ChangeGradients: Promoting Adolescent Health Behavior Change
Promoting Adolescent Health Behavior Change With Clinically Integrated Sample-Efficient Policy Gradient Methods
2 other identifiers
interventional
200
1 country
1
Brief Summary
As most adolescents visit a healthcare provider once a year, health behavior change interventions linked to clinic-based health information technologies hold significant promise for improving healthcare quality and subsequent behavioral health outcomes for adolescents (Baird, 2014, Harris, 2017). Recognizing the potential to leverage recent advances in machine learning and interactive narrative environments, the investigators are now well positioned to design health behavior change systems that extend the reach of clinicians to realize significant impacts on behavior change for adolescent preventive health. The proposed project centers on the design, development, and evaluation of a clinically-integrated health behavior change system for adolescents. CHANGEGRADIENTS will introduce an innovative reinforcement learning-based feedback loop in which adolescent patients interact with personalized behavior change interactive narratives that are dynamically personalized and realized in a rich narrative-centered virtual environment. CHANGEGRADIENTS will iteratively improve its behavior change models using policy gradient methods for Reinforcement Learning (RL) designed to optimize adolescents' achieved behavior change outcomes. This in turn will enable CHANGEGRADIENTS to generate more effective behavior change narratives, which will then lead to further improved behavior change outcomes. With a focus on risky behaviors and an emphasis on alcohol use, adolescents will interact with CHANGEGRADIENTS to develop an experiential understanding of the dynamics and consequences of their alcohol use decisions. The proposed project holds significant transformative potential for (1) producing theoretical and practical advances in how to realize significant impacts on adolescent health behavior change through novel interactive narrative technologies integrated with policy-based reinforcement learning, (2) devising sample-efficient policy gradient methods for RL that produce personalized behavior change experiences by integrating theoretically based models of health behavior change with data-driven models of interactive narrative generation, and (3) promoting new models for integrating personalized health behavior change technologies into clinical care that extend the effective reach of clinicians.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Feb 2024
Typical duration for not_applicable
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
September 10, 2019
CompletedFirst Posted
Study publicly available on registry
October 1, 2019
CompletedStudy Start
First participant enrolled
February 12, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
July 31, 2026
ExpectedStudy Completion
Last participant's last visit for all outcomes
September 30, 2026
October 31, 2025
October 1, 2025
2.5 years
September 10, 2019
October 29, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (3)
Mean scores on assessment of Alcohol Use
Standard validated questions taken from the "Alcohol and other Drug Use" scale of the Youth Risk Behavior Surveillance Survey (CDC surveillance system that monitors adolescent risk behavior) will be administered. Measures include quantity and frequency of use and safety (drinking and driving), Current use of alcohol measured by quantity and frequency of use in the past 30 days (Centers for Disease Control and Prevention, 2018). Scale ranges vary based on questions and questions are scored individually. Responses to questions about alcohol use in general (past 12 months and ever) are scored as No = 0 and Yes = 1. Values on questions about alcohol use in the past 30 days are scored on a scale from 0-7, with higher values corresponding to greater alcohol consumption. Questions about drinking and driving are scored on a scale from 0-5 with higher numbers corresponding to more frequent instances of driving/being driven by others after alcohol was consumed.
30 days
Mean score on a Self-efficacy tool developed by Drs Elizabeth Ozer and Dr. Albert Bandura
Self-efficacy will be measured using a tool developed by Drs Elizabeth Ozer and Dr. Albert Bandura designed for this study. The tool assesses confidence in avoiding drinking in various scenarios. Participants are asked to rate level of confidence in drinking avoidance across various situations. Responses are rated on a scale of 0 to 10, with a rating of 0 indicating 'not at all confident', a rating of 5 indicating 'moderately confident', and rating of 10 indicating t 'completely confident'. Scenarios include: "When a close friend offers you a drink," and, "When you feel depressed or nervous." Scores on this assessment are calculated by summing participant responses and dividing by the number of questions to obtain a mean self-efficacy score.
30 days
Quality of Care: Adolescent Report of the Visit (AROV)
The Adolescent Report of the Visit (AROV) is a validated measure to assess the quality of care delivered to adolescents (Ozer, 2004), which has been utilized in clinics nationally and internationally (Sanci, 2015). The investigators are specifically using questions from this measure assessing provider rates of screening and counseling adolescents for alcohol use during adolescent visits. All questions are scored separately on a binary scale, with response scoring as No = 0 and Yes = 1. An answer of Yes to any item indicates higher quality of care.
1 day, immediately following baseline clinic visit
Study Arms (2)
Treatment (ChangeGradients)
EXPERIMENTALAdolescent participants will be introduced to the intervention through a brief introductory video trailer during their clinic visit and receive a link that enables them to engage with CHANGEGRADIENTS interactive narratives at home over a course of four weeks (i.e., one per week) on a personal computing device (e.g., laptop or tablet).
No Intervention (Usual Care)
NO INTERVENTIONParticipants will receive usual care at the clinic.
Interventions
CHANGEGRADIENTS is an interactive web-based tool which includes narrative-centered behavior change experiences that are dynamically generated.
Eligibility Criteria
You may qualify if:
- Adolescents between the ages of 15 and 17 years of age
- Report current alcohol use
- Presenting for a well-visit at UCSF Pediatric primary care clinics (the Mt. Zion Pediatric Primary Care Practices at UCSF and The Adolescent/Young Adult Clinic at UCSF)
You may not qualify if:
- Non-English speakers
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- University of California, San Franciscolead
- North Carolina State Universitycollaborator
- National Cancer Institute (NCI)collaborator
Study Sites (1)
University of California San Francisco Adolescent and Young Adult Medicine Clinic
San Francisco, California, 94107, United States
Related Publications (8)
Baird A, Nowak S. Why primary care practices should become digital health information hubs for their patients. BMC Fam Pract. 2014 Nov 25;15:190. doi: 10.1186/s12875-014-0190-9.
PMID: 25421733BACKGROUNDHarris SK, Aalsma MC, Weitzman ER, Garcia-Huidobro D, Wong C, Hadland SE, Santelli J, Park MJ, Ozer EM. Research on Clinical Preventive Services for Adolescents and Young Adults: Where Are We and Where Do We Need to Go? J Adolesc Health. 2017 Mar;60(3):249-260. doi: 10.1016/j.jadohealth.2016.10.005. Epub 2016 Dec 20.
PMID: 28011064BACKGROUNDOzer EM, Bandura A. Mechanisms governing empowerment effects: a self-efficacy analysis. J Pers Soc Psychol. 1990 Mar;58(3):472-86. doi: 10.1037//0022-3514.58.3.472.
PMID: 2324938BACKGROUNDOzer EM, Adams SH, Orrell-Valente JK, Wibbelsman CJ, Lustig JL, Millstein SG, Garber AK, Irwin CE Jr. Does delivering preventive services in primary care reduce adolescent risky behavior? J Adolesc Health. 2011 Nov;49(5):476-82. doi: 10.1016/j.jadohealth.2011.02.011. Epub 2011 Jun 8.
PMID: 22018561BACKGROUNDSanci L, Chondros P, Sawyer S, Pirkis J, Ozer E, Hegarty K, Yang F, Grabsch B, Shiell A, Cahill H, Ambresin AE, Patterson E, Patton G. Responding to Young People's Health Risks in Primary Care: A Cluster Randomised Trial of Training Clinicians in Screening and Motivational Interviewing. PLoS One. 2015 Sep 30;10(9):e0137581. doi: 10.1371/journal.pone.0137581. eCollection 2015.
PMID: 26422235BACKGROUNDOzer EM, Adams SH, Lustig JL, Millstein SG, Wibbelsman CJ, Babb J. The effect of preventive services on adolescent behavior (abstract). Pediatric Research. 2004;53(suppl. 4, pt. 2):265A.
BACKGROUNDOzer EM. The impact of childcare responsibility and self-efficacy on the psychological health of working mothers. Psychology of Women Quarterly. 1995;19:315-35.
BACKGROUNDOzer E, Rowe J, Tebb K, Culbertson K, Berna M, Jasik C, et al. A self-adaptive personalized behavior change system for adolescent preventive care. The Indian Journal of Pediatrics, Special Supplement The International Association for Adolescent Health, 11th World Congress on Adolescent Health, 27-29 October, 2017, New Delhi, India2017. p. SS-1.
BACKGROUND
Related Links
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Elizabeth Ozer, PhD
University of California, San Francisco
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- PREVENTION
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
September 10, 2019
First Posted
October 1, 2019
Study Start
February 12, 2024
Primary Completion (Estimated)
July 31, 2026
Study Completion (Estimated)
September 30, 2026
Last Updated
October 31, 2025
Record last verified: 2025-10
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP
De-identified data may be shared with research collaborators during the course of the study