A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms
IntroductionDepression is the leading cause of worldwide disability, until now only 3% of patients with major depressive disorder (MDD) experiences full recovery or remission. Different studies have tried to better understand MDD pathophysiology and its resistant forms (TRD), focusing on the identif...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-11-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1321345/full |
| _version_ | 1827670620058419200 |
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| author | Annarita Vignapiano Annarita Vignapiano Francesco Monaco Francesco Monaco Claudio Pagano Claudio Pagano Martina Piacente Federica Farina Gianvito Petrillo Raffaella Sica Alessandra Marenna Jae Il Shin Jae Il Shin Marco Solmi Marco Solmi Marco Solmi Marco Solmi Marco Solmi Giulio Corrivetti Giulio Corrivetti |
| author_facet | Annarita Vignapiano Annarita Vignapiano Francesco Monaco Francesco Monaco Claudio Pagano Claudio Pagano Martina Piacente Federica Farina Gianvito Petrillo Raffaella Sica Alessandra Marenna Jae Il Shin Jae Il Shin Marco Solmi Marco Solmi Marco Solmi Marco Solmi Marco Solmi Giulio Corrivetti Giulio Corrivetti |
| author_sort | Annarita Vignapiano |
| collection | DOAJ |
| description | IntroductionDepression is the leading cause of worldwide disability, until now only 3% of patients with major depressive disorder (MDD) experiences full recovery or remission. Different studies have tried to better understand MDD pathophysiology and its resistant forms (TRD), focusing on the identification of candidate biomarkers that would be able to reflect the patients’ state and the effects of therapy. Development of digital technologies can generate useful digital biomarkers in a real-world setting. This review aims to focus on the use of digital technologies measuring symptom severity and predicting treatment outcomes for individuals with mood disorders.MethodsTwo databases (PubMed and APA PsycINFO) were searched to retrieve papers published from January 1, 2013, to July 30, 2023, on the use of digital devices in persons with MDD. All papers had to meet specific inclusion criteria, which resulted in the inclusion of 12 articles.ResultsResearch on digital biomarkers confronts four core aspects: (I) predicting diagnostic status, (II) assessing symptom severity and progression, (III) identifying treatment response and (IV) monitoring real-word and ecological validity. Different wearable technologies have been applied to collect physiological, activity/sleep, or subjective data to explore their relationships with depression.DiscussionDepression’s stable rates and high relapse risk necessitate innovative approaches. Wearable devices hold promise for continuous monitoring and data collection in real world setting.ConclusionMore studies are needed to translate these digital biomarkers into actionable interventions to improve depression diagnosis, monitoring and management. Future challenges will be the applications of wearable devices routinely in personalized medicine. |
| first_indexed | 2024-03-10T03:24:38Z |
| format | Article |
| id | doaj.art-aa47437358f7441eb3ea336b1b00ccb6 |
| institution | Directory Open Access Journal |
| issn | 1664-0640 |
| language | English |
| last_indexed | 2024-03-10T03:24:38Z |
| publishDate | 2023-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj.art-aa47437358f7441eb3ea336b1b00ccb62023-11-23T09:55:01ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402023-11-011410.3389/fpsyt.2023.13213451321345A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant formsAnnarita Vignapiano0Annarita Vignapiano1Francesco Monaco2Francesco Monaco3Claudio Pagano4Claudio Pagano5Martina Piacente6Federica Farina7Gianvito Petrillo8Raffaella Sica9Alessandra Marenna10Jae Il Shin11Jae Il Shin12Marco Solmi13Marco Solmi14Marco Solmi15Marco Solmi16Marco Solmi17Giulio Corrivetti18Giulio Corrivetti19Department of Mental Health, Salerno, ItalyEuropean Biomedical Research Institute of Salerno (EBRIS), Salerno, ItalyDepartment of Mental Health, Salerno, ItalyEuropean Biomedical Research Institute of Salerno (EBRIS), Salerno, ItalyDipartimento di Scienze Aziendali—Managment e Innovation Systems, Università di Salerno, Salerno, ItalyInnovation Tecnology e Sviluppo (I.T. Svil), Salerno, ItalyEuropean Biomedical Research Institute of Salerno (EBRIS), Salerno, ItalyEuropean Biomedical Research Institute of Salerno (EBRIS), Salerno, ItalyInnovation Tecnology e Sviluppo (I.T. Svil), Salerno, ItalyDepartment of Mental Health, Salerno, ItalyEuropean Biomedical Research Institute of Salerno (EBRIS), Salerno, ItalyDepartment of Pediatrics, Yonsei University College of Medicine, Seoul, Republic of KoreaSeverance Underwood Meta-Research Center, Institute of Convergence Science, Yonsei University, Seoul, Republic of KoreaDepartment of Psychiatry, University of Ottawa, Ontario, ON, CanadaOn Track: The Champlain First Episode Psychosis Program, Department of Mental Health, The Ottawa Hospital, Ontario, ON, CanadaClinical Epidemiology Program, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada0School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada1Department of Child and Adolescent Psychiatry, Charité—Universitätsmedizin, Berlin, GermanyDepartment of Mental Health, Salerno, ItalyEuropean Biomedical Research Institute of Salerno (EBRIS), Salerno, ItalyIntroductionDepression is the leading cause of worldwide disability, until now only 3% of patients with major depressive disorder (MDD) experiences full recovery or remission. Different studies have tried to better understand MDD pathophysiology and its resistant forms (TRD), focusing on the identification of candidate biomarkers that would be able to reflect the patients’ state and the effects of therapy. Development of digital technologies can generate useful digital biomarkers in a real-world setting. This review aims to focus on the use of digital technologies measuring symptom severity and predicting treatment outcomes for individuals with mood disorders.MethodsTwo databases (PubMed and APA PsycINFO) were searched to retrieve papers published from January 1, 2013, to July 30, 2023, on the use of digital devices in persons with MDD. All papers had to meet specific inclusion criteria, which resulted in the inclusion of 12 articles.ResultsResearch on digital biomarkers confronts four core aspects: (I) predicting diagnostic status, (II) assessing symptom severity and progression, (III) identifying treatment response and (IV) monitoring real-word and ecological validity. Different wearable technologies have been applied to collect physiological, activity/sleep, or subjective data to explore their relationships with depression.DiscussionDepression’s stable rates and high relapse risk necessitate innovative approaches. Wearable devices hold promise for continuous monitoring and data collection in real world setting.ConclusionMore studies are needed to translate these digital biomarkers into actionable interventions to improve depression diagnosis, monitoring and management. Future challenges will be the applications of wearable devices routinely in personalized medicine.https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1321345/fullmajor depressive disorderdigital biomarkerswearable devicesartificial intelligencepersonalized treatmentmental healthcare |
| spellingShingle | Annarita Vignapiano Annarita Vignapiano Francesco Monaco Francesco Monaco Claudio Pagano Claudio Pagano Martina Piacente Federica Farina Gianvito Petrillo Raffaella Sica Alessandra Marenna Jae Il Shin Jae Il Shin Marco Solmi Marco Solmi Marco Solmi Marco Solmi Marco Solmi Giulio Corrivetti Giulio Corrivetti A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms Frontiers in Psychiatry major depressive disorder digital biomarkers wearable devices artificial intelligence personalized treatment mental healthcare |
| title | A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms |
| title_full | A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms |
| title_fullStr | A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms |
| title_full_unstemmed | A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms |
| title_short | A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms |
| title_sort | narrative review of digital biomarkers in the management of major depressive disorder and treatment resistant forms |
| topic | major depressive disorder digital biomarkers wearable devices artificial intelligence personalized treatment mental healthcare |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1321345/full |
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