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

Obesity Clinical Trial

— StoryLCSS  

Official title:

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

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT05622045
• Other study ID #: 5220330
• Status: Active, not recruiting
• Start date: February 1, 2023
• Est. completion date: December 2024

Study information

• Verified date: September 2023
• Source: Loma Linda University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 59
• Est. completion date: December 2024
• Est. primary completion date: May 2024
• Gender: All
• Age group: 18 Years to 74 Years

Eligibility

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

Related Conditions & MeSH terms

• Body Weight
• Body Weight Changes
• Obesity
• Weight Loss

Intervention

Behavioral:
• Voice data
Recorded response to a question about their participation in a weight loss study.

Locations

Country	Name	City	State
United States	Nutrition Research Center, School of Public Health, Loma Linda University	Loma Linda	California

Sponsors (2)

Lead Sponsor	Collaborator
Loma Linda University	Scaled Insights

Country where clinical trial is conducted

United States, 

References & Publications (7)

Alberga AS, Russell-Mayhew S, von Ranson KM, McLaren L. Weight bias: a call to action. J Eat Disord. 2016 Nov 7;4:34. doi: 10.1186/s40337-016-0112-4. eCollection 2016. — View Citation

Dalle Grave R, Calugi S, Compare A, El Ghoch M, Petroni ML, Tomasi F, Mazzali G, Marchesini G. Weight Loss Expectations and Attrition in Treatment-Seeking Obese Women. Obes Facts. 2015;8(5):311-8. doi: 10.1159/000441366. Epub 2015 Oct 8. — View Citation

Flint SW, Leaver M, Griffiths A, Kaykanloo M. Disparate healthcare experiences of people living with overweight or obesity in England. EClinicalMedicine. 2021 Sep 15;41:101140. doi: 10.1016/j.eclinm.2021.101140. eCollection 2021 Nov. — View Citation

Flint SW, Piotrkowicz A, Watts K. Use of Artificial Intelligence to understand adults' thoughts and behaviours relating to COVID-19. Perspect Public Health. 2022 May;142(3):167-174. doi: 10.1177/1757913920979332. Epub 2021 Jan 21. — View Citation

Hardcastle SJ, Taylor AH, Bailey MP, Harley RA, Hagger MS. Effectiveness of a motivational interviewing intervention on weight loss, physical activity and cardiovascular disease risk factors: a randomised controlled trial with a 12-month post-intervention follow-up. Int J Behav Nutr Phys Act. 2013 Mar 28;10:40. doi: 10.1186/1479-5868-10-40. — View Citation

Puhl RM, Phelan SM, Nadglowski J, Kyle TK. Overcoming Weight Bias in the Management of Patients With Diabetes and Obesity. Clin Diabetes. 2016 Jan;34(1):44-50. doi: 10.2337/diaclin.34.1.44. No abstract available. — View Citation

Wilding JPH, Batterham RL, Calanna S, Davies M, Van Gaal LF, Lingvay I, McGowan BM, Rosenstock J, Tran MTD, Wadden TA, Wharton S, Yokote K, Zeuthen N, Kushner RF; STEP 1 Study Group. Once-Weekly Semaglutide in Adults with Overweight or Obesity. N Engl J Med. 2021 Mar 18;384(11):989-1002. doi: 10.1056/NEJMoa2032183. Epub 2021 Feb 10. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Predicted patient weight change success	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.	The voice data measurement will take place at baseline and take about 10-15 minutes for collection to take place.
Primary	Clinician predictions	Clinician (physician) judgement of patient weight loss success during a weight loss study.	The clinician judgement will be measured during the second month of the subject's weight loss study.
Primary	Predicated patient calorie intake	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.	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.
Primary	Predicated patient physical activity level	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.	The voice data measurement will take at baseline and take about 10-15 minutes for collection to take place.
Secondary	Personality attributes and values	Extrapolated personality attributes and values as determined by Scaled Insights Behavioural Artificial Intelligence based on subject voice data. These are qualitative non-numerical descriptors.	The voice data measurement will take place at baseline and take about 10-15 minutes for collection to take place.
Secondary	Predicted patient attrition rate	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.	The voice data measurement will take place at baseline and take about 10-15 minutes for collection to take place.