App-Assisted Day Reconstruction to Reduce Logistic Toxicity in Cancer

Completed

Brief Summary: The number of new cases of cancer diagnosed in the U.S. was 1.7 million in 2017 and is expected to increase by 35% to 2.3 million in 2030\[1\]. Cancer treatments often create numerous logistic challenges in prioritizing and managing treatment and everyday life priorities and how these challenges affect their everyday lives and well-being (hence "logistic toxicity"). However, there are no established reliable tools to monitor patients' logistic challenges and the associated impacts; and logistic toxicity has been largely unaddressed in cancer care delivery. The objective is to develop the first digital health app for cancer patients to continuously monitor logistic toxicity in their daily lives. The app will combine objective data from mobile sensing with subjective self-reported data to form an app-assisted day reconstruction system that captures activity engagement and well-being information associated with cancer treatment-related activities and trips throughout the day.

Detailed Description: The proposed patient monitoring app that captures logistic toxicity information on an ongoing basis will empower patients to advocate for care that better fits their life, give providers new insights into potential reasons for treatment non-adherence and nonresponse, and allow health systems to design more patient-centered care regimens.

A participatory design approach will be used to inform the design of our system, performing in-depth interviews and follow-up surveys with 20 diverse patients undergoing treatment for cancer. Patients will supply examples of logistic toxicity and how they would like to measure and communicate logistic toxicity across scenarios. Follow-up surveys will ask participants to provide satisfaction ratings towards user interface sketches and app function narratives.

Recruitment & Eligibility

Inclusion Criteria

18 years of age, currently receiving treatment for cancer, able to read/write/speak in English, and able to provide voluntary informed consent.

Exclusion Criteria

Those who are currently incarcerated or have opted out of research contact within M Health Fairview system.

Primary Outcome Measures

Name	Time	Method
Interviews	7 months	Number of Interviews completed to help identify themes to develop a cancer-specific, multi-tiered activity/trip classification system to organize cancer treatment-related activities and trips in the app; and user stories to describe what the users want to do with the proposed app. 45-minute interviews.
Satisfaction Score Follow-Up Survey	7 months	Participants with overall satisfaction with proposed system design will be measured using a 5-point Likert scale from not at all satisfied to very satisfied. The primary endpoint will be the proportion of participants who report an overall satisfaction score of 4.0 or above. 10-Minutes.

Secondary Outcome Measures