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Concurrent and Predictive Validity of a Self-reported Measure of Medication Adherence

Morisky, Donald E., Green, Lawrence W., Levine, David M.·1986·Medical Care

Abstract

Adherence to the medical regimen continues to rank as a major clinical problem in the management of patients with essential hypertension, as in other conditions treated with drugs and life-style modification. This article reviews the psychometric properties and tests the concurrent and predictive validity of a structured four-item self-reported adherence measure (alpha reliability = 0.61), which can be easily integrated into the medical visit. Items in the scale address barriers to medication-taking and permit the health care provider to reinforce positive adherence behaviors. Data on patient adherence to the medical regimen were collected at the end of a formalized 18-month educational program. Blood pressure measurements were recorded throughout a 3-year follow-up period. Results showed the scale to demonstrate both concurrent and predictive validity with regard to blood pressure control at 2 years and 5 years, respectively. Seventy-five percent of the patients who scored high on the four-item scale at year 2 had their blood pressure under adequate control at year 5, compared with 47% under control at year 5 for those patients scoring low (P less than 0.01).

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Metadata

Authors
Morisky, D. E., Green, L. W., & Levine, D. M.
Venue
Medical Care
Published
1986-01
Volume
24
Issue
1
Pages
67-74
ISSN
0025-7079 (ISSN-L)
OpenAlex
W2031756259
Cited by
5,317
References
0
FWCI
4.19
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Concurrent and Predictive Validity of a Self-reported Measure of Medication Adherence. https://app.cochat.ai/papers/10.1097/00005650-198601000-00007
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Morisky, D. E., Green, L. W., & Levine, D. M. (1986). Concurrent and Predictive Validity of a Self-reported Measure of Medication Adherence. Medical Care. https://doi.org/10.1097/00005650-198601000-00007

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.