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Self-efficacy is a strong predictor of compliance in the medical intervention literature, predicting medication adherence and smoking and alcohol avoidance (Schweitzer et al 2007).
The TMLE, in this application, relies on 1) a multinomial logistic regression model for predicting medication adherence given potential confounders and number of consecutive months virally suppressed and 2) a logistic regression model for the probability of virologic failure given adherence, confounders, and number of consecutive months virally suppressed.
Genetic markers predicting medication response, if found, would potentially be clinically useful.
MAPE, mean absolute prediction error; MAPE*, MAPE divided by the mean of cost As shown in Table 4, the Rx-MGs models also performed better than the diagnosis-based models for predicting medication cost concurrently and prospectively.
But, unlike the results of the total cost prediction models, the ADGs models had a lower predictive R-squares and a higher MAPE rate than the model adjusted by Elixhauser's index for predicting medication cost.
The objectives were to determine: 1) how the information from uniocular and binocular trials can best be used to determine medication effectiveness, and 2) whether uniocular and binocular trials are equally successful at predicting medication effectiveness.
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Although illness perceptions have been theorized to predict medication adherence, evidence has been limited to cross-sectional studies.
To further refine a measure of self-management, the Responsibility and Familiarity with Illness Survey (REFILS), and to determine if this score predicts medication adherence and, thus, fewer instances of allograft rejection among pediatric liver transplant recipients.
In the original study, it was shown that HSLC predicts medication consumption, psychological consequences of headache episodes (e.g. depression and headache-related disability) and preference for treatment modality even when controlling for headache severity (frequency and intensity) in a sample of college students with recurrent headaches [5].
A variety of factors may predict medication adherence among HIV-infected adults.
In our study, we identified one modifiable variable in the multiple regression model that predict medication adherence.
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