共同研究：長期薬を改善するためのマルチスケールモデリングと介入

Purpose/objective:

The investigators have created a new integrated medication monitoring (MM) system for long-term monitoring of medication adherence consisting of baseline, 3-month, and 6-month surveys, smartphone based ecological momentary assessment, smartphone sensors, a medication event monitoring system (MEMS; Wisepill) sensor, and a wrist-worn wearable sensor (Fitbit) that will be used to collect data to understand and model medication-taking behaviors. The objective of the project is to deploy this system to predict nonadherence to endocrine therapy for breast cancer survivors and implement intervention strategies to improve medication adherence. These interventions will be evaluated for preliminary impact on behavior, acceptability, attractiveness, and usefulness.

Overview:

The investigators will conduct a single arm study collecting data in multiple ways and multiple intervals, over six months' time: 1) baseline, 3-month, and 6-month surveys via Qualtrics; 2) smartphone-based ecological momentary assessment (via Digital Trails application) at the following intervals: every 2-3 days, weekly, and monthly; 3) wireless medication event monitoring system devices (MEMS; Wisepill; daily), 4) a wrist-worn wearable sensor (Fitbit; continuous); and 5) smartphone sensors (data collected via Digital Trails application, continuous). Participants will be provided personalized intervention content based on their specific risk via the Digital Trials app. Fifteen breast cancer survivors will be asked to participate in this longitudinal study for six months.

Intervention:

The investigators have created a new integrated medication monitoring (MM) system consisting of baseline, 3-month, and 6-month surveys, smartphone-based ecological momentary assessment via an application installed on a smartphone (Digital Trails based on the UVA Sensus app), a wireless medication event monitoring system device (MEMS; Wisepill), and a wearable sensor (Fitbit), and data collected passively from smartphone sensors using the Digital Trails app. These sources of information will be used to understand predictors of medication taking behaviors and, after two months of monitoring, to deploy appropriate interventions which will be delivered via the Digital Trails app platform. The objective of the project is to deploy this MM system to predict nonadherence to endocrine therapy for breast cancer survivors and implement intervention strategies to improve medication adherence (via Digital Trails). These interventions will be evaluated for preliminary impact on behavior, acceptability, attractiveness, and usefulness.

Participant Eligibility Criteria Fifteen breast cancer survivors will be included in the study if they: 1) are English-speaking and reading; 2) are between ages 21 and 70 years; 3) are diagnosed with stage 0-3 breast cancer in the past 5 years; 4) have completed all surgery, radiation, and chemotherapy, except endocrine therapy; 5) are prescribed endocrine therapy; 6) do not have a physical impairment that would prevent them from using the MM system; 7) are able to provide informed consent; 8) are willing and able to use the MM system for 6 months; and 9) have an Iphone or Android phone.

Participant Recruitment Using convenience sampling, the investigators will recruit 15 breast cancer survivors. The study will be publicized using a number of different ways, including ads on social media. Participants will be directed to complete an online screening survey via Qualtrics or to contact the study staff via email or phone. The investigators will contact interested participants and do a telephone or HIPAA-Zoom screening to assess study inclusion criteria, after obtaining informed consent. The investigators will then provide sensors to participants (via mail) and in a subsequent baseline data collection session (via Zoom), assist participants with completing baseline surveys via Qualtrics, in learning how to use the sensors, and in downloading and using smartphone applications. Participants will be asked to use two sensors: 1) a medication event monitoring system device (MEMS; Wisepill); and 2) a wrist-worn wearable sensor (Fitbit) daily for the next 6 months (see below). Participants will be asked to download the Fitbit and Digital Trails apps to their smartphones. Participants will also be asked to complete ecological momentary assessment (EMA; short surveys) using a smartphone app (Digital Trails) for six months.

Data Collection Digital Trails is an app that combines Sensus, a novel mobile sensing system for Android and iOS capable of collecting data from smartphone and Bluetooth-enabled sensors and administering EMAs, with a smartphone intervention. EMA surveys will be implemented at the following intervals: 1) randomly; 2) every 2- 3 days; 3) every 14 days; and 4) every 28 days. Digital Trails will also collect data from the participants' smartphone if authorized by the participant. These may include, but are not limited to, GPS, accelerometer, gyroscope, and pedometer data. Participants will complete 3 surveys via Qualtrics, at baseline, three month follow-up, and six-month follow-up. These surveys will be administered via Qualtrics. Participants will be asked to use two sensors daily for the entire six month period: 1) a Fitbit wrist sensor; and 2) a Wisepill MEMS cap. The investigators will use the Fitbit Sense smartwatch to collect data including steps, calories burned, total distance traveled, sleep, flights of stairs climbed, active minutes, exercise, and average heart rate. Participants will be asked to download the Fitbit app onto their personal smartphone. Participants' Fitabase data will be monitored by the study team using the Fitabase dashboard.

Primary Outcomes: Adherence to medication, receipt of intervention components, perception of intervention (thoughts, most useful components, lease useful components, most attractive components, least attractive components, problems with the intervention, suggested changes to intervention, additional information that should be provided by intervention, willingness to use intervention/system in future).

Planned analyses:

Evaluation of immediate response to delivery of each intervention module will consist of examining MM data that measure: 1) detection of a risk for missed medication; 2) delivery of the specific intervention module suggested by our modeling; and 3) whether the participant subsequently took the medicine as prescribed after the intervention module was deployed (within a 24 hour interval from the last dose plus or minus 6 hours). The investigators will also summarize data regarding participants' use of each type of module offered and their assessment of the acceptability, attractiveness, and usefulness of intervention modules used. Data collected from close-ended questions (i.e., use of an intervention module) will be summarized using descriptive data (i.e., counts and frequencies). Qualitative data collected from open-ended questions will be summarized using content analysis by having two raters code data on the three a priori themes (i.e., acceptability, attractiveness, and usefulness).