Implementing Personalized Exercise Prescriptions Through Mobile Health in the Elderly Cancer Survivors
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Cancer remains a vital public health concern in the U.S. Research evidence has shown that physical activity provides many physical and mental health benefits after cancer diagnosis and plays an important role in reducing all-cause, cancer-related death and cancer events in the elderly cancer survivors (CS). Adopting a physically active lifestyle may decrease cancer risks, improve cancer prognosis and quality of life.
However, most CS did not achieve recommended 150 min/week of moderate-to- vigorous physical activity (PA [MVPA]). This issue is particularly pronounced for CS in low-income areas who tend to have considerably less access to PA-conducive environments compared to urban peers. To this accord, it is imperative to promote PA in elderly CS to offer appropriate supportive care. Thus, implementing innovative PA interventions with the goal of improving their self-regulatory health behaviors in CS is paramount.
Full description
Cancer remains a vital public health concern in the U.S. Research evidence has shown that physical activity provides many physical and mental health benefits after cancer diagnosis and plays an important role in reducing all-cause, cancer-related death and cancer events in the elderly cancer survivors (CS). Adopting a physically active lifestyle may decrease cancer risks, improve cancer prognosis and quality of life.
However, most CS did not achieve recommended 150 min/week of moderate-to- vigorous physical activity (PA [MVPA]). This issue is particularly pronounced for CS in low-income areas who tend to have considerably less access to PA-conducive environments compared to urban peers. To this accord, it is imperative to promote PA in elderly CS to offer appropriate supportive care. Thus, implementing innovative PA interventions with the goal of improving their self-regulatory health behaviors in CS is paramount.
One promising area of technology for increasing health behaviors is mobile health (m-health), which includes new technologies such as smartphone app, wearables, and social media in improving quality of healthcare. 6-8 Recently, researchers have applied such technologies to promote health through increased individual PA and reduced sedentary behavior in CS and some findings are promising. Despite positive findings, limitations of the preceding literature such as small samples, lacked personalized prescriptions, and lacked big data analysis are worth noting. Further, geographic environment not only affects individual's PA but is also an important pathway through which socio-economic inequalities create health disparities. Intervention impacts may be magnified in environments (e.g., urban vs. rural) stimulating more PA, with urban leading to higher PA than rural. According to Social Ecological Model, combined interventions yielded better outcomes than single level interventions. Yet, few studies examined interactive effects of the technologies on PA and other outcomes in CS, a major gap for advancing tailored intervention. In response, the primary aim of this project is to examine effects of combination of a personalized smartwatch and a Facebook health education intervention on CS' PA (daily steps) as compared to personalized Facebook only, personalized smartwatch only, and attention control conditions, over a 6-month period. This project will also determine the effects of the m-health interventions on CS' personal (e.g., daily calories, fitness, body composition, quality of life, and beliefs) and interpersonal (social support) health outcomes.
Empirical evidence also suggests a positive link between community participation and emotions (e.g., empathy and satisfaction), which may facilitate social support and subsequent sustained behavior in CS. Understanding the effect of social support and positive emotions on PA promotion is current lacking and necessary for us to explore a potential new type of intervention for healthcare outcome. With the advancement of technology, social media and apps focusing on promoting a healthy lifestyle have been increasingly used in cancer prevention and management. Further, a sentiment analysis of online patient-authored text, or retrieving information about a patient's perception, has the potential to offer new insights on the health impact of online social support and behavior, but such analysis generally requires manual annotations which can be time-consuming and costly for health professionals. To gain these new insights, health informatics approaches (e.g., text mining techniques and natural language processing [NLP] of large datasets, including sentiment analysis ) can be leveraged to examine the relationship between changes in emotions and health outcomes among online community members. This study also attempts to explore the relationships between patients' sentiments, smart watch data and other health outcomes across time.
This project attempts to examine innovative m-health interventions on CS's PA and health outcomes while offering personalized exercise prescriptions via big data analysis. If successful, it can significantly impact the development of effective and remote PA programs to promote health and protect diseases in CS. Moreover, its findings can guide health professionals and local communities to initiate such novel intervention programs with the goal of promoting PA and health in elderly CS, particularly during or post the pandemic.
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Inclusion criteria
- Have had one or more of the cancers of interest (i.e., breast, colon, bladder, prostate, endometrium, esophagus, lung, kidney & renal pelvis, stomach)
- Complete active cancer treatment at least three months prior to enrollment, with the exception of anti- hormonal therapy
- Possess an Android or Apple smartphone
- Having a Facebook account, or are willing to make one
- Engage in some type of physical activity (PA) as assessed by PA readiness survey.
Exclusion criteria
- Diagnosed with stage IV cancer
- Completed primary cancer treatment (e.g., surgery, radiotherapy) less than six months ago with new cancer diagnosis or recurrence
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126 participants in 4 patient groups
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Data sourced from clinicaltrials.gov
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