Video Games for Obesity and Diabetes Prevention
With the increasing rates of child obesity and diabetes, innovative programs are needed that capture children's attention and permit behavior change messages to get through. Serious video games with their immersive stories offer one such promising alternative. "Escape from Diab" and "Nanoswarm: Invasion from Inner Space" are two video games guided in their design by four behavior change theories that were targeted at increasing fruit, vegetable and water intakes, and lowering sedentary behaviors, and have been shown to change these children's diet and physical activity practices in a pilot study with a relatively low risk sample. In light of this preliminary success, it is important to test the efficacy of these interventions on diabetes risks (i.e. fasting insulin) with higher risk children (which should increase the effect) and with a larger sample to learn how the games change behaviors using mediating variable analyses. A study with 444 high risk (85%tile<BMI<99%tile) 10 to 12 year old children is proposed. Children will be randomly assigned to treatment or control groups. The control group will be a wait-list control and receive the intervention at the end of the second post assessment. Video games are a promising low cost approach to intervention since the games have already been developed, and can be broadly disseminated by simply reproducing and distributing their DVDs. No study has appeared that tested the effects of theory based video games on diet and physical activity that was adequately powered to investigate mediating variables. Conducting the mediating variable analyses will inform the design of future video games and enhance their ability to promote health behavior change. While using video games for health promotion is controversial, this study will establish whether video games efficaciously change diabetes risks (especially insulin, diet and physical activity) among children.
|Study Design:||Allocation: Randomized
Endpoint Classification: Efficacy Study
Intervention Model: Parallel Assignment
Masking: Single Blind (Outcomes Assessor)
Primary Purpose: Prevention
|Official Title:||Video Games for Obesity and Diabetes Prevention: Efficacy Trial|
- Change in fasting insulin from baseline to up to 3 months post baseline (immediate post intervention) [ Time Frame: Three time points: baseline, up to three months post baseline (immediate post), two month post immediate post ] [ Designated as safety issue: No ]Fasting blood will be drawn to assess fasting insulin. The evening before data collection, study staff will call the child scheduled for the next day's blood draws to remind them not to eat any food or drink except water after midnight and not to eat breakfast. At check-in, students will be questioned about the last time they had anything to eat or drink and will be rescheduled if they are not fasting. Standard procedures will be followed by nurses and licensed phlebotomists. A study physician will be available by phone in case of adverse events. A numbing cream will be applied with appropriate consent. Blood will be drawn in the CNRC metabolic unit. Samples will be inserted in EDTA tubes, placed on ice, centrifuged at 4oC and transferred to labeled storage tubes and frozen at -80oC until analyzed. Plasma insulin will be measured using commercially available double sandwich assay on an Elecsys 1010 instrument (Roche Diagnostics Corporation, Indianapolis, IN).
- Change in Fruit and Vegetable Intake [ Time Frame: Three time points: baseline, up to three months post baseline (immediate post), two month post immediate post ] [ Designated as safety issue: No ]The investigators will use the ASA24-Kids to assess usual dietary intake, and obtain three 24-hour dietary recalls (24hdr) using ASA24-Kids on nonconsecutive days at each observation. Three days has been demonstrated to obtain acceptably reliable estimates of usual intake. The 24hdr will be obtained for two weekdays, and one weekend day. ASA24-Kids will ask the child where each meal/snack was eaten, who else was there, whether a TV was on and whether they attended to the TV during the meal. Children 10 years and older can give a reasonably accurate self-report of intake. 24hdr completed by telephone have been found to provide accurate data from 8-10 year old African-American girls and adolescents. The dietary recalls will be analyzed for servings of fruit and vegetables. The investigators will assess fruit and vegetable servings by day of the week, meal/snack, and environment. The investigators helped create the ASA24-Kids and conducted the first validation study.
- Change in Moderate to Vigorous Physical Activity [ Time Frame: Three time points: baseline, up to three months post baseline (immediate post), two month post immediate post ] [ Designated as safety issue: No ]Physical activity will be assessed using the latest Actigraph GT3X accelerometer. This accelerometer is a small device which measures acceleration in 3 dimensions plus step counts. Accelerometers have been shown to provide accurate and reliable assessments of activity among youth. Participants will wear accelerometers for seven days (with a minimum of 600 min of recording from 6am to midnight to count as a valid day) and mean minutes of MVPA will be established for weekdays and weekend days using published cut-points. Accelerometer counts per minute, an indication of the volume of activity in which the children engaged, will be calculated.
|Study Start Date:||September 2013|
|Estimated Primary Completion Date:||August 2016 (Final data collection date for primary outcome measure)|
Experimental: Two serious videogames for health
This efficacy trial will be conducted using a two group design (treatment (trt), control (ctl)) with randomization to group occurring after baseline assessment (to obviate observer bias), and three assessment periods (baseline, immediate post and 2 month post). The treatment group will play the 1)Diab and 2)Nanoswarm videogames.
Behavioral: 1)Diab and 2)Nanoswarm
The Escape from Diab and Nanoswarm games present fun, challenging: 1) knowledge mini-games that enable children to learn what constitutes desired behavior; 2) goal-setting activities tailored to a child's current behaviors and preferences to make specific lifestyle changes; 3) problem solving routines to enable children to determine strategies to overcome likely barriers to behavior changes; 4) motivational statements tailored to a child's values to enhance the child's desire to make the goal related lifestyle changes; and 5) energy balance games to enable children to select appropriate portions and aerobic/strength enhancing physical activities. Each game has 9 sessions with approximately 45-60 min of game-play per session. At the end of each session, the child was allowed to return to the game to re-play certain mini-games, and related video segments, but could not redo the goal setting or review portions.
|No Intervention: Wait List Control|
Hide Detailed Description
Youth obesity has risen dramatically over the past few decades. While most child obesity prevention programs have had little or no effect, serious video games offer promise of effective behavior change by immersing children in a story that engages them in behavior change procedures inserted in the game. "Escape from Diab" and "Nanoswarm: Invasion from Inner Space," (hereinafter called Diab and Nano), two epic video games designed to lower risks of T2D and obesity from these theory based procedures, changed diet behaviors in a small pilot trial in a lower risk group of children (see Approach). This project is to conduct an efficacy trial of Diab and Nano. Since change interventions have had effects primarily among the overweight and obese, implementing these video games in higher risk groups should attain larger effects. To assess their potential for minimizing T2D and obesity risk, the investigators will assess dietary intakes and PA. Glucose levels are tightly regulated (not likely amenable to change by a public health intervention), and impacting BMI requires a long duration intervention, but fasting insulin has been responsive over shorter intervals. Thus, the investigators will target decreasing fasting insulin as the primary outcome, both as reducing an important indicator of type 2 diabetes risk and as an objective indicator of behavior change. To assess mechanisms, this study will be powered to test for mediation effects.
The proposed research will be conducted in two phases, covering a 3 year period: implementation and evaluation phase of 2.5 years and an analysis phase of 0.5 years.
Specific Aim 1: Conduct an efficacy outcome evaluation randomized clinical trial with Diab and Nano.
Specific Aim 2: Conduct analyses of the efficacy evaluation of Diab and Nano.
The hypotheses to be tested include:
Hypothesis 1: Children playing Diab and Nano will decrease fasting insulin by, at least, 2μU/dl, increase FV intake by at least 1.0 servings/day, and increase MVPA by at least 10 min/day from baseline to up to 3 months post baseline.
Hypothesis 2: Child diet, MVPA and fasting insulin changes from playing Diab and Nano will not be moderated by demographic characteristics (e.g. gender, age, ethnic group).
Hypothesis 3: Child fasting insulin change will be mediated by changes in diet, PA and SB.
Hypothesis 4: Child diet and PA change outcomes will be mediated by changes in preferences and intrinsic motivation for FV and PA.
Research Strategy Approach Methods
Specific Aim 1. Conduct an efficacy trial with Diab and Nano. Data will be collected to test the efficacy of Diab and Nano on FV intake, PA, and type 2 diabetes risks. The effects on mediating, and of moderating, variables will be examined to explain the pathways of effect to enhance understanding of how serious videogames influence behavior change and it's maintenance.
1.1. Research Design. This efficacy trial will be conducted using a two group design (treatment (trt), control (ctl)) with randomization to group occurring after baseline assessment (to obviate observer bias), and three assessment periods (baseline, up to 3 months post baseline (immediate post) and 2 months post immediate post). There will be no assessment between games because the investigators' pilot indicated differences emerged only after both games were played. Parents and their children will come to the CNRC at each assessment point for measurement. Two weeks are allowed for each assessment period to permit obtaining the multiple days of diet and physical activity measurement. A two month follow up was selected because in the investigators' experience this is the longest period over which it is likely to detect behavior change maintenance post intervention and the analyses should emphasize predicting behavior change maintenance. The investigators are allowing for a three month intervention period. The briefest possible time to complete one of these games is 3 weeks each, or 6 weeks total (1.5 months). For example, during each session the child sets goals to change specific behaviors at specific meals/times on specific forthcoming days. These goals are distributed across one to five days after a session (depending on number of goal days and days selected by the child). The longest it would take a child to complete a game while likely retaining their immersion in the game story would be 45 days per game or 3 months. The database retains a record of sessions completed and goals attained to provide child feedback. Project staff will call the children if they did not complete a session within 2 days after an expected play date as indicated by email messages automatically sent at the completion of a session. We will schedule immediate post assessment for the treatment groups at the end of 18 completed sessions, and schedule control either at the end of completed sessions or 3 months (whichever comes first). Randomization to group will be achieved by sequentially entering names into a list with sequential positions on the list randomly assigned to group from a random number generator. Before study recruitment begins, 444 sequential IDs will be created and attached to a random number following a uniform distribution within a (0,1) interval generated in SAS by the study statistician. Each ID will have the same probability of being assigned any number within the interval. The IDs associated with the lowest and highest 222 random numbers will be assigned to the treatment and control groups, respectively.
1.2. Control Intervention. A wait list control group will be employed. Control group children will receive the intervention at the end of the 2 month post assessment.
1.3. Recruitment and Screening. The primary tool for recruiting children to participate in this project will be radio advertisements that target ethnic minority communities (African-American, Hispanic) with parents of children in the targeted age groups. The investigators have ample successful experience using this recruitment channel. Houston is the center of a large diverse metropolitan area of 5.6 million people (4th largest city in the US), approximately 15% of whom are African American, and 45% Hispanic. This is amply large to provide the sample needed. Listeners will be given a telephone number to call. A bilingual professional CNRC participant recruiter (Marilyn Navarrete) will receive those calls, answer questions, conduct a preliminary screen for target child: age, child speaks English, height, weight, brief medical history, access to a computer and the internet, and willingness to provide a blood sample, answer questions on the phone about diet, and wear an accelerometer for multiple days. Children passing the screen, or for whom passing is not clear, will be forwarded to a project staff who will answer any further parent questions, complete preliminary screening and schedule an appointment for baseline assessment. As back up, children will be recruited from a variety of other sources, including the CNRC participant data base (with names, ages, demographics and contact information on over 9800 children whose parents have indicated interest in their child participating in CNRC research projects), posters and fliers distributed around the Texas Medical Center (with over 95,000 employees), press release announcements by Baylor College of Medicine and presentations to area schools (public and private). The investigators recruited over 1600 children to participate in a PROP taste sensitivity epidemiology study using combinations of these methods, recruited 153 10-12 yo children for the pilot study, and have recruited thousands of other children across a broad variety of studies. To minimize barriers to participation, the child's transportation to and from each of the assessments will be paid by the grant, if necessary.
1.4. Cohort maintenance and tracking procedures for longitudinal study. Data will be collected in 25 waves of 17 or 18 children each. The waves are interdigitated to permit continuous use of staff for data collection. (The data collection team included in this budget can efficiently handle this number of participants, with overlap between waves.) Investigators will make every effort to obtain all data from each child in the 25 waves. At the baseline assessment, the investigators will obtain participant name, address, phone number, email address, and the name and phone number of two individuals likely to know how to contact the participant (in case of moving, etc). At each subsequent parent data collection period, this information will be updated. Reminder phone calls will be made and letters with "address correction requested" will be mailed out, if necessary, prior to follow up observations. Graduated monetary incentives will be provided to youth and parents who participate in each measurement. Flyers will also be mailed to the home address of record. If these techniques do not enable us to maintain contact with the family, the alternative contact individuals identified at the beginning of the study will be contacted. If this does not work, the investigators will submit the parent's name and address to a "FIND ANYBODY" website, where people can be located at minimal cost. All known avenues will be exhausted to contact the family to participate in follow up data collection activities. This comprehensive strategy should enable the investigators to maximize participation maintenance throughout the study.
1.5. Sample Size and Power. Intention to treat procedures will be followed. Based on standard deviations from previous studies, the standardized effects (differences/standard deviation) to be detected are 0.80 (MVPA), 0.78 (FV), and 0.02 (fasting insulin). Given a repeated measures analysis of covariance to control for baseline measures, one between groups factor (intervention, control), one within subjects factor (post 1, post 2), a correlation over time of 0.10, an alpha of 0.05, and 80% power, 400 participants are needed to detect a small standardized effect (=0.2). For the remaining hypotheses, power and sample size requirements are based on path analyses. Because of model complexity, there is no set standard for calculating sample size for structural equation/path models. Therefore, the sample size needed to assess the moderation and longitudinal mediation is based on (1) the rule of thumb, (2) the framework for power in covariance structure modeling, and (3) Monte Carlo simulation. It is recommended that there are 10-20 cases per estimated parameter, for realistic and ideal conditions, respectively. Given regression paths, variances, correlations, and auto-correlations, a model at three time points with two mediators, one outcome, and an intervention effect would have 36 parameter estimates. A final sample of 400 just exceeds the minimum 10:1 case-parameter ratio. Using MacCallum's SAS power analysis for covariance structures, a sample of 400, 10 variables, and 22 degrees of freedom, would provide 80% power to provide significant support for a model yielding good fit. The Monte Carlo simulation used 10,000 repetitions, 400 participants, normally distributed data, 10 variables (plus intervention by demographic interactions), and all path estimates in the hypothesized direction (magnitudes=0.17). Given acceptable (<5%) parameter and standard error bias and acceptable (0.91-0.98) coverage, the range of power for path estimates were 0.84-0.97. Given an anticipated 10% sample attrition over the 7 months of participation in the trial (based on experience), the investigators inflated the recruited sample to 444.
1.6. Intervention Implementation. Children will play the game at home. Each intervention child will be provided with a manual and emailed a download address. The child can email or call the project office if problems develop. A project intervention coordinator will be fully trained in how to implement the project, identify and correct common technical difficulties, and collect and manage data. The intervention coordinator will attend to and answer the emails and phone calls. The intervention coordinator will monitor game completion and inform data collection staff when children can be scheduled for immediate post game data collection. Each game session should take about 45 to 60 minutes to complete with an ability to go back and replay some of the mini-games.
1.7. Quality Assurance of the Intervention. During implementation of the efficacy trial, the intervention coordinator will monitor child use of game by organizing and reviewing email messages each time a child completes a session, answer call-in questions, repair minor malfunctions of hardware or software system, arrange for speedy repair of larger malfunctions, and record all the above.
1.8. Child data collection procedure. Project data collection staff will be blinded to group. For data collected on PDAs or iPads, children will be logged into the PDA using a user name and password; questions will appear on the screen one at a time, and participant will be prompted to select an answer. Program will not progress until an answer has been selected, which minimizes, if not effectively eliminates, missing values. Actual names and corresponding user names, passwords, and codes will be stored in a separate location to maintain confidentiality. Some process evaluation data (e.g. log on rates, progression through game, time spent on certain activities, goal attainment) will be automatically collected during the intervention and emailed to a secure central server at the end of each session. Other process evaluation data will be collected and maintained by interviewers. Three 24hrDR will be conducted using ASA24-Kids, web-based dietary data collection software. Accepted procedures will be followed. To optimize use of trained data collectors and equipment (e.g. accelerometers) children will participate in 25 groups/cohorts/waves of approximately 17-18 children each staggered over 2.5 years. The importance of these waves are to continuously use highly trained staff over long time intervals while insuring minimal overlap in use of limited equipment (e.g. accelerometers, PDAs). These time intervals are not precise. Some children will finish gameplay before the time allowed, and brought in for data collection out of sync with the wave to ensure that immediate post data collection occurs soon after game-play. Seasonal and other holidays will lengthen some of these time intervals. Unanticipated, yet not unexpected, cataclysmic events, e.g. hurricanes, other severe weather, will also play havoc with neatly planned schedules. The investigators have allowed some flexibility in anticipation of such events. Starting each wave with 18 children provides enough flexibility in time at the end to allow us to complete data collection for this trial and thoroughly conduct data editing and analyses.
1.9. Parent data collection procedure. Parent data will be collected by PDAs and questionnaires, where necessary, in English or Spanish. Parents will select their preferred language prior to baseline. To maintain confidentiality, parents will be assigned a unique user number. The master list of actual and user names will be kept in a locked room at CNRC.
1.10. Incentives. Incentives will be provided for child participation in data collection. Graduated incentives are utilized to enhance the likelihood youth and parents will participate in all data collection points. Because of the required blood draws, child incentives are: $60 for baseline assessment; $65 for immediate post assessment; and $70 for 2-month follow up. Participants will receive a healthy snack in light of their needing to fast prior to data collection. Parents/legal guardians will also receive graduated incentives for participating in interviews as follows: $20 for the immediate post-intervention questionnaire and $25 for the 2-month post questionnaire.
Measures. Outcome variables are those which should change as a result of the intervention. Mediating variables are those which provide component mechanisms by which the intervention produces its outcome: changes in mediating variables should be correlated with changes in outcome. Moderating variables are those for which the outcomes may vary. Confounding variables minimize the desired differences across the experimental conditions. Process evaluation determines whether the intervention was delivered and worked as designed.
2.1. Blood Related Variables. Since several intervention studies have impacted diabetes risk factors, but not any of the various derivatives of ht and wt, the investigators believe it is important to measure both fasting insulin and glucose. Since fasting glucose is tightly regulated the investigators do not expect to impact it, but we will monitor it. Several studies have had beneficial impact on fasting insulin including the recently completed HEALTHY study for which the investigators were a participating site.
2.2. FV Intake. Food frequency questionnaires (FFQ) are a standard method of diet assessment among adults. FFQs, however, have demonstrated problems in reliability of assessment among children 10-12 years.
2.3. Physical Activity. Physical activity will be assessed using the latest Actigraph GT3X accelerometer.
2.4. Anthropometrics. Body mass index (BMI; kg/m2) is the national criterion for the definition of overweight and obese among children and adolescents. Participant's height will be measured to the nearest 0.1 cm twice using a stadiometer (Shorr Height Measuring Board; Olney, MD) and the mean of the two recordings calculated. Body weight will be measured to the nearest 0.1 kg twice using a calibrated scale (Seca Research Model scales; Vogel and Halke, Hamburg, Germany) and the mean of the two recordings calculated. BMI will then be computed as well as the participants' age and gender specific BMI z-score which will be obtained from the CDC web site. Waist circumference will be assessed using a Figure Finder tape (Novel Products, Inc., Rockton, IL), because central adiposity has been independently associated with an increased risk of developing the metabolic syndrome. Triceps skinfold will be assessed, using a Lange caliper, since it correlated highest with DEXA assessed percent body fat. Standardized procedures for assessing these variables twice during each measurement period with the mean of the two recordings used in analyses will be used. To assess inter-rater reliability a second, independent data collector (not aware of the initial assessments) will repeat ten percent of all measurements.
2.5. FV, W preferences, self efficacy, and intrinsic motivation. Preferences, self efficacy, and intrinsic motivation are the most commonly reported significant influences on dietary intake. Preferences are the extent to which a person enjoys eating a group of foods. Self efficacy is the confidence one has in being able to overcome barriers to doing a behavior. Intrinsic motivation is the extent to which someone does a behavior to please oneself versus please others. Items to assess preferences, self efficacy, and outcome expectations for the targeted behavior change (increasing FV consumption to five or more servings and W to eight servings a day) will be obtained from measures developed and tested by this team.
2.6. PA Psychosocial Variables. Similar to diet, PA preferences/enjoyment, self efficacy, intrinsic motivation and home equipment availability have been demonstrated to influence children's physical activity, and will be assessed in this study.
2.7. Energy Balance Knowledge. The investigators are developing a measure of Energy Balance Knowledge. Energy Balance is a complex set of ideas requiring a person/child to know that foods are sources of calories; physical activities burn calories; different levels of calories are associated with different food intakes and portion sizes; calories expended are associated with different kinds of activities, intensity of effort and duration; the level of calories at balance for the respondent; etc. The investigators are developing items and honing the tool to make it appropriate for 10-12 year old children.
2.8. Transportation/immersion/liking. Transportation (also called "immersion") is "a distinct mental process, an integrative melding of attention, imagery and feeling", which can "draw" people into a story, "lose" themselves, or capture their complete attention. Immersion should enhance a participant's attention to the behavior change procedures inserted in the game. Recent work has led to new validated measures of immersion in game play. This is a 33 item questionnaire with a 5 category response scale from strongly disagree to strongly agree. In addition, standard questions used in the pilot trial in regard to whether the children liked the game will be employed. All these questions will be applied to each game.
2.9. Social desirability. Social desirability of response reflects giving answers that are socially acceptable or expected and has been observed in regards to self-report in both adults and children, including the investigators' pilot study. Because this may bias responses, thereby affecting the validity of the study, it will be assessed using the 9-item "Lie Scale" from the Revised Children's Manifest Anxiety Scale, which has a yes/no response format, and "lie" score determined by summing the "yes" responses. The instrument has shown good reliability and validity in children across a variety of ethnic groups, including the pilot study. This instrument will be programmed into the PDA and completed at baseline by the students.
2.10. Demographics. Parents will be asked to provide marital status, current employment status, race/ethnicity, number of children living in the home, highest educational level in household, and annual household income, as part of the informed consent form.
2.11. Parent reported Home FV availability and accessibility. A strong predictor of consumption of FV in the home is whether FV are in the home and easily accessible. The investigators GIMME 5 curriculum changed home FV availability; validity correlations of parent report with home observations were high (r=0.55).
2.12. Process Evaluation. A thorough process evaluation for each component of the intervention will be conducted. Process evaluation concerns the documentation of delivery of a program, factors that influence its delivery and factors resulting from program delivery. The investigators will assess: recruitment of participants, maintenance of participation, context of implementation, implementation (fidelity and dose), reach, barriers to implementation, exposure to program, initial use of program materials/tasks, continued use of the program, materials/tasks, and contamination. Much of the implementation and exposure assessments will be documented using web collected data records of Diab and Nano components. Diab and Nano have been programmed to automatically monitor and record log on and goals attained, as youth navigate and play the game. The process data will be emailed to the Intervention Coordinator after each session and stored in the project data base.
Specific Aim 2. Conduct analyses of the efficacy evaluation of Diab and Nano. 3.1. Data management. Code books will be created for all variables. Electronic data files will be created in which to enter and store data using latest available software. Any data entered by hand will be double entered and reviewed to minimize data entry errors. Data sets will be backed up nightly on the BCM secure server. Any hard copies of data generated by this study will be kept in a locked room at CNRC.
3.2. Partial or missing data. The longitudinal analysis models in this proposal handle available-data analyses. Available-data methods are more efficient because they incorporate the partial information obtained from those who dropout. During statistical analysis, the issue of missing data will be addressed. The investigators will apply imputation procedures for the missing responses following dropout, such as multiple imputation, in which each missing value is replaced with several plausible values. Several statistical procedures are now available to address issues related to missing or partial data. Little's likelihood ratio test will be used to test whether the data are missing completely at random.
3.3. Testing Hypotheses. Field and range checks will be conducted. Distributional characteristics will be assessed and outliers checked. Prior to inferential procedures, extensive descriptive statistical analyses of the outcome and predictor variables will be conducted. Standard descriptive statistics including means, standard deviations, ranges, box plots, histograms, and frequencies will be calculated where appropriate. Normalizing transformations will be explored as appropriate. Bivariate association will be evaluated using Pearson correlations (or Spearmann correlations, depending on distributional characteristics), scatter plots and contingency tables. Tests will be conducted of differences between those included vs. excluded, treatment vs. control, and those completing all data collection and those not. Analyses and presentation of data will be in accordance with the CONSORT guidelines with the primary comparative analysis being conducted on an intention-to-treat basis with due emphasis placed on confidence intervals for the between arm comparisons. Descriptive statistics will be used to ascertain imbalance between arms at baseline. A mixed model approach to account for the repeated measures among children will be conducted to test hypothesis 1: (H1) Children playing Diab and Nano will increase their FV intake by at least 1.0 servings/day, increase MVPA by at least 10 min/day, and decrease fasting insulin by 2 μU/dl, as compared to the control group. The mixed model will allow for investigating the correlation of the repeated measures over time. The model will contain time, a within subjects factor (post 1, post 2), and study group, a between subjects factor (intervention, control), and control for the baseline outcome. Separate models will be used for each set of dependent variables (fasting insulin, FV intake, PA). The analysis of variance portion of the model will contain main effects for time and group, as well as a time by group interaction. A significant group main effect will indicate a difference in the outcome after the intervention. The model will control for potential confounding variables (e.g., demographic characteristics, duration of game play, immersion, number of sessions completed). A longitudinal path model will be used to test hypotheses 2, 3, and 4: (H2) Child diet, MVPA and fasting insulin changes from playing Diab and Nano will not be moderated by demographic characteristics. To test this hypothesis, interactions of demographic characteristics (gender, age, ethnic/racial groups, SES) with group will be included in a longitudinal mediation model. The magnitude of moderation will be determined from the standardized regression coefficient. (H3) Child fasting insulin change will be mediated by changes in diet and PA. (H4) Child diet and PA change will be mediated by changes in preferences and outcome expectancies for FV and PA. Path models, a special case of structural equation models, utilize a series of steps to test the mediational processes that involve tests of added components, omitted paths, and assumption of stationarity (levels of the variable remain unchanged over time), as well as estimating the effects of the mediators. Because of the longitudinal model, the autoregressive effects are modeled as lags where baseline measures are predictors of post 1 measures and post 1 measures are predictors of post 2 measures, thus the temporal order is preserved. The ultimate goal is to identify the most parsimonious model that exhibits acceptable fit, evaluated using the same indication as for general structural equation models. Because there is no one standard for determining the fit of the model, a range of fit statistics, based on Hu and Bentler's criteria, will be used to assess model fit. The indicators and acceptable criteria include: the model chi-square goodness of fit (with a p value > 0.15), the root mean square error of approximation (with a value <0.05 indicative of good fit and <0.08 of acceptable fit), the comparative fit index and the non-normed fit index (with >.90 indicating acceptable fit). Because the model fit indices are influenced by sample size, the values of the standardized residuals (< 2.58 acceptable), the proportion of variance explained by the indicators, and model modification indices will also be used to evaluate the fit of the model. To assess mediation, the total, direct, and indirect effects of the intervention on the outcome will be evaluated. To test the statistical significance of the mediation with three time points, only the indirect effect of the intervention on the outcome at post 2 through the mediators at post 2 will be used to assess the mediated changes in FV and PA. Because of the sample size and model complexity, mediation analyses will be conducted for FV and PA separately.
- Timeline. The proposed research will encompass 3 years, divided into two phases: implementation (2.5 yrs), and analysis (0.5 yrs). Although any individual's experience in the project will cover approximately 7 months (including a maximum of 3 months for game play), the investigators will need to efficiently use staff and equipment by using a rolling enrollment across 2.5 years and allow for data analysis in last half year.
|United States, Texas|
|Children's Nutrition Research Center, Baylor College of Medicine||Not yet recruiting|
|Houston, Texas, United States, 77030|
|Contact: Alicia Beltran, MS 713-798-0503 firstname.lastname@example.org|
|Contact: Janice Baranowski, MPH, RD 713-798-6763 email@example.com|
|Principal Investigator: Tom Baranowski, Ph.D.|
|Principal Investigator:||Tom Baranowski, PhD||Baylor College of Medicine|