Drug attitude and other predictors of medication adherence in schizophrenia: 12 months of electronic monitoring (MEMS(®)) in the Swedish COAST-study.

The aim was to investigate clinical predictors of adherence to antipsychotics. Medication use was electronically monitored with a Medication Event Monitoring System (MEMS(®)) for 12 months in 112 outpatients with schizophrenia and schizophrenia-like psychosis according to DSM-IV. Symptom burden, ins...

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Main Authors: Brain, C, Allerby, K, Sameby, B, Quinlan, P, Joas, E, Karilampi, U, Lindström, E, Eberhard, J, Burns, T, Waern, M
Format: Journal article
Language:English
Published: 2013
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author Brain, C
Allerby, K
Sameby, B
Quinlan, P
Joas, E
Karilampi, U
Lindström, E
Eberhard, J
Burns, T
Waern, M
author_facet Brain, C
Allerby, K
Sameby, B
Quinlan, P
Joas, E
Karilampi, U
Lindström, E
Eberhard, J
Burns, T
Waern, M
author_sort Brain, C
collection OXFORD
description The aim was to investigate clinical predictors of adherence to antipsychotics. Medication use was electronically monitored with a Medication Event Monitoring System (MEMS(®)) for 12 months in 112 outpatients with schizophrenia and schizophrenia-like psychosis according to DSM-IV. Symptom burden, insight, psychosocial function (PSP) and side effects were rated at baseline. A comprehensive neuropsychological test battery was administered and a global composite score was calculated. The Drug Attitude Inventory (DAI-10) was filled in. A slightly modified DAI-10 version for informants was distributed as a postal questionnaire. Non-adherence (MEMS(®) adherence ≤0.80) was observed in 27%. In univariate regression models low scores on DAI-10 and DAI-10 informant, higher positive symptom burden, poor function, psychiatric side effects and lack of insight predicted non-adherence. No association was observed with global cognitive function. In multivariate regression models, low patient-rated DAI-10 and PSP scores emerged as predictors of non-adherence. A ROC analysis showed that DAI-10 had a moderate ability to correctly identify non-adherent patients (AUC=0.73, p<0.001). At the most "optimal" cut-off of 4, one-third of the adherent would falsely be identified as non-adherent. A somewhat larger AUC (0.78, p<0.001) was observed when the ROC procedure was applied to the final regression model including DAI-10 and PSP. For the subgroup with informant data, the AUC for the DAI-10 informant version was 0.68 (p=0.021). Non-adherence cannot be properly predicted in the clinical setting on the basis of these instruments alone. The DAI-10 informant questionnaire needs further testing.
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spelling oxford-uuid:4992d159-a4d1-49e9-b8f7-7852fdc1dab92022-03-26T15:32:27ZDrug attitude and other predictors of medication adherence in schizophrenia: 12 months of electronic monitoring (MEMS(®)) in the Swedish COAST-study.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:4992d159-a4d1-49e9-b8f7-7852fdc1dab9EnglishSymplectic Elements at Oxford2013Brain, CAllerby, KSameby, BQuinlan, PJoas, EKarilampi, ULindström, EEberhard, JBurns, TWaern, MThe aim was to investigate clinical predictors of adherence to antipsychotics. Medication use was electronically monitored with a Medication Event Monitoring System (MEMS(®)) for 12 months in 112 outpatients with schizophrenia and schizophrenia-like psychosis according to DSM-IV. Symptom burden, insight, psychosocial function (PSP) and side effects were rated at baseline. A comprehensive neuropsychological test battery was administered and a global composite score was calculated. The Drug Attitude Inventory (DAI-10) was filled in. A slightly modified DAI-10 version for informants was distributed as a postal questionnaire. Non-adherence (MEMS(®) adherence ≤0.80) was observed in 27%. In univariate regression models low scores on DAI-10 and DAI-10 informant, higher positive symptom burden, poor function, psychiatric side effects and lack of insight predicted non-adherence. No association was observed with global cognitive function. In multivariate regression models, low patient-rated DAI-10 and PSP scores emerged as predictors of non-adherence. A ROC analysis showed that DAI-10 had a moderate ability to correctly identify non-adherent patients (AUC=0.73, p<0.001). At the most "optimal" cut-off of 4, one-third of the adherent would falsely be identified as non-adherent. A somewhat larger AUC (0.78, p<0.001) was observed when the ROC procedure was applied to the final regression model including DAI-10 and PSP. For the subgroup with informant data, the AUC for the DAI-10 informant version was 0.68 (p=0.021). Non-adherence cannot be properly predicted in the clinical setting on the basis of these instruments alone. The DAI-10 informant questionnaire needs further testing.
spellingShingle Brain, C
Allerby, K
Sameby, B
Quinlan, P
Joas, E
Karilampi, U
Lindström, E
Eberhard, J
Burns, T
Waern, M
Drug attitude and other predictors of medication adherence in schizophrenia: 12 months of electronic monitoring (MEMS(®)) in the Swedish COAST-study.
title Drug attitude and other predictors of medication adherence in schizophrenia: 12 months of electronic monitoring (MEMS(®)) in the Swedish COAST-study.
title_full Drug attitude and other predictors of medication adherence in schizophrenia: 12 months of electronic monitoring (MEMS(®)) in the Swedish COAST-study.
title_fullStr Drug attitude and other predictors of medication adherence in schizophrenia: 12 months of electronic monitoring (MEMS(®)) in the Swedish COAST-study.
title_full_unstemmed Drug attitude and other predictors of medication adherence in schizophrenia: 12 months of electronic monitoring (MEMS(®)) in the Swedish COAST-study.
title_short Drug attitude and other predictors of medication adherence in schizophrenia: 12 months of electronic monitoring (MEMS(®)) in the Swedish COAST-study.
title_sort drug attitude and other predictors of medication adherence in schizophrenia 12 months of electronic monitoring mems r in the swedish coast study
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