Clinical trial
Does Personality Predict Patient Adherence, Health Behaviors, and Weight Loss Outcomes During the Latino Crossover Semaglutide Study (LCSS)? (Story-LCSS Project)
Active, not recruiting · Not applicable · 1 countries · Registry ID NCT05622045
What this study is about
The goal of this observational study is to learn about the personality attributes and values of people living with obesity that are part of the Latino community, and how these personality attributes and values can help to predict success during a weight loss program. The main questions it aims to answer are: * What are the personality attributes and values of people living with obesity that sign up to the LCSS-Latino Crossover Semaglutide Study trial? * Can behavioral artificial intelligence (a computer formula) predict which patients will complete the LCSS-Latino Crossover Semaglutide Study trial? * How do behavioral artificial Intelligence predictions (a computer formula) compare to clinician predictions of patient success? * Can behavioral artificial intelligence (a computer formula) predict patient weight loss, calorie consumption and physical activity levels during the LCSS-Latino Crossover Semaglutide Study trial? Participants will be recorded in English and Spanish while responding to a question regarding participation in a weight loss study.
Basic eligibility
Full registry criteria
Treatments and study arms
Voice data
Recorded response to a question about their participation in a weight loss study.
Primary outcomes
Predicted patient weight change as determined by Scaled Insights Behavioural Artificial Intelligence based on subject voice data. Weight loss exceeding 5-10 pounds over 6 months will be considered to be successful. Predicted weight change will be compared to the weight change measured in a separate clinical trial \[Latino Crossover Semaglutide Study (LCSS) NCT05087342\]. Similar weight change values between the predicted and measured outcomes will indicate that the Scaled Insights Behavioural Artificial Intelligence is good predictor.
Clinician (physician) judgement of patient weight loss success during a weight loss study.
Predicted patient calorie intake as determined by Scaled Insights Behavioural Artificial Intelligence based on subject voice data. Predicted calorie intake will be compared to the calorie intake measured in a separate clinical trial \[Latino Crossover Semaglutide Study (LCSS) NCT05087342\]. Similar calorie values between the predicted and measured outcomes will indicate that the Scaled Insights Behavioural Artificial Intelligence is good predictor.
Predicted patient physical activity level as determined by Scaled Insights Behavioural Artificial Intelligence based on subject voice data. Predicted physical activity will be compared to the physical activity measured in a separate clinical trial \[Latino Crossover Semaglutide Study (LCSS) NCT05087342\]. Similar physical activity level values between the predicted and measured outcomes will indicate that the Scaled Insights Behavioural Artificial Intelligence is good predictor.
Study locations
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