By 2022, there will be nearly 4 million breast cancer survivors in the USA. Adherence to long-term endocrine therapy is crucial for survivors of hormone receptor-positive breast cancer prescribed these daily medications to prevent cancer recurrence. Despite the life-saving benefits of these medications, rates of adherence are low. Medication-taking behavior is simultaneously influenced by multiscale factors, including personal and environmental factors, and a patient's other behavioral patterns. Despite advances in smart and connected health, there have been few attempts to develop and deliver personalized interventions for medication adherence. Existing technology-based interventions focus on cognitive reasons for non-adherence to medications experienced by some people (e.g., forgetting), but fail to account for interactions between cognitive factors and other types of factors (i.e., environmental, behavioral) that contribute to adherence. Furthermore, few technology-driven interventions have been assessed for efficacy in supporting medication adherence. Tools to understand interactions between multiscale factors and the effect that personalized interventions have on these factors would ultimately improve medication adherence. This 3-phase project will overcome these fundamental scientific barriers by developing and employing a Multiscale Modeling and Intervention (MMI) system. First, a system consisting of sensor-rich smartphones, wireless medication event monitoring systems (MEMS), wireless beacons, and wearable sensors that collect in situ data on medication adherence, will be developed to provide continuous, noninvasive adherence assessment and multiscale monitoring of factors. Second, the MMI system will be deployed to breast cancer survivors to model relationships between adherence and multiscale factors, identify patterns associated with medication-taking behavior, and develop interventions. Third, a proof-of-concept for MMI will be demonstrated through a human subjects study, with subjects receiving multiscale interventions. The proposed research has significant public health implications as it is expected to increase our understanding of medication adherence in breast cancer survivors, thus providing a general framework that will be applicable to oral chemotherapy use across multiple cancers.
Adherence to long-term endocrine therapy is crucial for survivors of hormone receptor-positive breast cancer prescribed these daily medications to prevent cancer recurrence. However, rates of adherence to these are low. This proposed work is the first to develop technology-driven dynamic modeling and intervention of medication adherence focusing on the links between environmental, personal, and behavioral contexts of medication-taking behavior.