Study Hypotheses
Table 1 summarizes the hypothesized mechanisms across structured programs and Table 2 describes the hypothesized gains in BMI z-score across the school year, summer, and 12-month year.
Aim 1.1 Hypotheses. Specific Aim 1.1 has 4 hypotheses:
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Children provided a voucher for a free ASP and SDC will experience smaller increases in BMI z-score than the three other groups over 12-months (school and summer),
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Children provided a voucher for a free ASP only and SDC only will experience less BMI z-score gains over a 12-months (school and summer) compared to children provided no voucher,
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Children provided the free ASP voucher (i.e., SDC and ASP or ASP only vouchers) will experience less BMI z-score gain during the school year than children provided the free SDC only voucher and children provided no voucher.
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Children provided the free SDC voucher (i.e., SDC and ASP or SDC only vouchers) will experience less BMI z-score gain during the summer than children provided the free ASP only voucher and children provided no voucher.
Aim 1.2 Hypotheses. Specific Aim 1.2 has the same 4 hypotheses as Aim 1.1 but for fat mass, fat free mass, and percent body fat.
Aim 1.3 Hypotheses. Specific Aim 1.3 has 2 hypotheses:
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Children who receive a SDC voucher (i.e., SDC and ASP or SDC only vouchers) will engage in fewer obesogenic behaviors during the summer than children who do not receive a SDC voucher.
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Children who receive an ASP voucher (i.e., SDC and ASP or ASP only vouchers) will engage in fewer obesogenic behaviors during the hours after school than children who do not receive an ASP voucher.
Aim 2 Hypotheses. Specific Aim 2 will examine the cost effectiveness of providing the ASP only voucher, SDC only voucher, and combined ASP and SDC vouchers. While no specific hypotheses have been generated, costs associated with providing children with vouchers to attend ASPs, a SDC, or an ASP and a SDC and the associated impact of each condition on children’s BMI z-score will be explored. This will inform researchers and policy makers about the cost and feasibility of scaling this approach should it prove successful.
Aim 3 Hypotheses. Specific Aim 3 will examine facilitators and barriers to the implementation, effectiveness, and sustainability of the Voucher Program by conducting qualitative interviews with key informants. While no specific hypotheses have been generated it is of interest to explore the facilitators and barriers to operating the program in order to inform refinements of the programming and/or additional strategies that may be needed to optimize the impact and future widespread dissemination of similar programs aiming to mitigate accelerated summer BMI gain.
Study Design
The study employs a 2x2 full factorial design [63]. The two factors will be access, through vouchers, to 1) ASP or 2) SDC. The four groups will be no program vouchers, ASP voucher only, SDC voucher only, and vouchers for both ASP and SDC. The study will last for 3 years, and a total sample of 480 children will participate. Each spring we will recruit 160 children who will be evenly randomized to one of the 4 conditions (i.e., 40 per condition each year). To achieve the proposed sample size, the study will enroll kindergarten through 4th grade students. Students recruited into the study will be observed over 14 months (summer and school year) following their recruitment. For example, a kindergarten student will be observed during the spring they are recruited, over the summer following kindergarten, and during their 1st grade year while a 4th grade student will be observed during spring they are recruited, over the summer following 4th grade, and during their 5th grade year. A timeline for the study is depicted in Figs. 1 and 2.
Participants
A total of 4 elementary schools in one local school district in the southeastern United States will participate in this study. Schools were selected because they serve the age range targeted for this study (5–12 years, kindergarten through 5th grade), serve primarily families with low-income (76% of the students are in poverty), and are served by the SDC and ASP provider that we have partnered with for this study. A total of 1,999 children are enrolled in these schools; 49% of students are female, and the majority of students identify as either Black (52%) or White (25%), while 8% identify as Hispanic.
Recruitment and Randomization
In the spring (~ February through April) of years 1–3, all children in the participating schools will be invited to enroll in the study. The primary procedure for the recruitment of parents/children will be through the distribution of fliers and consent forms via school communication. The consent document describes the protocols and procedures of the intervention and all measures and indicates that participants’ deidentified data will be included in scientific publications and may be used for additional future studies. The primary procedure for identifying eligible children will be to include a series of questions on the informed consent documents to screen for eligibility. For parents who indicate “yes” to participating on the informed consent document, they will be asked to sign their names, provide a phone number, indicate their highest education level attained, their child’s age, biological sex, self-identified race/ethnicity, and if their child has any special needs. The inclusion criteria will be: K-4th grader in a partner school and a parent who indicates “yes” on an informed consent document for participation in the study. The exclusion criteria for children to participate in the study will be special needs that require specially trained staff or increased staff per child ratios to accommodate. This decision was made because the SDCs and ASPs included in this study do not have the resources to accommodate children with special needs in the programs participating in our study. For those children that are ineligible because they have special needs we will refer them to other ASPs and SDCs that do provide accommodations for children with special needs.
Given the high demand for ASP and SDC in the participating schools, we anticipate recruiting more participants than can be included in the study. Should more families than we can accommodate indicate interest in participating, we will stratify by grade and biological sex and randomly select families to participate in the study. Children (n = 480; ~50% girls, ~ 20% K, ~ 20% 1st, ~ 20% 2nd, ~ 20% 3rd, and ~ 20% 4th graders) will then be randomly assigned via computer-generated random numbers by an assistant data scientist to receive no vouchers, a voucher for the full price of 10 weeks of SDC, a voucher for the full price of 39 weeks of ASP, or a voucher for the full price of SDC and ASP. Data analysts will be blinded to assignment (data sheets and treatment arms will be anonymous). There are no circumstances under which unblinding participants to data collectors or analysts is permissible. Families not selected will be placed on a waiting list for the next school year.
Intervention
Voucher Program. Children randomized to receive the SDC voucher will receive a voucher that covers all enrollment fees associated with accessing a preexisting SDC operated by our partner provider at their school. The cost to enroll in these SDCs is $140/week/child. The $140 fee covers all operating expenses of the camp. The camps are currently operating for the entire summer (~ 10 weeks). The total value of the voucher for 10 weeks will be $1,400/child.
Children randomized to receive the ASP voucher will receive a voucher that covers all enrollment fees associated with accessing a preexisting ASP operated by our partner provider at their school. The cost to enroll in these ASPs is $65/week/child. The $65/week fee covers all operating expenses plus transportation, when needed, to and from the ASP. The ASPs are currently operating for 39 weeks during the school year. The total value of the voucher for a single child for 39 weeks will be $2,535.
Children randomized to receive the ASP and SDC voucher will be provided with the 10-week SDC voucher and 32-week ASP voucher for the academic year in which they participate in the study. The total value of the voucher for a single child will be $3,935.
Description of SDCs for the Voucher Program. The SDCs will be existing camps operated by a local parks and recreation department which take place at a school in the district from which children will be recruited. The camps are not singularly focused, such as sport camps or academic only camps. Rather, the camps provide indoor and outdoor opportunities for children to be physically active each day, provide enrichment and academic programming, as well as provide breakfast and lunch. Importantly, these camps are enrolled in the USDA Summer Food Service Program meals will adhere to the Summer Food Service Program nutrition guidelines [36]. The camps employ 1 staff member for every 12 children – which is consistent with childcare regulations in the state in which the trial will take place. The camps operate daily (Mon-Fri) for ~ 10 weeks during the summer. The camps open at 7:00am and close at 6:00pm. Physical activity opportunities are scheduled for 3 to 4 hours each day, with the remaining 4 to 5 hours dedicated to enrichment, academics, or meals. These camps will operate according to their routine practice, with no outside assistance from the investigative team.
Description of ASPs for the Voucher Program. The ASPs will be existing community-based programs operated by the same parks and recreation department that take place immediately after the regular school day (typically 3:00–6:00pm); are located in a school in our partner school district; are available daily throughout the academic year (Mon-Fri); and provide a combination of scheduled activities, which include a snack, homework assistance/tutoring, enrichment activities (e.g., arts and crafts, music), and opportunities for children to be physically active for approximately 60 minutes each day. These ASPs serve a snack and/or dinner that complies with the Child and Adult Care Food Program nutrition guidelines for content and quantity [64]. The ASPs also employ 1 staff member for every 12 children.
Control Group
The children in the control group will be children enrolled in the same schools as those randomized to receive the vouchers for ASP and/or SDC. The control group will not receive a voucher to attend an ASP or SDC. It is possible that children serving in the control/comparison condition may elect to voluntarily participate in an ASP or SDC. However, based on the associated costs of enrolling (i.e., summer = $140 per week per child, ASP = $65 per week per child), and national data indicating that few children from families with low-income attend ASPs or SDCs [35, 54], it is likely that only a few of the control children will enroll in an ASP or SDC without a voucher.
Outcome measures
A summary of the measures collected in this study is presented in Table 3 and described in detail below.
Anthropometrics Measures. Students enrolled in the partnering schools will have their height and weight measured using standard procedures during physical education classes. All height and weight measures will be collected by trained research staff with the assistance of the physical education teacher to ensure accuracy. Height (nearest 0.1 cm) and weight (nearest 0.01 kg.) will be collected using a portable stadiometer (Model S100, Ayrton Corp., Prior Lake, Minn.) and the scale on the bioelectrical impedance device (see below). BMI will be calculated (BMI = kg/m2) and transformed into age and sex specific z-scores [65].
Bioelectrical impedance will be used as a secondary measure of children’s body composition. This will allow for the quantification of whole-body fat mass, fat free mass, and percent body fat. Bioelectrical impedance will be collected via an InBody bioelectrical impedance analyzer (Model 270, InBodyUSA, Cerritos, CA). Bioelectrical impedance will be collected every time a child’s height and weight are measured. When used with children, bioelectrical impedance has been shown to have strong test-retest reliability and acceptable validity when compared to criterion measures of body composition [66–68]. However, bioelectrical impedance has the advantage of being portable, less invasive, and less costly to complete than criterion measures of body composition.
Physical Activity & Sedentary Time. Time (minutes per day) spent sedentary and in light, moderate, and vigorous physical activity will be collected using a non-dominant wrist-placed Axivity AX3 accelerometer (Axivity, Ltd. United Kingdom) for 14 days (common timeframe to collect physical activity data) [69] at the three time points. Non-dominant wrist-placement improves compliance over waist placement [70, 71]. The device is waterproof, allowing us to capture water activities like going to pools during the summer. Data will be downloaded via Open Movement, saved in .cwa format, and processed using the GGIR package [72] in R. Time spent in sedentary and physical activity intensity categories will determined using intensity thresholds described by Hildebrand et al [73, 74]. Widely accepted protocols for a valid day of data will be used [75–79]. Each parent will report non-wear time on a time use record that will be sent via an electronic survey nightly during accelerometer wear. Parent-reported non-wear time will be cross-referenced with the accelerometer data for quality assurance.
Sleep. Using the protocols described above, children’s sleep will also be assessed via wrist-placed Axivity AX3 accelerometers. This procedure produces valid sleep data and is used extensively in sleep studies [11, 80, 81]. Sleep onset, offset, and duration each night will be determined using the heuristic algorithm looking at distribution of change in Z-Angle [82].
Screen Time. Each day of the 14-day accelerometer protocol, parents will receive a text to complete a time use record via their smartphone. Consistent with past studies [21, 83, 84], one of the questions of the time use record will ask parents to estimate the total amount of time (hours and minutes) their child spent in front of a screen that day (e.g., TV, computer, video game, smartphone, and tablet). The time use record has been described in detail elsewhere [58].
Dietary Intake. For diet, parents will complete a screener that captures sugar-sweetened beverages, salty snacks, sweets, milk, and fruit and vegetables consumed by their child that day [85–87]. This screener has been shown to have strong validity compared to daily food records [86]. This will be collected nightly on the same time use record survey as the screen time measure.
Process Evaluation Outcomes. For this study, we will collect process evaluation outcomes related to attendance at structured programming and programmatic offerings of these programs. For each child participating in the study, information regarding attendance at any ASPs or SDCs will be collected. For those randomized to receive a voucher, detailed information regarding the daily attendance at the ASPs and/or SDCs where the vouchers are eligible will be collected by ASP and SDC staff and shared with research staff weekly. These data will be used to determine the total exposure to ASPs and SDCs children receive across all groups. For all children, including those not receiving a voucher, children’s primary parent/guardian will report the days during the school year that their child attended an ASP and the days during the summer that their child attended a SDC program (of any type). At the end of each month, respondents will be asked to report the days in the past month that they attended a structured program, the type program (e.g., ASP, SDC, etc.), name of provider, and location. Responses will be collected on a monthly basis via an online texted survey that we have developed specifically for this project. Programmatic offerings occurring at the ASPs and SDCs will be documented via direct observation of the scheduled opportunities (e.g., enrichment, mealtimes, physical activity) using the SOSPAN (System for Observing Staff Promotion of Activity and Nutrition) [88–95] on four unannounced random days by research staff in each program (i.e., ASP and SDC) each year. The types of foods and beverages served at all eating occasions at the voucher ASPs and SDCs will be recorded via program menus (i.e., breakfast, lunch, dinner, and snack).
Cost Effectiveness Outcomes. We will estimate the cost-effectiveness of the three voucher conditions relative to the control condition in terms of incremental cost-effectiveness ratios. We will consider the primary outcome (BMI z-score) and all costs related to delivering the ASP, the SDC, and combination ASP/SDC separately [96], including costs related to administering the vouchers to families, training staff, purchasing materials, daily operations, and transportation to and from the ASP/SDCs. Costs will be collected from call logs maintained by research assistants, training logs, budgeting materials, purchase records, and invoices collected from the ASP/SDC program provider.
Qualitative Outcomes. To evaluate facilitators and barriers to the implementation, perceived effectiveness, and sustainability of the voucher program, we will conduct qualitative interviews with key informants. Interviews are an ideal method in research to explore the “why” behind the “what” (i.e., to understand the reasons underlying observable phenomena) [97]. If the voucher program proves successful, and cost-effective it has the potential to be disseminated on a large-scale given that many pre-existing ASPs and SDCs exist across the country. Thus, it is vital to ensure that the barriers to and facilitators of implementation, perceived effectiveness, and sustainability are well understood. Key informants will include children and parents of voucher program recipients in each condition; ASP and SDC staff and administrators; and administrators from the participating schools. Efforts will be made to recruit parent/child dyads from families where the child attended frequently and infrequently. Interview questions for children will address enjoyment of the program, perceived benefits of the program, and willingness/desire to attend. Interview questions for parents will address perceived benefits of the program, perceived barriers to attendance, and willingness/ability to pay for a similar program. Semi-structured interview questions with ASP and SDC program staff and administrators and school administrators will address perceived benefits of the program, ease of implementation, and barriers and facilitators to sustainability.
Schedule of Measures
A schedule of measures is presented in Figs. 1 & 2. BMI will be collected at baseline (end of school year, ~May), 3-month (post summer, start of school year ~ Aug), and 12-month follow-up (post school, end of school year ~ May). Obesogenic behaviors (i.e., physical activity, sleep, screen time, diet) will be collected during spring (~ April/May), summer break (~ July), and fall (~ October). Cost measures will be tracked throughout the summer and school year while the SDC and ASP are operating. Semi structured interviews will happen immediately following the SDC and throughout the school year when the ASP is operating across all 3 years of data collection.
Power and Data Analysis
The sample size for our study was chosen based on best practice for factorial designs [98]. Power calculations were based upon detecting differences in BMI z-score gain/loss between groups. Previous large scale longitudinal studies of school year vs. summer BMI gain [99–102], studies examining the provision of a structured program during the summer [103, 104], and our pilot work have shown that the Cohens d effect size of the difference between groups should be approximately 0.50. However, the study was powered to detect a difference of 0.38 to ensure that the sample size is sufficient for the detection of an effect in the secondary outcomes in addition to the primary outcome and to ensure that the sample size could withstand up to 30% missing data. The power analysis was performed using G*Power (v.3.1.7) assuming power of 0.80, correlation among repeated measures of 0.80 (assumed based upon our pilot work [46]), and alpha of 0.05. Given these assumptions, with a sample of of 480 participants with the current study is powered to detect a Cohens d effect size of 0.38. The sample size was calculated using a variance inflation correction factor of 1.36 to account for clustering of children within schools. The variance inflation factor was calculated using VIF = 1 + ρ (n – 1) where, ρ represents the intraclass correlation of children within schools and n is the number of schools [105]. A ρ of 0.06 was assumed based on school intraclass correlation in the Trial for Activity in Adolescent Girls and our pilot data [46, 106].
All analyses will be completed following the completion of the study (i.e., all cohorts have completed the trial). Data from all study measures will undergo initial data cleaning to identify potential outliers, assess normality, and enumerate loss to follow-up and other missing data. Descriptive statistics at baseline will be compared between the treatment groups. We also will account for potential confounding of structured environments (i.e., children in the control group attending structured programs outside of the school day) by completing both intent-to-treat (primary) and as-treated analyses (secondary).
The following describes the analytical modeling procedures for Aim 1.1, 1.2, and 1.3 that will be used to examine differences within and between the four groups in BMI z-score and obesogenic behaviors. All models will account for the clustering of children within schools and for the repeated measures within children. Intent-to-treat analyses will be the primary analysis plan and will include all participants in the original groups to which they were randomized regardless of if they attended, or did not attend, structured programming outside of the school day. As-treated analyses will be the secondary analysis plan. For the as-treated analyses we will analyze children based on which structured programming outside of the school day they actually attended. For instance, if a child randomized to the control condition attended an ASP they would be analyzed in the ASP group. On the other hand, if a child randomized to the ASP only voucher condition did not attend the program they would be analyzed in the control condition. The intent-to-treat analysis (primary) will provide us with an estimate of the effects of providing vouchers under real world conditions. The as-treated analysis (secondary) will provide an estimate of the impact of structured programming on children’s body composition outcomes and obesogenic behaviors.
To test the hypotheses in Aim 1.1 we will follow best practice for analyzing factorial experiments [107, 108]. The design is a 2X2 full factorial with four groups (i.e., no voucher, after-school only voucher, summer only voucher, and after-school and summer voucher). Repeated measures linear regression models accounting for repeated measures within children and children nested within schools will estimated change in BMI z-score. All models will include hierarchical nested random effects to account for the nested nature of the data (measures within children). A categorical variable for group (no voucher, after-school only voucher, summer only voucher, and after-school and summer voucher), time (0-, 3-, 12-months), and setting (summer vs. school year), along with all group-x-time, group-x-setting, and group-x-time-x-setting interactions will be included. Hypothesis 1 will be the first contrast of interest and will be tested via the after-school and summer voucher group-x-time interaction at 12-months. The after-school only group-x-time interaction, summer only group-x-time at 12-months and the after-school only group-x-time-x-setting interaction, summer only group-x-time-x-setting interaction will be second and third contrasts of interest, respectively. These contrasts will test hypotheses 1–4. To control for multiple comparisons while preserving power we will use the Benjamini-Hochenberg [109]. For Aim 1.2 we will follow the same procedures described for Aim 1.1 but with fat mass, fat free mass, and percent body fat as the outcome of interest.
For Aim 1.3, the analysis plan will differ if the obesogenic behavior is available on a daily basis (e.g., sleep) or on an intra-daily basis (e.g., physical activity). For those available on a daily basis the analyses will be identical to Aim 1.1. For those available on an intra-daily basis, an additional variable indicating if the measurement was during or after-school hours will be added. For these models, the 3-way interaction of group-x-time-x-during/after-school will be the primary contrast of interest. Specifically, during the school year we hypothesize students taking part in after-school activities will have lower obesogenic behaviors in the after-school hours. These analyses have 6 outcomes corresponding to the measures at baseline, summer and during the year taken either during or after-school hours. Again we will use the Benjamini-Hochenberg procedure with a false discovery rate of 10% to account for multiple comparisons [109].
For Aim 2, we will evaluate the cost effectiveness of the ASP and SDC interventions from the budgetary perspective using incremental cost effectiveness ratios, defined as (costintervention – costcontrol) / (outcomeintervention – outcomecontrol). The incremental cost effectiveness ratios will inform policymakers of the additional cost per additional unit of outcome obtained from the intervention relative to the control (e.g., a given hypothetical program A costs an additional X amount for each unit of BMI z-score score reduced.) The evaluation will follow best practice methods to calculate incremental cost effectiveness ratios [110, 111]. We will first order the interventions from the most to the least costly and calculate the incremental cost and incremental outcome step by step in this order, likely to be ASP + SDC, ASP only, SDC only, and no voucher. We will then consider incremental cost effectiveness ratios from the budgetary perspective, with BMI z-score from Aim 1.1 as the primary outcome. In other words, we will generate 3 separate incremental cost effectiveness ratios, one for each of the 3 pairs of comparisons ordered by cost of the 4 interventions. These incremental cost effectiveness ratios will help resource-constrained policy makers make cost-effective decisions by providing the incremental cost required to achieve an incremental reduction in BMI z-score, for example if SDC voucher only is chosen over no voucher, or if ASP and SDC vouchers are prioritized over ASP vouchers only. As additional analyses, we will also include measures of obesogenic behavioral outcomes from Aim 2. As noted previously, the cost of each arm of the intervention will determined using the cost of the vouchers and the cost of distributing the vouchers. These costs will be collected as part of the data collection process before and during the intervention.
For Aim 3, we will evaluate facilitators and barriers to the implementation, perceived effectiveness, and sustainability of the voucher program by conducting qualitative interviews with key informants (i.e., children, parents, staff, administrators). The interview transcripts will be analyzed using modified analytic induction [112]. This analytic technique combines deductive and inductive reasoning to develop themes representing major ideas or concepts embedded in the data. Deductive reasoning involves identifying and collating excerpts from the transcripts that align with key concepts and postulates from the theoretical literature used to inform the interview questions. Inductive reasoning involves drawing out and connecting ideas from the data without imposing an a priori theoretical perspective on the analysis. Combining deductive and inductive approaches in qualitative data analysis allows the researcher to consider the data both in light of the current knowledge base (i.e., existing literature) and within the unique space of the study phenomena. Therefore, themes emerging from data analysis can take root in generalizable principles, as well as in contextual anomalies.
To ensure trustworthiness of the qualitative results [113], two trained research assistants will analyze the interview data together and discuss any disagreements until consensus is reached. In addition, member checking will be used, which will involve sending interview transcripts and emerging themes to the interview participants to check the accuracy of the transcripts and the veracity of the findings. Finally, the research assistants will search for negative cases in the data (i.e., instances where the data do not align with the emerging themes) and explore these cases by conducting brief follow-up interviews with the participants.
Withdrawal and safety
Consistent with ethical practice and the of South Carolina’s Institutional Review Board, participants are free to withdraw from the study at any time with no reason given and no negative consequences. There are limited risks involved with participating in this study. For children, the risk to wearing the wrist-based activity monitor is minimal. We specifically selected wrist-placement to help in compliance with wearing the monitor across the 14-day protocol. These monitors are water-proof; therefore, a child can keep the monitor on his/her wrist for the entire 14-day assessment period, giving us additional daily measures of sedentary and activity time. There is also a minimal amount of risk for children participating in summer day camp and afterschool programs. However, our partner providers operate afterschool programs and summer day camps for hundreds of children each year and have well established rules and protocols for the safety of children. For parents, the risk associated with completing the daily diaries and surveys is minimal. The diaries do not ask about anything considered sensitive in nature, focusing exclusively on their child’s obesogenic behaviors. The surveys will be kept in locked file cabinets and secure computer files at the University of South Carolina. All participants will be encouraged not to answer any questions or take part in any measures that make them uncomfortable. While there are no anticipated harms in the traditional since for this study it is important to monitor if harms or unintended consequences occur [114]. We anticipate that the qualitative interviews with parents and children are a natural place to monitor for any harm or unintended consequences and will ask specific questions related to harm or unintended consequences experienced by participants.
Retention plan
We have designed the study to maximize participation and have developed the measures to limit burden, thereby increasing retention across time. We have also included an incentive for participants in the form of a voucher to afterschool and summer programming. Those participating in data collection (comparison/control condition) will receive a financial incentive of approximately $435 per year. Also, we have a detailed plan to address missing data. For instance, where we have missing assessments, such as daily diaries, activity data, or BMI, we will contact the parents and, where willing, invite them to re-complete the missing assessments. If children/families miss a pre- or post-summer BMI assessment, body composition, or fitness measures, we will work with our partnering afterschool and summer camp providers to follow-up with the family to re-schedule the measurement. If this is not feasible due to scheduling demands, a trained member of the research team will schedule a visit in a public place with the child/family to perform the standard height and weight measures at the family’s earliest convenience.
For any given year, we anticipate 25% of the sample will have missing data (pre or post summer BMI measures, obesogenic behavior data) or will leave due to reasons unrelated to the study such as relocating to another city or major illness/life event. We anticipate very few instances of such events and we will document any occurrences of this nature. For children/families enrolled in the study but unwilling to continue, we will attempt to contact the children/families to obtain detailed process information as to the main contributing factors.
Data management and confidentiality
The investigative team is responsible for managing and overseeing the trial, monitoring that data is being collected appropriately and that the trial is progressing sufficiently. Study materials and data will be coded with numeric identifiers and will be accessed only by the principal investigator and a limited number of project staff. The linking codebook, with child names and IDs, will be retained on a university computer that is not connected to an intra/internet, is password protected, and resides in a locked office. There will be no reporting of individual school/child/family level information – all information will be presented using descriptive statistics (e.g., means, median, standard deviation). Staff will be trained in human subjects and confidentiality issues and procedures. Study materials and data will be kept in secure computer files and file cabinets at the Arnold School of Public Health, University of South Carolina. The study does not have a formal data monitoring committee. The research team along with an independent safety officer who is not affiliated with the study will monitor data monthly for adverse events throughout the study.