Use of Text Messages to Increase Whole Grain Consumption in Colorectal Cancer
Phase: NA
Conditions: Colon Adenocarcinoma, Colorectal Carcinoma, Rectal Adenocarcinoma
Sponsor: University of California, San Francisco



UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 2 of 30
Protocol Signature Page
1.
I agree to follow this protocol version as approved by the Institutional Review Board (IRB).
2.
I will conduct the study in accordance with Good Clinical Practices (ICH-GCP) and the 
applicable IRB, ethical, federal, state, and local regulatory requirements. 
3.
I certify that I, and the study staff, have received the required training to conduct this 
research protocol. 
4.
I agree to maintain adequate and accurate records in accordance with IRB policies and 
federal, state, and local laws and regulations.
UCSF Principal Investigator 
Printed Name
Signature
Date

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 3 of 30
Abstract
Title
 Optimization of Adaptive Text Messages for Cancer Survivors II 
(OATS II)
Study Description
This study aims to develop a continuously adaptive text message-
based intervention using reinforcement learning, a type of artificial 
intelligence, to increase the proportion of grains consumed that are 
whole grains in a racially/ethnically diverse group of colorectal cancer 
(CRC) survivors.
Study Intervention
Adaptive 12-week text message intervention using reinforcement 
learning to increase whole grain and reduce refined grain intake 
Study Population
Participants for this study will include up to 60 CRC survivors for the 
proof-of-concept single-arm trial
Primary Objective
To determine the intervention’s feasibility and acceptability 
Secondary 
Objectives
1.
To estimate the effect of the intervention on the percent of grains 
that are whole
2.
To estimate the effect of the intervention on total fiber intake (g/d)
Recruitment 
Methods
Participants will be recruited through MyChart messages and letters 
from the UCSF CTSI Participant Recruitment Program, as well as 
clinician referrals at the University of California, San Francisco (UCSF) 
Helen Diller Family Comprehensive Cancer Center (HDFCCC) and the 
Zuckerberg San Francisco General (ZSFG) hospital.
Sample Size
Participants for this study will include up to 60 CRC survivors for the 
proof-of-concept single-arm trial
Duration of Study 
Participation
12 weeks
Unique Aspects of 
this Study
This study is the first to develop a continuously adaptive text 
message-based intervention using reinforcement learning, a type of 
artificial intelligence, to increase the proportion of grains consumed 
that are whole grains in a racially/ethnically diverse group of CRC 
survivors.

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 4 of 30
List of Abbreviations
AE
adverse event
BCT
behavior change technique
COM-B
Capability Opportunity Motivation – Behavior
CRC
colorectal cancer
CRF
case report form
CTCAE
Common Terminology Criteria for Adverse Events
CTMS
Clinical Trial Management System
DSMC
Data and Safety Monitoring Committee
DSMP
Data and Safety Monitoring Plan
GCP
Good Clinical Practice
HDFCCC
Helen Diller Family Comprehensive Cancer Center
HIPAA
Health Insurance Portability and Accountability Act
ICF
informed consent form
ICH
International Conference on Harmonization
IRB
Institutional Review Board
PRMC
Protocol Review and Monitoring Committee (UCSF)
RL
reinforcement learning
ZSFG
Zuckerberg San Francisco General

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 5 of 30
Table of Contents
Protocol Signature Page ...............................................................................................................2
Abstract
……………………………………………………………………………………………3
List of Abbreviations ......................................................................................................................4
Table of Contents ..........................................................................................................................5
1
Introduction........................................................................................................................7
1.1
Background on Dietary Interventions for Colorectal Cancer........................................7
1.2
Background on Text Messaging as a Behavioral Intervention in Diverse 
Populations.............................................................................................................7
1.3
Study Rationale.......................................................................................................8
1.4
Innovation..............................................................................................................8
1.5
Risks/Benefits.........................................................................................................8
2
Study Objectives and Endpoints........................................................................................9
2.1
Primary Objective ...................................................................................................9
2.2
Secondary Objectives ............................................................................................10
2.3
Exploratory Objective............................................................................................10
3
Study Design ...................................................................................................................10
3.1
Schema ................................................................................................................10
3.2
Characteristics ......................................................................................................11
3.3
Sample Size..........................................................................................................11
3.4
Primary Completion ..............................................................................................11
3.5
Study Completion .................................................................................................11
4
Selection and Enrollment of Participants.........................................................................11
4.1
Eligibility Criteria .................................................................................................11
4.2
Recruitment Methods ............................................................................................12
4.3
Inclusion and Recruitment of Women and Minorities ...............................................13
4.4
Inclusion Across the Lifespan.................................................................................13
4.5
Participant Registration..........................................................................................13
4.6
Assignment to Intervention ....................................................................................14
5
Study Intervention............................................................................................................14
5.1
Delivery of Study Intervention ...............................................................................15
5.2
Interventionist Training and Tracking .....................................................................15
5.3
Adherence Assessment ..........................................................................................15
5.4
Participant Discontinuation/Withdrawal from the Study............................................16
5.5
Lost to Follow-up..................................................................................................16
6
Study Procedures and Assessments...............................................................................17
6.1
Schedule of Activities............................................................................................17
6.2
Study Procedures and Assessments.........................................................................19
7
Reporting and Documentation of Results........................................................................20
7.1
Measures and Instruments......................................................................................20
8
Adverse Events and Serious Adverse Events .................................................................21
8.1
Definition of Adverse Event (AE)...........................................................................21
8.2
Definition of Serious Adverse Event (SAE).............................................................21
8.3
Classification of Adverse Events ............................................................................22
8.4
Adverse Events Monitoring....................................................................................22

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 6 of 30
8.5
Follow Up of Adverse Events.................................................................................23
8.6
Documenting and Reporting of Adverse Events .......................................................23
9
Statistical Considerations ................................................................................................23
9.1
Sample Size Considerations ...................................................................................23
9.2
Statistical Analysis Plans .......................................................................................23
10
Study Management .........................................................................................................24
10.1
Pre-study Documentation.......................................................................................24
10.2
Institutional Review Board Approval ......................................................................24
10.3
Informed Consent..................................................................................................25
10.4
Changes in the Protocol .........................................................................................25
10.5
Case Report Forms (CRFs) ....................................................................................25
10.6
Record Retention ..................................................................................................25
10.7
Publications..........................................................................................................26
10.8
Multicenter Communication...................................................................................26
10.9
Regulatory Documentation.....................................................................................26
11
Protection of Human Subjects .........................................................................................26
11.1
Protection of Privacy.............................................................................................26
11.2
Protection from Unnecessary Harm ........................................................................27
12
References ......................................................................................................................28

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 7 of 30
1
Introduction
1.1Background on Dietary Interventions for Colorectal Cancer
Dietary interventions are a promising approach for reducing colorectal cancer (CRC) mortality.1-3 
Guinter et al. reported that individuals with a low American Cancer Society (ACS) nutrition 
guideline score (based on intake of whole grains, fruits and vegetables, and red and processed 
meat) pre-diagnosis and high score post-diagnosis had a 29% lower risk of CRC-specific 
mortality versus patients with low scores at both time points.2,4 When examining the 
components in the ACS score among 992 stage III colon cancer patients, our team observed 
that those in the fourth quartile of proportion of grains that are whole had 35% lower risk of 
cancer recurrence and mortality compared to those in the first quartile (median % grains that 
were whole was 76% in 4th quartile vs.11% in 1st quartile).1,4 An independent study of 1,575 
people with stage I-III CRC reported that a 5-g/d increase in cereal fiber intake after diagnosis 
was associated with 33% lower risk of CRC-specific mortality.5 Overall, there is strong evidence 
that a high-fiber diet rich in whole grains lowers risk of CRC mortality. 
Most CRC survivors do not achieve recommended intakes of whole grains or fiber.3,6,7 In a 
nationally representative sample of 1,550 cancer survivors, mean fiber intake was 15 g/d, half 
the 30 g/d recommended by the American Institute for Cancer Research.8 Moreover, differences 
in diet quality may play a role in CRC disparities. For example, on average in the United States 
(US), Black people have lower intake of grains compared to non-Latinx White people.9 Work 
from our team and others suggests that barriers to a high-fiber diet among cancer survivors 
include lack of time, energy, social support, access to healthy foods, and experience preparing 
high-fiber foods.10-15 While several dietary interventions have been developed for cancer 
survivors, past studies have largely tested resource-intensive, multi-component interventions in 
non-representative populations.16 These studies have observed changes in diet, but changes 
have often been small.17 Thus, more research is needed to develop dietary interventions for 
CRC survivors.
1.2Background on Text Messaging as a Behavioral Intervention in Diverse 
Populations
Text messages are a promising tool for behavioral interventions in diverse populations. Nearly 
all adults in the US have mobile phones, and text messages are used by the majority of mobile 
phone users with little variation by race/ethnicity.18,19 Text messages do not require heavy data 
usage or high digital literacy, are inexpensive, and can be used to apply behavior change 
techniques (BCTs) such as information, instruction, feedback, prompts/cues, social support, 
self-monitoring, goal setting, and action planning.20,21 We and others have reported that text 
message-based interventions are feasible, acceptable and effective for dietary change.10,11,18,22 
In fact, data suggest that stand-alone text messaging interventions could be as effective as 
blended interventions that combine text messaging with other tools (e.g., coaching) for less 
cost.18 Data are limited, however, in CRC survivors and people who identify with racial/ethnic 
minority groups.17 Moreover, patients consistently desire a more tailored experience in text 
message interventions and the optimal frequency, timing, and interactivity of text messages are 
not known.10,18,23
Artificial intelligence solutions, including reinforcement learning (RL), may optimize digital health 
interventions in a scalable automated way. In 2019, Forman et al. reported on one of the first 
pilot studies to use RL in a weight loss intervention.24 Their algorithm determined if participants 
would receive a coach call, a coach text message, or a non-tailored text message based on the 
frequency that participants self-monitored weight or diet, met calorie goals or physical activity 
goals, and weight loss. In a pilot study of 52 primarily White participants, the RL optimized 
intervention resulted in equal weight loss for half the cost of phone coaching. Yet, participants 

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 8 of 30
desired more personalization, suggesting the need for message tailoring by individual 
characteristics and adaptation over time to account for behavior change and to maintain 
engagement.
1.3Study Rationale
To address gaps and build on prior research, our team proposes to develop an adaptive text 
message-based dietary intervention for CRC survivors.25 We will develop a RL algorithm to 
continuously adapt text message content and timing to increase whole grain and reduce refined 
grain intake. We plan to focus on CRC specifically because people with CRC have been under-
represented in past behavioral intervention studies for cancer survivors, and the evidence for a 
role of diet after CRC diagnosis is strong.1,5,16  Additionally, experience from multiple studies 
suggests recruitment of people with CRC to clinical trials may require a more targeted approach 
than survivors of other common cancers.27,28
1.4Innovation
Past behavioral intervention trials have focused primarily on physical activity or weight loss.29 
Yet data suggest that diet is equally important for CRC survivors1. Optimizing a behavioral 
intervention based on diet, which cannot be passively measured, is a particular challenge that 
we will address in this proposal. The results of this study will inform the design of a scalable 
intervention with broad reach that we will ultimately test in a randomized controlled trial. 
Enhancing CRC survivors’ diet quality has potential to reduce CRC mortality and greatly 
improve public health.
1.5Risks/Benefits
Potential Risks 
The risks involved in this study are few. There is a minor risk of loss of confidentiality, either 
through the breach of data collected via the Internet or text messaging or through the breach of 
secure study databases, physical files, etc. Dietary modifications may result in changes in bowel 
function, including but not limited to diarrhea, constipation, increased urgency, flatulence, and/or 
bloating. These changes are not expected to be clinically significant but could impact quality of 
life if they occur.
Potential Benefit of the Proposed Research to Participants and Others
The benefits of healthy diet are well established. Intervention participants may experience 
decreases in symptom burden and improved physical functioning and quality of life. This study 
will produce societal benefit regarding knowledge about how to optimize a text message-based 
intervention to improve diet quality in cancer survivors. Given the minimal risk of study 
participation and potential benefits, the risks to participants are reasonable in relation to the 
anticipated benefits to society.
Procedures used to minimize risk

Numerous studies have demonstrated that healthy diet is safe, feasible, and beneficial for 
cancer patients and survivors.

Participants will receive tips on how to alleviate or avoid digestive changes due to increased 
whole grain and fiber intake.

Participants will be asked to contact the study team at any time if they have questions or 
concerns about the study.

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 9 of 30

All study files, folders, and records will be kept in locked file cabinets that can be accessed 
only by study personnel.

All data will be exchanged over an SSL-protected connection, and all data will be encrypted.

The study database and all survey data will be collected and stored in REDCap, the 
HealthySMS platform, Twilio, and UCSF’s Research Analysis Environment (RAE), which 
have protections needed for storage of PHI.
Limited private identifiable information necessary for the conduct of the study will be collected in 
the proposed research project. For example: names, phone numbers, and email addresses. 
This information will be stored securely in REDCap, the HealthySMS platform, Twilio, and 
UCSF’s Research Analysis Environment (RAE; mytransfer.ucsf.edu), which have the 
protections in place and approvals for the storage of PHI. 
Importance of Knowledge to be Gained
Promotion of a healthy diet is an important aspect of cancer survivorship care. This research 
aims to create an intervention that can be remotely delivered and is appropriate for 
implementation on a large scale. We believe that the minimal risk involved with study 
participation are reasonable in relation to the knowledge that is expected to result.
2
Study Objectives and Endpoints
2.1
Primary Objective
1) The intervention will be determined feasible if the median response proportion to text messages that ask for a reply 
is ≥ 70%, and the median score for the Feasibility of Intervention measure is ≥4.
2) The intervention will be determined acceptable if median scores on the Acceptability of Intervention and 
Intervention Appropriateness Measures are ≥4.
Primary Objective
Endpoint(s)
Time Frame
Determine the intervention’s feasibility1 
and acceptability2 

Participants’ 
responses to text 
messages that ask for 
a response

Participant surveys

Semi-structured end of 
study interviews
From 0 to 12 weeks

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 11 of 30
3.2  Characteristics
This is a single-arm proof-of-concept trial. In this study, we will assess the feasibility and 
acceptability of a 12-week adaptive text message-based dietary intervention that uses 
reinforcement learning (RL; a type of machine learning) to determine what type of text 
messages to send, and when to send text messages, based on participants’ diet behavior and 
engagement (replies to text messages). The target population for the intervention includes CRC 
survivors who speak and read English or Spanish.
3.3
Sample Size
We will accrue up to 60 CRC survivors. Participants who withdraw or are otherwise not 
evaluable will not be replaced.
3.4
Primary Completion
The expected primary completion date is 24 months after the study opens to accrual.
3.5
Study Completion
The expected study completion date is 30 months after the study opens to accrual.
4
Selection and Enrollment of Participants
4.1
Eligibility Criteria
4.1.1 Inclusion Criteria
To be eligible to participate in this study, an individual must meet the following criteria. Eligibility 
will be determined by self-report and/or medical record review.
1.
Age > 18 years
2.
Subject has provided informed consent
3.
Diagnosis of colon or rectal adenocarcinoma
4.
Not on active treatment at the time of screening and not expected to receive active anti-
cancer therapy (e.g., surgery, radiation, chemotherapy) during the study period
5.
At least 6 weeks since a major surgery and fully recovered
6.
Owns a mobile phone and is willing and able to receive and send text messages
7.
Able to speak/read English or Spanish
8.
Based on a screening survey, eat grains and ≤50% of total grains are whole grains
4.1.2 Exclusion Criteria
None.
Our goal is to develop a broadly generalizable intervention. Patient demographics will be 
monitored closely during the accrual period. We aim to enroll approximately equal number of 
participants who identify as Black, Latinx, non-Latinx White, and Asian/Pacific Islander CRC 

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 12 of 30
survivors. However, participants do not have to identify with one of these race/ethnicity groups 
to be eligible.
4.2
Recruitment Methods
The recruitment and screening procedures outlined below present no more than minimal risk to 
the privacy of the patients who are screened, and a screening log containing minimal patient 
health information (Protected Health Information (PHI)) will be maintained. For these reasons, 
we seek a waiver for the purposes of 1) reviewing medical records to identify potential research 
participants and obtain information relevant to the enrollment process; 2) conversing with 
patients regarding possible enrollment, 3) handling of PHI contained within those records and 
provided by the potential participants; and 4) maintaining information in a screening log of 
patients approached.
Participants will be recruited through MyChart messages and letters from the UCSF CTSI 
Participant Recruitment Program, as well as clinician referrals at the University of California, 
San Francisco (UCSF) Helen Diller Family Comprehensive Cancer Center (HDFCCC) and the 
Zuckerberg San Francisco General (ZSFG) hospital. 
Recruitment of UCSF Patients
Potentially eligible patients may be identified through searches of the UCSF Cancer Registry, 
APeX, review of clinic schedules, and people who have participated in past studies and 
consented to be contacted about future research. The study team will review medical records of 
identified patients to assess initial eligibility. Potential participants may be contacted in clinic 
and/or e-mailed information about the study. The informational email will ask patients who do 
not wish to be called about the study to respond and let us know. If we do not hear otherwise, 
we may call patients to tell them about the study and ask if they are interested in participating. If 
they are interested, they will be asked to complete a brief screening survey either by phone or 
online using REDCap.
MyChart Recruitment at UCSF
We will also work with the UCSF CTSI’s Participant Recruitment Program to use MyChart for 
recruitment along with cohort identification and direct mail for recruitment of patients who are 
not enrolled in MyChart. MyChart (Apex) conducts a search for patients based on the study’s 
inclusion and exclusion criteria. This is a computer-aided search, meaning the computer — and 
not a person — searches patient charts. When a patient is identified as potentially eligible, they 
receive an email from MyChart that says to log in to MyChart to read about a study that they 
might be interested in. The email is short and is the same for every recipient—there is no 
patient-specific, study-specific or disease information in it. When the patient logs into MyChart, 
there is a new “Research” page with template information about participating in research and 
how to opt out of receiving recruitment messages. Then, the patient can click through to learn 
about a specific study that they may be eligible for. The study-specific language is attached to 
this submission.
Note: 1) The patient has the option of clicking a link/button to let the study team know that they 
are interested in learning more about the study. Only if the patient takes this action will the study 
team receive information about the patient. If the patient clicks “No thanks” or simply does not 
respond, they will not be contacted by the study team, they will not receive any follow-up emails 
from MyChart about this study, and their information will not be shared with the study team. 2) 
The messaging in all recruitment materials—email, MyChart research page, and study 
description—have been written to clearly state that the patient is being contacted about 
research, not clinical care. 3) We are also collaborating with the CTSI Participant Recruitment 

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 14 of 30
4.6
Assignment to Intervention
This is a single-arm study. All participants will receive the 12-week adaptive text message 
intervention.
5
Study Intervention
We aim to develop a dietary intervention that will continuously adapt text message content and 
timing based on factors that may include: participants’ sociodemographic characteristics, dietary 
behavior, and engagement with the text messages. 
Our theoretical framework is based on the Capability Opportunity Motivation-Behavior (COM-B) 
model which states that individuals’ behaviors are the result of interactions between their 
capabilities, opportunities, and motivations. Applying the model to whole grain intake, CRC 
survivors must have: 
1) capability – the physical ability to consume whole grains without side effects (e.g., gas, 
bloating, bowel frequency); knowledge and skills to select and prepare whole grains; and 
psychological capability to resist cravings and control urges for refined grains; 
2) opportunity – whole grains must be available, affordable, and socially acceptable; and 
3) motivation – motivated to eat whole grains and develop a plan for doing so. 
Intervention Components
Adaptive text messages using reinforcement learning (RL)
After completing baseline assessments, all participants will receive text messages for 12 weeks. 
Most days, participants will receive 1-2 messages. Text messages will be sent through the 
HealthySMS Platform and Twilio. Message content will target COM-B components of capability, 
opportunities, and motivations. The RL model will use a bank of text messages to target COM-B 
constructs. For example, to address psychological capability, messages will increase knowledge 
of what foods are recommended and how to prepare them. Behavior change techniques will 
include providing information, feedback, self-monitoring, and prompts/cues to increase 
knowledge. To address physical opportunity, text messages will focus on how to economically 
shop for and prepare whole grain foods. Behavior change techniques will include restructuring 
the physical environment, prompts/cues, instruction, feedback, and self-monitoring.
We will use the most up-to-date approaches for our RL model. For example, this may include a 
multi-armed bandit algorithm that predicts the outcome or “reward” (e.g., eating whole grains the 
previous day [yes/no], or servings of whole grains eaten on the previous day) based on action 
variables (e.g., whether to send a message, message type) and contextual variables (e.g., 
individual characteristics, whole grain intake yesterday/past week). RL algorithms “explore” what 
text messages to send by sending messages randomly at first and then “exploit” the information, 
so that over time, the algorithm sends more of the messages that predict more frequent intake 
of whole grains. In our proposal, participants’ replies to daily text messages asking about their 
intake of whole grains on the previous day will be used as the “reward” data.
Participants’ response rate to the daily question about whole grain intake is a primary outcome 
in this study. We will send a reminder message to participants who have not responded (e.g., 
“Please respond even if you ate 0 whole grains yesterday.”) If participants do not respond a few 
days in a row, we will send a non-response message (e.g., “We haven’t heard from you in a few 
days. Please respond to the text messages or contact our team at [study phone number].”) If a 
participant does not respond for 7 consecutive days, we may invite them to a semi-structured 

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 15 of 30
interview to understand reasons for non-response. Non-responders will continue to receive 
study text messages unless they request the messages be stopped (e.g., by texting back STOP 
or notifying the study team).  All participants, including non-responders, will be asked to 
complete the surveys at 12 weeks to gather quantitative usability and acceptability data and 
estimate the effect of the intervention on diet behavior.
Educational material
At enrollment, all participants will receive printed materials defining the recommendations for 
whole grain intake, what is a whole grain, whole grain serving sizes, and cooking tips. 
Intervention Components for Food Insecure Participants
We will use the Food Security module from the National Health Interview Survey to identify food 
insecure participants at enrollment. We will follow the standard of care at ZSFG for food 
insecure individuals: the study coordinator will provide a list of resources including food banks 
and meal delivery programs and facilitate application or SNAP benefits, if needed. 
5.1
Delivery of Study Intervention
We will use REDCap, the HealthySMS platform (developed for prior work led by Dr. Aguilera), 
UCSF’s Research Analysis Environment (RAE), and Twilio to conduct the proposed study. 
REDCap is a secure study management and database platform with mature features for online 
surveys and forms for data entry. HealthySMS is a web-based automated text messaging 
platform for use in health and social service settings, clinically and for research purposes. The 
system allows for scheduling of text messages to be sent automatically to individual patients or 
patient groups. It supports two-way communication between participants and researchers. The 
web-based platform enables the visualization of participants’ data and contains a dashboard 
that allows for viewing data from multiple participants in one screen. 
5.2
Interventionist Training and Tracking
Consistent implementation of the study protocol, measurements, and interventions is essential. 
Training manuals will be created. Data will be collected in REDCap through online surveys, 
HealthySMS and Twilio through text messages, recording of interviews on Zoom, and 
dashboards for study staff to enter data. We will monitor recruitment and study progress using a 
flow sheet template consistent with the CONSORT guidelines for reporting of feasibility trials to 
ensure we are meeting recruitment and retention goals. Members of the study team will meet 
weekly, or as needed, throughout the study.
5.3
Adherence Assessment
Intervention Adherence
Adherence to the intervention will be measured using number of replies to text messages that 
asked for a response.
Proposed Engagement Strategies for Retention 
To prevent attrition, our study staff develop good rapport and open, responsive communication 
with participants. Participants will be provided with a phone number and email address to 
contact if they encounter issues with any aspect of the study. Staff will convey reminders of 
study tasks by phone, email, and/or text messages. Participants may be compensated with gift 
cards as described in Section 4.2. If a participant does not respond to a study-related request, 
up to five automated reminders will be sent and the study staff will reach out to the participant 

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 16 of 30
via phone and/or e-mail. If we are unable to reach a participant after three more attempts, we 
will determine a participant lost to follow-up.
5.4
Participant Discontinuation/Withdrawal from the Study
Participants are free to withdraw from participation in the study at any time upon request.
An investigator may discontinue a participant from the study for the following reasons:

Unacceptable adverse event(s)

Lost-to-follow up; unable to contact participant (see Section 5.5 - Lost to Follow-Up)

Any event or medical condition or situation occurs such that continued collection of 
follow-up study data would not be in the best interest of the participant or might require 
an additional treatment that would confound the interpretation of the study

The participant meets an exclusion criterion (either newly developed or not previously 
recognized) that precludes further study participation
5.5
Lost to Follow-up
A participant will be considered lost to follow-up if he or she fails to reply to a study-related 
request after the study staff have sent the following attempts to contact:

up to five automated email reminders

study staff will reach out to the participant via phone and/or e-mail up to three more 
times
These contact attempts will be documented in the participant’s study file. Should the participant 
continue to be unreachable, he or she will be considered to have withdrawn from the study with 
a primary reason of lost to follow-up.

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 17 of 30
6
Study Procedures and Assessments
6.1
Schedule of Activities
Screening/Baseline
Study Intervention Period
End of Study
Period/Procedure
Visit -1
(D-84 to D1)
Weeks 1-12
(D1 to D84)
Study Week 12
(+/-84 days)
Administrative Procedures
Consent1
X
Medical Record Review, if available
 X2
Inclusion/Exclusion Criteria
X
Other Study Assessments
Sociodemographic and Clinical Variables survey
X
Adverse Events (Recent Health Survey)3
X
X
Dietary Assessment Survey  (FFQ)
X
X
Food Security Survey
X
X
Food Beliefs Survey (theoretical constructs)
X
X
Text Message Intervention Engagement4
Throughout
“Reasons for Non-Response” Interview
See Footnote 6
System Usability Scale (SUS)
X
Acceptability of Intervention Measure (AIM)
X
Intervention Appropriateness Measure (IAM)
X
Feasibility of Intervention Measure (FIM)
X
End of Study Interview (optional)
X
1 DocuSign or paper copy mail with prepaid return envelope
2 Participants will be allowed to self-report their clinical information if no medical records are available (e.g., patients for whom we cannot obtain records).
3 Pre-existing expected adverse events (e.g., diarrhea, constipation, etc.) will be assessed at enrollment via a Recent Health Survey containing questions from PRO-CTCAE, and 
emergent events will be assessed at 12 weeks. Medical records may be collected in the event that an SAE is observed. 
4 Measured via text message response

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 18 of 30
5 Food Security module from the National Health Interview Survey
6 Only for participants who do not respond to text messages; If a participant does not respond to text messages for 7 days, we will invite them to a semi-structured interview to 
understand reasons for non-response.

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 19 of 30
6.2
Study Procedures and Assessments
6.2.1 Screening Period / Visit -1 (Day -84 to Day 1)
Participants will complete eligibility screening online or by phone. Interested participants will 
then complete consent online via DocuSign or a paper copy of the consent will be mailed to 
them with an addressed, prepaid return envelope. The consent documents will include contact 
information for the study team, in case the potential participants have any questions. 
After an individual provides informed consent, the following activities will be performed during 
the Screening Period:

Medical record review, if available – age, insurance status, cancer diagnosis, stage, 
treatments, recurrence, metastases. This will not be required to assess eligibility.

Inclusion/exclusion criteria review

Enrollment Surveys:
o
Sociodemographic and clinical variables
o
Dietary Assessment (food frequency questionnaire; FFQ)
o
Food Security module from the National Health Interview Survey
o
Theoretical constructs assessed using a modified Food Beliefs survey 
o
Pre-existing adverse events assessed by a Recent Health Survey, using 
questions from the NCI’s Patient Reported Outcomes version of the Common 
Terminology Criteria for Adverse Events (PRO-CTCAE)
6.2.2 Study Intervention Period (Day 1-84)

Text message intervention engagement (text message responses)

Non-response interview (if applicable)
6.2.3 End of Study Intervention (Study Week 12 ± 84 days)

12-week surveys:
o
Dietary Assessment (FFQ)
o
Food Security module from the National Health Interview Survey
o
Theoretical constructs assessed using a modified Food Beliefs survey 
o
Adverse events in past 12 weeks assessed by a Recent Health Survey, using 
questions from the NCI’s Patient Reported Outcomes version of the Common 
Terminology Criteria for Adverse Events (PRO-CTCAE). Medical records may be 
collected in the event that an SAE occurs. 
o
System Usability Scale (SUS)
o
Acceptability of Intervention Measure (AIM)

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 20 of 30
o
Intervention Appropriateness Measure (IAM)
o
Feasibility of Intervention Measure (FIM)

End of study interview (optional)
6.2.4 Follow-up
Participants will not be followed after discontinuing the study intervention.
7
Reporting and Documentation of Results
7.1
Measures and Instruments
Dietary Assessment Survey (FFQ)
Participants will complete a validated food frequency questionnaire (FFQ) at enrollment and 
week 12.30 The FFQ will ask about diet in the past 3 months. For each item, participants will be 
asked to report how often, on average, they ate the specified portion size in the past 3 months. 
Participants can choose from frequency options ranging from never or less than once per month 
to ≥6 times a day. To compute calorie and nutrient intakes, we will multiply the frequency of 
consumption of each food by the amount of each nutrient in the specified portion size using 
composition values from the U.S. Department of Agriculture and other sources. 
The FFQ specifically queries intake of the following whole grain items: cooked oatmeal/cooked 
oat bran (including instant); other cooked breakfast cereal, including grits; whole wheat, whole 
grain oat, whole multigrain bread or pita; whole grain/whole wheat crackers; brown rice; whole 
grain pasta, e.g., spaghetti, macaroni; other whole grains, e.g., quinoa, barley, spelt, etc. 
Refined grains on the FFQ include: white, wheat, oatmeal (not whole grain) bread or pita; 
rye/pumpernickel bread or pita; tortillas: corn or flour, e.g., burritos, quesadillas etc.; other 
crackers; bagels, English muffins, or rolls; muffins or biscuits; pancakes or waffles; white rice; 
other pasta (not whole grain), e.g., spaghetti, noodles, macaroni, etc. Participants also report 
intake of cold breakfast cereal and the brand of cereal that they eat most often; cereal brand is 
used to classify their cold breakfast cereal intake as whole or refined grain. Using these data, 
we will calculate the percent of total grains that are whole, servings/day of whole grains and 
refined grains, and total fiber (g/d) at each time point.
The survey will be administered using REDCap. A paper FFQ will be made available for 
participants who are not able to complete the survey online.
Other Survey Data
Participants will be asked to complete additional surveys using REDCap at 0 and 12 weeks. 
Paper copies will be made available for participants who are not able to complete the surveys 
online. 
Sociodemographic and clinical factors will be assessed at baseline. 
At baseline and 12 weeks, a Recent Health Survey with questions from the NCI Patient 
Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-
CTCAE) Measurement System will be used to collect adverse events (AEs) by self-report in 
study participants.

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 21 of 30
At 0 and 12-weeks, we will use validated surveys to measure theoretical constructs: the Food 
Security module from the National Health Interview Survey and a modified Food Beliefs survey 
(which includes self-efficacy, social support, self-monitoring, etc.). 
At 12-weeks, we will assess usability and acceptability of the intervention via the System 
Usability Scale (SUS), Acceptability of Intervention Measure (AIM), Intervention 
Appropriateness Measure (IAM), and the Feasibility of Intervention Measure.31 The System 
Usability Scale (SUS) is a valid and reliable 10-item tool for measuring usability.32 The 
acceptability of each intervention component (e.g., behavior change messages, whole grain 
intake messages, educational material, food security support) will be evaluated separately.
End of study interview (optional)
Participants may be invited to complete an optional 15 to 30-minute end of study interview to 
obtain open-ended, qualitative feedback.
8
Adverse Events and Serious Adverse Events
8.1
Definition of Adverse Event (AE)
An adverse event (AE) is defined as any untoward medical occurrence associated with the use 
of an intervention in humans, whether or not considered intervention related. 
Adverse event assessment:
A Recent Health Survey with modified questions from the NCI Patient Reported Outcomes 
version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) Measurement 
System will be used to collect AEs by self-report in study participants. The survey measures 
participant-reported frequency, severity, and interference of expected symptoms and also allows 
the participant to report the severity of unexpected symptoms. Most symptoms are graded on a 
5 point Likert scale ranging from 0 to 4. Frequency responses are assessed by the question 
“How often do you have [symptom]?” and include: Never, Rarely, Occasionally, Frequently, and 
Almost constantly. Severity responses are assessed by the question “What was the severity of 
your [symptom] at its worst?” and include: None, Mild, Moderate, Severe, Very Severe. 
Interference responses are assessed by “How much did [the symptom] interfere with your usual 
or daily activities?” and include: Not at all, A little bit, Somewhat, Quite a bit, and Very much. For 
this study, assessments of frequency, severity, and interference are based on a 12-week recall 
period.
8.2
Definition of Serious Adverse Event (SAE)
A participant-reported AE that results in any of the following outcomes is defined as a Serious 
Adverse Event:

Death,

Life-threatening adverse experience*,

Inpatient hospitalization or prolongation of existing hospitalization,

Persistent or significant disability/incapacity,

Congenital anomaly/birth defect, or cancer, or

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 22 of 30

Any other experience that suggests a significant hazard, contraindication, side effect 
or precaution that may require medical or surgical intervention to prevent one of the 
outcomes listed above,

Event that changes the risk/benefit ratio of the study. 
*A life-threatening adverse experience is any AE that places the patient or participant, in the 
view of the investigator, at immediate risk of death from the reaction as it occurred, i.e., it does 
not include a reaction that, had it occurred in a more severe form, might have caused death.
8.3
Classification of Adverse Events
8.3.1 Severity
Severity of expected, non-serious AEs will be assessed using the PRO-CTCAE severity 
responses by the question “What was the severity of your [symptom] at its worst?” and include: 
None, Mild, Moderate, Severe, Very Severe.
Any participant-reported event that is deemed to be an SAE will be graded according to the 
Common Terminology Criteria for Adverse Events (CTCAE) v5.0, as developed and revised by 
the Common Therapy Evaluation Program (CTEP) of the National Cancer Institute. 
8.3.2 Attribution of SAEs
Serious adverse events are further given an assignment of attribution or relationship to study 
intervention.  Attribution categories are:

Definite – The serious adverse event is clearly related to the study intervention.

Probable – The serious adverse event is likely related to the study intervention.

Possible – The serious adverse event may be related to the study intervention.

Unrelated – the serious adverse event is clearly not related to the study intervention.
SAEs attributed to the intervention are not expected for this minimal risk study, but will 
be monitored, should they occur. 
8.3.3 Expectedness
An adverse event is considered unexpected if it is not listed at the specificity or severity that has 
been observed, or the event is not consistent with the risk information described in the general 
investigational plan or elsewhere in the current application.
8.4
Adverse Events Monitoring
This study is a minimal risk level study that does not require monitoring by the HDFCCC Data 
and Safety Monitoring Committee (DSMC) as per the National Cancer Institute-approved Data 
and Safety Monitoring Plan. Ultimately, the PI is responsible for the safety and conduct of this 
study. However, the DSMC will provide Serious Adverse Event (SAE) review (if applicable), as 
well as review of all protocol violations and consent incident reports prior to submission to the 
IRB.

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 23 of 30
8.5
Follow Up of Adverse Events
All participants who experience adverse events will be followed with appropriate medical 
management in accordance with standard of care until resolved or stabilized.
8.6
Documenting and Reporting of Adverse Events
Adverse Events that are deemed to be SAEs will be documented in the study Case Report 
Forms (CRFs) and reported to the IRB, HDFCCC DSMC, and collaborators in accordance with 
all applicable institutional and regulatory requirements.
9
Statistical Considerations
9.1
Sample Size Considerations
9.1.1 Sample Size and Power Estimate
Sample size: up to 60. 
We will consider our study to the median response proportion to text messages that ask for a 
reply is ≥ 70%, and the median Feasibility of Intervention Measure score is 4 or higher. The 
intervention will be determined acceptable if median scores on the Acceptability of Intervention 
and Intervention Appropriateness Measures are ≥4. With our sample size of 60 participants and 
assuming a standard deviation (SD) for the mean text message response rate of 25% based on 
prior work,10 we will be able to detect an average text message response rate of 70% with a 
95% CI of 64%-76%.33 
For our secondary outcome of percent of grains that are whole, using a paired t-test to compare 
mean proportion of total grains that are whole at 0 and 12 weeks, alpha=0.05, a SD=23% for the 
mean change in proportion of grains that are whole,10 20% drop out, and 60 participants, we will 
have 80% power to detect a ≥9% change in proportion of grains that are whole.34
9.1.2 Accrual Estimates

Zuckerberg San Francisco General (ZSFG) is a public safety net hospital that sees 40-50 
stage II-III CRC patients/year; 80-90% of whom identify with a racial/ethnic minority group. 
We estimate 70% will be eligible for the proposed study (~30/year). We aim to enroll 10 
participants from ZSFG.

UCSF HDFCCC GI Oncology Clinic sees ~150 cases of stage I-III CRC each year; 40% of 
whom identify with a racial/ethnic minority group. Based on prior work, ~70% of these 
patients will be eligible for the proposed study (~105/year). We have also identified over 
3,000 people who meet our clinical eligibility criteria using the CTSI Participant Recruitment 
Program services. We aim to enroll 50 participants from UCSF.
9.2
Statistical Analysis Plans
9.2.1 Primary Analysis (or Analysis of Primary Endpoints)
Descriptive Analyses: We will use descriptive statistics [means (standard deviation, SD) and 
median (interquartile range, IQR) for continuous variables and proportions for categorical 
variables] to summarize participant characteristics and baseline variables from the survey data 
as well as attrition and intervention adherence outcomes. We will quantify text message 
response rates using medians (interquartile range; IQR) for continuous variables and 
proportions for categorical variables. We will describe System Usability Scale (SUS) score, 

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 24 of 30
Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and 
the Feasibility of Intervention Measure using median (IQR). A score >68 on the SUS is above 
average usability. 
Qualitative data analysis: Audio recordings of interviews will be transcribed, translated to 
English (if needed), and imported into Dedoose software for structural coding and thematic 
content analyses. 
9.2.2 Secondary Analysis (or Analysis of Secondary Endpoints)
We will compare intake of dietary factors, including whole grains (servings/day), refined grains 
(servings/d) and total fiber (g/d), before and after the intervention using paired t-tests. For 
example, for whole grains, our null hypothesis is that there is no difference in whole grain intake, 
on average, between 0 and 12 weeks. Our alternative hypothesis is that whole grain intake is 
higher at 12 weeks, on average, compared to 0 weeks. We will use mean (95% CI) and median 
(IQR) to describe intakes at each time point and change over time for normally and non-
normally distributed continuous variables, respectively.
9.2.3 Exploratory/Correlative Analysis 
The RL algorithm will initially send messages from the three COM-B categories (capability, 
motivation, opportunity) or no message at random. If a category is predictive of subsequent 
higher whole grain intake or engagement (responses to text messages), the algorithm will begin 
to send that type of message more often. We will use one sample tests of proportions to explore 
if the proportion of text messages sent from each of the three COM-B categories or no message 
differs from 0.25. For example, for capability messages, our null hypothesis is that the 
proportion of messages targeting capability is equal to 0.25. The alternative hypothesis is that 
the proportion of messages targeting capability is not equal to 0.25.
We will also explore whether the distribution of text message type varies by sociodemographic 
factors (e.g., age, gender, race/ethnicity) using chi-square tests. For example, our null 
hypothesis is that the distribution of text message type is the same across racial/ethnic groups. 
The alternative hypothesis is that the distribution of text message type differs across 
racial/ethnic groups. 
10
Study Management
10.1
Pre-study Documentation
Before initiating this trial, the PI will have written and dated approval from the Institutional 
Review Board for the protocol, informed consent form, participant recruitment materials, and 
any other written information to be provided to participants before any protocol related 
procedures are performed on any participants.  
The PI must comply with GCP/ICH guidelines and all applicable regulatory requirements.  
10.2
Institutional Review Board Approval
The protocol, informed consent form, and all forms of participant-facing materials related to the 
study (e.g., advertisements used to recruit participants) will be reviewed and approved by the 
IRB.  The initial protocol and all protocol amendments must be approved by the IRB prior to 
implementation.  

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 25 of 30
10.3
Informed Consent
All participants will be provided a consent form describing the study with sufficient information 
for each participant to make an informed decision regarding their participation.  Participants 
must sign the IRB-approved informed consent form prior to participation in any study specific 
procedure. The participant must receive a copy of the signed and dated consent document.  
The original signed copy of the consent document must be retained in the medical record or 
research file. 
10.4
Changes in the Protocol
Once the protocol has been approved by the IRB, any changes to the protocol must be 
documented in the form of an amendment. The amendment must be signed by the PI and 
approved by the IRB prior to implementation.  
If it becomes necessary to alter the protocol to eliminate an immediate hazard to participants, an 
amendment may be implemented prior to IRB approval. In this circumstance, however, the PI 
must then notify the IRB according to institutional requirements.
The Study Chair and the UCSF study team will be responsible for updating any participating 
sites.
10.5
Case Report Forms (CRFs)
The PI and/or designee will prepare and maintain adequate and accurate participant case 
histories with observations and data pertinent to the study. Study specific Case Report Forms 
(CRFs) will document study data for safety monitoring and data analysis.  All study data will be 
entered into OnCore® or other CTMS used for the study via standardized CRFs in accordance 
with the CTMS study calendar, using single data entry with a secure access account.  Study 
personnel will complete the CRFs; the PI will review and approve the completed CRFs. 
The information collected on CRFs shall be identical to that appearing in original source 
documents. Source documents will be found in the participant’s medical records maintained by 
study personnel. All source documentation should be kept in separate research files for each 
participant. 
In accordance with federal regulations, the PI is responsible for the accuracy and authenticity of 
data entered onto CRFs.  The PI will approve all completed CRFs to attest that the information 
contained on the CRFs is true and accurate. 
All source documentation and CTMS data will be available for review/monitoring.
10.6
Record Retention
The PI is required to prepare and maintain adequate and accurate case histories that record all 
observations and other data pertinent to the investigation on each study participant. Study 
documentation includes all CRFs, data correction forms or queries, source documents, 
Sponsor-Investigator correspondence, monitoring logs/letters, and regulatory documents (e.g., 
protocol and amendments, IRB correspondence and approval, signed participant consent 
forms). Source documents include all recordings of observations or notations of clinical activities 
and all reports and records necessary for the evaluation and reconstruction of the research 
study. The PI shall retain records for a period of 2 years following the conclusion of the study.

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 26 of 30
10.7
Publications
The preparation and submittal for publication of manuscripts containing the study results shall 
be in accordance with a process determined by mutual agreement among the PI and 
collaborators.  
10.8
Multicenter Communication
The UCSF Coordinating Center provides administration, data management, and organizational 
support for the participating sites in the conduct of a multicenter study. The UCSF Coordinating 
Center will also coordinate, at minimum, quarterly conference calls with the participating sites.  
The following issues will be discussed as appropriate:

Enrollment information 

Cohort updates 

Adverse events (i.e. new adverse events and updates on unresolved adverse events 
and new safety information)

Protocol violations

Other issues affecting the conduct of the study
10.9
Regulatory Documentation
Prior to implementing this protocol at UCSF or any participating site, the protocol, informed 
consent form, and any other information pertaining to participants must be approved by the 
UCSF IRB. Prior to implementing this protocol at the participating sites, approval of the UCSF 
IRB approved protocol must be obtained from the participating site’s IRB. 
The following documents must be provided to UCSF HDFCCC before the participating site can 
be initiated and begin enrolling participants: 

Participating Site IRB approval(s) for the protocol, informed consent form, and HIPAA 
authorization 

Participating Site IRB approved consent form 

Participating Site IRB membership list 

Participating Site IRB’s Federal Wide Assurance number and OHRP Registration 
number 

Curriculum vitae and medical license (if applicable) for each investigator and consenting 
professional 

Documentation of Human Subject Research Certification training for investigators and 
key staff members at the Participating Site 
Upon receipt of the required documents, UCSF HDFCCC will formally contact the site and grant 
permission to proceed with enrollment.
11
Protection of Human Subjects
11.1
Protection of Privacy
Participants will be informed of the extent to which their confidential health information 
generated from this study may be used for research purposes. Following provision of this 
information, they will be asked to sign the HIPAA form and informed consent documents. The 

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 27 of 30
original signed document will become part of the participant’s medical records, and each 
participant will receive a copy of the signed document. The use and disclosure of protected 
health information will be limited to the individuals described in the informed consent document.
11.2
Protection from Unnecessary Harm 
Each clinical site is responsible for protecting all participants involved in human 
experimentation. This is accomplished through the IRB mechanism and the process of informed 
consent. The IRB reviews all proposed studies involving human experimentation and ensures 
that the participant’s rights and welfare are protected and that the potential benefits and/or the 
importance of the knowledge to be gained outweigh the risks to the individual. The IRB also 
reviews the informed consent document associated with each study to ensure that the consent 
document accurately and clearly communicates the nature of the research to be done and its 
associated risks and benefits. 

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 28 of 30
12 References
1.
Van Blarigan EL, Fuchs CS, Niedzwiecki D, et al. Association of Survival With 
Adherence to the American Cancer Society Nutrition and Physical Activity Guidelines for Cancer 
Survivors After Colon Cancer Diagnosis: The CALGB 89803/Alliance Trial. JAMA Oncol 2018; 
4(6): 783-90.
2.
Guinter MA, McCullough ML, Gapstur SM, Campbell PT. Associations of Pre- and 
Postdiagnosis Diet Quality With Risk of Mortality Among Men and Women With Colorectal 
Cancer. J Clin Oncol 2018: JCO1800714.
3.
Sengupta R, Honey K. AACR Cancer Progress Report 2020: Turning Science into 
Lifesaving Care. Clin Cancer Res 2020; 26(19): 5055.
4.
Brown JC, Zhang S, Niedzwiecki D, et al. Grain Intake and Clinical Outcome in Stage III 
Colon Cancer: Results From CALGB 89803 (Alliance). JNCI Cancer Spectr 2018; 2(2): pky017.
5.
Song M, Wu K, Meyerhardt JA, et al. Fiber Intake and Survival After Colorectal Cancer 
Diagnosis. JAMA Oncol 2018; 4(1): 71-9.
6.
US Department of Agriculture and US Department of Health and Human Services. 
Dietary Guidelines for Americans, 2020–2025.  DietaryGuidelinesgov. 9th ed. Washington, DC: 
US Government Publishing Office; 2020.
7.
Shams-White MM, Brockton NT, Mitrou P, et al. Operationalizing the 2018 World Cancer 
Research Fund/American Institute for Cancer Research (WCRF/AICR) Cancer Prevention 
Recommendations: A Standardized Scoring System. Nutrients 2019; 11(7).
8.
Zhang FF, Liu S, John EM, Must A, Demark-Wahnefried W. Diet quality of cancer 
survivors and noncancer individuals: Results from a national survey. Cancer 2015; 121(23): 
4212-21.
9.
Sengupta R, Honey K. AACR Cancer Disparities Progress Report 2020: Achieving the 
Bold Vision of Health Equity for Racial and Ethnic Minorities and Other Underserved 
Populations. Cancer Epidemiol Biomarkers Prev 2020; 29(10): 1843.
10.
Van Blarigan EL, Kenfield SA, Chan JM, et al. Feasibility and Acceptability of a Web-
Based Dietary Intervention with Text Messages for Colorectal Cancer: A Randomized Pilot Trial. 
Cancer Epidemiol Biomarkers Prev 2020; 29(4): 752-60.
11.
Kenfield SA, Van Blarigan EL, Ameli N, et al. Feasibility, Acceptability, and Behavioral 
Outcomes from a Technology-enhanced Behavioral Change Intervention (Prostate 8): A Pilot 
Randomized Controlled Trial in Men with Prostate Cancer. Eur Urol 2019; 75(6): 950-8.
12.
Klassen AC, Smith KC, Shuster M, et al. "We're Just Not Prepared for Eating Over Our 
Whole Life": A Mixed Methods Approach to Understanding Dietary Behaviors Among Longer 
Term Cancer Survivors. Integr Cancer Ther 2018; 17(2): 350-62.
13.
Wang EY, Graff RE, Chan JM, et al. Web-Based Lifestyle Interventions for Prostate 
Cancer Survivors: Qualitative Study. JMIR Cancer 2020; 6(2): e19362.
14.
Palmer SM, Winham DM, Oberhauser AM, Litchfield RE. Socio-Ecological Barriers to 
Dry Grain Pulse Consumption among Low-Income Women: A Mixed Methods Approach. 
Nutrients 2018; 10(8).
15.
Dave JM, Thompson DI, Svendsen-Sanchez A, McNeill LH, Jibaja-Weiss M. 
Development of a Nutrition Education Intervention for Food Bank Clients. Health Promot Pract 
2017; 18(2): 221-8.
16.
Burden S, Jones DJ, Sremanakova J, et al. Dietary interventions for adult cancer 
survivors. Cochrane Database Syst Rev 2019; 2019(11).
17.
Basen-Engquist K, Alfano CM, Maitin-Shepard M, et al. Agenda for Translating Physical 
Activity, Nutrition, and Weight Management Interventions for Cancer Survivors into Clinical and 
Community Practice. Obesity (Silver Spring) 2017; 25 Suppl 2: S9-S22.

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 29 of 30
18.
Hall AK, Cole-Lewis H, Bernhardt JM. Mobile text messaging for health: a systematic 
review of reviews. Annu Rev Public Health 2015; 36: 393-415.
19.
Pew Research Center. Mobile Fact Sheet. Internet & Technology Web site.  (accessed 
[2019.
20.
Willcox JC, Dobson R, Whittaker R. Old-Fashioned Technology in the Era of "Bling": Is 
There a Future for Text Messaging in Health Care? J Med Internet Res 2019; 21(12): e16630.
21.
Fadhil A, Wang Y, Reiterer H. Assistive Conversational Agent for Health Coaching: A 
Validation Study. Methods Inf Med 2019; 58(1): 9-23.
22.
Steinberg DM, Levine EL, Askew S, Foley P, Bennett GG. Daily text messaging for 
weight control among racial and ethnic minority women: randomized controlled pilot study. J 
Med Internet Res 2013; 15(11): e244.
23.
Chan JM, Van Blarigan EL, Langlais CS, et al. Feasibility and Acceptability of a 
Remotely Delivered, Web-Based Behavioral Intervention for Men With Prostate Cancer: Four-
Arm Randomized Controlled Pilot Trial. J Med Internet Res 2020; 22(12): e19238.
24.
Forman EM, Kerrigan SG, Butryn ML, et al. Can the artificial intelligence technique of 
reinforcement learning use continuously-monitored digital data to optimize treatment for weight 
loss? J Behav Med 2019; 42(2): 276-90.
25.
Creswell JW, Klassen AC, Plano Clark VL, Clegg Smith K, With the Assistance of a 
Specially Appointed Working Group. Best Practices for Mixed Methods Research in the Health 
Sciences: Office of Behavioral and Social Sciences Research (OBSSR), 2013.
26.
Aguilera A, Figueroa CA, Hernandez-Ramos R, et al. mHealth app using machine 
learning to increase physical activity in diabetes and depression: clinical trial protocol for the 
DIAMANTE Study. BMJ Open 2020; 10(8): e034723.
27.
Snyder DC, Morey MC, Sloane R, et al. Reach out to ENhancE Wellness in Older 
Cancer Survivors (RENEW): design, methods and recruitment challenges of a home-based 
exercise and diet intervention to improve physical function among long-term survivors of breast, 
prostate, and colorectal cancer. Psychooncology 2009; 18(4): 429-39.
28.
Winters-Stone KM, Lyons KS, Dieckmann NF, Lee CS, Mitri Z, Beer TM. Study protocol 
for the Exercising Together(c) trial: a randomized, controlled trial of partnered exercise for 
couples coping with cancer. Trials 2021; 22(1): 579.
29.
Demark-Wahnefried W, Morey MC, Sloane R, et al. Reach out to enhance wellness 
home-based diet-exercise intervention promotes reproducible and sustainable long-term 
improvements in health behaviors, body weight, and physical functioning in older, 
overweight/obese cancer survivors. J Clin Oncol 2012; 30(19): 2354-61.
30.
Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC. 
Reproducibility and validity of an expanded self-administered semiquantitative food frequency 
questionnaire among male health professionals. Am J Epidemiol 1992; 135(10): 1114-26; 
discussion 27-36.
31.
Weiner BJ, Lewis CC, Stanick C, et al. Psychometric assessment of three newly 
developed implementation outcome measures. Implement Sci 2017; 12(1): 108.
32.
U.S. General Services Administration Technology Transformation Service. System 
Usability Scale (SUS). https://www.usability.gov/how-to-and-tools/methods/system-usability-
scale.html. Published 2020 (accessed October 9, 2020).
33.
Hulley SB, Cummings SR, Browner WS, Grady DG, Newman TB. Designing clinical 
research: an epidemiologic approach. 4th ed. Philadelphia, PA: Lippincott Williams & Wilkins; 
2013.
34.
Harnack L, Block G, Subar A, Lane S, Brand R. Association of cancer prevention-related 
nutrition knowledge, beliefs, and attitudes to cancer prevention dietary behavior. J Am Diet 
Assoc 1997; 97(9): 957-65.

UCSF Helen Diller Family Comprehensive Cancer Center
Version date: 12-01-2023
Protocol CC#: 224523
Adaptive text message-based intervention
Page 30 of 30
35.
Avila-Garcia P, Hernandez-Ramos R, Nouri SS, et al. Engaging users in the design of 
an mHealth, text message-based intervention to increase physical activity at a safety-net health 
care system. JAMIA Open 2019; 2(4): 489-97.