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Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach

BACKGROUND: Based on the theoretical model of medication adherence (WHO, 2003), the aims of the study were (1) to develop and test a theory-based multidimensional model for the predictive power of barriers to and facilitators of medication adherence and (2) to identify the mediating effects of barri...

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Autores principales: Quaschning, Katharina, Koerner, Mirjam, Wirtz, Markus Antonius
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9063142/
https://www.ncbi.nlm.nih.gov/pubmed/35501793
http://dx.doi.org/10.1186/s12913-022-07987-3
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author Quaschning, Katharina
Koerner, Mirjam
Wirtz, Markus Antonius
author_facet Quaschning, Katharina
Koerner, Mirjam
Wirtz, Markus Antonius
author_sort Quaschning, Katharina
collection PubMed
description BACKGROUND: Based on the theoretical model of medication adherence (WHO, 2003), the aims of the study were (1) to develop and test a theory-based multidimensional model for the predictive power of barriers to and facilitators of medication adherence and (2) to identify the mediating effects of barriers to medication adherence on drug-related patient outcomes (barrier “MedAd- “: forget; facilitator “MedAd + ”: regular intake). METHODS: Within a cross-sectional study entitled “Increasing medication adherence to improve patient safety in cardiological rehabilitation (PaSiMed)”, the model was evaluated in structural analytical terms based on data collected online of N = 225 patients with cardiometabolic diseases. The revised “Freiburg questionnaire on medication adherence (FF-MedAd-R)" was used to measure the latent constructs (e.g., facilitator: communication; barrier: reservations).” RESULTS: The structural equation model proved to exhibit an appropriate data fit (RMSEA: .05; CFI: .92). For all first-order facilitators of medication adherence, a high proportion of variance (62–94%) could be explained by the second-order factor “Physician–patient relationship (PPR)”. All paths from “PPR” to the constructs depicting barriers to medication adherence showed significant negative effects. Facilitators (“MedAd + ”) and barriers (“MedAd-”) accounted for 20% and 12% of the variance, respectively, in global items of medication adherence. Whereas “Carelessness” showed a full mediation for “MedAd-”, ‘‘Reservations’’ showed a partial mediation for “MedAd + ”. CONCLUSIONS: “PPR” is an important predictor of patient medication adherence. The results underline the importance of a trustful physician–patient relationship in reducing barriers and enhancing medication adherence. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-07987-3.
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spelling pubmed-90631422022-05-04 Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach Quaschning, Katharina Koerner, Mirjam Wirtz, Markus Antonius BMC Health Serv Res Research BACKGROUND: Based on the theoretical model of medication adherence (WHO, 2003), the aims of the study were (1) to develop and test a theory-based multidimensional model for the predictive power of barriers to and facilitators of medication adherence and (2) to identify the mediating effects of barriers to medication adherence on drug-related patient outcomes (barrier “MedAd- “: forget; facilitator “MedAd + ”: regular intake). METHODS: Within a cross-sectional study entitled “Increasing medication adherence to improve patient safety in cardiological rehabilitation (PaSiMed)”, the model was evaluated in structural analytical terms based on data collected online of N = 225 patients with cardiometabolic diseases. The revised “Freiburg questionnaire on medication adherence (FF-MedAd-R)" was used to measure the latent constructs (e.g., facilitator: communication; barrier: reservations).” RESULTS: The structural equation model proved to exhibit an appropriate data fit (RMSEA: .05; CFI: .92). For all first-order facilitators of medication adherence, a high proportion of variance (62–94%) could be explained by the second-order factor “Physician–patient relationship (PPR)”. All paths from “PPR” to the constructs depicting barriers to medication adherence showed significant negative effects. Facilitators (“MedAd + ”) and barriers (“MedAd-”) accounted for 20% and 12% of the variance, respectively, in global items of medication adherence. Whereas “Carelessness” showed a full mediation for “MedAd-”, ‘‘Reservations’’ showed a partial mediation for “MedAd + ”. CONCLUSIONS: “PPR” is an important predictor of patient medication adherence. The results underline the importance of a trustful physician–patient relationship in reducing barriers and enhancing medication adherence. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-07987-3. BioMed Central 2022-05-02 /pmc/articles/PMC9063142/ /pubmed/35501793 http://dx.doi.org/10.1186/s12913-022-07987-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Quaschning, Katharina
Koerner, Mirjam
Wirtz, Markus Antonius
Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach
title Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach
title_full Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach
title_fullStr Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach
title_full_unstemmed Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach
title_short Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach
title_sort analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9063142/
https://www.ncbi.nlm.nih.gov/pubmed/35501793
http://dx.doi.org/10.1186/s12913-022-07987-3
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