Participation in regular physical activity is vital to a healthy lifestyle. Research has shown that regular participation in physical activity among cancer survivors is not only able to improve health outcomes, but is also related to their quality of life. As we live in an age of technology, health wearables and smartphone apps might be one novel manner by which to help cancer survivors increase physical activity as well as improve health outcomes. Yet, the effectiveness of wearable and app as a tool for health promotion among cancer survivors is largely unstudied. The purpose of this study is to evaluate the effectiveness of a personalized m-health intervention via fitness wearable (Fitbit Inspire 3) exercise app (sFitRx) on physical activity, weight, quality of life, individual beliefs, and emotions among cancer survivors.
Cancer remains a vital public health concern in the U.S. Research has shown that physical activity (PA) provides many physical and mental health benefits after cancer diagnosis and plays an important role in reducing all-cause and cancer-related mortality, as well as cancer incidence, in cancer survivors (CS). Adopting a physically active lifestyle is therefore crucial to decrease cancer risk and improve cancer prognosis and quality of life. However, most CS do not achieve the recommended 150 min/week of moderate-to-vigorous PA (MVPA). This issue is particularly pronounced for CS in low-income, underserved areas who tend to have considerably less access to PA-conducive environments compared to their more affluent peers. It is therefore imperative to study innovative, ease-to-implement health interventions CS that can promote increased engagement and self-regulation of health behaviors, such as PA, while also improving other health outcomes; thereby offering better supportive care. One promising easy-to-implement medium to improve engagement in and self-regulation of health behaviors is mobile health (mHealth), which includes advanced smartphone application technology often combined with wearables and social media to improve the healthcare delivery experience. Researchers have recently applied such technologies with CS to promote improved health through increased PA and reduced sedentary behavior (SB), with observations promising. Despite promising observations, these studies were often conducted with small samples over short durations (less than or equal to three months), with the interventions lacking personalized PA prescriptions informed by back end big data analysis techniques to further improve intervention implementation. As such, examining how a longer-term tailored, big data-informed mHealth PA intervention in CS might improve health and well-being would fill a major literature gap. The investigators thus propose a 12-month randomized-controlled trial to investigate how an mHealth-delivered PA intervention informed by big data analysis (hereafter, 'personalized mHealth intervention') can improve the health and well-being of CS over a 12-month period. Experimental Group participants would receive access to a study-developed mHealth application, sFitRx, that delivers personalized PA programming as well as be provided with a fitness tracker to monitor their habitual PA levels. Comparison Group participants would receive the fitness tracker only. Successful study completion will inform the development of effective, mHealth-delivered PA programs in CS that might guide health professionals in the initiation of such novel programs in lower-income communities with the goal of promoting PA and health in this population.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Enrollment
160
Experimental Group - Will receive a personalized mHealth application and fitness tracker. Specifically, Experimental Group participants will receive the sFitRx smartphone application that provides weekly personalized PA interventions informed by big data analysis. They will also receive a Fitbit Inspire 3 to track real-time PA, with PA data uploaded to Fitabase. Importantly, the PA data from the Fitbit Inspire 3 will inform the big data analyses used to generate the personalized PA intervention provided by the sFitRx application.
Comparison Group - Will receive the Fitbit Inspire 3 only.
University of Tennessee Medical Center
Knoxville, Tennessee, United States
RECRUITINGPhysical Activity
Physical Activity. CS's mean steps/day will be the primary outcome and will be assessed using Fitbit Inspire. Participants will be instructed to wear the Fitbit on the non-dominant wrist at all times throughout the study.
Time frame: Baseline (i.e., pre-intervention), six months, and 12 months.
Health Indicators
Participants' height (m) and weight (kg) will be measured at home by themselves, with body mass index (BMI) calculated by their height and weight (kg/m\^2).43
Time frame: Baseline (i.e., pre-intervention), six months, and 12 months.
Health Indicators
Psychosocial beliefs (e.g., self-efficacy, social support) will be assessed by standardized self-report surveys through established questionnaires.45-50
Time frame: Baseline (i.e., pre-intervention), six months, and 12 months.
Health Indicators
The investigators will assess quality of life (QoL) using the Patient Reported Outcome Measurement Information System44. Investigators are most interested in assessing physical functioning, anxiety, and depression.
Time frame: Baseline (i.e., pre-intervention), six months, and 12 months.
Physical Activity
Mean calories burned/day and SB/day will also be examined as a secondary outcome. As mentioned previously, investigators will retrieve Fitbit data via Fitabase.40-42
Time frame: Baseline (i.e., pre-intervention), six months, and 12 months.
Health Indicators
The researchers will assess participants emotions via the Positive and Negative Affect Scale.
Time frame: Baseline (i.e., pre-intervention), six months, and 12 months.
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