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Predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric FACE-SZ dataset

Schizophrenia is characterized by the most salient medication adherence problems among severe mental disorders, but limited prospective data are available to predict and improve adherence in this population. This investigation aims to identify predictors of medication adherence over a 1-year period...

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Autores principales: Misdrahi, David, Dupuy, Maud, Dansou, Yecodji, Boyer, Laurent, Berna, Fabrice, Capdevielle, Delphine, Chereau, Isabelle, Coulon, Nathalie, D’Amato, Thierry, Dubertret, Caroline, Leignier, Sylvain, Llorca, Pierre Michel, Lançon, Christophe, Mallet, Jasmina, Passerieux, Christine, Pignon, Baptiste, Rey, Romain, Schürhoff, Franck, Swendsen, Joel, Urbach, Mathieu, Szöke, Andrei, Godin, Ophélia, Fond, Guillaume
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630458/
https://www.ncbi.nlm.nih.gov/pubmed/37935695
http://dx.doi.org/10.1038/s41398-023-02640-x
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author Misdrahi, David
Dupuy, Maud
Dansou, Yecodji
Boyer, Laurent
Berna, Fabrice
Capdevielle, Delphine
Chereau, Isabelle
Coulon, Nathalie
D’Amato, Thierry
Dubertret, Caroline
Leignier, Sylvain
Llorca, Pierre Michel
Lançon, Christophe
Mallet, Jasmina
Passerieux, Christine
Pignon, Baptiste
Rey, Romain
Schürhoff, Franck
Swendsen, Joel
Urbach, Mathieu
Szöke, Andrei
Godin, Ophélia
Fond, Guillaume
author_facet Misdrahi, David
Dupuy, Maud
Dansou, Yecodji
Boyer, Laurent
Berna, Fabrice
Capdevielle, Delphine
Chereau, Isabelle
Coulon, Nathalie
D’Amato, Thierry
Dubertret, Caroline
Leignier, Sylvain
Llorca, Pierre Michel
Lançon, Christophe
Mallet, Jasmina
Passerieux, Christine
Pignon, Baptiste
Rey, Romain
Schürhoff, Franck
Swendsen, Joel
Urbach, Mathieu
Szöke, Andrei
Godin, Ophélia
Fond, Guillaume
author_sort Misdrahi, David
collection PubMed
description Schizophrenia is characterized by the most salient medication adherence problems among severe mental disorders, but limited prospective data are available to predict and improve adherence in this population. This investigation aims to identify predictors of medication adherence over a 1-year period in a large national cohort using clustering analysis. Outpatients were recruited from ten Schizophrenia Expert Centers and were evaluated with a day-long standardized battery including clinician and patient-rated medication adherence measures. A two-step cluster analysis and multivariate logistic regression were conducted to identify medication adherence profiles based on the Medication Adherence rating Scale (MARS) and baseline predictors. A total of 485 participants were included in the study and medication adherence was significantly improved at the 1-year follow-up. Higher depressive scores, lower insight, history of suicide attempt, younger age and alcohol use disorder were all associated with poorer adherence at 1 year. Among the 203 patients with initially poor adherence, 86 (42%) switched to good adherence at the 1-year follow-up, whereas 117 patients (58%) remained poorly adherent. Targeting younger patients with low insight, history of suicide, alcohol use disorder and depressive disorders should be prioritized through literacy and educational therapy programs. Adherence is a construct that can vary considerably from year to year in schizophrenia, and therefore may be amenable to interventions for its improvement. However, caution is also warranted as nearly one in five patients with initially good adherence experienced worsened adherence 1 year later.
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spelling pubmed-106304582023-11-07 Predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric FACE-SZ dataset Misdrahi, David Dupuy, Maud Dansou, Yecodji Boyer, Laurent Berna, Fabrice Capdevielle, Delphine Chereau, Isabelle Coulon, Nathalie D’Amato, Thierry Dubertret, Caroline Leignier, Sylvain Llorca, Pierre Michel Lançon, Christophe Mallet, Jasmina Passerieux, Christine Pignon, Baptiste Rey, Romain Schürhoff, Franck Swendsen, Joel Urbach, Mathieu Szöke, Andrei Godin, Ophélia Fond, Guillaume Transl Psychiatry Article Schizophrenia is characterized by the most salient medication adherence problems among severe mental disorders, but limited prospective data are available to predict and improve adherence in this population. This investigation aims to identify predictors of medication adherence over a 1-year period in a large national cohort using clustering analysis. Outpatients were recruited from ten Schizophrenia Expert Centers and were evaluated with a day-long standardized battery including clinician and patient-rated medication adherence measures. A two-step cluster analysis and multivariate logistic regression were conducted to identify medication adherence profiles based on the Medication Adherence rating Scale (MARS) and baseline predictors. A total of 485 participants were included in the study and medication adherence was significantly improved at the 1-year follow-up. Higher depressive scores, lower insight, history of suicide attempt, younger age and alcohol use disorder were all associated with poorer adherence at 1 year. Among the 203 patients with initially poor adherence, 86 (42%) switched to good adherence at the 1-year follow-up, whereas 117 patients (58%) remained poorly adherent. Targeting younger patients with low insight, history of suicide, alcohol use disorder and depressive disorders should be prioritized through literacy and educational therapy programs. Adherence is a construct that can vary considerably from year to year in schizophrenia, and therefore may be amenable to interventions for its improvement. However, caution is also warranted as nearly one in five patients with initially good adherence experienced worsened adherence 1 year later. Nature Publishing Group UK 2023-11-07 /pmc/articles/PMC10630458/ /pubmed/37935695 http://dx.doi.org/10.1038/s41398-023-02640-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Misdrahi, David
Dupuy, Maud
Dansou, Yecodji
Boyer, Laurent
Berna, Fabrice
Capdevielle, Delphine
Chereau, Isabelle
Coulon, Nathalie
D’Amato, Thierry
Dubertret, Caroline
Leignier, Sylvain
Llorca, Pierre Michel
Lançon, Christophe
Mallet, Jasmina
Passerieux, Christine
Pignon, Baptiste
Rey, Romain
Schürhoff, Franck
Swendsen, Joel
Urbach, Mathieu
Szöke, Andrei
Godin, Ophélia
Fond, Guillaume
Predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric FACE-SZ dataset
title Predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric FACE-SZ dataset
title_full Predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric FACE-SZ dataset
title_fullStr Predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric FACE-SZ dataset
title_full_unstemmed Predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric FACE-SZ dataset
title_short Predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric FACE-SZ dataset
title_sort predictors of medication adherence in a large 1-year prospective cohort of individuals with schizophrenia: insights from the multicentric face-sz dataset
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630458/
https://www.ncbi.nlm.nih.gov/pubmed/37935695
http://dx.doi.org/10.1038/s41398-023-02640-x
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