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临床试验/NCT05622045
NCT05622045进行中(未招募)不适用

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

Loma Linda University2 个研究点 分布在 1 个国家目标入组 59 人开始时间: 2023年2月1日最近更新:
适应症

试验速览

阶段
不适用
状态
进行中(未招募)
入组人数
59
试验地点
2
主要终点
Predicated patient physical activity level

研究概览

简要总结

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.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 74 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Participation in the LCSS-Latino Crossover Semaglutide Study

排除标准

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

结局指标

主要结局

Predicated patient physical activity level

时间窗: 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.

Predicted patient weight change success

时间窗: 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.

Clinician predictions

时间窗: 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.

Predicated patient calorie intake

时间窗: 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.

次要结局

  • Personality attributes and values(The voice data measurement will take place at baseline and take about 10-15 minutes for collection to take place.)
  • Predicted patient attrition rate(The voice data measurement will take place at baseline and take about 10-15 minutes for collection to take place.)

研究者

申办方类型
Other
责任方
Sponsor

研究点 (2)

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