1
|
Anmella G, Mas A, Sanabra M, Valenzuela-Pascual C, Valentí M, Pacchiarotti I, Benabarre A, Grande I, De Prisco M, Oliva V, Fico G, Giménez-Palomo A, Bastidas A, Agasi I, Young AH, Garriga M, Corponi F, Li BM, de Looff P, Vieta E, Hidalgo-Mazzei D. Electrodermal activity in bipolar disorder: Differences between mood episodes and clinical remission using a wearable device in a real-world clinical setting. J Affect Disord 2024; 345:43-50. [PMID: 37865347 DOI: 10.1016/j.jad.2023.10.125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/16/2023] [Accepted: 10/18/2023] [Indexed: 10/23/2023]
Abstract
BACKGROUND Bipolar disorder (BD) lacks objective measures for illness activity and treatment response. Electrodermal activity (EDA) is a quantitative measure of autonomic function, which is altered in manic and depressive episodes. We aimed to explore differences in EDA (1) inter-individually: between patients with BD on acute mood episodes, euthymic states and healthy controls (HC), and (2) intra-individually: longitudinally within patients during acute mood episodes of BD and after clinical remission. METHODS A longitudinal observational study. EDA was recorded using a research-grade wearable in patients with BD during acute manic and depressive episodes and at clinical remission. Euthymic BD patients and HC were recorded during a single session. We compared EDA parameters derived from the tonic (mean EDA, mEDA) and phasic components (EDA peaks per minute, pmEDA, and EDA peaks mean amplitude, pmaEDA). Inter- and intra-individual comparisons were computed respectively with ANOVA and paired t-tests. RESULTS 49 patients with BD (15 manic, 9 depressed, and 25 euthymic), and 19 HC were included. Patients with bipolar depression showed significantly reduced mEDA (p = 0.003) and pmEDA (p = 0.001), which increased to levels similar to euthymia or HC after clinical remission (mEDA, p = 0.011; pmEDA, p < 0.001; pmaEDA, p < 0.001). Manic patients showed no differences compared to euthymic patients and HCs, but a significant reduction of tonic and phasic EDA parameters after clinical remission (mEDA, p = 0.035; pmEDA, p = 0.004). LIMITATIONS Limited sample size, high inter-individual variability of EDA parameters, limited comparability to previous studies and non-adjustment for medication. CONCLUSION EDA ecological monitoring might provide several opportunities for early detection of depressive symptoms, and might aid at assessing early response to treatments in mania and bipolar depression.
Collapse
Affiliation(s)
- Gerard Anmella
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain.
| | - Ariadna Mas
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Miriam Sanabra
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Clàudia Valenzuela-Pascual
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Marc Valentí
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Isabella Pacchiarotti
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Antoni Benabarre
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Iria Grande
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Michele De Prisco
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Vincenzo Oliva
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Giovanna Fico
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Anna Giménez-Palomo
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Anna Bastidas
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain
| | - Isabel Agasi
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain
| | - Allan H Young
- Centre for Affective Disorders (CfAD), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
| | - Marina Garriga
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | | | - Bryan M Li
- School of informatics, University of Edinburgh, UK
| | - Peter de Looff
- Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands; Fivoor, Science and Treatment Innovation, Expert centre "De Borg", Den Dolder, the Netherlands
| | - Eduard Vieta
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain
| | - Diego Hidalgo-Mazzei
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain; Bipolar and Depressive Disorders Unit, Digital Innovation Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, Institute of Neurosciences (UBNeuro), University of Barcelona (UB), Barcelona, Catalonia, Spain; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
| |
Collapse
|
2
|
Tani N, Fujihara H, Ishii K, Kamakura Y, Tsunemi M, Yamaguchi C, Eguchi H, Imamura K, Kanamori S, Kojimahara N, Ebara T. What digital health technology types are used in mental health prevention and intervention? Review of systematic reviews for systematization of technologies. J Occup Health 2024; 66:uiad003. [PMID: 38258936 PMCID: PMC11020255 DOI: 10.1093/joccuh/uiad003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 09/21/2023] [Accepted: 10/10/2023] [Indexed: 01/24/2024] Open
Abstract
Digital health technology has been widely applied to mental health interventions worldwide. Using digital phenotyping to identify an individual's mental health status has become particularly important. However, many technologies other than digital phenotyping are expected to become more prevalent in the future. The systematization of these technologies is necessary to accurately identify trends in mental health interventions. However, no consensus on the technical classification of digital health technologies for mental health interventions has emerged. Thus, we conducted a review of systematic review articles on the application of digital health technologies in mental health while attempting to systematize the technology using the Delphi method. To identify technologies used in digital phenotyping and other digital technologies, we included 4 systematic review articles that met the inclusion criteria, and an additional 8 review articles, using a snowballing approach, were incorporated into the comprehensive review. Based on the review results, experts from various disciplines participated in the Delphi process and agreed on the following 11 technical categories for mental health interventions: heart rate estimation, exercise or physical activity, sleep estimation, contactless heart rate/pulse wave estimation, voice and emotion analysis, self-care/cognitive behavioral therapy/mindfulness, dietary management, psychological safety, communication robots, avatar/metaverse devices, and brain wave devices. The categories we defined intentionally included technologies that are expected to become widely used in the future. Therefore, we believe these 11 categories are socially implementable and useful for mental health interventions.
Collapse
Affiliation(s)
- Naomichi Tani
- Department of Ergonomics, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu 807-8555, Japan
| | - Hiroaki Fujihara
- Department of Ergonomics, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu 807-8555, Japan
| | - Kenji Ishii
- The Ohara Memorial Institute for Science of Labour, Tokyo 151-0051, Japan
| | - Yoshiyuki Kamakura
- Department of Information Systems, Faculty of Information Science and Technology, Osaka Institute of Technology, Osaka 573-0196, Japan
| | - Mafu Tsunemi
- Department of Occupational and Environmental Health, Nagoya City University Graduate School of Medical Sciences/Medical School, Nagoya 467-8601, Japan
| | - Chikae Yamaguchi
- Department of Nursing, Faculty of Nursing, Kinjo Gakuin University, Aichi 463-8521, Japan
| | - Hisashi Eguchi
- Department of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health,Kitakyushu 807-8555, Japan
| | - Kotaro Imamura
- Department of Digital Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
| | - Satoru Kanamori
- Graduate School of Public Health, Teikyo University, Tokyo 173-8605, Japan
| | - Noriko Kojimahara
- Section of Epidemiology, Shizuoka Graduate University of Public Health, Shizuoka 420-0881, Japan
| | - Takeshi Ebara
- Department of Ergonomics, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu 807-8555, Japan
| |
Collapse
|
3
|
Kleiman EM, Glenn CR, Liu RT. The use of advanced technology and statistical methods to predict and prevent suicide. NATURE REVIEWS PSYCHOLOGY 2023; 2:347-359. [PMID: 37588775 PMCID: PMC10426769 DOI: 10.1038/s44159-023-00175-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/13/2023] [Indexed: 08/18/2023]
Abstract
In the past decade, two themes have emerged across suicide research. First, according to meta-analyses, the ability to predict and prevent suicidal thoughts and behaviours is weaker than would be expected for the size of the field. Second, review and commentary papers propose that technological and statistical methods (such as smartphones, wearables, digital phenotyping and machine learning) might become solutions to this problem. In this Review, we aim to strike a balance between the pessimistic picture presented by these meta-analyses and the optimistic picture presented by review and commentary papers about the promise of advanced technological and statistical methods to improve the ability to understand, predict and prevent suicide. We divide our discussion into two broad categories. First, we discuss the research aimed at assessment, with the goal of better understanding or more accurately predicting suicidal thoughts and behaviours. Second, we discuss the literature that focuses on prevention of suicidal thoughts and behaviours. Ecological momentary assessment, wearables and other technological and statistical advances hold great promise for predicting and preventing suicide, but there is much yet to do.
Collapse
Affiliation(s)
- Evan M. Kleiman
- Department of Psychology, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | | | - Richard T. Liu
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| |
Collapse
|
4
|
Galatzer-Levy IR, Onnela JP. Machine Learning and the Digital Measurement of Psychological Health. Annu Rev Clin Psychol 2023; 19:133-154. [PMID: 37159287 DOI: 10.1146/annurev-clinpsy-080921-073212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Since its inception, the discipline of psychology has utilized empirical epistemology and mathematical methodologies to infer psychological functioning from direct observation. As new challenges and technological opportunities emerge, scientists are once again challenged to define measurement paradigms for psychological health and illness that solve novel problems and capitalize on new technological opportunities. In this review, we discuss the theoretical foundations of and scientific advances in remote sensor technology and machine learning models as they are applied to quantify psychological functioning, draw clinical inferences, and chart new directions in treatment.
Collapse
Affiliation(s)
- Isaac R Galatzer-Levy
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA;
- Current affiliation: Google LLC, Mountain View, California, USA
| | - Jukka-Pekka Onnela
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| |
Collapse
|
5
|
Anmella G, Corponi F, Li BM, Mas A, Sanabra M, Pacchiarotti I, Valentí M, Grande I, Benabarre A, Giménez-Palomo A, Garriga M, Agasi I, Bastidas A, Cavero M, Fernández-Plaza T, Arbelo N, Bioque M, García-Rizo C, Verdolini N, Madero S, Murru A, Amoretti S, Martínez-Aran A, Ruiz V, Fico G, De Prisco M, Oliva V, Solanes A, Radua J, Samalin L, Young AH, Vieta E, Vergari A, Hidalgo-Mazzei D. Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study. JMIR Mhealth Uhealth 2023; 11:e45405. [PMID: 36939345 DOI: 10.2196/45405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 02/20/2023] [Accepted: 03/07/2023] [Indexed: 03/21/2023] Open
Abstract
BACKGROUND Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity alongside physiological alterations that wearables can capture. OBJECTIVE We explored whether physiological wearable data could predict: (aim 1) the severity of an acute affective episode at the intra-individual level, (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to the prior predictions, generalization across patients, and associations between affective symptoms and physiological data. METHODS We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded with a research-grade wearable (Empatica E4) across three consecutive timepoints (acute, response, and remission of episode). Euthymic patients and healthy controls (HC) were recorded during a single session (∼48 hours). Manic and depressive symptoms were assessed with standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), temperature (TEMP), blood volume pulse (BVP), heart rate (HR), and electrodermal activity (EDA). For data pre-processing, invalid physiological data were removed using a rule-based filter, channels were time-aligned at 1 second time units and then segmented window lengths of 32 seconds, since those parameters showed the best performances. We developed deep learning predictive models, assessed channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel fully automated method for analysis of physiological data from a research-grade wearable device, including a rule-based filter for invalid data and a viable supervised learning pipeline for time-series analyses. RESULTS 35 sessions (1,512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 HC (age 39.7±12.6; 31.6% female) were analyzed. (aim 1) The severity of mood episodes was predicted with moderate (62%-85%) accuracies. (aim 2) The polarity of episodes was predicted with moderate (70%) accuracy. The most relevant features for the former tasks were ACC, EDA, and HR. Kendall W showed fair agreement (0.383) in feature importance across classification tasks. Generalization of the former models were of overall low accuracy, with better results for the intra-individual models. "Increased motor activity" was associated with ACC (NMI>0.55), "aggressive behavior" with EDA (NMI=1.0), "insomnia" with ACC (NMI∼0.6), "motor inhibition" with ACC (NMI∼0.75), and "psychic anxiety" with EDA (NMI=0.52). CONCLUSIONS Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression respectively. These findings represent a promising pathway towards personalized psychiatry, in which physiological wearable data could allow early identification and intervention of mood episodes. CLINICALTRIAL
Collapse
Affiliation(s)
- Gerard Anmella
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Filippo Corponi
- School of informatics, University of Edinburgh, UK., Edinburgh, GB
| | - Bryan M Li
- School of informatics, University of Edinburgh, UK., Edinburgh, GB
| | - Ariadna Mas
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Miriam Sanabra
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Isabella Pacchiarotti
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Marc Valentí
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Iria Grande
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Antoni Benabarre
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Anna Giménez-Palomo
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Marina Garriga
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Isabel Agasi
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Anna Bastidas
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Myriam Cavero
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | | | - Néstor Arbelo
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Miquel Bioque
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Clemente García-Rizo
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Norma Verdolini
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Santiago Madero
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Andrea Murru
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Silvia Amoretti
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Anabel Martínez-Aran
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Victoria Ruiz
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Giovanna Fico
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Michele De Prisco
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Vincenzo Oliva
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Aleix Solanes
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) group, Barcelona, ES
| | - Joaquim Radua
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) group, Barcelona, ES
| | - Ludovic Samalin
- Department of Psychiatry, CHU Clermont-Ferrand, University of Clermont Auvergne, CNRS, Clermont Auvergne INP, Institut Pascal (UMR 6602), Clermont-Ferrand, France., Clermont-Ferrand, FR
| | - Allan H Young
- Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom., London, GB
| | - Eduard Vieta
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Antonio Vergari
- School of informatics, University of Edinburgh, UK., Edinburgh, GB
| | - Diego Hidalgo-Mazzei
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| |
Collapse
|
6
|
Anmella G, Sanabra M, Primé-Tous M, Segú X, Solanes A, Ruíz V, Morilla I, Also Fontanet A, Sant E, Murgui S, Sans-Corrales M, Martínez-Aran A, Fico G, De Prisco M, Oliva V, Murru A, Zahn R, Young AH, Vicens V, Viñas-Bardolet C, Aparicio-Nogué V, Martínez-Cerdá JF, Mas A, Carreras B, Blanch J, Radua J, Fullana MA, Cavero M, Vieta E, Hidalgo-Mazzei D. Antidepressants overuse in primary care: Prescription trends between 2010 and 2019 in Catalonia. REVISTA DE PSIQUIATRIA Y SALUD MENTAL 2022:S1888-9891(22)00137-9. [PMID: 37758595 DOI: 10.1016/j.rpsm.2022.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 11/17/2022] [Accepted: 12/04/2022] [Indexed: 12/15/2022]
Abstract
INTRODUCTION There has been an increase in the prescription of antidepressants (AD) in primary care (PC). However, it is unclear whether this was explained by a rise in diagnoses with an indication for AD. We investigated the changes in frequency and the variables associated with AD prescription in Catalonia, Spain. METHODS We retrieved AD prescription, sociodemographic, and health-related data using individual electronic health records from a population-representative sample (N=947.698) attending PC between 2010 and 2019. Prescription of AD was calculated using DHD (Defined Daily Doses per 1000 inhabitants/day). We compared cumulative changes in DHD with cumulative changes in diagnoses with an indication for AD during the study period. We used Poisson regression to examine sociodemographic and health-related variables associated with AD prescription. RESULTS Both AD prescription and mental health diagnoses with an indication for AD gradually increased. At the end of the study period, DHD of AD prescriptions and mental health diagnoses with an indication for AD reached cumulative increases of 404% and 49% respectively. Female sex (incidence rate ratio (IRR)=2.83), older age (IRR=25.43), and lower socio-economic status (IRR=1.35) were significantly associated with increased risk of being prescribed an AD. CONCLUSIONS Our results from a large and representative cohort of patients confirm a steady increase of AD prescriptions that is not explained by a parallel increase in mental health diagnoses with an indication for AD. A trend on AD off-label and over-prescriptions in the PC system in Catalonia can be inferred from this dissociation.
Collapse
Affiliation(s)
- Gerard Anmella
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; University of Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain
| | - Miriam Sanabra
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Mireia Primé-Tous
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Xavier Segú
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Aleix Solanes
- Mental Health Research Networking Center (CIBERSAM), Madrid, Spain; Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Victoria Ruíz
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Ivette Morilla
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Antonieta Also Fontanet
- CAP Casanova, Consorci d'Atenció Primaria de Salut Barcelona Esquerra (CAPSBE), Barcelona, Spain
| | - Elisenda Sant
- CAP Casanova, Consorci d'Atenció Primaria de Salut Barcelona Esquerra (CAPSBE), Barcelona, Spain
| | - Sandra Murgui
- CAP Comte Borrell, Consorci d'Atenció Primaria de Salut Barcelona Esquerra (CAPSBE), Barcelona, Spain
| | - Mireia Sans-Corrales
- CAP Comte Borrell, Consorci d'Atenció Primaria de Salut Barcelona Esquerra (CAPSBE), Barcelona, Spain
| | - Anabel Martínez-Aran
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; University of Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain
| | - Giovanna Fico
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; University of Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain
| | - Michele De Prisco
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; University of Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain
| | - Vincenzo Oliva
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; University of Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain
| | - Andrea Murru
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; University of Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain
| | - Roland Zahn
- Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Allan H Young
- Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | | | - Clara Viñas-Bardolet
- Data Analytics Programme for Health Research and Innovation (PADRIS), Catalan Agency for Health Quality and Evaluation (AQuAS), Barcelona, Spain
| | - Vicenç Aparicio-Nogué
- Data Analytics Programme for Health Research and Innovation (PADRIS), Catalan Agency for Health Quality and Evaluation (AQuAS), Barcelona, Spain
| | - Juan Francisco Martínez-Cerdá
- Data Analytics Programme for Health Research and Innovation (PADRIS), Catalan Agency for Health Quality and Evaluation (AQuAS), Barcelona, Spain
| | - Ariadna Mas
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Bernat Carreras
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Jordi Blanch
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; University of Barcelona, Barcelona, Spain; Abi Global Health, Spain; Mental Health and Addiction Programme, Department of Health, Generalitat de Catalunya, Barcelona, Spain; President of the European Association of Psychosomatic Medicine, Spain
| | - Joaquim Radua
- Mental Health Research Networking Center (CIBERSAM), Madrid, Spain; Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Miquel A Fullana
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain; Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Myriam Cavero
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; University of Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain
| | - Eduard Vieta
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; University of Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain
| | - Diego Hidalgo-Mazzei
- Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; University of Barcelona, Barcelona, Spain; Mental Health Research Networking Center (CIBERSAM), Madrid, Spain; Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
| |
Collapse
|
7
|
Potier R. Revue critique sur le potentiel du numérique dans la recherche en psychopathologie : un point de vue psychanalytique. L'ÉVOLUTION PSYCHIATRIQUE 2022. [DOI: 10.1016/j.evopsy.2022.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
|