Addressing Social Determinants of Health During Clinical Care Visits to Promote Equitable Behavior Change and PREVENT Cardiovascular Disease
Phase: NA
Conditions: Cardiovascular Disease, Childhood Obesity
Sponsor: Washington University School of Medicine

Title: 
Addressing Social Determinants of Health during Clinical Care Visits to 
Promote Equitable Behavior Change and PREVENT Cardiovascular 
Disease 
 
 
NCT#:   
 
NCT04530825 
 
 
Version Date:   
07/21/2022 

 
 
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Addressing Social Determinants of Health during Clinical Care Visits to Promote 
Equitable Behavior Change and PREVENT Cardiovascular Disease 
 
Protocol Version 8 
IRB #: 202007026 
 
Principal Investigator: 
 
Maura Kepper, PhD 
 
 
 
 
 
Prevention Research Center, Brown School 
Washington University in St. Louis 
 
One Brookings Dr.  
St. Louis, MO 63130 
kepperm@wustl.edu 
314-935-0142 
 
 
Co- Investigators: 
 
 
Randi Foraker, PhD, MA 
Institute for Informatics 
School of Medicine 
Washington University in St. Louis 
600 S. Taylor Avenue, Suite 102 
Campus Box 8102 
St. Louis, MO 63119 
Randi.foraker@wustl.edu 
314-272-2211 
 
Ross Brownson, PhD 
Prevention Research Center, Brown School 
Washington University in St. Louis 
 
One Brookings Dr.  
St. Louis, MO 63130 
rbrownson@wustl.edu 
314-935-0114 
 
Robert J. Hayashi, MD 
Division of Pediatrics Hematology/Oncology 
Washington University School of Medicine 
660 S. Euclid Ave. 
Campus Box 8116 
Hayashi_r@wustl.edu 
314-454-6018 
 
Lisa de las Fuentes, MD, MS, FASE 
Medicine and Biostatistics 
Washington University School of Medicine 
660 S. Euclid Ave. 
Campus Box 8086 
lfuentes@wustl.edu 
314-747-8163 
 

 
 
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Russ Glasgow, PhD 
Family Medicine 
Dissemination and Implementation Science Program 
of ACCORDS (Adult and Child Consortium for Health 
Outcomes Research and Delivery Science)  
University of Colorado School of Medicine 
Russel.glasgow@cuanschutz.edu 
303-807-9079 
 
Biostatistician: 
Yan Yan, MD, PhD 
 
Division of Public Health Sciences, Department of Surgery 
 
Division of Biostatistics 
 
Washington University School of Medicine 
 
600 S. Taylor Avenue, 418E 
 
St. Louis, MO, 63119  
 
yany@wustl.edu 
 
314-747-1115 
 
Research Assistants: 
Callie Walsh-Bailey, MPH 
 
 
 
 
 
Prevention Research Center, Brown School 
Washington University in St. Louis 
 
One Brookings Dr.  
St. Louis, MO 63130 
Callie.w@wustl.edu 
 
Zoe Miller, MPH 
Prevention Research Center, Brown School  
Washington University in St. Louis 
One Brookings Dr.  
St. Louis, MO 63130 
miller.z@wustl.edu 
 
Kara Sauerburger 
Division of Pediatrics Hematology/Oncology 
Washington University School of Medicine 
660 St. Euclid Avenue Box 8116 
St. Louis, MO 63110 
sauerburgerk@wustl.edu 
 
Alan Beck, PhD 
Prevention Research Center, Brown Schooll  
Washington University in St. Louis 
One Brookings Dr.  
St. Louis, MO 63130 
Alan.beck@wustl.edu 
 
Pablo Zubeldia 
Biomedical Informatics & Data Science 

 
 
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Washington University School of Medicine  
660 S Euclid Avenue 
St. Louis, MO 63110 
pabloz@wustl.edu 
 
Min Zhao 
Biomedical Informatics & Data Science 
Washington University School of Medicine  
660 S Euclid Avenue 
St. Louis, MO 63110 
minzhao@wustl.edu 
 
 
 
Regulatory Contact:  
 
Maura Kepper, PhD 
 
 
 
 
 
Prevention Research Center, Brown School 
Washington University in St. Louis 
 
One Brookings Dr.  
St. Louis, MO 63130 
kepperm@wustl.edu 
314-935-0142 
 
 
 
 
 
 
 
 
 
 

 
 
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Table of Contents 
Background and Introduction: .................................................................................................... 6 
Significance: .............................................................................................................................. 6 
1.0 Study Aims: .......................................................................................................................... 7 
2.0 Summary of Study Plan........................................................................................................ 7 
3.0 Study Population .................................................................................................................. 8 
3.1 Patient eligibility criteria. ................................................................................................... 8 
3.2 Provider eligibility criteria. ................................................................................................. 8 
   3.3 Parent eligibility criteria ..................................................................................................... 8 
4.0 Study Procedures................................................................................................................. 8 
4.1 Recruitment ...................................................................................................................... 8 
4.1.1 Patient recruitment. .................................................................................................... 8 
4.1.2 Provider recruitment. .................................................................................................. 9 
4.2 Enrollment and Consent ................................................................................................... 9 
4.2.1 Patient enrollment. If patient is interested, .................................................................. 9 
4.2.3 Provider enrollment ...................................................................................................10 
4.3 Schedule of Events ..........................................................................................................11 
4.3.1 Patient Schedule of Events ...........................................................................................11 
4.3.2 Provider Schedule of Events .........................................................................................13 
4.4 Data Collection Methods ..................................................................................................14 
Theoretical underpinnings. .................................................................................................14 
4.4.1 EHR data extraction. .................................................................................................14 
4.4.2 Demographics Survey ...............................................................................................15 
4.4.3. Health Behavior & Attitudes Survey..........................................................................15 
4.4.4 Accelerometers .........................................................................................................15 
4.4.5 Patient and parent interviews ....................................................................................15 
4.4.6 Provider survey .........................................................................................................16 
4.4.7 Direct observation, ....................................................................................................16 
4.4.8 Patient follow-up surveys ..........................................................................................16 
4.4.9 Provider qualitative interviews ...................................................................................16 
4.4.10 Clinical Sustainability Assessment Tool (CSAT) ......................................................16 
5.0 Statistical Considerations ....................................................................................................17 

 
 
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5.1. Hypotheses. ...................................................................................................................17 
5.2. Data Analysis Plan .........................................................................................................17 
6.0 Data Management ...............................................................................................................17 
7.0 Confidentiality and Privacy ..................................................................................................18 
8.0 Data Safety and Management .............................................................................................18 
8.1 Data Safety and Monitoring Board ...................................................................................18 
8.2 Reporting of Unanticipated Problems, Adverse Events or Deviations ..............................19 
9.0 References..........................................................................................................................19 
 
 
 
 
 
 
 
 

 
 
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Background and Introduction: 
Obesity among youth in the United States, particularly those of low-socioeconomic 
status (SES), is a major public health concern that puts youth at risk for poor 
cardiovascular health (CVH).1-3 Inequities may be due, at least in part, to differential 
delivery of and compliance to behavior change prescriptions.4 Environmental barriers 
(e.g., poor access to safe places play and healthy food outlets) more prevalent in low-
SES neighborhoods may prevent patients from being active and eating healthy which 
can improve CVH.5-7 Health equity depends on the successful implementation and 
sustainment of tailored, evidence-based interventions to address risk behaviors in 
settings (e.g., clinics) that reach a large number of adolescents. 
Social determinants (e.g., social and built environments) have an important impact on 
health outcomes.8-10 Yet these factors are often ignored at the point-of-care. Providers 
lack time and patient- and community-specific data necessary to provide tailored, 
evidence-based care within their routine practice.11 Interactive Behavior Change 
Technology enables a data-driven, patient-centered approach to prevention that has 
potential to be scaled across clinics, populations and disease types.12 Increasing 
awareness of community resources (e.g., parks, community centers, farmer’s markets) 
has resulted in weight loss in children.13 Yet, an EHR-compatible tool has not been used 
to provide adolescents with patient-centered, community resources at the clinic visit. 
This research will fill this critical gap with our novel Patient-centered Real-timE 
interVENTion (PREVENT) tool. 
Significance:  
Only 4% of adolescents meet the American Heart Association’s Life Simple 7 CVH 
metrics (e.g., obesity, physical activity and healthy food intake) that are important for 
preventing cardiovascular disease, and this percentage was even lower among those of 
low-SES. 3,7,14-16 Increasing physical activity and healthy food intake using effective 
interventions that are scalable, sustainable, and elicit equitable change across 
populations are necessary to address the approximately 19% of adolescents with 
obesity.7 
Primary care physicians reach a large number of adolescents and have the potential to 
reduce poor CVH during well-child visits.17 Yet, providers lack the training and time to 
identify and address health behavior issues.18,19 Evidence-based behavior change has 
not been adopted into practice, despite technological advances (e.g., Interactive 
Behavior Change Technology) that can facilitate this with little burden.20  
To achieve health equity, behavior change interventions should address the environment 
surrounding at-risk youth.21 The ability to be physically active and improve healthy food 
intake is dependent on the built environment22-24 and/or knowledge of existing resources 
and infrastructure (e.g., transportation) to access resources, particularly for low-SES 
populations.25-28 Linking youth and their families to resources (e.g., parks, community 
centers, healthy food outlets) is a practice that aligns with the American Academy of 
Pediatrics recommendations for community pediatricians29 and the Chronic Care 
Model.30 Several primary care-based interventions have linked patients to community 
resources and show promising weight loss in adults and children.13,31,32 Yet, taking such 

 
 
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interventions, coupled with evidence-based behavior change strategies and integrating 
them into a clinical practice workflow has not been tested in adolescents.  
 
1.0 Study Aims: 
The proposed research will test the feasibility of administering PREVENT, a pragmatic, 
equitable approach to prevention, in the Late Effects Clinic at St. Louis Children’s 
Hospital and the St. Louis Children’s Specialty Care Center (CSCC) to prepare for 
subsequent implementation and dissemination. The central hypothesis is that PREVENT 
will improve patients’ attitudes toward behavior change recommendations, to better 
adhere to recommendations and improve CVH. 
Aim 1. Determine barriers to current and future implementation of the PREVENT tool 
(e.g., usability, acceptability, motivation, workflow compatibility) to inform adoption and 
maintenance. 
Aim 2. Assess the impact of the PREVENT tool on patients’ attitudes toward behavior 
change recommendations and on the control of CVH risk factors (e.g., body mass index 
[BMI], physical activity and healthy food intake). 
2.0 Summary of Study Plan 
Fifty adolescents aged 12 to 19 
years at risk for poor CVH (BMI ≥ 
85th percentile) will be recruited 
over a 9-month period (Table 1) 
from the Late Effects Clinic and 
randomized to intervention or 
wait-list control (Figure 1). 
Provider’s and patient’s 
perceptions of barriers to 
implementation and maintenance 
of PREVENT (e.g., usability, 
acceptability, motivation for use, 
workflow compatibility) will be 
examined using: 1) surveys administered to all providers at clinic; 2) semi-structured 
interviews with 5-10 diverse providers (e.g., physicians, nurses, clinic staff, clinical 
research associates); and 3) two focus groups, one with patients (n=10) and one with 
parents (n=10) (Aim 1). These evaluations will be guided by RE-AIM33 and administered 
following the intervention period. Implementation (e.g., intervention delivery, fidelity, time 

 
 
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of use) will be examined using direct observation and audio recordings of 15 provider-
patient interactions while using PREVENT. Patient attitudes toward behavior change 
recommendations and risk factors (BMI z-score, cholesterol, blood pressure, physical 
activity and food intake) will be measured using surveys, physical activity tracking 
devices (accelerometers) and EHR-data extraction at baseline and 3-months (Aim 2). 
An advisory board will be established and meet bi-annually to provide adolescent (n=5), 
parent (n=5) and provider (n=5) perspectives on study implementation and inform 
revisions to PREVENT.  
Key dates (Table 1).  
• 
Provider training: October 2020-January 2021 
• 
Patient recruitment: February 2021- April 2021 
• 
PREVENT feasibility study: January 2021-September 2021 
3.0 Study Population 
We will evaluate the PREVENT tool at the Late Effects Clinic at St. Louis Children’s 
Hospital and the CSCC with:  
1. Fifty adolescents aged 12 to 19 years at risk for poor CVH (BMI ≥ 85th percentile) 
and their parents. 
2. All providers and clinic staff (physicians, nurses, clinic staff, clinic research 
associates) who were involved with the implementation of PREVENT at the Late 
Effects Clinic.  
 
3.1 Patient eligibility criteria.  
1. Adolescents 12 to 19 years  
2. Prior diagnosis of pediatric cancer (diagnosed <21 years of age).  
3. Not receiving active therapy for their cancer 
4. Receiving care from the Pediatric Hematology/Oncology staff and 
physicians at St. Louis Children’s Hospital or the St. Louis Children’s 
Specialty Care Center 
5. At risk for poor CVH (BMI ≥ 85th percentile) 
 
3.2 Provider eligibility criteria. All providers and clinic staff (physicians, nurses, 
clinic staff, clinic research associates) in the Pediatric Hematology/Oncology program at 
St. Louis Children’s Hospital and the CSCC. 
3.3 Parent eligibility criteria. A parent or legal guardian of a study participant. The 
parent or legal guardian must have been present at the clinic visit in which the 
PREVENT tool was administered to the study participant.  
 
4.0 Study Procedures 
 
4.1 Recruitment  
4.1.1 Patient recruitment. A designee at the clinic will query the clinic’s EHR 
using inclusion/ exclusion criteria to develop a list of eligible patients with contact 

 
 
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information (parent contact information will be used for patients ≤18 years). Study 
staff will mail a letter informing them of the study and then recruit via telephone. 
The letter will be addressed to the parent/guardian if the patient is ≤18 years of 
age; otherwise, the letter will be addressed to the patient. The recruiter will 
describe the study and administer a phone-based screener. If interested and 
eligible, patients will be consented and enrolled.   
 
A subset of patients (n=10) and their parent (n=10) will be recruited to participate 
in a focus group discussions following the intervention period. Recruitment will 
leverage contact information collected during the feasibility trial to recruit over the 
phone or email.  
 
4.1.2 Provider recruitment. The study team will present the study and review 
the consent document at the clinic’s monthly research meeting and allow time for 
providers to ask questions. If an eligible provider is not in attendance, the 
provider will be contacted via email to schedule an individual meeting conducted 
over zoom to explain the study and review the consent document.  
 
4.2 Enrollment and Consent  
4.2.1 Patient enrollment. If patient is interested, the consent form will be 
reviewed over the phone. Adequate time will be allotted to allow the patient to 
ask any questions. Additionally, the patient may use the contact information 
provided on the consent document to follow-up with additional questions prior to 
completing the consent. If the patient is 18 years or younger, we will ensure that 
the parent is on the phone while we review the consent document. If the parent is 
not available, we will call back to discuss the consent form. Following this 
conversation, an electronic consent (developed in REDCap with guidance from 
the ICTS mHealth Research Core) will be emailed. The study team will send a 
test email in a secure manner (i.e., [secure] in subject line) prior to sending 
consent to verify the participant’s identify. The email will instruct the participant to 
send all information as a response to this thread and not to remove the “[secure]” 
from the subject line. All future email correspondence will follow this protocol. If 
the patient is 18 years or younger, the parent and patient will be required to 
complete the consent document. If the patient is at least 19 years of age, the 
parent is not required to provide consent. If the patient does not have access to 
complete an electronic form, a consent will be mailed with a return envelope to 
receive written consent. Postage costs will be covered by the study.  Once 
consent is obtained, the patient will received an emailed or hard copy of the 
signed document. Following consent, the patient will complete baseline 
measures (questionnaires administered electronically or by mail; accelerometers 
administered by mail). Following baseline measurement, patients will be 
randomized to intervention or wait-list control and attend their clinic visit. The 
study staff will call the participant one-week before their clinic visit to remind them 
of their appointment time, give them details about the appointment and address 
any barriers they may be facing to complete baseline measurements.  Follow-up 

 
 
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measures will be administered immediately following the clinic visit (within 48 
hours) and 3-months after the clinic visit electronically and by mail. Patients will 
only return to the clinic for a routine visit at 3-months if it meets their standard of 
care based on their baseline clinical values for CVH risk. Wait-list control will be 
sent tailored prescriptions via the PREVENT tool following the completion of 
follow-up measurements. Participants will receive up to $75 dollars in gift cards 
for participation. Participants will receive $25 after baseline, $25 after 3-month 
follow-up and $25 for wearing an accelerometry device to measure their physical 
activity.   
 
Patients (n=10) and their parents (n=10) who participate in focus groups will 
provide an additional written consent in-person prior to the start of the discussion. 
Consent will be administered in a single room with patients and parents. Once 
consent is administered, patients and parents will be divided into two private 
rooms to conduct separate focus groups simultaneously. 
 
 
 
4.2.3 Provider enrollment 
Following the presentation of the study at the clinic’s monthly research meeting, 
all eligible providers will be sent electronic consent documents and provided with 
Dr. Kepper’s contact information (phone and email) to ask additional questions. If 
consent is not received, the study team will follow-up with providers via email or 
phone. 
 

 
 
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4.3 Schedule of Events 
4.3.1 Patient Schedule of Events 
We anticipate that study participation will be between 4 and 5 months from the 
point of recruitment to completion (Figure 2). 
 
 
Consent, enrollment & baseline measurement will occur electronically or via 
mail prior to the clinic visit. The patient will complete a written signed consent, 

 
 
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complete a survey assessing their health behaviors and attitudes and wear an 
accelerometry device for 7 days prior to the clinic visit. Parents/legal guardians of 
study participants will be asked to complete a baseline demographics survey 
delivered electronically before the clinic visit or completed in the waiting room at 
the clinic visit. In addition, study staff will extract EHR data (patient demographics 
and CVH risk factors) and upload the most recent information into the PREVENT 
tool prior to the patient’s clinic visit.  The patient will be randomized to 
intervention or wait-list control.  
PREVENT tool interaction (intervention). The patient will attend a routine clinic 
visit remotely or in-person at the Late Effects Clinic at either St. Louis Children’s 
Hospital or the St. Louis Children’s Specialty Care Center. During this visit, the 
provider will use PREVENT on a tablet or computer (in-person or via a 
teleconference call) to discuss risk, and deliver a tailored behavior change plan 
inclusive of patient-centered community resources. The PREVENT tool will be 
pre-loaded by study staff with all necessary patient information (demographics 
and CVH risk factors) and show the date in which these data were collected. The 
provider may update any patient information at the time of the visit. PREVENT 
uses a robust informatics approach developed by Dr. Foraker (secondary-
mentor)34-36 to visually display Life’s Simple 7 Cardiovascular Risk Factors (e.g., 
weight, blood pressure, inactivity) and calculate the patient’s overall risk for 
developing cardiovascular disease. Physical activity and food intake 
recommendations that are tailored to the patient’s current weight status and 
health behaviors using evidence-based recommendations (Trim Kids,37 the 
Stoplight Diet38) proven to be effective in youth are delivered to the patient. An 
interactive map of community resources near the patient’s home will allow the 
patient to select resources that will support the recommended behavior change. 
Community resources (e.g., parks, fitness and recreation centers, farmer’s 
markets, food pantries) were pulled from YELP using an API key. Resources 
were validated against lists manually generated via online searching of physical 
activity and food departments and organizations (e.g., the department of parks, 
recreation and forestry) and google. A final action plan (behavior change 
prescription, community resources and education) will be provided to the patient 
at the visit and/or electronically via email or text-message. Patient follow-up will 
be supported by automatic email or text-message check-ins at 4, 8 and 12 
weeks. Within the 4-, 8- and 12- week email/text message check-ins the patient 
will be asked to answer questions about meeting their physical activity and 
nutrition goals. Based on the response, the patient will receive an automated 
email and/or text message with an updated prescription. 
Wait-list control. Patients will attend a routine care visit in-person or remotely. A 
PREVENT action plan (behavior change prescription, community resources and 
education) will provided to the patient via email after the completion of follow-up 
measurement.  
Follow-up measurement. Immediately following the clinic visit (within 48 
hours) all patients will be sent electronically a brief 10-question (yes/no) 
survey regarding their clinical interaction. Participants randomized to 
intervention will also receive questions about their satisfaction with the 

 
 
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PREVENT tool. Three months after the patient’s clinic visit, they will be sent the 
Health Behavior & Attitudes Survey electronically and an accelerometer via mail. 
Only patients who presented with abnormal values for CVH risk factors will return 
to the Late Effects Clinic to complete a routine clinic visit in accordance with the 
standard of care for these high-risk patients. Study staff will extract the most-
recent EHR data for CVH risk factors for all patients.  
Qualitative data collection. Semi-structured interviews will be completed within 
one month of the completion of follow-up measurement for all participants that 
received the PREVENT tool.  
4.3.2 Provider Schedule of Events 
 
 
We anticipate that providers study participation will be approximately 11 months 
in duration. All providers at The Late Effects Clinic will be invited to view an 
online training on how to use the PREVENT tool prior to the start of patient 
recruitment. The online training will be recorded and disseminated to ensure that 
all providers are able to view the training. At this time, providers will be supplied 
login credentials to access the PREVENT tool. Following the training, all 
providers will be asked to complete the Clinical Sustainability Assessment Tool 
electronically. Once the intervention period begins, study staff will notify the 
provider if their patient was randomized to intervention to ensure that PREVENT 
is used during the care visit. Tablets will be available at the clinic if providers 
choose to use them to administer the PREVENT tool. However, the PREVENT 
tool can be administered via any computer or tablet using their login credentials. 
A subset of patient-provider interactions (n=15) may be observed and recorded 
while PREVENT is being used. Providers who used PREVENT will be asked to 
complete an electronic follow-up survey. Within one month of completing the 
intervention, providers will participate in in-depth interviews. Interviews will be 
held in-person, over the phone or using zoom technology.  

 
 
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4.4 Data Collection Methods 
Theoretical underpinnings. This feasibility study will apply principles of 
Designing for Dissemination, Implementation and Sustainability (D4DIS) to 
understand factors critical to external validity and refine the existing PREVENT 
tool to fit well with provider’s and patient’s needs, assets and timeframes.39 We 
seek to speed translation of the PREVENT tool into practice by simultaneously 
collecting mixed method data regarding determinants of current and future 
implementation of the PREVENT tool, guided by the new Reach, Efficacy, 
Adoption, Implementation, and Maintenance (RE-AIM) framework.40,41 The 
updated RE-AIM framework will be used to identify barriers to implementation 
and dissemination as outlined in Table 3.  
 
Table 3: RE-AIM Outcome Measures 
RE-AIM 
Construct 
Measure 
Data Source 
Stakeholder 
Reach 
Representativeness 
compared to eligible clinic 
population 
EHR data; 
Demographics survey 
Patients 
Efficacy 
Changes in health behaviors 
and attitudes; Change in CVH 
risk factors 
Health Behavior & 
Attitudes Survey; 
accelerometry; EHR 
data 
Patients 
Adoption 
Usability; acceptability; 
consistency with 
priorities/values 
Patient and parent 
interviews; Provider 
survey 
Patient, 
parent, 
provider 
Implementation Intervention delivery; fidelity to 
the protocol; time of 
PREVENT use; compatibility 
with workflow 
Direct observation, 
audio recordings of 
implementation 
Patient 
Maintenance 
Barriers and enabling factors 
for continued implementation 
of PREVENT 
Qualitative interviews; 
Provider survey; 
Clinical Sustainability 
Assessment Tool 
Provider 
 
 
4.4.1 EHR data extraction. Patient demographics (e.g., sex, date of birth, 
race/ethnicity) and the most recent risk factors for CVH (height, weight, fasting 
blood glucose, total cholesterol, blood pressure, smoking status) will be extracted 
at baseline (prior to clinic visit) and at follow-up (3-months). Available EHR data 
will be uploaded into PREVENT prior to the clinic visit but may be updated within 
the PREVENT tool at the time of the clinic visit if updated values are attained. 
CVH risk factor data within the tool at the time of the clinic will be used as 
baseline values and used to determine changes from baseline to follow-up. Only 
patients with abnormal baseline values will return for a follow-up clinic visit at 3-
months. Therefore, we acknowledge that not all patients will have updated 

 
 
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information for CVH risk factors (BMI, fasting blood glucose, total cholesterol and 
blood pressure) from baseline). This feasibility study is intended to determine 
what data are commonly available for a future study. We expect that height and 
weight will be the most commonly available data point at baseline and 3-months. 
Therefore, body mass index (BMI) is our primary health outcome and will be 
calculated based on CDC growth charts using height and weight. 
4.4.2 Demographics Survey will be used to collect parent and family 
demographics (e.g. annual household income, education-levels, family’s medical 
history) from parents of study participants (n=50) at baseline. The survey will be 
sent electronically using REDCap to give the parent the option of completing the 
survey prior to the clinic visit. Alternatively, the parent may complete the 
questionnaire while in the waiting room at the clinic.  
4.4.3. Health Behavior & Attitudes Survey will be used to collect physical 
activity and nutrition behaviors and attitudes from adolescent patients (n=50) at 
baseline and follow-up. This information will be used to populate the PREVENT 
tool’s risk profile and determine changes in physical activity and nutrition 
behaviors and attitudes from baseline to post-intervention. The physical activity 
questions are adapted from the International Physical Activity Questionnaire 
(IPAQ) that has been validated for use in adolescents.42,43 Nutrition questions are 
generated based on the Stoplight Diet38 for adolescents and the Rapid Eating 
Assessment for Participants - Shortened Version.44  Attitudes toward behavior 
change questions were adapted from two validated surveys: 1) 45-47the Treatment 
Self-Regulation Scale 48,49 and 2) the Rapid Eating Assessment for Participants - 
Shortened Version.44 
4.4.4 Accelerometers will be administered to patients at baseline and 6-month 
follow-up to objectively measure levels of physical activity (light, moderate, 
vigorous) and sedentary behaviors. At baseline, accelerometers will be mailed to 
participants after consent is obtained and returned by mail using a provided pre-
paid envelop or at the clinic visit. The following materials will be sent via mail with 
the accelerometer device: a pre-paid return envelope, a welcome letter, and 
directions for use. Participants randomized to the intervention group will also 
receive a document detailing “what to expect” at their clinic visit. At follow-up, 
accelerometers will be mailed including a pre-paid return envelope. Participants 
will be asked to wear the device for 7 days including 2 weekend days on a belt 
(provided) around their waist. Participants will be instructed to remove the device 
only when bathing or swimming; they will continue to wear the device while 
sleeping.  
4.4.5 Patient and parent qualitative interviews will examine facilitators and 
barriers to maintenance. Semi-structured interviews will be conducted individually 
with patients (n=10) and parents (n=10). Questions will assess satisfaction with 
their provider interaction, the PREVENT tool’s design, physical activity and 
nutrition prescriptions, community resources (e.g., are there other resources that 
would be helpful, did these resources help you or your child achieve the goals) 

 
 
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and, more generally, other ways the clinic may help them achieve behavior 
change. 
4.4.6 Provider survey will be conducted following the intervention to evaluate 
adoption and understand potential for maintenance. All providers will complete a 
web-based survey adapted from five previous instruments. The acceptability, 
appropriateness, and feasibility of the PREVENT tool will be assessed using the 
Acceptability of Intervention Measure (AIM), Intervention Appropriateness 
Measure (IAM), and Feasibility of Intervention Measure (FIM).44 Questions 
regarding the provider’s satisfaction with five aspects of health information 
technology: content, accuracy, format, ease of use and timeliness are adapted 
from Dr. Foraker’s (Co-I) previous research.34 Question to assess providers intent 
to change their behavior and continue using PREVENT (maintenance) were 
adapted from Legare’s CPD Reaction Questionnaire.50-52 We also include several 
team-developed items to align with previous measurement in the tool 
development phase. 
4.4.7 Direct observation, audio recordings of 15 patient-provider interactions 
will generate the following implementation outcomes: the delivery of the 
PREVENT tool (e.g., who is delivering the tool, how the provider delivers the 
information), whether it was delivered as intended (fidelity) and compatibility with 
clinic workflow. Additionally, observation will provide information on how the 
patient interacts with the tool. An observation form will be used by study staff to 
systematically observe PREVENT use. Audio recording will occur only while 
PREVENT is being used and will be assessed by two study staff to identify 
themes in patient-provider interaction and clinical decision-making.  
4.4.8 Patient follow-up surveys will be sent electronically at 4-, 8- and 12-
weeks to assess whether patient’s are obtaining their physical activity and food 
intake goals and provide tailored feedback (e.g., updated goals and motivation). 
4.4.9 Provider qualitative interviews will be conducted following the 4-month 
period to understand potential for maintenance. Thirty-minute interviews will be 
performed with a diverse group of 5-10 providers (e.g., physicians, physician 
assistants, nurses, clinic staff) at the clinic, by phone or by zoom technology. 
Interviews will be used to gain in-depth insight on what providers liked about the 
PREVENT tool, whether PREVENT is consistent with their and their clinic’s 
priorities/values, and barriers and enabling factors for sustaining PREVENT in 
their clinic.  
4.4.10 Clinical Sustainability Assessment Tool (CSAT) will be administered to 
all providers at the Late Effects Clinic following the intervention. CSAT will be 
administered to determine clinic-level readiness and capacity for sustainability of 
the PREVENT tool.53 Clinic-level factors include organization, financial, 
regulatory and political barriers.  

 
 
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5.0 Statistical Considerations  
5.1. Hypotheses.  
Aim 1. We hypothesize that the majority of providers, patients and parents will 
express positive views about the PREVENT tool and its sustained use in clinical 
settings.  
 
Aim 2. We hypothesize that patients who receive PREVENT will have greater 
improvements in attitudes toward behavior change recommendations, adherence 
to recommended behavior change and CVH compared to those who did not 
receive PREVENT during their clinic visit. 
 
5.2. Data Analysis Plan 
Statistical analysis will be performed using SAS v9.4 (quantitative data) and NVivo12 
software (qualitative data).  
For our Aim 1 hypothesis, analyses will be largely descriptive (using means, medians 
and frequencies) for adoption, implementation and maintenance outcomes using survey 
and observation data. Aim 1 will also be tested using qualitative data. In-depth interview 
and observation data will be professionally transcribed, anonymized, and imported into 
NVivo10 software for thematic analysis. The following steps will be performed for in-
depth interviews and observation data. Guides will be developed and piloted. Coders 
(n=2) will read over all transcripts and develop a draft of the coding tool. We will practice 
coding at least three transcripts together to make sure all concepts are adequately 
captured in the tool. Once the tool is finalized, coders will be assigned transcripts for 
coding, ensuring each one will be coded by at least two people for reliability and 
decreased positionality bias. We will summarize codes into general themes and highlight 
main findings with quotes. 
Our Aim 2 hypothesis will be tested using EHR data, accelerometry and patient survey 
data. Accelerometry data will be processed and analyzed using Actigraph software and 
SAS v9.4 using protocols validated in adolescents. The participants’ demographics and 
anthropometrics will be summarized using mean and standard deviation by treatment 
groups. The differences of factors of interest (physical activity, dietary intake, and CVH 
risk factors) between the 2 study groups at baseline will be compared using linear 
regressions. Change from baseline between study groups will be tested using linear 
regressions. Statistical significance will be defined as p<0.05. 
Ultimately, Aim 1 and Aim 2 quantitative and qualitative data will be integrated to 
determine overall feasibility, revise the PREVENT tool and identify barriers to current 
and future implementation that will inform an implementation strategy for the larger trial. 
 
6.0 Data Management 
Data will be stored on a secure information technology-maintained computing infrastructure 
behind the Washington University in St. Louis firewall, which has been certified to store 
protected health information. Paper forms will be stored in the principal investigators locked 

 
 
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office in a locked file cabinet. Accelerometry data will be downloaded and stored on the secure 
Washington University Server using patient ids. Data will be erased from the device immediately 
following download. All audio recording of patient visits and interviews will be transferred onto 
the secure server and de-identified. Audio-recordings will be deleted from the physical devices. 
Data from the PREVENT tool will also be stored on a secure information technology-maintained 
platform (Google Firebase) that complies with HIPPA standards. We will take consistent 
measures to protect the confidentiality of these data. When the data are collected and ready for 
analysis, the dataset will be downloaded by Dr. Kepper and used only for the purposes 
identified in these analysis. Only approved members of the research team will have access to 
these data. 
 
 
Table 4. Summary of Data Storage 
Data 
Location 
Informed consent/assent documents 
REDCap; paper forms 
Healthy Behavior Survey  
REDCap 
Acclerometry data 
Washington University Server 
EHR data 
Washington University Server 
Direct observation form 
REDCap 
Provider qualitative interviews 
Washington University Server 
Provider survey 
REDCap 
Adolescent and parent interviews 
Washington University Server 
Data entered into PREVENT 
Google Firebase 
 
7.0 Confidentiality and Privacy 
Confidentiality will be protected by collecting only information needed to assess study 
outcomes, minimizing to the fullest extent possible the collection of any information that could 
directly identify subjects, and maintaining all study information in a secure manner. To help 
ensure subject privacy and confidentiality, only a unique study identifier will appear on the data 
collection form. Any collected patient identifying information corresponding to the unique study 
identifier will be maintained on a linkage file, store separately from the data. The linkage file will 
be kept secure, with access limited to designated study personnel. Following data collection 
subject identifying information will be destroyed (three years after closure of the study), 
consistent with data validation and study design, producing an anonymous analytical data set. 
Data access will be limited to study staff. Data and records will be kept locked and secured, with 
any computer data password protected. No reference to any individual participant will appear in 
reports, presentations, or publications that may arise from the study. 
 
8.0 Data Safety and Management 
8.1 Data Safety and Monitoring Board The principal investigator (Dr. Kepper) will 
be responsible for the overall monitoring of the data and safety of study participants.  
The principal investigator will be assisted by other members of the study staff. 

 
 
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8.2 Reporting of Unanticipated Problems, Adverse Events or Deviations Any 
unanticipated problems, serious and unexpected adverse events, deviations or protocol 
changes will be promptly reported by the principal investigator or designated member of 
the research team to the IRB and sponsor or appropriate government agency if 
appropriate. 
 
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