Social Health, Activity Behaviors, and Quality of Life Among Young Adult Cancer Survivors
4 other identifiers
observational
250
1 country
1
Brief Summary
This study assesses how personal relationships (such as friendships, family relationships, or romantic partners) influence the physical activity (exercise) and well-being of young adult cancer survivors. Researchers also hope to learn how social relationships change after a cancer diagnosis, and how these changes might impact important health behaviors. The information provided may help researchers learn more about better ways to support young cancer patients in the future through interventions that help maintain good social relationships and health levels of physical activity.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Nov 2021
Longer than P75 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
October 14, 2021
CompletedStudy Start
First participant enrolled
November 24, 2021
CompletedFirst Posted
Study publicly available on registry
December 2, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2026
ExpectedStudy Completion
Last participant's last visit for all outcomes
December 31, 2027
December 2, 2025
November 1, 2025
5.1 years
October 14, 2021
November 20, 2025
Conditions
Outcome Measures
Primary Outcomes (7)
Rate of Change in trajectories of social health
Social health variables include the number, frequency and duration of hospitalizations, specifics of cancer diagnosis (i.e., stage at diagnosis, pertinent histology, recurrence or progression of disease), chemotherapy type, surgery related to cancer diagnosis, radiation field, immunotherapy type, and other relevant therapies related to cancer treatment. Changes in above variables will be measured using latent growth curve models to measure latent intercept (initial level), and the latent slope (rate of change) of social health variables during the course of therapy.
Baseline up to 1 year
Rate of Change in trajectories of physical activity
Changes will be measured using latent growth curve models to measure latent intercept (initial level) and the latent slope (rate of change) of physical activity during the course of therapy.
Baseline up to 1 year
Rate of Change in trajectories of quality of life
Changes will be measured using latent growth curve models to measure latent intercept (initial level) and the latent slope (rate of change) of quality of life during the course of therapy.
Baseline up to 1 year
Moderation by gender
Will conduct multi-group analyses by the categories of study moderators (e.g., gender, race/ethnicity, socioeconomic status \[SES\], health status). The strengths of group-specific pathways to link social health and activity behaviors to quality of life will be compared using the chi-square (χ2) difference test of model fit. The log-likelihood values with (versus \[vs.\] without) the equality constraints on the group-specific pathways to determine if the strength of associations estimated in the models significantly differ by the groups of each moderator (e.g., gender: female vs. male).
Up to 1 year
Moderation effect of race/ethnicity
Moderation effect is analyzed by the interaction between the independent variable (X), and the moderator variable (Y) in a regression model, where the endpoint is the dependent variable (Z). Moderation effect is the endpoint itself, indicated by the significance of the interaction term's regression coefficient (B3), which shows how the relationship between X and Y changes depending on the level of Z. 'X' is social health, physical activity, and quality of life. 'Y' is race/ethnicity. 'Z' is moderation effect. The strengths of group-specific pathways to link social health and activity behaviors to quality of life will be compared using the chi-square (χ2) difference test of model fit.
Up to 1 year
Moderation effect of Socio-Economic Status (SES)
Moderation effect is analyzed by the interaction between the independent variable (X), and the moderator variable (Y) in a regression model, where the endpoint is the dependent variable (Z). Moderation effect is the endpoint itself, indicated by the significance of the interaction term's regression coefficient (B3), which shows how the relationship between X and Y changes depending on the level of Z. 'X' is social health, physical activity, and quality of life. 'Y' is socio-economic status. 'Z' is moderation effect. The strengths of group-specific pathways to link social health and activity behaviors to quality of life will be compared using the chi-square (χ2) difference test of model fit.
Up to 1 year
Moderation effect of health status
Moderation effect is analyzed by the interaction between the independent variable (X), and the moderator variable (Y) in a regression model, where the endpoint is the dependent variable (Z). Moderation effect is the endpoint itself, indicated by the significance of the interaction term's regression coefficient (B3), which shows how the relationship between X and Y changes depending on the level of Z. 'X' is social health, physical activity, and quality of life. 'Y' is health status. 'Z' is moderation effect. The strengths of group-specific pathways to link social health and activity behaviors to quality of life will be compared using the chi-square (χ2) difference test of model fit.
Up to 1 year
Study Arms (1)
Observational (actigraph, surveys)
Patients complete surveys and wear an actigraph GT3X-BT accelerometer continuously for 7 days at baseline, 3, 6, and 12 months.
Interventions
Wear an actigraph GT3X-BT accelerometer
Complete survey
Eligibility Criteria
Patients diagnosed and/or treated with cancer between ages 18-39 at University of Southern California (USC) hospitals.
You may qualify if:
- Diagnosed and/or treated with cancer between ages 18-39 at USC hospitals.
- Cancer types prototypical for adolescents and young adults (AYAs) and cancer stages I-III; select patients with stage IV disease may be eligible, with approval by the principal investigator (PI) and in consultation with the treating clinician.
- Must be within three months of a de novo cancer diagnosis at recruitment and on/indicated for curative therapy (any modality). Patients may continue on adjuvant therapy throughout duration of the study.
- Patients must have anticipated survival of \>1-year at time of diagnosis.
You may not qualify if:
- Diagnosis of blood malignancies such as leukemias (these cancers have divergent treatment patterns of longer duration than other cancers and are more commonly pediatric cancers). Some early stage lymphomas with favorable prognoses may be eligible, with approval by the PI and in consultation with the treating clinician.
- Primary language other than English or Spanish.
- Inability to complete a survey and/or wear an accelerometer either per the patient or in consultation with the clinician's judgment.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- University of Southern Californialead
- National Cancer Institute (NCI)collaborator
Study Sites (1)
USC / Norris Comprehensive Cancer Center
Los Angeles, California, 90033, United States
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Kimberly Miller, PhD
University of Southern California
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- CASE ONLY
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
October 14, 2021
First Posted
December 2, 2025
Study Start
November 24, 2021
Primary Completion (Estimated)
December 31, 2026
Study Completion (Estimated)
December 31, 2027
Last Updated
December 2, 2025
Record last verified: 2025-11