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Decisional Balance among Potential Implantable Cardioverter Defibrillator Recipients: Development of the ICD-Decision Analysis Scale (ICD-DAS)
Decisional Balance among Potential Implantable Cardioverter Defibrillator Recipients: Development of the ICD-Decision Analysis Scale (ICD-DAS) PACE-PACING AND CLINICAL ELECTROPHYSIOLOGY Hazelton, A. G., Sears, S. F., Ford, J., Cahill, J., Nekkanti, R., DeAntonio, H., Ottoboni, L., Norton, L., Wang, P. 2014; 37 (1): 63-72Abstract
Sudden cardiac death is a well-documented public health problem and the implantable cardioverter defibrillator (ICD) has demonstrated benefit in reducing mortality. Prospective patients must identify and evaluate the ICD's pros and cons and produce a personal decision. The purpose of this study was to create and evaluate a measure of patient-evaluated pros and cons of the ICD, and its relationship to patient decision regarding ICD implantation.The ICD-decision analysis scale (ICD-DAS) was created and tested in prospective ICD recipients (N = 104). Factor analysis was performed to evaluate interitem relationships, and subsequently, identified subscales; additional psychosocial measures were used to predict the ICD decision. A two-factor measure for ICD decision making was established with two subscales: ICD Pros and ICD Cons. The subscales have high internal consistency and were strong predictors of intent to choose an ICD. Other psychosocial measures were not significantly predictive of ICD Choice, yet simultaneous entry of ICD Pros and Cons subscales resulted in a significant increase in R(2) , F(2, 59) = 19.36, P < 0.001. The full model was significantly greater than zero, F(11, 70) = 5.017, P < 0.001, R(2) = 0.48.The ICD-DAS provides the first empirically tested and clinically useful approach to understanding the specific pros and cons for prospective ICD patients. The measure can assist clinicians with patient-centered discussions regarding sudden cardiac arrest treatments. The ICD-DAS will allow for the provision of tailored education or counseling and may be used to predict postdecision outcomes.
View details for DOI 10.1111/pace.12253
View details for Web of Science ID 000329258600008
View details for PubMedID 24219117