Testing Digital Technologies to Help Families Build Healthy Habits
Phase: NA
Conditions: Childhood Obesity
Sponsor: Washington University School of Medicine

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
1 
 
 
 
 
 
 
 
Study 1 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
DATE: August 18th 2021 
 
 
 
Testing Digital Technologies to Help Families Build Healthy 
Habits 
 
Study 2 
Ellen Fitzsimmons-Craft, PhD – Principal Investigator 
Washington University School of Medicine 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
2 
 
 
 
 
TABLE OF CONTENTS 
A. List of Abbreviations 
3 
B. Introduction 
4 
B1.     Study Abstract 
4 
B2.     Primary Hypothesis 
4 
C. Background 
4 
C1.     Rationale for this Study 
4 
C2.     Prior Literature and Studies 
5 
D. Study Objectives 
6 
D1.     Study Aim 
6 
D2.     Rationale for the Selection of Outcome Measures 
6 
E. Study Design 
6 
E1.     Overview or Design Summary 
6 
E2.     Subject Selection and Withdrawal 
6 
E2.A.     Inclusion Criteria 
6 
E2.B.     Exclusion Criteria 
7 
E2.C.     Ethical Considerations 
7 
E2.D.     Participant Recruitment Plans and Consent Process 
8 
E2.E.     Randomization Method 
8 
E2.F.     Risks and Benefits 
8 
E2.G.     Early Withdrawal of Subjects 
11 
E2.H.     When and How to Withdraw Participants 
11 
E2.I.     Data Collection and Follow-up for Withdrawn Subjects 
11 
F. Study Procedures 
11 
F1.     Screening for Eligibility 
11 
F2.     Schedule of Measurements 
11 
F3.     Data Collection and Reporting Procedures for Adverse Events 
12 
G. Data Handling and Record Keeping 
12 
G1.     Confidentiality and Security 
12 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
3 
 
H. Study Administration 
13 
H.1.      Funding Source and Conflicts of Interest 
13 
H.2.      Participant Payment 
13 
I. References 
13 
J. Statistical Analysis Plan 
 
 
 
 
 
 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
4 
 
A. List of Abbreviations 
 
FBT 
 
Family-based Behavioral Treatment 
 
VR 
 
Virtual Reality 
 
 
REC 
 
Recruitment Enhancement Core 
 
REACH 
 
Community Based Recruitment and Retention 
WUSM 
 
Washington University in St. Louis School of Medicine 
 
NIH 
National Institutes of Health 
NIDDK 
 
National Institute of Diabetes and Digestive and Kidney 
Diseases 
 
PI 
 
Principal Investigator 
 
 
SUS 
 
System Usability Scale 
 
USE 
 
Usefulness, Satisfaction, and Ease of Use Questionnaire 
HIPAA 
Health Insurance Portability and Accountability Act 
PHI 
Protected Health Information 
T3 Research 
Translation to practice, including comparative effectiveness 
research, post-marketing studies, clinical outcomes 
research, as well as health services, and dissemination & 
implementation research 
WU PAARC 
Washington University Pediatric Adolescent Ambulatory 
Research Consortium 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
5 
 
ChEDE-Q 
Child Eating Disorder Examination-Questionnaire 
CDTR 
Center for Diabetes Translation Research (at Washington 
University in St. Louis) 
B. Introduction 
B1.     Study Abstract 
One in five children in the U.S. now has obesity.1 A child with obesity faces a life-threatening 
cascade of cardiovascular and metabolic disease and suffers from severe teasing and bullying 
that contribute to poor quality of life.2,3 Although evidence-based treatments exist, such as 
FBT,4,5 they are not widely available.6-11 Even when available, these treatments are costly and 
time-intensive, limiting reach, scalability, and adoption. More scalable approaches are needed 
for addressing childhood obesity. We propose to develop and build a 10-minute, prototype VR 
experience for children with overweight/obesity and their parents, based on a key tenet of FBT, 
in order to foster commitment to behavior changes in a format that would be engaging for 
children and scalable. This pilot study occurs after we have conducted usability testing with 
children with overweight/obesity and their parents over two cycles to inform refinements. 
B2.     Primary Hypothesis 
Piloting the VR experience through a small-scale randomized trial will allow for analysis of 
feasibility for a larger-scale NIH grant and provide initial impressions on whether VR may be able 
to magnify the effects of consideration of future consequences on cognitions and behavior. 
C. Background 
C1.     Rationale for this Study 
VR has been described as “the most psychologically powerful medium” in history.12 A 
fundamental characteristic of VR is that it provides users with a sense of “being there” (i.e., 
psychological presence), which results in VR environments producing emotional, behavioral, and 
physiological responses similar to those in real life, particularly in children.13-15 VR has shown 
promise for addressing obesity, eating disorders, and other psychiatric concerns in adults,16-19 
yet to date, there is a dearth of research on VR for childhood obesity. For this prototype, we 
plan to translate the FBT strategy of episodic future thinking to VR, which involves mentally 
projecting oneself into the future and pre-experiencing” a future event through visualization.20 
This increases the value of future events and hence motivation.21 Given VR’s ability to create 
psychological presence, this strategy is ripe for translation. If successful, this approach has 
potential for widespread dissemination and is in line with T3 research, as the ultimate goal is to 
translate key tenets from an evidence-based treatment into everyday settings by using a more 
scalable format. This work is highly aligned with the Strategic Plan for NIH Obesity Research,22 
which highlights key research opportunities, including “design[ing] and test[ing] novel weight-
control interventions that incorporate existing or emerging technologies (e.g., …virtual reality 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
6 
 
mediums)” and investigating “how electronic applications…can expand reach… and rapid 
dissemination.”  
C2.     Prior Literature and Studies 
Research has shown that VR is a promising tool for augmenting treatment approaches,23 
including for obesity and eating disorders.24,25 Preliminary work also shows VR as effective for 
delivering behavioral interventions in children.26,27 Embodiment experiences in immersive virtual 
environments, which allow individuals to see, hear, and feel digital stimuli as if they were in the 
physical world, have been shown to impact adults’ prosocial behavior and social anxiety;28 
however, less is known about VR’s effects in children. VR research in children has focused on 
treatment of ADHD, autism spectrum disorder, anxiety, pain, and rehabilitation,27, 29 and 
research with children undergoing physical rehabilitation suggests VR increases children’s self-
efficacy and adherence to their exercises by having their virtual bodies appear to move more 
fluidly than their physical bodies.30 Embodiment in VR may be particularly compelling compared 
to less immersive mediums, because children can control their avatar with their body  
movements, and the view of their physical body is replaced with their virtual body.31 Thus, 
embodiment in VR may be particularly promising for health interventions, and especially so for 
children.14,32 Despite burgeoning research on VR for health promotion, there is no work yet that 
leverages a VR experience as an intervention tool for childhood obesity.17 
 
FBT for childhood obesity is an evidence-based behavioral intervention that has been 
evaluated over the past 30 years by Co-Investigator Dr. Denise Wilfley and colleagues.5,33 One 
key tenet involves consideration of future consequences (i.e., episodic future thinking) to 
promote behavior change and is ripe for translation to VR, whereby the cognitive exercise of 
considering how present behavior impacts future health can be enhanced through 
embodiment. Specifically, a VR experience could amplify the impact of this strategy by allowing 
a child to experience what it might be like to live in various bodies in the future and see the 
long-term effects of dietary and activity behaviors in the immediate. Leveraging the flexibility of 
VR allows for the creation of avatars whose movements can differ from that of the 
participants' own, increasing the potential impact of consideration of the “future self” on 
motivation and behavior.34,35 Much work demonstrates the impact of consideration of one’s 
future or “possible” self on motivation and behavior across domains,36,37 including health 
behavior in early adolescents.38  VR has been used to connect individuals with a future self to 
promote behavior change;35 however, this has not been applied to health behaviors in 
children.  This project (studies 1 and 2) would translate a key tenet of FBT into a burgeoning 
technology and examine the usability, acceptability, and efficacy of the intervention on 
motivation and behavior among children aged 6-12 with overweight/obesity and their parents. 
D. Study Objectives 
D1.     Study Aim 
Study 2 aims to evaluate the efficacy of the VR experience vs video in terms of (2a) 
acceptability, (2b) motivation for behavior change, (2c) behavioral beliefs and intentions, 
and (2d) behavior (i.e., physical activity and dietary behavior two weeks later). Outcomes 
will be assessed at both the child and parent levels. Finally, we will compare the indirect 
effects of the two conditions on behavior through behavioral cognitions (2e; exploratory). 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
7 
 
With this study, we will generate data to set the stage for and inform subsequent NIH R-
series grants, thus launching a research program to establish a scalable solution to increase 
access to care for childhood obesity. 
D2.     Rationale for the Selection of Outcome Measures 
All participants will provide demographic information at baseline and will have height and 
weight measured. To determine acceptability (Aim 2a), we will use the SUS and USE. Those 
randomly assigned to VR will also complete the PQ. To examine motivation to make behavior 
change (Aim 2b), participants will complete measures assessing self efficacy39 and readiness to 
change behavior.40 Specifically, they will complete the 16-item Self-Efficacy for Healthy Eating 
and Physical Activity measure41 and self-efficacy to lose weight will be assessed with the 8-item 
Weight Efficacy Lifestyle Questionnaire.42,43 Readiness to change behavior will be measured by 
the 6-item Readiness to Change Diet and Physical Activity Scale.44 To examine behavioral beliefs 
and intentions (Aim 2c), participants will complete measures of behavioral cognitions from the 
Theory of Planned Behavior, including behavioral beliefs, attitudes, and intentions related to 
eating an activity behaviors.45,46 Finally, to examine behavior (Aim 2d), participants will complete 
self-report measures of activity and eating behavior over the past week, adapted from the 
Health Behavior in School-aged Children survey47 at baseline and 2-week follow-up. The 10-item 
Positive and Negative Affect Schedule for Child and Parent48 will be administered to control for 
mood and the child emotional eating scale serves as a measure of emotion regulation. Body 
esteem will be measured with several items from the Body Esteem Scale.49, 50   
E. Study Design  
E1.     Overview or Design Summary                                                                         
Study 2 will use a randomized pilot trial design to compare the VR experience to a video 
(created by team at WUSM) that provides child-friendly education on what types of foods are 
most nutritious and which are less healthy, and how the food they eat and activity they engage 
in now affects their health and future. The video will also encourage consideration of future 
consequences.  
E2.     Subject Selection and Withdrawal  
     E2.A.     Inclusion Criteria  
 
1. Parent is biological or legal guardian and can therefore consent on behalf of the child 
2. Parent BMI is greater than or equal to 25 (overweight or obese) 
2. Parent is under 80 years old and child is between 6 and 12 years old  
3. Child BMI is at or above the 85th percentile for age and sex.51  
4. Child is not in behavioral weight-loss treatment (behavior weight-loss treatment will not 
include if their pediatrician is counseling them on their weight, but instead refers to intensive 
outpatient behavioral treatment for overweight/obesity only)  
5. Child and parent do not have a history of seizures, a history of severe psychiatric conditions 
such as Schizophrenia or Paranoia, or use any medical devices such as pacemakers 
6. Child is not exhibiting any disordered eating behavior (i.e. purging, laxative or diuretic use). 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
8 
 
    E2.B.     Exclusion Criteria  
1. Parent is not biological or legal guardian and therefore cannot consent on behalf of the child 
2. Parent BMI is less than 25 (not overweight or obese) 
2. Parent is over 80 years old and/or child is younger than 6 or older than 12  
3. Child BMI is below the 85th percentile for age and sex.51  
4. Child is in behavioral weight-loss treatment (behavior weight-loss treatment will not include if 
their pediatrician is counseling them on their weight, but instead refers to intensive outpatient 
behavioral treatment for overweight/obesity only)  
5. Child and parent have a history of seizures, a history of severe psychiatric conditions such as 
Schizophrenia or Paranoia, or use any medical device such as a pacemaker 
6. Child has a history of disordered eating behavior (i.e. purging, laxative or diuretic use). 
 
    E2.C.     Ethical Considerations  
All key personnel involved in the design or conduct of research involving human subjects will 
receive the required education on the protection of human research participants prior to the 
start of the study. Participants will be informed that they do not have to answer any questions 
that make them uncomfortable. There are minimal risks for participating in pilot testing. Testing 
and assessments will occur in private rooms to protect the anonymity of the participant. 
 
Participants will be provided with the contact information of the research staff. As a clinical 
psychologist, the PI is trained in how to address safety issues. The PI, a licensed psychologist, will 
be available for in-person crisis assessment. Any participants that indicate they are engaging in 
disordered eating behaviors during screening or participation in the study will be offered 
referral information for in-person treatment. Any adverse event will be reported promptly to 
the IRB. 
 
Confidentiality: Participant confidentiality will be maintained in compliance with HIPAA privacy 
protected servers. Study IDs will be linked with participant names and email addresses in a 
separate password-protected file stored on a secure, password-protected server that only key 
study personnel have access to. All hard copy PHI will be stored in locked cabinets within locked 
doors in our laboratory at WUSM. All employees of the study with access to PHI are required to 
complete HIPAA training and comply with the privacy procedures in place at Washington 
University.  
 
BehaVR (https://behavr.com) is a HIPAA-compliant company focused on building VR 
products for behavior change and has a dedicated and talented team of software 
engineers. BehaVR will host the proposed VR experience and all data collected within the 
VR experience. Prior to beginning this study, BehaVR and Washington University will 
enter into a collaboration agreement.  
 
Adverse Events:  For the purpose of this study, adverse events will be defined as 
unanticipated problems involving risks to the study participant. A serious adverse event will 
be defined as any untoward occurrence that results in death, is life-threatening, or creates 
persistent and significant disability. The study team will work together to identify serious 
adverse events. Any potentially adverse events will be evaluated by the study team within 72 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
9 
 
hours. All serious adverse events will be immediately reported to the IRB. All adverse events 
and study withdrawals, together with a detailed explanation of the event and withdrawal, will 
be recorded. 
 
It is important to note that in previous studies of digital health interventions, the 
procedures outlined above have been used to protect against and minimize potential risks 
to participants, and they have proved effective in preventing emotional and physical 
complaints as well as adverse events. 
  
     E2.D.     Participant Recruitment Plans and Consent Process 
We plan to enroll 60 English-speaking children between the ages of 6 and 12 and one of their 
biological or legal adult guardians.  
 
Participants will be recruited from the community using methods such as social media, flyers 
and word of mouth. Flyers will be posted in local (i.e., primarily St. Louis, MO) kid-friendly public 
spaces. Social media recruitment will occur over family-friendly social media and webpages. The 
social media advertisement will be posted on relevant WUSM accounts and to relevant web 
pages (i.e. family-based and health related pages and groups). We may also utilize participant 
recruitment services available through REC and REACH. Additionally, we may seek permission 
from WU PAARC to ask pediatric practices that are familiar with our lab through another study 
we are conducting (PLAN with families) if they would be willing to advertise for this study via 
postcards made available to give to patient families.  
 
Interested individuals may call or email our research team whose contact information will be 
provided on flyers and social media posts and we may also reach out directly to some potential 
participants. If individuals are still interested after discussing the study directly with a research 
team member over phone and/or email, a research team member will conduct a brief phone 
screen to determine eligibility. If eligible, an appointment will be made for the parent and child 
to come into our lab at WUSM to review and sign consent and assent documents and then 
complete the study. Consent and assent information will be emailed to them so that they may 
have plenty of time to review these documents at their leisure. Upon arrival to our lab the 
informed consent process will take place, and subsequently the study. The informed consent 
process will occur in a private room in the Center for Healthy Weight and Wellness at 
Washington University School of Medicine in St. Louis. Participants will be consented according 
to the policies and procedures of the WUSM IRB, the IRB of Record for the study.  
 
8/10/21 
We will also use snowball sampling by reaching out to completed participants via email to ask if 
they would be willing to share recruitment materials with friends or family who may be 
interested in participating. 
      E2.E.     Randomization Method 
Using a random number generator, families will be randomly assigned to the experimental or 
control condition after baseline measures are taken. Those assigned to the experimental 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
10 
 
condition will undergo the 10-minute VR experience (both children and parents) while those 
assigned to the control condition will view the educational video and play the educational game 
for a total of 10 minutes.  
     E2.F.     Risks and Benefits 
Risks: All key personnel involved in the design or conduct of research involving human subjects 
will receive the required education on the protection of human research participants prior to 
the start of the study. Participants will be informed that they do not have to answer any 
questions that make them uncomfortable. There are minimal risks for participating in pliot 
testing. Testing and assessments will occur in private rooms to protect the anonymity of the 
participant. 
 
Participants will be provided with the contact information of the study staff. As a clinical 
psychologist, the PI is trained in how to address safety issues. If any participant appears to be 
in crisis during the experiment, appropriate action will be taken based on established crisis 
assessment protocol. All participants completing the experiment will be offered referral 
information for in-person treatment. Any serious adverse event will be reported promptly to 
the IRB. 
 
Physical Risks: Participants will be engaging with the virtual environment through physical 
movement (e.g., stepping), and will be unable to see their surroundings (because they will be 
wearing a device over their eyes to engage with the VR experience), so the area in which 
individuals use the VR equipment will be open and clear of objects. Users will be monitored by 
trained staff to ensure they are safe when using the VR equipment. Finally, some individuals can 
feel motion sickness or nausea during a VR experience. Although this is not likely, participants 
will be told that if they do not feel well, they do not have to continue with the VR experience 
and that they can discontinue participation in this aspect of the study without penalty. Trained 
staff will assist in the event that participants need further care.   
 
Psychological Risks: There are minimal psychological risks of participating in the pilot study for 
our proposed VR experience, although we recognize that programs designed to address weight 
may promote increased focus on weight in some individuals, more than which may exist before 
starting the program. It is also possible that participants may feel uncomfortable disclosing 
information or related thoughts about their weight. However, we have asked questions of a 
similar nature in several studies in the past and have not had participants report major 
discomfort. Because children may also be more likely to perceive the virtual environment as 
real, special consideration will be given to children after the VR experience to ensure they 
understood that the VR environment was not real if necessary (we did not find this to be an 
issue in study 1). Finally, participants may experience negative affect when experiencing the 
future embodiment part of the time machine game that is reflective of continued engagement 
in unhealthy behaviors with decreased agility. In order to decrease the likelihood of negative 
affect in the VR experience, all participants in the VR condition will experience the healthy and 
unhealthy future self, and the first future they go to will be determined by a food choice game 
in the present. This gives the participant the autonomy of choice, and presents two different 
futures, so that it is clear that they are not being told one way or another how they may feel in 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
11 
 
the future, just how it may feel if they were to engage in healthy vs. unhealthy behavior. 
Participants will be told that if they feel too uncomfortable in the VR experience, they can stop 
using it at any time without penalty.   
 
Social Risks: There may be some embarrassment related to completing questions related to 
weight and intentions to lose weight. 
 
Financial Risks: N/A 
 
Legal Risks: N/A 
 
Risks to Privacy: There are minimal to no risks to participant privacy. We will go to great lengths 
to keep participant information private and confidential.  
 
Other Risks: N/A 
 
Alternative Treatments: N/A – Participants in the current study will be participating in a pilot 
trial to test a VR experience to address childhood obesity. There are few widely available 
digital tools designed for this purpose. All participants who participate will be offered referral 
information for in-person treatment. 
 
Benefits 
 
For individuals participating in the pilot study, there may be no direct benefits in terms of 
addressing overweight or obesity. However, individuals participating may benefit from 
knowing that their feedback is helping to design a digital tool that may ultimately address 
childhood obesity. 
 E2.G.     Early Withdrawal of Subjects  
Informed consent will make clear that participants may withdraw at any time with no penalty.  
     E2.H.     When and How to Withdraw Participants  
Taking part in this research study is voluntary. Participants may choose not to take part in this 
research study or may withdraw their consent at any time. They may withdraw by telling the 
research team they are no longer interested in participating in the study. If participants do not 
respond to phone calls or emails after 6 attempts to contact, they will be withdrawn from the 
study. Additionally, there will be 6 attempts to contact participants for the 2 week follow-up 
surveys via email or phone. There will be no penalty or loss of benefits to which they were 
otherwise entitled. 
     E2.I.     Data Collection and Follow-up for Withdrawn Subjects  
When a participant withdraws from the study, the research team will stop collecting data from 
them. 
F. Study Procedures  

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
12 
 
F1.     Screening for Eligibility 
Eligibility will be assessed using the phone eligibility screen. 
F2.     Schedule of Measurements 
 
Construct 
Measure(s) 
Participant(s) Taking 
Time point 
Eligibility 
Screen for disordered 
eating behaviors 
Selected and Adapted 
Questions from ChEDE-Q 
Parent self and proxy-report Phone screen 
Screen for overweight and 
conditions that could 
make it unsafe to 
participate in VR condition 
Other Eligibility Questions 
 
In-lab height & weight 
Parent self and proxy-report 
 
Parent & Child 
Phone screen 
 
Pre 
1. Acceptability (Aim 2a) 
Usability 
System Usability Scale 
Parent proxy-report 
post 
 
Selected Child Interview 
Questions 
Child self-report 
Ease of Use 
Usefulness, Satisfaction 
and Ease of Use 
Parent proxy-report 
Selected Child Interview 
Questions 
Child self-report 
Degree of immersion (for 
those in VR condition) 
Presence Questionnaire 
Parent self-report 
Selected Child Interview 
Questions 
Child self-report 
1. 
Motivation to Change behavior (Aim 2b) 
Self-Efficacy 
Self-Efficacy for Healthy 
Eating and Physical 
Activity (SE-HEPA) 
Child self-report,  
Pre & post 
Readiness to Change 
Behavior 
Readiness to Change Diet 
and Physical Activity 
Scale 
Parent self-report  
Pre and post 
or 2-weeks 
depending on 
each question 
1. 
Behavioral Beliefs and Intentions (Aim 2d) 
Attitudes, Beliefs, and 
Intentions 
Theory of Planned 
Behavior Items 
Parent and child self-report 
Pre and post 
1. 
Behavior (Aim 2d) 
Eating and Physical Activity 
Behavior 
Weekly intake of fruits 
and vegetables; fast food; 
foods away from home; 
consumption of breakfast 
Parent proxy-report 
           
Pre and 2-
week 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
13 
 
Screen time and minutes 
of mild, moderate, and 
vigorous activity over the 
past week 
1. 
Other Measures 
Body Mass Index (BMI) 
In-lab height and weight 
Parent & Child 
pre 
Demographics 
Demographic 
Questionnaire 
Parent report 
pre 
Hunger 
1 item 7 point likert 
scale 
Child report 
pre 
Affect 
 
 
 
Positive and Negative 
Affect Schedule (PANAS) 
Child 
Pre and post 
Child Emotional Eating 
Scale Short Form (EES-C 
SF) 
Child self-report 
Pre and post 
Body Esteem Scale 
(adapted) 
Child self-report 
Pre and post 
F3.     Data Collection and Reporting Procedures for Adverse Events 
For the purpose of this study, adverse events will be defined as unanticipated problems 
involving risks to the study participant. A serious adverse event will be defined as any 
untoward occurrence that results in death, is life-threatening, or creates persistent and 
significant disability. The study team will work together to identify serious adverse events. 
Any potentially adverse events will be evaluated by the study team within 72 hours. All 
serious adverse events will be immediately reported to the IRB. All adverse events and study 
withdrawals, together with a detailed explanation of the event and withdrawal, will be 
recorded. 
 
It is important to note that in previous similar clinical trials of digital health interventions, 
the procedures outlined above have been used to protect against and minimize potential 
risks to participants, and they have proved effective in preventing emotional and physical 
complaints as well as adverse events. 
G. Data Handling and Record Keeping  
G1.     Confidentiality and Security 
Participant confidentiality will be maintained in compliance with HIPAA regulations. Data will 
be stored in locked file cabinets and on HIPAA privacy protected servers. Study IDs will be 
linked with participant names and email addresses in a separate password-protected file 
stored on a secure, password-protected server that only key study personnel have access to. 
All employees of the study with access to protected health information are required to 
complete HIPAA training and comply with the privacy procedures in place at Washington 
University. 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
14 
 
 
BehaVR (https://behavr.com) is a HIPAA-compliant company focused on building VR 
products for behavior change and has a dedicated and talented team of software 
engineers. BehaVR will host the proposed VR experience and all data collected within the 
VR experience. Prior to beginning this study, BehaVR and Washington University will 
enter into a Business Associate and Qualified Service Organization agreement. BehaVR 
will comply with the rules on handling of Protected Health Information under HIPAA. 
 
Training: All staff personnel are trained and comply with HIPAA regulations. All study team 
members will complete the CITI training and Good Clinical Practice training. 
 
Performance Monitoring: The Data and Safety Monitoring Plan for this trial includes close 
monitoring by the PI. Any adverse event will be reported promptly to the IRB.  
H. Study Administration 
H.1.      Funding Source and Conflicts of Interest 
This study is funded by the Washington University Center for Diabetes Translation Research, 
which is funded by the NIDDK. Any potential financial conflicts of interest for individual research 
team members are reported according to the IRB requirements and procedures. 
H.2.      Participant Payment 
Participants will each receive a $25.00 gift card for completing the in-lab visit and a $25.00 gift 
card for completing the two week follow-up survey as well as a chance to win one of two $250 
gift cards via a raffle. 
 
 
 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
15 
 
I. References 
1. Centers for Disease Control and Prevention. Overweight and obesity. 2018 
[Available from: https://www.cdc.gov/obesity/.  
2. Fallon EM, Tanofsky-Kraff M, Norman AC, McDuffie JR, Taylor ED, Cohen ML, et 
al. Health-related quality of life in overweight and nonoverweight black and 
white adolescents. J Pediatr. 2005;147(4):443-50. PMICID: PMC2266889.  
3. Schwimmer JB, Burwinkle TM, Varni JW. Health-related quality of life of severely 
obese children and adolescents. JAMA. 2003;289(14):1813-9. PMID: 12684360.  
4. Wilfley DE, Saelens BE, Stein RI, Best JR, Kolko RP, Schechtman KB, et al. Dose, 
Content, and Mediators of Family-Based Treatment for Childhood Obesity: A 
Multisite Randomized Clinical Trial. JAMA pediatrics. 2017;171(12):1151-9. 
PMCID: PMC6169680.  
5. Epstein LH, Paluch RA, Roemmich JN, Beecher MD. Family-based obesity 
treatment, then and now: twenty-five years of pediatric obesity treatment. 
Health Psychol. 2007;26(4):381-91. PMCID: PMC2387251.  
6. Cook S, Weitzman M, Auinger P, Barlow SE. Screening and counseling associated 
with obesity diagnosis in a national survey of ambulatory pediatric visits. 
Pediatrics. 2005;116(1):112-6. PMID: 15995040.  
7. Kolagotla L, Adams W. Ambulatory management of childhood obesity. Obes Res. 
2004;12(2):275-83. PMID: 14981220.  
8. Perrin EM, Flower KB, Garrett J, Ammerman AS. Preventing and treating obesity: 
pediatricians' self- efficacy, barriers, resources, and advocacy. Ambul Pediatr. 
2005;5(3):150-6. PMID: 15913408.  
9. Simpson LA, Cooper J. Paying for obesity: a changing landscape. Pediatrics. 
2009;123 Suppl 5:S301-7. PMID: 19470607.  
10. Story MT, Neumark-Stzainer DR, Sherwood NE, Holt K, Sofka D, Trowbridge FL, et 
al. Management of child and adolescent obesity: attitudes, barriers, skills, and 
training needs among health care professionals. Pediatrics. 2002;110(1 Pt 2):210-
4. PMID: 12093997.  
11. Tershakovec AM, Watson MH, Wenner WJ Jr., Marx AL. Insurance 
reimbursement for the treatment of obesity in children. Journal Pediatr. 
1999;134(5):573-8. PMID: 10228292.  
12. Bailenson J. Experience on demand: What virtual reality is, how it works, and 
what it can do: WW Norton & Company; 2018.  
13. de Carvalho MR, Dias TRS, Duchesne M, Nardi AE, Appolinario JC. Virtual Reality 
as a Promising Strategy in the Assessment and Treatment of Bulimia Nervosa and 
Binge Eating Disorder: A Systematic Review. Behav Sci (Basel). 2017;7(3). 
PMICID: PMC5618051.  
14. Sharar SR, Carrougher GJ, Nakamura D, Hoffman HG, Blough DK, Patterson DR. 
Factors influencing the efficacy of virtual reality distraction analgesia during 
postburn physical therapy: preliminary results from 3 ongoing studies. Arch Phys 
Med Rehabil. 2007;88(12):S43-S9. PMID: 18036981.  

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
16 
 
15. Won AS, Bailey J, Bailenson J, Tataru C, Yoon IA, Golianu B. Immersive Virtual 
Reality for Pediatric Pain. Children (Basel). 2017;4(7). PMICID: PMC5532544.  
16. Clus D, Larsen ME, Lemey C, Berrouiguet S. The Use of Virtual Reality in Patients 
with Eating Disorders: Systematic Review. J Med Internet Res. 2018;20(4):9. 
PMCID: PMC594841.  
17. Ferrer-Garcia M, Gutierrez-Maldonado J, Pla J. Cue-elicited anxiety and craving 
for food using virtual reality scenarios. Stud Health Technol Inform. 
2013;191:105-9. PMID: 23792853.  
18. McCann RA, Armstrong CM, Skopp NA, Edwards-Stewart A, Smolenski DJ, June 
JD, et al. Virtual reality exposure therapy for the treatment of anxiety disorders: 
an evaluation of research quality. J Anxiety Disord. 2014;28(6):625-31. PMID: 
25093964.  
19. Valmaggia LR, Latif L, Kempton MJ, Rus-Calafell M. Virtual reality in the 
psychological treatment for mental health problems: An systematic review of 
recent evidence. Psychiatry Res. 2016;236:189-95. PMID: 26795129.  
20. Atance CM, O'Neill DK. Episodic future thinking. Trends Cogn Sci. 2001;5(12):533-
9. PMID: 11728911.  
21. Hayes JF, Eichen DM, Barch DM, Wilfley DE. Executive function in childhood 
obesity: Promising intervention strategies to optimize treatment outcomes. 
Appetite. 2018;124:10-23. PMCID: PMC5702584.  
22. National Institute of Diabetes and Digestive and Kidney Diseases. Strategic Plan 
for NIH Obesity Research 2011 [Available from: 
https://www.niddk.nih.gov/about-niddk/strategicplans-reports/strategic- plan-
for-nih-obesity-research.  
Maskey M, Rodgers J, Ingham B, Freeston M, Evans G, Labus M, et al. Using 
Virtual Reality Environments to Augment Cognitive Behavioral Therapy for Fears 
and Phobias in Autistic Adults. Autism in Adulthood. 2019. DOI: 
10.1089/aut.2018.0019.  
23. Cesa GL, Manzoni GM, Bacchetta M, Castelnuovo G, Conti S, Gaggioli A, et al. 
Virtual Reality for Enhancing the Cognitive Behavioral Treatment of Obesity With 
Binge Eating Disorder: Randomized Controlled Study With One-Year Follow-up. J 
Med Internet Res. 2013;15(6):13. PMCID: PMC3713949.  
24. Manzoni GM, Cesa GL, Bacchetta M, Castelnuovo G, Conti S, Gaggioli A, et al. 
Virtual Reality-Enhanced Cognitive-Behavioral Therapy for Morbid Obesity: A 
Randomized Controlled Study with 1 Year Follow-Up. Cyberpsychology Behavior 
and Social Networking. 2016;19(2):134-40. PMCID: PMC4770914.  
25. Arane K, Behboudi A, Goldman RD. Virtual reality for pain and anxiety 
management in children. Can Fam Physician. 2017;63(12):932-4. PMICD: 
PMC5729140.  
26. Bioulac S, de Sevin E, Sagaspe P, Claret A, Philip P, Micoulaud-Franchi JA, et al. 
[What do virtual reality tools bring to child and adolescent psychiatry?]. 
Encephale. 2018;44(3):280-5. PMID: 28870688.  

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
17 
 
27. Ahn SJG, Bailenson JN, Park D. Short-and long-term effects of embodied 
experiences in immersive virtual environments on environmental locus of 
control and behavior. Comp Hum Behav. 2014;39:235-45. DOI: 
10.1016/j.chb.2014.07.025.  
28. Bailey JO, Bailenson JN. Considering virtual reality in children’s lives. J Child 
Media. 2017;11(1):107-13. DOI: 10.1080/17482798.2016.1268779.  
29. Won AS, Tataru CA, Cojocaru CM, Krane EJ, Bailenson JN, Niswonger S, et al. Two 
Virtual Reality Pilot Studies for the Treatment of Pediatric CRPS. Pain Med. 
2015;16(8):1644-7. PMID: 25930099.  
30. Won AS, Tataru CA, Cojocaru CM, Krane EJ, Bailenson JN, Niswonger S, et al. Two 
Virtual Reality Pilot Studies for the Treatment of Pediatric CRPS. Pain Med. 
2015;16(8):1644-7. PMID: 25930099.  
31. Baumgartner T, Speck D, Wettstein D, Masnari O, Beeli G, Jäncke L. Feeling 
present in arousing virtual reality worlds: prefrontal brain regions differentially 
orchestrate presence experience in adults and children. Front Hum Neurosci. 
2008;2:8. PMCID: PMC2572200.  
32. Wardle J. Parental influences on children's diets. Proc Nutr Soc. 1995;54(3):747-
58. PMID: 8643712.  
33. Raposo S, Sims T, Bailenson J, Carstensen L. Imagining but not confronting one's 
future self may improve views of old age. Gerontologist. 2016;56. DOI: 
10.1093/geront/gnw162.2550.  
34. Sims T, Bailenson J, Carstensen L. Connecting to your future self: Enhancing 
financial planning among diverse communities using virtual technology. Paper 
presented at the annual meeting of the Gerontological Society of America, 2015, 
Orlando, FL.  
35. Markus H, Nurius P. Possible selves. Am Psychol. 1986;41(9):954. DOI: 
10.1037/0003-066X.41.9.954  
36. Hoyle RH, Sherrill MR. Future orientation in the self-system: Possible selves, self-
regulation, and behavior. J Pers. 2006;74(6):1673-96. PMID: 17083662.  
37. Aloise-Young PA, Hennigan KM, Leong CW. Possible selves and negative health 
behaviors during early adolescence. J Early Adolesc. 2001;21(2):158-81. DOI: 
10.1177/0272431601021002002.  
38. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol 
Rev. 1977;84(2):191. PMID: 847061. 
39. Prochaska JO, Norcross JC. Stages of change. Psychother Theor Res Pract Train. 
2001;38(4):443. DOI: 10.1037/0033-3204.38.4.443. 
40. Steele MM, Burns LG, Whitaker BN. Reliability and validity of the SE-HEPA: 
Examining physical activity–and healthy eating–specific self-efficacy among a 
sample of preadolescents. Health Educ Behav. 2013;40(3):355-61. PMID: 
23041703. 
41. Clark MM, Abrams DB, Niaura RS, Eaton CA, Rossi JS. Self-efficacy in weight 
management. J Consult Clin Psychol. 1991;59(5):739-44. PMID: 1955608. 

 
 
 
 
 
 
______________________________________________________________________________________ 
 
______________________________________________________________________________________ 
18 
 
42. Quinlan NP, Kolotkin RL, Fuemmeler BF, Costanzo PR. Psychosocial outcomes in a 
weight loss camp for overweight youth. Int J Pediatr Obes. 2009;4(3):134-42. 
PMCID: PMC4696553. 
43. Rhee KE, McEachern R, Jelalian E. Parent readiness to change differs for 
overweight child dietary and physical activity behaviors. J Acad Nutr Diet. 
2014;114(10):1601-10. PMICD: PMC4177446. 
44. Branscum P, Sharma M. Using the theory of planned behavior to predict two 
types of snack food consumption among midwestern upper elementary children: 
implications for practice. Int Q Community Health Educ. 2012;32(1):41-55. PMID: 
22547496. 
45. Ajzen I, Fishbein M. Scaling and testing multiplicative combinations in the 
expectancy–value model of attitudes. J Appl Soc Psychol. 2008;38(9):2222-47. 
DOI: 10.1111/j.1559-1816.2008.00389.x. 
46. Levin KA, Kirby J, Currie C. Family structure and breakfast consumption of 11-15 
year old boys and girls in Scotland, 1994-2010: a repeated cross-sectional study. 
BMC Public Health. 2012;12(1):228. PMCID: PMC3373369. 
47. Ebesutani C, Regan J, Smith A, Reise S, Higa-McMillan C, Chorpita BF. The 10-
item positive and negative affect schedule for children, child and parent 
shortened versions: application of item response theory for more efficient 
assessment. J Psychopathol Behav Assess. 2012;34(2):191-203. DOI: 
10.1007/s10862-011-9273-2. 
48. Mendelson BK, White DR. Relation between body-esteem and self-esteem of 
obese and normal children. Percept Mot Skills. 1982;54(3):899–905. 
doi:10.2466/pms.1982.54.3.899 
49. Davison KK, Birch LL. Childhood overweight: a contextual model and 
recommendations for future research. Obes Rev. 2001;2(3):159–171. 
doi:10.1046/j.1467-789x.2001.00036.x 
50. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, et al. CDC growth charts: United 
States. Adv Data. 2000(314):1-27. 
 
J. Statistical Analysis Plan 
Univariate analyses of variance (ANOVA) models evaluated pre- to post-test changes in positive 
and negative affect by condition. T-tests evaluated the difference in acceptability measures 
between conditions. Repeated-measures general linear models, with time as the within-subjects 
factor, tested the effect of the VR intervention on eating and activity behaviors (pre to two-
weeks) and cognitions (pre to post). Child age was included as a covariate in all analyses. Tests 
of normality were conducted on dependent variables across and within conditions using 
histograms, normality plots, skewness, and kurtosis metrics, and relevant dependent variables 
were transformed (e.g., cubed) when necessary. Assumptions of linearity and homogeneity of 
regression slopes were examined with scatterplots and interaction terms of condition and the 
relevant pre-test variable.