Targeting Obesity and Blood Pressure in Urban Youth(Consortium Title: Childhood Obesity Prevention and Treatment Research [COPTR] and Site Project Name IMPACT (Ideas Moving Parents and Adolescents to Change Together).
Phase: NA
Conditions: Overweight, Obese
Sponsor: Case Western Reserve University

Project Title: IMPACT (Ideas Moving Parents and Adolescents to Change Together) 
NCT Number: NCT01514279
Date: March 30, 2012

Case Western Reserve University 
Main Trial Protocol 
TABLE OF CONTENTS 
List of Abbreviations .......................................................................................................... 4 
List of Tables ..................................................................................................................... 4 
List of Figures .................................................................................................................... 5 
List of Appendices ………………………………………………………………………………..5 
Appendix A: SystemCHANGE 36 month Teaching Plan 
Appendix B: HealthyCHANGE 36 month Teaching Plan
Appendix C: Tools4CHANGE (control group) Teaching Plan 
Appendix D:  Adaptive Intervention Protocol 
Appendix E:  Enriched School Environment
Appendix F   Consent Forms 
1.
EXECUTIVE SUMMARY ............................................................................................ 6 
2.
SPECIFIC AIMS AND OBJECTIVES FOR MAIN TRIAL
2.1. Primary Aims ....................................................................................................... 7-8 
2.2. Secondary Aims ................................................................................................... 8 
3.
BACKGROUND AND RATIONALE ............................................................................ 8-10 
4.
FORMATIVE RESEARCH – PHASE 1
4.1. Aims, Objectives, Interventions and Measurements……………………………   10-13 
4.2. Results from Phase 1……………………………………………………………….. 13-20 
4.3. Key Recommendations for  Phase 2………………………………………………. 20-21 
5.
STUDY POPULATION
5.1. Eligibility Criteria …………………………………………………………………….. 21-22 
5.2. Exclusions ……………………………………………………………………………. 22-23 
5.3. Inclusion Statement ............................................................................................  23 
6.
RECRUITMENT AND RETENTION
6.1. Recruitment Tracking ……………………………………………………………….  23-24 

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6.2. Recruitment of Minorities …………………………………………………………… 24-25 
6.3. Procedures for Obtaining Informed Consent ......................................................  25 
6.4. Randomization Procedures ………………………………………………………… 25-29 
6.5. Techniques for Retention …………………………………………………………..  29-33 
7.
INTERVENTION
7.1. Conceptual Framework ……………………………………………………………... 33-34 
7.2. Description of the Intervention(s)…………………………………………………… 34-38 
7.3. Process Measures …………………………………………………………………..  38-45 
7.4. Unblinded Process Measures ……………………………………………………… 45-47 
8.
CONTROL CONDITION .............................................................................................  47 
9.
MEASUREMENTS
9.1.  Methods
9.1.1.  Primary outcome (the other anthropometric variables)………………….  48-51 
9.1.2.  Common mediators, moderators and secondary outcomes ……………  51-74 
9.1.3.  Site-Specific Demographics, Mediators, Moderators and 
Secondary Outcomes ……………………………………………………….  74-77 
9.2.  Quality Control 
9.2.1. Primary Outcome* ………………………………………………………….   77-78 
9.2.2. Common Mediators, Moderators, and Secondary Outcomes* ………..   78-79 
9.2.3. Site-Specific Mediators, Moderators and Secondary Outcomes ………  79-81 
9.3.  Measurement Schedule ……………………………………………………………  81 
10. PARTICIPANT SAFETY AND ADVERSE EVENTS MONITORING
10.1. Potential Risks and Protection Against Risks …………………………………..   81-83 
10.2. Potential Benefits …………………………………………………………………..   83 
10.3. Safety Monitoring Plan …………………………………………………………….   83-86 
10.4. Informed Consent Documents ……………………………………………………   86 
11. STUDY DESIGN, STATISTICAL CONSIDERATION AND ANALYSIS PLAN
11.1. Study Design ………………………………………………………………………..  87 
11.2. Primary Research Question and Hypothesis ……………………………………  87 
11.3. Primary Outcome …………………………………………………………………..   87 
11.4. Primary Analysis 
11.4.1. Statistical Model and Approach …………………………………………..  87-88 
11.4.2. Assumptions with Justification ……………………………………………  88-90 
11.4.3. Missing data ………………………………………………………………..   90 
11.5. Detectable Difference, Sample Size and Power ……………………………….   90-92 
11.6. Analysis for Possible Effect Modifiers ……………………………………………  92 
11.7. Analysis for Possible Effect Mediators ………………………………………….   93 

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11.8. Secondary Hypotheses and Analyses …………………………………………..   93-94 
11.9. Additional Analysis …………………………………………………………………  94 
12. DATA MANAGEMEMENT AND QUALITY CONTROL …………………………….   94 
12.1. Common Database (data capture and data audits)* …………………………  94-101 
12.2. Site-Specific Database (data capture and data audits) ……………………..  102-104 
13. SITE SPECIFIC TIMELINE ……………………………………………………………  105 
14. LITERATURE CITED…………………………………………………………………… 106-121 
*Asterisk those items that are common across sites.

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List of Abbreviations 
BMI 
Body Mass Index 
EBP 
Elevated Blood Pressure  
CMSD 
Cleveland Metropolitan School District 
COPTR 
Child Obesity Prevention and Treatment Research  
IMPACT 
Ideas Moving Parents and Adolescents to Change Together 
WRTC 
We Run This City Youth Marathon Program 
YRBS 
Youth Risk Behavior Survey 
List of Tables 
Table 6.1  Minimization Approach:  Distributed by Study Group 
and Stratification Level ……………………………………………………………. 28 
Table 7.1 Process Measures – Case Western Reserve University ……………………….38-40 
Table 7.2 Fidelity Measures: Case Western Reserve University ………………………… 41 
Table 7.3 Unblinded Process Variables: Case Western Reserve University …………….46-47 
Table 9.1 Anthropometric Common Measures by Research Center ................................ 49 
Table 9.2  Characteristics of questionnaire administration by Field Sites .......................... 52 
Table 9.3  Questionnaire Common Measures by Field Site ………………………………...53-56 
Table 9.4  Source and Response Sets of Questionnaire Common Measures ……………57-62 
Table 9.5  Specifications of the GT3X devices .................................................................. 64 
Table 9.6 Examples of dietary quality indices used in children ........................................ 67 
Table 9.7  Site specific 24 hour dietary recall data collection plans ................................... 69 
Table 9.8.  Case Western Reserve University Site-Specific Mediators, Moderators and 
Secondary Outcomes ………………………………………………………………75-77 
Table 11.1 Expected Distribution of 85th percentile or higher among baseline 
boys and girls ………………………………………………………………………. 89 
Table 11.2 Expectations for Average BMI Results ………………………………………….. 90 

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List of Figures 
Figure 7.1 
IMPACT Conceptual Framework ................................................................. 33 
Figure 11.1.  CWRU-COPTR Anticipated Trajectories ...................................................... 88 
Figure 12.1 Screenshot of the MyHome space ............................................................... 97 
Figure 12.2 Screenshot of a confirmed demographics upload ........................................ 99 
Figure 12.3 Screenshot of a rejected demographics upload ........................................... 100 
Figure 12.4 Screenshot of the accelerometry file upload screen .................................... 101 
Appendices: 
Appendix A:  SystemCHANGE 36 month Teaching Plan 
Appendix B:  HealthyCHANGE 36 month Teaching Plan  
Appendix C:  Tools4CHANGE (control group) Teaching Plan 
Appendix D   Adaptive Intervention Protocol 
Appendix E:  Enriched School Environment  
Appendix F:  Informed Consent Documents 

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1. EXECUTIVE SUMMARY
Executive Summary 
Targeting Obesity and Blood Pressure in Urban Youth 
Case Western Reserve University 
The Case Western Reserve University COPTR project is named IMPACT (Ideas Moving 
Parents and Adolescents to Change Together).  This protocol document  describes the aims, 
study design, interventions, measures, and planned statistical considerations and analyses. 
Eligibility criteria, planned recruitment and retention strategies, and participant safety and 
adverse events monitoring are explained. Data capture, management and transfer 
procedures are delineated. We also have included the results of our formative work that 
consisted of focus groups, community assessments, and a pilot test of the study recruitment, 
intervention and measurement protocols. Lastly, a timeline for the project is displayed. 
The primary aim of this 3-group randomized trial is to compare the effects of three distinct 
behavioral interventions on BMI in overweight/obese middle school, urban youth. Secondary 
aims are to: (1) evaluate the moderating effect of an enriched school environment on the 
impact of the child-family interventions on BMI; (2) compare the effects of the interventions on 
blood pressure in overweight/obese middle school students; and (3) assess the effects of the 
interventions on secondary outcomes related to cardiovascular risk (insulin sensitivity, lipids. 
CRP, fitness, body composition)  and quality of life.  We also will assess the costs and the 
cost-effectiveness of the interventions. Intermediate outcomes of the interventions on 
participants’ diet, physical activity, sedentary behavior, and sleep will be determined and we 
will explore whether the impact of the interventions on relevant outcomes is influenced by 
selected mediating and moderating variables.  
Our target population is Cleveland Metropolitan School District and public charter school 
students (6th-8th grade; n=360) recruited via an established BMI and BP screening program. 
One half of the schools will be “enriched” (participate in an innovative YMCA partnership to 
increase students' physical activity, and have supplemental nutrition education programs, 
social marketing, and navigators). The three study arms consist of: (1) SystemCHANGE 
(SC), a promising new behavioral approach focusing on system redesign of the family 
environment and daily routines (based on ecological and personal process improvement 
theory), (2) HealthyCHANGE (HC), a behavioral approach focusing on building skills and 
increasing intrinsic motivation (based mainly on cognitive behavioral theory), and (3) 
education-only (attention control). The intervention period is 36 months and measures are 
obtained at baseline, 12, 24 and 36 months.  Intent-to treat analyses are planned to assess 
the value of our interventions as compared to education-only control to reduce BMI across a 
three-year study window.  Our hypothesis is that both SC and HC will have greater impact 
than education alone on BMI.  

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2. SPECIFIC AIMS AND OBJECTIVES FOR MAIN TRIAL 
   
Over 25 million U.S. children are overweight or obese1, 2.  Cleveland has one of the highest 
obesity rates in the country (past studies have indicated that 42.8% of Cleveland children are 
overweight or obese).  Cleveland is also the second poorest city in the nation.  The burden of 
poverty and its impact on health is borne disproportionately by the region’s children.  Over 
40% of the city’s children live in poverty3 and, in addition to the high obesity rates, past 
studies have noted that nearly one-third have elevated BP (EBP).   
 
Our study focuses on both the child-family environment and the school-community 
environment in addressing obesity. It involves a 3-arm group randomized controlled trial of 
three behavioral interventions (1) HealthyCHANGE, a behavioral approach focusing on 
building skills and increasing intrinsic motivation (based on cognitive-behavioral theory with 
motivational interviewing components); (2) SystemCHANGE, an innovative behavioral 
approach focusing on system re-design of the family environment and daily routines (based 
on social-ecological and personal process improvement theories); and (3) education-only (an 
attention control group representing usual care referred to as Tools4CHANGE).  All enrolled 
children and their families receive the consistent message of lifestyle change - modifying diet 
in accordance with a Dietary Approaches to Stop Hypertension (DASH)-like model, 
increasing physical activity, and decreasing sedentary behavior; however, the interventions 
differ markedly in approach, theoretical basis, and intensity. 
 
Enriched school-community environments in this study refer to schools that participate in a 
school/community program (We Run This City [WRTC] Youth Marathon Program) that 
encourages physical activity in students by building their capacity to participate (walking or 
running) in a segment of the Cleveland Marathon, supplemented by project-supported fresh 
produce programs, school-wide social marketing campaigns, and trained "navigators" who 
facilitate participation among study participants and provide resource information to students 
and families. Non-enriched school-community environments are schools from the same 
school district that have none of these supplements to regular classroom-based health and 
physical education.   
 
2.1. 
Primary Aims 
 
The primary aim of this protocol is to conduct a 3 year randomized controlled trial that 
compares the effects of 3 distinct behavioral interventions on BMI in overweight/obese urban 
youth.  Specifically, we will randomly assign 360 overweight or obese youth meeting eligibility 
criteria over two years to one of three behavioral interventions:  SystemCHANGE, 
HealthyCHANGE, and education-only (control;Tools4CHANGE). Each intervention is 
described in detail below. 
 

8 
 
In addition, the study will assess the potential additive impact on BMI to be achieved by an 
enriched school-based intervention (We Run This City) in participants assigned to each of the 
three behavioral programs described above.   
 
2.2. 
Secondary Aims 
 
 Assess the effects of the interventions on cardiovascular risk factors (including BP, 
insulin sensitivity, lipids, CRP, body composition, biomarkers, fitness); 
 Define the effects of the interventions on participants’ (a) diet, (b) physical activity, (c) 
sedentary behavior, (d) sleep, and (e) quality of life; 
 Assess the costs and cost-effectiveness of the interventions; 
 Explore whether the impact of the intervention on relevant outcomes is influenced by 
selected (a) socioeconomic and demographic factors, (b) environmental (home, 
school, neighborhood) factors, (c) peer norms, and (d) personal and psychosocial 
characteristics of the child and parent(s)/guardians 
 
3. BACKGROUND AND RATIONALE 
  
Despite the explosion of childhood obesity4, 5, treatments that provide substantial and sus-
tainable benefits for a wide range of populations remain elusive. Many models for primary 
prevention of obesity have been studied, but successful templates for broad implementation 
are lacking6.  Without effective preventions, it is particularly important to identify effective 
methods to treat the vast population of children who are already overweight or obese; without 
effective treatment, most will become obese adults7-9. Several treatment modalities have 
been developed and some show promise in specific populations10-23. However, treatments 
with substantial and/or sustained benefits in general populations are not known9. Further, 
many previous studies have involved non-representative samples, wide age ranges, absence 
of stratification by risk, and short follow-up periods- limiting their generalizability24. The lack of  
clearly effective or feasible methods to treat childhood obesity in general populations is 
particularly important because of the upsurge in associated co-morbidities, many increasing 
cardiovascular risk - including hypertension, insulin resistance, diabetes, lipid abnormalities, 
and sleep-disordered breathing19,25-27.  
 
The striking increase in childhood obesity is therefore of great concern because of the 
expectation that it will result in escalating morbidity and early mortality as these children 
mature28-30. Overweight children are significantly more likely to have coronary heart disease 
when they reach adulthood31. Further, because of today’s childhood obesity rates, by 2035 
there are expected to be more than 100,000 excess deaths from heart disease32. Direct 
medical costs of obesity in the U.S. are $147 billion33 The data underscore the looming 
impact of today’s obesity on tomorrow’s population health and health costs. 
 
Elevated BP (EBP) in overweight children and adolescents is an increasingly recognized epi-

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demic34-37.  Approximately 30% of overweight or obese 10-17yr olds have EBP34, 38, 39.  Many 
overweight/obese youth with EBP already have other cardiovascular risk factors and evi-
dence of end-organ damage34,35,39-42. Children with EBP are likely to become adults with 
EBP, and therefore are at increased risk for cardiovascular and renal disease37, 43-46. These 
data indicate that children with obesity and EBP are at particularly high risk, and require inter-
vention39. Weight loss is a powerful tool to reduce BP in children and adults37, 47.  A diet rich in 
fruits/vegetables, low-fat dairy, low-fat protein (e.g. DASH-like diet) and/or reduced sodium 
intake can also reduce BP, particularly  in African-American adults37, 48-51. Combined with 
calorie reduction, activity, and behavioral interventions, DASH diets facilitate simultaneous 
reduction of BMI and BP in adults52. However, the most effective methods to facilitate adop-
tion of these lifestyle changes in children are not clear, and education alone (usual care) is 
often ineffective50. This knowledge gap is particularly important because of the huge potential 
impact of small changes in BP- at a population level, only a 3 mm Hg reduction in systolic BP 
in adults can reduce mortality from stroke and cardiovascular disease by 8% and 5% respec-
tively37. 
 
 
Racial and socioeconomic disparities in rates of obesity and its co-morbidities (including EBP) 
compound the issues.  Although obesity has risen in all racial/ethnic groups since the early 
1980s, nonwhite children are disproportionately affected53, 54.  The reasons for higher 
prevalence of childhood obesity in non-white populations may involve genetic, cultural, 
socioeconomic, physiological, environmental factors, and interactions among these factors55-
57. In the U.S., low socioeconomic status (SES) is a risk factor58,59. EBP is also more common 
in African-American children who are obese than in other groups60. Racial and socioeconomic 
disparities in prevalence of childhood obesity and EBP are of great concern, as they threaten 
to worsen already existing disparities in cardiovascular disease during adulthood. Based on 
high need and existing data gaps, this proposal targets an urban population (predominantly 
low-income, African–American) of overweight/obese youth, including half with EBP.  
 
In spite of increasing evidence for biological contributors to obesity (including birth size, 
perinatal factors, breast feeding, gut flora, specific genes, and hormone-neural paths 
controlling appetite),61-69 these do not account for the huge rise in childhood obesity and EBP 
since the 1980s.   In contrast, there is strong evidence identifying several behavioral, 
contextual, and environmental factors as critical underpinnings of the obesity surge70-81.  
Family, school, peers, community, and policy act together (superimposed on biological 
predisposition) to provide the environmental contexts that shape children’s energy intake and 
expenditure - and therefore together influence the development of obesity and its co-
morbidities. The evidence that family, school, community, and policy environments are all 
likely contributors supports viewing childhood obesity from the perspective of a socio-
ecological model 79, 82-84.  In this model, the child resides within several environmental 
systems: interpersonal (e.g. family, peers, culture), organizational (e.g. schools, churches), 
community (e.g., community organizations, neighborhood), and public policy28, 82.  This model 
is rooted in the evidence that a single cause of the childhood obesity epidemic is unlikely, and 

10 
 
that processes leading to the surge of obesity probably involve combinations of factors at 
multiple environmental levels85.  Accordingly, to gain traction in treating obesity, it is important 
to target more than one level of environmental influence.  Further, it has been suggested that 
“small changes in one or more key factors may have large effects” overall85.  This multilevel 
approach may be particularly suitable for addressing obesity and EBP, as recommended  
interventions for both include reduced intake, increased activity, and reduce sedentary beha-
vior19, 39, 70. The multi-level approach has been effective in combating smoking and HIV, and 
encouraging physical activity, underscoring its potential86-89. 
 
Two critical levels for interventions aiming to reduce obesity and EBP in youth are the child-
family environment (i.e. interpersonal level) and the child-school-community environment (i.e. 
organizational and community levels).  Multiple factors within the child-family environment 
influence children’s eating and exercise habits, and therefore may affect adoption of 
behaviors increasing or reducing obesity.  These include (a) the child’s personal 
characteristics (ethnicity, degree of overweight/obesity, sleep duration, presence/absence of 
co-morbidities, self-esteem, self-efficacy, motivation, depressive symptoms, stress, social 
problems, eating symptoms); (b) the parents’ personal characteristics (e.g., BMI/BP status, 
psychosocial functioning, parenting stress, health beliefs and practices); and (c) family 
characteristics (e.g. socioeconomic factors, mealtime routines and problem-solving skills)23, 90-
101.The overall importance of the family is underscored by evidence that the success of child 
obesity intervention programs is directly related to parent involvement102-104.    
 
Factors in the child’s school-community environment (e.g., access to healthy and unhealthy 
foods104b,104c, neighborhood safety and walkability81, venues for physical activity and social 
networks104b), together with family and peers, shape beliefs, norms and expectations about 
nutrition, activity, and body habits.  Research indicates the potential for school environments 
to modify obesogenic behavior 105-107, although interventions at additional levels are likely 
needed to maximize potency and longevity of effect.   
 
Interventions effectively targeting both the child-family environment and the child’s school-
community environment are therefore likely to be more powerful in reducing obesity and EBP 
than interventions addressing either alone.  This may be particularly true for young 
adolescent108-110. If the fundamental message (e.g., reduce energy intake, increase physical 
activity, reduce sedentary behavior) is consistent across these two key environments, and if 
both provide opportunities to operationalize the message, there is likely to be greater impact. 
Yet, most previous interventions have been unimodal.  In this study, we will directly address 
the need for multilevel approaches to childhood obesity, by targeting both child-family and 
school-community interventions. 
 
4. FORMATIVE RESEARCH-- PHASE 1 
 
 
4.1. Aims, Objectives, Interventions, Measurements 

11 
 
 
4.1.1.  Aims and Objectives 
 
As described in our original proposal, we have conducted or will conduct a total of four 
projects during the formative phase of the study.  We: 
 
1. conducted focus groups with children and parents to engage them as co-designers of 
the intervention and assessment protocols; 
2. solidified our partnerships with the community to optimize parent interest and support 
and ensure smooth and successful integration of our study with existing programs, 
including the We Run This City Youth Marathon Program (part of our school-based 
intervention) and the BMI Screening Program partnership between the CWRU School 
of Nursing and the Cleveland Metropolitan School District (CMSD).  
3. are collecting available school and neighborhood level environmental data for use in 
the main trial’s analyses; and,    
4. are conducting a one-year pilot study to assess feasibility and acceptability of the 
recruitment, intervention, and data collection protocols, as well as the impact of the 
interventions on the main trial’s physiological and psychosocial outcomes.   
 
Aim of Focus Groups:  One of our interventions (SystemCHANGE) had been found to be 
successful with adults, but not yet adapted to be used with adolescents, and had primarily 
focused on exercise.  Thus, after the initial adaptation of the intervention by the study team, 
we conducted a series of focus groups of parents and children, using a participatory design 
approach. Our goals were to: 1) identify the children's and parents' suggestions for making 
the intervention components culturally-appropriate for African Americans and Hispanics; 2) 
obtain reactions to and suggestions for refining the intervention materials and methods to 
ensure that they are engaging; and 3) determine age- and gender-appropriate refinements 
needed.  We also solicited feedback on adaptations needed for the intervention's application 
across different families or contexts (e.g. attitudes regarding diet and exercise, barriers to 
healthy living and approaches that could be useful, socio-cultural influences such as family 
resources, home/work/school structures and schedules, etc). At the completion of these focus 
groups, we created an adaptive intervention that is now being tested in the pilot study. 
 
Aim of Community Engagement:  The aims of this component of the formative phase were to 
(a) establish a Community Advisory Board specific to the project, to conduct informational 
meetings with community partners, school officials, parents, and parents groups to assess 
community interest and perceived barriers to study recruitment and retention; (b) to solidify 
plans with our partners at the YMCA of Greater Cleveland and the Cleveland Metropolitan 
School District, who conduct the school fitness program, We Run This City, that we are 
integrating into the design of our study; and to work out the procedures for connecting the 
study to the BMI screening program that is conducted by the School of Nursing, which 
provides the study with its eligible population. 

12 
 
 
Aim of the Environmental (School, Community) Measures Scan:   The aim of this component 
was to determine the feasibility of collecting and or accessing secondary sources of school 
and community level data that can be linked to each child in the study and to develop 
algorithms for creating child-specific environmental profiles based on the child’s 
neighborhood socioeconomic status (e.g., based on income, female-headed households, 
education levels); school and neighborhood food environment (e.g., fast food to 
grocery/market ratio; classroom snacking policy, average fruits & veggie consumption and 
physical activity levels of school peers); safety (based on crime data and perceptions); and 
the built environment impacting physical activity (park, rec centers, green space).  As part of 
this effort, we also sought to determine the feasibility of expanding the currently administered 
Youth Risk Behavior Survey to all CMSD schools so that school-specific norms on diet and 
physical activity opportunities and patterns could be accessed for use in the study. 
 
Aims Specific to the Pilot Study: Because this was formative work, our major goal was to 
assess the feasibility and acceptability of the study protocols. We viewed the pilot study as an 
opportunity to learn more about the usefulness of our recruitment, enrollment, intervention, 
clinical and psychosocial measurement plans, data collection and management systems, and 
retention strategies. Importantly, we also wanted to assess subject engagement and 
satisfaction with our protocols. Process information is being carefully monitored throughout 
the pilot study and reflections on these data are conducted often by the study team to 
determine if adjustments are and will be needed (in the main trial). Our goal has been to learn 
as much as we can in order to make adjustments to the larger trial protocol to enhance its 
effectiveness, as well as assessing the role of the same moderators and impact of the 
interventions on the same set of mediators and physiological and psychosocial outcomes of 
the main trial.   
 
4.1.2. Interventions and Measurement of the Pilot 
 
As with the main trial, the population for the pilot were drawn from a list provided to the study 
team from the Cleveland Metropolitan School District (CMSD) of children who met our study 
criteria of being > 85th percentile on BMI and did not opt out of being contacted by the study.   
Letters and information on the study were mailed to parents, followed by phone calls by the 
study team. Among those who were interested, baseline intake assessments were scheduled  
 
Baseline and Follow-up Assessments. Intake visits took place at the clinical research unit 
(CRU) at University Hospitals Rainbow Babies and Children’s Hospital.  Prior to any 
procedures, the study was fully explained using a standardized presentation designed for 
grade 5th literacy level and assent/consent obtained for participation in the study.  After 
consent, baseline measures were taken, as described in later sections of this report. The 
child and parent are given lunch, during which time the accelerometer was given for 1 week 
wear, its use explained, and arrangements made for its pick-up, and the visit completed.  

13 
 
After the baseline visit was complete, randomization to one of the three study groups 
(SystemCHANGE, HealthyCHANGE, Control) took place.  Data collectors were kept blind to 
study assignment throughout the study. 
 
Procedures of the Pilot RCT.   Those assigned to HealthyCHANGE or SystemCHANGE 
began their group meetings within 4 weeks of assignment.  For those assigned to the usual 
care group, a dietitian met the family at a convenient location to provide the education 
intervention within 4 weeks of assignment. The behavioral intervention arms 
(HealthyCHANGE and SystemCHANGE) received 16 face-to-face group education sessions 
at 2-week intervals over an 8-month period, followed by rotating monthly face-to-face 
meetings or phone calls for a further 4 months. The control group received a one-hour dietary 
counseling session with a registered dietitian at initiation of the study and then received (or 
will receive) three additional contacts with study personnel approximately quarterly 
throughout the study year (this is in addition to the  clinical assessment received by all study 
subjects). Two of the contacts are phone calls during which there is a general discussion 
reminding them of their participation in the study and checking on accuracy of home address 
and school attended. The third contact is a social gathering event (i.e., picnic, ball game) of 
small groups of families in the control group.  Each intervention group included 10 children, 
each with at least one family member.  Throughout the pilot study, we also monitor and 
systematically collect data associated with the fidelity of the intervention protocols.  
 
Intervention Protocols.   The pilot compares three intervention arms targeting the child-family 
environment: (1) SystemCHANGE (ecological and personal process improvement), (2) 
HealthyCHANGE (cognitive behavioral skill building), and (3) Tools4CHANGE (education 
only attention control group) - in achieving reduction in BMI.    Each session consists of 45 
minutes of behavior change content/activities consistent with the conceptual framework of the 
respective interventions and 45 minutes of either physical activity or diet information/activities 
(similar for both behavioral interventions). The child is weighed on a scale privately at each 
session as a method of providing feedback to participants on their progress.  Each session is 
led by two interventionists trained in the respective intervention protocol. Parents and children 
are often separated to receive different content/activities during the sessions. 
Materials/activities addressing developmentally- and culturally-appropriate diet and physical 
activity and techniques for optimal management for older children and adolescents are 
provided.  The sessions are designed to be very interactive and include cooking classes, 
guest chefs, and creation of photo or video presentations on healthy living by the children. A 
series of class attendance incentives is provided, including a “points reward system” for gifts. 
The 8 months of intensive face-to-face meetings is followed by 4 months of booster sessions 
(alternating telephone and face-to-face meetings at monthly intervals) reinforcing concepts 
presented in the earlier sessions. 
 
 
 

14 
 
4.2. Results from Phase 1  
 
4.2.1  Focus Groups   
 
Sixteen focus groups were conducted during February – April, 2011 (IRB #11-10-22). The 
purpose of the focus groups was to engage the children and their parents/guardians as co-
designers of the study protocols.  Students in the 6th, 7th and 8th grades from Cleveland 
Metropolitan School District who had a BMI in the 85th percentile or higher and their 
parents/guardians were recruited, drawn from a list of participants in the We Run This City 
Youth Marathon Program.  Participants were invited to attend two different focus group 
sessions that were held one month apart. Children and their parents/guardians provided 
written informed assent/consent and completed demographic data during their first group 
session. Data were then collected in the form of information provided in round table 
discussions in response to open-ended questions, a structured interview guide, and graffiti 
art. Participants’ reactions to and suggestions for improving study recruitment and retention 
approaches, data collection procedures, and intervention format and materials were sought.  
All leaders were trained; the majority of the sessions were led by persons of the same race as 
the participants. Data were collected using digital recordings and observer notes. A total of 16 
focus group sessions were conducted: 8 each of children and parents/guardians. The 
children’s focus groups were gender-specific. Each focus group session lasted approximately 
2 hours and consisted of 8-15 participants.  Adults received a $50 money order and children 
received a $25 money order for their participation in each session. Data were transcribed and 
analyzed using qualitative approaches.   
 
The sample consisted of 45 children and 44 adults. The children had a mean age of 12.6 
years (range = 11-15).  51% of the children were male; 49% were female.   The children were 
evenly distributed among the 6th, 7th and 8th grades.   24% identified themselves as 
Hispanic/Latino, 64% as African-American or Black, 16% as White and 7% as mixed race.  
49% of the children reported that neither parent was married.  The adults had a mean age of 
43 years (range = 29-85).  84% were female; 9% were male, 7% declined to identify their 
gender.  15% of the adult participants identified themselves as Hispanic/Latino, 2% were 
American Indian/Alaskan Native, 64% were African-American or Black, 18% were white, and 
14% identified themselves as other.   
 
Results indicate that parents and students (1) are interested in behavioral interventions such 
as those planned, (2) strongly believe that the emphasis should be on health and wellness, 
rather than specifically on obesity, (3) would like the method of recruitment to involve letters 
(with opt-out option for those wishing not to be contacted further) followed by telephone calls, 
(4) agreed that mixed male and female intervention groups are acceptable, and (5) want the 
intervention sessions to be held in convenient community venues. Parents and children had 
some hesitation about the 3-year commitment of the intervention component of the main 
study and provided ideas about how to make the interventions enjoyable, useful, and 

15 
 
engaging over the course of the study.  Boys and girls differed in their perceptions regarding 
healthy living. The majority of the girls expressed that they felt healthiest when they were 
younger because they were thinner.  Boys expressed that they felt healthiest when they were 
involved in organized sports. The girls described that they wanted to lose weight, whereas the 
boys placed a strong emphasis on both muscle and bone strength. Girls stated that they were 
motivated when they were on a team, training for an event, or had someone to be active with. 
More than half of the boys said that they were motivated by role models, performance goals 
and personal outlets. 
 
4.2.2.  Community Engagement    
 
We undertook a number of different efforts to solidify our partnerships with the community to 
optimize parent interest and support and ensure smooth and to successfully integrate our 
study with existing programs, including the We Run This City Youth Marathon Program (part 
of our school-based intervention) and the BMI Screening Program partnership between the 
CWRU School of Nursing and the Cleveland Metropolitan School District (CMSD).  
 
During the first six months of the project, we established a Community Advisory Board (CAB), 
which is comprised of (1) school and public health officials; (2) parent leaders (school-based); 
(3) parents/guardians of participant-aged children; (4) neighborhood leaders and other 
community stakeholders, as well as representative from both the YMCA of Greater Cleveland 
and the Cleveland Metropolitan School District, who serve our primary institutional partners.  
We have sought their opinions on methods of recruitment and engagement of families, 
advertising, screening procedures, retention strategies, intervention and data collection 
locations, perceived protocol burden, the importance or not of gender-specific intervention 
groups, and barriers to the above due to beliefs or perceptions. 
 
With regard to the school-based, We Run The City (WRTC) Youth Marathon Program, we 
have finalized the role of the Navigator and how they will support and supplement the WRTC 
program in such a way to provide a natural support for IMPACT study participants to engage 
and stay involved with the WRTC program.  Navigators will provide focused and interactive 
activities (on nutrition, physical activity, stress and sleep) at both the school and team level, 
attend training sessions at least once a week and participate with their assigned teams on 
race day. 
 
In order to better understand how to retain study participants in the WRTC, we also examined 
program retention among overweight and normal weight children in last year’s (2011) 
program, and conducted a series of interviews with Marathon coaches and previous WRTC 
participants (CWRU IRB- addendum to WRTC protocol #20100518, approved 21 August, 
2011) to assess the factors that were associated with low attendance, program dropout and 
retention among overweight participants.   
 

16 
 
In 2011, 35% of all WRTC participants were overweight (85-94th percentile) or obese (>95th 
percentile), and overall, approximately 70% of WRTC participants (normal, overweight or 
obese) completed the training and participated on race day (note: the primary reason for 
program dropout is poor grades or disciplinary reasons). When comparing participation rates 
by weight status, the obese participants completed fewer training sessions and were slightly 
less likely to participate on race day than either overweight or normal weight (<85th percentile) 
children; however, there were no differences in training levels or program retention between 
overweight and normal weight participants.  This leads us to believe that we will need to add 
additional encouragement to the obese IMPACT students who participate in the WRTC 
program; however, with encouragement the program should retain most of the IMPACT 
students.  
 
As part of the pilot phase of the IMPACT study, we selected and interviewed 22 children from 
6 different schools who participated in the 2011 WRTC program, chosen based on their 
weight status (60% were overweight (85th -94th %tile) and 40% obese (>95th %tile)) and the 
level of sustained involvement in the program (half completing more than 10 training sessions 
or completing more than 20 miles during the 16-week training period, and half of whom did 
not).  We sought to better understand the factors the contributed to drop out, as well as 
retention among overweight and obese participants.  
 
Surprisingly, little distinguished the overweight/obese child who completed versus did not 
complete the program.  Regardless of whether or not they completed the program, the 
majority of overweight and obese participants said they joined the program to “get fit and 
healthy”.  Encouragement from coaches and friends in the program was also an important 
part of the program and 85% of the students interviewed reported they had several friends on 
the team.  Where completers and non-completers differed was in their perceptions of 
exercise. For example, 62% of overweight participants enjoyed running while only 33% of 
obese participants responded with a similar response.  Overall, students enjoy WRTC, like 
their coach, have fun with friends, and participate in an active program that encourages a 
healthier lifestyle. 
 
Other Activities:   Our partners and their commitment to the IMPACT study are highlighted in 
a video (http://www.youtube.com/watch?v=4FKy6pKeaAY) that was produced by the 
Cleveland CTSC (Clinical and Translational Science Collaborative) to be shown to Dr. 
Francis Collins, Director of the NIH as part of a recent visit to Cleveland.  The video has 
turned out to be an invaluable tool for sharing (and selling) the project to the local community. 
 
Lastly, due to economic issues and a broadening scope of educational options through a 
school-voucher program, the number of children enrolled in the Cleveland Metropolitan 
School District (CMSD) has dropped significantly in the past five years. In order to ensure that 
we will have an adequate pool of possible students to draw from, we will need to expand the 
population of students that are screened for BMI, particularly from the growing number of 

17 
 
charter schools in the city.  To this end, the CWRU Prevention Research Center for Healthy 
Neighborhoods (Borawski, PI), will conduct a BMI and BP screening program in interested 
charter schools, using the same screening protocol developed by the School of Nursing for 
their program with the CMSD.  This will add an additional 450 children to the population of 
eligible students.  
 
4.2.3. Assessment of School and Community Environmental Data 
 
During this formative phase, we have identified four tools to be used to collect school and 
community environmental data.  These tools are briefly discussed below. 
 
The School Food and Beverage Audit Tool is a modified version of the food and beverage 
marketing and advertising too used by Samuels and Associates, commissioned by The 
California Endowment and the Public Health Institute111.  The SFBA Tools will be used to 
assess the availability of food and beverage and healthy or un-healthy marketing on school 
grounds.  The tool will also assess discrepancies in the school menus and what is actually 
served in the cafeterias, locations and availability of vending machines, the quality and 
availability of school dining facilities, and school stores when applicable.  This training 
protocol is being finalized and data will be collected in May 2012. 
The Neighborhood Food Environment Database (NFED) will be developed in conjunction with 
the Prevention Research Center for Healthy Neighborhoods (Borawski, PI) to allow us to 
create student-centric scores for analysis.  We have begun with the identification of locations 
in the City of Cleveland that sell food using the Cleveland food vendor inspection database112 
as well as other sources when appropriate. We expect that we may need to add to this 
database as explained in more detail below. 
Using Arc-GIS113, a geographical information system software package, we will calculate a 
0.25 and 0.75 mile Euclidean buffer around a participant’s home and school in order to 
conceptualize the immediate surroundings (0.25 mile) and neighborhood food retail 
environments (0.75 mile buffer) respectively.  The number of food retail establishments that 
fall within these buffers will be enumerated and used to calculate densities of facilities within a 
given neighborhood. 
During this formative period, we have worked with local government to acquire the food 
vendor inspection database for the city of Cleveland, which included all vendors inspected in 
2010.  To establish the completeness of this dataset, we created a GIS map layer using the 
database, then added the CMSD schools as an additional layer.  Using Arc-GIS, a mapping 
software package, we were able to draw a 0.25 mile Euclidean buffer around each school to 
identify the food retail locations.  Following creation of these buffer zones and corresponding 
listings of food retail locations, study staff set out to “ground-truth” the actual food retail 
environment.  Armed with maps and location addresses for several schools, staff established 
that identified vendors were still in operation and also noted other vendors that were not 

18 
 
listed.  In reviewing these schools, it was found that we did not have 100% agreement for any 
of the six schools, and we would need to ground-truth food retail locations. 
Given the vast undertaking of ground-truthing all food-retail within the city of Cleveland, we 
have prioritized such that we will ground-truth all food retail locations within 0.75 mile 
Euclidean buffer around each school and each participant’s home address.  Food retail 
locations that are identified via ground-truthing will be added to the database, allowing us to 
create child-centric scores related to food retail environment around the home and the school. 
We will also be drawing objective social environment data from the Northeast Ohio 
Community and Neighborhood Data for Organizing (NEO-CANDO), a free and publicly 
accessible social and economic data system developed by the Center on Urban Poverty and 
Community Development, housed at Case Western Reserve University.  NEO-CANDO will 
provide data on indicators including poverty, education, employment, public assistance, and 
crime at the census-tract level.  This will allow for social and economic indices to be created 
for each participant based on where they live.  We have already begun to download the 
relevant indicators from NEO-CANDO for all census tracts in the city of Cleveland, and we 
are currently waiting for all data from the 2010 US Census to be uploaded to NEO-CANDO 
(should be completed within the next several months). 
Finally, the Youth Risk Behavior Survey will be utilized to capture school-specific normative 
data on physical activity, nutrition, and student perception of school policies in these areas. 
We have confirmed that the PRCHN will administer the survey in all K-8 schools within the 
Cleveland Metropolitan School District and all charter schools who participate in the 
screening program, every other year (beginning in spring 2012).  This was expanded from 
their prior methodology of a random sampling of schools.  The full district approach will allow 
us access to school-specific normative data on all children in the study, even if they move 
from their original school.       
 
4.2.4. Results from the Pilot Study 
 
We are conducting a one year pilot study to assess feasibility and acceptability of the 
recruitment, (family) interventions, and data collection protocols. Outcome measures are 
obtained at baseline, 4 mo, and 8 mo, with a meeting at 1 year to assess overall retention.  
Here are the highlights of the pilot: 
 
 We recruited 25 overweight/obese children in the target range and 25 parents (1/child).  
The children were 56% female; most (88%) were African-American, with 4% each 
American-Indian, Caucasian, and Hispanic. Of parents, 88% receive food stamps or 
SNAP, and 80% reported annual household incomes under $35,000 (with 56% under 
$25,000).  

19 
 
 They were randomly assigned to the two behavioral interventions, HealthyCHANGE 
(n=10) or SystemCHANGE (n=10), or to education-only control (Tools4CHANGE; 
n=5); 
 Intake visits (including assent/consent and baseline measures went very smoothly; 
 We designed a responsive intervention approach;  
 Intervention groups have been doing well to date (6 months into the pilot study) with 
good attendance and engagement; 
 Data are collected using electronic data capture and management using REDCap, 
audio-supported, computerized (iPad) surveys for parents and children.  Data collected 
were clean and complete;  
 There was 96% retention for the 4-month follow-up visits. 
 
4.2.5.  Lessons learned from the pilot 
 
Ties to the School Year:  Because our subject pool is obtained from the Cleveland schools, 
we have found that it is critical for us to conduct the screening for the main trial during the 
school year from January through April in each of the next two years. In turn, this allows us 
sufficient time to conduct baseline measures on the children during the spring and summer 
period each year and to begin the intervention (administered via 5 cohorts of 45 
children/parents each) prior to fall.  
 
Recruitment Strategies:   We believe that a major strength of our study is our ability to recruit 
directly from the Cleveland Metropolitan School District (CMSD) through a successful 
screening program administered by faculty and students from the CWRU School of Nursing.  
The data are turned back to CMSD, who then provide us with the list of eligible students 
whose parents have not opted out of further contact and their contact information.   The pilot 
study allowed us to test the effectiveness of this screening program as our primary approach 
for identifying eligible participants (i.e., ≥85th percentile).   The screening and eligibility 
process went very well.  However, it was disconcerting (while not completely surprising) to 
find that the information on nearly half of the eligible students was no longer valid when we 
reached out to them.  Saying that, we were extremely pleased to find that of those who we 
were able to contact, about a third came for the baseline assessment and consented to enroll 
in the intervention phase of the project.  Thus, for the main trial we have made changes to our 
protocol to address the issue of updated information to not only ensure adequate numbers for 
recruitment but to ensure that more Cleveland families have the opportunity to participate.  
Subsequently, we have met with the school district and they will allow us to obtain updated 
information directly from the students during the screening process, which will significantly 
increase our recruitment pool and provide us with an adequate pool from which to draw our 
180 subjects each year.   
 
Measurement Protocols.  Our intake and follow-up measurement protocols have been shown 
to work well. Although the pilot evaluation visits went very well without complaints by 

20 
 
participants and with full completion of data collection, we have reduced our intake protocol 
from 3.5 hrs to 2.5 hrs to further reduce subject burden.  We learned that some of the children 
who had screened at or above the 85th BMI threshold for participation in the study, fell below 
this threshold at the actual intake baseline visit (some kids grew a lot during this 3-4 month 
period), and thus clarified our protocol regarding how to manage this. We have decided that 
they must meet the study eligibility criteria of having a BMI of > 85th at the time of the baseline 
measure.  We will thank families who no longer are eligible and pay them the visit incentive. 
Intervention Design and Delivery.  We learned from the focus groups of parents and children 
about the importance of making such a long intervention (3 years as required for all COPTR 
projects) fully engaging, fun, informative and feasible. Thus, we have designed the 
intervention group sessions to be very interactive and include learning games, guest chefs, 
group outings (e.g., wall rock climbing, sports events), PhotoVoice, and the creation of 
healthy living commercials. In our pilot study, these activities have been well received and 
create a lot of participant enthusiasm for the project and each others’ success.  Although we 
learned in the focus groups that we did not need to have gender-specific intervention 
sessions, we have learned in the pilot study that both parents and children prefer to be 
separated for much of the intervention session time (children are much more active in 
participation when parents are not present to hear their responses  - and the parents have 
acknowledged this as well). We have now redesigned the sessions for “breakout time” where 
parents and children separate following some common time together at the beginning and 
end of the sessions.  This change has necessitated the need for a third interventionist in 
some of the group sessions.  We also have learned the need for ongoing incentives for 
engagement in the intervention meetings and thus we incorporate many “grab bag incentives” 
and opportunities to participate in drawings for larger prizes for attendance.  Lastly, based on 
recent literature114  and our pilot experiences, we have built maximum flexibility into the 
sequencing of our educational material and have added more individual counseling so that if 
participants miss intervention sessions they are not disillusioned and think that they are “too 
far behind to catch up.”  We have found this flexibility to be more acceptable to participants 
and important in keeping them engaged over the long intervention and study follow-up period.  
 
Data Collection:   For the pilot, we developed a fully integrated, electronic data capture 
system, using audio-supported iPads and the REDCap system.  We were pleased to find that 
the system worked extremely well.  Both adolescents and parents acclimated very quickly to 
using the IiPads, and the integration of the clinical, dietary, accelerometer and survey data 
into one system (REDCap) has greatly reduced the post-data collection cleaning and 
management, which will in turn expedite the return of the data to the RCU.  Due to the ability 
to set ranges, skip patterns, and required responses (including refusal), the data are clean 
and complete, with very little missing data.   
 
 
 
 

21 
 
4.3. Key Recommendations for Phase 2 
 
 Need to screen and recruit for main trial beginning in January of each of the next 2 
years in order to start the last of 4-5 intervention groups by fall  of each year to assure 
adequate intervention exposure to school-level intervention 
 Need to recruit at urban schools other than Cleveland Metropolitan School District, 
such as Charter Schools.  This is also important because of a shift within Cleveland, 
as children are increasingly enrolled in charter schools 
 Need for a protocol for managing child change in eligibility criteria for children losing 
eligibility between screening and intake assessment (BMI drops below 85th %) 
 Plan to get updated phone numbers of students at the time of school screening (closer 
to enrollment in study to reduce number of wrong phone numbers) 
 Remain attentive to intervention design and subject incentives for maintaining subject 
participation in interventions.  
 Initiate re-invigoration protocol and responsive intervention protocol for 
individuals/families who have missed several intervention sessions.   
 
5.  MAIN TRIAL STUDY POPULATION AND ELIGIBILITY 
 
Potential participants will be drawn from a list provided to the study team from the Cleveland 
Metropolitan School District (CMSD) and participating public Charter Schools of rising 6th 
graders (going into the 6th grade in the fall) meeting the study criteria of a BMI >85th percentile 
whose parents do not opt out of being contacted by the study team. These constitute the pool 
from which the participants in this study will be sought, as described.   Based on prior 
preliminary work, we expect approximately 40% of children to be identified as potentially 
eligible. Based on the demographics of the CMSD and Charter Schools, we expect the 
population for this study to include approximately 70% African-Americans, 15% white, 11% 
Hispanic, 3% other, and be predominantly low income. 
 
Specifically, the CMSD schools are part of a cooperative agreement between CMSD and the 
Case Western Reserve University School of Nursing in which the School of Nursing provides 
annual standard school screenings of BMI and BP in the CMSD schools as a service.  The 
CWRU Prevention Research Center for Healthy Neighborhoods (PI E Borawski) has recently 
established a similar service for charter schools within the city of Cleveland.  CMSD and the 
participating charter schools send the screening results to the parents in a packet; for children 
with BMI > 85th percentile (i.e. CDC definition of overweight or obese70), the letter also indi-
cates that the child may be eligible to participate in a program focusing on health that is led 
by Case Western Reserve University.  The letter explains that the Case project team will 
contact the family to explain more about the project unless the family chooses to opt out of 
being contacted further about the study (by telephoning or e-mailing).  Following this, CMSD 
and participating Charter Schools will send the IMPACT team a list of eligible students whose 
parents did not opt out of being contacted.  The IMPACT team then sends a letter and a bro-

22 
 
chure to families whose children are potentially eligible and who have not opted out; the letter 
explains that an IMPACT team member will be contacting the family by phone in approxi-
mately 1 week to see if they are interested in learning more about the project and potential 
participation.  An IMPACT team member will then call the family and offer more information 
about the study by phone or, if the family prefers, in person through meeting at a convenient 
place at the families’ discretion to provide any further information the family wishes and to 
further pre-screen for eligibility (see below; this has worked well in the pilot study).    
 
5.1.  Eligibility Criteria    
 
The Main Study inclusion/exclusion criteria are listed below, and will be ascertained through 
the recruitment process which begins after CMSD and Charter Schools provide contact 
information for families (of potentially eligible children) who have chosen not to opt out from 
further contact regarding the project.   To be eligible for the study, a child must be a rising 6th 
grade CMSD  or Charter School student who is found at  school screenings to be overweight 
or obese (BMI 85th- 94th percentile or ≥ 95th percentile for age/sex respectively70) and 
whose parent(s) did not opt out. 
 
5.2   Exclusions 
 
 
The exclusion criteria for entering the trial include:   
 taking medications that alter appetite or weight (e.g. glucocorticoids, metformin, 
insulin, Risperidone (Risperdal), Olanzapine (Zyprexa), Clozapine (Clozaril), 
Quetiapine (Seroquel), Ziprasidone (Geodon), Carbamazepine (Tegretol), Valproic 
acid (Depakote/Depakene/Depacon), Aripiprazole (Abilify), Orlistat (Xenical), 
Sibutramine (Meridia), Phentermine, Diethylproprion (Tenuate), Topirimate (Topamax), 
glitazones; 
 stage 2 hypertension or stage 1 hypertension with end organ damage (left ventricular 
hypertrophy, microalbuminuria) as these conditions would best be treated by 
medication rather than lifestyle interventions39; 
 Sickle Cell Disease (makes measurement of HbA1C inaccurate); 
 severe behavioral problems that preclude group participation (as reported by 
parent/guardian); 
 child involvement in another weight management program; 
 family expectation to move from the region within 1 year, or 
 the presence of a known medical condition that itself causes obesity (e.g.,Prader-Willi 
syndrome).     
 
ADHD medications will not be an exclusion criterion because of their widespread use in this 
population, but their use will be measured. Additionally, known co-morbidities such as 
hyperlipidemia, asthma, sleep apnea are not themselves reasons for exclusion as they 
represent co-morbidities commonly found in overweight/obese youth, and to exclude them 

23 
 
could make the population non-representative. However, their presence/absence will be 
considered a covariate and such children will be eligible for the program unless physical 
activity is precluded by their physician. Similarly, if during the course of the study, a child who 
was eligible on study entry develops a condition that would have been exclusionary at entry 
(eg begins a medication such as glucocorticoids), that child will not be excluded from the 
protocol but his/her new condition will be noted as a covariate. 
 
If a family has more than one eligible child, the one with the birthday closest to a set date will 
be included for data collection (although others can take part in the intervention sessions). 
Disabilities (e.g. blindness, hearing loss) will be accommodated using the services of the 
FIND Lab (Full INclusion of persons with Disabilities in research), directed by MPI Moore.              
 
Parents/guardians.   The study participants will also include one index parent/guardian for 
each child participant. If more than one parent/guardian is available, we will ask the 
parent/guardian signatory (index study parent) to be the one likely to be most available to 
bring the child to visits. Data will be collected  from this index parent/guardian. However, all 
parents/guardians may participate in the project, as they may attend Intervention meetings.  If 
the index parent/guardian becomes unavailable during the course of the study (e.g. dies, 
moves without the child), the family will be asked to identify another index parent/guardian 
who would participate after signing consent.    For the index parent/guardian, inclusion criteria 
are being the parent or guardian of an eligible child and being able to attend data collection 
sessions. Parents are strongly encouraged to participate in the intervention visits but it is not 
mandatory they participate.  The intervention team will have guidelines regarding reaching 
out to families who are not attending the intervention visits.   
  
5.3  Inclusion Statement 
 
The study population consists of children who are rising 6th graders in the spring of 2012 
(Cohort 1) or 2013 (Cohort 2) who were identified through the school-based screening as 
having BMI >85th percentile, whose parents did not opt out of being contacted, who did not 
meet any of the exclusion criteria, whose parents provided consent and they provided assent 
to participate, and who have been randomized into the study. 
 
6.  RECRUITMENT AND RETENTION 
  
6.1.  Recruitment Tracking 
 
Recruitment begins after CMSD and the public Charter Schools provide the project team with 
the parent/guardian names and contact information of all rising 6th graders who (1) 
participated in the school BMI and blood pressure screening and who are potentially eligible 
for this project (i.e. BMI > 85th percentile) and (2) parents did not opt out of being contacted.   
 

24 
 
The research team will send a letter to the homes of parents/guardians on the list provided by 
CMSD and participating Charter schools that briefly describes the study and states that they 
soon will be contacted by phone to learn more about the project. This letter will also include a 
brochure introducing the study.  Within 2 weeks after the letter is sent to homes, trained 
research team members will contact the parent/ guardian of the potentially eligible children by 
phone to provide a basic description of the project and ask if the family is interested in 
learning more about the study.  Study personnel will offer to present the information about the 
study to the parent/guardian in several ways: 1) further discussion over the phone at this 
time, 2) arrange to meet the parent/guardian at a convenient time and place, 3) send 
information through mail if family has not received.  If a parent/guardian wishes to receive 
more time to consider participation, follow-up contact by phone or in-person will be done. If a 
parent/guardian expresses immediate interest in participation whether by phone or in-person, 
the “Pre-screening Information Sheet” will be read to them and the pre-screening questions 
asked to the parent/guardian. 
 
People may also find out about the study from community and school meetings where the 
study is being discussed.  These people can call the project office to find out if they are 
eligible, and the information provision system detailed above will be offered.  
 
Because it is necessary for the research team to collect pre-screening information to deter-
mine full eligibility into the study, a “Pre-screen Information Sheet” has been developed.  This 
“Pre-screen Information Sheet” will inform parents/guardians about the study, and what in-
formation will be collected related to their child’s medical information at the time of recruit-
ment (past medical history, illnesses, medications; see inclusion/exclusion criteria).  The Pre-
screen Information Sheet” will also include study contact team names and phone numbers so 
the parent/guardian can contact study team at any time with questions.  The parent/guardian 
will be asked questions (pre-screening script attached) related to the presence/absence of 
the exclusionary criteria for study eligibility and to confirm family contact information (ad-
dresses, phone numbers, email addresses).  Study consent and baseline intake visits with 
interested families will be scheduled for a later date in the Clinical Research Unit.  
 
Recruitment tracking will also include standardized forms developed by COPTR (see Re-
cruitment and Retention Tracking Protocol).  In these forms, we will define number screened 
as the number who were found to be overweight or obese on school screenings, did not opt 
out of further contact by the research team, and were screened for inclusion/exclusion crite-
ria.  We define he number eligible as the number eligible for recruitment after screening.  We 
define the number consented as the number who consented/assented to participation in the 
study conditional on their completion of measures required for randomization.  We define the 
number randomized to be those who, following consent, met eligibility for randomization (ie 
collection of required baseline measures) and were randomized.  
 
 

25 
 
6.2.  Recruitment of Minorities 
 
Racial and socioeconomic disparities in prevalence of childhood obesity are of great concern, 
as they threaten to worsen already existing disparities in cardiovascular disease during 
adulthood. Based on high need and existing data gaps, our study targets an urban population 
(predominantly low-income, African–American) of overweight/obese youth, many with 
elevated blood pressure.  Our recruitment targets children living in the city of Cleveland, the 
second poorest city in the country after Detroit.  Based on the demographics of the CMSD 
and Charter Schools, we expect the population for this study to include approximately 70% 
African-Americans, 15% white, 11% Hispanic, 3% other, and be predominantly low income.  
The District reports that all children (100%) within the Cleveland Metropolitan School District 
qualify for the free and reduced lunch program. 
 
6.3.  Procedures for Obtaining Informed Consent 
 
Families who are interested in participating and appear eligible based on pre-screening will 
be scheduled for a baseline visit in the CRU at which time the study will be re-explained and 
the consent and assent forms for participation signed.  Members of the study team who are 
certified in Human Subject Protection will obtain informed consent for the study.  The 
research protocol, risks and potential benefits will be discussed with the parent/guardian and 
youth privately.  They will have time to consider participation in the research study and to 
have their questions fully answered.  The consent and assent forms (Appendix F) will indicate 
that randomization and participation is entirely voluntary and that the family can withdraw at 
any time.   
 
At the intake baseline visit (time 0), members of the research study team will initially explain 
the study using the consent and assent forms.  All research study staff will be CREC certified. 
All questions will be answered.  Inclusion and exclusion criteria will be rechecked to ensure 
eligibility. This includes checking weight and height to see if BMI still meets eligibility 
requirements at baseline as per COPTR national guidelines. If the child is eligible and the 
family is interested in participating, assent and consent will be obtained for participation in the 
full study. Rarely, children’s BMI at the CRU visit will be below the threshold for eligibility (ie 
their BMI will be <85th percentile; this may occur if the child has grown a lot in height between 
their school screening and CRU visit).  The consent form will specify that if the BMI criterion is 
not met at the baseline visit (ie BMI<85th percentile), the participant will not be eligible for 
participation based on national COPTR guidelines; in such rare occurrences, the family will 
receive the visit incentive as if they had completed the entire visit and will receive  handouts 
discussing healthy living. The consent forms will also specify that if the screening tests 
indicate diabetes (FBG > 126 mg/dl) or renal disease (elevated BUN, creatinine), those 
children may not be eligible for the full study since other specific medications may be needed 
(we anticipate this to occur very rarely); however, with the family’s permission, the primary 
care physician will be notified and referral to a specialist offered. We expect the consent 

26 
 
process will take about 30 minutes.  The full consent/assent process plus collection of 
baseline data is expected to last approximately 2.5 hours.  If a participant is found not to meet 
the eligibility criteria at the baseline visit, the family will still receive the monetary incentive 
and transportation and parking reimbursement.   
 
6.4.   Randomization Procedures 
 
6.4.1.  Eligible Population and Selection of the Study Sample 
 
The study sample of 360 children will be enrolled over two years in two waves (180 in Project 
Year 3 and 180 in Year 4). In each of these years, between January and May, approximately 
3,200 children in urban Cleveland entering the 6th grade in the upcoming Fall will be 
screened for BMI as part student service-learning engagement projects at Case’s School of 
Nursing and the Case Prevention Research Center. The IMPACT project team will be 
provided with contact information (including parent/guardian names) for all screened students 
who are potentially eligible for this project (i.e. BMI ≥ 85th percentile) – excluding those 
children whose parents/guardians opted out of further contact. Based on our pilot work, we 
expect approximately 1,500 children in each of the two years will meet BMI eligibility 
standards for this study. 
  
We will thus have the entire sampling frame of 1,500 eligible parent-guardian/child pairs 
available to us before we enroll any subjects for that year. Based on our pilot data, we expect 
that 20% of families will not be available for contact (due to incorrect phone numbers, etc.) so 
we expect to approach approximately 1200 parent/family dyads for participation in each year. 
We will approach subjects for participation selecting randomly from the sampling frame within 
four strata defined by two important criteria.  
 
Specifically, we will first identify: (A) the child’s region of residence (East Side or West Side of 
Cleveland – we expect approximately 50% of eligible students to fall in each region, based on 
current school enrollments) and (B) the child’s school’s enrichment status (enriched or not 
enriched – we expect approximately 40% of eligible students will fall in enriched schools, 
based on regional enrollment in the enrichment program). 
 
The crossing of region and enrichment yields four combinations (East enriched, East not 
enriched, etc.) Grouping intervention sessions by region facilitates convenient access for the 
child and family – each of the small groups for intervention delivery will be restricted to 
students from the same region (so we’ll have some East small groups and some West small 
groups, but no groups requiring students at enrollment to cross regions.) School enrichment 
status is a key part of some secondary analyses. 
 
In each year, we will divide the enrollment period into four scheduling windows, each filled by 
contacting approximately 300 families. In each window, we will concentrate on either East or 
West region children and select subjects by moving down the sampling frame, after randomly 

27 
 
ordering the names in the initial frame within each of our four region*enrichment groups. 
Should our eventual acceptance rate be less than we expect, we will be able to add a fifth 
scheduling block in each of the recruitment years by approaching more charter schools to 
participate in the BMI screening program. We will review our procedures after evaluating the 
success of Project Year 3 recruitment so as to make appropriate adjustments to this selection 
procedure in Project Year 4. 
 
6.4.2.  Randomization and Assignment to Study Groups 
 
We expect that of the 300 families approached in each of the four scheduling windows in 
each year, at least 45 will consent/assent to participate and will meet eligibility requirements 
for randomization (i.e., including BMI confirmed as ≥ 85th percentile; completion of baseline 
anthropometrics, BP, questionnaires [other than those declined for personal reasons], 
accelerometry for minimum of 4 valid days, minimum of two diet recalls [2 weekdays or 1 
weekend, 1 weekday], and fasting blood tests [unless staff unable to draw blood] within one 
month of baseline visit) This is expected to yield approximately 180 subjects (parent-child 
dyads) per year for each of two years who will then be randomly and equally assigned to one 
of three study arms: HealthyCHANGE, SystemCHANGE, or a low-dose education-only 
control group, using the following approach. 
 
We wish to ensure that three key variables (obesity status, blood pressure status, and 
gender) are balanced (at least in distribution) across our three study groups. These are (in 
order of importance from highest to lowest): 
1. Baseline obesity status (BMI in 85th through 94th percentile vs. BMI ≥ 95th percentile) 
2. Baseline blood pressure status: (elevated [either SBP or DBP > 90th percentile] as 
defined through rigorous school screening using criteria of The Fourth Report39  or not) 
3. Gender (male, female) 
 
Each child’s value on these three key stratification variables will be entered into the overall 
study database at the time of the baseline assessment by trained data collectors.  Once a 
child has completed all procedures needed for randomization (described above; 6.4.2), the 
study coordinator (who will not be involved in data collection) will access and record a 
computer-generated study group assignment for a family, including the subject ID, level of 
each of the three minimization variables, and the randomization algorithm (note: data 
collectors are therefore kept blinded to participants’ group assignments).  The coordinator will 
both telephone the family to inform them about the group assignment and will send a 
welcome letter providing the same information, the assigned interventionist will then also 
contact the family to welcome them to the intervention and arrange logistics for their 
participation according to the protocol, and participants will be given token items branded for 
the study (T shirt, water bottle). .  
 

28 
 
Subjects will thus be randomly assigned to one of the three study groups using the 
minimization method115,116 as implemented within our REDCap system. The minimization 
approach may be thought of as a generalization of Efron’s117 original biased coin approach, 
but applied to the problem of more than two treatment arms and multiple prognostic factors 
for stratification. We have used this method in previous clinical trials with good results. As 
compared to simple random assignment or to stratified randomization using the permuted 
blocks approach, this technique has been shown to achieve better balance between study 
group assignments within levels of stratification variables.115  
 
The minimization technique may be less familiar than alternative structures for sequential 
group assignment with similar goals, such as permuted blocks or biased coin, so we provide 
some details here. Our three key stratification variables (BMI at two levels, BP at two levels 
and gender) form a set of 8 strata in the experimental design, as shown in the table below.  
 
The first subject is randomly assigned with equal probability to a study group 
(SystemCHANGE, HealthyCHANGE or education-only [Tools4CHANGE].) The approach for 
determining subsequent subject’s group assignment is determined by the minimization 
algorithm, and this is best illustrated by selecting an arbitrary point within the trial.  
 
Suppose that 20 subjects have been assigned to groups so far, and we have the following 
distribution. 
 
Table 6.1. Minimization Approach:  Distributed by Study Group and Stratification Levels 
Study Group 
BMI Percentile 
BP Elevated 
Gender 
Total 
85-94 
95+ 
Yes 
No 
Male 
Female 
SystemCHANGE 
2 
5 
3 
4 
4 
3 
7 
HealthyCHANGE 
3 
3 
4 
2 
2 
4 
6 
Tools4CHANGE 
4 
3 
3 
4 
3 
4 
7 
Total 
9 
11 
10 
10 
9 
11 
20 
  
Suppose the next patient (subject 21) has baseline BMI in the 85-94 percentile range, BP is 
not elevated, and gender is female. As applied to subject 21, the current balance of 
assignments across study groups is the range (maximum – minimum) of each column that 
applies to subject 21’s status. For instance, in the 85-94 BMI group, we have 2, 3 and 4 
assigned subjects – a range of 4-2 or 2. In the BP not elevated group, we have 4, 2, and 4 – 
so the range is also 2, and in the female group, we have 3, 4 and 4 subjects, so the range is 
1. We calculate a weighted sum across these three range results, weighting BMI percentile at 
3, BP elevated at 2, and gender at 1, based on our importance ratings. Thus, our total 
balance score is 3(2) + 2(2) + 1(1) = 11 at present for subjects in Subject 21’s stratum. Our 

29 
 
job is to select the group assignment for Subject 21 that produces the smallest balance score. 
If two or more assignments are tied, we randomly choose between them. 
 
Option 1: If we assign Subject 21 to SystemCHANGE, we will have the following table: 
 
Study Group 
BMI Percentile 
BP Elevated 
Gender 
85-94 
95+ 
Yes 
No 
Male 
Female 
SystemCHANGE 
3 
5 
3 
5 
4 
4 
HealthyCHANGE 
3 
3 
4 
2 
2 
4 
Tools4CHANGE 
4 
3 
3 
4 
3 
4 
Column Range 
4-3 (=1) 
5-2 (=3) 
4-4 (=0) 
Importance Weight 
3 
2 
1 
 
Balance score is 3(1) + 2(3) + 1(0) = 9 if Subject 21 is assigned to SystemCHANGE 
 
Option 2: If we instead assign Subject 21 to HealthyCHANGE, we have the following: 
 
Study Group 
BMI Percentile 
BP Elevated 
Gender 
85-94 
95+ 
Yes 
No 
Male 
Female 
SystemCHANGE 
2 
5 
3 
4 
4 
3 
HealthyCHANGE 
4 
3 
4 
3 
2 
5 
Tools4CHANGE 
4 
3 
3 
4 
3 
4 
Column Range 
4-2 (=2) 
4-3 (=1) 
5-3 (=2) 
Importance Weight 
3 
2 
1 
 
Balance score is 3(2) + 2(1) + 1(2) = 10 if Subject 21 is assigned to HealthyCHANGE, and, 
similarly, the Balance score is 3(2) + 2(2) + 1(1) = 11 if patient 21 is assigned to 
Tools4CHANGE. So, Subject 21 would thus be assigned to SystemCHANGE.  
 
Note that this minimization procedure can be generalized in several ways. It can be 
implemented with other (or without) importance weights, with any balancing score (for 
instance, standard deviations rather than ranges) and also can assign groups with varying 
probabilities based on the balance achieved to date (i.e. 2/3 for the study group which most 
improves balance and 1/6 for each of the other two groups) rather than selecting the best 
balance with probability one. 
 
As described in section 12, the randomization database security settings will be specified so 
that, once loaded, no one on the study team will have write privileges for the algorithm, so as 
to prevent anticipation or subversion of the randomization process, nor will the person 
receiving the assignment be able to see the assignments of other participants at the time of 
assignment.  
 
 

30 
 
6.5.  Techniques for Retention 
 
The following describe the techniques that will be used to engage and retain study 
participants in the interventions and annual assessments throughout the 3 years of the study. 
 
6.5.1. Overall Study Retention/Ongoing Retention 
 Collect personal information of both parent/guardian and child (full name, mother’s 
maiden name, spouse’s name, address, home/work/cell phone numbers, birth dates, 
email addresses, child’s name and grade in school).  Collect/confirm contact 
information each time contact is made.  Determine when is the most convenient day 
and time of day for participant to receive calls.   
 Collect contact information of 3 relatives/friends who are most likely to know contact in-
formation of study participants. Ask participants to inform contacts that they were listed 
as possible contacts and therefore may be contacted in the future. Give participants a 
form that they can give to the3 relatives/friends with the study’s contact information on 
it. Collect contact information from parent in response to the question, “Five years from 
now who is the one person who is mostly likely to know where you are?”  
 As participants are willing, have within-arm participants exchange contact information 
in order to develop a buddy system so that in the event of loss of contact with any 
participant other participants can be encouraged to contact that member.  
 Interventionists will confirm contact information each time they have contact with 
participant, and pass updated contact information to database managers as soon as 
they receive it.  
 We will have a 24-hour study phone number and designated contact person for the 
participants if any further information is needed by the participant, or if participant 
cannot/does not contact the staff specific to their arm of the study.   
 Send three newsletters a year highlighting staff members, stories/art from participants; 
things happening around town; recipes (not to include anything that would constitute 
“intervention.”) Newsletter will be sent to all participants, addressed to “index child and 
Family”. First newsletter will be sent two months after start of intervention and then q4 
months until the end of the study.  
 Send a Birthday card to both participant and parent; send a holiday card to participant 
and parent.  
 Build relationships with subjects: 
o Hire and train interventionists who will develop strong positive relationship with 
families and who will make the intervention sessions events that families look 
forward to 
o Communicate effectively and maintain close communication with subjects and 
families. IMPACT intervention staff will stay familiar with participant family 
members and family situation. When talking with participants intervention staff 
will avoid use of medical or other scientific jargon. Use every-day language 
without talking down to participants. 

31 
 
o Match data collectors to the same participant in each data collection wave to 
build and maintain interviewer/participant rapport. IMPACT staff will establish a 
project identity by frequently using particular language and phrases that 
characterize the study in a memorable way. We will use language and 
terminology that allows participants to easily describe the study. 
o Schedule participant visits at times convenient for them; IMPACT intervention 
staff will use nights or weekends to accommodate participants. 
o Be efficient in use of subject time at data collection and during intervention 
sessions.  
o IMPACT clinical core staff will schedule visits, and make reminder calls. 
o  Attempt to match data collectors with participants based on race/ethnicity 
whenever possible.   
o Interventionists will make reminder calls before each face-to-face session;  
o Return phone calls promptly. All misdirected calls from participants will be 
forwarded to designated contact person (see 24-hour phone number and 
designated contact person above).  
 Travel reimbursement to/from data collection  
o This can take the form of cab vouchers, bus fare, or mileage reimbursement.  
o For cab vouchers: if possible use same cab company for each participant. 
o For those using public transportation: provide passes.  
o For those participants driving themselves: Pay for parking wherever it is not 
free.  
 Travel reimbursement to/from intervention sessions 
o This can take the form of cab vouchers, bus fare, or mileage reimbursement.  
o For cab vouchers: if possible use same cab company for each participant 
o For those using public transportation: provide  passes; different types of passes 
will accommodate individuals and adults traveling with young children, for a day 
or for longer periods.  
o For those participants driving themselves: Pay for parking wherever it is not 
free.  
 Unexpected Token gifts – t-shirts, water bottles, special annual gift, for participant and 
parent 
o At each face-to-face session have an inexpensive grab bag-type gift for each 
participant and accompanying adult (average value not more than $1). 
 $50 Incentives for each child and each parent  at annual data collection visit. Use 
credit card-type gift cards that can be used anywhere, and function like credit cards, 
not like debit cards.  
 Protocol for tracking down lost-to-follow up (LTF) participants. 
o If phone calls result in “disconnected or no longer in use”, use all information 
collected and updated to locate participant. Attempt all cell phone and land line 
numbers given by participant. Use directory information to attempt to find new 

32 
 
information. Call at different times of day and different days of the week. 
IMPACT staff will make 5 calls attempting contact in not more than 7 days. 
o If call results in “mailbox full” response, or if otherwise unable to leave message, 
send letter to participant family requesting a response, and saying we were 
unable to contact them by phone. Continue to call at least every other day in 
case mailbox or messaging resolves. 
o If phone numbers are disconnected, mail letter to participant family requesting a 
response to last known address (include “Address Correction Requested” on 
the envelope so IMPACT will receive new address if known). Contact those 
named by participant as personal contacts and request current contact 
information for participant/family. 
o As in agreed-upon protocol with school system, contact school who will work 
with home room teacher for latest contact information. 
 
6.5.2.  Keeping Participants Engaged in the Interventions 
 
 We have branded the study so that participants feel part of an “exclusive” group 
o Give Tshirts, waterbottles, etc with project logo 
 Subjects earn points/tickets (based on attendance/participation) that are put in a lottery 
for larger prize such as gift cards, mp3 players, tickets to ball games, etc; for both 
parents and kids. 
o Grab bag “prizes” are provided at each intervention session (Items provided will 
cost about $1.00 and consist of items such as lip gloss, nail polish, key chains, 
pens/pencils, jump ropes, small balls, stress balls, and  season and holiday 
specific items such as gloves, socks, scarves, Halloween items, Valentine) . 
o Having four large activities each year (i.e., swimming, rock climbing, sporting 
event tickets, bowling). 
 Making the intervention sessions fun 
o Try It – in beginning of session introduce a new and interesting fruit or 
vegetable or exercise (i.e., yoga) method to try 
 Give frequent feedback on their weight loss progress 
 Cooking demonstrations 
o Have a guest chef to class 
o Provide cooking classes on a quarterly basis to help introduce new foods 
o Cooking competitions parent/child teams (could be a large activity) 
o Babysitting For families that need it, babysitting of small children will be 
provided at sessions to ensure participation 
o Children engaged in creative activities to display what they learn 
o Resources available for children to create “healthy” commercials, where these 
commercials can also be shown at their school 
o PhotoVoice – materials provided for children to develop pictorial collages of 
their “healthy” changes and experiences. 

33 
 
o Opportunity to make cooking videos as showcased on currenttv…can make 
their own IMPACT Youtube channel to showcase children’s cooking videos 
 Establishing a re-invigoration plan if attendance is not good. 
o Initiate a call to participant to see why attendance is not good. 
o Phone call day before session to assure attendance. 
o Attempt to problem solve attendance by offering, transportation, babysitting 
options 
o Mail information from session to home 
o Follow up phone call regarding information that was mailed. 
o Establishing a re-invigoration plan if not responding to intervention 
o Implement responsive intervention protocol 
o Provide private session with participant to go over details of what is desired 
from intervention 
o Special outreach to families 
o Following adverse events (hospitalization, illness, etc) 
o Following change in family situation (divorce, separation, death or bad illness in 
family), family move to new location, child changes schools 
 
7. INTERVENTION 
 
7.1. Conceptual Framework   
Our study addresses obesity in urban youth by focusing on two levels of the child’s environ-
ment: the child-family environment and the school-community environment. The primary 
goals of both the child-family interventions and the school-community program are to reduce 
BMI by catalyzing changes in lifestyle (diet, physical activity, sedentary behavior).   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 7.1: IMPACT Conceptual Framework 

34 
 
The proposed relationships among the major study variables and their corresponding study 
aims are depicted in the figure below. Our primary aim is to determine the impact of the two 
innovative child-family interventions (SystemCHANGE, HealthyCHANGE) when compared to 
an education-only approach, on reducing BMI (Path A), as well as assessing the moderating 
impact of an enriched school environment (Path B).  That is, will the impact of the child-family 
interventions on BMI differ among children exposed to a supportive school environment from 
those who are not. 
 
BMI and BP are termed “distal” outcomes as they likely depend on changes in other more 
“proximal” outcomes – dietary intake, physical activity, sedentary behaviors, and sleep.  As 
part of our secondary aims, we will explore the impact of the child-family interventions (and 
the moderating impact of the enriched school environment) on these more proximal outcomes 
(Paths D and C, respectively, as well as secondary outcomes, including cardiovascular risk 
factors, body composition, cost and quality of life (also Path A).   
Proposed mediators through which the interventions effect changes in both proximal and 
distal outcomes are: child’s self-efficacy, social support, motivation and family problem-
solving, systems thinking, self-regulation (Paths E and F).  The mediators represent the 
targeted approaches of each intervention (e.g., systems thinking for SystemCHANGE, 
motivation for HealthyCHANGE).  Lastly, we will explore potential moderators that influence 
the degree to which the interventions are effective including the family’s socioeconomic status 
and demographic characteristics, personal characteristics of the child, parent/guardian, and 
family (including physiological and psychosocial characteristics), the child’s physical and 
social environment (neighborhood, school, and family), and peer norms surrounding nutrition, 
physical activity and perceived environment (Paths G).  We posit that these factors may 
moderate the impact of the interventions on outcomes, as well as interventions on the 
program-specific mediators Covariates deemed from the literature to be confounders also will 
be assessed.  
 
 
7.2. Description of the Intervention(s) 
 
The IMPACT study tests two innovative family-focused interventions, HealthyCHANGE and 
SystemCHANGE, as well as the influence of a study-enriched, school-based program (We 
Run This City) that provides additional opportunity and support for the four pillars of the 
family-focused interventions (diet, physical activity, sleep, stress management).  Both the 
HealthyCHANGE and the SystemCHANGE groups receive comparable information regarding 
diet (DASH diet), physical activity, sleep and stress management. The two interventions differ 
in the behavior change approaches taught.  The content of our education-only control group 
is described below in Section 8.0. An outline of the two interventions and the control group 
protocols is attached in Appendices A-C. 
 
 

35 
 
7.2.1.  HealthyCHANGE 
 
The HealthyChange intervention is a multidisciplinary family-based weight management pro-
gram based in cognitive-behavioral theory with elements of Motivational Interviewing (MI) . 
This intervention is a modification of a hospital-sponsored program (Healthy Kids, Healthy 
Weight; HKHW) developed by co-PI Cuttler, co-I Ievers-Landis, and others. HKHW was 
modeled on family-based behavioral programs with proven efficacy23, 102, involving12 weekly 
sessions conducted over the course of three months.  Each session includes two separate 
parent and child groups focusing on food and physical activity, followed by a family (parent + 
child) session.   
 
In HealthyCHANGE, we teach a set of cognitive-behavioral/MI-consistent strategies 
addressing diet, physical activity, sedentary behavior and sleep for children of this age group. 
Using interactive teaching methods and activities, we assist youth and their parents to assess 
their value systems regarding these target behaviors as being advantageous for meeting their 
short- and intermediate-term life goals, including weight management. Approaches to 
enhancing diet and exercise self-efficacy, problem-solving abilities, and relapse prevention 
skills also will be introduced. Family communication strategies are taught and reinforced 
throughout the sessions to support the positive enactment of home-based behaviors. The 
interventionists will employ MI-consistent techniques in the sessions, including asking open-
ended questions, reflective listening and making affirmations and summary statements. MI 
will also be used to identify any barriers to children completing activity and diet logs, with 
parental assistance as needed. When reviewing these logs at each session, children and par-
ents will be asked to identify areas in which to improve diet and exercise and ideas of 
possible solutions targeting these areas. If needed, they will be assisted to problem-solve any 
barriers they anticipate in implementing these solutions. We also will provide parents with 
tools for evaluating their children’s current behaviors via daily monitoring, setting realistic 
small-increment goals to improve their children’s health-related behaviors, and practicing 
positive parenting strategies using at-home behavioral assignments. Cognitive-behavioral 
skill development will be included in each session, beginning with weekly parental monitoring 
of children’s diet and activity.  
 
7.2.2.  SystemCHANGE  
 
This study will test a newly designed intervention, SystemCHANGE, which is designed to 
assist children and their families to focus on changing the daily systems in their lives (events, 
circumstances) that affect dietary intake, physical activity, and sedentary behavior. The 
SystemCHANGE intervention teaches people to apply a distinct set of strategies associated 
with the System Improvement Framework.  This framework, also known as Continuous 
Quality Improvement (CQl) and Process Improvement, emphasizes system thinking and 
specifies that change is best accomplished by identifying a measurable goal, examining the 
system processes surrounding attainment of that goal, listing several ideas about how best to 

36 
 
improve the system, engaging in a series of experiments to test the best ideas to improve the 
process, implementing the most successful ideas based on data from the experiments, and 
monitoring the system to hold the gains. 
 
In the SystemCHANGE intervention (based on systems improvement and choice architecture 
theories) participants are taught a set of skills to change daily routines using a set of self-
designed experiments. Participants are taught about the interdependencies of their daily 
routines with others in their life and how to engage those individuals in redesigning 
family/school/work systems to promote healthier choices regarding eating, activity and sleep. 
Participants are taught to experiment with changes in the systems around them, rather than 
to try and change their personal effort or motivation for health changes.  Participants are 
taught a set of strategies to change a system to achieve a specific goal. These strategies 
include identifying a chain of steps/events that comprise the system in which the desired 
change is to occur, counting and keeping track of data about the system process to 
understand it, designing and implementing short trials of possible improvement (change) 
solutions, evaluating success by reviewing graphically-displayed data, and making provisions 
for holding the gains. The SystemCHANGE intervention focuses less on individual motivation 
than on building habitual behavioral and change into day-to-day routines. The targeted 
behaviors are exercise, diet, sedentary behavior, and sleep.  
 
The family daily routine is considered the social environment affecting this lifestyle behavior. 
Families are taught how to modify their immediate environment so that they succeed despite 
wavering motivation. A number of process improvement techniques are used, including flow 
charting daily routines, fishbone diagrams to identify a range of cause and effects on the de-
sired behavior change, selection of systems-oriented vs individual motivation-oriented 
solutions for change, using cycles of small experiments to test their ideas for improvement, 
tracking objective data about cause and effect on behavior through use of Cause and Effect 
diaries, and family storyboards.  
 
7.2.3. Adaptive Intervention  
 
As recommended by the larger national COPTR Coordinating Center, we are employing an 
adaptive intervention design118 to tailor our interventions to participants in the study. 
Participant-specific modifications to the behavioral interventions are built-in to the intervention 
protocols based on baseline, process, or outcome measures taken on participants over the 
course of the study. Explicit decision rules will be used to govern the modifications in order to 
ensure that the interventions are applied consistently to all participants in a respective arm 
and can be replicated by others. We have designed a set of decision rules for the adaptations 
for each of the family behavioral interventions (see Appendix D). 
 
 
 

37 
 
7.2.4. Enriched School-Community Environments   
 
This refers to the second “level” of our multi-level intervention and refers to schools that 
participate in a school-community-based program (We Run This City [WRTC]; 
http://www.clevelandymca.org/community/marathon/index.html) that encourages physical activity in 
students by building their capacity to participate (walking or running) in a segment of the 
Cleveland Marathon, and one that receives study supplemented programming and support, 
provided through a special interventionist called a “Navigator”. Navigators will be blinded with 
regard to the child’s family intervention group assignment.   
 
Each year, approximately 30 of the 65 K-8 CMSD schools register a “team” to participate in 
the WRTC program – approximately 85% of these schools have been engaged for multiple 
years.  Each team is lead by a “coach”, typically a physical education teacher and teams are 
comprised of 6-8th graders, varying in size from 10 to 50, depending upon the size of the 
school.  This is not a program for innate athletes; rather it was originally designed to fill the 
gaps in physical education within the CMSD curriculum.  Typically, 30-40% of the WRTC 
participants are overweight or obese and most have never run or walked for fitness in the 
past. The teams are created each December-January and training begins at the end of 
January.   All students run/walk at least 25 miles prior to the mid-May Rite Aid Cleveland 
Marathon and then finish their training with one of three options: (1) run the remaining 1.2 
miles, completing a total of 26.2 miles (distance of a marathon) by combining training miles 
and race miles); (2) run/walk the 10k (6.2 miles); or (3) run the ½ Marathon (13.1 miles).  Last 
year, over 850 CMSD students participated (45% in 1.2; 45% in the 10k and 10% in the half-
marathon).    
 
Starting in the 2012-2013 school year and the 2012 WRTC season, the IMPACT study will 
begin supplementing the WRTC teams and schools with additional programming and support 
through the study-supported Navigators. For each of the WRTC schools, the Navigators will 
work to promote healthy lifestyle behaviors among the entire student body through the 
following: 1) display of health-oriented social marketing campaign materials that complement 
the same materials that are distributed in both HealthyCHANGE and SystemCHANGE; 2) 
conduct of four, school-wide activities during each school year (2 in the fall, 2 in the spring) 
aimed at the four pillars of the study (nutrition, physical activity, sleep and stress reduction).  
A summary of the different levels of school-based programming is provided in Appendix E. 
 
In addition, program efforts will extend directly to the WRTC Youth Marathon team at each 
respective school.  These activities will be conducted in collaboration with the WRTC 
Marathon Coach; a member of the school staff.  IMPACT personnel will work closely with the 
YMCA to provide trainings for the coaches on best practices for encouraging and motivating 
overweight children for sustained participation in physical activity, as well as receiving 
additional information from their assigned Navigator for programmatic support during 
trainings, assisting coaches to improve tracking of student progress, supporting IMPACT 

38 
 
student participation and working to motivate study participants by modeling healthy 
behaviors.  Therefore, the Navigator will participate in marathon training activities at least 
twice per month (schedule permitting), will assist the coach in monitoring IMPACT participant 
conditioning patterns, and organize monthly contests that include small prizes for the “runner 
of the Month”.   
 
Non-enriched school-community environments are schools from the same school district that 
do not participate in the WRTC program and have none of these supplements to regular 
classroom-based health and physical education.    
 
7.2.5. Intervention Dose 
 
Each non-control, study participant will receive 36 months of one of the two child-family 
interventions.  SystemCHANGE and HealthyCHANGE participants will have intensive face-to-
face group meetings at 2-week intervals over the first 12 months (24 sessions of 90 minutes 
in length), followed by rotating monthly face-to-face meetings or phone calls for a further 24 
months.  Description of the control intervention is included in the next section.  
  
Approximately half of the respondents will have up to three years of the school-community 
enrichment exposure.  Due to the transient nature of many CMSD students and the changes 
in WRTC schools each year due to school closings and teacher transfers, exposure to the 
school-level intervention will be assessed as an accumulative exposure over a year’s time.  
IMPACT students will be assigned a monthly “exposure score” based on (1) whether they 
were in a WRTC school and if so, (2) their exposure to IMPACT support activities. Each 30 
days IMPACT students will be given a score using the following metric: (0) not in a WRTC 
school, (1) in a WRTC school but either no programming was conducted that month or the 
child did not participate (not enrolled in WRTC), (2) in a WRTC school and either attended a 
IMPACT supported activity or was enrolled in the program and high participation (attending 
75% or more of the scheduled activities).  These monthly status scores will be summed for an 
annual exposure, with a range from 0-36.   
 
We will communicate with each subject/family approximately q2 weeks during the first year, 
and approximately monthly thereafter. Vigilant inquiries about home address changes and 
school changes throughout the study by assigned study interventionists and data collection 
personnel have been written into our study retention plans.   
 
7.3.  Process and Fidelity Measures 
 
7.3.1.  Process Measures  
 

39 
 
Process measures will focus on intervention delivery and receipt as well as the process 
surrounding recruitment, scheduling, data collection, retention efforts, and processes 
associated with intervention personnel (see Table 7.1. below). 
 
Table 7.1.   Process Measures – Case Western Reserve University 
1. Family Intervention Delivery 
 
Bi-monthly weight of child 
 
Baseline BMI 
 
Baseline binge eating score 
 
Participants needing travel by cab for intervention visits 
 
# of sessions scheduled (face-to-face and phone) 
 
Dates each session held 
 
# sessions held (face-to-face and phone) 
 
Topics covered 
 
Features of responsive intervention activated – which features and face or phone follow-up  
according to protocol 
2. 
Family Intervention Receipt 
 
# of sessions attended – child and parent 
 
# of phone sessions attended 
 
Reasons for missing sessions 
 
Session length 
 
Session number 
 
Features of responsive intervention received - which features and face or phone follow-up 
 
Subject evaluation of individual sessions 
 
Course evaluation 
3. 
 Family Intervention Enactment 
 
Experiments (#, topic, target behavior, systems-orientation, use of storyboard/diary) 
 
Goals # identified, # met, diary (days of food and activity recorded, freq and min of PA, # fruits 
and vegs intake, sodium intake recorded) 
4. School-based Intervention Delivery  
 
School name 
 
Dates each activity conducted 
 
Time each activity conducted 
 
Activity audience (entire school, middle school students, WRTC team)  
 
Number of students in attendance (estimate) 
 
Number of staff/teachers in attendance (estimate) 
 
# of IMPACT students in attendance 
 
IMPACT participant name 
 
Location of activity (Gym, cafeteria, classroom, other) 
 
Activity leader (Navigator, WRTC Coach, Other Health Prof., Other) 
 
Activity name 
 
Activity #  
 
Target behavior of activity (diet, PA, sleep or stress) 
5. School-based Intervention Receipt 
 
# of school activities attended – child  
 
# of Marathon team-specific activities attended – child 
 
Activity length 
 
Activity topic 
 
# of face-to-face discussions with child outside of marathon activities. 
6. Navigators (school-based) 
 
Number trained 
 
Gender 
 
Race 
 
Other demographics of Navigators – discipline, experience, etc 

40 
 
 
Documentation of initial training, retraining and bi-weekly supervision – time, topics 
 
Time spent by Navigators 
o 
School-based intervention delivery  
o 
WRTC Coach Support 
o 
Intervention activity preparation 
o 
Travel to school/YMCA 
o 
Other contacts/follow-up with participants 
 
Training/retraining/supervision meetings 
7. Family Interventionists  
 
Number trained 
 
Gender 
 
Race 
 
Other demographics of interventionists – discipline, experience, etc 
 
Documentation of initial training and retraining – time, topics 
 
Time spent by interventionists – intervention delivery (face-to-face and phone) 
o 
Intervention preparation 
o 
Intervention travel 
o 
Other contacts/follow-up with participants 
o 
Training/retraining/supervision meetings 
8. Recruitment  
 
Size of population – # of children in population, #children screened, number study eligible, 
reason for non-eligibility 
 
# to be approached for participation (qualified on first screen) 
 
# reached 
 
# agreeing to come to CRU 
 
# ineligible on second screen and why 
 
# coming to CRU 
 
# consenting 
 
Reasons for refusal 
 
# of people assigned to arm 
 
Cohort number 
 
Number in the cohort 
9. Scheduling & Retention for CRU visits 
 
# attempts to reach the participant after parent/guardian expresses interest in participating (ie 
includes busy signals, no answers)? 
 
# phone calls to the participant to schedule visit?  
 
# needing to be rescheduled (and breakdown:  cancel, no show, etc) 
 
# participants answering or  returning our calls for the 4th and 9th day of wearing the 
Accelerometer 
 
Days for return of accelerometer after call on last day of wear? 
 
Reminder calls:  # per scheduled visits  
 
# participants needing cabs 
10. Study Data Collection Procedures 
 
#  of parents and children declining to use the iPad and  preferring to do the questionnaire via 
paper 
 
# children using headphones versus reading questions on the iPad 
 
Time to complete visit (and its components) 
 
# calls to complete all the diet recalls/evaluation visits 
 
# of assessment visits within window 
11.  Retention 
 
# of children moving away from area 
 
# of children moving within area 
 
# of children changing school (and which school moved to) 
 
Number of children choose to  withdraw from study (and reason) 
 

41 
 
7.3.2. Fidelity Measures 
 
In addition to process measures, a plan has been developed to capture the five important 
components of intervention delivery:  fidelity, dose delivered, dose received, program design 
and reach. These measures are outlined in the table below. 
Table 7.2:  Fidelity Measures: Case Western Reserve University 
Part I:  Fidelity: The extent to which the intervention is delivered as intended; quality of the 
intervention; how well an intervention is being implemented compared to its original design; 
could include, but not limited to, content & quality of messages,  adherence to protocol, and 
intervention staff skill/training/certification 
Fidelity 
Fidelity Construct 
Data Collection 
Method 
Completed By 
Timing of Data 
Collection 
Intervention Component #1: Family-Based 
 
 
 
Family 
Intervention 
Component  
Content and quality 
of messages 
Family Intervention 
Session Audit Forms 
Intervention 
manager 
First 4 sessions, 
then random 30% 
of sessions 
Adherence to 
intervention protocols 
Family Intervention 
Session Audit Forms 
Intervention 
manager 
First 4 sessions, 
then random 30% 
of sessions 
Interventionist 
Session Checklists 
Interventionists 
At each session 
Interventionist 
Training: 
Standardized training  
 
Interventionist 
Training Checklists 
 
Intervention 
Trainer (PI/PD) 
 
After initial 
interventionist 
training &  
annually 
Interventionist 
Training Evaluation 
Survey 
Interventionists 
After initial 
interventionist 
training &  
annually 
Interventionist skill 
acquisition and 
competency 
Family Intervention 
Session Audit Forms 
Intervention 
manager 
First 4 sessions, 
then random 30% 
of sessions 
Interventionist 
delivery:  
Number and length of 
sessions delivered 
 
Family Intervention 
Session Audit Forms 
Intervention 
manager 
First 4 sessions, 
then random 30% 
of sessions 
Interventionist 
Session Checklists 
Interventionists 
Each session 
Interventionist Time 
Log (Participant 
Contacts) 
Interventionists 
After each 
participant contact 
(phone or face-to-
face) 
Interventionist 
attrition rates 
Special 
Administrative data 
base 
Intervention 
Trainer (PI/PD) 
Annually 

42 
 
interventionist 
training and re-
training 
Field notes of PI 
Interventionists 
Annually 
 
Intervention Component #2: School/Community-Based 
Community 
Intervention 
Component 
Content and quality 
of messages 
School-based 
Intervention Activity 
Audit Forms 
School 
Intervention 
Coordinator or 
Community and 
Data Core 
Manager 
Attend and 
observe first 
school-wide 
activity and first 
WRTC training, 
then audit random 
30% of sessions.  
Adherence to 
protocol 
School-based 
Intervention Activity 
Audit Forms 
School 
Intervention 
Coordinator or 
Community and 
Data Core 
Manager 
Attend and 
observe first 
school-wide 
activity and first 
WRTC training, 
then audit random 
30% of sessions.  
School-based 
Intervention Activity & 
WRTC Training 
Session Checklists 
Navigators 
After each school-
wide or WRTC 
activity. 
Navigator Training: 
Standardized training 
Navigator Training 
Checklists 
School 
Intervention 
Coordinator or 
Community and 
Data Core 
Manager 
After initial 
Navigator training 
&  annually 
Navigator skill 
acquisition and 
competency 
 
 
Navigator Training 
Evaluation Survey 
Navigator 
Trainer  
Navigator 
After initial 
Navigator training 
&  annually 
School-based 
Intervention Activity 
Audit Forms 
School 
Intervention 
Coordinator 
First school-wide 
activity  and 
WRTC training, 
then random 30% 
of sessions 
Navigator delivery:  
Number and length of 
sessions delivered 
School-based 
Intervention Activity 
Audit Forms 
 
School 
Intervention 
Coordinator 
 
Attend and 
observe first 
school-wide 
activity and first 
WRTC training, 
then audit random 
30% of sessions.  
School-based 
Intervention Activity & 
WRTC Training 
Session Checklists  
Navigators 
At each school 
activity and/or 
WRTC training 
session  
Navigator Time Log 
(WRTC Coach & 
Participant Contacts) 
Navigators 
After each WRTC 
Coach & 
participant contact  
Navigator attrition 
rates 
Administrative data 
base 
Navigator 
Trainer 
(PI/SIC/C&D 
Annually 

43 
 
Manager) 
Special Navigator 
training and re-
training 
Field notes of PI 
Navigators 
Annually 
Part II:  Dose Delivered: The amount of intervention that was delivered; could include, but 
not limited to, number and length of sessions implemented 
Dose 
Delivered 
Dose Delivered 
Construct 
Data Collection 
Method 
Completed By 
Timing of Data 
Collection 
Intervention Component #1: Family-Based 
Family 
Intervention 
Component 
Subject Attendance 
 
Participant 
Intervention Process 
Forms 
Interventionists 
Each Session 
Number and length of 
sessions 
implemented 
Family Intervention 
Session Audit Forms 
Intervention 
manager 
First 4 sessions 
then random 30% 
of sessions 
Interventionist Time 
Logs 
(Participant contacts) 
Interventionists 
After every subject 
contact 
Participant 
Intervention    
Process Forms 
Interventionists 
Beginning of every 
session 
Adherence to 
protocol 
Interventionist 
Session Checklists 
Interventionists 
After every 
session 
End-of-Session 
Evaluations 
Participants 
End of every 
session 
Intervention Component #2: School/Community-Based 
Community 
Intervention 
Component 
Subject Attendance 
School-based 
Intervention Activity  
Process Forms 
Navigators 
Each Session 
Number and length of 
activities, 
implemented, and 
WRTC training 
sessions attended. 
School-based 
Intervention Activity 
Audit Forms 
School 
Intervention 
Coordinator 
Attend and 
observe first 
school-wide 
activity and first 
WRTC training, 
then audit random 
30% of sessions.  
Navigator Time Logs 
(WRTC Coach & 
Participant contacts) 
Navigators 
After each WRTC 
Coach & 
participant contact  
Content and quality 
of messages 
School-based 
Intervention Activity  
Process Forms 
Navigators 
At the beginning of 
each activity 
Adherence to 
protocol 
School-based 
Intervention Activity & 
WRTC Training 
Session Checklists  
Navigators 
At each school 
activity and/or 
WRTC training 
session  
End of WRTC 
Season Evaluation 
WRTC 
Coaches, and 
team members 
inclusive of 
IMPACT 
Participants 
End of WRTC 
Marathon season 
(annually) 

44 
 
PART III:  Dose Received:  The amount of intervention that was received; could include, but 
not limited to, participant engagement, and intervention messages or materials received 
Dose Received 
Dose Received 
Construct 
Data Collection 
Method 
Completed By 
Timing of 
Data 
Collection 
Intervention Component #1: Family-Based 
Family 
Intervention 
Component 
Subject Attendance 
Family Attendance 
Participant 
Intervention 
Process Forms 
Interventionists 
Each Session 
Content and quality 
of messages, 
Number and length 
of contacts 
Family Intervention 
Session Audit Form 
Intervention 
manager 
First 4 
sessions, then 
random 30% 
of sessions 
Participant 
engagement 
Participant 
Intervention 
Process Form 
Interventionists 
Beginning of 
every session 
Participant 
satisfaction 
behavioral change 
Participant 
Behavioral Logs 
Participants 
 
At each 
session 
Participant 
Experiment Logs 
Participants 
At each 
session 
End-of-Session 
Evaluation  
Participants 
After every 
session 
End-of-Study 
Evaluation 
Participants 
Annually and 
End of Study 
Intervention Component #2:  School/Community Based 
Community 
Intervention 
Component 
Subject Attendance 
School-based 
Intervention Activity  
Process Forms 
Navigators 
Each session 
Content and quality 
of messages, 
Number and length 
of contacts 
School-based 
Intervention Activity 
Audit Forms 
School Intervention 
Coordinator 
Attend and 
observe first 
school-wide 
activity and 
first WRTC 
training, then 
audit random 
30% of 
sessions.  
Participant 
engagement  
 
School-based 
Intervention Activity  
Process Forms 
Navigators 
 
Each session 
Participant 
satisfaction 
End of WRTC 
Season Evaluation 
 
WRTC Coaches, 
and team members 
inclusive of IMPACT 
Participants 
 
End of WRTC 
Marathon 
season 
(annually) 
Part IV.  Program Design: The assessment of non-specific treatment effects, could include, 
but not limited to participant satisfaction with, feasibility, and costs of intervention 
Program 
Design 
Program Design 
Construct 
Data Collection 
Method 
Completed By 
Timing of 
Data 
Collection 
Intervention Component #1: Family-Based 

45 
 
 
 
 
 
Family 
Intervention 
Component 
Participant 
satisfaction with 
program 
components 
End-of-Session 
Evaluation  
Participants 
After each 
session 
End-of-Study 
Evaluation 
Participants 
Annually and 
at end of 
study 
Interventionist time 
to prepare and travel 
to deliver 
intervention 
Interventionist Time 
Log (Non-participant 
Contacts) 
Interventionists 
After every 
contact 
Intervention Component #2: School/Community-Based 
Community 
Intervention 
Component 
Participant 
satisfaction with 
program 
components 
End of WRTC 
Season Evaluation 
IMPACT participants 
End of WRTC 
Marathon 
season 
(annually) 
Navigator time to 
prepare and travel to 
deliver intervention 
Navigator Time 
Logs 
(Non-participant 
Contacts) 
Navigator 
After each 
activity 
Part V.  Reach:  The proportion of intended recipients who actually participate in an 
intervention; the extent to which the intervention is reaching the target population; could 
include, but not limited to, attendance, participation, and engagement by group (e.g. race, 
gender, SES, intervention group) 
Reach 
Reach Construct 
Data Collection 
Method 
Completed By 
Timing of 
Data 
Collection 
Intervention Component #1: Family-Based 
Family 
Intervention 
Component 
Representation 
(eligible, consented) 
Recruitment Logs 
Recruiter 
Ongoing  
Attendance, 
participation, 
completion, attrition, 
& engagement by 
race, gender, 
school, intervention 
group, BP status, 
and obesity level 
Participant 
Intervention 
Process Form 
Interventionists 
Every session; 
group analysis 
reviewed 
quarterly by 
PIs 
Clinical Data 
Data collectors 
Data manager 
Annually and 
end of study 
Intervention Component #2: School/Community Based 
Community 
Intervention 
Component 
Representation, 
(eligible, consented)  
Recruitment Logs 
Recruiter 
Ongoing  
Attendance, 
participation, 
completion, attrition, 
and engagement. 
School-based 
Intervention Activity  
Process Forms 
Navigators 
Every session; 
group analysis 
reviewed 
quarterly by 
PIs 
Annually and 
end of study 

46 
 
7.4.  Unblinded Process MeasuresT 
 
The following is the list of process variables where unblinding for aggregation by study arm or 
cohort is requested by the Case Western Reserve study site.  
 
Table 7.3:  Unblinded Process Variables: Case Western Reserve University 
Variables 
When 
Aggregation Level 
Purpose 
Arm 
Cohort 
Family Intervention Delivery 
# of sessions scheduled (face-to-
face and phone) 
Monthly 
X 
X 
Assure comparable attention 
across study arms and cohorts. 
# of sessions actually held  
Monthly 
X 
X 
Topics covered in sessions (to be 
coded) 
Monthly 
X 
X 
Activation  of responsive intervention 
(which features and # of face-to-face 
or phone follow-up sessions)  
Monthly 
X 
X 
Assure comparable delivery of 
responsive intervention protocol 
across study arms and cohorts. 
# subjects needing cab 
transportation for intervention visits 
Quarterly 
X 
X 
Assure comparable access to 
interventions across study arms 
and cohorts. 
Family Intervention Receipt 
# of sessions attended by child and 
by parent 
 
Monthly 
 
X 
 
X 
Assure comparable attention 
across study arms and cohorts. 
# of phone calls attended by child 
and by parent 
Monthly 
X 
X 
Reasons participants miss sessions 
Quarterly 
X 
X 
Problem-solve possible issues 
regarding intervention receipt by 
arm or cohort. 
Session length and number 
Quarterly 
X 
X 
Assure comparable attention 
across study arms and cohorts. 
Features of responsive intervention 
received (which features and # of 
face-to-face or phone follow-up 
sessions) 
 
Monthly 
 
X 
 
X 
Assure comparable receipt of 
responsive intervention protocol 
across study arms and cohorts. 
Subject evaluations of individual 
sessions 
Monthly1 
X 
X 
Problem-solve intervention 
receipt issues by arm and 
cohort. 
Course evaluations 
Annually 
X 
X 
Family Intervention Enactment 
Experiments (#, topics, target 
behaviors, systems orientation) 
Quarterly 
 
X 
Within SystemCHANGE arm 
only. For comparison by cohort 
to monitor/assure subject receipt 
of key intervention components  
Use of storyboard  
Quarterly 
 
X 
 
               As Above 
Goals (# identified, # met)  
Quarterly 
 
X 
HealthyCHANGE arm only. . For 
comparison by cohort 
to monitor/assure subject receipt 
of key intervention components 
                                                          
 
 

47 
 
Diary Completion 
Quarterly 
 
X 
Comparison of rates of 
completion within each arm to 
assure comparable delivery and 
receipt across both arms. 
Community  Intervention Delivery and Receipt 
Child Marathon participation status 
Monthly 
X 
X 
Assure comparable receipt of 
school intervention across arms 
and cohorts.  
Interventionist Information 
 
# of interventionists  
 
Quarterly 
X 
X 
Assure comparable number of 
interventionists across arms and 
cohorts. 
Interventionist gender, age, race, 
discipline, experience, other 
demographics 
Annually 
 
X 
 
X 
Assure comparable expertise 
levels, as well as race and age 
match across arms and cohorts. 
Interventionist training/ retraining 
(time, topics) 
Quarterly 
X 
X 
Assure comparable 
interventionist expertise across 
arms and cohorts. 
Interventionists time spent in 
delivery, travel, participant follow-up 
Quarterly 
X 
X 
Assure comparable subject- 
interventionist contact time 
across arms and cohorts. 
Participant Recruitment and Retention 
# participants assigned  
Monthly 
X 
X 
Assure comparable intervention 
group size across study periods. 
# of children moving out of city 
Monthly 
X 
X 
Assure comparable access to 
interventions across arms and 
cohorts. 
# of children moving within the city 
Monthly 
X 
X 
# of children changing school 
Monthly 
X 
X 
Assure comparable access to 
school intervention across arms 
and cohorts. 
1 Data will be gathered at the end of each face-to-face session, but aggregated results will be reviewed on a monthly 
basis. 
 
 
8. CONTROL CONDITION  - Tools4CHANGE 
In contrast to the behavioral arms, youth with their parent(s)/guardian randomized to the 
education-only group will have one 60-minute face-to-face meeting at initiation of the study 
with a dietitian who is also trained in recommendations for exercise and sedentary behavior. 
The dietitian will review the goals of the Tools4CHANGE intervention pertaining to diet, 
physical activity, and sedentary behavior described above. The dietitian will provide individual 
Dash diet meal plan and review food groups and serving sizes. The family will be given 
several handouts and booklets (5th-6th grade level) that provide written documentation of the 
recommended guidelines and useful suggestions. The family will also be given tools to guide 
gradual increase in physical activity and reducing sedentary behavior with the goals 
described.  The importance of family involvement will be reviewed.   
 
After the initial 60-min session, participants in this group will receive three other contacts with 
study personnel approximately quarterly in each of the study years (this is in addition to the 
annual clinical assessment received by all study participants).  Two of the contacts will be 
phone calls during which there will be a general discussion reminding them of their 

48 
 
participation in the study and checking on accuracy of home address and school attended. 
The third contact will be a social gathering event (i.e., picnic, ball game) of small groups of 
families in the control group. 
 
9. MEASUREMENTS 
 
9.1  Methods 
 
9.1.1.  Primary Outcome  (BMI) and Other Anthropometric Measures 
 
Primary Outcome – BMI 
 
BMI - Background and Rationale.   The measure used as the primary outcome variable of all 
four COPTR trials is body mass index (BMI).  BMI assesses body weight adjusted for height 
and is correlated with percent body fat as assessed by dual energy x-ray absorptiometry119-
121.  When calculated using measured anthropometrics BMI is highly reliable.  BMI has 
demonstrated clinical validity in its associations with type 2 diabetes mellitus122; 123, 
hyperinsulinemia124, blood pressure and hypertension120; 125; 124, adverse lipoprotein 
profiles124-126  and early atherosclerotic lesions127; 128  among children and adolescents.  
Importantly, BMI can be assessed easily in clinical and public health settings and is generally 
accepted and well understood. 
 
BMI – Objective.  The objective of the BMI measures is to provide a precise and accurate 
measure of the impact of the intervention on relevant aspects of body size in the children 
studied in COPTR. 
 
BMI – Methods.   All consented index children in the COPTR study have weight and height 
measured at the beginning and end of the intervention (36 months) and at two common 
interim time points (12 and 24 months).  All baseline anthropometric data will be collected 
prior to randomization.  Weight and height are measured with the participant in light clothing 
without shoes.  Weight is measured to the nearest 0.1 kg using research precision grade, 
calibrated, digital scales and height is measured to the nearest 0.1 cm using a free-standing 
or wall mounted stadiometer.  BMI is calculated as weight in kilograms divided by the square 
of height in meters. 
 
All height and weight measurements are collected by trained and certified staff.  COPTR will 
use a “train the trainer” model.  Each field center will designate one or more “Master Trainers” 
who participate in a central training organized by the RCU at the University of North Carolina 
at Chapel Hill on April 16-18, 2012.  These Master Trainers are responsible for training and 
certifying the data collection staff at their center.  
 
 

49 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
Other Anthropometric Secondary Outcomes 
Anthropometric secondary outcomes differ by site as detailed in Table 9.1.  Variables 
measured in the index child at all sites include waist circumference and triceps skinfold.  All 
sites are measuring height and weight in at least one adult family member of the index child 
and some sites are measuring siblings.  Secondary outcomes that will be calculated from 
anthropometry in at least one site include BMI z-score, waist-to-height ratio (WtHR), and 
percent body fat.  
Other Anthropometrics:  Background and Rationale.  BMI z-scores provide a method for 
evaluating the weight status of children adjusted for age and gender.  The measure is 
commonly used in clinical practice to track body size trajectory.  However, several authors 
have cautioned against the use of BMI z-scores for research using longitudinal designs citing 
concerns that their use could result in spurious differences between groups129; 130.  One 
reason for this problem is that children at the extreme ends of the BMI distribution require 
substantially greater changes in weight than their thinner counterparts for the same change in 
z-score.  Also because the BMI z-score curves were constructed using only data between the 
3rd and 97th percentiles, the CDC recommends extreme caution when using the growth 
curves outside this range131.  Finally, Berkey et al. noted that the difference between z-scores 
reflect larger differences in BMI in older compared to younger children.  For these reasons 
Table 9.1 Anthropometric Common Measures by Research Center 
Anthropometric Measure 
Case 
Minnesota 
Stanford 
Vanderbilt 
Index Child 
 
 
 
 
     Weight 
x 
x 
x 
x 
     Height 
x 
x 
x 
x 
     Waist circumference 
x 
x 
x 
x 
     Triceps skinfolds 
x 
x 
x 
x 
 
 
 
 
 
Other Children 
 
 
 
 
     Weight 
-- 
x* 
x† 
-- 
     Height 
-- 
x* 
x† 
-- 
     Waist circumference 
-- 
-- 
x† 
-- 
     Triceps skinfolds 
-- 
-- 
x† 
-- 
 
 
 
 
 
Other Adults 
 
 
 
 
     Weight 
x 
x* 
x 
x 
     Height 
x 
x* 
x 
x 
     Waist circumference 
-- 
-- 
x 
x 
     Triceps skinfolds 
-- 
-- 
-- 
x 
* Minnesota: All children and adults in household. 
† Stanford: Only study eligible children 

50 
 
the COPTR investigators have chosen to study BMI z-score as a secondary rather than a 
primary outcome. 
 
Abdominal adiposity is associated with metabolic risk factors in children132-135  although 
evidence to date suggests that anthropometric measures tend to only moderately predict 
visceral fat136; 137.  Waist circumference is a feasible non-invasive measure of abdominal 
fatness for community-based assessments of children. It has also been shown to be sensitive 
to change in response to prevention interventions138. 
 
Waist-to-height ratio (WtHR) is a simple index that has recently received increased interest 
from investigators139.  After the age of four years, waist and height appear to simultaneously 
increase during childhood and adolescence140.  Thus, WtHR could provide a practical 
estimate of adiposity that could be consistently applied to a wide range of age groups.  
Recently Browning et al. published a systematic review of waist to height ratio as a screening 
tool for cardiovascular and diabetes-related outcomes139.  In their examination of 13 cross-
sectional studies in children they found that waist-to-height ratio compared favorably with 
waist circumference and BMI.  In a cross-sectional study of 1,511 youth 8 to 17 years of age 
McMurray et al.  found that waist circumference performed well as a predictor of insulin 
resistance in boys but not girls141.  Better performance was observed when waist 
circumference was divided by height, producing an index that was highly associated with 
insulin resistance in both genders and over a range of ages.  Kahn et al. and Savva et al. 
have suggested a WtHR cut point of 0.49 to distinguish high and low levels of risk, however, 
McMurray et al. suggest that a WtHR of 0.54 may result in fewer misclassifications.  WtHR 
can also be analyzed in the continuous form140-142.  COPTR can provide an opportunity to 
further evaluate this index using both cross-sectional and longitudinal designs. 
 
Triceps skinfold thickness is a measure of subcutaneous fat and is a component of equations 
used to predict percent body fat.  COPTR investigators are using data from the NHANES 
study to develop a prediction equation for percent body fat that uses triceps skinfold along 
with other anthropometric variables collected in COPTR (height, weight and waist 
circumference) together with demographic variables to predict percent body fat (see section 
4.8. in RCU protocol).   Equations were developed in children in the age ranges being studied 
by Case Western and Stanford.  Preliminary work indicates that this equation has an R2 of 
over 0.8.  Unfortunately estimates of percent body fat from DEXA are not available in children 
less than 8 years of age in NHANES.  Therefore Vanderbilt and Minnesota will estimate 
percent body fat in younger children in their study using the prediction equation created by 
Dezenberg  (R2=0.95 as compared to DEXA, Model SEE=0.46) using data from White and 
African American 4 to 11 year old children143. This method has been shown to have higher 
validity across subgroups than other equations144; 145  and has been validated in 3 to 8 year 
old White and Hispanic children.   
 

51 
 
Obesity has been shown to cluster in families such that having obese parents increases the 
risk of obesity in children146-148.  This clustering is due to both shared environment and 
genetic factors. The collection of anthropometric variables in the families of the index children 
in COPTR provides an opportunity to examine longitudinal changes within families in the 
family members and to assess any impact of the intervention on family members. 
 
Other Anthropometrics - Objective.  The anthropometric secondary outcomes are assessed 
to provide a richer understanding of the changes in body size characteristics associated with 
the COPTR interventions.   
 
Other Anthropometrics - Methods. Waist circumference and triceps skinfolds will be 
measured at the beginning and end of the intervention (36 months) and at two common 
interim time points (12 & 24 months).  Measurement details have been determined with 
guidance from the 2007 NHANES anthropometry procedures manual (Centers for Disease 
Control, 2007, (http://www.cdc.gov/nchs/data/nhanes/nhanes_07_08/manual_an.pdf).  Waist 
is measured to the nearest 0.1 cm just above the uppermost lateral border of the right ilium 
using a Gulick II tape measure, model 67020.   
 
The triceps skinfold is measured using a Lange skinfold caliper (or a Harpenden caliper if the 
measurement exceeds capacity of the Lange skinfold caliper) in the midline of the posterior 
aspect (back) of the arm, over the triceps muscle, at a point midway between the lateral 
projection of the acromion process of the scapula (shoulder blade) and the inferior margin 
(bottom) of the olecranon process of the ulna (elbow).  Skinfolds are measured to the nearest 
0.1 mm. 
9.1.2.  Common Demographics, Moderators, Mediators and Secondary Outcomes 
 
Demographics, Moderators and Mediators 
 
Background and Rationale.   Self-reported information will be collected from COPTR index 
children and other household members by obtaining responses to written or verbalized 
questions.  Although we refer to “questionnaires”, as discussed in the methods section below, 
several methods are used to collect these data, and only a minority of the data is collected 
through the use of paper questionnaires.  The information obtained is used to describe the 
study population or as a confounder, mediator, moderator or secondary outcome of 
intervention effects.   
 
In general, the mediators chosen for measurement are targeted by the intervention, are 
expected to change as a result of the intervention and to result (directly or indirectly) in 
change in BMI.  In COPTR, each Field Site's intervention is unique and many of the mediator 
variables are site-specific because they serve as explanatory constructs for the site-specific 
theoretical model.  A moderating variable is defined as a variable that could influence the 
primary or secondary outcomes because the variable interacts with the intervention to change 

52 
 
study outcomes.  In other words, the intervention affects people differently, depending on their 
status on the moderator variable. These variables are evaluated at the beginning and the end 
of the intervention, and in some cases as interim measurements.  
 
Objective.  The purpose is to describe the characteristics of participants, to determine 
possible mediators and moderators of intervention effects and to study secondary outcomes 
that are impacted by the intervention.  
 
 
Methods.  The demographic, household, mediators and moderators survey is administered to 
parents/primary caregivers of the participating child and/or to the participating child.  Table 
9.2. summarizes the location where the questionnaire will be administered and administration 
format in each site.  To accommodate the sample being studied some sites administer 
questionnaires in Spanish.    
 
Table 9.3 lists the questions used to collect common questionnaire data and shows which 
sites are collecting each item.  All of the common survey questions are not administered at all 
Field Sites. The source of the 55 common questions and the responses are listed in Table 
9.4. There will be four common measurement time points – baseline, 12 months, 24 months 
and 36 months.  All common data collection will occur between May 2012 and February 
2017.  All baseline data collection will occur prior to randomization.  Measurement data 
collectors are not intervention staff unless data are collected prior to randomization.   
 
Table 9.2  Characteristics of questionnaire administration by Field Sites 
 
Field Sites 
Case Western 
Minnesota 
Stanford 
Vanderbilt 
Administration 
Location 
Clinic 
Home 
Community center, 
Home, or Clinic 
Community center 
Administration 
Format 
Interviewer 
administered 
Interviewer 
administered 
Interviewer 
administered (child) 
and mix of interviewer 
and self-administered 
(parent) 
Interviewer 
administered 
Data collection 
format 
Computer 
Computer 
Paper 
Computer 
Computer 
Languages 
English 
Spanish 
English 
Spanish 
 
English and 
Spanish (parents) and 
English (child) 
English only in 
pilot; English and 
Spanish in main 
trial 
Respondent 
Parent or primary 
adult caregiver and 
participating child 
Parent or primary 
adult caregiver 
Parent(s) or primary 
adult caregivers and 
participating child 
Parent or primary 
adult caregiver 

53 
 
Table 9.3  Common Demographics, Moderators and  Mediators by Site 
Construct 
Item 
Case 
Minnesota 
Stanford 
Vanderbilt 
Household 
Configuration 
For all children and adults living in your 
household, please tell me: 
 
 
 
 
Gender, 
X 
X 
X 
 
Birth date, or age 
X 
X 
X 
 
Relationship to the participating child. 
X 
X 
X 
 
Child’s date of 
birth 
Child’s date of birth 
X 
X 
X 
X 
Child Sex 
What is this child sex?  
X 
X 
X 
X 
Child Ethnicity 
Is this child Hispanic, Latino/a or of 
Spanish origin?  
X 
X 
X 
X 
Child Race 
Which of the following best describes 
your child?  
X 
X 
X 
X 
Parent Ethnicity 
Are you Hispanic, Latino/a or of Spanish 
origin?  
X 
X 
X 
X 
Parent Race 
Which of the following best describes 
you?  
X 
X 
X 
X 
Parent Country 
of Birth 
In what country were you born? 
 
X 
X 
X 
Child Country of 
Birth 
In what country was this child born? 
 
X 
 
X 
Years Parent 
Lived in USA 
How many years total have you lived in 
the United States? 
 
X 
X 
X 
Employment 
Status 
What is your employment status? 
X 
X 
X 
X 
Marital Status 
What is your current marital status? 
X 
X 
X 
X 
Access to Car 
Is there a car that you can use 
whenever you need to? 
X 
X 
 
X 
Frequency of 
Speaking 
English at 
Home with 
Family 
How often do you speak English at 
home with your family? (Choose one.) 
 
X 
X 
 
If you do not always speak in English at 
home with your family, what languages 
do you speak the rest of the time? 
X 
X 
 
 
WIC 
Do you participate in WIC? WIC stands 
for Women, Infants, and Children, a 
Federal assistance program. 
X 
X 
 
X 
Food Stamps/ 
SNAP 
Does anyone in your household receive 
food stamps or SNAP? SNAP stands for 
X 
X 
X 
X 

54 
 
Supplemental Nutrition Assistance 
Program. 
Unemployment/  
Social Security/  
Disability  
Does anyone in your household receive 
Unemployment, Social Security, or 
Disability Benefits? 
X 
X 
X 
 
Education 
Completed 
What is the highest degree or level of 
school that you have completed?  
X 
X 
X 
X 
What is the highest degree or level of 
school that your child's other parent 
living in the household or adult 
caregiver living in the household has 
completed?  
X 
X 
X 
X 
Child Care 
In a usual week, how much time does 
this child spend being cared for by 
someone other than parent/guardian? 
 
 
 
 
in your own home 
 
X 
X 
X 
in someone else’s home 
 
X 
X 
X 
in childcare center/after school 
program 
 
X 
X 
X 
Household 
Income 
What was your total household income 
from all sources before taxes last year? 
By "household", we mean that you 
should report the combined income of 
everyone in your home. 
X 
X 
X 
X 
Child Health 
Insurance 
Is your child covered by a health 
insurance plan? 
X 
X 
X 
 
Which type of plan are they covered by? 
X 
X 
X 
 
Free or 
Reduced Price 
Breakfast or 
Lunch 
Does any child in your household 
receive free or reduced price breakfast 
or lunch at school? 
 
X 
X 
 
Maturation 
Status 
Has your daughter started having her 
menstrual period? 
X 
 
X 
 
When did she have her first menstrual 
period? 
X 
 
X 
 
Breastfeeding/ 
Pregnancy Risk 
Did <this child> breastfeed for more 
than a month? 
X 
X 
 
X 
How old was <this child> in months 
when he/she first received a bottle of 
formula, cow’s milk, water, juice, tea, or 
cereal at least once a day? 
X 
X 
 
X 
How much did this child weigh at birth? 
X 
X 
 
X 
Did a doctor say that <you/birth mother> 
X 
X 
 
X 

55 
 
had diabetes when pregnant with <this 
child>? 
Did a doctor say that <you/birth mother> 
had hypertension (high blood pressure) 
when pregnant with <this child>? 
X 
X 
 
X 
Food Security 
“The food that (I/we) bought just didn't 
last, and (I/we) didn't have money to get 
more." Was that often, sometimes, or 
never true for (you/your household) in 
the last 12 months? 
X3 
X 
X 
X 
“I/we couldn't afford to eat balanced 
meals." Was that often, sometimes, or 
never true for (you/your household) in 
the last 12 months? 
X3 
X 
X 
X 
In the last 12 months, since (date 12 
months ago) did (you/you or other 
adults in your household) ever cut the 
size of your meals or skip meals 
because there wasn't enough money for 
food? 
X3 
X 
X 
X 
How often did this happen --almost 
every month, some months but not 
every month, or in only 1 or 2 months? 
X3 
X 
X 
X 
In the last 12 months, did you ever eat 
less than you felt you should because 
there wasn't enough money to buy 
food? 
X3 
X 
X 
X 
In the last 12 months, were you ever 
hungry but didn't eat because you 
couldn't afford enough food?. 
X3 
X 
X 
X 
 
TV & Media 
How many working TVs do you have in 
your home? 
X1 
X 
X 
 
Is there a working TV in the room where 
<this child> sleeps? 
X1 
X 
X 
X 
Is there a computer in your home? 
X1 
X 
X 
X 
Is there a computer in the room where 
<this child> sleeps? 
X1,2 
X 
X2 
X 
Is there a video game player in your 
home? 
X1 
X 
X 
 
Is there a video game player in the 
room where <this child> sleeps? 
X1 
X 
X 
X 
Do you have Internet access in your 
home? 
X1 
X 
 
 
On an average WEEK day, how many 
 
X 
 
X 

56 
 
 
hours does <this child> watch TV? 
On an average WEEKEND day, how 
many hours does <this child> watch 
TV? 
 
X 
 
X 
On an average day, how many hours 
does <this child> play video or 
computer games, or use a computer for 
something that is not school work? 
(Include activities such as Play Station, 
Xbox, hand held video games, 
computer games, and the Internet.) 
 
X 
 
X 
Food Norms 
During the past seven days, how often 
did your family eat breakfast together? 
 
X 
 
X 
During the past seven days, how often 
did your family eat lunch together? 
 
X 
 
X 
During the past seven days, how often 
did your family eat dinner together? 
 
X 
 
X 
Weight Status 
How would you classify your own 
weight? 
X 
X 
X 
X 
How would you classify <this child's> 
current weight? 
X 
X 
X 
X 
1 – The TV/Media questions for Case are derived from a group of embedded scale questions 
2 – Case and Stanford uses the term “desktop” computer in their question. 
3—Case questions are embedded into a survey and are not administered as an interview. 

57 
 
 
Table 9.4  Source and Response Sets of Questionnaire Common Measures 
Construct 
Item 
Response Options 
Source 
Household 
Configuration 
For all children and adults living in 
your household, please tell me: 
 
Developed 
Gender, 
Male; Female 
Birth date or age 
MMDDYYYY; __ __ yrs 
Relationship to the 
participating child. 
Mother; Father; Stepmother; 
Stepfather; Other male CG, 
(list);  Other female CG, (list) 
Child’s date of 
birth 
Child’s date of birth 
MMDDYYY 
Developed 
Child’s sex 
What is this child’s sex? 
Male; Female 
HHS data 
standards220  
Child Ethnicity 
Is this child Hispanic, Latino/a, or 
of Spanish origin? (Choose all that 
apply.) 
No, not of Hispanic, Latino/a 
or Spanish origin; Yes, 
Mexican American, 
Chicano/a; Yes, Puerto 
Rican; Yes, Cuban; Yes, 
Another Hispanic, Latino/a or 
Spanish origin 
HHS data 
standards220  
Child Race 
Which of the following best 
describes your child? (Choose all 
that apply.) 
American Indian or Alaskan 
Native Asian; Black or 
African American; Native 
Hawaiian or Pacific Islander; 
White; Other (please 
describe) 
U.S. Census, 2010 
Parent Ethnicity 
Are you Hispanic, Latino/a, or of 
Spanish origin? (Choose all that 
apply.) 
No, not of Hispanic, Latino/a 
or Spanish origin; Yes, 
Mexican American, 
Chicano/a; Yes, Puerto 
Rican; Yes, Cuban; Yes, 
Another Hispanic, Latino/a or 
Spanish origin 
HHS data 
standards220  
Parent Race 
Which of the following best 
describes you? (Choose all that 
apply.) 
American Indian or Alaskan 
Native Asian; Black or 
African American; Native 
Hawaiian or Pacific Islander; 
White; Other (please 
describe) 
U.S. Census, 2010 
Parent Country 
of Birth 
In what country were you born? 
USA; Mexico; Somalia; 
Laos/Thailand/Vietnam; 
Other  (please describe) 
Marin 
Acculturation 
Scale 
Child Country of 
In what country was this child 
USA; Mexico; Somalia; 
Laos/Thailand/Vietnam; 
Modified Marin 
Acculturation 

58 
 
Table 9.4  Source and Response Sets of Questionnaire Common Measures 
Construct 
Item 
Response Options 
Source 
Birth 
born? 
Other  (please describe) 
Scale 
Years Parent 
Lived in USA 
How many years total have you 
lived in the United States? 
_ _ yrs 
Marin 
Acculturation 
Scale 
Employment 
Status 
What is your employment status? 
Working full time; Working 
part time; Not working for pay 
Developed 
Marital Status 
What is your current marital 
status? 
Married or living as married; 
Single 
Developed  
Access to Car 
Is there a car that you can use 
whenever you need to? 
Yes and I drive; Yes but I 
don’t drive; No 
Developed  
Frequency of 
Speaking 
English at Home 
with Family 
How often do you speak English at 
home with your family? (Choose 
one.) 
Never; Sometimes; About ½ 
the time; Most of the time; 
Always 
Marin 
Acculturation 
Scale 
 
If you do not always speak in 
English at home with your family, 
what languages do you speak the 
rest of the time? 
Free text 
WIC 
Do you participate in WIC? WIC 
stands for Women, Infants, and 
Children, a Federal assistance 
program. 
Yes; No; Don't know 
Developed 
Food Stamps/ 
SNAP 
Does anyone in your household 
receive food stamps or SNAP? 
SNAP stands for Supplemental 
Nutrition Assistance Program. 
Yes; No; Don't know 
Developed  
Unemployment/  
Social Security/  
Disability  
Does anyone in your household 
receive Unemployment, Social 
Security, or Disability Benefits? 
Yes; No; Don't know 
Developed  
Education 
Completed 
What is the highest degree or level 
of school that you have 
completed? (Choose one answer.) 
6th grade (elementary 
school) or less; 7th - 8th 
grade (attended some 
middle school/junior high); 
9th - 12th grade (attended 
some high school); High 
school graduate (received 
diploma or the equivalent, 
GED for example); 
Completed some college 
credit, (or technical school) 
but no degree; Technical 
degree; Associate’s degree; 
College degree; Master’s, 
Professional, or Doctoral 
Modified U.S. 
Census, 2010  

59 
 
Table 9.4  Source and Response Sets of Questionnaire Common Measures 
Construct 
Item 
Response Options 
Source 
degree 
What is the highest degree or level 
of school that your child's other 
parent living in the household or 
adult caregiver living in the 
household has completed? 
(Choose one answer.) 
6th grade (elementary 
school) or less; 7th - 8th 
grade (attended some 
middle school/junior high); 
9th - 12th grade (attended 
some high school); High 
school graduate (received 
diploma or the equivalent, 
GED for example); 
Completed some college 
credit, (or technical school) 
but no degree; Technical 
degree; Associate’s degree; 
College degree; Master’s, 
Professional, or Doctoral 
degree 
Modified U.S. 
Census, 2010 
Child Care 
In a usual week, how much time 
does this child spend being cared 
for by someone other than 
parent/guardian… 
 
Developed 
in your own home? 
0 Hours; 1-10 Hours; 11-20 
Hours; 21-30 Hours 
31-40 Hours; 41+ Hours 
in someone else’s home? 
0 Hours; 1-10 Hours; 11-20 
Hours; 21-30 Hours 
31-40 Hours; 41+ Hours 
in childcare center/after school 
program? 
0 Hours; 1-10 Hours; 11-20 
Hours; 21-30 Hours 
31-40 Hours; 41+ Hours 
Household 
Income 
What was your total household 
income from all sources before 
taxes last year? By "household", 
we mean that you should report 
the combined income of everyone 
in your home. 
$14,999 or less;  
$15,000 - $24,999; $25,000 - 
$34,999; $35,000 - $49,999; 
$50,000 - $74,999; $75,000 - 
$149,999; $150,000 -  
$199,999; $200,000 or more; 
Don't know; I prefer not to 
answer 
Developed 
Child Health 
Insurance 
Is your child covered by a health 
insurance plan? 
Yes; No; Don't know 
 
Which type of plan are they 
covered by? 
Medicaid, Medicare, CHIP, 
state funded, or other 
federally funded; Private - 
through work or purchased 
individually; Military; Other, 
 

60 
 
Table 9.4  Source and Response Sets of Questionnaire Common Measures 
Construct 
Item 
Response Options 
Source 
type unknown; Don't know 
Free or Reduced 
Price Breakfast 
or Lunch 
Does any child in your household 
receive free or reduced price 
breakfast or lunch at school? 
Yes; No; Don't know 
Modified from 
TAAG2 
Maturation 
Status 
Has your daughter started having 
her menstrual period? 
Yes; No; Don't know 
Developed 
When did she have her first 
menstrual period? 
MMYYYY 
Developed 
Breastfeeding/ 
Pregnancy Risk 
Did <this child> breastfeed for 
more than a month? 
Yes; No; Don't know 
Schwarz et al. 210 
How old was <this child> in 
months when he/she first received 
a bottle of formula, cow’s milk, 
water, juice, tea, or cereal at least 
once a day? 
_ _ mos. 
Schwarz et al. 210 
How much did this child weigh at 
birth? 
_ _ lbs _ _oz 
Schwarz et al. 210 
Did a doctor say that <you/birth 
mother> had diabetes when 
pregnant with <this child>? 
Yes; No; Don't know 
Schwarz et al. 210 
Did a doctor say that <you/birth 
mother> had hypertension (high 
blood pressure) when pregnant 
with <this child>? 
Yes; No; Don't know 
Schwarz et al. 210 
Food Security 
“The food that (I/we) bought just 
didn't last, and (I/we) didn't have 
money to get more." Was that 
often, sometimes, or never true for 
(you/your household) in the last 12 
months? 
Often true; Sometimes true; 
Never true; Don’t know; 
Refused 
USDA (Bickel, 211 
“I/we couldn't afford to eat 
balanced meals." Was that often, 
sometimes, or never true for 
(you/your household) in the last 12 
months? 
Often true; Sometimes true; 
Never true; Don’t know; 
Refused 
USDA 211 
In the last 12 months, since (date 
12 months ago) did (you/you or 
other adults in your household) 
ever cut the size of your meals or 
skip meals because there wasn't 
enough money for food? 
Yes; No; Don’t know; 
Refused 
USDA  211 

61 
 
Table 9.4  Source and Response Sets of Questionnaire Common Measures 
Construct 
Item 
Response Options 
Source 
How often did this happen --almost 
every month, some months but not 
every month, or in only 1 or 2 
months? 
Almost every month; Some 
months but not every month; 
Only 1 or 2 months; Don’t 
know; Refused; Not asked 
USDA  211 
In the last 12 months, did you ever 
eat less than you felt you should 
because there wasn't enough 
money to buy food? 
Yes; No; Don’t know; 
Refused 
USDA  211 
In the last 12 months, were you 
ever hungry but didn't eat because 
you couldn't afford enough food?. 
Yes; No; Don’t know; 
Refused 
USDA  211 
TV & Media 
How many working TVs do you 
have in your home? 
text 
Derived from 
Borzekowski212, ; 
Robinson138,; 
Robinson et al.213 
Is there a working TV in the room 
where <this child> sleeps? 
Yes  
No 
Is there a computer in your home? 
Yes  
No 
Is there a computer in the room 
where <this child> sleeps? 
Yes  
No 
Is there a video game player in 
your home? 
Yes  
No 
Is there a video game player in the 
room where <this child> sleeps? 
Yes  
No 
Do you have Internet access in 
your home? 
Yes, No, Don't Know 
On an average WEEK day, how 
many hours does <this child> 
watch TV? 
None  
Less than 1 hour per day 
1 hour per day 
2 hours per day 
3 hours per day 
4 hours per day 
5 or more hours per day 
Schmitz et al.214  
On an average WEEKEND day, 
how many hours does <this child> 
watch TV? 
None 
Less than 1 hour per day 
1 hour per day 
2 hours per day 
3 hours per day 
4 hours per day 
5 or more hours per day 
Schmitz et al.214 
On an average day, how many 
hours does <this child> play video 
or computer games, or use a 
None 
Less than 1 hour per day 
1 hour per day 
Modified Schmitz 
et al.214 

62 
 
Table 9.4  Source and Response Sets of Questionnaire Common Measures 
Construct 
Item 
Response Options 
Source 
computer for something that is not 
school work? (Include activities 
such as Play Station, Xbox, hand 
held video games, computer 
games, and the Internet.) 
2 hours per day 
3 hours per day 
4 hours per day 
5 or more hours per day 
Food Norms  
During the past seven days, how 
often did your family eat breakfast 
together? 
0 times 
1-2 times 
3-4 times 
5-6 times 
7 or more times 
Developed 
During the past seven days, how 
often did your family eat lunch 
together? 
0 times 
1-2 times 
3-4 times 
5-6 times 
7 or more times 
Developed 
During the past seven days, how 
often did your family eat dinner 
together? 
0 times 
1-2 times 
3-4 times 
5-6 times 
7 or more times 
Developed 
Weight Status 
How would you classify your own 
weight? 
Very Underweight 
Underweight 
Normal 
Overweight 
Very Overweight 
Modified Birch et 
al.215 
How would you classify <this 
child's> current weight? 
Very Underweight 
Underweight 
Normal 
Overweight 
Very Overweight 
Modified Birch et 
al.215 
 
A “train the trainer” model is used to prepare staff to collect questionnaire data.  Each Field 
Site designates two or more “Master Trainers” who participate in central trainings conducted 
by the RCU at the University of North Carolina at Chapel Hill on April 16-18, 2012.  These 
Master Trainers are responsible for training and certifying the data collection staff at their 
Field Site.  To be certified, Master Trainers attends the central training, reads the protocol 
and manual of procedures, complete the questionnaire and administer the questionnaire.  
The data collectors are certified by a Master Trainer who will describe the data collection 
process, insure that the protocol and manual of procedures are read and observe the 
questionnaire being administered to a volunteer.    
 
 

63 
 
Secondary Outcomes:  Accelerometry 
Background and Rationale.  Physical activity (PA) will be measured objectively using a 
commercially available ActiGraph GT3X+ (all youth). For parents and other adults GT3X+ 
accelerometers (Vanderbilt) or GT3X accelerometers (Minnesota) will be used. (ActiGraph, 
Pensacola, FL). The rationale for using ActiGraph is that among currently available devices 
it provides consistent and high quality data supported by feasibility, reliability, and validity 
testing in children and adults.  
ActiGraph monitors have been used in numerous studies to assess PA in children149-152. The 
validity of the ActiGraph has been examined in several studies involving children aged  2 
to18 years. ActiGraph has been validated using direct observation153-155, doubly labeled 
water (DLW)156; 157 (, indirect calorimetry158-162  and other accelerometers159; 154  as reference 
methods. Correlations between ActiGraph counts and observed activity was moderate to 
high (r = 0.52-0.77) in older ActiGraph models (Hands, 2006; Kelly et al., 2004; Sirard, 2005) 
and higher in a newer ActiGraph (GT1M) model and when using more advanced algorithms 
(Choi et al., 2010). Although the validity of ActiGraph GT3X and GT3X+ models in 
populations including children has not be reported, it is expected to be at least as high or 
higher than the GT1M and older ActiGraph models. 
 
The GT3X+ and GT3X contain electronic motion sensors consisting of piezo-electric 
sensors that generate an electric charge in response to a mechanical force, thus, 
acceleration. They do not respond to constant acceleration. Their major advantage is that no 
power supply is required, except for data storage, resulting in a considerable reduction in 
the size and weight of the device.  Both monitors provide activity counts, vector magnitude, 
and inclinometry data. Other data calculated by the ActiGraph manufacturer-provided 
software includes activity intensity levels, energy expenditure (METs) and number of steps. 
 
The GT3X+ collects data in the raw format at a pre-defined sample rate from 30 to 100 
Hertz (Hz). When collecting data at 40 Hz, the battery life is stated to be 13 days and the 
data memory lasts for 16 days. The GT3X has the ability to collect 1-second epoch data for 
at least 7 days. The GT3X does not have adequate data storage capacity to collect raw data 
for multiple days. 
 
Accelerometry technology is still improving and mathematical models to predict PA and PA-
related energy expenditure are being developed. We expect these advances to continue. 
Thus, COPTR investigators will collect raw acceleration data in the index child that could be 
used to measure physical activity and sedentary behavior using both currently existing 
algorithms and new algorithms/approaches that emerge during the study (next 6 years).  
Table 9.5. summarizes the specifications of the GT3X devices. 
 
 

64 
 
Table 9.5.  Specifications of the GT3X devices 
Specifications 
GT3X+ 
GT3X 
Transducer 
Tri-axis, solid state accelerometer 
Tri-axis, solid state 
accelerometer 
Dynamic Range 
+/- 3G 
+/- 3G 
Dimensions 
4.6cm x 3.3cm x 1.5cm 
3.8cm x 3.7cm x 1.8cm 
Capacity 
16 Days (Raw data at 40 Hz) 
16MB or 400 Days (60 sec 
epoch) 
Battery Life 
13 Days (Fully Charged at 40 Hz) 
20 Days (Fully Charged) 
Weight 
19 g 
27 g 
Resolution 
12-bit A/D conversion; 1.46 mG (Raw 
Data) 
12-bit A/D conversion; 1.46 mG 
(Raw Data) 
Sample Rate 
30Hz-100 Hz 
30 Hz 
 
Limitations of accelerometry.   Accelerometers are the best currently available relatively 
simple and precise device for objectively assessing physical activity and sedentariness. 
However, they do not provide information on types of activities, nor can they be used to 
assess lifestyle activities such as raking and shoveling, static activities such as bicycling and 
weight lifting, and aquatic activities such as showering and swimming. These limitations may 
be addressed as new algorithms emerge during the course of the study. Other limitations 
are related to use and application of collected data in device-specific arbitrary counts (PA 
counts) or more comparable approach of using acceleration (m/sec2) to summarize 
accelerometry data. 
Objective.   Accelerometry monitoring will provide an objective measurement of the amount 
and patterns of physical activity and sedentary behavior. 
 
Methods.  Accelerometry data on children and parent (Minnesota and Vanderbilt) will be 
collected at four common data collection time points – baseline, 12 months, 24 months and 
36 months.  All baseline accelerometer data will be collected prior to randomization.  The 
GT3X+ will be set to 40-Hertz frequency and the GT3X will be set to 1-second epoch.    
 
The index children in the study will wear the GT3X+ monitor on the right hip for seven 
complete days (including while sleeping and naptime) except during water activity (e.g., 
bathing, swimming, showering).  The responding parent in Minnesota and Vanderbilt will 
also wear the GT3X and GT3X+ monitor, respectively for seven days on their right hip.  A 
consensus has been reached that the monitoring period should include two weekend days 
and five weekdays.  In some cases, participants may be able to provide only 6 days of data, 
which is acceptable.  If the participant does not wear the activity monitor for four days, it may 
be necessary to have the participant wear the monitor again in order to get valid data.  The 
valid wear time criteria (minimums) are 4 days (3 weekdays and 1 weekend day) of at least 
6 hours of awake time with 33% non-zero epochs per hour.   For some participants, 

65 
 
accelerometer data for the 2 wears will be combined in order to meet the minimum wear 
time criteria.   
 
Any major updates in the ActiLife software version used during the trial will be made as a 
collaborative decision by the Diet and Physical Activity Working Group.  If a change does 
occur, it will be on the same calendar day for all Field Sites.  Regular (minor) updates in the 
ActiLife software will be done by each Field Site as they are released by ActiGraph. The 
Accelerometer Manual of Procedures will be updated only after major updates in the ActiLife 
software (e.g. Version 6.0 to Version 7.0).   
 
COPTR will use a “train the trainer” model.  Each field center will have at least two activity 
monitor master trainers who will participate in a central in-person training organized by the 
RCU at the University of North Carolina at Chapel Hill on April 16-18, 2012.  Following part 1 
of the training session, the master trainers will wear the accelerometer for at least 8 hours.  
The certification process requires the master trainer to successfully initialize, download and 
transfer accelerometer data.   The master trainers will train and certify additional research 
staff at their site.   Data collectors/staff do not initialize or download accelerometer data until 
after they have been trained and certified.   
 
Secondary Outcomes:  Dietary Assessment  
 
Background and Rationale.   The 24-hour recall is the most widely used method to assess 
diet in studies of populations, and is used in national food consumption surveys such as the 
NHANES. This method allows assessment of all foods, beverages and dietary supplements 
consumed during the 24-hour period obtained – typically beginning with the first item 
consumed the previous day. The 24-hour method, which can be performed face-to-face or 
by telephone, has been validated in lean and obese individuals163; 164. In face-to-face 
interviews, the use of visual aids such as food models, food portion booklets and measuring 
utensils improves the accuracy of estimation of quantities consumed165. For telephone 
interviews, visual aids and instructions are often mailed to subjects166. In addition, with a 
trained interviewer, they are relatively quick and easy to administer. An important strength of 
the 24-hour recall method is that it allows comparison of groups of individuals by 
demographic variables such as age, gender, race/ethnicity or geographic region.  Another 
strength is that the 24-hour recall (Nutrition Data Systems for Research or NDSR) has been 
used to generate Healthy Eating Index scores, and thus to assess dietary quality167.  The 
main limitations of capturing quantitative dietary intake information by use of 24-hour recalls 
are: 1) the variability in day-to-day dietary intakes; 2) reliance on subject memory; and 3) the 
potential of over or underreporting of intakes. To compensate for these possible limitations, 
interviewers typically capture data on more than one day of the week which includes both 
weekdays and weekend days, and use the USDA 5-step multi-pass method165. 
 

66 
 
Objective.   The purpose of performing dietary intake assessment is to capture quantitative 
nutrient information on all the foods, beverages and dietary supplements that study subjects 
consume.  The dietary intakes are analyzed for:  volume of food, total energy, 
macronutrients, micronutrients, water, dietary fiber, added sugars and specific food groups.  
We will also examine glycemic load, dietary energy density, nutrient adequacy ratios, and 
dietary pattern and quality. Examples of diet quality indices used in children are shown in 
Table 9.6. 
 

67 
 
Table 9.6. Examples of dietary quality indices used in children 
Citation 
Subjects 
Diet Assessment 
Group/Index 
Methods 
 
N 
Sex 
Age 
 
 
Daniels, EJCN, 
2009168 
1,810 
m/f 
 2y 
24 hr recall 
Diet Diversity score(DDS-
10g) - FAO (score 1-9)  
Cross-sectional: 1 pt per 10g of a each food group or 
1 pt for 1g oil. 
Feskanich, 
JAmDietAssoc, 
2004169 
16,452 
m/f 
9-14y 
132 item FFQ 
Youth HEI- 13 components 
(score 0-100) 
Modified HEI and compared to YHEI (Note: YHEI not 
strongly related to energy intake).  
Freedman, 
JNutr, 2010170 
17,311 
m/f 
2y 
24hr recall 
HEI-2005:  12 dietary 
components 
NHANES (’01-’04) data- 3 part model (they create) 
based on Tooze 2- part model219 in >1000 subjects. 
Guenther, 
JAmDietAssoc, 
2008171 
8,650 
m/f 
2y 
24 hr recall 
HEI-2005  
NHANES (’01-’02) compared HEI-2005 assessed 
validity through 4 methods (concluded valid).  
Kennedy, JNutr, 
2007172 
3,164  
m/f 
24-71 
mo 
24 hr recall 
Diet Diversity Score (DDS) – 
10 food group & 
DDS-10g  
Filipino Nutrition Database. DDS 
summed unique food groups for score. DDS-10g 
required minimum amounts (see: Daniels, 2009). 
Manios, 
JAmDietAssoc, 
2009173 
2,287 
m/f 
2-5y 
24 hr recall + 
weighed records 
+ food diaries 
HEI- 10 component 
Weighed records were used in nurseries and recalls 
or diaries were used outside nurseries. Summed 
individual scores- used quartiles of the scores for 
analysis.  
Steyn, Public 
Health Nutr, 
2006174 
2,200 
m/f 
1-8y 
24 hr recall 
DDS- following FAO 
guidelines 
Food Variety Score (FVS)  
(Score 0-45)    
Secondary analysis of NFCS in South Africa. 1 24 hr 
recall by caregivers. Also used nutritional adequacy 
ratio and mean adequacy ratio.  
 
Serra-Majem, 
EJCN, 2003175 
3,166 
m/f 
6-24y 
24 recall +16 
item FFQ 
KIDMED- Mediterranean 
diet measure  
(Score: -3 to 12)  
Assessed diet from Spanish children has high, med, 
low KIDMED. 
Kranz, 
JAmDietAssoc, 
2006176 
5,437 
m/f 
2-5y 
24 recall 
Created new- RC-DQI 
 
Continuing Survey of Food intakes by individuals 
(1994-1996, 1998) components chosen based on My 
Food Pyramid, ADA, and APA recommendations 
(Nutrient-based) 
Hurley, JNutr, 
2009177 
317 
m/f 
11-19 
131 item- youth/ 
adolescent FFQ 
Compared HEI and YHEI  
Compared the indices to body composition and 
found HEI better correlated with body composition 
and disease risk. 
LaRowe, 
JAmDietAssoc, 
2010178 
135 
m/f 
2-5 
24 hr recall 
My Food Pyramid  
Great Lakes Inter-Tribal Council Head Start 
programs- baseline data from HCSF intervention.  
 
Cheng, JNutr, 
2010179 
376 
m/f 
6-8y 
3-day weighed 
record 
Nutritional Quality Index 
(NQI)- Density measure 
RC-DQI- nutrient based 
German Cohort 

68 
 
 
Methods.   Dietary Intakes will be measured using 24-hour recalls that are conducted on two 
weekdays and one weekend day per study time-point using NDS-R version 2012.  Any update 
in the NDS-R version during the trial will be made as a collaborative decision by the Diet and 
Physical Activity Working Group.  If a change does occur, it will be on the same calendar day 
for all Field Sites with one caveat.  Participants who have already completed 1 or 2 recalls in 
the old version of NDS-R will have their remaining recalls conducted using the same older 
version of NDS-R such that all 3 recalls are collected using the same version of NDS-R. 
 
Dietary assessment data will be collected at baseline, and 12, 24 and 36 months during the 
study.  All baseline dietary assessment data will be collected prior to randomization.  Table 
9.11 summarizes the specific data collection plans for each Field Site.  To avoid collecting 
days with similar foods, recalls should not be conducted on consecutive days.  In addition, in 
order to capture variability of food supplies in the home, all three recalls should not occur 
within a seven day period.  The third recall needs to be collected more than one week after the 
first recall.  All three recalls must be collected within 30 days.  This is a hard deadline.  While 
the goal is to collect three dietary recalls per participant, it is possible that a limited number of 
participants at each Field Site may only have two dietary recalls completed within the 30 day 
window.  All efforts will be made to obtain a minimum of two recalls (1 weekday and 1 
weekend) for each participant.  All dietary intakes (i.e., food, and beverages including water) 
will be collected.  For Diet Recall of young children, those responsible for child feeding (e.g. 
parents, daycare providers) will be the reporter.  Details of the procedures to be used in dietary 
assessment are in the COPTR Manual of Procedures for Dietary Assessment. 
 
COPTR will use the “train- the- trainer” model.  Each field center will have two diet master 
trainers who will participate in a central in-person training organized by the RCU at the 
University of North Carolina at Chapel Hill on April 16-18, 2012.  Following the training session, 
the master trainers will complete two dietary recalls for certification by the RCU.  The master 
trainers will train and certify additional research staff at their site.  No diet recalls will be 
conducted until after the trainer has been trained and certified.   
 
 
 
 
 
 
 
 
 
 

69 
 
 
 
 
 
 
 
 
 
 
 
 
 
Secondary Outcomes: Blood Pressure 
 
Background and Rationale.    Elevated blood pressure (BP) in overweight children and 
adolescents is an increasingly recognized epidemic180-183 (.   Many overweight/obese youth 
with elevated BP already have other cardiovascular risk factors and evidence of end-organ 
damage184-186; 182; 187; 183 Children with elevated BP are likely to become adults with elevated 
BP, and therefore are at increased risk for cardiovascular and renal disease180; 188-191. These 
data indicate that children with obesity and elevated BP are at particularly high risk, and 
require intervention185.  Weight loss is a powerful tool to reduce BP in children and adults180; 
192.  A diet rich in fruits/vegetables, low-fat dairy, low-fat protein (e.g. DASH-like diet) and/or 
reduced sodium intake can also reduce BP, particularly in African-American adults180; 193-195; 
209.  Combined with calorie reduction, activity, and behavioral interventions, DASH diets 
facilitate simultaneous reduction of BMI and BP in adults196. However, the most effective 
methods to facilitate adoption of these lifestyle changes in children are not clear, and 
education alone (usual care) is often ineffective193.  This knowledge gap is particularly 
important because of the huge potential impact of small changes in BP180.  Therefore, blood 
pressure will be obtained for all participants from the two COPTR sites (Case Western 
Reserve University and Stanford University) testing interventions to treat overweight and 
obesity.   
 
Objective.  We will determine if interventions to reduce overweight and obesity reduce blood 
pressure.  In addition we will use the 3-year longitudinal data to examine risk factors and 
correlates of blood pressure changes over time in children and adolescents. 
 
Table 9.7.  Site specific 24 hour dietary recall data collection plans 
 
Case 
Minnesota 
Stanford 
Vanderbilt 
Number of 
recalls 
3 
3 
3 
3 
# weekdays 
2 
2 
2 
2 
# weekends 
1 
1 
1 
1 
Recaller 
Child & parent 
Parent & day care 
provider 
Child & parent 
Parent & day 
care provider 
How collected 
(1st, 2nd, 3rd) 
In-person 
Telephone 
Telephone 
In-person 
In-person/Telephone 
In-person/Telephone 
In-person 
Telephone 
Telephone 
Telephone 
Telephone 
Telephone 
Announced/ 
Unannounced 
Announced 
Announced 
Unannounced 
Announced 
Language 
administered 
English, Spanish 
English, Spanish 
English, Spanish 
English,  
Spanish 
Use of Portion 
Size Devices 
Food Booklet 
Food Booklet  
Food Booklet 
Food Booklet & 
Measuring 
Utensils  

70 
 
 
Methods.   An automated blood pressure measurement device (OMRON HEM-705-CP or 
OMRON HEM-705-CPN Digital Blood Pressure Monitor) and a standardized procedure for the 
measurement of blood pressure and pulse will be utilized, as specified in the Blood Pressure 
Manual of Procedures (MOP).  The design and operation of the OMRON HEM-705-CP and the 
OMRON HEM-705-CPN Digital Blood Pressure Monitor are based upon the combined 
principles of compression of the brachial artery under an elastic, inflatable cuff and estimation 
of the systolic and diastolic blood pressure levels by oscillometric methods. 
 
Blood pressure and pulse will be measured at four data collection time points – baseline, 12 
months, 24 months and 36 months.  All baseline blood pressure and pulse measurements will 
be collected prior to randomization.  Blood pressure measurement must be conducted early in 
the visit and not following potentially stressful exam components such as the blood drawing.  
Before measurements commence participants are offered the opportunity to visit a restroom or 
bathroom. The participant should not have smoked or had any caffeine within the last 30 
minutes prior to the blood pressure determinations.   
 
Blood pressure measurements will be taken using the right arm.  Participants should sit quietly 
for 4-5 minutes before the first measurement is taken.  Seated, resting blood pressure and 
pulse are measured three times at each evaluation visit. The first reading will be discarded and 
the average of the second and third measurements will be used in analysis.   
 
The OMRON HEM-705-CP and the OMRON HEM-705-CPN are automated devices.  The data 
collector determines and places the correct size cuff on the participant's arm, pushes the 
button on the device and waits for the output.  All readings will be recorded to the nearest 
integer. 
 
COPTR uses a “train the trainer” model.  Each Field Site designates two or more “master 
trainers” who participate in central trainings organized by the RCU at the University of North 
Carolina at Chapel Hill, NC from April 16 to April 18, 2012.  The designated master trainers are 
responsible for training and certifying the data collection staff at their center.  For certification, 
the data collector is observed by the trainer.  The participants must include 5 or more children 
requiring varying cuff sizes. The trainee must correctly select the appropriate cuff size and 
demonstrate consistent compliance with the MOP to be certified.  No blood pressure and pulse 
measurements will be taken until after the data collector has been trained and certified. 
 
Secondary Outcomes: Biomedical Measures 
 
Background and Rationale.  Hyperinsulinemia/insulin resistance is a risk factor for future Type 
2 diabetes, and is associated with increased blood pressure, adverse lipid profiles and 
increased body fatness in children and adolescents124; 197; 198, and weight loss is associated 
with improved insulin sensitivity among adolescents199.   Thus, insulin resistance serves both 
as a direct indicator of a significant risk factor and as a biochemical marker of metabolically-

71 
 
 
significant adiposity and changes in adiposity. Increased fasting insulin concentration is an 
appropriate marker of insulin resistance for this study.   
 
Fasting insulin concentrations can also be combined with fasting glucose concentrations using 
a number of algorithms, including the HOMA and QUICKI, among others, to generate indices. 
However, all of these calculated measures of insulin resistance appear to be highly correlated 
with fasting insulin concentrations in non-diabetic subjects200.  The Stanford group have 
recently confirmed this with their own data from the 8-10 year old African-American girls in 
Stanford GEMS (correlations of .98-.99). However, because a fasting glucose will also be 
collected, the Field Sites will be able to examine each of these combination indices. Fasting 
glucose will also be collected to identify children with previously undiagnosed type 2 diabetes 
(fasting glucose ≥ 126 mg/dl) and to identify children who will be referred for further evaluation 
by their primary care medical provider (fasting glucose ≥ 110 mg/dl) according to Field Sites 
clinical monitoring protocol.  
 
Adverse lipid profiles are risk factors for cardiovascular diseases and increased BMI is 
associated with increased total cholesterol, LDL-cholesterol, and triglycerides and lower HDL-
cholesterol concentrations125; 201; 124; 202; 203.   Thus, lipid measures also serve both as direct 
indicators of a significant risk factor and as a biochemical marker of metabolically-significant 
adiposity and changes in adiposity. 
 
High levels of C-reactive protein (CRP) is a marker for inflammation.  CRP prospectively 
assesses the risk of atherosclerotic complications, may be a mediator of vascular injury and is 
strongly related to obesity204.   In adults, higher body mass index (BMI) levels are associated 
with higher CRP concentrations.  Some clinicians are starting to use CRP levels when 
assessing risk for cardiovascular disease.  Using cross-sectional data from the National Health 
and Nutrition Examination survey 1999-2000, Ford found significant associations between 
CRP levels and BMI in children 3 to 17 years of age205.  CRP levels were also associated with 
age and systolic blood pressure, but BMI had the strongest association.   
 
Unexplained elevated levels of alanine Aminotransferase (ALT) has been liked with adiposity 
and may be a marker for nonalcoholic fatty liver disease (NAFLD) in adolescents and adults206; 
207.   Researchers have found a close association between metabolic syndrome, insulin 
resistance, elevated ALT levels and NAFLD in overweight/obese children and adolescents206; 
208.  
 
Objective.  We will determine if the COPTR interventions to reduce overweight and obesity 
change cardiovascular risk factors measured in blood.  In addition we will use the 3-year 
longitudinal data to examine the risk factors and their correlates over time.  
 
Methods.  Blood specimens are collected at baseline, 12 months and 36 months at the two 
Field Sites testing interventions to treat overweight and obesity – Case Western Reserve 
University and Stanford University.  All baseline blood specimen samples are collected prior to 

72 
 
 
randomization.  All common blood specimens are analyzed by the Northwest Lipid Metabolism 
and Diabetes Research Laboratories (NWRL).  The biomedical measures analyzed in the 
index child are Hemogloblin A1c (HbA1c), Glucose, Total Cholesterol, LDL-cholesterol, HDL-
cholesterol, Triglycerides, high-sensitivity C-reactive protein (hs-CRP), Insulin and Alanine 
Aminotransferase (ALT).  Salivary DNA will be obtained from the child at the year 1 visit with 
additional consent/assent (not yet submitted to IRB); families who decline provision of DNA will 
still be able to continue in the study.  This approach is based on our experience that consent 
for DNA can take substantial time and may intimidate some families who may decline to 
participate in the study if DNA is collected at baseline 
 
Fasting status will be confirmed prior to blood draw.  A trained phlebotomist at each site is 
responsible for the blood collection.  However, a data collector might have the responsibility for 
mailing the blood specimens to the NWRL.  All specimen samples will be frozen to allow for 
batch shipment.  The assays and quality control for each measurement is described below. 
 
HbA1c  
The measurement of the relative proportion of hemoglobin subclasses and calculation of the 
HbA1c levels are performed by an NGSP-certified auto-analyzer (G-8 Tosoh, Biosciences, 
Inc.) using non-porous ion exchange high performance chromatography to achieve rapid and 
precise separation of stable HBa1c from other hemoglobin fractions. The system calibration is 
maintained using two point calibration reagents. A set of quality control samples are analyzed 
twice daily. The acceptance allowance for quality control is + 0.1% variance from the target 
value for the low level, and + 0.2% variance from the target value for the high level. The inter-
assay CVs for the low and high quality control samples are 0.9% and 0.6%, respectively.  
Glucose  
Analysis of fasting and post glucose intake samples is performed enzymatically on a Roche 
Hitachi Modular P chemistry autoanalyzer. This instrument executes the glucose hexokinase 
method described by216-218 and recognized as the most specific method for the determination 
of glucose. Quality control samples with normal and high glucose levels are used for 
monitoring glucose assay performance. The inter-assay CV is <3%. Lyophilized samples at 
two different glucose concentrations are used to monitor possible analytical drift. 
Lipid Profile  
Measurements of total plasma cholesterol in plasma, cholesterol in the lipoprotein fractions 
and triglycerides are performed enzymatically on the Roche Modular P autoanalyzer using 
methods standardized to the Centers for Disease Control and Prevention Reference Methods. 
Determination of HDL-cholesterol is performed after precipitation of apo B-containing particles 
by dextran sulfate Mg2+. LDL-cholesterol is calculated by the Friedewald equation. This 
approach for measuring LDL-CH is clinically reliable if the measurements of total CH, HDL-CH 
and triglycerides are performed with a high level of accuracy and precision. However, the 

73 
 
 
Friedewald equation for the estimation of LDL-CH is inaccurate when triglycerides are >400 
mg/dl. In this case, a complete lipoprotein separation by ultracentrifugation which allows 
quantitation of the individual lipoprotein classes is performed using the Lipid Research Clinics 
Beta Quantification procedure.  
Quality control materials (BCL-Low, BCL-High (Biocell Laboratories) and L1-Medium (In-house 
prepared fresh frozen pool) are used at the beginning and at the end of each run.  
The inter-assay CVs are consistently <1.5% for total cholesterol and triglycerides and <2% for 
HDL cholesterol.  
Long-term Drift:  A large quantity of two lyophilized quality control materials was acquired from 
Bio Rad for lipids. Values for each analyte were assigned by analyzing the samples daily for at 
least two weeks to achieve a minimum of 50 values. The mean of all the values constitutes the 
target value for each analyte. These materials are stored at -70°C and analyzed monthly to 
monitor for analysis drift. Actions are taken if the values are consistently above or below the 2 
SD limit on two consecutive months.  
C-Reactive Protein  
 
Levels of C-reactive protein (CRP) in plasma are measured immunochemically on a 
nephelometer autoanalyzer (BNII). The reagents are obtained from Siemens Inc. This high 
sensitivity method is based on polystyrene particles coated with monoclonal antibodies specific 
to CRP which form immunocomplexes with CRP in plasma samples.The intensity of the 
scattered light in the nephelometer is directly proportional to the concentration of CRP which is 
determined versus dilutions of a standard of a known CRP concentration. The method is 
standardized against the IFCC/BCR/CAP reference preparation. 
Insulin  
The Insulin assay is a two site immuno-enzymometeric assay performed using Tosoh 2000 
auto-analyzer. The assay is calibrated to WHO IRP 66/304 standard. The assay has a 
sensitivity level of 0.5 uU/mL and the standard curve linearity is up to 330 uU/mL. A set of high, 
medium and low insulin level controls are included in each batch of samples to monitor assay 
performance. The inter assay CVs for Low, Medium and High insulin level controls are 2.8%, 
2.5% and 2.0% respectively. The assay has high specificity as cross- reactivity with Human C-
peptide, intact Proinsulin, split (32, 33) Proinsulin and Des (64,65) proinsulin is 0%, 2 %, 2.6% 
and 39.8 % respectively. A Reference Interval for apparently healthy donors has been 
established at <17.0 uU/mL. The laboratory has participated in external proficiency evaluation 
program by the College of American Pathologists (CAP). Additionally, the laboratory has 
participated in the ADA sponsored Insulin Standardization workshops in 2007 and 2011. In the 
2007 insulin standardization workshop this assay was reported as top performer with high 
sensitivity and specificity. Most recently, in 2011, ADA Insulin standard prepared and target 
level assigned by IDMS reference method was distributed to the laboratories. The ADA criteria 
of individual laboratory performance was set at up to 15.5% measurement bias from the 

74 
 
 
assigned target level. Using the current insulin assay our laboratory achieved a bias less than 
8.5%.  
Alanine Aminotransferase (ALT)  
This assay is performed on a Roche Double Modular P Analytics automated analyzer using 
Roche Diagnostics reagents. L-alanine reacts with alphaketoglutarate in the presence of ALT 
to form pyruvate and Lglutamate. NADH is then added to the pyruvate in the presence ofLDH 
to form L-lactate and NAD+. The rate of NADH oxidation to form NAD+ is directly proportional 
to the rate of pyruvate formation indicating ALT activity. The rate of decrease in absorbance at 
340nm due to the formation of NAD is directly proportional to the rate of pyruvate formation 
and proportional to the ALT activity of the sample. The normal reference ranges for adults are: 
17–67U/L (Male) and 13–50U/L (Female). 
 
9.1.3.  Site-Specific Mediators, Moderators and Secondary Outcomes. 
 
Background and Rationale.   Self-reported information will be collected from COPTR index 
children and other household members by obtaining responses to written or verbalized 
questions.  Although we refer to “questionnaires”, as discussed in the methods section below, 
several methods are used to collect these data, and only a minority of the data is collected 
through the use of paper questionnaires.  The information obtained is used to describe the 
study population or as a confounder, mediator, moderator or secondary outcome of 
intervention effects.   
 
As shown in our conceptual framework, our study will examine a comprehensive list of both 
mediators and moderators.  First, our theoretical framework assumes that our two family-
based interventions, SystemCHANGE and HealthyCHANGE will have an impact on BMI via 
two different sets of mediators – first, a set of cognitive mediators that are tied to the targeted 
approach of each intervention (systems thinking for SystemCHANGE, motivation for 
HealthyCHANGE) tat we hypothesize will influence the proximal outcomes of diet, physical 
activity, sleep and stress, which in turn (also mediators themselves) will impact  more distal, 
physiological outcomes (i.e., BMI, blood pressure, fitness levels, cardiovascular risk).  
Proposed cognitive mediators include: child’s self-efficacy, social support, motivation and 
family problem-solving, systems thinking, self-regulation.    
 
A moderating variable is defined as a variable that could influence the primary or secondary 
outcomes because the variable interacts with the intervention to change study outcomes.  In 
other words, the intervention affects people differently, depending on their status on the 
moderator variable. These variables are evaluated at the beginning and the end of the 
intervention, and in some cases as interim measurements.  
 
There is strong evidence identifying several behavioral, contextual, and environmental factors 
as critical underpinnings of the adolescent obesity70-81.  Family, school, peers, community, and 

75 
 
 
policy act together (superimposed on biological predisposition) to provide the environmental 
contexts that shape children’s energy intake and expenditure - and therefore together influence 
the development of obesity and its co-morbidities.  These factors are not only likely to have an 
independent impact on BMI outcomes, but also are likely to moderate the impact of the 
interventions themselves.. 
 
Our list of potential moderators have been carefully selected based on the literature, our own 
work and the psychometric properties of the measurements themselves.  These include: the 
family’s socioeconomic status and demographic characteristics, personal characteristics of the 
child, parent/guardian, and family (including physiological and psychosocial characteristics), 
the child’s physical and social environment (neighborhood, school, and family), and peer 
norms surrounding nutrition, physical activity and perceived environment.  We posit that these 
factors may moderate the impact of the interventions on outcomes, as well as interventions on 
the program-specific mediators Covariates deemed from the literature to be confounders also 
will be assessed.  
 
Objective.   The purpose is to describe the characteristics of participants, to determine possible 
mediators and moderators of intervention effects and to study secondary outcomes that are 
impacted by the intervention. 
 
Methods.  The demographic, household, mediators and moderators survey is administered to 
parents/primary caregivers of the participating child and/or to the participating child.  Table 9.2. 
summarizes the location where the questionnaire will be administered and administration 
format in each site.  To accommodate the sample being studied, we are administering the 
surveys in both English and Spanish  
 
The following table (Table 9.8.) outlines the list of site-specific mediators, moderators, 
covariates and self-reported secondary outcomes that will be considered in our study.   
 
Table 9.8.  Case Western Reserve University Site-Specific Mediators,  
Moderators and Secondary Outcomes* 
Construct 
Respondent 
# Questions 
Treatment Self-Regulation Questionnaire 
Child 
6 
Brief scale for sedentary equipment in the home  
Child 
9 
Brief scale for physical activity in the home  
Child 
14 
Active Where? Survey – Rules for TV   
Child 
8 
Parental Monitoring Scale 
Child 
6 
Social Support and Exercise Survey  
Child 
10 
Self-efficacy scale for physical activity barriers 
Child 
4 

76 
 
 
Modified Rosenberg Self-Esteem Inventory  
Child 
6 
Center for Epidemiological Studies Depression Scale for Children  
Child 
20 
Neighborhood environment walkability scale – Safety scales  
Child 
13 
Youth Risk Behavior Survey  physical activity  
Child 
3 
Modified activity questionnaire  
Child 
10 
Active Where? Survey – Active transportation to school  
Child 
2 
Active Where? Survey – Food scale  
Child 
18 
Active Where? Survey – Rules for eating 
Child 
12 
Child Food Security Survey  
Child 
9 
School wide food practices scale  
Child 
7 
Social support and eating habits survey 
Child 
20 
Children’s self-efficacy for eating habits survey 
Child 
15 
Modified -Youth Eating Disorder Examination Questionnaire  
Child 
3 
Family Ritual Questionnaire – dinnertime subscale  
Child 
7 
Sleep evaluation questionnaire (SEQ)  
Child 
10 
Adolescent sleep wake scale (ASWS)  
Child 
28 
Pediatric Daytime Sleepiness Scale 
Child 
8 
Perceived Stress Scale  
Child 
10 
Systems Thinking Scale  
Child 
16 
Index of Self-Regulation  
Child 
7 
Impact of weight on quality of life (IWQOL)  
Child 
27 
PACER Test 
Child 
1 
Brief scale for sedentary activity equipment in the home  
Parent 
9 
Brief scale for physical activity equipment in the home  
Parent 
14 
Active Where? Survey – Rules for TV  
Parent 
8 
Child Behavior Checklist – social problems subscale 
Parent 
7 
Center for Epidemiological Studies Depression Scale 
Parent 
20 
Family Assessment Device  
Parent 
12 
Neighborhood environment walkability scale – Safety scales  
Parent 
13 
Active Where? Survey – Active transportation to school  
Parent 
2 
Active Where? Survey – Rules for eating scale  
Parent 
12 

77 
 
 
The Child Feeding Questionnaire  
Parent 
31 
Obstructive Sleep Apnea screen 
Parent 
8 
Systems Thinking Scale  
Parent 
20 
The Stress Index for Parents of Adolescents  
Parent 
34 
Family Health History 
Parent 
20 
Maternal History 
Parent 
5 
Medical History 
Parent 
9 
*The Health Utilities Index (child, 40 items) is also under consideration by the OPCTR 
consortium for addressing cost-effectiveness. 
 
Site-Specific Secondary Outcomes 
 
In addition to the secondary outcomes outlined in the common measures section, we will also 
assess the following secondary (proximal) outcomes: 
 
Sedentary Behavior will be assessed primarily using 1-week accelerometer data at each 
evaluation point, as described, and supplemented by MAQ 221questions about TV, video, and 
leisure computer fine (expressed as hr/d). 
 
Sleep.  Quality and Quantity of sleep will be assessed with the Sleep Evaluation Questionnaire 
(SEQ)222; the Adolescent Sleep Wake Scale (ASWS)223 and the Pediatric Daytime Sleepiness 
Scale 224. 
  
Fitness Assessment.  A standard shuttle run test (in which the child runs between two 
markers) will be performed according to standard protocols138,152-154. 
 
9.2. Quality Control (common and site-specific) 
 
The overall goal of quality assurance is to assure complete, precise and accurate date.  This is 
accomplished through monitoring the quality of the data collected and training and certification 
of the staff who collect the measurements.  Biannually the RCU provides the DSMB Quality 
Assurance tables for the common measurements and site specific measurements. 
 
9.2.1.  Quality Control - Primary Outcome (BMI) and Other Anthropometric Measures 
 
Ten percent (10%) of the measurements (height and weight) that compose the primary 
outcome (BMI) and the other anthropometric measurements (waist circumference and triceps 
skinfold) are measured by two different data collectors.  Ideally one of the data collectors is a 
Master Trainer.  The method used to select the 10% sample is site specific and is incorporated 
into the site’s data management system to track who requires the second measurer. Duplicate 

78 
 
 
measures are recorded to confirm inter-rater reliability, but the first data collection staff’s 
measurements will be used in the analysis. To be acceptable, the absolute difference between 
the calculated values by the two data collectors must be less than 0.5 cm for height, 0.3 kg for 
body mass, 1 cm for waist, and no larger than 2 mm if the skinfold is less than 10 mm or 
greater than 10% if the skinfold is 10 mm or larger.  If a data collection staff’s agreement on a 
measurement (height, weight, waist circumference or skinfold) is outside this range in more 
than two out of ten individuals, then he/she must complete retraining.   
 
Range checks are built into the data management system to prevent the collection of 
erroneous data.  The 2003-2010 NHANES was used to determine age and gender-specific 
range checks for the anthropometric variables.  Range checks are set so that participants with 
extreme and erroneous values are brought to the attention of the data collection staff for 
scrutiny.   
 
The bounds for range checks in the baseline data collection vary by center since the 
anthropometric eligibility criteria for enrollment of index children vary.   
 
9.2.2.  Quality Control – Common Mediators, Moderators and Secondary Outcomes 
 
The demographic variables are collected via questionnaires along with additional mediator 
variables (e.g. food security, tv and media).  The survey collection, review and editing 
procedures are site specific.  The RCU monitors for missing and out of range values on the 
common questions across the Field Sites.  
 
Physical activity is measured by accelerometry.  Because activity levels change daily and the 
test retest relationships would be low, participants are not asked to wear the activity monitor 
twice for quality control.  In addition, an interview is not a good quality control check since it 
does not provide the necessary data for a comparison, and thus are not used for quality 
control.  The RCU monitors and reports the amount of data (e.g. the number of valid days, 
number of re-wears).  The valid wear time criteria (minimums) are 4 days (3 weekdays and 1 
weekend day) of at least 6 hours of awake time with 33% non-zero epochs per hour.   For 
some participants, accelerometer data for the 2 wears will be combined in order to meet the 
minimum wear time criteria.   
 
The dietary interviewer reviews and edits the 24-hour dietary recall as soon as possible after 
its administration.  During editing, special attention is paid to NDS-R Missing Foods, Priority 
Notes and all other Notes.  Full quality assurance must be conducted on at least 10% of 
recalls.  The quality assurance checks include ensuring information is entered correctly in 
header tab, meal information window, food tab and trailer tab. In the header tab the goal is to 
make sure information is filled in correctly (e.g. ID, Date of intake, Site ID).  The meal 
information window should have meals in order by time and the eating and activity codes 
entered correctly.  The quality assurance checks in the food tab include checking that foods 
entered correctly, amounts match code, missing foods and priority notes are resolved.  Recalls 

79 
 
 
that have issues that need to be resolved are put into the FIX project. All data must be cleaned 
and missing foods, or priority notes must be resolved before the output file is run and sent to 
the RCU on a quarterly basis.  All missing foods are discussed at diet interviewer staff 
meetings.   There will be quarterly reviews of data entry issues and shared user recipes to 
standardize the data entry process across all sites. 
 
In SAS or other statistical package a quality assurance report is run to generate for each 
record total energy, percent kilocalories from fat, fruit servings, vegetable servings and grams 
of fluid.  Ranges are set for school aged children and preschool aged children.  Records with 
values beyond the cutoff points below are printed and checked.  
 
School Aged Samples       Preschool Samples 
Total Energy                      <500; >2500                       <250; >1200 
% kcal from fat                   <25%; >45%                      <25%; >45% 
Fruit Servings 
>3 
 
     >2 
Vegetable Servings            >3                                      >2 
Grams of Fluid                   <300; >2000                      <200; >1500 
 
To protect against erroneous blood pressure and pulse measurements, computer entered data 
can be deleted and reentered as needed.  Since the blood pressure and pulse measurement 
are collected using an automated device, end digit preference (e.g. 0 or 5) should not be an 
issue.  Also, the OMRON blood pressure device does not require calibration.  The RCU will 
calculate the correlations between the 2nd and 3rd blood pressure and pulse measurements 
within an individual.   
 
All biomedical samples are sent to the Northwest Lipid Metabolism and Diabetes Research 
Laboratories, University of Washington (Seattle, WA, USA) for analysis.    The laboratory 
participates in the Center for Disease Control and Prevention (CDC) lipids standardization 
program and is the Central Lab for several NIH sponsored studies.  Standard procedures are 
implemented to ensure high quality data analysis and monitor for long term drift.  See section 
9.1.3.4. for specific quality assurance details for each lab measure. 
 
9.2.3.  Quality Control - Site-Specific Mediators, Moderators and Secondary Outcomes   
 
The site specific mediators, moderators and potential covariates/confounders that are 
highlighted in our conceptual framework are, for the most part, collected via audio-supported 
electronic data collection, where respondents have the options to read the questions or have 
them “read” to them. Audio files for the surveys have been prerecorded and attached to each 
corresponding question.  Participants may use this feature throughout the entire survey, or on 
specific questions they might not understand or having difficulty reading.  Those who prefer to 
have the questions read to them are given a set of reusable headphones.  The headphones 
are sanitized after each use. 
  

80 
 
 
The nature of the electronic-based survey allows researchers to program a variety of additional 
quality control measures.  Each survey question required a participant to provide an answer 
before moving on to the next question.  If the participant feels uncomfortable answering or 
refuses to answer a question, they are given the choice, “I prefer not to answer”.  
  
Skip patterns are employed throughout the surveys to eliminate the confusion and/or burden of 
being asked questions not applicable to the participant.  In the rare event that internet 
connectivity is an issue, all survey data will be collected through paper-and-pencil surveys.  
Designated members of the research staff will be responsible for entering survey data directly 
into REDCap once internet connectivity becomes a non-issue. 
  
Triggers have also been employed in various sections of the survey to notify study staff in the 
event that a participant’s depression score, binge eating score, or sleep score require follow-up 
from a clinician.  If a child or parent reaches a clinical threshold for depression, binge eating or 
sleep, an email will be sent to a member of the research staff indicating that a threshold has 
been reached by the participant.  No names or any identifiable information will ever be 
included in the email, only that a threshold was reached and follow-up with a clinician is 
required. 
  
At the end of each data collection day results from the participant surveys will be downloaded 
to a secure server, quickly reviewed and then imported into REDCap.  Before REDCap 
accepts the import, data quality checks are enacted to ensure that value ranges, variables 
names, etc match the database formatting and are linked to the correct participant.  If the 
import passes the data quality check, overview of all of the data being submitted is displayed 
and confirmation is required from the Data Manager.  If the data quality check fails, a summary 
of what went wrong is displayed so that appropriate actions can be taken to address the 
problem.  This process will eliminate possible data transcription error, improving data quality. 
  
In the rare event that internet connectivity is an issue, all survey data will be collected through 
paper-and-pencil surveys.  Designated members of the research staff will be responsible for 
entering survey data directly into the electronic survey once internet connectivity becomes a 
non-issue.  Survey responses entered by a member of the research staff will be verified by 
another member of the research staff to decrease the likelihood of transcription error. 
  
Other data not obtained by a survey, such as interviews and lab results, will be directly entered 
into REDCap.  Much like the participant surveys, REDCap is programmed with a variety of 
data quality checks.  All fields require a response and skip patterns prevent unnecessary 
questions.  Data validations are used to ensure data is entered in the correct format, such as 
dates and times and data ranges are used to flag abnormal data at the time of entry. 
 
REDCap also provides additional data quality protections that will be used throughout the 
duration of the study.  To ensure that REDCap users have access only to data and information 
that they are supposed to have within the application, user privileges are utilized within the 

81 
 
 
system. Each user is assigned their own account, and their user account will only have access 
to REDCap databases assigned by the data manager or that they themselves have created for 
a different study in which they are involved.  
 
User privileges are also granular on the project level and can be modified within any of the 
study database by the data manager. The data manager will automatically be given full rights 
to everything within each database and is responsible for granting other members of the 
research staff access to the project and assigned each user a set of privileges based on their 
role in the study. Within each study database, there are user controls to limit access to various 
functionality and modules, such as being able to export data, to enter data, to add or modify 
database fields or survey questions, to build or run reports, to modify user privileges, to view 
the logging records, etc. 
 
The creation of data access groups to help segregate users and the data they enter.  
Research staff will be placed into data access groups according to their role in the study and 
will only be able to access records created by someone within the same group. 
  
REDCap also maintains a built-in audit trail that logs all user activity and all pages viewed by 
every user, including contextual information (e.g. the project or record being accessed).  The 
Logging page allows such users to view or export the entire audit trail for that project, and also 
to filter the audit trail in various ways based upon the type of activity and/or user. The built-in 
audit trail in REDCap allows administrators to be able to determine all the activity and all the 
data viewed or modified by any given user. 
 
9.3. Measurement Schedule 
 
Data collection will occur at  four time points: baseline (time 0), 1 year  after the intervention 
begins,  2 years  after the intervention begins, and 3 years after the intervention begins.   
 
Visits are planned to be conducted at a Clinical Research Unit (UH Dahms Clinical Research 
Unit (DCRU) or MetroHealth Medical Center  (CRU). An unlikely event may result in data 
collection occurring over the phone, in the home or community if family is unable to make it to 
the CRU locations or after the family leaves the visit some data is found to be missing.  
Meetings have been conducted with staff of both CRUs regarding the overall project.   Data will 
be collected by the research study team, assisted by CRU staff (nurses, dietitian, diet techs).  
All personnel collecting data will be CREC-certified and, for specific anthropometric measures 
(height, weight, skin-fold thickness, waist circumference), certified as proficient by the COPTR 
Coordinating Center (UNC).    All data will be collected with parent/guardian and participant in 
private.  Questionnaire and interview-based data will be obtained by private interview and, for 
some questionnaires, by audio-assisted survey software (Qualtrex).  Data will be entered 
directly into a laptop or iPad225. 
 
 

82 
 
 
10. PARTICIPANT SAFETY AND ADVERSE EVENTS MONITORING 
 
10.1. Potential Risks and Protection against Risks 
 
10.1.1.  Potential Risks 
 
Potential risks include loss of privacy and confidentiality, but we will take great care to maintain 
privacy and confidentiality.  There may be pain/discomfort or bruising and a small chance of 
infection with venipuncture, but we will offer LMX or EMLA cream and venipuncture is 
performed by skilled nurses.  There is the potential for stigmatization due to weight status; 
however, measurements are taken in private and all results are reported privately in a sensitive 
and culturally appropriate manner.  If baseline questionnaires indicate symptoms suggestive of 
depression or suicidal ideation or an eating disorder, the results will be reviewed with Dr. 
Landis, Ph.D. (co-investigator, licensed clinical psychologist, #5331) who will consult with the 
youth and/or parent/guardian to determine whether the youth or parent/guardian is in need of a 
referral for further evaluation and treatment.  Potential risks arising during the study could 
involve development of new co-morbidities associated with obesity itself and/or worsening of 
elevated blood pressure (EBP).  These are discussed under Safety Monitoring Plan below  
 
10.1.2. Protections Against Risk 
 
Children with stage 1 hypertension (found on CMSD or Charter School screening) who would 
otherwise meet inclusion criteria are potentially eligible to enroll in study if an evaluation shows 
that the hypertension is essential/primary in origin and is not associated with target organ 
damage (Left ventricular hypertrophy).Children with secondary hypertension and/or target 
organ damage require different management including antihypertensive drug therapy.  
Families of children found to have stage 1 hypertension at school screening will be advised to 
schedule an appointment with a hypertension physician at UH Rainbow, MHMC, or The 
Cleveland Clinic Foundation. At these appointments, history, physical examination, urinalysis, 
echocardiogram, and renal ultrasound will be performed, as recommended in standard medical 
practice39. These evaluations would not be paid through the study as they represent standard 
of care for children with confirmed hypertension and are regularly covered by commercial 
insurance. If the child’s evaluation suggests essential/primary hypertension, the child will be 
eligible and proceed with the CRU visit as described. The child would still need to have a renal 
function panel to fully ensure normal renal function and electrolyte balance; this is unlikely to 
be abnormal if all other tests are normal and will be drawn as part of baseline visit to avoid an 
extra blood draw. The consent will specify that for such children indication of renal dysfunction 
on baseline blood tests will preclude participation (see below). 
 
Results of height, weight, BMI status, BP, and lab tests that screen for comorbidities / 
cardiovascular risk factors will be reported to families by letter (and families will be called if 
results exceed thresholds defined. 
 

83 
 
 
The consent form will specify that if the screening tests indicate diabetes (FBG > 126 mg/dl) or, 
renal disease [elevated BUN, creatinine]), those children may not be eligible for the full study 
since other specific medications may be needed; however, with the family’s permission, the 
primary care physician will be notified and referral to a specialist offered.  If the tests show 
other abnormalities, impaired glucose tolerance (fasting glucose >110mg/dl), liver function 
tests 2 or more times normal, cholesterol >200mg/dl, triglycerides >135mg/dl, LDL-C 
>130mg/dl, HDL-C <35mg/dl), the family will be informed by letter and they will be referred to 
their primary care physician so that evaluation can be arranged can be arranged; however, 
these children remain eligible for the study.  If they do not have a primary physician, we will 
provide a list of potential physicians.  
  
Each study participant will be assigned a unique identifier for tracking purposes, which will be 
stored in a locked cabinet in locked office.  The code which will match study participant to the 
unique identifier will be stored in a locked file cabinet in a secured room.  Access to the code 
will be restricted to authorized study personnel identified (Study Coordinators, PI’s).  
Participant tracking information will be stored on a password database.  Data will be entered 
and stored in a secure computer database.  Original paper forms and all paper copies will be 
stored in locked cabinets (separate from the locked cabinet in which codes matching study 
participants to identifiers are kept) in a secured room.  Access to the computer and backup 
copies of the data will be controlled so that unauthorized use of the computer, destruction of 
data, or breach of confidentiality will be prevented.  Staff will be instructed to avoid discussing 
any study subject with persons who are not part of the research team.   
 
10.2. Potential Benefits 
 
The study may benefit participants by increasing their knowledge of healthy lifestyle, and 
potentially increasing their fitness and general health, and reducing their weight.  If successful, 
the program may improve family interaction and child self-efficacy.  In addition, children found 
to have a co-morbidity will be referred for medical attention.    Eligible families who are 
interested and want to take part but cannot, as enrollment is completed, will receive 
informational material and will be informed about community resources to achieve a healthy 
lifestyle.    The potential benefits to participants’ families are also increased knowledge about 
healthy lifestyle.   
 
10.3. Safety Monitoring Plan 
 
10.3.1. Level of risk 
 
We believe that the risks associated with participation in this protocol fall in the low risk 
classification. The procedures to be performed include history/physical examination, 
questionnaires, ultrasound, exercise, and venipuncture. 
 
10.3.2. Mechanism of safety monitoring 

84 
 
 
 
We have developed a set of action items to prompt follow up action in order to ensure the 
safety of participants and to optimize their medical care. While the interventions in this study 
are not invasive, we believe that it is important and ethical to ensure that an abnormal physical 
finding, lab value or diagnostic test is appropriately followed up. These will be reviewed by the 
PIs or their authorized designee after each visit.  
 
If the standard questionnaires completed at any of the visits  suggest depression, suicidal 
ideation, or eating disorder, the results will be reviewed with Dr. Landis, Ph.D. (co-investigator, 
licensed clinical psychologist, #5331)) who will consult with the youth and/or parent/guardian to 
determine whether the youth or parent/guardian is in need of a referral for further evaluation 
and treatment.  If baseline assessment suggests sleep apnea 164,177, the child will be 
recommended for a sleep study and, depending on the result, may be suggested to their 
primary physician to see ENT or Sleep clinic.  If baseline tests indicate an abnormality (e.g. 
liver function tests more than 2 x normal; elevated lipids), the child will be referred to their 
primary care physician (or, if physician and/or parent prefer, to an appropriate specialist), 
Response to non-emergent treatment and disease-related events will be coordinated and 
mediated through the participant’s primary care physician. If the participant does not have a 
primary care physician, every effort will be made to facilitate care within our healthcare 
systems. If during the course of the study, participants show evidence to suggest a new or 
worsening complication of obesity (e.g., polyuria/polydipsia), appropriate tests will be 
performed (e.g. glucose) and treatment instituted if needed. If a child with normal BP at 
baseline develops elevated BP during the study, the child will have 2 repeat BP assessments 
within 2 weeks; It these BP measurements confirm stage 1 or 2 hypertension, Dr. Vogt (co-I) 
will arrange for prompt evaluation with a Pediatric Hypertension specialist. Children with Stage 
1 essential/primary hypertension without target organ damage who are participating in the 
study will be followed regularly by the pediatric hypertension specialist who did their initial 
evaluation prior to study enrollment. If at any point after baseline, the child develops Stage 2 
hypertension, further evaluation and drug therapy will be initiated by the hypertension 
specialist. Participants started n antihypertensive medications will be able to continue in the 
study so as to continue to observe their BMIs and other outcomes.  
 
10.3.3. Reporting of Adverse Events. 
 
The reporting of adverse events experienced by study participants meets the important 
purpose of providing the mechanism for reporting the occurrence and severity of adverse 
events to the study group and the NIH.   
 
Definition.  An adverse event is any untoward medical occurrence experienced by a study 
subject. An event can be any unfavorable and unintended sign, symptom, laboratory 
abnormality, or disease associated with study participation.  
 

85 
 
 
Classification.  Monitoring of adverse events requires that they be classified as to seriousness, 
expectedness, and potential relationship to the study intervention, which then drives the 
reporting process. In the COPTR studies, adverse events should be rare, and monitoring 
should be commensurate with risk, which is minimal. Adverse events will be recorded for the 
duration of participation in the study. 
 
A serious adverse event (SAE) is one that: (a) Results in death, (b) Is life-threatening, (c) 
Requires inpatient hospitalization or prolongation of existing hospitalization, (d) Results in 
persistent or significant disability/incapacity, or (e) Is a congenital anomaly/birth defect in the 
offspring of a participating parent/adult or teen. 
 
An event definitely, probably, or possibly related to the study procedure is one that follows a 
reasonable temporal sequence from the time of study participation, and cannot be reasonably 
explained by other factors such as the subject’s clinical state, therapeutic interventions, or 
concomitant drugs administered to the subject. 
 
Data collection procedures for adverse events.  Events are recorded by the field center staff, 
including the date and time (if relevant) of occurrence, description, severity, 
frequency/duration, outcome/resolution, potential relationship to study participation, and action 
taken with respect to study participation, as specified in the data elements forms.   For those 
participants in the intervention groups, they will be asked at every visit if they have been 
hospitalized since the last session. 
 
Reporting procedures for Serious Adverse Events (SAEs).  If classified as serious, 
unexpected, and possibly, probably or definitely related to study participation, reports will be 
forwarded electronically to the RCU within 4 working days of learning of the event. The RCU 
will report any such events to the NHLBI and the DSMB Chair as soon as possible, but no later 
than 7 calendar days after first knowledge of the event, followed by a complete report within 15 
calendar days.  
 
Reporting procedures for events not classified as serious.  If not classified as serious, 
unexpected, and possibly, probably or definitely related to study participation, reports will be 
reported annually or twice-annually to the RCU according to the meeting schedule of the 
DSMB. The RCU will report these events to NIH and the DSMB. 
 
Adverse Events (AEs) aka non-serious adverse events (Non-SAEs).  If classified as 
unexpected, and possibly, probably or definitely related to study participation, will be reported 
annually or twice-annually to the RCU according to the meeting schedule of the DSMB. The 
RCU will report these events to NIH and the DSMB.  
 
The site investigators or designees will report all adverse events to the local IRB according to 
local IRB policies. 
 

86 
 
 
Serious Adverse Events and Adverse Events data elements forms. SAEs and AEs will be 
collected systematically at all regularly scheduled data collection visits.  SAEs and AEs will be 
queried at the end of the data collection visit (preferably) but at least after measurement of 
height and weight, to prevent unnecessary unmasking of data collectors at that visit. 
 
The accompanying forms will be used for querying and recording SAEs and AEs. Some sites 
may collect this information using paper-and-pencil methods and others may use direct 
computer data entry. All will be via interview (not self-administered).  For each participant, 
SAEs will be queried first, followed by queries for AEs. 
 
The same forms (data elements) will be used for adult and child SAEs and very similar data 
elements will be used for collection of AEs. 
 
SAEs and AEs reported between scheduled data collection visits will be designated as such 
(see item on form) and use the same format.  However, these will be reported separately from 
those collected at regularly scheduled data collection visits, to minimize the potentially 
misleading results from having differing opportunities for reports in different intervention groups 
(e.g., more contact with treatment group participants, and thus more opportunities to learn of 
adverse events). 
 
As noted on the forms, Principal Investigators or their designee(s), and not data collectors, 
shall make determinations regarding expectedness and relatedness of SAEs and AEs to study 
participation, at the time they are identified and reported. These will be reported to the DSMB 
and the DSMB may also make their own determinations at the time of their review. 
 
10.4. Informed Consent Documents  
 
10.4.1. Description of the informed consent process 
 
Families who are interested in participating and appear eligible based on pre-screening will be 
scheduled for a baseline visit in the CRU at which time the study will be re-explained and the 
consent and assent forms for participation signed.  Members of the study team who are 
certified in Human Subject Protection will obtain informed consent for the study.  The research 
protocol, risks and potential benefits will be discussed with the parent/guardian and youth 
privately.  They will have time to consider participation in the research study and to have their 
questions fully answered.  The consent and assent forms (attached) will indicate that 
randomization and participation is entirely voluntary and that the family can withdraw at any 
time.   
 
10.4.2.  Informed Consent Documents 
 
See APPENDIX F  for Informed Consent documents  
 

87 
 
 
11. STUDY DESIGN, STATISTICAL CONSIDERATION AND ANALYSIS PLAN 
 
11.1 Study Design 
 
IMPACT is an individually randomized group trial with three study groups (SystemCHANGE 
[SC], HealthyCHANGE [HC], and active education-only control.)   Subjects (n = 360 patients 
and their families) will be randomized equally to these three study groups with half of the 
patients entering in Project Year 3 and the remaining half in Project Year 4. Outcome 
measures will be assessed at baseline, and then at approximately 12, 24 and 36 months after 
randomization.  
 
11.2 Primary Research Question and Hypothesis 
 
Our primary analysis assesses the value of our interventions (SystemCHANGE [SC] and 
HealthyCHANGE [HC]) as compared to education-only control (Tools4CHANGE) in terms of 
reducing the BMI of overweight/obese urban youth, across a three-year study window.  Our 
hypothesis is that both SC and HC will have greater impact than education alone on BMI.  
 
11.3 Primary Outcome 
 
Our primary outcome is a derived outcome - specifically the changes (slopes) in BMI alone 
over the three-year window, with outcomes multiply imputed for patients without BMI values 
post-baseline to permit a true "intent to treat" comparison. Our primary analysis compares HC 
to Control and SC to Control, collapsed across levels of the school-community enrichment 
exposure. 
 
11.4 Primary Analysis 
 
11.4.1. Statistical Model and Approach 
 
The primary analysis will be an intent-to-treat comparison across all 360 subjects providing 
baseline BMI and randomized to a study arm (120 subjects in each of SC, HC and control.) 
BMI values will be measured at baseline, 12, 24 and 36 months, and our primary outcome is a 
derived value - specifically the annualized slope in BMI across the study period.  
 
Our primary analysis addresses the impact of both SC and HC as compared to Control 
patients in terms of mean BMI reduction. The statistical model for our primary outcome (BMI 
slope for subject j) follows. 
 
 
 

88 
 
 
across subjects j = 1, 2, ..., 360. Using this model, we test  
 using an 
appropriate F test with two degrees of freedom for our primary analysis. Note that we will 
account for (what we anticipate to be modest) clustering within intervention small groups (n ≤ 
12 students per small group) and within schools (n = 7.2 students per school on average) 
through modeling the small groups and schools as levels of nested random effects in our 
primary analysis. 
 
All other planned comparisons, including comparisons of the SC and HC groups to each other 
(see Section 11.8), comparisons of the enriched vs. non-enriched school-community 
environments (see Section 11.6), and the interaction of our interventions with enrichment are 
not primary, and are thus described later in Section 11. 
 
11.4.2. Assumptions with Justification 
 
Anticipated Effects.   We anticipate a non-linear effect of our interventions over time, as shown 
at right. However, our primary analysis 
focuses on changes over time, 
expressed in the form of linear 
regression slopes, because our ability to 
estimate non-linear relationships with 
baseline and three follow-up 
assessments is weak. Our primary 
analysis will therefore be somewhat 
conservative in assuming a linear change 
over the three year period. Note that as 
part of our secondary analyses, we will 
consider the impact of this decision – 
fitting models that look at comparisons 
limited to particular spans of time, in particular, fitting slopes that use only the data from 
baseline and 12, then 24, then 36 months.  
 
Control Group.  We anticipate an approximately linear relationship with a positive (increasing) 
slope between BMI and time for our control group. The strength of the evidence to support an 
increasing relationship in overweight and obese subjects as they move from age 11 to age 14 
is quite strong across both sexes, in fact well-established.  
 
The strength of the evidence to support an assumption of no substantial non-linear relationship 
is moderate – clearly the patterns observed in somewhat related previous cohorts (for 
instance, the control patients in Savoye et al226 and in Savoye, et al227 have not been 
described as substantially non-linear, and analyses have been conducted for these studies 
assuming linearity.  
 

89 
 
 
We expect the slope in our control group to be approximately +0.8 kg/m2 per year, based in 
part on the results observed in Savoye 227 (24 month control group change from baseline of 1.9 
kg/m2), and on a careful examination of slopes in CDC percentiles, which show a similar result. 
Examining the confidence intervals at various time points (6, 12 and 24 months) provided in 
Savoye 2011 suggests a standard deviation of approximately 0.4 kg/m2 based on the 12 
month data. Boys in our sample will have a BMI of at least 20.2 at study entry, while girls will 
have a BMI of at least 20.8 (85th percentile or higher.) From CDC age-percentile data (modified 
10/16/2000) we would expect the following distribution at 11 years old: 
 
 
 
 
 
 
This implies that our baseline sample (assuming equal numbers of boys and girls) would likely 
have a mean between 22 and 23, with a standard deviation near 2. At 3 years, we thus 
anticipate a mean BMI in our control group near 25 (on the basis of our anticipated increase in 
BMI over three years) with a somewhat larger standard deviation – perhaps between 2.5 and 3 
kg/m2. A review of our pilot data within the COPTR project suggests nothing to invalidate our 
assumptions here, although after 4 months and a small pilot sample, it is difficult to evaluate 
the magnitude of change, we continue to believe that the control group will, on average, show 
increases in BMI close to that which we have assumed.  
 
Treatment Effects.  We expect a non-linear shape to the association of BMI with time in our 
treatment groups, with a larger effect at the start of the study (especially in year 1) and some 
reduction in the size of this effect (as compared to baseline) in years 2 and 3. We anticipate a 
decline in BMI of about 1.8 kg/m2 in our HC and SC intervention groups in year 1. In years 2 
and 3, we anticipate a leveling off to a more modest decline or perhaps a slight rise (we 
assume a flat linear relationship in the second two years in what follows.) The evidence to 
support an expectation of a non-linear effect, leveling off after year 1, is modest. The Savoye 
et al study227, for instance, saw a substantial reduction in the size of the observed effect after 
the most intensive part of the treatment was completed. We have seen similar results in our 
studies among adults. 
 
We anticipate a decline in BMI of about 1.8 kg/m2 in our HC and SC intervention groups in 
year 1. In years 2 and 3, we anticipate a leveling off – while we would be happy to simply hold 
the gains in BMI in this period, we expect a small rise, with a smaller slope than will be 
observed over this time in the control periods. We expect the lowest BMIs to be observed at 
the end of year 1 – roughly age 12. We anticipate a mean BMI near 21 for our HC and SC 
patients at the three year time point, with a larger standard deviation than in our control group 
– perhaps 4 kg/m2. 
 
Table 11.1.  Expected Distribution of 85th percentile or 
higher among baseline boys and girls 
11 year old 
85th 90th 95th 
97th 
Boys 
20.2 21.2 23.2 
24.8 
Girls 
20.8 22.0 24.2 
25.8 

90 
 
 
While we expect the largest effect to occur in the first year, the trend towards rising BMIs in the 
control group suggests that the largest difference in raw BMI (not change in BMI) between 
groups will be at 36 months. Again, a review of our pilot COPTR data suggests nothing to 
invalidate our assumptions, although given the small pilot size, we did not focus on the 
magnitude of loss in the experimental group after just 4 months. 
 
11.4.2. Missing Data 
 
For our primary analysis, we assume missingness at random for the purposes of multiply 
imputing annualized slope values for those patients who do not have a BMI value recorded 
after baseline, incorporating the nested groups (small delivery groups for the intervention as 
well as the student's school) as random effects in our imputation model. We intend to complete 
imputations for primary analysis by directly imputing the derived outcomes (the slopes) and, 
then, in secondary analyses (see Section 11.8), imputing the individual values at missing time 
points, then deriving the slopes. We anticipate that this distinction will have little impact in this 
case. 
 
11.5. Detectable Difference, Sample Size and Power 
 
Our primary analysis involves a two-tailed (α = 0.05) comparison of SC vs Control and HC vs 
Control using an F test with two degrees of freedom and the linear model in Section 11.4.1.  
 
In our sample size calculations, we anticipate a modest design effect of 1.25. This modest 
design effect is reasonable, given the small number of subjects (≤12) in each of the 
interventional study groups, the small number of subjects (average = 7.2) within each baseline 
school-community environment and because we anticipate only mild clustering effects on BMI 
slope within these groupings.  
 
We based our initial assessment of a minimum clinically meaningful effect size on our review 
of the literature, and our prior work. Our expectations for average BMI results across 
participants within each study group are summarized in the table below, which matches the 
trajectories shown in Figure 11.1. 
 
 
Table 11.2.  Expectations for Average BMI Results  
Group 
Baseline 
12M 
24M 
36M 
Annualized BMI Slope 
Control 
22.5 
23.17 
23.83 
24.5 
0.67 
HC 
22.5 
20.8 
20.9 
21.0 
-0.44 
SC 
22.5 
20.8 
20.9 
21.0 
-0.44 
 
Such an effect would naturally be quite large if observed across the trial, and so instead we 
selected our sample size to provide sufficient power to detect a smaller effect. Specifically, we 
identify a mild-to-moderate effect size for our two degree of freedom comparison, 

91 
 
 
corresponding to a Cohen's f2 value of 0.065, in comparing either HC (or SC) to education-only 
controls in terms of our primary outcome (BMI slope.) A Cohen’s f2 value of 0.065 corresponds 
to the effect size observed in a linear model for BMI slope using group assignment as predictor 
that accounts for just over 7% (R2 = 0.061) of the variation in BMI slopes, after accounting for 
baseline BMI. Note that Cohen's f2 is R2/(1-R2), and that Cohen identified medium effect sizes 
at 0.15 and small effect sizes at 0.02, so our effect of 0.065 is appropriately described as mild-
to-moderate.  
 
As noted, we then conservatively assume 20% attrition across our 360 subjects across the 36 
month study window, where such attrition pertains to subjects who will be completely lost to 
follow-up (in terms of outcome measurement) after baseline, i.e. those patients whose BMI 
slope will need to be imputed using only baseline BMI information. Our intent to treat analysis 
will use imputation of the BMI slopes across all 360 subjects. To account for this attrition in our 
power calculation, we further dilute our anticipated effect size (again conservatively) by a full 
20%, from f2 = 0.065 down to f2 = 0.052, which corresponds to a linear model with incremental 
R2 = 0.05 attributable to group assignment, although we expect the actual impact of imputation 
to be substantially smaller than this. 
 
Our sample includes 360 subjects, with 120 enrolled in each of our three intervention arms. 
We next describe the effective sample size after accounting for these rather conservative 
estimates of attrition and clustering. All enrolled patients (120 per arm) will have outcome 
information (imputed or not) past baseline. Applying a design effect of 1.25 yields an effective 
sample size which may be as small as 96 patients per intervention arm. So, assuming an 
effective sample size of 96 patients per intervention arm, we describe two illustrative 
calculations related to power concerns.  
 
First, we performed calculations based on a linear model and ANOVA-style F test (with 2 and 
285 degrees of freedom - based on our effective sample size of 96 subjects per study group) 
and a two-tailed α = 0.05 significance level to compare HC to control and SC to control, 
assuming a modest effect size diluted 20% by imputation so that our Cohen’s f2 = 0.052.  
 
Using the pwr library in the R statistical software language, we conclude that an effective 
sample size of 288 subjects - 96 per arm - yields just over 94% power to detect an effect of 
size Cohen f2 = 0.052, which corresponds to an incremental R2 of approximately 5% for the 
joint effect of our interventions as compared to control on BMI slope, after adjusting for 
baseline BMI, accounting for 20% loss of information due to missingness, as accounted for by 
imputation. 
 
With 90% power, an F test based on our effective sample size could detect an effect as small 
as that represented by a Cohen f2 of 0.044, corresponding to an incremental R2 for the 
intervention of 4.2%. With 80% power, this test could account for Cohen f2 as small as 0.034, 
which corresponds to an incremental R2 of 3.3%, and so this is consistent with our ability to 
detect mild-to-moderate effect sizes with our sample size. 

92 
 
 
 
In a perhaps more familiar and simpler "worst case" calculation, an independent-samples t test 
restricted to our smallest effective sample size of 96 patients in any two of the intervention 
arms (say, HC and control) has 93% power to detect a difference (α = 0.05, two-tailed) in 
mean slope corresponding to an effect size of Cohen's d = 0.50. Again, we believe this result, 
though acceptable, clearly understates our true power, since it assumes our worst case 
scenario regarding clustering will occur, and that the incorporation of BMI at baseline data as a 
covariate will not aid in our assessment of the intervention. 
 
11.6. Analysis for Possible Effect Modifiers 
 
11.6.1. Studying Enrichment Exposure 
 
In studying school-community enrichment's effect on BMI and its impact (via interaction 
effects) on our conclusions with regard to our interventions, we plan additional analyses which 
are only briefly sketched here. The main complicating factor is potential confounding, due to 
the fact that while children within each school will be randomized to each intervention, the 
environments themselves are assigned (without randomization) at the school level.  This 
makes the exposure assessment part of an observational study. 
 
As a means of accounting for this potential exposure selection, we will use propensity scores 
to design the observational study. Specifically, we will follow the approach of Rubin228 and 
Rosenbaum229,230 by estimating a propensity score for enrichment across all patients, using 
available covariates. Next, we will compare the distributions of propensity scores across the 
two enrichment exposures, within and across intervention arms, without using outcome 
information. Should substantial selection bias be present, unadjusted regression models for 
our outcomes would be inappropriate, and we will apply propensity score weighting and/or 
matching to adjust comparisons until we obtain exposure groups that are appropriate for fair 
comparisons via regression analysis. Weighting approaches are likely to be more useful in this 
setting given the relatively modest sample sizes (180 patients in each enrichment group.)  
 
Once we have either verified that the enriched and unenriched groups are comparable in terms 
of baseline covariates or made them comparable via propensity weighting or matching, will we 
then fit linear models to account for both intervention (operationalized as SC/HC vs. Education 
to improve power) and exposure (Enriched/Not) effects and their interaction on our derived 
primary outcome, followed by our secondary outcomes.  In these analyses, we will again 
account for missing data via multiple imputation, and clustering via modeling the small groups 
and schools as levels of nested random effects, and, in case exposure selection pressures not 
accounted for by our propensity scores remain a concern, we will complete formal sensitivity 
analyses (Rosenbaum 229,230) to assess the necessary amount of hidden bias required to 
invalidate our conclusions. 
 
 

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11.7. Analysis for Possible Effect Mediators 
 
AS shown in our conceptual model of the study (Figure 7.1) and in our table of moderators and 
mediators (Table 9.8.), we have conceptualized and will be obtaining measures of several 
possible mediating variables. Our analysis of effect mediators is currently under development. 
This work will continue as we move toward the completion of the main study under the 
guidance of the COPTR Mediation and Moderation Team, at which point these analyses will be 
further refined.  
 
11.8. Secondary Hypotheses and Analyses 
 
If significant, the primary comparison described in Section 11.4.1 will be followed (in secondary 
analyses) by one degree-of-freedom pre-planned comparisons of HC to Control and SC to 
Control, adjusting for multiple comparisons. In further analyses, analogous models will be fit to: 
[1] compare HC to SC directly, [2] incorporate additional covariates into our comparisons for 
purposes of adjustment and [3] describe the impact of our interventions on the slope of blood 
pressure and other outcomes. These models form our analytic framework for questions related 
to the comparative effectiveness of our interventions, collapsed across enrichment exposure.  
 
The simple intervention model described in Section 11.4.1 does not permit the effect of the 
interventions to vary substantially based on baseline levels of BMI. This assumption seems 
unlikely, and so we will expand our analytic structure using the following model: 
 
 
 
across subjects j = 1, 2, ..., 360, and where the interaction terms permit differential effects on 
BMI slope for each intervention, depending on baseline BMI.  We will include baseline BMI 
elements as described above in all primary analyses, and investigate the impact of this 
decision (and also consider the inclusion of other covariates) in secondary analyses to assess 
the stability and sensitivity of our conclusions.  
 
While we anticipate a non-linear effect of our interventions over time, as shown in Section 
11.4.2, our primary analysis focuses on changes over time, expressed in the form of linear 
regression slopes, because our ability to estimate non-linear relationships with baseline and 
three follow-up assessments is weak. In secondary analyses, we will consider the impact of 
this decision – fitting models that look at comparisons limited to particular spans of time, in 
particular, after 12 months, then at 24 and finally at 36 months without inclusion of intermediate 
values.  
 
In keeping with the broader plans across COPTR sites, we will need to thoroughly investigate 
the properties of all fitted models. As at other sites, this will involve the usual diagnostic 

94 
 
 
approaches looking at predicted values, residual plots, and so forth. We will also adopt the 
simulation approach to model-checking recommended by Gelman and Hill231 where we use the 
fitted model to simulate new outcomes and then compare these results to what we have 
observed. 
 
Secondary outcomes of special interest include changes in blood pressure (for which 
analogous approaches to those taken for BMI change will apply), and a major secondary 
analysis will assess the potential additive impact on BMI and BP changes achieved by 
exposure to an enriched school-based intervention (We Run This City) which will be observed 
in approximately 40% of study participants (see Section 11.6). 
 
Robustness, Sensitivity and Stability of Conclusions.  As noted above, we plan multiple 
secondary analyses to check for the robustness of our conclusions in light of differing analytic 
decisions. These include a set of potential imputation assumptions (imputing our derived 
outcome directly vs. imputing individual BMI values before deriving the outcome, as well as 
assessing whether the data can be properly assumed to be MCAR or [more likely] MAR) and 
assessing whether interaction of other covariates with baseline BMI should be incorporated 
into our imputation models, assumptions about linearity of our key outcomes (the use of BMI 
slopes as our principal outcomes, rather than time-specific BMI values, adjusted for earlier 
values, and the potential inclusion of regression splines a la Harrell232, the inclusion or 
exclusion of covariates in our models, including baseline BMI and interaction terms, and the 
use of multiple propensity score weighting and matching approaches in our observational 
study of enrichment exposure. 
 
11.9. Additional Analysis 
 
We plan a cost-effectiveness analysis of these interventions, but the details of that work are 
still evolving, as we work with our project economist and the larger COPTR project. We have 
planned for an economic analysis from the beginning of our project, however, and in 
consultation with our economist, have identified important variables on which we are collecting 
data in order to conduct the economic analysis, such as interventionist preparation and contact 
time with subjects and health services utilization by subjects.  
  
12.  DATA MANAGEMENT & QUALITY CONTROL 
 
12.1. Common Database (Data Capture and Data Audits)* 
 
The COPTR Data Center was designed after extensive discussions with representatives from 
all of the sites to provide a secure, easy, and effective set of tools for submitting Common 
Measures to a central repository for the consortium.  Each of the four Field Sites has a site-
specific data system for conducting the daily tracking and data collection..  The COPTR Data 
Center does not dictate how those disparate site systems are designed or used.  Instead, the 

95 
 
 
Data Center provides a set of web-based tools for sites to upload completed Common 
Measures to the central repository at the RCU.   
 
Field Sites collect a subset of the Common Measures following the protocols and manual of 
procedures (MOPs) for those common measures.  The common measure subsets for each 
Field Site differ slightly but the MOPs and protocols defining the measurement/collection 
procedures are identical.  The recruitment data elements identified for submission to the RCU 
are identical at each Field Site.  Each Field Site submits the current collection of common 
measures quarterly and the recruitment and retention data monthly to the RCU to be included 
in the central data store of the Consortium.  Variables collected at only one Field Site are not 
transferred to the RCU.   
 
One or more representatives from each Field Site have been designated as members of the 
Data Capture Working Group.  These representatives contributed to the design of the Data 
Center tools and continue to contribute to improved functionality of the Data Center site.  
These representatives also serve as the primary contacts at a Field Site when the RCU notices 
irregularities with the submitted data.   
 
The RCU data transfer system utilizes a restricted access website to provide encrypted 
transfer of data files containing common measures (measurements collected at more than one 
Field Site) to a central data repository at the RCU.  Each Field Site will have one or more 
project staff authorized to have access to the Data Center website.  An individual at a site must 
receive authorization from the site’s PI prior to getting an assigned Data Center userid and 
password.  Field Site staff login to the Data Center via the following URL:  
http://www.shepscenter.unc.edu/coptr 
 
After successful authentication, the user will land on the “MyHome” page of the affiliated Field 
Site.  Access is restricted according to Field Site affiliation and defined roles.  An authorized 
staff for a Field Site only has permission to work within that site’s defined workspace.  Some 
RCU staff are authorized to work across all Field Sites’ workspace.   Figure 12.1 is a 
screenshot of the Case Western MyHome space. 
 
On this MyHome page, a Field Site user (e.g. Case Western user) will see two sections that 
give real-time information on successful uploads and attempts.  The top left box provides a 
Summary of the data records by type that have been uploaded to the Data Center and 
Confirmed by any of the site’s authorized users.  The Dataset Files box just below the 
Summary box provides more detailed information on each upload attempt.  Authorized site 
users always have access to these status displays.  Furthermore, authorized RCU users can 
see the status displays of all four Field Sites, providing an opportunity for RCU staff to monitor 
upload processes and provide assistance when errors are displayed.  In addition to the 
MyHome displays, the Data Center system has extensive error logging available to RCU staff 
to troubleshoot any problems encountered.  Last, to the right of the Summary box are the tools 
for uploading data sets.   

96 
 
 
Figure 12.1 Screenshot of the MyHome space 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
12.1.1.  Uploading Data to the RCU 
The COPTR  Capture Working Group decided to use file upload facilities versus web data 
entry forms for submitting site data to the Data Center. To upload a data set, the user will 
Browse his/her local file space for the desired CSV file, select the corresponding type by 
clicking on the appropriate radio button (e.g. Anthropometrics, Demographics, etc.), then click 
“Upload Selected File”.  The upload process evaluates the incoming data file, looking for the 
required unique identifiers, the correct site ID, and comparing the field names, data types, and 
data values according to the predefined “definition”.  (The “definition” files are available to read 
via the “definition” links.)  If any required data check fails, the RCU rejects the incoming file and 
reports the reasons to the user.  The user can then correct those issues and upload the file 
again.  If all required data checks pass, the incoming file is held with “Unconfirmed” status and 
the user is presented a report on the number of new records and number of modified records 
found in this incoming file.  This report provides the user an opportunity to confirm that those 

97 
 
 
numbers are as s/he expects.  If the numbers are as expected, the user can “Confirm” the 
upload and the process is complete.  Otherwise, the user can “Cancel” the upload then 
investigate the issues offline and attempt the upload again at another time. 
The next section on the screenshot in Figure 12.1 shows a running log of the dataset upload 
activities for the site.  The log shows the date and time of each upload attempt, the type of 
upload, the user performing the upload, and the status of that upload attempt.  Clicking on a 
“Confirmed” link in the Status column loads more detailed information about the confirmed 
upload.  Figure 12.2 shows the details of a confirmed Demographics upload from Case 
Western.  The more detailed information includes the local File Name of the uploaded file, the 
Upload Summary, and the unique identifiers of the New Records that were included in that file.  
In addition, if there were records uploaded that were intended to update or correct data that 
had previously been uploaded to the RCU Data Center, details of those changes would be 
listed in the right hand table labeled “Changed Records in this upload”.  Changes to data fields 
in existing records are made by matching the unique record key of an existing record with that 
of an incoming record then accepting the new incoming record as the most up-to-date.  (The 
older record is kept for reference.  It is not overwritten.) 
The Data Center is designed with three objectives in mind: 
1. Promote the submission of the highest quality data to the RCU for future use of the 
Common Measures; 
2. Provide an upload facility that is efficient and easy to use from the individual site’s 
perspective;  
3. Give the users enough information and flexibility to track progress and correct 
problems with Common Measures submissions. 
To that end, all data uploads with the exception of the accelerometer GT3X or AGD uploads, 
follow the same general model:  organize your data to fit the approved definition, upload a CSV 
file via the website, confirm the upload or correct the errors and try again. Figures 1-3 illustrate 
the information provided and assistance with identifying and correcting problems prior to the 
RCU accepting data. 
 

98 
 
 
 
Figure 12.2  Screenshot of a confirmed demographics upload  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Clicking on a “Rejected” link in the Status column will load more detailed information about a 
file with data that did not match the required criteria for acceptance in the Data Center.  Figure 
12.3 below shows the details of a rejected Demographics upload.  Again, the local File Name 
is displayed along with Date/Time and Uploaded By user.  The File Errors box in this example 
indicates that an upload was attempted that contained extra fields that the RCU was not 
expecting (first message).  Also, the second message indicates there are fields or columns 
missing in the upload that are required as Demographics Common Measures.  If there had 
been any data type mismatches or data values out of range, error messages would be 
presented in the “Row Errors” box.      
 

99 
 
 
 
Figure 12.3 Screenshot of a rejected demographics upload 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
12.1.2. Authoritative ID File – Study Arm 
 
The RCU Data Center requires one of the data uploads to be the authoritative source for Index 
Child IDs.  Having an authoritative “master” list of Index Child IDs allows the RCU to prevent 
orphan records from being introduced in any of the other data uploads.  The consortium has 
designated the Study Arm upload to be this source.  As such, a Study Arm record for an Index 
Child must be uploaded to the RCU before any other Common Measure records are accepted 
into the Data Center.  The Index Child IDs in other data uploads (e.g. Anthropometric, 
Demographic, etc.) are verified against the RCU’s Study Arm records prior to accepting the 
data records.  Data records that do not have a matching Index Child ID in the RCU’s Study 
Arm data are rejected to prevent orphan records from being introduced into the Data Center. 
 
12.1.3. Accelerometer Data 
 
Accelerometer data on an individual consists of two distinct parts:  a Physical Activity Monitor 
(PAM) record, and recorded data from the ActiGraph device (GT3X or AGD format).  The RCU 
requires sites to upload the PAM record of the pair prior to uploading the matching GT3X or 
AGD file.  The steps for uploading PAM records follows the same steps described above for 
other data uploads.  However, the steps for uploading GT3X or AGD files are different because 

100 
 
 
of the difficulties introduced in handling these large files.  (We are anticipating the average size 
of these files to be around 200MB.)  After successfully uploading and confirming PAM records, 
the user clicks the “Accelerometer Uploader” button shown in Figure 12.1.  The user is then 
presented with a screen similar to Figure 12.4 below.  The user can then queue up one or 
more GT3X/AGD files for upload either by clicking “Add files…” or by dragging files from local 
file space into the upload area.  Clicking “Start upload” will begin uploading the queued files in 
the order they are shown.  Each GT3X/AGD file is verified against the uploaded PAM records 
to ensure a PAM record exists for a GT3X/AGD file before allowing the upload to proceed. This 
verification allows the RCU to accurately link a PAM record to an incoming GT3X/AGD file.  
The user must make sure all queued uploads are completed before leaving this web page. 
 
Figure 12.4 Screenshot of the accelerometry file upload screen 
 
 
Uploaded GT3X and AGD files are not automatically analyzed at the RCU.  The files are 
simply stored in a file system for later use.  Each site is responsible for analyzing GT3X and 
AGD files for completeness prior to uploading to the RCU Data Center. 
 
 
 
 
 
 
 
 
 

101 
 
 
12.2. Site-Specific Database  (Data Capture and Data Audits) 
 
12.2.1.  Surveys/Self-Report Data 
 
Surveys will be administered to each participant during scheduled assessment days.  Most 
surveys will be administered to participants electronically on iPads using a web-based survey 
application known as Qualtrics and some will be administered in person; if a participant says 
s/he is uncomfortable with the computer based system, in-person interviewing will be 
performed.  Qualtrics has SAS 70 Certification and meets the rigorous privacy standards 
imposed on health care records by the Health Insurance Portability and Accountability Act 
(HIPAA). All Qualtrics accounts are hidden behind passwords and all data is protected with 
real-time data replication.  All data collected electronically through Qualtrics will be stored on 
Qualtrics’ server.  No survey data will ever be stored directly on the iPad.  No identifiable 
information will ever be stored on in the survey or on Qualtrics’ server.  Data will be linked to 
each participant by a unique ID number.  Data will be transferred from Qualtrics to the 
REDCap database on a regular basis.  After data has been successfully transferred from 
Qualtrics to the REDCap database, it will be removed from Qualtrics’ server. 
 
In the rare event that internet connectivity is an issue, all survey data will be collected through 
paper-and-pencil surveys.  Designated members of the research staff will be responsible for 
entering survey data directly into REDCap once internet connectivity becomes a non-issue.  
Paper-and-pencil surveys will be stored in a secure location—a locked filing cabinet—at the 
clinical research unit where it was collected.  Only key research staff will have access to this 
filing cabinet. 
 
12.2.2. Anthropometric Data 
 
Anthropometric data collected by research staff will be directly entered into REDCap through 
iPads during each visit.  No data will ever be stored directly on the iPad.  No identifiable 
information will ever be stored on this database.  Data will be linked to each participant by a 
unique ID.   A Manual of Operations will detail all procedures related to the protocol.  It will 
include detail on participant recruitment, data collection, database usage, and data 
management.  Study personnel roles and responsibilities, as well as access rights to the data 
will also be specified.  All results will be reported in aggregate only and at no time will 
individuals or identifiable groups be described.  Data quality will be monitored by random 
inspection of the completed forms by the data manager and any problems detected will be 
discussed with the PIs.  Data entry and/or data collection personnel will receive standardized 
training; if the inspections indicate errors or drift, re-training will occur. 
 
12.2.3. Study Databases 
 
Data collected for this study will be stored on three independent REDCap databases. REDCap 
is a secure, web-based application for building and managing online surveys and databases, 

102 
 
 
supported by the university’s Clinical and Translational Science Collaborative.  All three 
databases will be hosted on the CWRU REDCap server, which is imperative for the PIs and 
their designated staff (CWRU, UH and Metro employees) to have access to the databases. 
Throughout the duration of the study, members of the research team will require quick, 
immediate access to the database, from different locations.  This can only be accommodated 
by the CWRU’s REDCap system because it allows the database administrator to assign 
usernames to any individual, regardless of their place of employment.  Moreover, the system 
permits different access levels for each research staff member, dependent upon the access 
needs.  Some members of the research staff will be granted permission to access, enter or 
change data into each database.  Others may be given read-only access.  Select individuals 
will have the permission to download/export data from REDCap.  These individuals will be 
determined by the PIs of the study. 
 
Recruitment Database:  Prior to recruitment into the pilot study,  the Cleveland Metropolitan 
School District and Charter Schools  will provide the PIs will the contact information of all 
eligible students for the study (rising 6th graders who were screened and parents did not opt 
out of contact).  This population will form the basis of the recruitment database.  This database 
will store contact information (e.g., address, phone) and the process and outcomes of the 
recruitment process (e.g., dates contacts, result of call, whether additional information was 
sent, whether they came to a parent information meeting, date of initial assessment).  No other 
data will ever be stored in this database.  The database will only be used to record information 
related to the recruitment of participants, which will be used to report to NHLBI and the DSMB.  
Upon enrollment in the study, contact information for study participants will be transferred to 
the second database, the personal information database. Upon completion of all required 
reporting to NHLBI and the DSMB, the recruitment database will be destroyed. 
 
Personal Information Database:  The Personal Information Database will be used to store all 
identifiable information recorded on each enrolled study participant. This database will be used 
to store all identifiable information, including phone numbers, addresses, birthdates and 
tracking and scheduling information regarding assessment and group intervention dates.  
Intervention fidelity data (e.g., sessions attended) will also be stored in this database.  A 
unique participant ID will be assigned to each participant and stored in this database.  This is 
the only place where a participant’s name will ever be linked to study ID.  No other study data 
will be stored in this database.   Only key members of the research staff who will require 
access to this database will be granted access.  Most members of the research staff with 
access to this database will only have permission to add information.  Select individuals, as 
determined by PIs of the research study, will be granted permission to download/export data 
from REDCap to a secure, password protected computer.  All downloaded datasets will require 
password protection and will not be allowed to leave the designated computer.   
 
Process, Tracking and Fidelity Database:  All data related to contacting participants, 
attendance, and data collected during interventions will be directly entered into a REDCap 
database stored on Case Western Reserve University’s server (see Data Processing).  It is 

103 
 
 
imperative that CWRU’s REDCap be used to store the data since the research team is 
comprised of both UH and CWRU staff who will require convenient and immediate access.  No 
Identifiable information will ever be stored on this database.  Each participant will be assigned 
a unique ID.  This unique ID will be used to link the participant with the data. 
 
De-identified Database:  All data collected during the scheduled assessments (e.g., collected 
via interview, survey, assessment) will be directly entered into a REDCap database stored on 
Case Western Reserve University’s server (see Data Processing).  It is imperative that 
CWRU’s REDCap be used to store the data since the research team is comprised of both UH 
and CWRU staff who will require convenient and immediate access.  No Identifiable 
information will ever be stored on this database.  Each participant will be assigned a unique ID.  
This unique ID will be used to link the participant with the data. 
 
In order to accurately assess hypertension risk according to NHLBI standards and determine 
BMI percentile according to the CDC’s, birthdates and data collection dates must be collected.  
This information is required to properly assess blood pressure and BMI status for this age 
population. Other than these two dates, no identifiable information will ever be stored on this 
database.  Each participant will be assigned a unique ID.  This unique ID will be used to link 
the participant with the data. 
 
Each member of the research staff requiring access to the REDCap database will be assigned 
a unique user ID and password.  User-rights will be established for all research staff requiring 
access to this REDCap database.  User-rights will be determined by PIs and based and 
database access needs.  Most members of the research staff with access to this database will 
only have permission to add information.  Select individuals, as determined by PIs of the 
research study, will be granted permission to download/export data from REDCap to a secure, 
password protected computer.  All downloaded datasets will require password protection and 
will not be allowed to leave the designated computer.  
 
For final analyses of the resulting de-identified database, in keeping with modern practice, Dr. 
Love (project statistician and co-investigator) and Mr. Thomas (statistical programmer) will use 
a variety of statistical software packages, including R (for basic and complex graphical work, 
implementation of new methods, model fitting, and some data management) and Stata (for 
some model-fitting, multiple imputation and data management tasks.) Main analyses of an 
appropriately cleaned and locked master database will be conducted in the final project year. 
In addition, the statistical analysts will be responsible for responding to all requests for 
analyses of the local data that come forth from the RCU or DSMB. 
 
 

104 
 
 
 
13. SITE SPECIFIC TIMELINE 

105 
 
 
 
 
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