Literature DB >> 23218590

Adherence to and beliefs in lipid-lowering medical treatments: a structural equation modeling approach including the necessity-concern framework.

Erik Berglund1, Per Lytsy, Ragnar Westerling.   

Abstract

OBJECTIVE: This study attempts to identify a structure among patient-related factors that could predict treatment adherence in statin patients, especially with regards to the necessity-concern framework.
METHODS: 414 Swedish patients using statins completed a questionnaire about their health, treatment, locus of control, perception of necessity-concern and adherence. The data were handled using a structural equation modeling approach.
RESULTS: Patients that reported high perceptions of necessity to treatment seemed to adhere well, and side effects appear to affect adherence negatively. Disease burden, cardiovascular disease experience and high locus of control seem to have mediating effects on adherence.
CONCLUSION: This study provides support for the hypothesis that health- and treatment-related factors, as well as locus of control factors, are indirectly associated with treatment adherence via their association with mediating factor necessity. PRACTICE IMPLICATIONS: This study highlights the importance of considering patients' beliefs about medications, disease burden, experience of cardiovascular events and locus of control as these factors are associated with adherence behavior to statin treatment. This study also emphasizes more generally the importance of an approach targeting necessity and concern when communicating with and treating patients with lipid-lowering medication.
Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2012        PMID: 23218590     DOI: 10.1016/j.pec.2012.11.001

Source DB:  PubMed          Journal:  Patient Educ Couns        ISSN: 0738-3991


  30 in total

Review 1.  What are validated self-report adherence scales really measuring?: a systematic review.

Authors:  Thi-My-Uyen Nguyen; Adam La Caze; Neil Cottrell
Journal:  Br J Clin Pharmacol       Date:  2014-03       Impact factor: 4.335

2.  Comparison Between Statistical Model and Machine Learning Methods for Predicting the Risk of Renal Function Decline Using Routine Clinical Data in Health Screening.

Authors:  Xia Cao; Yanhui Lin; Binfang Yang; Ying Li; Jiansong Zhou
Journal:  Risk Manag Healthc Policy       Date:  2022-04-26

3.  The Influencing Contexts and Potential Mechanisms Behind the Use of Web-Based Self-management Support Interventions: Realistic Evaluation.

Authors:  Marscha Engelen; Betsie van Gaal; Hester Vermeulen; Rixt Zuidema; Sebastian Bredie; Sandra van Dulmen
Journal:  JMIR Hum Factors       Date:  2022-07-01

4.  Association of Patient Perceptions of Cardiovascular Risk and Beliefs on Statin Drugs With Racial Differences in Statin Use: Insights From the Patient and Provider Assessment of Lipid Management Registry.

Authors:  Michael G Nanna; Ann Marie Navar; Pearl Zakroysky; Qun Xiang; Anne C Goldberg; Jennifer Robinson; Veronique L Roger; Salim S Virani; Peter W F Wilson; Joseph Elassal; L Veronica Lee; Tracy Y Wang; Eric D Peterson
Journal:  JAMA Cardiol       Date:  2018-08-01       Impact factor: 14.676

5.  Associations Between Treatment Satisfaction, Medication Beliefs, and Adherence to Disease-Modifying Therapies in Patients with Multiple Sclerosis.

Authors:  Andrew V Thach; Carolyn M Brown; Vivian Herrera; Rahul Sasane; Jamie C Barner; Kentya C Ford; Kenneth A Lawson
Journal:  Int J MS Care       Date:  2018 Nov-Dec

6.  Lifestyle factors as predictors of nonadherence to statin therapy among patients with and without cardiovascular comorbidities.

Authors:  Heli Halava; Maarit Jaana Korhonen; Risto Huupponen; Soko Setoguchi; Jaana Pentti; Mika Kivimäki; Jussi Vahtera
Journal:  CMAJ       Date:  2014-06-23       Impact factor: 8.262

7.  Strategies for Primary Prevention of Coronary Heart Disease Based on Risk Stratification by the ACC/AHA Lipid Guidelines, ATP III Guidelines, Coronary Calcium Scoring, and C-Reactive Protein, and a Global Treat-All Strategy: A Comparative--Effectiveness Modeling Study.

Authors:  Benjamin Z Galper; Y Claire Wang; Andrew J Einstein
Journal:  PLoS One       Date:  2015-09-30       Impact factor: 3.240

Review 8.  Understanding patients' adherence-related beliefs about medicines prescribed for long-term conditions: a meta-analytic review of the Necessity-Concerns Framework.

Authors:  Rob Horne; Sarah C E Chapman; Rhian Parham; Nick Freemantle; Alastair Forbes; Vanessa Cooper
Journal:  PLoS One       Date:  2013-12-02       Impact factor: 3.240

9.  Adherence to Long-Term Therapies and Beliefs about Medications.

Authors:  Abdullah Alhewiti
Journal:  Int J Family Med       Date:  2014-02-13

10.  An Unbiased Machine Learning Exploration Reveals Gene Sets Predictive of Allograft Tolerance After Kidney Transplantation.

Authors:  Qiang Fu; Divyansh Agarwal; Kevin Deng; Rudy Matheson; Hongji Yang; Liang Wei; Qing Ran; Shaoping Deng; James F Markmann
Journal:  Front Immunol       Date:  2021-07-08       Impact factor: 7.561

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