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Patient Prefer Adher · Jan 2017
The prevalence of medication nonadherence in post-myocardial infarction survivors and its perceived barriers and psychological correlates: a cross-sectional study in a cardiac health facility in Malaysia.
- Kurubaran Ganasegeran and Abdul Rashid.
- Department of Public Health Medicine, Penang Medical College, George Town, Malaysia.
- Patient Prefer Adher. 2017 Jan 1; 11: 1975-1985.
BackgroundAlthough evidence-based practice has shown the benefits of prescribed cardioprotective drugs in post-myocardial infarction (MI) survivors, adherence rates remain suboptimal. The aim of this study was to determine the prevalence and factors associated with medication nonadherence among post-MI survivors in Malaysia.Materials And MethodsThis cross-sectional study was conducted from February to September 2016 among 242 post-MI survivors aged 24-96 years at the cardiology outpatient clinic in a Malaysian cardiac specialist center. The study utilized an interviewer-administered questionnaire that consisted of items adapted and modified from the validated Simplified Medication Adherence Questionnaire, sociodemographics, health factors, perceived barriers, and novel psychological attributes, which employed the modified Confusion, Hubbub, and Order Scale and the Verbal Denial in Myocardial Infarction questionnaire.ResultsThe prevalence of medication nonadherence was 74%. In the multivariable model, denial of illness (AOR 1.2, 95% CI 0.9-1.8; P=0.032), preference to traditional medicine (AOR 8.7, 95% CI 1.1-31.7; P=0.044), lack of information about illness (AOR 3.3, 95% CI 1.1-10.6; P=0.045), fear of side effects (AOR 6.4, 95% CI 2.5-16.6; P<0.001), and complex regimen (AOR 5.2, 95% CI 1.9-14.2; P=0.001) were statistically significant variables associated with medication nonadherence.ConclusionThe relatively higher medication-nonadherence rate in this study was associated with patient-, provider-, and therapy-related factors and the novel psychological attribute denial of illness. Future research should explore these factors using robust methodological techniques to determine temporality among these factors.
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