This clinical trial compares how well a home-based personalized physical activity program (PAP) that is delivered by a digital application (app) (the ExerciseRx app) works compared to health education in improving physical activity for patients with bladder cancer that has not reached the muscle wall of the bladder (non-muscle invasive). For people who are not physically active, previous studies have shown that increasing step counts can reduce incidence of death, reduce frailty, and reduce healthcare costs. The ExerciseRx app tracks adherence to home exercise, adapts step count goals based on the patient's progress, and provides encouraging feedback and motivation from the healthcare team. Additional features include activity summaries, progress towards current goal, nudges, helpful facts about the benefits of activity, and ideas for how to incorporate daily movement. A home-based PAP using the ExerciseRx app may work better in increasing physical activity among patients with non-muscle invasive bladder cancer compared to a health education only group.
Adults (age >= 18 years)
Prior diagnosis of non-muscle invasive bladder cancer (NMIBC), currently on surveillance or receiving maintenance intravesical therapy (including intravesical chemotherapy, immunotherapy)
Classified as insufficiently active on the Physical Activity as a Vital Sign (PAVS) assessment
Has an Android or Apple Smartphone/Tablet
Severe cognitive or memory impairment/dementia precluding ability to follow instructions or participate in survey assessments
Inability to read or understand English
Lack of access or lack of sufficient facility to use an Android or iOS smart device with the minimum criteria to run the ExerciseRx app
Not receiving treatment at University of Washington (UW)
Parallel
Internet-Based Intervention
Other interventionGiven access to the ExerciseRx app
Best Practice
Other interventionGiven instruction to continue physical activity as usual
Internet-Based Intervention
Other interventionGiven access to the ExerciseRx app locked to the baseline home screen
Exercise Intervention
Other interventionComplete home exercise sessions
Health Telemonitoring
Other interventionGiven a FitBit® to wear continuously
Educational Intervention
Other interventionGiven NCCN Survivorship for Healthy Living Guidelines pamphlet
Questionnaire Administration
Other interventionAncillary studies
Interview
Other interventionAncillary studies
Electronic Health Record Review
Other interventionAncillary studies
Change in mean daily step count
Average daily step count (per 24-hour day) will be assessed by the Fitbit tracker. Summary statistics (mean and standard deviations; counts and percentages) will be used to describe and compare baseline characteristics between the two treatment arms. Will use a linear mixed effects model with average daily step count as the outcome, with fixed effects for time (T1, T2, and T3), treatment assignment, and the week-treatment interaction, and a random intercept for each participant. A significant interaction between T2 and treatment assignment will indicate the change in step count from baseline to T2 differs between the two treatment arms and will be used to evaluate the co-primary outcomes of step-count improvement at the end of treatment using a two-sided significance level of 0.05. The minimum amount of time that participants need to have worn the Fitbit for their step data to be valid for use in analysis is one week (7 days) post baseline period.
Qualitative experience
Will be assessed by Zoom interviews (usability interview) with a subset of volunteer participants from the physical activity program (PAP) arm. Will analyze the semi-structured interview data using a process of reflexive thematic analysis, drawing on our reflexivity as designers, health informatics researchers, and clinical researchers to interpret data and construct themes using affinity analysis to identify ways in which ExerciseRx can be improved to meet the needs of patients with bladder cancer. Similarly, will apply the Discover Design Built Test framework from the University of Washington ALACRITY Center to adapt the ExerciseRx provider dashboard for healthcare providers caring for patients with bladder cancer.
Active time/24 hours (minutes) per week on study
A linear mixed effect model will be used to analyze the impact of the ExerciseRx platform comparing PAP to Health Education Group (HEG). Each model will include this outcome with fixed effects for time, treatment assignment, and the time-treatment interaction as well as a random effect for each participant to account for repeated measures. Significant interaction terms will indicate a treatment effect is present at that measurement time.
Change in mean daily step count
A linear mixed effect model will be used to analyze the impact of the ExerciseRx platform comparing PAP to HEG. Each model will include this outcome with fixed effects for time, treatment assignment, and the time-treatment interaction as well as a random effect for each participant to account for repeated measures. Significant interaction terms will indicate a treatment effect is present at that measurement time.
Change in functional mobility
Assessed by the Short Physical Performance Battery. A linear mixed effect model will be used to analyze the impact of the ExerciseRx platform comparing PAP to HEG. Each model will include this outcome with fixed effects for time, treatment assignment, and the time-treatment interaction as well as a random effect for each participant to account for repeated measures. Significant interaction terms will indicate a treatment effect is present at that measurement time.
Change in frailty
Assessed by the Cancer and Aging Research Group - Geriatric Assessment. A linear mixed effect model will be used to analyze the impact of the ExerciseRx platform comparing PAP to HEG. Each model will include this outcome with fixed effects for time, treatment assignment, and the time-treatment interaction as well as a random effect for each participant to account for repeated measures. Significant interaction terms will indicate a treatment effect is present at that measurement time.
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University of Washington
Lead sponsor
Andy Hill CARE Fund
Collaborator
