Identifying targets for cardiovascular medication adherence interventions through latent class analysis.


Objective: Reasons for nonadherence to cardiovascular medications vary widely between individuals. Yet, adherence interventions are often uniformly applied, limiting their effectiveness. This study employed latent class analysis (LCA) to identify multidimensional profiles of reasons for nonadherence to cardiovascular medications. Method: Participants (N = 137; MAge = 58.8, SDAge = 11.8) were drawn from an observational study of the impact of cardiac-induced posttraumatic stress disorder (PTSD) on cardiac medication adherence in patients presenting to the emergency department with a suspected acute coronary syndrome. Demographics and depressive symptoms were assessed at baseline. Extent of nonadherence to cardiovascular medications, reasons for nonadherence, and PTSD symptoms were assessed 1 month after discharge. Results: LCA identified 3 classes of reasons for medication nonadherence: capacity (related to routine or forgetting; approximately 45% of the sample), capacity + motivation (related to routine/forgetting plus informational or psychological barriers; approximately 14% of the sample), and no clear reasons (low probability of endorsing any items; approximately 41% of the sample). Participants reporting greater nonadherence were more likely to be in the capacity + motivation or no clear reasons classes compared with the capacity class. Participants endorsing higher PTSD severity were more likely to be in the capacity + motivation or capacity classes compared with the no clear reasons class. Conclusions: Three distinct classes of reasons for nonadherence were identified, suggesting opportunities for tailored interventions: capacity, capacity + motivation, and no clear reasons. These preliminary findings, if replicated, could aid identification of patients at risk for greater extent of medication nonadherence and inform tailored interventions to improve adherence. (PsycINFO Database Record (c) 2018 APA, all rights reserved)