RECRUITING

Temporal Investigation of Multimodal Elements

Study Overview

This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.

Description

The TIME Study is a research project aiming to understand the body's natural rhythms. The goal is to see how daily and weekly changes in our bodies-from what's happening at a molecular level to data from wearable devices-are connected. What is the study about? This study is trying to create a detailed map of how a person's body changes over time. By looking at information from blood, urine, and other samples, as well as data from smartwatches and other devices, researchers want to learn how our bodies' natural cycles work in healthy older adults. The long-term goal is to use this knowledge to help develop more personalized healthcare in the future. Who can participate? The study is looking for healthy adults, age 55 or older, who have a smartphone and are able to travel to the Buck Institute in Novato, California, for study visits. Participants will be asked to: Attend weekly visits over 11 weeks to provide blood and other samples. Wear health-tracking devices like a smart ring and watch. Use a smartphone app to answer questions about their daily routines. Complete two "challenge" tests, including drinking a glucose solution and exercising on a stationary bicycle. Return for follow-up visits after 6 and 12 months. Are there any risks or benefits? Benefits: There are no direct health benefits for participants. However, the information gained will help scientists create better diagnostic tools and treatments for future generations. Risks: The main risks are minor discomfort from things like blood draws or skin irritation from the wearable devices. All personal information and data are kept private and secure.

Official Title

An Observational, Longitudinal Study to Characterize the Dynamic Structure of Molecular and Digital Health Data in Healthy Older Adults

Quick Facts

Study Start:2025-06-15
Study Completion:2028-06
Study Type:Not specified
Phase:Not Applicable
Enrollment:Not specified
Status:RECRUITING

Study ID

NCT07107386

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Ages Eligible for Study:55 Years
Sexes Eligible for Study:ALL
Accepts Healthy Volunteers:Yes
Standard Ages:ADULT, OLDER_ADULT
Inclusion CriteriaExclusion Criteria
  1. Age 18 years or older
  2. Willing and able to provide informed consent
  3. Able to understand and follow study procedures
  4. Stable medical condition
  1. Pregnancy or breastfeeding
  2. Severe psychiatric disorders
  3. Active substance abuse
  4. Unstable medical conditions
  5. Inability to comply with study requirements

Contacts and Locations

Study Contact

Brianna Stubbs, Research Assistant Professor, PhD.
CONTACT
(415) 209-2072
TIME-Study@buckinstitute.org
Alison Le, Project Manager
CONTACT
TIME-Study@buckinstitute.org

Principal Investigator

James Yurkovich, PhD
PRINCIPAL_INVESTIGATOR
Phenome Health, The Buck Institute for Research on Aging

Study Locations (Sites)

Buck Institute
Novato, California, 94945
United States

Collaborators and Investigators

Sponsor: Buck Institute for Research on Aging

  • James Yurkovich, PhD, PRINCIPAL_INVESTIGATOR, Phenome Health, The Buck Institute for Research on Aging

Study Record Dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Registration Dates

Study Start Date2025-06-15
Study Completion Date2028-06

Study Record Updates

Study Start Date2025-06-15
Study Completion Date2028-06

Terms related to this study

Additional Relevant MeSH Terms

  • To Map Human Biorhythms Using Molecular &Amp; Digital Health Data for Personalized Healthcare