Abstract
The purpose of this study is to evaluate the role of persuasive technology in home-based medication adherence in a cardiovascular disease patient population. Cardiovascular disease is the leading cause of death in the United States (Mozaffarian et al., 2015), which is why prevention is increasingly important in this national epidemic. Several medical conditions put people at a higher risk for developing cardiovascular disease, such as diabetes, obesity, hypertension, and hyperlipidemia (Mozaffarian et al., 2015). Because of the numerous co-morbidities that accompany heart disease, patients frequently are tasked with taking several different medications to treat these conditions, which can lead to issues related to medication non-compliance. Research studies show that medication compliance is directly linked to improved patient outcomes (Ho et al., 2009). For example, one study with self-reported measures of medication compliance showed that non-adherent patients had nearly double the cardiovascular events compared to adherent patients and independently predicted adverse cardiovascular events (Gehi et al., 2007). A literature search was conducted to learn more about the many contributing factors leading to medication non-adherence, and to gather data on current methods of measuring and increasing medication adherence. This information was useful in informing our decisions to develop a preliminary survey on potential technology p reference for medication adherence for cardiac patients. The survey was administered to twenty patients at the University of Maryland Medical Center. All patients had a history of either cardiovascular disease resulting in revascularization, myocardial infarction, and/or stroke. This survey, which was given to patients with the aim of learning about current behaviors, current technology use, and desires for technology to manage their medication and disease, will eventually be used to tailor a non-invasive technology intervention (in the form of an audio-visual reminder or a similar system) for this population. We predict that those with the technology will have improved outcomes of medication adherence and a better quality of life. We hope to also develop a set of human-computer interaction guidelines that will render the technology more usable to the specific population.
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