰Marie-Claude Potier⁸Filip Rybakowski⁵Ferran Sanz^11,9Alessio Squassina^10,12Silke Jörgens^1,13Bernhard Baune^1,14,15*

• ¹Department of Mental Health, University of Münster, Münster, Germany
• ²Department of General Internal Medicine and Psychosomatic, University Hospital Heidelberg, Heidelberg, Germany
• ³Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
• ⁴Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
• ⁵Department of Adult Psychiatry, Poznan University of Medical Sciences, Poznan, Poland
• ⁶Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
• ⁷Department of Pharmacology, Dalhousie University Halifax, Halifax, Canada
• ⁸Paris Brain Institute (ICM), National Centre for Scientific Research (CNRS), Paris, France
• ⁹Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute (IMIM), Barcelona, Spain
• ¹⁰Section of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
• ¹¹Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
• ¹²Department of Psychiatry, Dalhousie University, Halifax, Canada
• ¹³Department Hamm 2, Hochschule Hamm-Lippstadt, Hamm, Germany
• ¹⁴The Florey Institute of Neuroscience and Mental Health, Parkville, Australia
• ¹⁵Department of Psychiatry, University of Melbourne, Melbourne, Australia

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 Depression 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. 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.