Publications

OBJECTIVE

Medication adherence is a complex behavior that is influenced by numerous factors. Applying self-efficacy theory, the primary aim of this randomized controlled trial was to compare medication self-efficacy among patients with coronary heart disease who received: (a) text messages (TMs) for medication reminders and education, (b) TMs for education, or (c) no TMs. The second aim was to identify the personal (sociodemographic and clinical characteristics) and psychosocial factors that were associated with and predicted medication adherence.

METHODS

Customized TMs were delivered over 30 days. Repeated measures analysis of variance was used to analyze medication self-efficacy. A multiple regression analysis was performed at baseline and follow-up to determine variables that were associated with and predicted self-reported medication adherence.

RESULTS

Among 90 subjects with mean age 59.2 years (standard deviation (SD) 9.4, range 35-83), total scores for medication self-efficacy improved over 30 days; however, there was no significant difference in this improvement as a function of the different treatment groups (p=0.64). Controlling for other variables in the model (age, education, depression, and social support), less depression (p=0.004) and higher social support (p=0.02) positively predicted higher medication adherence in the final model.

CONCLUSIONS

TM medication reminders and/or health education did not improve medication self-efficacy. Further theory testing of current and future models and interventions are required to understand variables related to self-efficacy and medication adherence. Addressing psychosocial factors such as depression and social support should be a priority to improve medication adherence among patients with coronary heart disease.

Specific bacterial species are implicated in the pathogenesis of exacerbations of chronic obstructive pulmonary disease (COPD). However, recent studies of clinically stable COPD patients have demonstrated a greater diversity of airway microbiota, whose role in acute exacerbations is unclear. In this study, temporal changes in the airway microbiome before, at the onset of, and after an acute exacerbation were examined in 60 sputum samples collected from subjects enrolled in a longitudinal study of bacterial infection in COPD. Microbiome composition and predicted functions were examined using 16S rRNA-based culture-independent profiling methods. Shifts in the abundance (≥ 2-fold, P < 0.05) of many taxa at exacerbation and after treatment were observed. Microbiota members that were increased at exacerbation were primarily of the Proteobacteria phylum, including nontypical COPD pathogens. Changes in the bacterial composition after treatment for an exacerbation differed significantly among the therapy regimens clinically prescribed (antibiotics only, oral corticosteroids only, or both). Treatment with antibiotics alone primarily decreased the abundance of Proteobacteria, with the prolonged suppression of some microbiota members being observed. In contrast, treatment with corticosteroids alone led to enrichment for Proteobacteria and members of other phyla. Predicted metagenomes of particular microbiota members involved in these compositional shifts indicated exacerbation-associated loss of functions involved in the synthesis of antimicrobial and anti-inflammatory products, alongside enrichment in functions related to pathogen-elicited inflammation. These trends reversed upon clinical recovery. Further larger studies will be necessary to determine whether specific compositional or functional changes detected in the airway microbiome could be useful indicators of exacerbation development or outcome.