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NCT Number: NCT05622045

Does Personality Predict Patient Adherence, Health Behaviors, and Weight Loss Outcomes During the Latino Crossover Semaglutide Study (LCSS)? (Story-LCSS Project)

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.

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This study is active but is not currently recruiting participants.

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Key information

Conditions

Obesity Body Weight Body Weight Changes Nutrition Disorders Nutritional and Metabolic Diseases Overnutrition Overweight Pathological Conditions, Signs and Symptoms Signs and Symptoms Weight Loss

Age range

18 year–74 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Nutrition Research Center, School of Public Health, Loma Linda University

Loma Linda, California, 92350, United States

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Participation in the LCSS-Latino Crossover Semaglutide Study

Exclusion criteria

  • Not a participant of the LCSS-Latino Crossover Semaglutide Study at the point of data collection

Treatment and study plan

Voice data

Behavioral

Recorded response to a question about their participation in a weight loss study.

Primary outcomes

  1. Predicted patient weight change success

    Time frame: The voice data measurement will take place at baseline and take about 10-15 minutes for collection to take place.

    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.

  2. Clinician predictions

    Time frame: The clinician judgement will be measured during the second month of the subject's weight loss study.

    Clinician (physician) judgement of patient weight loss success during a weight loss study.

  3. Predicated patient calorie intake

    Time frame: The voice data measurement will take place during the subject's initial clinic visit and take about 10-15 minutes for collection to take place.

    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.

  4. Predicated patient physical activity level

    Time frame: The voice data measurement will take at baseline and take about 10-15 minutes for collection to take place.

    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.

Secondary outcomes

  1. Personality attributes and values

    Time frame: The voice data measurement will take place at baseline and take about 10-15 minutes for collection to take place.

    Extrapolated personality attributes and values as determined by Scaled Insights Behavioural Artificial Intelligence based on subject voice data. These are qualitative non-numerical descriptors.

  2. Predicted patient attrition rate

    Time frame: The voice data measurement will take place at baseline and take about 10-15 minutes for collection to take place.

    Predicted patient attrition rate from the weight loss study as determined by Scaled Insights Behavioural Artificial Intelligence based on subject voice data. Predicted patient attrition rate will be compared to the attrition rate occurring during the weight loss study. Similar attrition rates between the predicted and actual rates will indicate that the Scaled Insights Behavioural Artificial Intelligence is good predictor.

Sponsors and collaborators

Lead sponsor

Loma Linda University

Other

Collaborators

  • Scaled Insights

Registry information

Acronym: StoryLCSS

Important dates

Study start
2023
Primary completion
2024
Study completion
2027
First posted
Nov 18, 2022
Registry last updated
Jun 8, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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