Implementing Personalized Exercise Prescriptions Through Mobile Health in the Elderly Cancer Survivors
NCT ID: NCT05069519
Last Updated: 2022-12-23
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
126 participants
INTERVENTIONAL
2021-11-01
2022-10-30
Brief Summary
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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.
Detailed Description
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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.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
SUPPORTIVE_CARE
SINGLE
Study Groups
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Facebook Condition
Participants assigned to this intervention will take part in personalized Facebook health education, receive a smartwatch, receive weekly health education, share sentiments on Facebook, and receive personalized feedback.
Facebook Health Education
Participants assigned to this condition will receive a Fitbit smartwatch, continue with standard care, but will receive health education tips developed in the investigators' previous studies from a private Facebook group in which only group members and researchers can access. Additionally, the investigators will track login counts, analyze their post activity and online sentiments via texting mining and natural language processing, and then offer weekly personalized feedback based on the data to facilitate social support
Smartwatch Condition
Participants assigned to this intervention will use a Fitbit to track daily physical activity (PA), share PA data remotely, and receive personalized feedback.
Personalized Smartwatch
Participants will continue with standard care, but will receive a Fitbit and be encouraged to participate in at least 150 min. moderate-to-vigorous physical activity (5 sessions aerobic exercise, 30 min. per session; and 2 sessions of strength training) per week if their body condition allows throughout the intervention period. The previously established daily and weekly exercise prescription will be offered to participants based on their previous week Fitbit data.
PA improvements will be tailored over time based on each participant's previous week PA and they will be encouraged to increase PA by 5-10 min/week if possible depending on specific situations. Participants will save each workout and synchronize the Fitbit PA data to its app where they only share daily data and receive weekly personalized exercise prescriptions established in pilot studies.
Combined Condition
Participants assigned to this condition will receive both Fitbit and Facebook health education programs, (The Smartwatch and Facebook Conditions). The investigators will also provide weekly personalized feedback, based on PA data and sentiment analysis, that have been developed in prior pilot studies.
Personalized Smartwatch
Participants will continue with standard care, but will receive a Fitbit and be encouraged to participate in at least 150 min. moderate-to-vigorous physical activity (5 sessions aerobic exercise, 30 min. per session; and 2 sessions of strength training) per week if their body condition allows throughout the intervention period. The previously established daily and weekly exercise prescription will be offered to participants based on their previous week Fitbit data.
PA improvements will be tailored over time based on each participant's previous week PA and they will be encouraged to increase PA by 5-10 min/week if possible depending on specific situations. Participants will save each workout and synchronize the Fitbit PA data to its app where they only share daily data and receive weekly personalized exercise prescriptions established in pilot studies.
Facebook Health Education
Participants assigned to this condition will receive a Fitbit smartwatch, continue with standard care, but will receive health education tips developed in the investigators' previous studies from a private Facebook group in which only group members and researchers can access. Additionally, the investigators will track login counts, analyze their post activity and online sentiments via texting mining and natural language processing, and then offer weekly personalized feedback based on the data to facilitate social support
Attention Control
Participants assigned to the control condition will not receive any intervention. They will receive a Fitbit smartwatch, and continue with their standard care currently done in their life during the intervention period.
No interventions assigned to this group
Interventions
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Personalized Smartwatch
Participants will continue with standard care, but will receive a Fitbit and be encouraged to participate in at least 150 min. moderate-to-vigorous physical activity (5 sessions aerobic exercise, 30 min. per session; and 2 sessions of strength training) per week if their body condition allows throughout the intervention period. The previously established daily and weekly exercise prescription will be offered to participants based on their previous week Fitbit data.
PA improvements will be tailored over time based on each participant's previous week PA and they will be encouraged to increase PA by 5-10 min/week if possible depending on specific situations. Participants will save each workout and synchronize the Fitbit PA data to its app where they only share daily data and receive weekly personalized exercise prescriptions established in pilot studies.
Facebook Health Education
Participants assigned to this condition will receive a Fitbit smartwatch, continue with standard care, but will receive health education tips developed in the investigators' previous studies from a private Facebook group in which only group members and researchers can access. Additionally, the investigators will track login counts, analyze their post activity and online sentiments via texting mining and natural language processing, and then offer weekly personalized feedback based on the data to facilitate social support
Eligibility Criteria
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Inclusion Criteria
* 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
* Completed primary cancer treatment (e.g., surgery, radiotherapy) less than six months ago with new cancer diagnosis or recurrence
50 Years
ALL
No
Sponsors
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University of Minnesota
OTHER
Responsible Party
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Principal Investigators
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Zan Gao
Role: PRINCIPAL_INVESTIGATOR
University of Minnesota School of Kinesiology
Locations
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University of Minnesota
Minneapolis, Minnesota, United States
Countries
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Other Identifiers
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2021LS024
Identifier Type: -
Identifier Source: org_study_id