| Epidemiological |
Monitoring and assessing PA
How does activity change over the course of cancer treatment? How do activity patterns change in a specified time period (i.e., 6 months, 1 year) following treatment? How do PA patterns change in a specified time period (i.e., 6 months, 3 months) before cancer diagnosis? Is physical inactivity in issues for a specific individual, population or subgroup? Understanding context and correlates of PA
What behavioral, psychosocial, or clinical factors influence changes in PA? Do activity patterns vary by treatment type (i.e., surgery, chemotherapy, radiation, hormonal therapy) and/or dose? Do activity pattern changes vary by disease characteristics (i.e., stage, time since diagnosis, recurrence status)? Are activity pattern changes related to patient reported outcomes (i.e., fatigue, depression) or motivational factors (i.e., self-efficacy, outcome expectations)? Understanding individual disease trajectories
Are PA patterns related to cancer diagnosis in high-risk groups? Are PA pattern changes prior to, during, or following treatment indicative of worse treatment outcomes? Are PA pattern changes prior to, during, or post treatment related to disease recurrence? Can PA pattern changes predict hospitalizations or other adverse events? Are PA pattern changes at specified time period predictive of functional outcomes, persistence of negative side effects, or disease prognosis? Are PA pattern changes related to treatment adherence, tolerance, or efficacy?
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If integrated into EHR, ability to “Flag” high-risk patients for additional observation, testing or clinical or behavioral intervention to promote PA. Individuals who are meeting PA could also be indicated to reinforce behavior or indicate other risk factors may be a greater priority. More personalized treatment decisions. More accurate predictions of treatment side effects or outcomes. More accurate prediction of disease prognosis. Targeted interventions could be developed/delivered to those at highest risk. Specific factors that may impact PA (i.e., fatigue, depression) could be identified and treated.
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| PA promotion |
Does giving a high-risk individual a wearable device prevent or delay disease onset? Could wearable PA data be used to predict cancer diagnosis prior to onset of clinical symptoms? Does giving cancer patients undergoing treatment wearables devices reduce typically observed activity decline? Does giving cancer patients undergoing treatment wearable devices improve their health outcomes? What is the optimal timing to give a patient a wearable device? Does a wearable device impact PA participation long-term?
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Wearable devices could be given to high-risk individuals to help them maintain or increase PA. Wearables could be given to cancer patients to help them maintain or increase their PA depending on treatment time point. Data from wearables could be integrated into patient charts so clinicians could follow-up with them and check-in on their progress.
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