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Structural equation modeling of the proximal–distal continuum of adherence drivers

OBJECTIVES: Nonadherence to prescription medications has been shown to be significantly influenced by three key medication-specific beliefs: patients’ perceived need for the prescribed medication, their concerns about the prescribed medication, and perceived medication affordability. Structural equa...

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Autores principales: McHorney, Colleen A, Zhang, Ning Jackie, Stump, Timothy, Zhao, Xiaoquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3508554/
https://www.ncbi.nlm.nih.gov/pubmed/23204839
http://dx.doi.org/10.2147/PPA.S36535
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author McHorney, Colleen A
Zhang, Ning Jackie
Stump, Timothy
Zhao, Xiaoquan
author_facet McHorney, Colleen A
Zhang, Ning Jackie
Stump, Timothy
Zhao, Xiaoquan
author_sort McHorney, Colleen A
collection PubMed
description OBJECTIVES: Nonadherence to prescription medications has been shown to be significantly influenced by three key medication-specific beliefs: patients’ perceived need for the prescribed medication, their concerns about the prescribed medication, and perceived medication affordability. Structural equation modeling was used to test the predictors of these three proximal determinants of medication adherence using the proximal–distal continuum of adherence drivers as the organizing conceptual framework. METHODS: In Spring 2008, survey participants were selected from the Harris Interactive Chronic Illness Panel, an internet-based panel of hundreds of thousands of adults with chronic disease. Respondents were eligible for the survey if they were aged 40 years and older, resided in the US, and reported having at least one of six chronic diseases: asthma, diabetes, hyperlipidemia, hypertension, osteoporosis, or other cardiovascular disease. A final sample size of 1072 was achieved. The proximal medication beliefs were measured by three multi-item scales: perceived need for medications, perceived medication concerns, and perceived medication affordability. The intermediate sociomedical beliefs and skills included four multi-item scales: perceived disease severity, knowledge about the prescribed medication, perceived immunity to side effects, and perceived value of nutraceuticals. Generic health beliefs and skills consisted of patient engagement in their care, health information-seeking tendencies, internal health locus of control, a single-item measure of self-rated health, and general mental health. Structural equation modeling was used to model proximal–distal continuum of adherence drivers. RESULTS: The average age was 58 years (range = 40–90 years), and 65% were female and 89% were white. Forty-one percent had at least a four-year college education, and just under half (45%) had an annual income of $50,000 or more. Hypertension and hyperlipidemia were each reported by about a quarter of respondents (24% and 23%, respectively). A smaller percentage of respondents had osteoporosis (17%), diabetes (15%), asthma (13%), or other cardiovascular disease (8%). Three independent variables were significantly associated with the three proximal adherence drivers: perceived disease severity, knowledge about the medication, and perceived value of nutraceuticals. Both perceived immunity to side effects and patient engagement was significantly associated with perceived need for medications and perceived medication concerns. CONCLUSION: Testing the proximal–distal continuum of adherence drivers shed light on specific areas where adherence dialogue and enhancement should focus. Our results can help to inform the design of future adherence interventions as well as the content of patient education materials and adherence reminder letters. For long-term medication adherence, patients need to autonomously and intrinsically commit to therapy and that, in turn, is more likely to occur if they are both informed (disease and medication knowledge and rationale, disease severity, consequences of nonadherence, and side effects) and motivated (engaged in their care, perceive a need for medication, and believe the benefits outweigh the risks).
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spelling pubmed-35085542012-11-30 Structural equation modeling of the proximal–distal continuum of adherence drivers McHorney, Colleen A Zhang, Ning Jackie Stump, Timothy Zhao, Xiaoquan Patient Prefer Adherence Original Research OBJECTIVES: Nonadherence to prescription medications has been shown to be significantly influenced by three key medication-specific beliefs: patients’ perceived need for the prescribed medication, their concerns about the prescribed medication, and perceived medication affordability. Structural equation modeling was used to test the predictors of these three proximal determinants of medication adherence using the proximal–distal continuum of adherence drivers as the organizing conceptual framework. METHODS: In Spring 2008, survey participants were selected from the Harris Interactive Chronic Illness Panel, an internet-based panel of hundreds of thousands of adults with chronic disease. Respondents were eligible for the survey if they were aged 40 years and older, resided in the US, and reported having at least one of six chronic diseases: asthma, diabetes, hyperlipidemia, hypertension, osteoporosis, or other cardiovascular disease. A final sample size of 1072 was achieved. The proximal medication beliefs were measured by three multi-item scales: perceived need for medications, perceived medication concerns, and perceived medication affordability. The intermediate sociomedical beliefs and skills included four multi-item scales: perceived disease severity, knowledge about the prescribed medication, perceived immunity to side effects, and perceived value of nutraceuticals. Generic health beliefs and skills consisted of patient engagement in their care, health information-seeking tendencies, internal health locus of control, a single-item measure of self-rated health, and general mental health. Structural equation modeling was used to model proximal–distal continuum of adherence drivers. RESULTS: The average age was 58 years (range = 40–90 years), and 65% were female and 89% were white. Forty-one percent had at least a four-year college education, and just under half (45%) had an annual income of $50,000 or more. Hypertension and hyperlipidemia were each reported by about a quarter of respondents (24% and 23%, respectively). A smaller percentage of respondents had osteoporosis (17%), diabetes (15%), asthma (13%), or other cardiovascular disease (8%). Three independent variables were significantly associated with the three proximal adherence drivers: perceived disease severity, knowledge about the medication, and perceived value of nutraceuticals. Both perceived immunity to side effects and patient engagement was significantly associated with perceived need for medications and perceived medication concerns. CONCLUSION: Testing the proximal–distal continuum of adherence drivers shed light on specific areas where adherence dialogue and enhancement should focus. Our results can help to inform the design of future adherence interventions as well as the content of patient education materials and adherence reminder letters. For long-term medication adherence, patients need to autonomously and intrinsically commit to therapy and that, in turn, is more likely to occur if they are both informed (disease and medication knowledge and rationale, disease severity, consequences of nonadherence, and side effects) and motivated (engaged in their care, perceive a need for medication, and believe the benefits outweigh the risks). Dove Medical Press 2012-11-09 /pmc/articles/PMC3508554/ /pubmed/23204839 http://dx.doi.org/10.2147/PPA.S36535 Text en © 2012 McHorney et al, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.
spellingShingle Original Research
McHorney, Colleen A
Zhang, Ning Jackie
Stump, Timothy
Zhao, Xiaoquan
Structural equation modeling of the proximal–distal continuum of adherence drivers
title Structural equation modeling of the proximal–distal continuum of adherence drivers
title_full Structural equation modeling of the proximal–distal continuum of adherence drivers
title_fullStr Structural equation modeling of the proximal–distal continuum of adherence drivers
title_full_unstemmed Structural equation modeling of the proximal–distal continuum of adherence drivers
title_short Structural equation modeling of the proximal–distal continuum of adherence drivers
title_sort structural equation modeling of the proximal–distal continuum of adherence drivers
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3508554/
https://www.ncbi.nlm.nih.gov/pubmed/23204839
http://dx.doi.org/10.2147/PPA.S36535
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