Grant Details
Grant Number: |
5R21CA263539-02 Interpret this number |
Primary Investigator: |
Van Blarigan, Erin |
Organization: |
University Of California, San Francisco |
Project Title: |
Engaging Diverse Colorectal Cancer Survivors in the Design of an Adaptive Text Message-Based Intervention to Improve Diet Quality |
Fiscal Year: |
2023 |
Abstract
Colorectal cancer (CRC) is the 2nd leading cause of cancer death in the United States. Interventions that are
accessible and effective in the large, culturally diverse populations of people affected by CRC will greatly
improve public health. Dietary interventions hold particular promise for reducing CRC mortality because strong
evidence supports that a high-fiber diet rich in whole grains is associated with lower mortality among people
with CRC. Yet, <15% of CRC survivors consume a high-fiber diet. Therefore, our goal is to develop a scalable
intervention to increase intake of whole grains and reduce intake of refined grains that is acceptable to CRC
survivors of varied cultural backgrounds. Text messages are a promising intervention component for reaching
a wide range of CRC survivors. However, most studies have developed and tested “one size fits all” static
programs with limited generalizability. To address this gap, we propose to develop a continuously adaptive text
message-based intervention using reinforcement learning (RL). RL is a type of machine learning that can be
used to optimize text messages over time based on participant characteristics (e.g., race/ethnicity, language),
engagement, and/or behavior. Dr. Aguilera (co-I) has developed a text message intervention that uses RL to
increase physical activity in low income people with depression and diabetes; messages are sent in English or
Spanish. While promising, it is not known if a RL algorithm can be used to improve diet behavior. In this
proposal, we will develop a RL algorithm to optimize text message content and timing based on whole grain
intake assessed through text messages. Informed by the Capability Opportunity Motivation – Behavior (COM-
B) model, we propose an embedded mixed method study. In Aim 1, we will conduct four focus groups among
Black, Latinx, non-Latinx white, and Asian American/Pacific Islander CRC survivors (5-8/group) and 20 semi-
structured interviews. We aim to understand CRC survivors’ capabilities, opportunities, and motivations for a
healthy diet and preferences for text messages. Using these data, we will refine our theoretical framework and
revise/update our library of >200 diet-focused text messages from previous work in non-Latinx white cancer
survivors. In Aim 2, informed by Aim 1, we will develop an adaptive text message intervention using RL to
increase the proportion of grains consumed that are whole grains among CRC survivors. We will determine the
intervention’s feasibility and acceptability and estimate its effect on diet (intake of whole grains, refined grains,
total fiber) in a 12-week single-arm study among 60 CRC survivors, approximately equal numbers of whom
identify as Black, Latinx, non-Latinx white, and Asian American/Pacific Islander. Our multidisciplinary and
multicultural team has the expertise needed to complete this study. Our proposal will inform a scalable dietary
intervention with broad generalizability that we will ultimately test in a randomized controlled trial. Improving
CRC survivors’ diet quality has potential to reduce CRC mortality and have great public health impact.
Publications
None