Examining Influence of Social Media Ads on Black and White Adolescents' Food Choices
Phase: NA
Conditions: Food Choices
Sponsor: NYU Langone Health

 
 
Official Title: 
Examining Influence of Facebook Ads on Black and White Adolescents' 
Food Choices   
NCT Number: 
NCT05380505 
Study Number: 
20-01796 
Document Type:  
Study Protocol and Statistical Analysis Plan 
Date of the 
Document: 
• 
 December 4, 2020 
 

Study Number: s20-01796 
Version Date: 12/03/20 
Examining the Influence of Facebook Ads on Black and 
White Adolescents’ Food Purchases (s20-01796) 
Principal Investigator:   Dr. Marie Bragg 
Co-Investigators:          Dr. Andrea Troxel 
Collaborators:   
Dr. Emily Balcetis 
  Dr. Christina Roberto* 
Purpose of the Study and Background 
Purpose of the Study 
Poor diet and excess weight during adolescence predicts excess weight and diet-related cancers 
during adulthood, yet there is little research on the risk factors that contribute to weight gain among 
adolescents. The National Academy of Medicine identifies exposure to food advertisements (ads)as a 
major predictor of poor diet among children (<12 years of age) because studies have shown that 
children who are exposed to food ads consume more calories than children who are exposed to non-
food ads. The few food ad studies that have included adolescents (13–17 years of age) found 
associations between self-reported exposure to television (TV)food ads and poor diet, but we do not 
know which mechanisms explain this relationship. It is also well established that food companies 
promote their least healthy products to Black consumers more than White consumers and perceive 
Black youth as trendsetters. But it is not known whether seeing racially congruent ads (i.e., the 
person in the ad and the viewer are the same race) places Black adolescents at higher risk of poor 
diet relative to Whites. Finally, most food ad research is based on TV ads, but food companies are 
increasingly targeting adolescents on social media. The overall objective of our three studies is to 
identify the extent to which exposure to Facebook food ads increases the number of calories 
purchased and consumed by Black and White adolescents. Guided by strong preliminary data, we 
will test three aims: 1)To evaluate the extent to which exposure to racially congruent vs. incongruent 
Facebook food ads causes Black vs. White adolescents to purchase more calories for a snack;2)To 
determine the extent to which exposure to many vs. few “likes” on Facebook food ads causes Black 
and White adolescents to purchase more calories for a snack; and 3)To test the degree to which 
visual attention to unhealthy foods, racially congruent people, and/or “likes” in Facebook ads explains 
the relationship between ad exposure and calorie intake.  
 

Background 
Clear diet-related disparities exist among adolescents in the United States, and poor diet is linked to 
colon, kidney, and liver cancers.1,2,3,4,5,6 Black adolescents have higher rates of overweight and 
obesity (38.2%) than White adolescents(26.3%)7and face higher risks for diet-related cancers later in 
life.8And the prevalence of obesity continues to increase among adolescents from low-income 
households, but not other income groups. Biologically, adolescents may make unhealthy food choices 
due to underdeveloped impulse control and greater neural sensitivity to reward in the nucleus 
accumbent compared to adults and children.9 Psychologically, adolescents are more likely than 
adults to focus on the present instead of long-term health10,11and a strong need to belong leads them 
to mimic cultural influences (e.g., social media, television [TV]).12,13Further, the National Academy of 
Medicine identifies exposure to food advertisements (ads) as a major predictor of poor diet among 
children (<12 years of age), and eye-tracking studies show overweight children visually attend to food 
ads more than non-overweight peers.14But far less is known about the influence of food ads on 
adolescents (age 13–17 years).15, Some studies show adolescents’ self-reported food ad exposure is 
linked with poor diet,16,17,18but we do not know which mechanisms explain this relationship. It is also 
well established that food companies promote their least healthy products to Black consumers more 
                                               
1 de Ferranti SD, Gauvreau K, Ludwig DS, Neufeld EJ, Newburger JW, Rifai N. Prevalence of the metabolic syndrome in 
American adolescents: findings from the Third National Health and Nutrition Examination Survey. Circulation. 
2004;110(16):2494-2497. 
2 Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH. Prevalence of a metabolic syndrome phenotype in adolescents: 
findings from the third National Health and Nutrition Examination Survey, 1988-1994. Arch Pediatr Adolesc Med. 
2003;157(8):821-827. 
3 Lobstein T, Baur L, Uauy R, IASO International Obesity TaskForce. Obesity in children and young people: a crisis in public 
health. Obes Rev. 2004;5 Suppl 1:4-104. 
4 Dietz WH. Health consequences of obesity in youth: childhood predictors of adult disease. Pediatrics. 1998;101(Supplement 
2):518-525. 
5 vTodd AS, Street SJ, Ziviani J, Byrne NM, Hills AP. Overweight and obese adolescent girls: the importance of promoting 
sensible eating and activity behaviors from the start of the adolescent period. Int J Environ Res Public Health. 2015;12(2):2306-
2329. 
6 Alberga AS, Sigal RJ, Goldfield G, Prud’homme D, Kenny GP. Overweight and obese teenagers: why is adolescence a critical 
period? Pediatr Obes. 2012;7(4):261-273. 
7 Data Resource Center for Child & Adolescent Health. Child and Adolescent Health Measurement Initiative. Data Resource 
Center for Child & Adolescent Health.  
8 DeSantis C, Naishadham D, Jemal A. Cancer statistics for African Americans, 2013. CA Cancer J Clin. 2013;63(3):151-166. 
9 Casey BJ, Jones RM, Hare TA. The adolescent brain. Ann N Y Acad Sci. 2008;1124:111-126. PMCID: PMC2475802. 
10 Harris JL, Brownell KD, Bargh JA. The Food Marketing Defense Model: Integrating Psychological Research to Protect Youth 
and Inform Public Policy. Soc Issues Policy Rev. 2009;3(1):211-271. 
11 Pechmann C, Levine L, Loughlin S, Leslie F. Impulsive and Self-Conscious: Adolescents’ Vulnerability to Advertising and 
Promotion. Journal of Public Policy & Marketing. 2005;24(2):202-221. 
12 Yau JC, Reich SM. “It’s Just a Lot of Work”: Adolescents’ Self-Presentation Norms and Practices on Facebook and 
Instagram. J Res Adolesc. 2018;65:169. 
13 Ritson M, Elliott R. The Social Uses of Advertising: An Ethnographic Study of Adolescent Advertising Audiences. J Consum 
Res. 1999;26(3):260-277. 
14 van Meer F, Charbonnier L, Smeets PAM. Food Decision-Making: Effects of Weight Status and Age. Curr Diab Rep. 
2016;16(9):84. 
15 Cairns G, Angus K, Hastings G, Caraher M. Systematic reviews of the evidence on the nature, extent and effects of food 
marketing to children: A retrospective summary. Appetite. 2013;62:209-215. 
16 Scully M, Wakefield M, Niven P, et al. Association between food marketing exposure and adolescents’ food choices and 
eating behaviors. Appetite. 2012;58(1):1-5. 
17 McClure AC, Tanski SE, Gilbert-Diamond D, et al. Receptivity to television fast-food restaurant marketing and obesity among 
U.S. youth. Am J Prev Med. 2013;45(5):560-568. PMCID: PMC3934414. 
18 Story M, Neumark-Sztainer D, French S. Individual and environmental influences on adolescent eating behaviors. J Am Diet 
Assoc. 2002;102(3 Suppl):S40-S51. 

than White consumers19,20,21,22,23,24,25and perceive Black youth as trendsetters.26But it is not known 
whether seeing racially congruent ads(i.e., the person in the ad and the viewer are the same race) 
places Black adolescents at higher risk of poor diet relative to White adolescents. Finally, most food 
ad research is based on TV ads, but social media is a new advertising frontier that may pose serious 
health risks. Adolescents’ daily social media use (2.0 hours) now rivals time spent watching TV (2.6 
hours),32>90% of them use social media,27and they command $175billion in spending power.16And 
global expenditures for social media ads have now surpassed $35billion annually.28 
Study Design 
The overall objective is to determine the extent to which racially congruent Facebook food ads 
influence adolescents’ food purchases and actual caloric intake. We will accomplish these objectives 
by conducting three randomized controlled trials (RCTs). The first two aims trials will involve 15-
minute online surveys in which participants (Black and White adolescents) will rate ads then complete 
a “food purchasing” task through a virtual vending machine. The third trial will involve an in-person, 
hour long lab study where participants will be shown ads while investigators covertly monitor their eye 
movements. The first RCT will answer the research question “Does exposure to racially congruent vs. 
incongruent Facebook ads for unhealthy foods cause Black (vs. White) adolescents to purchase 
snacks with more calories?”. The second RCT will answer: “Does exposure to many “likes” (vs. few 
“likes”) on Facebook ads for unhealthy foods lead to even higher calorie purchases for both Black and 
White adolescents?”. Lastly, the hour-long study will answer the question: “To what extent does the 
visual attention to foods vs. people vs. “likes” in ads predict adolescents' caloric intake?” (Aim 3). For 
the first two online survey trials, we will measure the average calories purchased for a snack and for 
the last trial we will measure the average calories consumed.  
                                               
19 Harris JL, Schwartz MB, LoDolce M, et al. Sugary drink FACTS 2014: Some progress but much room for improvement in 
marketing to youth. Rudd Center for Food Policy and Obesity: New Haven, CT. 2014.  
20 Harris JL, Schwartz MB, Munsell CR, et al. Fast food FACTS 2013: Measuring progress in nutrition and marketing to children 
and teens. Yale Rudd Center for Food Policy and Obesity. 2013.  
21 Grier SA, Kumanyika S. Targeted marketing and public health. Annu Rev Public Health. 2010;31:349-369. 
22 Harris JL, Shehan C, Gross R, et al. Food Advertising Targeted to Hispanic and Black Youth: Contributing to Health 
Disparities. Rudd Center for Food Policy & Obesity; 2015. 
23 Story M, French S. Food Advertising and Marketing Directed at Children and Adolescents in the US. Int J Behav Nutr Phys 
Act. 2004;1(1):3. 
24 Powell LM, Wada R, Kumanyika SK. Racial/ethnic and income disparities in child and adolescent exposure to food and 
beverage television ads across the U.S. media markets. Health Place. 2014;29:124-131. 
25 Powell LM, Szczypka G, Chaloupka FJ. Adolescent exposure to food advertising on television. Am J Prev Med. 2007;33(4 
Suppl):S251-S256. 
26 Zmuda N. How Coke Is Targeting Black Consumers. Advertising Age. http://adage.com/article/the-big-tent/marketing-coke-
targeting-african-american-consumers/137716/. Published July 1, 2009. Accessed June 24, 2017. 
27 Teens, social media, and technology overview 2015: smartphones facilitate shifts in communication landscape for teens. Pew 
Research Center. http://assets.pewresearch.org/wp-
content/uploads/sites/14/2015/04/PI_TeensandTech_Update2015_0409151.pdf. Published April 9, 2015. Accessed September 
27, 2017. 
28 Cohen D. STUDY: Global Social Media Ad Spend to Reach $36B in 2017. AdWeek.  

Characteristics of the Research Population 
Number of Subjects 
For this study we intend to recruit a total of 3,032 adolescents (1,252 in Aim 1; 1,300 in Aim 2; and 
480 in Aim 3—the in-person lab study). Participants will be selected through Dynata, a survey firm. A 
power analysis was conducted to determine the sample size in which the size of 1,252 participants 
provides 80% power to detect an effect size of 0.2 SD between conditions.  
Gender of Subjects 
We will recruit males and females because research shows pre-adolescent males consume more fast 
food than females. We will therefore examine differences in responses based on sex. Adjustment of 
primary analysis will be undertaken to accommodate any imbalances.  
Age of Subjects 
We intend to recruit a total sample of 3,032 adolescents ages 13-17 years. This age group is chosen 
as a follow up to the online within-subject pilot experiment and because of the purpose of the study 
being to gain more knowledge specifically on how targeted ads affect this age group. 
Racial and Ethnic Origin 
We will recruit 3,032 adolescents that identify as only non-Latino White or only Black/African 
American. The purpose being that targeted ads usually appeal to Black youth in particular. This 
marketing tactic is a potent one worth further investigation since most of the targeted ads are for 
unhealthy foods. And black adolescents experience higher rates of obesity and report higher social 
media use than their peers. We will use the White participants as a comparison group since they are 
featured in most ads and are, therefore, unlikely to experience heightened effects from racially 
targeted ads. There are plans to study other racial/ethnic groups in future research, but we would not 
be adequately powered in this proposal to understand the effects for each racial/ethnic group.  
Inclusion Criteria 
Participants must: 1) be 13–17 years of age; 2) identify as only non-Latino White or only Black/African 
American; 3) report that they log into Facebook at least once daily; and 4) read and speak English. 
We will include the SCOFF29, screening tool—a five-item, validated eating disorders assessment—at 
the end of the study. We will not exclude adolescents who report symptoms. If a participant reports 
having symptoms, we will provide them resources as described in our Human Subjects attachments. 
                                               
29 Hill LS, Reid F, Morgan JF, Lacey JH. SCOFF, the development of an eating disorder screening questionnaire. 
Int J Eat Disord. 2010;43(4):344-351. 
 

Exclusion Criteria 
Any criteria not met as listed above will bar an adolescent from participating in the study.  
Vulnerable Subjects 
In this study we will include 13–17 year olds because they are the target population and highly 
susceptible to targeted food ads. 
Methods & Procedure 
Aim 1: After obtaining parental permission and assents, participants will view and rate 18 ads in the 
online survey. They will view and rate one ad before viewing and rating the next ad. They will then 
complete the food purchasing task. In this task, six foods and six beverages from the brands that 
target adolescents the most will appear in a virtual vending machine embedded in the online survey. 
Half of the food items will be healthy snacks and half will be unhealthy, as scored by the Nutrient 
Profile Model, a validated nutrition rating tool designed by nutritionists and used in public health 
studies. Three of the beverages will be sugar-sweetened beverages and three will be the zero-calorie 
versions of those sugar-sweetened beverages. Participants will select one food item and one 
beverage they would like to consume. To incentivize actual purchasing behavior, we will tell them we 
will provide $8 for their snack purchases and they can keep any money they choose not to spend. We 
will also tell them that we will mail the items to their home. This approach will incentivize adolescents 
to consider the trade-offs of keeping money vs. spending it on snacks, which is more representative 
of real-world purchasing behavior. In reality, we will provide the $8 at the end of the study instead of 
mailing the items. After the food purchasing task, participants will complete demographic questions 
and then receive $25 for participating and $8 for their snack purchases 
 
Aim 2: Parental consent and adolescent assent process will be obtained as described for Aim 1. After 
providing assent, participants will be randomized to view and rate 18 racially congruent Facebook 
food ads that feature many (>10,000) or few (<100) “likes.” After viewing each ad, they will complete 
the ad rating questions for that ad (Table 2) before proceeding to the next ad. Participants will then 
complete the same food purchasing task described in Aim 1(section E.3.4.). Finally, they will 
complete the demographic questions. At the end of the study, they will view a debriefing statement 
similar to the statement from Aim 1 (sectionE.3.4). Dynata will then provide each participant with $25 
compensation and $8 for the purchased snack products. 
 
Aim 3: Participants will visit our collaborator Dr. Balcetis in her lab —located at NYU Washington 
Square Campus—and sit in front of a Tobii eye-tracking computer. The computer monitor displays an 
advertisement and youth view it as they would any other type of document on a computer. Eye-
tracking technology allows for the documentation of fixations, an objective measure of attention, 
which occurs when an individual pauses to examine or interpret a component of an advertisement or 
image. The Tobii eye tracking device allows moderately free head movements. It returns a real-time 
estimate of the left and right eye gaze positions on the screen, as well as the 3D position of the two 
eyes with respect to the screen center. After obtaining consent and assent in-person, we will ask 

participants to “answer a few questions about how they are feeling today” and hunger will be one of 
the items they rate, which will allow us to unobtrusively measure baseline hunger and control for it 
during analyses. We will then tell them that we will show them a series of images that are for their 
viewing pleasure, and that we have snacks and a drink they can enjoy as a thank you for 
participating. Participants will view 30 ads per block that appear at a predetermined rate to hold total 
viewing time constant across all ads. Researchers will calibrate the eye-tracking computer using a 
guise developed by our collaborator Dr. Balcetis that asks the participant to count the number of 
times a ball bounces on the screen (n = 6), "so you can take a moment to let your mind rest after 
rushing through the busy city to arrive at the lab today." Dr. Balcetis has used this technique on 
>1,000 participants and <1% noted suspicion. 
 
 During the eye-tracking task, snacks will be positioned in bowls on a Cardinal Detecto stainless steel 
scale that looks like a serving tray but transmits weight information wirelessly to the control room. 
Similar to previous food ad studies,30,31,32we will include two unhealthy snacks and two healthy 
snacks with a 20-ounce bottle of water. The unhealthy snacks will include M&Mcandies (high-fat, 
sweet) and Doritos chips (high-fat, savory). The healthy snacks will include Quaker Rice Cakes (low-
fat, savory) and grapes (low-fat, sweet). To minimize the risk of ceiling effects (i.e., where participants 
eat all the food), we will include 150g of each snack: M&Ms (296-ml bowl), Doritos and Quaker Rice 
Cakes (1,419-ml bowls), and grapes (473-ml bowl).Our pilot data also suggest—and a systematic 
review reinforces15—that most participants eat during food ad studies. To conclude the study, 
participants will complete demographic questions (Table 1). We will use a funneled debriefing 
procedure to ask participants what they believed was the purpose of the study so we can test for 
moderation of effects as a function of awareness during analyses. We will disclose the purpose of the 
study, solicit questions, conduct a second assent procedure after disclosing eye-tracking was used 
and was ethically approved, and provide the same information from the debriefing form in Aim 1 and 
2 (section E.3.4). Finally, we will distribute $35 compensation in cash and subway/bus fare to cover 
travel costs. Those who travel by other means will also receive the travel fare. 
Data Analysis 
Aim 1- Statistical considerations: Power and sample size: We wish to have adequate power to detect 
a difference of ~20% in calories purchased between the groups. Data from studies on adolescents’ 
snack choices indicated an average of 400–600 calories. Thus, we wish to detect a between-group 
difference of ~100 calories. Estimates of standard deviation of food choices vary widely. Most 
estimates are 100–300 calories, but to be conservative, and because we do not have direct data on 
purchases in an online survey, we assume a standard deviation of 400calories. Accounting for 
participants who fail the attention check item, and using a two-sided Type I error rate of 0.017to 
control the experiment-wise error rate to 0.05, a final sample size of 1,252 participants (100 pre-test 
participants that will not be part of the final sample, plus 288 per group in each of the four conditions = 
                                               
30 Harris JL, Bargh JA, Brownell KD. Priming effects of television food advertising on eating behavior. Health Psychol. 
2009;28(4):404-413. 
31 Dias M, Agante L. Can advergames boost children’s healthier eating habits? A comparison between healthy and non-healthy 
food. J Consumer Behav. 2011;10(3):152-160. 
32 Harris JL, Speers SE, Schwartz MB, Brownell KD. US Food Company Branded Advergames on the Internet: Children’s 
exposure and effects on snack consumption. Journal of Children and Media. 2012;6(1):51-68. 

1,252 total participants)provides 80% power to detect a difference of 80 calories between the groups 
who see racially congruent vs. racially incongruent ads. This sample size also provides 80% power to 
detect a difference of 113 calories between White adolescents who see racially congruent ads and 
Black adolescents who see racially congruent ads. Secondary outcomes: This sample size provides 
80% power to detect an effect size of 0.2 standard deviation (SD)between outcomes. Analytic plans: 
Descriptive analyses: All data will be summarized prior to analysis, using means, medians, ranges, 
and standard deviations for continuous variables and frequencies for categorical variables. BMI-z 
scores, which a readjusted for age and sex, will be calculated using Centers for Disease Control 
growth charts. Participants who fail our data integrity check questions will be excluded. This is 
expected to be ~9% of participants based on our pilot studies and previous work with 
adolescents.33We will assess balance by randomization status with respect to demographic and 
behavioral factors. Adjustment of primary analyses will be undertaken to accommodate any 
imbalances 
 
Analysis of primary outcome: Linear regression will be used to evaluate whether the number of 
calories purchased by the adolescents who viewed racially congruent ads differs from those who 
viewed racially incongruent ads. If the calorie count data are skewed, a suitable transformation (e.g., 
log) will be applied to improve the approximation of normality. To evaluate our hypothesis that Black 
adolescents—compared to White adolescents—will purchase more calories after viewing racially 
congruent ads, an additional model will also include a term for participant race, as well as an 
interaction term between participant race and ad congruence to determine if there is a differential 
association. We will also run all models controlling for eating restraint and presence of eating 
disorders symptoms to examine if those factors affect the number of calories purchased by 
adolescents. Analyses of secondary outcomes: We will use linear regression models that include 
participant race, racial congruence, and the interaction of the two as predictors; emotional responses 
to the ads and time spent viewing ads will be our outcomes. To investigate affective responses to the 
ad as a potential mediator for the relationship between the type of ad viewed and calories purchased, 
an additional model will include participant race, racial congruence of the ads, and an interaction 
term, as well as affective responses to the ads as predictors of calories purchased. We Will assess 
whether associations between calories purchased and the racial congruence term and the interaction 
between racial congruence and participant race term are weakened by the addition of affective 
response to the model. We will use the Bonferroni-holm procedure to correct for multiple comparison 
 
 
Aim 2- Statistical considerations: Power and sample size: We wish to have adequate power to detect 
a difference of ~20% in calories purchased between the conditions. As in Aim 1, we use data from 
studies on adolescents’ snack selections to inform power calculations. Using a two-sided Type I error 
rate of 0.017 to control the experiment-wise error rate at 0.05, assuming a SD of 400 calories, and 
accounting for some participants to fail an attention check item, a sample size of 1,200 participants 
(600 in each of two conditions = 1,200 total, not including the 100 pretest participants) provides 80% 
power to detect a difference of 78 calories between teens viewing ads with many “likes” vs. few 
“likes.” This sample size also provides 80% power to detect a difference of 110 calories between 
White adolescents and Black adolescents who see ads with many “likes.” Secondary outcomes: This 
                                               
33 Bragg MA, Miller AN, Kalkstein DA, Elbel B, Roberto CA. Evaluating the influence of racially targeted food and beverage 
advertisements on Black and White adolescents’ perceptions and preferences. Appetite. 2019;140:41-49. 

sample size provides 80% power to detect an effect size of 0.2 SD between conditions. Analytic 
plans: Descriptive analyses: Data will be summarized as described in Aim 1. We will assess balance 
by randomization status with respect to demographic and behavioral factors. Adjustment of primary 
analyses will be undertaken to accommodate any imbalances. Primary outcome: Linear regression 
will be used to evaluate differences in the mean calories purchased between conditions, with 
appropriate transformations to improve the approximation of normality if necessary. To explore 
whether the effect of many vs. few “likes” varies by race, we will include participant race as a main 
effect, as well as an interaction term between race and condition. We will also use linear regression to 
adjust for demographic and behavioral characteristics to investigate how these factors relate to 
responsiveness to ads. We will also conduct sensitivity analyses to control for the presence of eating 
disorder symptoms measured at the end of the study. Finally, participants who fail our data integrity 
check questions will be excluded. This is expected to be <9% of participants based on our pilot 
studies. Secondary outcomes: We will use linear regression models to assess the relationships 
between the number of “likes” on the ad and cognitive and emotional responses as well as time spent 
viewing ads. We will evaluate whether the association between the number of “likes” and calories 
consumed is moderated by affective responses to the model. The Bonferroni-Holm procedure will be 
used to correct for multiple comparisons.  
 
Aim 3- Statistical considerations: Power and sample size: We based our sample size on the 
expectation of a racial congruence effect that is small in size for White adolescents (0.2) and larger 
for Black adolescents (0.3). West our final sample size with the requirement of 80% power to detect 
the smallest correlation coefficient (at least 0.2) within each group (i.e., 200 Black and 200 White 
adolescents provide adequate power).Analytic plans: We will follow data cleaning procedures for eye-
tracking data established by our collaborator Dr. Balcetis for handling data loss or calibration 
issues.34The sampling rate—the proportion of time eyes are directed at the screen—must equal 80% 
or higher. Participants with <20% sampling rate will be eliminated (typically <5% of participants). 
Sampling Rates can be low because some rare types of cornea refractions and contact lens types 
impair the reflection of light the system measures. To account for nonindependence in consumption 
across blocks, we will conduct analyses using the MIXED procedure in SPSS, and calculate degrees 
of freedom using a Satterthwaite correction to predict consumption as a function of ad type within 
blocks 1–4 and separately blocks 5–8. We will include the random intercept of participants, the 
random intercept of block order, and the random slope of block order to account for linear changes in 
consumption over time. We will use linear regression to predict calorie intake from visual attention to 
race-relevant ad features, product, and “likes” for Black and White adolescents 
 
Data Monitoring 
 
The database will be secured with password protection. The study manager will receive only coded 
information that is entered into the database under those identification numbers. Electronic 
communication with outside collaborators will involve only unidentifiable information. 
 
The PI and/or study staff will review all data collection forms on an ongoing basis for data completeness 
and accuracy as well as protocol compliance.  
                                               
34 Granot Y, Balcetis E, Schneider KE, Tyler TR. Justice is not blind: visual attention exaggerates effects of group identification 
on legal punishment. J Exp Psychol Gen. 2014;143(6):2196-2208. 

 
Review of the rate of subject accrual and compliance with inclusion/exclusion criteria will occur monthly 
during the 4-month recruitment phase and then every 3 months to ensure that a sufficient number of 
participants are being enrolled and that they meet eligibility criteria and the targeted ethnic diversity 
goals outlined in the grant proposal. 
 
Data on adherence to the treatment protocol will be collected once and reviewed by research staff, the 
PI, and the study statistician. Adherence of participants will be evaluated by completing the study. If a 
participant does not sign the assent form, they will be informed that they cannot participate in the study 
 
This study will be stopped prior to its completion if: (1) the intervention (i.e., exposure to food ads) is 
associated with adverse effects that call into question the safety of the intervention; (2) difficulty in study 
recruitment or retention will significantly impact the ability to evaluate the study endpoints; (3) any new 
information becomes available during the study that necessitates stopping the study; or (4) other 
situations occur that might warrant stopping the study. 
 
Because our study involves a 15-minute online survey experiment where participants view and rate 
Facebook food ads, as well as the use of an eye-tracking computer, we do not anticipate the need for 
an independent monitor nor a study report outline. 
 
Data Storage and Confidentiality 
During this study, participants will view racially congruent or incongruent Facebook ads and answer 
survey questions about them. Afterwards, participants will complete a food purchasing task and 
answer demographic questions. All of the material collected are for research purposes only, and data 
will be kept in strict confidence. Demographic and survey data will be collected using Qualtrics, a 
survey software company that hosts the survey data. Qualtrics Enacts several safeguards to protect 
online data. Qualtrics FedRAMP certified which is one of the highest non-military security programs 
for security certifications. FedRAMP was initially designed to asses, authorize, and monitor cloud 
software providers and protect the data housed in federal agencies but has since expanded to protect 
third-party platforms and systems, like Qualtrics. Finally, our consent and assent form will inform 
parents and adolescents that although a data breach is possible, it is unlikely. No information will be 
given to anyone without permission from the subject. The consent and assent forms include the 
informed consent and assent statements required by New York University School of Medicine for 
studies Involving Adolescents. This statement guarantees confidentiality and identifies the subject as 
the owner of the information from the collected data Furthermore, since this is a NIH-sponsored 
study, we will be issued a Certificate of Confidentiality which prohibits the disclosure of identifiable, 
sensitive research information to anyone not connected to the research. Confidentiality will also be 
ensured by use of identification codes. All data will be identified with a randomly generated 
identification code unique to the subject. B. Database Protection The database will be secured with 
password protection. The study manager will receive only coded information that is entered into the 
database under those identification numbers. Electronic communication with outside collaborators will 
involve only unidentifiable information. Confidentiality During Adverse Event (AE) Reporting we do not 
anticipate the occurrence of adverse effects because the study is an online survey study where 
adolescents will view and rate food ads. Still, AE reports and annual summaries will not include 
subject-or group-identifiable material. Each report will only include the identification code. 

 
All participant responses will be anonymous. For the study, only the PI will have access to identifiable 
private information and participant data, which will only be used for research purposes. Other 
members of the research team will have access to identifiable private information for the purposes of 
recruitment and scheduling or participant data, but not both 
 
Specific study team members will be in charge of ensuring quality of collected data. During data 
collection, study team members will record themselves to be reviewed by the data management team 
to ensure adherence to the study protocol across study team members. The data management team 
will also review uploaded survey responses for completion and address any issues noted by the study 
team member. Additionally, study team members will be trained to record any anomalies during the 
participant interactions and/or data collection that could impact the quality of the data collected (e.g. 
interruptions of the survey, posters at location encouraging healthy eating, the participant mentioning 
that they are anticipating a big meal following the survey). 
 
The data containing private information will be stored on RedCap . Only authorized study staff will 
have access to the study data. One RedCap data collection project will be, and a separate project will 
be used store etc.). This ensures that the personally identifiable information and research data are 
segregated. Data users on the research team must agree to restrictions against attempting to identify 
study participants, destruction of the data after completing their analyses, reporting responsibilities, 
and proper acknowledgement of the data resource. Any computers holding data will be stored in a 
locked office. 
 
Study records that do not hold PI or PHI will be collected in a binder that will be stored in a locked 
cabinet in a locked office. The principal investigator and all other study team members will have 
access to this binder. Study records including consent forms, assent forms, receipt forms, and any 
other documentation containing PI or PHI will be put in participant packets and stored in a locked 
cabinet in a locked room. The Principal Investigator and study team members designated to deal with 
identifiable information will have access to these packets. 
 
Study documents will be retained for the longer of 3 years after close out or 5 years after final 
reporting/publication. These documents should be retained for a longer period, however, if required 
by local regulations. No records will be destroyed without the written consent of the sponsor, if 
applicable. It is the responsibility of the sponsor to inform the investigator when these documents no longer 
need to be retained. 
 
 
 
Risk/Benefit Assessment 
The risks associated with this study, if any, are considered to be minimal and are addressed in the 
protocol and consent form. There may be some discomfort when using an eyetracker, but reports of 
this are minimal. Further, participants may experience boredom or irritation when completing the 
online surveys and other tasks embedded within them. Participants and their caregivers will be 

informed that an online data breach is possible, though not likely, and that no identifying information 
will be collected during the study. Exposure to food ads during in-person lab experiments is known to 
increase consumption of unhealthy foods among children during the 30–60-minute period after ad 
exposure. During such studies, researchers provide the snacks in order to measure how many 
calories are consumed in response to food and exposure. This study does not provide snacks to 
participants, but it's still possible that participants of this study may consume unhealthy foods in 
response to seeing food ads in our study. Because we are providing a small dose of ad exposure 
compared to what adolescents view over the course of a week or more, it is unlikely that participating 
in this study would have longer-term negative influences on participants’ diets.  To inform adolescents 
of the possibility that viewing food ads may cause them to eat more calories after the study than they 
would have otherwise, we will also describe in an online debriefing statement that in-person lab 
studies involving food ad exposure have shown that children eat more unhealthy snacks in response 
to seeing food ads compared to non-food ads. The debriefing form will also state that it is possible 
that participants will experience a desire to consume more food during the 30–60 minutes after the 
study and should aim to select healthy options such as water, whole fruit, or nuts. The measures 
taken to reduce any associated risks will be protecting participant information. The study statistician, 
PI, and Independent Monitor will review adverse event rates monthly. Any Adverse event will be 
reported to the NYU IRB and NIH. 
 
Subject Identification, Recruitment and Consent/Assent 
Process of Consent 
Aims 1–2 
Informed Consent: Electronically signed informed consent will be obtained from each parent/primary 
caregiver and an electronically signed assent form will be obtained from each subject at entry into the 
study. Informed Consent is obtained by the following process: 
 
1.Dynata, the online survey company who will recruit participants, will send a consent form to a 
primary caregiver. 
2.Once the caregiver reviews the form and consents their adolescent’s participation, Dynata will email 
the adolescent with the assent form and survey. 
3.After reviewing the study and agreeing to participate, the adolescent will sign the assent form and 
begin the survey 
 
Informed consent/assent and debriefing procedures: Parents whose adolescents are eligible for the 
survey will receive a link to the informed consent form; if they sign it, then the adolescent will receive 
a link to an assent form. This will be done through Dynata, a survey firm that maintains an online 
participant panel of adolescents and adults in the U.S. We have recruited thousands of adolescents 
through Dynata for pilot research and published studies.34,35 Dynata conducts a rigorous, three-step 
                                               
35 VanEpps EM, Roberto CA. The Influence of Sugar-Sweetened Beverage Warnings: A Randomized Trial of Adolescents’ 
Choices and Beliefs. Am J Prev Med. 2016;51(5):664-672. 

recruitment process. First, randomly selected participants who are already members of Dynata’s panels 
are combined with a pool of potential participants who are joining Dynata for the first time after responding 
to online recruitment materials.  Participants will be told in the assent form that researchers are 
interested in learning about their opinions of social media and consumer brands. This minor 
deception (i.e., they will not be told the study is about food choices until the end) is commonly used 
with children in food and research and has been approved by the IRB at NYUGSoM for our previous 
studies (s19-01102 Ethnically Diverse Study and s15-00879 NYU Media Project). 
 
Aim 3 
In Study 3, the consent form will explain to caregivers the potential risks of the study and what 
measures have been taken to mitigate these risks. The form will also detail the use of personal 
information and will explain the removal of identifying information. Caregivers will be asked to sign the 
consent form, indicating that they understand the risks and preventative measures and that they give 
consent for the researchers to survey their adolescent and obtain assent.  
 
Our research team will then confirm the adolescent's assent in-person to participate in the 
study. Before assenting, though, members of our research team will speak with the adolescent about 
the potential risks, the preventative measures to assess those risks, and the removal of any 
identifying data. During the study, two researchers will supervise each participant. 
Debriefing Procedures 
At the end of the study, participants will view a debriefing statement explaining the study’s purpose. 
We will use a funneled debriefing procedure to ask participants what they believed was the purpose 
of the study so we can test for moderation of effects as a function of awareness during analyses. We 
will disclose the purpose of the study, solicit questions, conduct a second assent procedure after 
disclosing eye-tracking was used and was ethically approved, and provide the same information from 
the debriefing form in Aim 1 and 2. 
 
 
To inform adolescents of the possibility that viewing food ads may cause them to eat more calories 
after the study than they would have otherwise, we will also describe in the online debriefing 
statement that studies have shown that viewing food ads can increase caloric intake among youth, 
and they should try to choose healthy options such as water, whole fruit, or nuts if they experience a 
desire to snack after the study. Dynata will then provide each participant with $25 in gift cards for 
participating and $8 petty cash for the snacks they purchased. 
Costs to the Subject 
Participants will not incur any costs for the first two trials. We will distribute $35 compensation via gift 
cards and reimburse  travel costs for the third aim . 

Payment for Participation 
For Aims 1 and 2- After the food purchasing task, participants will complete demographic questions 
and then receive $25 in gift cards for participating and $8 petty cash for their snack purchases. 
For Aim 3- Participants will receive $35 compensation via gift card. We will reimburse participants for 
any travel costs. To compensate community sites for recruitment assistance, we will provide each site 
an $800 honorarium via check.