Objectives: Adherence to psychotropic medication is poor among individuals with bipolar disorder (BD). To understand treatment experiences and associated adherence among these individuals, we developed a novel construct of Clinical Net Benefit (CNB) using psychiatric symptoms, adverse effects and overall functioning assessments. We tested whether adherence differed across classes of CNB, whether individuals transitioned between classes over time, and whether these transitions were differentially associated with adherence.
Methods: Data come from individuals aged 18+ during five years of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Latent class analysis identified groups of CNB. Latent transition analysis determined probabilities of transitioning between classes over time. Adherence was defined as taking 75%+ of medications as prescribed. Associations between CNB and adherence were tested using multiple logistic regression adjusting for sociodemographic characteristics.
Results: Five classes of CNB were identified during the first two years (high, moderately high, moderate, moderately low, low), and four classes (removing moderately high) during the last three years. Adherence did not differ across classes or time points. Medication regimens differed by class; those with higher CNB taking fewer medications had lower odds of adherence while those with lower CNB taking more medications had higher odds of adherence compared with monotherapy. Probability of transitioning from higher to lower CNB, and lower to higher CNB was greatest over time.
Conclusions: CNB is heterogeneous in individuals treated for BD, and movement between classes is not uncommon. Understanding why individuals adhere despite suboptimal CNB may provide novel insights into aspects influencing adherence.
Identifer | oai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-5793 |
Date | 01 January 2017 |
Creators | Bareis, Natalie |
Publisher | VCU Scholars Compass |
Source Sets | Virginia Commonwealth University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses and Dissertations |
Rights | © The Author |
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