Korean J Psychopharmacol.  2010 Jan;21(1):29-34.

Predicting Factors Associated with Drug Compliance in Psychiatric Outpatients of a University Hospital

Affiliations
  • 1Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Korea. youngwoo@catholic.ac.kr

Abstract


OBJECTIVE
Drug compliance is closely related to progress and prognosis of psychiatric disease. We investigated drug compliance in psychiatric outpatients and factors that influence their compliance.
METHODS
Patients who visited a university hospital were asked about drug information and drug compliance using questionnaires. Medical records of the patients were reviewed. Demographic variables, clinical characteristics and drug compliance related variables were compared between non-compliance group and compliance group. Logistic regression analysis was performed to clarify predictors of poor compliance.
RESULTS
One hundred eighty one patients participate in this study. 150 patients (82.9%) were compliance group, 31 patients (17.1%) were included in non-compliance group. Patient-related, illness-related and treatment-related factors, DAI total score and knowledge of side effect did not show any difference in both groups. However, illness severity was relatively higher in non-compliance group (p = 0.070) and patient's satisfaction about explanation of side effect was lower in noncompliance group (p = 0.061). Moreover, patients who negatively answered for question about negative recognition to psychiatric medication in DAI questionnaire were more common in non-compliance group (p = 0.075). In logistic regression, answering negatively to question about negative recognition to psychiatric medication in DAI questionnaire was related to non-compliance, but did not reached statistical significance (p = 0.086).
CONCLUSION
This study suggests that improving negative recognition about psychiatric medication through drug education and good doctor patient relationship could enhance drug compliance.

Keyword

Drug compliance; Negative recognition; Outpatient

MeSH Terms

Compliance
Humans
Logistic Models
Medical Records
Outpatients
Prognosis
Surveys and Questionnaires
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