An Engagement Engine for Fitness Trackers

Study Overview
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Brief Summary
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The iTrackFitness study aims to test the engagement engine that was developed from activity tracker and survey data gathered during phase I of the study. For the current phase the engagement engine will support successful and sustained engagement with health trackers thereby increasing physical activity.

Detailed Description
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Due to the growing interest in tracking personal health and wellness information, the use of wearable fitness trackers is becoming a necessary tool in providing the tracking data. However, the potential benefits of the tool can be fully realized only if the adoption and use of the tracker is sustained. The decision to engage in physical activity (or not) is complex, and therefore, the investigators attempt to engage people in a physical activity program will consider adopting an individualized approach to barrier management which takes into account personal beliefs and perceptions regarding physical activity, setting goals in addition to using an engagement engine designed specifically for this study. The primary objective of the phase 2 of this study is to test an engagement engine that will support successful and sustained engagement with health trackers thereby increasing physical activity. The study will be recruiting a total of 138 participants from the general public via Massachusetts General Hospital (MGH) research broadcast e-serve list, the study website, flyers and study informational tables at MGH-affiliated health clinics. Participants can enroll in the study by consenting remotely where the screening and consenting will take place online through the study website. After the consenting process, enrolled participants will be instructed on how to download the FitBit smartphone application and provide the study staff authorization to collect step data from their tracker. The enrollment process will involve completing a set of enrollment questions related to general health, barriers to physical activity, exercise regulation, Prochaska's stage of change, demographics and technology use via a web link on the study website. Next a research analyst will mail a copy of the consent form, wearable activity tracker (Fitbit Charge) and device instructions via traceable mail to the research participants. For participants who enroll from the informational tables, the research analyst will provide them the FitBit in person. Once confirmed that participants have received their device, the participant will be contacted by the Partners Connected Health (PCH) study staff to conduct a brief phone interview to determine a personalized goal that can be used for targeted, personalized messages as needed. Participants will be enrolled in the study for (24 weeks) and for the first week the engagement engine will calculate the average step count and use data from the enrollment questionnaire to recommend a physical activity goal. During the study, the engagement engine will recommend a daily physical activity goal and will assess the user's levels of engagement with the activity tracker. At week 12, participants will be sent a midpoint questionnaire and at week 24 the closeout questionnaire will be sent to the participant. The investigators do not foresee any significant risks for study participants and participants may not directly benefit from this the study. It is hoped that data collected from this study will allow the investigators to assess the engagement engine that could potentially be used to help individuals remain engaged with their physical activity tracker thereby sustaining regular physical activity. The risk for potential inadvertent release of Protected Health Information is taken very seriously. Investigators have taken several steps to minimize this risk as much as possible. Data collected on paper will be stored in a locked cabinet at PCH, accessible only to research staff. For the purposes of this study, participants will be asked to authorize the PCH database to access and store activity data from the activity tracker server. This is done using a secure, OAUTH procedure in which participants will be asked to enter their account username and password. The OAUTH process does not store this information on the PCH/study website, making this a secure and confidential method for participants to enable the PCH study staff to have access to their activity data. Activity data retrieved from the FitBit app will be stored on password protected server maintained by PCH Information Systems. At the conclusion of the study participants can change their account user settings on the study website and revoke PCH study database access to their account and data. Participants will be instructed on this process at the close-out of the study.

Official Title
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Evaluating an Engagement Engine to Support Long Term Use of Fitness Trackers and Sustain Physical Activity

Conditions
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Overweight, Obese

Intervention / Treatment
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* Other: Machine Learning Algorithm


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Ages 18+ years of age Body Mass Index (BMI) 25-40 kg/m2 Interest in using a fitness tracker for the duration of the study (24 weeks) Possess a smartphone, tablet or computer with the FiBit app Consent to undergo a phone interview with a member of the study staff Ability to receive text messages on their phone Fluency in English Exclusion Criteria: Self-reported eating disorder and/or other psychiatric disorders Pregnancy or plans to get pregnant within 6 months of enrollment Disability, dementia or neurological deficits, and other medical or surgical conditions preventing participants from engaging in physical activity Serious co-morbid conditions (e.g., terminal cancers, end-stage renal disease) that preclude safe participation in moderate levels of physical activity

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 95 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Other
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Other: Machine Learning Algorithm<br>Single group participants that will use the algorithm to be engaged in using their fitness tracker. | Other: Machine Learning Algorithm<br>* The algorithm will help participants improve physical activity by sustaining long term engagement with their fitness tracker.<br>* Other names: Engagement Engine;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Engagement level with the tracker | To assess the level of participant's engagement with physical activity tracker | 24 weeks | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Change in Physical Activity | To assess participant's change in physical activity from baseline throughout the remaining 23 weeks in the study via step data collected from the FitBit | 24 weeks | 
| Change in Self-efficacy scale for Physical Activity | To assess participant's change in self-efficacy to be physically active, this questionnaire will be given at 0 and 24 weeks | 24 weeks | 
| Change in Barriers to Being Active Questionnaire | To assess participant's change in perception of barriers to physical activity, this questionnaire will be administered at 0 and 24 weeks | 24 weeks |