Literature DB >> 20678768

Illness perceptions and adherence to therapeutic regimens among patients with hypertension: a structural modeling approach.

Shiah-Lian Chen1, Jen-Chen Tsai, Kuei-Ru Chou.   

Abstract

BACKGROUND: Patients' lay views of illness are influential on adherence to therapeutic regimes. However, factors associate with non-adherence are not examined simultaneously.
OBJECTIVES: The purpose of the study was to test a hypothetical model of the relationships between illness perception and adherence to prescribed medication and self-management recommendations of hypertensive patients based on theoretical assumptions of the Common-Sense Model.
DESIGN: A cross-sectional, descriptive, correlational design. SETTINGS: Cardiovascular clinics of three teaching hospitals in central Taiwan. PARTICIPANTS: Three hundred and fifty-five hypertensive patients.
METHODS: Data were collected through face-to-face interviews using structured questionnaires, including the Illness Perception Questionnaire-Revised, the Medication Adherence Inventory, and the Inventory of Adherence to Self-Management. Data were analyzed by structural equation modeling using LISREL.
RESULTS: The findings suggested that the illness identity may directly affect patient adherence to prescribed medications or indirectly affect patient adherence via control of the disease and cause. Control of the disease exhibited direct effects on adherence to prescribed medications and self-management, while the cause of the illness only showed direct effects on adherence to prescribed medications. The relationships were independent of systolic blood pressure, age, the total number of antihypertensive medication, and comorbidity.
CONCLUSIONS: The findings of the study extend the utility of the Common-Sense Model, suggesting that adherence to therapeutic regimens may be enhanced by improving a sense of controllability. For patients who experience symptoms related to high blood pressure, barriers to adherence may be reduced by assessing and clarifying the meaning of illness identity and causal attributions.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20678768     DOI: 10.1016/j.ijnurstu.2010.07.005

Source DB:  PubMed          Journal:  Int J Nurs Stud        ISSN: 0020-7489            Impact factor:   5.837


  19 in total

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