The goal of this observational study is to evaluate the feasibility and acceptability of a 12-week intervention utilizing a Fitbit and artificial intelligence (AI)-delivered diabetes self-management education and support (DSMES) with tailored text messages. The main question it aims to answer is: Does providing a wearable fitness and activity tracker plus AI-tailored and DSMES improve clinical outcomes for patients with type 2 diabetes? Participants will complete a baseline visit, wear a Fitbit and answer text messages for 12-weeks, and complete by a final visit.
Study Type
OBSERVATIONAL
Enrollment
36
Participants will wear their Fitbit devices daily for 12-weeks and will receive personalized messages from the AI Chatbot every week with a new exercise recommendation based on their previous week's activity level. Additionally, they can engage with the AI Chatbot through text message for further support and education.
The control group will consist of patients with type 2 diabetes who meet the study's inclusion criteria but have not participated in the intervention.
University of Colorado, Anschutz
Aurora, Colorado, United States
RECRUITINGFeasibility - Recruitment
Recruitment of 36 adults within 6 months.
Time frame: 6 months
Feasibility - Retainment
Retainment of 85% of participants for post-assessments.
Time frame: 6 months
Feasibility - Fitbit wear
Fitbit wear ≥ 5 days/week \> 12 hours per day, wear at night \> 3 nights/week.
Time frame: 12 Weeks
Feasibility - Text message responses
Responding to 80% of text messages when prompted.
Time frame: 12 Weeks
Feasibility - Technical issues
Participation with ≤10% technical issues (battery life, data sync between device and app/dashboard, device failure).
Time frame: 12 Weeks
Acceptability - Participant Experience and Satisfaction
Obtaining \> 60% satisfaction from participants via a satisfaction survey.
Time frame: 12 Weeks
Change in HbA1c
Change in HbA1c from baseline to post-intervention.
Time frame: 12 Weeks
Change in Body Mass Index
Change in Body Mass Index (BMI) from baseline to post-intervention.
Time frame: 12 Weeks
Change in lipid panel
Change in lipid panel from baseline to post-intervention.
Time frame: 12 Weeks
Change in weight
Change in weight from baseline to post-intervention.
Time frame: 12 Weeks
Change in blood pressure
Change in blood pressure from baseline to post-intervention.
Time frame: 12 Weeks
Change in diabetes distress
Change in diabetes distress as measured by the T2-DDAS: The Type 2 Diabetes Distress Assessment System from baseline to post-intervention.
Time frame: 12 Weeks
Experience with technology
Patient experience with technology as measured via the System Usability Scale (SUS).
Time frame: 12 Weeks
Experience with technology
Patient experience with technology as measured via the FACETS Comfort with Technology assessment.
Time frame: 12 Weeks
Cost
Cost of delivering remote patient monitoring intervention as measured via time-diaries and patient logs.
Time frame: Weekly, 12 weeks
Revenue
Revenue modeling from practice perspective of remote patient monitoring intervention as measured via staff and patient time logs.
Time frame: Weekly, 12 weeks
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