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Integration of a Trained Language Model to Improve Glycemic Control Through Increased Physical Activity: a Fully Digital My Heart Counts Smartphone App Randomized Trial

Not Applicable
Not yet recruiting
Conditions
Type2diabetes
Interventions
Behavioral: Validation of language model prompts in increasing short-term physical activity
Behavioral: Assessment of long-term changes to physical activity and glycemic control
Registration Number
NCT06596330
Lead Sponsor
Stanford University
Brief Summary

Type 2 diabetes (T2D) is one of the most common and fastest growing diseases, affecting 1 in 8 adults (nearly 800 million) worldwide by 2045. Sedentary behavior and increased adiposity are major risk factors for T2D. Cardiovascular disease is the leading cause of death in those with T2D, while diabetic microvascular disease, causing kidney disease, neuropathy, and retinopathy, contributes to T2D morbidity.

Physical activity is one of the most potent therapies in preventing/treating T2D and its complications. Mean daily steps is a proxy for physical activity, with even modest improvements in step count (i.e., +500 steps) associated with decreased T2D and mortality. However, adherence to regular physical activity remains low in T2D patients, with short-term decreases in daily step count associated with impaired glycemic control and T2D recurrence.

The investigators have developed an artificial intelligence (AI) language model (similar to ChatGPT), which can automatically generate coaching prompts to encourage physical activity by incorporating an individual's stage of change. The investigators will extend our research using the My Heart Counts (MHC) smartphone app to 1) validate the efficacy of the AI-generated prompts in patients with T2D and 2) perform a longer-term randomized crossover trial using the language model as a social accountability chatbot - encouraging participants to maintain their physical activity changes over months. The investigators hypothesize that my AI-assisted coaching prompts will significantly increase 1) mean daily step count by 500 steps in 1,000 adults recruited nationwide over a 7-day period, and 2) improve HbA1c and weight via long-term behavior change over a 24-week intervention period.

Detailed Description

Not available

Recruitment & Eligibility

Status
NOT_YET_RECRUITING
Sex
All
Target Recruitment
1000
Inclusion Criteria
  • Individuals aged ≥18 years old, with a clinical diagnosis of T2D, able to read and understand English, and who are physically able to walk, will be included in our study
Exclusion Criteria
  • Criteria that fall outside of the inclusion criteria.

Study & Design

Study Type
INTERVENTIONAL
Study Design
CROSSOVER
Arm && Interventions
GroupInterventionDescription
LLM-generated coaching promptValidation of language model prompts in increasing short-term physical activity-
LLM-generated coaching promptAssessment of long-term changes to physical activity and glycemic control-
10,000 Step ReminderValidation of language model prompts in increasing short-term physical activity-
10,000 Step ReminderAssessment of long-term changes to physical activity and glycemic control-
Primary Outcome Measures
NameTimeMethod
Mean daily steps7 days and 24 weeks

Mean daily steps over the course of an intervention week (aim 1) and 24 week period (aim 2).

Secondary Outcome Measures
NameTimeMethod
Change in weight24 Weeks

Change in weight over the long term intervention (Aim 2)

Change in HbA1c24 Weeks

Change in HbA1c over the long term intervention (Aim 2)

Weekly Active Minutes7 days and 24 Weeks

Total weekly active minutes over the course of an intervention week (aim 1) and 24 week period (aim 2).

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