Helping Patients and Providers Make Better Decisions About Colorectal Cancer Screening
Phase: NA
Conditions: Cancer Screening Tests
Sponsor: Indiana University

 
 
 
 
 
Helping Patients and Providers Make Better Decisions about 
Colorectal Cancer Screening 
 
ClinicalTrials ID#:  NCT04683731 
 
May 1, 2023 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
 
 
 
 
Helping Patients and Providers Make Better Decisions about  
Colorectal Cancer Screening 
 
 
Principal Investigator: Peter H. Schwartz, PhD, MD 
Department of Medicine, Indiana University School of Medicine 
 
 
 
 
Support Provided by: 
Patient-Centered Outcomes Research Institute (CDR-2018C3-14715) 
Measuring the Impact of Providing Personalized Risk Information to Patients and their Providers 
 
 
 
IRB #:  2004109966 
ClinicalTrials ID#:  NCT04683731 
 
 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
 
 
 
Table of Contents: 
 
Study Schema 
Specific Aims ........................................................................................................... 3 
1.0 
Background & Rationale ......................................................................................... 4 
2.0 
Approach ................................................................................................................. 9 
2.1 
Primary Objective ....................................................................................... 5 
2.2 
Secondary Objective ................................................................................... 6 
3.0 
Outcome Measures ............................................................................................... 10 
3.1 
Primary Outcome Measures ..................................................................... 12 
3.2 
Secondary Outcome Measures ................................................................. 12 
3.3 
Additional Measures ................................................................................. 13 
4.0 
Eligibility Criteria 
4.1 
Inclusion Criteria ....................................................................................... 13 
4.2 
Exclusion Criteria....................................................................................... 13 
5.0 
Study Design.......................................................................................................... 14 
6.0 
Enrollment/Randomization .................................................................................. 16 
7.0 
Study Procedures .................................................................................................. 17 
8.0 
Reportable Events ................................................................................................. 20 
9.0 
Data Safety Monitoring ......................................................................................... 20 
10.0 
Statistical Considerations ...................................................................................... 20 
11.0 
Statistical Data Management................................................................................ 21 
12.0 
Privacy/Confidentiality Issues ............................................................................... 21 
13.0 
References ............................................................................................................ 23 
14.0 
Appendix 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 3 
 
A.  SPECIFIC AIMS:   The colorectal cancer (CRC) screening rate in the U.S. remains under 65%,1 
significantly lower than for breast and cervical cancer (RQ-3).2-4 This low rate means that thousands of 
people die of CRC unnecessarily.  Precision CRC prevention – providing information about an individual’s 
specific risk for CRC – has great promise to increase uptake and improve decision making.  This 
approach, however, has not been widely tested or adopted. 
 
Low uptake of CRC screening is due, in part, to providers’ offering only colonoscopy, which many 
patients are reluctant to undergo.  Studies show that uptake increases when patients are offered non-
invasive options such as the fecal immunochemical test (FIT) or DNA/FIT test (Cologuard),5 for which 
only some patients require a follow-up colonoscopy.6  Fully considering all options requires knowing the 
comparative effectiveness of the tests, which depends, in part, on a person’s current risk of advanced 
colorectal neoplasia (ACN), i.e. a CRC or advanced, precancerous polyp.7-12  Colonoscopy has greater 
effectiveness in patients with a higher risk of ACN than in those with a lower risk, due to the higher 
likelihood of detecting and removing it.7,13  As ACN risk gets smaller, the comparative effectiveness of 
colonoscopy decreases, and the attractiveness of non-invasive options increases. 7,13 Even among 
individuals with “average risk,” i.e. without a family history or medical condition that confers high risk 
for CRC, the risk of ACN varies greatly, as much as 10-fold (22% vs. 2%).7  
 
Our research team has developed and pilot tested a CRC screening decision aid and provider message 
that discloses the patient’s current risk of ACN, based on a prediction rule that was developed and 
validated by Dr. Tom Imperiale, a member of our team.7,8  The Imperiale rule has important advantages 
over others: it uses just five variables that are easy to collect and identifies a wide range of risk for 
current ACN among average risk patients.  For patients with “high-average” risk (22%), personalized 
messages in our decision aid and provider notification highlight the advantage of colonoscopy because 
of the likelihood of finding and removing an ACN.  For patients at low risk for ACN (2% or 4%), 
personalized messages highlight the advantage of stool testing, due to the relatively low chance of 
failing to detect ACN.   
 
In our pilot testing, personalized messages including ACN risk increased patients’ intent to be screened 
and influenced their test choice.  Over 95% of patients (156 of 160) who viewed personalized 
information agreed that others considering screening should receive this information.  Providers rated 
the personalized message as helpful in 93% of cases presented to them (26 of 28), and the personalized 
message changed their recommended test in 57% (16 of 28).  Working with our partner health systems, 
we have piloted a system that holds promise for delivering decision aids to patients effectively and 
affordably in clinics, through the patient portal of electronic health record systems.   
 
Study Aims: Our long-term goal is to increase uptake of CRC screening by informing and improving 
patient and provider discussion and decisions. The main objective of this application is to test whether 
providing patients and their providers with personalized messages about ACN risk results in higher 
screening uptake and higher decision quality (i.e., informed choice and receipt of the preferred 
screening test), compared to an approach that does not utilize ACN risk.   
 
Aim 1:  To measure the impact on patient decision quality and screening uptake of providing patients 
and their providers with personalized messages about the patient’s current risk of having advanced 
colorectal neoplasia (ACN).   
Primary hypotheses:  The proportion of patients who make a high-quality decision and complete 
screening at six months will be higher 
1.1 for patients who receive the personalized message than those who do not, and 
1.2 for patients whose providers receive the personalized message than those whose providers 
do not. 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 4 
 
 
Aim 2:  To examine mediators and moderators of the interventions’ effectiveness. 
 
 Study Design:  To achieve these aims, we will conduct a 2x2 design, cluster randomized, controlled trial 
(see Table 1) to compare decision quality and screening uptake in four groups of patients who view a 
decision aid:   
• 
Group 1) without the personalized message and whose providers do not receive the 
personalized message (control group), 
• 
Group 2) with the personalized message and whose providers do not receive the personalized 
message, 
• 
Group 3) without the personalized message and whose providers receive the personalized 
message, and  
• 
Group 4) with the personalized message and whose providers receive the personalized message. 
 
Our study is innovative since it employs a 
newly developed ACN prediction rule and 
informs patients and their providers about 
the implications of this risk level for test 
choice utilizing an electronic health record.  
Our study is significant since it will identify 
the impact of providing personalized information to providers and patients and will collect information 
 
 
1.0 
Background & Rationale 
 
CRC Screening:  Colorectal cancer (CRC) is the second-largest cancer killer in the U.S., and low screening 
rates leads to thousands of preventable deaths.  Each year, over 140,000 people are diagnosed with CRC 
and more than 50,000 die.2  Under 65% of eligible adults are current with screening, a rate that pales in 
comparison to breast and cervical cancer screening.2-4 Raising the CRC screening rate to 80% by 2018, 
which was the Colorectal Cancer Roundtable’s goal, would have prevented over 20,000 deaths from CRC 
per year and 203,000 deaths by 2030.14 
 
“Precision prevention” in this area is a promising way to motivate screening and help patients choose 
the best test for them.  Leading guidelines approve multiple testing strategies, including colonoscopy 
every 10 years, flexible sigmoidoscopy every five years, annual stool testing with high-sensitivity fecal 
occult blood testing (FOBT) or fecal immunochemical testing (FIT), or stool testing for high risk DNA.4,6,15  
Colonoscopy is the most sensitive and specific for identifying polyps or cancers,15-17 and is best known. 
But it is an invasive procedure involving a lengthy preparation, IV sedation, and the need to take a day 
off. There are significant risks, including hemorrhage and perforation.6  
 
Stool (or fecal) blood testing is the second most commonly utilized approach, and many patients prefer 
stool testing to colonoscopy when they are informed about both tests.18-24 We concentrate here on FIT 
since it is widely used and available nationwide, and is recommended by all major guideline 
organizations.4,6,15 Stool blood testing may be done in the privacy of one’s home, is low cost, and 
requires no preparation.  The main limitations are that it must be done annually, it requires the patient 
to handle stool, and all positive tests require evaluation with colonoscopy.  Newer forms of stool testing, 
such as Cologuard, which combines FIT with testing for high risk DNA, are being used relatively rarely, 
and they can be considered similarly to FIT for this application, except that they may be performed 
every 3 years.6 
 
TABLE 1 
Patient views: 
Provider receives: 
Decision aid WITHOUT 
personalized message  
Decision aid WITH 
personalized message  
Screening reminder  
Group 1 
Group 2 
Screening reminder + 
Personalized message 
Group 3 
Group 4 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 5 
 
Primary care providers often fail to describe alternatives to colonoscopy,25-27 causing patients who are 
reluctant to undergo this test put off screening entirely, instead of choosing the less invasive stool test 
(RQ-3).  In a recent study, an outreach program that recommended just colonoscopy for screening 
resulted in a 38% uptake, while recommending a stool test or offering a choice between colonoscopy 
and stool test resulted in uptake of 67% and 69%, respectively.5   Multiple national organizations 
recommend that providers describe and explain the alternatives to colonoscopy.  A slogan used by the 
80 by 2018 initiative declares that “The best CRC screening test is the one that gets done.”28,29 
 
Precision prevention:  Guidelines recommend only colonoscopy for patients with particularly high risk 
for CRC, such as those with a significant family history, a genetic condition such as Lynch syndrome, or 
inflammatory bowel disease.4,30  Approximately 90% of patients lack these risk factors and are 
considered “average risk,” so can choose any CRC screening test, according to guidelines. But even 
within this average risk group, people have varying chances of having an “advanced colorectal 
neoplasm” (ACN), i.e. a colorectal cancer or precancerous polyp.7,8   A polyp counts as “advanced” if it is 
greater than 1 cm or has high-risk pathology, e.g. villous histology or high-grade dysplasia. 
 
An individual’s chance of currently having an ACN affects the comparative effectiveness of CRC 
screening tests, and, thus, is relevant information for making a screening test decision. Colonoscopy has 
higher effectiveness in patients who have a high probability of having a current ACN because of the 
larger chance that colonoscopy will identify a dangerous that should be removed.7,13  Nearly all ACN are 
polyps rather than cancers (15:1 ratio in a recent study),7 and polyps are considered the prime target of 
screening since they can be removed to prevent cancer.12   
 
In patients whose probability of having a current ACN is lower, the burdens associated with colonoscopy 
may be difficult to justify since the chance of finding a lesion that should be removed is lower.  And the 
chance that FIT or Cologuard will fail to identify a dangerous polyp or cancer is lower in a patient with 
lower baseline risk of ACN.  FIT and Cologuard are approved for all average risk patients because they 
provide long-term risk reduction in colorectal cancer that rivals colonoscopy.31,32  Still, failing to identify 
a polyp or cancer in the colon is a negative outcome of screening (a “false negative”),32 so it is important 
that the chance of this occurring is smaller in patients with lower baseline risk of ACN. 
  
Validated, usable rules for estimating the probability of current 
ACN in average risk patients are available.  Our study utilizes a 
prediction rule that was validated for individuals receiving their 
first screening colonoscopy who do not have a risk factor that 
would place them at elevated risk for CRC (Imperiale et al. 
2015).7  Table 1 shows the risk level and percent of patients 
placed in each category in a validation set of 1467 patients.7  
The rule has three advantages over previous rules:  First, it calculates risk of ACN using variables that are 
easy to collect:  age, gender, smoking history, waist circumference, and family history.  Second, the 
Imperiale rule identifies a wider range of probabilities in chance of having ACN than previous rules.11,33-37  
Third, the Imperiale rule classifies a significant percentage of average-risk patients into high-average and 
low risk.  Fully 53% of the population have low or very-low ACN-risk, and 15% have high-average risk.  
 
This risk stratification has clear implications for the comparative effectiveness of tests: 
• 
Probability that screening colonoscopy will find an ACN:  The chance of identifying and removing 
an ACN is five-times higher when performing colonoscopy in an individual with high-average of 
ACN (22% chance) than in someone with low risk (4% chance), and 10-times higher than an 
individual with very low risk (2% chance).   
TABLE 1 
Individual’s  
Risk level  
Probability of 
current ACN 
Percent of 
Patients 
Very low  
2% 
8% 
Low 
4% 
45% 
Intermediate 
10% 
30% 
High-average 
22% 
15% 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 6 
 
• 
Probability that a single application of FIT will fail to identify an ACN:  Performing a FIT on each 
member of a high-average risk population will fail to identify ACN in about 11% of individuals, 
vs. just 2% of individuals in a low-risk population, and 1% in a very-low-risk population.   
A patient’s chance of current ACN, therefore, impacts test choice in a way other calculations do not. 
Some calculators, such as the NCI’s CRC Risk Assessment Tool,38,39 provide an estimate of future risk of 
CRC, but such information has no direct link to selecting a test: Having a chance of cancer in the next 10 
years of 0.5% vs. 3% – the probabilities for the lowest quintile and the highest quintile for the NCI CRC 
risk tool40 – does not clearly support one test over another. 
 
Potential to improve healthcare decisions and outcomes:  Our study will fill gaps left by previous 
studies in two key ways.  First, it will use the Imperiale rule, which provides a more robust discrimination 
among average risk patients in their risk for current ACN.7  Second, the personalized risk message for 
patients and providers explains how current ACN risk can inform choice of screening test.   
 
Disclosing information about a patient’s risk of having a current ACN has potential to increase uptake of 
screening.  Letting patients know that their chance of having an ACN is low can support decisions to 
choose and complete the FIT test.  Knowing that a patient who prefers FIT has low ACN risk may help 
providers overcome their hesitancy to order this test, by reassuring them that the chance of FIT’s 
missing a cancer or dangerous polyp for this patient is low.  Informing patients and providers that the 
patient has a high-average risk for an ACN can motivate discussion of screening colonoscopy and 
completion of that test.   
 
At a system level, guiding patients at high-average risk toward colonoscopy and those with low-average 
risk to FIT could improve the efficiency of screening.7,10,11,44  While colonoscopy is an effective screening 
test for all individuals with average risk from ages 50 to 75, it is more cost-effective for those with higher 
chance of ACN.  If all eligible patients chose colonoscopy, endoscopy centers would be overwhelmed.45-
47  Given that the recently validated rule found that over 50% of the population had low- or very-low risk 
of having an ACN, the impact on reducing over-use of colonoscopy and the cost of CRC screening could 
be substantial. 
 
Gaps in the evidence (RQ-1): Information about the probability of current ACN has not been 
incorporated into screening discussions for two reasons:  First, randomized trials have not shown clear 
benefits of disclosing ACN risk.  Second, no tools exist to quickly calculate patients’ probability of ACN 
and convey that information clearly to patients and providers.   
 
Skinner and colleagues (2015, 2016) – including Dr. Rawl, a member of our team – created and tested 
the tablet-based Cancer Risk Intake System, which identifies individuals’ risk factors and screening 
barriers.  Patients and their providers were given a printout summarizing the risk factors and barriers.  
High-risk patients, i.e. those with certain medical conditions or family history, were directed towards 
colonoscopy. Average-risk patients, i.e. without these risk factors, were told they could choose 
colonoscopy or stool blood testing.  The tailored print out resulted in an increased level of discussion of 
CRC screening and increased uptake in patients eligible for screening.41,42  Patients were not told their 
chance of an ACN, and those at average risk were not told whether their risk was high-average, 
intermediate, or low.   
 
Schroy et al. (2016) studied the impact of providing information to average risk patients about their 
probability of having an ACN.  In this study, 341 patients with average risk for CRC viewed a decision aid 
about CRC screening and half were randomized to be told their personal risk of currently having an ACN, 
either “low” (3%), or “intermediate/ high” (8%).  All patients were given a handout with this information 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 7 
 
to share with their healthcare provider.43 This information had no significant impact on any of the 
measured outcomes, including screening choice.   
 
These studies leave important gaps in the evidence (RQ-1).  Skinner et al. (2015,2016) did not assess the 
impact of telling average-risk patients about having low vs. high-average risk for CRC and provided no 
guidance to average risk patients regarding the impact of risk factors or risk level on test choice.  Schroy 
et al. (2017) provided average-risk patients with information about current probability of ACN but the 
difference between “low” and “intermediate/high” groups was just 3% vs. 8%, The small magnitude of 
this difference may have minimized impact.  In addition, patients and providers in Schroy’s study 
received no guidance about how to utilize ACN probability information to choose a screening test.  
Without an explanation why high risk for current ACN may be a reason to choose colonoscopy, or why 
low risk for ACN can support use of FIT, patients and providers may not make those connections. (RQ-4) 
 
Patient and provider interest in research questions and outcomes: Patient interest (RQ-6, PC-1):  In our 
pilot studies, patients have endorsed the importance of personalized information about CRC risk and 
probability of current ACN:  
• 
Out of 57 patients who saw an estimate of their risk of current ACN, all 57 (100%) agreed or 
strongly agreed that “The information is important to me,” and 55 (95%) agreed or strongly 
agreed that “I would recommend this information to other people.”   
• 
Out of 102 patients who saw a calculation of their personal risk of developing CRC in their 
lifetime, based on the NCI’s Colorectal Cancer Risk Assessment Test,38 and risk reduction 
provided by screening test, 100 (98%) agreed or strongly agreed that “The information is 
important to me,” and 101 (99%) agreed or strongly agreed that “Other people should have 
similar information.” 
Our pilot studies also confirmed that viewing personalized information about CRC risk and probability of 
ACN increased intent to be screened and impacted test choice.  These findings confirm our impression 
from our recently completed public deliberation, where patients expressed high interest in receiving 
quantitative information about the risk for CRC (RQ-6, PC-1).  In a recent qualitative study, a patient said 
he would get FIT if he had low risk, since he really didn’t want to go through colonoscopy anyway:  “As 
much as I wanted to have the relief of knowing, I really didn’t want to go through the pain.”50 
 
Provider interest:  In a survey of 57 PCPs, 95% (n=56) preferred colonoscopy for CRC screening, but the 
majority considered patient risk level (67%) and patient preference (63%) as important factors in 
choosing a screening test.10  When informed about the possibility of “an electronic risk index that could 
accurately stratify their average-risk patients into low-, intermediate- or high-risk categories for the 
likelihood of ACN,” 97% stated they would be likely to use this tool “often” or “sometimes.”  In key-
informant interviews, 9 PCPs said that risk stratification of patients eligible for CRC screening would be 
helpful to their discussions of screening (PC-1)(RQ-6).10   
 
Two pilot studies by our team had similar findings.  In our pilot testing of our provider messages about 
ACN risk, PCPs rated 26 out of 28 messages as very or somewhat helpful (See Methods, Choice of 
Comparators, p. 7, below)  A qualitative study with 15 PCPs found significant support for use of the 
Imperiale ACN rule (RQ-6)(PC-1).50  PCPs emphasized the importance of the rule providing an overall risk 
score that could help convince patients to be screened and the ability of such a rule to support 
discussions about CRC screening and consideration of FIT for some patients (RQ-6)(PC-1).  One PCP said, 
that it “… seems more…appropriate...more rational, and maybe even a little bit safer, if we could avoid 
doing colonoscopies on patients with very low risk. It seems like a better balance of risk and benefit.”50 
Some PCPs pointed to the similarity between this rule and risk calculations made on use of cholesterol 
medications.  Potential barriers include limited time, questions about validity, and absence of national 
guidelines recommending its use. 50 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 8 
 
 
Cross cutting implications:  Our decision aid and provider message for CRC screening exemplifies an 
approach that highlights providing simple information that is directly linked to decisions at hand. This 
approach could be a model far beyond CRC screening (RQ-1).  The information we will gather about 
implementing a system for providing decision aids through the patient portal of EHRs, and for sending 
provider notifications, will apply to other areas 
 
Engagement (PC-1), Dissemination, and Implementation:  In developing this proposal, we actively 
engaged with patients, partner healthcare systems leadership, providers, and staff, local patient 
advocacy groups, and national organizations involved in CRC screening and we will continue this 
engagement throughout the project.  A separate research protocol was developed to address our plan 
for studying the facilitators and barriers to implementing a system for providing decision aids to 
patients, and for sending provider notifications. 
 
Patients:   Development of proposed study:  The patient advisory board of our previous study repeatedly 
asked about ways to calculate CRC risk levels for individuals and said that they would find such 
information helpful.  Members of our patient advisory board were involved in development and pilot 
testing of the personalized-messages and decision aid.    
• 
Involvement in upcoming study:  Four of the patients who served on the patient advisory board 
in the last study will serve as patient consultants and will attend research team meetings and work 
independently in concert with the team.  Patient consultants will review and edit recruitment letters, 
phone call scripts, decision aids, and outcome measures.  They will also continuously review our 
information regarding providing decision aids through the EHR patient portal.  Patient consultants will 
get input from family and friends at key points. (PC-1) 
• 
Dissemination:  Patient consultants will accompany other research team members to national 
meetings, and may serve as panel members or discussants. (PC-4) 
 
Leadership of partner healthcare systems:  Development of proposed study:  IU Health and Eskenazi 
leadership and quality improvement teams have always worked closely with our research team on CRC 
screening projects due to our shared interest in increasing CRC screening uptake rate.  More recently, 
we have developed the proposal to provide decision aids through the patient portal of the EHR systems 
(Epic at Eskenazi, Cerner at IU Health).  Both institutions wish to use these portals more frequently in 
patient care.  We have worked closely with the information technology teams at both institutions to 
develop this plan and pilot the system at Eskenazi.  (PC-1) 
• 
Involvement in upcoming study:  In our previous studies, the quality improvement teams at IU 
Health and Eskenazi Health worked with the research team by serving on a community advisory board.  
A separate research protocol was developed to address our plan for studying the facilitators and barriers 
to implementing a system for providing decision aids to patients, and for sending provider notifications 
(PC-1) 
• 
Dissemination and Implementation:  Leadership at both institutions intend to implement 
research findings regarding how to use patient portals to distribute decision aids, with or without 
personalized information. (PC-4) 
 
Providers and Staff of partner healthcare systems:  Development of proposed study:  Providers at IU 
Health and Eskenazi who participated in previous studies by serving on the stakeholder advisory board 
or allowing us to enroll their patients provided important input on developing this study.  Providers also 
participated in pilot testing of the provider message. 
• 
Involvement in upcoming study:   Decision aid:  Before initiating the study, staff and providers 
from participating clinics will view the decision aids and provide feedback on content and plan for 
providing to patients through the online portal, including timing in relation to an upcoming visit.  

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 9 
 
Changes will be made based on this feedback.  A separate research protocol was developed to address 
our plan for studying the facilitators and barriers to implementing a system for providing decision aids 
to patients.  
• 
Involvement in upcoming study:  Provider notification:  Providers will provide feedback on draft 
versions of the message and will identify preferred timing for receiving the message (i.e. how long 
before patient visits).  A separate research protocol was developed to address our plan for studying the 
facilitators and barriers to implementing a system for sending provider notifications  We will also 
quantify the percentage of provider notifications that were read by each provider and will evaluate 
characteristics of providers who opened a high percentage vs. a low percentage of messages, including 
elements of practices for high and low users, such as staff communications and leadership support. (PC-
1) 
• 
Implementation:  Staff and providers involved in this engagement will potentially become 
champions and “super users” for future implementation of decision aids and provider notifications in 
their clinics. (PC-4) 
 
National organizations and local patient advocates:  Development of proposed study:  The development 
of the proposed study has been informed by engagement with local and regional groups that have 
served as key partners previously, including the American Cancer Society and Little Red Door cancer 
agency.  We have had involvement of national leaders such as co-investigator Brian Zikmund-Fisher, 
PhD, and consultants Paul Han, MD, MA, and Michael Barry, MD.  For preparing the current 
resubmission, Jon Keevil, MD, Vice President for clinical decision support at EBSCO provided an industry 
perspective.  We benefited from input from leadership of national groups focused on CRC screening, 
including Richard Wender, MD, Chair of the National Colorectal Cancer Roundtable, and Chief Cancer 
Control Officer of the American Cancer Society, and David Lieberman, MD, President of the American 
Gastroenterology Association.   
• 
Involvement in upcoming study:  These individuals and groups have agreed to remain involved in 
the study as a National Engagement and Dissemination Team, which will hold three-times-per-year 
teleconferences, to discuss the design, conduct, results, and potential implications of our study. If the 
study is funded, additional members will be recruited.  Regional group representatives will also 
participate in teleconferences. Dr. Zikmund-Fisher and Dr. Han will bring a national perspective to the 
research team and will provide external review and edits for all materials and plans. 
Implementation:  This broad involvement will keep our focus on implementation throughout the project.  
The representatives of prominent national groups will provide avenues for dissemination.  Through 
these groups, we will make the decision aids, provider notifications, and materials for distribution of the 
decision aid by the electronic health record, available to interested healthcare systems and providers. 
(PC-4) 
 
 
2.0 
Approach 
 
Study Aims: Our long-term goal is to increase uptake of CRC screening by informing and improving 
patient and provider discussion and decisions. The main objective of this study is to test whether 
providing patients and their providers with personalized messages about ACN risk results in higher 
screening uptake and higher decision quality (i.e., informed choice and receipt of the preferred 
screening test), compared to an approach that does not utilize ACN risk. 
 
Aim 1:  To measure the impact on patient decision quality and screening uptake of providing patients 
and their providers with personalized messages about the patient’s current risk of having advanced 
colorectal neoplasia (ACN).   
 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 10 
 
Aim 2:  To examine mediators and moderators of the interventions’ effectiveness. 
 
To achieve Aim 1, we will test the following hypotheses:   
Primary hypotheses:   
1.  The proportion of patients who make a high-quality decision and complete screening at six months 
will be higher:  
1.1  for patients who receive the personalized message than for those who do not, and 
1.2  for patients whose providers receive the personalized message than for those whose providers 
do not. 
Secondary hypotheses:    
2. Among patients with low risk of ACN, the proportion who make a high-quality decision and undergo a 
stool blood test (FIT) by six months will be higher 
2.1  for patients who receive the personalized message than for those who do not, and   
2.2  for patients whose providers receive the personalized message than for those whose providers 
do not. 
3.  Among patients with high-average risk of ACN, the proportion who make a high-quality decision and 
undergo a colonoscopy by six months will be higher 
3.1  for patients who receive the personalized message than for those who do not, and   
 for patients whose providers receive the personalized message than for those whose providers do not. 
 
 
3.0 
Outcome Measures/Endpoints 
 
Choice of Outcomes (PC-3, RQ-6):   The primary outcomes are screening uptake and decision quality, 
each of which is essential to providing high-quality and patient-centered care.   
• 
Screening uptake will be defined as performance of colonoscopy, FIT, or another approved 
screening test within six months after enrollment, as documented in the EHR, as in our previous study.51   
• 
Decision quality will be defined by the multi-dimensional measure of informed consent 
(MMIC),53 where a high-quality decision is one where the individual has adequate knowledge regarding 
the available options and undergoes the intervention that he or she has chosen or that fits his or her 
values (“value concordance”) (PC-3)(RQ-6).  Sepucha et al. (2018) recently used the MMIC approach in 
the Colorectal Cancer Screening Decision Quality Instrument (CRC-DQI).54  We will identify knowledge 
and the patient’s intention to be screened shortly after a provider visit (T2).  We will measure 
concordance between the test choice at T2 and screening test underwent, if any, within six months after 
enrollment (T3).55-58 
 
Increasing screening uptake is an essential outcome since screening saves lives (RQ-6).  Providers and 
healthcare institutions aim to get their patients screened, heeding the ethical principle of beneficence.59  
Our partner healthcare institutions have repeatedly expressed their desire to increase their screening 
rates(RQ-6). We heard the same message – the importance of getting patients screened – from lay 
people participating in our public deliberation exercise (RQ-6).60   Both patients and lay people have 
emphasized, from the beginning of our work on CRC screening, and in the public deliberation, the 
importance of improving decision quality about CRC screening.(RQ-6)  Patients who view decision aids as 
part of our studies often learn about FIT for the first time, and often respond that there should be more 
public awareness of this option.(RQ-6) 
 
We chose not to make decision conflict61 or shared decision-making distal outcomes, due to our focus 
on screening uptake and quality of decision making.  However, we will collect these subjective measures 
as potential mediators for the primary outcomes.  Improved outcomes may result from patients feeling 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 11 
 
more supported in their decision making, as captured by the decision conflict scale,61 or feeling that they 
participated in shared decision making with their healthcare provider, as captured by one section of the 
CRC Screening Decision Quality Instrument developed by Sepucha et al (2018).54 
 
Theoretical framework:  See Figure 1: (CI-1)  Our theoretical framework is based on the Health Belief 
Model,62 which has been previously applied to research on CRC screening uptake.63-65  We expect the 
personalized message to impact patients at low risk, intermediate risk, and high-average risk, as 
described below: 
• 
Low risk:  For patients at low risk, patients and providers who view the personalized message 
will have increased perceived benefit of FIT and lower perceived barriers (i.e. concern over false 
negative result).  These effects will increase the proportions of patients intending to be screened and to 
undergo FIT, and the proportion of providers who are willing to order FIT for patients who choose that 
test.  Agreement between the patient’s choice and the provider’s ordered test will increase uptake 
(Hypothesis 1.1 and 2.1),43  and higher concordance between patient choice and completed FIT will 
increase decision quality as measured by the MMIC (Hypotheses 1.2 and 2.2).(RQ-4)(CI-1) 
• 
High-average risk:  For patients with high-average risk, patients and providers who view the 
personalized message will have increased perceived susceptibility to CRC due to the high probability of a 
current ACN (22%) and increased perceived benefit of colonoscopy.  These effects will increase the 
proportions of patients intending to be screened with colonoscopy, and the proportion of providers who 
order colonoscopy for patients who choose this test.  This will result in increased uptake of screening 
(Hypotheses 1.1 and 3.1) and increase concordance between patient choice and performed test, which 
will increase decision quality as measured by MMIC (Hypotheses 1.2 and 3.2).(RQ-4) 
• 
Intermediate risk:   For patients with high-average risk, patients and providers who view the 
personalized message will have increased perceived susceptibility to CRC due to the significant 
probability of a current ACN (10%).  This will increase patients’ intention to be screened, providers’ 
interest in discussing CRC screening and ordering a test, and successful follow through by patients, 
which will contribute to an increase in uptake of screening (Hypothesis 1.1) and in concordance and thus 
decision quality as measured by MMIC (Hypotheses 1.2).(RQ-4)(CI-1) 
 
Figure 1 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 12 
 
3.1 
Primary Outcome Measures 
The primary outcomes are screening uptake and decision quality, each of which is essential to providing 
high-quality and patient-centered care.   
• 
Screening uptake will be defined as performance of colonoscopy, FIT, or another approved 
screening test within six months after enrollment, as documented in the EHR.   
• 
Decision quality will be defined by the multi-dimensional measure of informed consent 
(MMIC),53 where a high-quality decision is one where the individual has adequate knowledge regarding 
the available options and undergoes the intervention that he or she has chosen or that fits his or her 
values (“value concordance”). (PC-3, IR-4)  
o Knowledge (T2) will be assessed by a 12-item test made up of 6 multiple choice 
questions and 6 true-false questions that was updated from what we used in our 
previous study to reflect changes in screening guidelines.  Adequate knowledge = 9 
correct  
o Concordance (T3) will be measure between the test choice at T2 and screening test 
underwent, if any, within six months after enrollment(T3). 
 
3.2 
Secondary Outcome Measures 
Patients: Data will be collected from patients at four time points:  before they view the decision aid (T0); 
immediately after they view the decision aid (T1); aiming for 4-7 days after their appointment with their 
provider (T2); and six months after enrollment (T3). 
• 
Screening Intent (T0, T1, T2):  Intent to be screened for CRC with any test (“Screening Intent”), will 
be measured with 1 item: “Do you plan to get any type of colon test within the next 6 months?” and  
has a response option of: 5=Definitely, 4=Probably, 3=May or May not, 2=Probably not, and 
1=Definitely not.  This measure has been used in previous studies by our research team (PC-3, IR-
4).51,52 
• 
Test choice (T0, T1, T2) (PC-3, IR-4):  As in our previous studies:51,52 
o For those who answer Screening Intent with “Definitely not,” “Probably not,” or “May or may 
not,” Test Choice is categorized as No screening.   
o Those who answer Screening Intent with “Probably” or “Definitely” have Test Choice categorized 
based on their answer to a single item: “If you have a colon test, which one would you choose?” 
Response options are: Stool test (FIT or Cologuard), Colonoscopy, Another test, or Don’t know. 
• 
Perceived CRC risk (T0, T1, T2):   
o Perceived personal CRC risk will be assessed with a three-item scale, modified from items 
originally developed by Champion to measure perceived breast cancer risk78,79 and used by 
members of our team in multiple projects.51,52,69  Each item uses a four-point response option, 
where 1 = very unlikely and 4 = very likely, to assess participants’ beliefs about how likely they 
are to get CRC in the next 5 years, in the next 10 years and sometime during their lifetime.  
Cronbach alpha was 0.90 in our recent study. (PC-3, IR-4) 
o Perceived comparative CRC risk will be assessed with a single item measuring perceived 
comparative risk,66 which asks “Compared to other women/men your same age, would you say 
your change of getting colon cancer in the next 10 years is higher, about the same, lower, or 
don’t know?” (PC-3, IR-4) 
• 
Decision Conflict (T0, T1, T2) will be assessed with the low literacy version of the Decision Conflict 
Scale, a ten-item instrument that assesses patients’ subjective feeling regarding the decision process 
over five areas and has been used widely in studies of decision aids (PC-3, IR-4).61,70 
• 
Perceived Shared Decision Making (T2) will be assessed with two measures. Patients will first answer 
five items adapted from the Shared Decision Making Process_4 Survey. This tool is a National 
Quality Foundation Measure used to assess the extent to which patients are involved in the 
decision-making process (PC-3, IR-4).54   Patients will also respond to the 3-item CollaboRATE 
measure that assess three key areas of shared decision making; 1) explaining the health issue; 2) 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 13 
 
asking for patient preferences; and 3) incorporating patient preferences into the decision. Each item 
uses likert response options ranging from “no effort was made” to “every effort was made”.73, 74  
• 
Numeracy:  Subjective numeracy will be assessed at T0 with the Subjective Numeracy Scale (SNS) – 
short form, a validated instrument that involves 3 Likert-style questions.67,71,72  
• 
Literacy (T0) will be assessed using a 3-item health literacy scale (IR-4).75 
• 
Demographic data (T0) (including age, gender, income, education), as well as data on previous MD 
CRC screening recommendations, will be assessed utilizing a survey that has been used by our team 
and other researchers in multiple studies of CRC screening.51,69   
 
3.3 
 
Additional Measures 
• 
Program evaluation:  We will evaluate the presentation with 7 investigator created items at T1 and 2 
items at T2 for all patient-participants and an additional 5 items at T1 for those patients who viewed 
the personalized risk information. The items will measure satisfaction and usefulness of the 
presentation as well as the perceived trustworthiness of the information. 
• 
Provider Intervention evaluation: We will evaluate the personalized message with an investigator 
created survey for all providers randomized to receive the screening reminder + personalized 
message. The items will measure how much the personalized information was helpful, how much 
they would use it if integrated into the electronic health record (EHR), what type of patient they 
would use the informtion  
• 
Impact of COVID-19 on screening preferences and intentions (T2):  will be assessed with one open-
ended question: “How has the COVID-19 pandemic affected your decision about getting screened 
for colorectal cancer?” Patients also will be provided with a list of common factors affecting 
decisions from which they can check all that apply.  
• 
Reasons for test preference, test choice, and follow-up for discordance (T2):  Patients will answer an 
open-ended question about their intent to be screened and test preference. Patients whose 
screening intent or test choice changed from T1 will be asked to explain the reason for the change. 
 
Providers:  Data collection from providers will include:   
• 
Ordering of CRC screening test will be assessed by reviewing the EHR for orders for FIT, colonoscopy, 
or other CRC screening test for each patient at six-month follow up. 
• 
Opening of provider notification will be assess for providers by reviewing the EHR.  
• 
Demographic data (including age, gender, time in practice at enrollment) will be assessed using the 
AMA Physician Datafile. 
 
 
4.0 
Eligibility Criteria 
 
4.1 
Inclusion Criteria 
Patients will be eligible if they are:  
• 
age 50-75 years 
• 
have not had colonoscopy performed in last 10 years, sigmoidoscopy in last 5 
years, or fecal occult blood testing (FOBT or FIT) in the last year, or Cologuard in the last 3 years 
• 
have not had a colonoscopy since age 50 years  
• 
have a scheduled appointment with a provider who agreed to participate in the 
study and approved approaching their patients.  
 
Providers will be eligible: 
• 
if they are a physician (MD or DO), nurse practitioner (NP), or physician assistant 
(PA) practicing at one of our research sites 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 14 
 
 
4.2 
Exclusion Criteria 
Patients will be excluded if they are:  
• 
undergoing workup for symptoms consistent with CRC, such as unexplained weight 
loss, change in bowel habit, or rectal bleeding  
• 
have a diagnosis or medical history conferring elevated risk for CRC including a 
previous adenomatous polyp or CRC, inflammatory bowel disease, high-risk syndromes, or a 
significant family history of CRC (two or more FDRs with CRC or one FDR with a CRC diagnosis 
prior to age 60) 
• 
are unable to speak and read English  
• 
previously participated in any research projects regarding colorectal cancer 
screening or colonoscopy including, but not limited to our previous studies. 
• 
Members of the study team will not be participating in the study; therefore, 
patients who have a scheduled appointment with any member of the study team will not be 
eligible. 
 
Providers will be excluded if they are: 
• 
None 
 
5.0 
Study Design 
 
We will conduct a 2x2, randomized, controlled trial (see Table 2) to compare decision quality and 
screening uptake in four groups of patients who view a decision aid:   
• 
Group 1) without the personalized message and whose providers do not receive the personalized 
message (control group) 
• 
Group 2) with the personalized message and whose providers do not receive the personalized 
message; 
• 
Group 3) without the personalized message and whose providers receive the personalized message, 
and  
• 
Group 4) with the personalized message and whose providers receive the personalized message. 
 
 
 
 
 
 
 
 
 
 
We have chosen a 2x2 design in order to separately evaluate the impact of personalized messages 
provided to patients and to providers.  It is essential to evaluate these two interventions separately due 
to the expense and effort required for implementing either of them.  We will cluster patients by 
provider in order to avoid the danger that providers who received the message for some of their 
patients would use similar methods for patients for whom they did not receive the message. 
 
Comparators:  Our study involves three comparators:  (1) a CRC screening decision aid without a 
personalized ACN risk message, (2) a CRC screening decision aid with a personalized ACN risk message, 
(3) A provider message with personalized ACN risk information. 
 
Table 2 
Patient views: 
Provider receives: 
Decision aid WITHOUT 
personalized message 
Decision aid WITH 
personalized message 
Screening reminder 
Group 1 
Group 2 
Screening reminder + 
Personalized message 
Group 3 
Group 4 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 15 
 
Study Flow Diagram:  
 
 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 16 
 
6.0 
Enrollment/Randomization 
 
Patients: We will recruit patients from primary care clinics from two healthcare systems in Central 
Indiana:  the IU Health Physicians’ primary care practices of the Indiana University Health system 
(currently 34) and the primary care practices of Eskenazi Health (currently 9).  These clinics serve a wide 
range of socioeconomic groups, including rural, upper-income suburban, middle-income urban/ 
suburban, and lower-income urban (including 7 Federally Qualified Health Centers).  Nineteen of the IU 
Health practices are outside of Indianapolis, and 4 are > 40 miles from the academic health center.  (PC-
2) 
 
Clinical Information Specialists at IU Health will identify potentially eligible patients who have an 
upcoming appointment using a query of their electronic health record (Cerner) and will share that list 
with the research team weekly or biweekly.  Eskenazi Health’s potentially eligible patients will be 
identified by the Regenstrief Data Core, also on a weekly or biweekly basis. Both health systems will 
save a list of potentially eligible patients, along with their medical record number (MRN), street 
address, phone number, upcoming clinic appointment date and healthcare provider, and EHR patient 
portal enrollment status in a secure server accessible by the project manager and data manager. These 
lists will be updated on a regular basis throughout the recruitment period. 
 
The research team will send potentially eligible patients a letter of introduction explaining the study (see 
Notes & Attachments for letter and brochure).  The letter will also include a phone number that patients 
can call to opt out of being contacted.  A week later, the research assistant will call patients (see Notes & 
Attachments for phone script) who have not opted out to explain the study and answer questions about 
study requirements, potential risks, and compensation. If the patient is interested in joining, the 
research assistant will confirm eligibility. If the patient is eligible, the research assistant will review the 
study information sheet (SIS) and HIPAA authorization. The SIS and HIPAA authorization will be emailed 
to the participant after the recruitment call with instructions and encouragement to contact the study 
team with questions.  If the patient prefers, the research assistant can schedule a follow-up call to 
discuss the SIS and HIPAA authorization after the patient has had time to receive and review.  For those 
patients who refuse to be assessed for eligibility, the RA will record reasons for refusal. 
 
Participants will be offered three options to access the decision aid and complete the first two surveys 
(T0 and T1).  They may choose to receive an electronic link: (i) through the EHR patient portal 
(preferred), (ii) by email, or (iii) on an iPad provided at the patient’s clinic.  For systems (i) and (ii), the 
research assistant will provide assistance as needed by phone when the patient opens the link or in the 
clinic for those who wish to use the iPad (method iii).   
 
The electronic link will take the patient to a Qualtrics database. A randomization scheme, generated by 
our Biostatistics team, will be connected to the Qualtrics database.  When the participant enters 
Qualtrics, this will trigger Qualtrics to assign them to the Control group (view the non-personalized DA) 
or the Intervention group (View the personalized DA). 
 
Research team members interacting with the participants will be blinded to patient assignment. The 
patients will be blinded to assignment of their provider. 
 
Providers: The providers will be identified through each health system’s provider directory, and 
confirmed and updated by the practice administrators. All eligible providers will be sent a letter and 
study information sheet explaining the study (see Notes & Attachments for letter and SIS), and be given 
the opportunity to let the research team know if they choose not to participate. Providers who agree to 
participate will be randomized to the Control group (receives a generic message) or the intervention 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 17 
 
group (receives patient’s ACN risk). The providers will be randomized based on a randomization scheme 
generated by our Biostatistics team.  
 
The research team will not be blinded to provider assignment as they will need to know which 
notification to send. Providers will know that their patient enrolled in the study; however, the provider 
will be blinded to the patient’s group assignment. 
 
 
7.0 
Study Procedures 
Since the goal of the proposed research is to improve patient decisions regarding screening and 
prevention by testing an innovative approach to informing patients and their healthcare providers 
about personal risk for colorectal cancer, we require the involvement of both patients and healthcare 
providers. 
 
7.1 Interventions 
Patients:  
Decision aid without personalized message (RQ-5):  For the study, we have modified the “verbal” 
decision aid designed and tested in our study supported by PCORI (CDR-1403-11040).  In this study, 688 
patients eligible for screening viewed a decision aid that provided extensive information about CRC 
screening, including baseline risk of lifetime CRC mortality and incidence (no screening), risk reduction 
provided by colonoscopy and FIT, sensitivity of colonoscopy or FIT, and rate of FIT turning positive 
(requiring colonoscopy) and of complications from colonoscopy.51  Half the patients viewed a decision 
aid presenting this information using numbers and icon charts (quantitative arm); the other half viewed 
a decision aid presenting the information using only verbal descriptions (no numbers) (verbal arm).51 
 
Viewing either decision aid in this project led to significant increases in mean intent to undergo 
screening (3.94 vs. 3.52, p < .001) and to undergo FIT (3.41 vs. 3.05, p < .001), both on a five-point scale, 
and lower decision conflict (18.8 vs. 39.5, p< .001).  Compared to participants in the Verbal arm, those in 
the Quantitative arm had a larger increase in intent to undergo FIT (p = 0.011), and were more likely to 
switch their preferred test from non-FIT to FIT (28% vs. 19%, p =.010).51  There was no difference in 
uptake of screening at six months (about 30% in both arms) or test choice (RQ-5).  
 
The current study’s decision aid without personalized message consists of a PowerPoint presentation 
converted to mp4 (video) with text, photos, and an audio track, that is advanced by the viewer and can 
be viewed online.  It begins with a 60 sec video on CRC screening produced by the Centers for Disease 
Control and Prevention (CDC), followed by slides summarizing the advantages and disadvantages of 
colonoscopy and stool testing with the fecal immunochemical test (FIT)51 and DNA+FIT (Cologuard). (See 
appendix for DA script) 
 
Decision aid with personalized risk message (RQ-5):  For the current study, we have modified two 
decision aids developed and tested in previous studies. Initially, we developed a decision aid that 
provides a personalized risk message based on the ACN risk rule to be used in this trial7 and pilot tested 
it with 96 patients (RQ5).  Viewing this decision aid resulted in a significant increase in mean intent to 
get screened (3.22 vs. 2.68, p < .001), intent to have FIT (2.59 vs. 1.98, p < .001), intent to have 
colonoscopy (2.82 vs. 2.64, p = .002), and lower decision conflict (35.9 vs. 61.9, p < .001), compared to 
before viewing the decision aid.  Of note, the groups with low and very low risk for ACN were combined 
into one group (“low risk”).  Individuals with low ACN risk (n=16) were randomized to view a description 
of the advantages of FIT for people with low risk. Patients in this group who viewed this description had 
a larger increase in intent to undergo FIT than did those who did not view the information (-0.06 vs. 
+1.00, p = .001).  

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 18 
 
 
Patients in this pilot study received messages whether their risk of current ACN was low, intermediate, 
or high-average based on the ACN prediction rule, but did not receive more specific information about 
their ACN risk (i.e. 4%, 10%, or 22%).   
 
Based on our previous studies showing mildly beneficial effects of providing quantitative 
information,51,52 we modified the decision aid to include an icon chart depicting this probability as a 
frequency, and we pilot tested that decision aid with 9 patients.  While this small pilot test did not allow 
formal statistical testing, intent to be screened was increased or unchanged after viewing the decision 
aid, compared to beforehand, for all patients.  
 
The current study’s decision aid with personalized message will first present the decision aid without 
personalized message followed by additional PowerPoint slides converted to mp4 (video) with text, 
photos, and an audio track briefly explaining the risk tool, the participant’s score on the 5 risk factors, 
total score, ACN risk, and implications for screening and test choice. (see Appendix for DA script) 
 
The decision aid without personalized message is approximately 10 minutes and the additional slides 
with the personalized message take approximately another 4 ½ minutes to view. 
 
Providers: 
Provider personalized ACN risk message (RQ-5):  We designed and pilot tested a personalized message 
for providers that discloses: 
• 
the patient’s ACN risk:  low (combining low and very low categories), intermediate, or high-
average,  
• 
the predicted frequency of ACN on an icon chart:  4 per 100; 10 per 100; or 22 per 100, and  
• 
implications for screening decision and test choice.  
The personalized message was slightly modified from one tested by Skinner et al. (2015, 2016), which 
was found to increase discussion of CRC screening and uptake in some groups.41,42  Both messages list 
patient risk factors for CRC and guideline-consistent recommendations for screening.  Our message 
differs from Skinner’s in that it classifies the probability of having a current ACN as low-average, 
intermediate, or high-average, displays the probability on an icon chart, and recommends FIT for 
patients at low risk and colonoscopy for those at high-average risk.  Like Skinner’s, our message specifies 
that both tests are acceptable for average-risk patients. 
 
We tested the modified provider message with six primary care providers (5 MDs and 1 NP), each of 
whom viewed messages for four or five patients from their clinic who participated in the pilot testing of 
the final decision aid (28 evaluations total).  Providers estimated the patient’s risk of current ACN (low, 
average, or high) before and after viewing the message, and they changed their estimate in 17 of 28 
evaluations (61%).  The providers’ recommended screening test (colonoscopy, FIT, or either) changed 
after viewing the message in 16 of 28 evaluations (57%).  For 26 of 28 evaluations, providers rated the 
information about ACN risk very helpful or somewhat helpful (PC-1). 
 
For the current study, we have further modified the provider message based on feedback from IU 
Health and Eskenazi providers. The notification will include the patient’s ACN risk (very low, low, 
moderate, high-average) and implications for screening decisions and test choice. Links to a web landing 
page containing a more detailed explanation of the risk tool and additional references will be included. 
(see Appendix for notifications and web landing page) 
 
Providers randomized to the control group will receive a message informing them that their enrolled 
patient is due for CRC screening.   

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 19 
 
 
Providers will receive the message by email linked to the EHR system. The message will be sent by the 
research team within 24 hours of the provider’s appointment with the enrolled patient.   
 
 
 
7.2 Data Collection 
Patients: Potentially eligible patients will be sent a letter of introduction and explanation about the 
study. The letter will inform patients that they will receive a call about the study in the next few days 
and will include a telephone number to call if they wish no further contact. A week after letters are 
mailed, the research assistants will call patients who have not called the “opt out” number. The 
research assistants will explain the study and answer patients’ questions about study requirements, 
potential risks, and compensation. If the patient is interested in joining, the research assistant will 
confirm eligibility. If the patient is eligible, the research assistant will review the study procedures, the 
informed consent document and HIPAA authorization, and obtain verbal consent and authorization.  
 
The research assistant will then collect the data to calculate the participant’s risk for having an advanced 
colorectal neoplasm (ACN). This involves confirming gender, age, and family history of colorectal cancer. 
The research assistant will ask the patient for their smoking history and calculate pack years (none, < 30 
pack years; ≥ 30 pack years). The research assistant will also ask the participant for their waist size (for 
men: under 37 ½ in; 37 ½ -47 in; > 47 in; and for women: < 34 ½ in; 34 ½ - 43 ½ in; > 43 in). 
 
The research assistant will discuss with the participant which of the 3 options they prefer to access the 
decision aid and survey: (i) through the EHR patient portal, (ii) by email, or (iii) on a iPad at a primary 
care practice. Based on that discussion, the research assistant will send the participant the link to their 
survey and decision aid. The research assistant can be available by phone or in-person at the practice as 
needed to assist participants in accessing the survey and decision aids.  The research assistant will 
encourage participants who choose to access the surveys and decision aid on their own device to do so 
in a quiet location free as possible from distractions. 
 
The email sent to participants will review the study procedures, who to contact with questions, and the 
unique link to their survey in Qualtrics. When the participant clicks the link, they will be taken to 
Qualtrics and the baseline survey (T0). After the participant completes T0, Qualtrics is programmed to 
stream the appropriate decision aid for that participant. When the decision aid completes, the post-
intervention survey (T1) will display. Following completion of T1, the participant will be automatically 
sent a confirmatory email thanking them for completing this part of the study, reminding them of the 
next study contact, and who to contact with questions. 
 
The baseline (T0) and post-intervention (T1) surveys are planned to take about 10 minutes each to 
complete. The control decision aid is approximately 10 minutes long and the intervention decision aid is 
approximately 15 minutes long (see Appendix for T0 and T1 surveys).  
 
Research assistants will start contacting participants approximately four days after the participant’s 
provider visit to complete the post-provider visit (T2) survey. Research assistants will aim to start 
collecting the T2 data four days after the provider visit; however, if the patient requests contact sooner 
due to scheduling conflicts, the research assistant will contact the patient as requested. Research 
assistants will first attempt to collect the T2 data over the phone; however, if unsuccessful or if the 
participant prefers, the research assistant can email the participant a link to complete the survey online 
in REDCap.  
 
The post-provider visit (T2) survey is planned to take about 15 minutes (see Appendix for T2 survey). 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 20 
 
 
Research assistants will start contacting participants 6 months after study enrollment to complete the 6-
month follow-up (T3) survey. Research assistants will first attempt to collect the T3 data over the phone; 
however, if unsuccessful or if the participant prefers, the research assistant can email the participant a 
link to complete the survey online in REDCap. 
 
The 6-month follow-up (T3) survey is planned to take about 15 minutes (see Appendix for T3 survey). 
      
The patient’s medical record will be queried for documentation of colonoscopy, FIT, or another 
approved screening test within six months of study enrollment. Regenstrief Data Core will query the 
electronic health records (EHR) for screening uptake for both Eskenazi Health and IU Health patients. 
Research assistants will confirm discrepancies between query results and patients’ self-reported 
uptake. 
 
Providers:  
The Regenstrief Data Core will query the EMR for orders for colonoscopy, FIT, or other approved CRC 
screening test entered by each provider for their enrolled patients. They will also query the EHRs for the 
read status for all the provider notifications that were sent. Demographic data will be assessed using the 
AMA Physicians Datafile. 
 
 
8.0 
Reportable Events 
 
If a participant experiences an adverse event that occurs in greater frequency or severity than 
previously known, this will be reported to the IRB either as a prompt report if it meets reporting 
criteria, or at time of study closure. 
 
 
9.0 
Data Safety Monitoring 
 
Dr. Peter H. Schwartz, principal investigator will have ultimate responsibility for monitoring the safety 
and security of the participants and data. Dr. Schwartz and his study team will engage in quality 
improvement practices beginning with development and then with ongoing review of study procedures. 
The Co-Investigators will be actively involved in quality assurance activities including monitoring of 
recruitment, adherence to eligibility criteria, adherence to study protocol, quality of data entry, and 
adherence to any adverse event reporting.  
 
 
10.0 
Statistical Considerations 
 
Sample Size Justification: This trial is powered for the two primary hypotheses.  For Aim 1, we expect 
exposure to either personalized message will increase uptake from 30%, which was the uptake at six 
months seen in our current PCORI project, to 40% and the combined effect to be additive (i.e. no 
interaction between the interventions). We believe a 10% increase in uptake is a minimally important 
difference to detect.  An earlier study found that patients who viewed a personalized message about risk 
of colorectal cancer had a 9% higher uptake than did those who viewed a non-personalized message (CI-
2).41 We believe our intervention will have greater impact, due to its encouraging low-risk individuals 
(50% of patients)7 to use a non-invasive test. An earlier study found that individuals due for screening 
who were offered a non-invasive test had a 31% higher rate of screening than those offered just 
colonoscopy (69% vs. 38%)(CI-2).5  To detect an effect of 10% increase (odds ratio of 1.55) with a power 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 21 
 
of 80% (two-sided α= 0.05) a sample size of 732 subjects (183 per group) is needed for the Wald test for 
either patient or provider message main effect in a logistic model if patient outcomes were 
independent.  To account for clustering due to randomization by provider, we inflate the sample size 
based on the design effect. We assume an intraclass correlation of .05 for provider, and average number 
of subjects per provider of 8. (RC-3) We will allow for an attrition rate of 10%. This results in a final 
sample size of 1100 (275 per group). For the informed choice outcome, we expect exposure to either 
personalized message would increase informed choice from 20%, the outcome in our current PCORI 
project, to 30% (odds ratio of 1.71) and the effect to again be additive.  This leads to an initial sample 
size of 604 total (151 per group) before accounting for inflation and attrition, which is less than for 
uptake.  Thus, the sample size needed for both outcomes is 1100 (275 per group, 130 providers). These 
recruitment goals are readily achievable based on the INFORM study.  Aim 2 is considered exploratory 
because we don’t have sufficient preliminary data to estimate all effect sizes; however, we will have 
sufficient power for some hypotheses. (IR-1) 
Analytic plan:  Preliminary analyses will compare baseline demographic information across the four 
groups using means and standard deviations for continuous variables and frequency distributions for 
categorical variables. We will adjust for those characteristics in subsequent analyses if significant 
differences emerge at a conservative level for inclusion of a covariate (p<.20). Characteristics of 
participants who don’t complete T1 and/or T2 will be compared with those who remain to determine 
what biases may exist. The above analyses will be conducted using ANOVA, chi-square tests, or exact or 
non-parametric equivalents.  If there appear to be biases in dropout, we will conduct pattern mixture 
models analyses to see how the results could change based on the missing data assumption (IR-5, MD-2, 
MD-3, MD-4).  Primary analysis of outcomes will employ an intent-to-treat analysis. For Aim 1, our 
primary hypotheses will be tested using logistic regression models with the outcomes of informed 
choice and uptake (both yes/no outcomes) and main effects for:  1) patient receipt of personalized 
message; and 2) provider receipt of personalized message.  A random effect for provider will be included 
to account for the clustered randomization.  We will test for an interaction effect, but do not expect one 
so have not powered the study for an interactive effect.  The secondary hypotheses (planned subgroup 
analyses with low risk group) will be tested using the same model type (HT-2, HT-3).  The secondary 
hypotheses are considered exploratory.  For Aim 2, mediation effects (RQ-6) will be estimated in a 
logistic regression setting, fitting the appropriate mediation models using MPlus76 and then testing 
indirect effects using the percentile bootstrap approach to estimate the indirect effect.77  For primary 
analyses, we will fit models that estimate the effects of either or both of the interventions relative to 
control. Moderators (RQ-4, HT-1, HT-2, HT-3, HT-4) will be identified by significant interaction terms in 
the regression models from Aim 1.   
 
 
11.0 
Statistical Data Management 
 
We will create a secure web-based system to capture study data using the REDCap and Qualtrics 
database management system. We will review and process data using multiple verification and edit 
checking programs (e.g. range-checks, missing data reports). We will also conduct rudimentary analyses 
to ensure that the data have been properly collected and to identify any outliers or errors. A consort 
diagram will be constructed for reporting that accounts for all missing data (IR-5, IR-7, MD-1, MD-4). 
 
 
12.0 
Privacy/Confidentiality Issues 
 
Potential Risks 
 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 22 
 
A breach of confidentiality is always a risk with minimal risk studies. In addition, participating in a 
research study and answering questions may cause anxiety. 
 
For patient-participants, the information presented regarding risk of colorectal cancer and choice of 
screening test may cause patient-participants to become confused or anxious.  Finally, after 
participating in this study, patients may make a different decision regarding colorectal cancer screening 
than they would have made if they had not participated in the study.  This is true, of course, in any study 
that provides patients with information regarding medical conditions or available interventions. 
Participation in the study still counts as carrying minimal risk, though, since (a) all patient-participants 
will receive evidence-based, high quality information about colorectal cancer and screening, and (b) 
each of the recommended choices are approved, available screening tests with proven ability to reduce 
morbidity and mortality of colorectal cancer. 
 
Protecting against, or Minimizing Potential Risks 
 
For both patient and provider participants, all information required for recruitment and tracking will be 
stored in a HIPAA-aligned database accessible only by authorized study team members primarily the 
recruiters. All team members will adhere to our institution’s HIPAA policy and use of protected health 
information. All data provided by the patient and provider participants will be collected and stored in a 
separate HIPAA-aligned database accessible only by authorized study team members. Authorization to 
access both databases will be managed and overseen by the project manager and the principal 
investigator. The Department of Biostatistics will maintain all de-identified data, cleaning and preparing 
the datasets for analysis. 
 
Confidentiality will be maintained by assigning each participant a unique identification number and using 
this number to identify the participant on all data collection forms. We will keep all paper documents 
locked in lockable cabinets in a locked office suite. Most of the data will be entered directly into 
REDCap or Qualtrics, HIPAA-aligned web environments. Processes and procedures have been 
documented and implemented to ensure the security and protection of the data within the computer 
operations centers, the servers, and the databases. Only those study team members who need access 
to this information will be allowed by the PI or study coordinator. All participants will be fully informed 
about the study prior to enrollment and be given the opportunity to decline to answer any questions 
or to discuss any issues they find troubling. They will be told that they can terminate participation at 
any time for any reason. 
 
Research team members will be trained in procedures to allow participant to withdraw from the study. 
REDCap and Qualtrics surveys will allow participants to pass over questions and still continue through 
the remainder of the questions. 
 
All study team members including those involved with the recruitment, informed consent process, and 
data collection will be adequately trained. Training will include passing of our institution’s required 
Collaborative Institutional Training Initiative (CITI) modules and ongoing study-specific training from 
study personnel. 
 
Any files that contain protected health information that might be created during the course of the study 
will be stored on department servers.  The PI and project manager will coordinate with the Department 
IT staff to control access to these folders. 
 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 23 
 
In a step to minimize any confusion about the information presented to the patient-participants, all 
patients will initially view a video that provides information about CRC screening in an accessible and 
understanding way. It should be noted that patient responses to this type of video in previous research 
projects were great thankfulness for the information provided, which goes beyond what many patients 
hear from their doctor. In addition, since the participants will be recruited from a list of patients 
scheduled to receive care at the practice, they will have the chance to ask their health care provider for 
additional information. In fact, fostering such discussions is a potential benefit of study participation.  In 
addition, the informed consent will give information on how to contact the principal investigator with 
any questions or concerns. 
 
Protections for Research Data 
 
Most of the data will be entered directly into one of several instruments in the study's REDCap project, a 
HIPAA aligned web environment. Privileges to the instruments will be granted or restricted by the PI or 
project manager based on what user rights are necessary to do the job. This could include no access, 
read only, or read and edit the data.  Any files that contain protected health information that are 
created during the course of the study will be saved on the Department's servers. The PI or project 
manager will coordinate with the Department's IT to control access to these folders. 
 
Protections for Participant Privacy 
 
Initial contact with the patient will be a recruitment letter mailed through the US Postal Service to the 
address provided by the patient to be included in the EHR. The recruitment phone calls will be made 
from a private office to the phone number listed in the EHR and if additional phone calls are required, 
the recruiter will confirm with the potential participant their preferred contact number and time; the 
study team will make arrangements to comply with the potential participant's wishes.   
 
Research staff will encourage the patient-participants to complete the baseline (T0) and post-
intervention (T1) surveys and view the decision aid (intervention) in a quiet, private area; however, the 
participants ultimately will choose the location. Research Assistants will initially contact the participant 
to complete the post-visit survey (T2) and 6-month follow-up (T3) surveys by phone in a private office 
and conduct the interview at a time and phone number chosen by the participant. If the participant 
prefers to complete the surveys online, then the research assistant will email the participant the link to 
the surveys and the participant will choose where to complete the surveys. 
 
Initial contact with the provider will also be with a recruitment letter delivered to their primary care 
practice by study team members. Providers will access the notification (intervention) using the 
procedures they usually would when they access any communication sent to them through their health 
systems' EHR. Providers will choose where they open their email and access the link to complete the 
provider surveys. 
 
 
13.0 
References 
 
1. 
Smith RA, Andrews KS, Brooks D, et al. Cancer screening in the United States, 2018: A review of 
current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J 
Clin. 2018;68(4):297-316. 
2. 
Siegel RL, Miller KD, Fedewa SA, et al. Colorectal cancer statistics, 2017. CA Cancer J Clin. 
2017;67(3):177-193. 
3. 
Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. CA Cancer J Clin. 2017;67(1):7-30. 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 24 
 
4. 
Smith RA, Andrews K, Brooks D, et al. Cancer screening in the United States, 2016: A review of 
current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J 
Clin. 2016;66(2):96-114. 
5. 
Inadomi JM, Vijan S, Janz NK, et al. Adherence to colorectal cancer screening a randomized clinical 
trial of competing strategies. Archives of Internal Medicine. 2012;172(7):575-582. 
6. 
Bibbins-Domingo K, Grossman DC, et al. Screening for Colorectal Cancer: US Preventive Services 
Task Force Recommendation Statement. JAMA. 2016;315(23):2564-2575. 
7. 
Imperiale TF, Monahan PO, Stump TE, Glowinski EA, Ransohoff DF. Derivation and validation of a 
scoring system to stratify risk for advanced colorectal neoplasia in asymptomatic adults: A cross-
sectional study. Ann Intern Med. 2015;163(5):339-346. 
8. 
Imperiale TF, Yu M, Monahan PO, et al. Risk of advanced neoplasia using the National Cancer 
Institute's colorectal cancer risk assessment tool. J Natl Cancer Inst. 2017;109(1). 
9. 
Schroy PC, Duhovic E, Chen CA, et al. Risk stratification and shared decision making for colorectal 
cancer screening: A randomized controlled trial. Medical Decision Making. 2016;36(4):526-535. 
10. 
Schroy PC, Caron SE, Sherman BJ, Heeren TC, Battaglia TA. Risk assessment and clinical decision 
making for colorectal cancer screening. Health Expectations. 2015;18(5):1327-1338. 
11. 
Schroy PC, 3rd, Wong JB, O'Brien MJ, Chen CA, Griffith JL. A risk prediction index for advanced 
colorectal neoplasia at screening colonoscopy. Am J Gastroenterol. 2015;110(7):1062-1071. 
12. 
Winawer SJ, Zauber AG. The advanced adenoma as the primary target of screening. Gastrointest 
Endosc Clin N Am. 2002;12(1):1-9, v. 
13. 
Schroy PC, 3rd, Coe AM, Mylvaganam SR, et al. The Your Disease Risk Index for colorectal cancer is 
an inaccurate risk stratification tool for advanced colorectal neoplasia at screening colonoscopy. 
Cancer Prev Res (Phila). 2012;5(8):1044-1052. 
14. 
Meester RGS, Doubeni CA, Zauber AG, et al. Public health impact of achieving 80% colorectal 
cancer screening rates in the United States by 2018. Cancer. 2015;121(13):2281-2285. 
15. 
Rex DK, Boland CR, Dominitz JA, et al. Colorectal cancer screening: Recommendations for 
physicians and patients from the U.S. Multi-Society Task Force on Colorectal Cancer. 
Gastrointestinal endoscopy. 2017;86(1):18-33. 
16. 
Imperiale TF, Ransohoff DF, Itzkowitz SH, et al. Multitarget Stool DNA Testing for Colorectal-
Cancer Screening. New Engl J Med. 2014;370(14):1287-1297. 
17. 
Lin JS, Piper MA, Perdue LA, et al. Screening for Colorectal Cancer Updated Evidence Report and 
Systematic Review for the US Preventive Services Task Force. JAMA 2016;315(23):2576-2594. 
18. 
Nelson RL, Schwartz A. A survey of individual preference for colorectal cancer screening 
technique. BMC Cancer. 2004;4:76. 
19. 
Sheikh RA, Kapre S, Calof OM, Ward C, Raina A. Screening preferences for colorectal cancer: a 
patient demographic study. South Med J. 2004;97(3):224-230. 
20. 
Pignone M, Bucholtz D, Harris R. Patient preferences for colon cancer screening. J Gen Intern Med. 
1999;14(7):432-437. 
21. 
Ling BS, Moskowitz MA, Wachs D, Pearson B, Schroy PC. Attitudes toward colorectal cancer 
screening tests. J Gen Intern Med. 2001;16(12):822-830. 
22. 
Hawley ST, Volk RJ, Krishnamurthy P, Jibaja-Weiss M, Vernon SW, Kneuper S. Preferences for 
colorectal cancer screening among racially/ethnically diverse primary care patients. Med Care. 
2008;46(9 Suppl 1):S10-16. 
23. 
Marshall DA, Johnson FR, Phillips KA, Marshall JK, Thabane L, Kulin NA. Measuring patient 
preferences for colorectal cancer screening using a choice-format survey. Value Health. 
2007;10(5):415-430. 
24. 
Shokar NK, Carlson CA, Weller SC. Informed decision making changes test preferences for 
colorectal cancer screening in a diverse population. Ann Fam Med. 2010;8(2):141-150. 
25. 
McQueen A, Bartholomew LK, Greisinger AJ, et al. Behind closed doors: Physician-patient 
discussions about colorectal cancer screening. J Gen Intern Med. 2009;24(11):1228-1235. 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 25 
 
26. 
Wackerbarth SB, Tarasenko YN, Joyce JM, Haist SA. Physician colorectal cancer screening 
recommendations: an examination based on informed decision making. Patient Educ Couns. 
2007;66(1):43-50. 
27. 
Ling BS, Trauth JM, Fine MJ, et al. Informed decision-making and colorectal cancer screening: is it 
occurring in primary care? Med Care. 2008;46(9 Suppl 1):S23-29. 
28. 
National Colorectal Cancer Roundtable. http://nccrt.org/ Accessed February 11, 2019. 
29. 
Inadomi JM. Colorectal cancer screening: Which test is best? JAMA oncology. 2016;2(8):1001-
1003. 
30. 
Lieberman D, Ladabaum U, Cruz-Correa M, et al. Screening for Colorectal Cancer and Evolving 
Issues for Physicians and Patients: A Review. JAMA. 2016;316(20):2135-2145. 
31. 
Zauber AG, Lansdorp-Vogelaar I, Knudsen AB, Wilschut J, van Ballegooijen M, Kuntz KM. Evaluating 
test strategies for colorectal cancer screening: a decision analysis for the U.S. Preventive Services 
Task Force. Ann Intern Med. 2008;149(9):659-669. 
32. 
Knudsen AB, Zauber AG, Rutter CM, et al. Estimation of Benefits, Burden, and Harms of Colorectal 
Cancer Screening Strategies: Modeling Study for the US Preventive Services Task Force. JAMA. 
2016;315(23):2595-2609. 
33. 
Cai QC, Yu ED, Xiao Y, et al. Derivation and validation of a prediction rule for estimating advanced 
colorectal neoplasm risk in average-risk Chinese. Am J Epidemiol. 2012;175(6):584-593. 
34. 
Kaminski MF, Polkowski M, Kraszewska E, Rupinski M, Butruk E, Regula J. A score to estimate the 
likelihood of detecting advanced colorectal neoplasia at colonoscopy. Gut. 2014;63(7):1112-1119. 
35. 
Lin OS, Kozarek RA, Schembre DB, et al. Risk stratification for colon neoplasia: screening strategies 
using colonoscopy and computerized tomographic colonography. Gastroenterology. 
2006;131(4):1011-1019. 
36. 
Tao S, Hoffmeister M, Brenner H. Development and validation of a scoring system to identify 
individuals at high risk for advanced colorectal neoplasms who should undergo colonoscopy 
screening. Clin Gastroenterol Hepatol. 2014;12(3):478-485. 
37. 
Yeoh KG, Ho KY, Chiu HM, et al. The Asia-Pacific Colorectal Screening score: a validated tool that 
stratifies risk for colorectal advanced neoplasia in asymptomatic Asian subjects. Gut. 
2011;60(9):1236-1241. 
38. 
NCI. Colorectal Cancer Risk Assessment Tool. https://www.cancer.gov/colorectalcancerrisk/. 
Accessed February 11, 2019. 
39. 
Freedman AN, Slattery ML, Ballard-Barbash R, et al. Colorectal cancer risk prediction tool for white 
men and women without known susceptibility. J Clin Oncol. 2009;27(5):686-693. 
40. 
Imperiale TF, Yu MG, Monahan PO, et al. Risk of advanced neoplasia using the National Cancer 
Institute's colorectal cancer risk assessment tool. Jnci-J Natl Cancer I. 2017;109(1). 
41. 
Skinner CS, Halm EA, Bishop WP, et al. Impact of risk assessment and tailored versus nontailored 
risk information on colorectal cancer testing in primary care: A randomized controlled trial. Cancer 
Epidemiol Biomarkers Prev. 2015;24(10):1523-1530. 
42. 
Skinner CS, Gupta S, Bishop WP, et al. Tailored information increases patient/physician discussion 
of colon cancer risk and testing: The Cancer Risk Intake System trial. Prev Med Rep. 2016;4:6-10. 
43. 
Schroy PC, 3rd, Duhovic E, Chen CA, et al. Risk stratification and shared decision making for 
colorectal cancer screening: A randomized controlled trial. Med Decis Making. 2016;36(4):526-
535. 
44. 
Fletcher RH. Personalized screening for colorectal cancer. Med Care. 2008;46(9 Suppl 1):S5-9. 
45. 
Seeff LC, Manninen DL, Dong FB, et al. Is there endoscopic capacity to provide colorectal cancer 
screening to the unscreened population in the United States? Gastroenterology. 
2004;127(6):1661-1669. 
46. 
Ballew C, Lloyd BG, Miller SH. Capacity for colorectal cancer screening by colonoscopy, Montana, 
2008. Am J Prev Med. 2009;36(4):329-332. 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 26 
 
47. 
Rodriguez-Moranta F, Trapero-Bertran M, Castells A, et al. Endoscopic requirements of colorectal 
cancer screening programs in average-risk population. Estimation according to a Markov model. 
Gastroenterol Hepatol. 2008;31(7):405-412. 
50. 
Matthias MS, Imperiale TF. A new risk stratification tool for colorectal cancer screening: A 
qualitative study of patient and provider acceptability. In preparation. 
51. 
Schwartz PH, Imperiale TF, Perkins SM, Schmidt KK, Althouse S, Rawl SM. Impact of including 
quantitative information in a decision aid for colorectal cancer screening: A randomized controlled 
trial. Patient Educ Couns. 2018. 
52. 
Schwartz PH, Perkins SM, Schmidt KK, Muriello PF, Althouse S, Rawl SM. Providing quantitative 
information and a nudge to undergo stool testing in a colorectal cancer screening decision aid: A 
randomized clinical trial. Med Decis Making. 2017;37(6):688-702. 
53. 
Marteau TM, Dormandy E, Michie S. A measure of informed choice. Health Expect. 2001;4(2):99-
108. 
54. 
Sepucha KR, Fowler FJ. Shared Decision Making Process_4 User Guide v1.0 © Massachusetts 
General Hospital, 2018.  
55. 
Sepucha K, Ozanne EM. How to define and measure concordance between patients' preferences 
and medical treatments: A systematic review of approaches and recommendations for 
standardization. Patient Educ Couns. 2010;78(1):12-23. 
56. 
Fowler FJ, Levin CA, Sepucha KR. Informing and involving patients to improve the quality of 
medical decisions. Health Affairs. 2011;30(4):699-706. 
57. 
Lee CN, Dominik R, Levin CA, et al. Development of instruments to measure the quality of breast 
cancer treatment decisions. Health Expectations. 2010;13(3):258-272. 
58. 
Solberg LI, Asche SA, Sepucha K, et al. Informed choice assistance for women making uterine 
fibroid treatment decisions: A practical clinical trial. Med Decis Making. 2009. 
59. 
Beauchamp TL, Childress JF. Principles of Biomedical Ethics, 6th Edition. Oxford: Oxford University 
Press; 2006. 
60. 
Schwartz PH, Imperiale TF, Perkins SM, et al. Describing the comparative effectiveness of colorectal 
cancer screening tests:  The impact of quantitative information. Final Report (passed peer review, 
undergoing revision, as of Feb. 2019). 
61. 
O'Connor AM. User Manual - Decision Conflict Scale. 2005; 
https://decisionaid.ohri.ca/docs/develop/User_Manuals/UM_Decisional_Conflict.pdf Accessed 
February 11, 2019. 
62. 
Champion VS, C. The Health Belief Model. In: Glanz KR, B.; Vizwanath, K., ed. Health Behavior and 
Health Education. 4th ed. San Franciso: Jossey-Bass; 2008:45-62. 
63. 
Sung JJ, Choi SY, Chan FK, Ching JY, Lau JT, Griffiths S. Obstacles to colorectal cancer screening in 
Chinese: a study based on the health belief model. Am J Gastroenterol. 2008;103(4):974-981. 
64. 
Cyr A, Dunnagan TA, Haynes G. Efficacy of the health belief model for predicting intention to 
pursue genetic testing for colorectal cancer. J Genet Couns. 2010;19(2):174-186. 
65. 
Rawl SM, Champion VL, Scott LL, et al. A randomized trial of two print interventions to increase 
colon cancer screening among first-degree relatives. Patient Educ Couns. 2008;71(2):215-227. 
66. 
Kreuter MW, Strecher VJ. Changing inaccurate perceptions of health risk: results from a 
randomized trial. Health Psychol. Jan 1995: 14(1):56-63. 
67. 
McNaughton CD, Cavanaugh KL, Kripalani S, et al. Validation of a short, 3-item version of the 
subjective numeracy scale. Med Decis Making. 2015 Novemeber; 35(8):932-936.  
69. 
Rawl SM, Skinner CS, Perkins SM, et al. Computer-delivered tailored intervention improves colon 
cancer screening knowledge and health beliefs of African-Americans. Health Educ Res. 
2012;27(5):868-885. 
70. 
Stacey D, Legare F, Lewis K, et al. Decision aids for people facing health treatment or screening 
decisions. Cochrane Database Syst Rev. 2017;4:CD001431. 

Version Date: 6b (2023-0501 for A011) – Protocol for IU KC-IRB  
Page 27 
 
71. 
Fagerlin A, Zikmund-Fisher BJ, Ubel PA, Jankovic A, Derry HA, Smith DM. Measuring numeracy 
without a math test: development of the Subjective Numeracy Scale. Medical Decision Making. 
2007;27(5):672-680. 
72. 
Zikmund-Fisher BJ, Smith DM, Ubel PA, Fagerlin A. Validation of the Subjective Numeracy Scale: 
effects of low numeracy on comprehension of risk communications and utility elicitations. Med 
Decis Making. 2007;27(5):663-671. 
73. 
Barr PJ, Forcino RC, Thompson R, et al. Evaluating CollaboRATE in a clinical setting: analysis of 
mode effects on scores, response reates and costs of data collection. BMJ Open. 2017;7:e014681. 
74. 
Elwyn G, Barr PJ, Grande SW, et al. Developing CollaboRATE: a fast and frugal patient-reported 
measure of shared decision making in clinical encounters. Patient Educ Couns. 2013;93(1):102-7. 
75. 
Chew LD, Bradley KA, Boyko EJ. Brief questions to identify patients with inadequate health 
literacy. Family medicine. 2004;36(8):588-594. 
76. 
Fritz MS, Taylor AB, Mackinnon DP. Explanation of Two Anomalous Results in Statistical Mediation 
Analysis. Multivariate Behav Res. 2012;47(1):61-87. 
77. 
Thoemmes F, Mackinnon DP, Reiser MR. Power Analysis for Complex Mediational Designs Using 
Monte Carlo Methods. Struct Equ Modeling. 2010;17(3):510-534. 
78. 
Champion VL. Instrument refinement for breast cancer screening behaviors. Nurs Res. 
1993;42(3):139-143. 
79. 
Champion VL, Scott CR. Reliability and validity of breast cancer screening belief scales in African 
American women. Nurs Res. 1997;46(6):331-337. 
 
 
14.0 
Appendix 
 
The appendix will be separate attachments for the Indiana University KC- IRB protocol (see 
Notes & Attachments in the KC-IRB protocol submission).