Impact of Behavioral Economic Strategies on Low-Income Older Adults' Food Choices in Online Retail Settings
Phase: NA
Conditions: Diet Habit
Sponsor: NYU Langone Health

 
 
Official Title: 
Impact of Behavioral Economic Strategies on Low-Income Older Adults' 
Food Choices in Online Retail Settings 
NCT Number: 
NCT04766034 
Study Number: 
20-01936 
Document Type:  
Study Protocol and Statistical Analysis Plan 
Date of the 
Document: 
December 23, 2021 
 

STUDY PROTOCOL 
 
 
 
Impact of Behavioral Economic Strategies 
on Low-Income Older Adults' Food 
Choices in Online Retail Settings 
Study Number 
s20-01936 
 
Protocol Version 
December 16, 2021 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
Study Number: s20-01937  
December 16, 2021 
 
2 
Study Personnel 
Principal Investigator 
Pasquale Rummo 
NYU Langone Health 
Department of Population Health 
Email: Pasquale.Rummo@nyulangone.org 
  
 
 
 

 
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Synopsis 
Study Description 
The specific aims of this proposal are to 1) develop the components of a behavioral 
economics strategy (i.e., healthy bundle defaults) to influence diet behaviors; 2) 
characterize the online grocery shopping behaviors and attitudes of low-income adults 
nationally; and 3) examine the extent to which "healthy bundles defaults" and other 
behavioral economic strategies increase fruit and vegetable purchases among low-income 
adults in an online randomized controlled experiment.  
The figure below shows the flow of our aims. To accomplish Aim 1, we will develop the 
components for the bundles in our online experiment, using publically-available data from 
the National Household Food Acquisition and Purchase Survey (FoodAPS). To 
accomplish Aim 2, we will use an online survey that we have already developed (and 
uploaded to Research Navigator). The survey will be administered to 2,692 participants, 
whom we will recruit through CloudResearch. After completing the online survey, the same 
participants will be randomized into one of four conditions and then participate in our 
experimental study (Aim 3) by clicking a link and simulating a shopping task in a web-
based supermarket platform developed by Cauldron Science Ltd. 
 
Overall, the research study will occur over 5 years (see timeline below). The development 
of the bundles and the web-based supermarket will occur in Year 1; data collection will 
occur in Years 2-4; data analysis will occur in Year 4; and Year 5 will involve development 
of manuscripts and dissemination activities. There will be no interaction with participants in 
Years 1 and 5. 

 
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Objectives 
Our primary objectives are to capture behaviors and attitudes related to online grocery 
shopping among low-income American adults; and examine the extent to which different 
behavioral economic strategies influence fruit and vegetable purchases of low-income 
adults in a web-based supermarket. Our secondary objective is to examine whether the 
impact of our different behavioral economic strategies differs by age group, gender, and 
race/ethnicity. 
Endpoints 
The endpoints for the online survey will be 1) whether participants report shopping for 
groceries online, and 2) whether participants report consuming at least 5 daily servings of 
fruits and vegetables. Among those who shop online for groceries, we will estimate the 
frequency of online grocery shopping, types of groceries purchased online, types of online 
retailers, and methods of delivery; and amount ($ and %) spent on online grocery 
shopping relative to the amount spent on in-store grocery shopping per week. We will also 
calculate the frequency (%) of reasons that participants choose as motivating or 
preventing them from purchasing groceries online (e.g., price, quality). 
The endpoint for the intervention is the proportion of real dollars spent on total fruit and 
vegetables per basket (i.e., shopping cart items) across conditions.  
Study Population 
The study population is a sample of low-income adults aged >18 years who have ever 
received SNAP benefits, read and speak English, live with fewer than 5 people, and have 
access to a personal computer, laptop, tablet, or mobile phone. Low-income adults are the 
target subject population because disparities in healthy food purchases and dietary intake 
are linked to the growing prevalence of obesity among low-income adults. In addition, low-
income consumers participating in SNAP are able to use their SNAP benefits in online 
transactions with participating retailers in select geographies. 
Accrual Ceiling 
We require 158 participants in each of the four arms (total n=632) to adequately power our 
analysis. This sample size provides power to detect a 9% difference between any 
experimental condition and controls. To allow examination of potential interaction effects 

 
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by demographic characteristics, we plan a total sample size of 2,692 participants (the rule 
of thumb that four times the sample size is needed to assess interactions compared to 
main effects requires us to enroll at least 2,528 participants). The number of persons 
found to be ineligible during screening is unknown. 
Phase 
Not applicable. 
Description of Sites/Facilities Enrolling Participants 
We propose to recruit our sample through CloudResearch, an online research company 
that recruits volunteer research participants from dozens of online panel providers. This 
means that people navigated to the panel website, created an account, and verified their 
desire to participate in studies by confirming their email address. Participants who join a 
panel have the option to unsubscribe at any time. When a study starts in the field, 
CloudResearch uses an assignment process to match participants with surveys they are 
likely to be eligible for and complete, with proprietary quality control procedures to ensure 
participants do not take the same survey twice. To reduce selection bias associated with 
the topic of the survey, invitations do not include specific details of the survey. Participants 
who complete CloudResearch's online surveys receive points that can be redeemed for 
various incentives, including cash, lotteries, or donations to charity. We have approval 
from NYU Medical Center Information Technology (MCIT) to use CloudResearch for 
recruitment. 
We will use Qualtrics to create and distribute the survey.  
We will also use Cauldron Science Ltd., which provides subscribers with access to their 
web-based tool “Gorilla”. “Gorilla” allows researchers to plan, design, and carry out online 
psychology experiments for research purposes, including a supermarket platform. The 
platform is already built and we have a license to use it for our experiment, with approval 
from the NIH, approval from NYU Medical Center Information Technology (MCIT), and a 
fully executed contract via the NYU legal office.  
Description of Study Intervention 
The people participating in the study will complete an online survey about what factors 
motivate or prevent them from shopping for groceries online. After completing the survey, 
all participants will participate in an online randomized controlled experiment. At the end of 
the survey, participants will be directed to click the link to our web-based supermarket and 
to emulate a typical online grocery shopping experience. Participants will be asked to 
simulate one grocery shopping trip in a web-based supermarket and to select a typical 
week's worth of food for their household, including fruits and vegetables. Participants will 
be randomized to one of four conditions. To mimic existing double-dollar incentive 

 
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programs, participants randomized to receive discounts will receive half-off qualifying fruits 
and vegetables. The discount will be applied directly to participants' online shopping cart 
items at point of selection. Participants randomized to healthy bundle defaults with no 
discount will be offered a bundle of food and beverage items pre-loaded in their online 
shopping cart (i.e., a healthy default). This bundle will be determined by participants’ 
answers to two questions in the online survey asking which fruits and beverages they 
purchase most often. Participants randomized to healthy bundle defaults plus a discount 
will receive a half-off discount on an identical tailored bundle. Participants will be allowed 
to remove the bundle from their shopping cart. Prior to shopping, participants will be given 
instructions regarding the discount and/or bundles. 
Study Duration 
The study will last 5 years, but data collection will specifically occur in 3 time periods, 
including quarters 1 and 2 of years 2, 3, and 4 of the study.  
Participant Duration 
The online survey will take approximately 10-15 minutes to complete and the simulated 
grocery shopping trip will take an additional 10-15 minutes, so the study will take a total of 
20-30 minutes to complete. Participants randomized to receive discounts will receive half-
off qualifying fruits and vegetables. Participants may participate in the study at any time of 
day. 
Schema 
Schedule of Activities (SoA) 
The people participating in the study will complete an online survey about what factors 
motivate or prevent them from shopping for groceries online. After completing the survey, 
all participants will participate in an online randomized controlled experiment. At the end of 
the survey, participants will be directed to click the link to our web-based supermarket and 
to emulate a typical online grocery shopping experience. Participants will be asked to 
simulate one grocery shopping trip in a web-based supermarket and to select a typical 
week's worth of food for their household, including fruits and vegetables.  
To incentivize participation and truthful responses, we will also notify participants prior to 
the experiment that they are automatically entered into a lottery to have the items in their 
shopping cart delivered to their household if they complete both the survey and shopping 
trip task. Every one in ten participants will be selected randomly and CloudResearch will 
distribute gift cards to winners. The PI will randomly select lottery winners using participant 
ID’s, which are not linked to personally identifiable information at any point in the study.  
CloudResearch will also debrief lottery winners about the purpose of the task, including 

 
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the justification for providing lottery winners gift cards with money loaded on to it 
equivalent to the amount of money that they spent in the study (rather than having the 
groceries delivered). The participants who do not win the lottery will also be debriefed. 
The online survey will take approximately 10-15 minutes to complete and the simulated 
grocery shopping trip will take an additional 10-15 minutes, so the study will take a total of 
20-30 minutes to complete.  
 
End of Study Definition 
The end of study is when we have collected data from 2,692 participants who have 
completed our online survey on Qualtrics and completed our online grocery shopping task 
on the “Gorilla” web-based supermarket platform. 
 
 
1 – Statement of Compliance 
1.1 Statement of Compliance 
This study will be conducted in accordance with the Code of Federal Regulations on the 
Protection of Human Subjects (45 CFR Part 46), any other applicable US government 
research regulations, and institutional research policies and procedures. The Principal 
Investigator will assure that no deviation from, or changes to the protocol will take place 
without prior agreement from the sponsor and documented approval from the Institutional 
Review Board (IRB), except where necessary to eliminate an immediate hazard(s) to the 
study participants. All personnel involved in the conduct of this study have completed 
Human Subjects Protection Training. 
 
 

 
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2 - Introduction 
2.1 Study Rationale 
The successful completion of the proposed research may highlight which issues related to 
online shopping could be addressed by changes to federal and local nutrition assistance 
programs; and for whom these changes would have the greatest impact. 
 
2.2 Background 
Dietary behaviors play a critical role in shaping multiple cardiovascular risk factors, including 
obesity, weight gain, and blood glucose levels. (1) Diets rich in energy, added sugars, and 
saturated fat, and low in whole grains, nuts, fruits, and vegetables, are positively associated 
with risk of excess adiposity, higher BMI, and increased risk of poor cardiovascular health. 
(2)  (3)  (4)  In conjunction with decreased consumption of energy-dense foods, increased 
fruit and vegetable consumption has been shown to prevent obesity and weight gain. (5)  
However, low-income adults consume fewer fruits and vegetables and have poorer diet 
quality scores than higher income adults. (6)  (7)  
 
Previous research has shown that food affordability and access to fast food restaurants and 
supermarkets are linked to obesity, high blood pressure, diabetes, and metabolic syndrome, 
(8)  (9)  likely via poor dietary behaviors and excess energy intake. (1)  In particular, 
disparities in food affordability and healthy food access contributes to inadequate intake of 
healthy foods among low-income adults. (10)  Low-income adults often live on fixed budgets 
and spend a greater proportion of their income on food than those in higher-income 
households. (11)  Further, access to supermarkets and healthy food is lower — and 
availability of energy-dense foods and fast food restaurants is higher — in low-income 
neighborhoods. (12)  Therefore, interventions to increase the affordability and accessibility of 
healthy foods may help improve diet behaviors in low-income adults. 
 
To address disparities in the cost of healthy foods and increase the purchasing power of 
low-income adults, the United States Department of Agriculture (USDA) also offers financial 
assistance through food assistance programs, such as the Supplemental Nutrition 
Assistance Program (SNAP) program. In 2016, SNAP served a monthly average of about 
44.2 million people in 21.8 low-income households. (13)  Recent studies have found that 
SNAP participation is associated with a decrease in food insecurity as well as reduced 
health care spending among low-income adults. (14)  (15)  However, household participation 
in SNAP is associated with lower HDL cholesterol, elevated fasting glucose, and metabolic 
syndrome. (16)  Research also suggests that adult SNAP participants purchase fewer 
vegetables, fruits, and whole grains than lower income nonparticipants; (17)  and purchase 

 
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more total calories, sodium, and sugars. (18)  Therefore, it is critical to evaluate potential 
policy proposals that promote healthy diet behaviors in SNAP households. 
In select geographies, low-income consumers participating in SNAP are able to use their 
SNAP benefits in online transactions with participating retailers. (19)  According to the Pew 
Research Center, internet use has increased by 74% and 89% in the past decade among 
U.S. adults, with higher overall use among younger age groups. (20)  Though absolute 
levels of internet use are lower for low-income consumers relative to higher income 
consumers, internet use increased by 27% between 2008 (54%) and 2018 (81%) among 
those with an annual income below $30,000. (20)  Though most adults in the U.S. still visit a 
brick-and-mortar store to buy groceries at least once a week, (21)   online grocery shopping 
is rapidly expanding in popularity. For example, a recent survey indicated that approximately 
20% of consumers who are responsible for grocery shopping for their household shopped 
online for groceries "at least occasionally" in 2018. (22)  However, little is known about 
online grocery shopping behaviors and attitudes of low-income adults nationally. 
The growth in online grocery shopping offers a promising opportunity to tailor healthy eating 
interventions to online food retail environments. Unlike most brick-and-mortar food stores, 
online groceries can be ordered at any time of the day and can be delivered to consumers' 
homes. Home delivery is a key benefit to low-income adults living in areas with limited 
access to healthy foods (i.e., food deserts). Online grocery shopping also has the potential 
to address other barriers to healthy eating, including few opportunities to plan and 
susceptibility to in-store marketing cues, which may lead to impulse purchases. (23)  (24)  
(25)  Relative to brick-and-mortar stores, it is easier to modify the design of online 
environments to influence consumer decision-making (e.g., default shopping cart items). On 
the other hand, online grocery shopping has many potential drawbacks. Exposure to 
unhealthy foods and beverages may be higher due to online retailers targeting products to 
consumers using personal information or previous purchase data. In addition, some grocery 
retailers may not deliver to low-income neighborhoods, and low-income consumers may not 
have regular internet access. This study will make a significant contribution by being the first 
to characterize online food shopping behaviors in a national sample of low-income adults. 
Interventions informed by behavioral economics can promote healthier food choices by 
nudging consumers in subtle, low-cost ways that honor individual preferences. (26)  
According to Thaler and Sunstein, nudges are "any aspect of the choice architecture that 
alters behavior in a predictable way without forbidding any options or significantly changing 
their economic incentives". Nudges leverage behavioral heuristics and biases based on the 
psychology of decision-making to change shopping environments. For example, people are 
highly susceptible to the status quo bias, (27)  or the preference for inaction and for things to 
stay the same. One way to leverage this bias to promote health is to change default options 
in the environment so that people are defaulted into healthy choices, but can opt out of them 
if they desire. Default options have been shown to increase participation in organ donation in 
opt-out countries, (28)  and increase orders of healthy foods in restaurants with healthy 

 
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default side items on menus (e.g., salad instead of fries). (29)  Providing subsidies for 
qualifying healthy food purchases is also a popular and effective strategy for promoting 
healthy food purchases. (30)  (31)  Though an economic strategy, subsidies may help to 
mitigate "present biased preferences," or consumers' tendency to ignore future health effects 
by focusing on immediate rewards, (27)  and cues in the environment that elicit temptation 
(e.g., promotions). A recent review of food pricing interventions found that subsidies improve 
dietary behaviors foods, especially multicomponent interventions (e.g., subsidies combined 
with education). (30)  With the option to use SNAP benefits online, there are a host of 
opportunities to create unique behavioral nudges to increase healthy food consumption. (32)  
Recently, a laboratory-based study found that displaying discounted 'bundles' in a brick-and-
mortar grocery store led to a 15% increase in fruit and vegetable purchases. (33)  However, 
no research has focused on bundling healthy food items in online food environments, or 
studying the effect of adding default food items to a shopping cart. 
To date, only a few studies have tested interventions aimed at encouraging consumers to 
purchase healthier food items in online supermarkets and results are mixed. Previous 
research has found that front-of-pack nutrition labels, product placement, and product 
promotions increased diet quality and promoted healthier food choices in online 
supermarkets, (34)  (35)  (36)  (37)  whereas healthy swaps (i.e., offering healthy 
alternatives) did not appear to affect purchases. (38)  Similarly, previous work has found that 
subsidies on healthy foods improved the nutrient quality of foods purchased in an online 
supermarket, (39)  though they may result in higher calories purchased overall. (35)  (38)  
Both discounts and bundling may be effective strategies to promote healthy food choices 
among individuals with a fixed budget, especially in online settings where individuals are 
able to preorder and deliver groceries to their home. To our knowledge, no research has 
evaluated interventions designed to promote healthier online food purchases among low-
income adults. 
 
2.3 Risk/Benefit Assessment 
2.3.1 Known Potential Risks 
There is low risk of a breach of confidentiality. Participants may be frustrated when 
completing survey and when we debrief them about the lottery and how CloudResearch is 
emailing them a gift card instead of delivering their shopping cart items to their residential 
address. As described above, the lottery is used to incentivize participation and truthful 
responses and this approach will mitigate potential issues related to delivery and avoid 
complications associated with changing grocery stock items. It is important that the 
participant thinks they are actually getting the groceries because it will encourage 
participants to provide truthful answers; whereas, knowledge of getting a gift card might 
result in participants making choices that do not reflect their actual preferences. We also 
anticipate that participants would prefer money they can spend on anything, rather than 
being restricted to grocery items.  

 
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11 
 
2.3.2 Known Potential Benefits 
There are no direct benefits to subjects.  
 
2.3.3 Assessment of Potential Risks and Benefits 
We will not collect personally identifiable information, so the potential risks are minimal. 
Thus, we assess that the benefits outweigh the risks. 
 

 
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3 - Objectives and Endpoints 
3.1 Objectives and Endpoints 
Our primary objectives are to capture behaviors and attitudes related to online grocery 
shopping among low-income American adults; and examine the extent to which different 
behavioral economic strategies influence fruit and vegetable purchases of low-income adults 
in a web-based supermarket. Our secondary objective is to examine whether the impact of 
our different behavioral economic strategies differs by age group, gender, and race/ethnicity. 
The endpoints for the online survey will be 1) whether participants report shopping for 
groceries online, and 2) whether participants report consuming at least 5 daily servings of 
fruits and vegetables. Among those who shop online for groceries, we will estimate the 
frequency of online grocery shopping, types of groceries purchased online, types of online 
retailers, and methods of delivery; and amount ($ and %) spent on online grocery shopping 
relative to the amount spent on in-store grocery shopping per week. We will also calculate 
the frequency (%) of reasons that participants choose as motivating or preventing them from 
purchasing groceries online (e.g., price, quality). 
The endpoint for the intervention is the proportion of real dollars spent on total fruit and 
vegetables per basket (i.e., shopping cart items) across conditions. 
 
 

 
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4 - Study Design 
4.1 Overall Design 
This research study includes three aims (see figure below), though only Aim 2 and Aim 3 
involve human subjects. The duration of the study is 5 years.  
 
In Aim 1, we will develop the components of healthy bundle defaults (i.e., preloaded cart 
items) using publically available data from the National Household Food Acquisition and 
Purchase Survey (FoodAPS), the literature, and expert advice. Specifically, we will measure 
the frequency of food and beverage purchases in FoodAPS, to enable us to determine the 
most frequent healthy food purchases by category (e.g., fruits, vegetables) among low-
income households by household size, gender, and race/ethnicity. These healthy bundle 
defaults will be used in Aim 3, specifically the arms with healthy bundle defaults. The 
development of the bundles will occur in Year 1. Aim 1 does not involve human subjects 
research. 
In Aim 2, we will recruit 2,692 low-income adults aged >18 years from a nationwide 
nonprobability panel via CloudResearch and administer an online survey to characterize 
participants' online grocery shopping behaviors and attitudes. After completing the online 
survey, we will randomize all participants from Aim 2 to one of four conditions, including 1) 
no intervention, 2) discount on eligible fruits and vegetables, 3) healthy bundle defaults with 
no discount, and 4) healthy bundle defaults plus a discount.  
In Aim 3, participants will click a link and simulate a shopping experience by selecting a 
week's worth of SNAP-eligible groceries for their household in a web-based supermarket 
platform. We will also use Cauldron Science Ltd., which provides subscribers with access to 
their web-based tool “Gorilla”. “Gorilla” allows researchers to plan, design, and carry out 
online psychology experiments for research purposes, including a supermarket platform. The 
platform is already built and we have a license to use it for our experiment, with approval 

 
Study Number: s20-01937  
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14 
from the NIH, approval from NYU Medical Center Information Technology (MCIT), and a fully 
executed contract via the NYU legal office. 
We will examine the impact of our behavioral economic strategies on the proportion of real 
dollars spent on total fruits and vegetables per online shopping basket. We will also explore 
whether the impact of our intervention on food purchases differs by sociodemographics. 
Data collection for Aims 2-3 will occur in Years 2-4. 
 
4.2 Scientific Rationale for Study Design 
The study design proposed will achieve robust and unbiased results because a randomized 
controlled experiment is a gold standard approach. To mimic existing double-dollar incentive 
programs, participants randomized to receive discounts will receive half-off qualifying fruits 
and vegetables. 
 
4.3 End of Study Definition 
The end of study is when we have collected data from 2,692 participants who have 
completed our online survey on Qualtrics and completed our online grocery shopping task 
on the “Gorilla” web-based supermarket platform. 
 
 

 
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5 - Study Population 
5.1 Inclusion Criteria 
The inclusion criteria include: 1) aged 18-99 years; 2) ability to read and speak English; 3) 
have ever received SNAP benefits, 4) live with fewer than 5 people; and 5) access to a 
personal computer, laptop, tablet, or mobile phone. 
 
5.2 Exclusion Criteria 
The exclusion criteria include: 1) aged <18 years or >99 years; 2) lack the ability to read and 
speak English; 3) have never received SNAP benefits, 4) live with 5 or more people; and/or 
5) do not have access to a personal computer, laptop, tablet, or mobile phone. 
 
5.3 Lifestyle Considerations 
There will be no restrictions during any parts of the study pertaining to lifestyle and/or diet. 
 
5.4 Screen Failures 
Screen failures include those who do not meet all of our inclusion criteria. Potential 
participants will answer four pre-screening questions to determine their eligibility. The pre-
screening questions include those related to 1) age; 2) the ability to read and speak English; 
3) receipt of SNAP benefits (ever), and 4) the number of household members (we do not 
explicitly ask about access to a personal computer, laptop, tablet, or mobile phone, since 
they are using Qualtrics to access our survey, which requires access to such devices). If 
they do not meet our inclusion criteria, these subjects will see the text "Thank you for your 
time, but unfortunately, you are not eligible for this study."  
Re-screening is not applicable. 
 
5.5 Strategies for Recruitment and Retention 
We propose to recruit our sample through CloudResearch, an online research company that 
recruits volunteer research participants from dozens of online providers. This means that 
people navigated to the panel website, created an account, and verified their desire to 
participate in studies by confirming their email address. CloudResearch uses an assignment 
process to match participants with surveys they are likely to be eligible for and complete, 
with proprietary quality control procedures to ensure participants do not take the same 
survey twice. To reduce selection bias associated with the topic of the survey, invitations do 
not include specific details of the survey. Participants who complete CloudResearch's online 
surveys receive points that can be redeemed for various incentives, including cash, lotteries, 
or donations to charity. We have approval from NYU Medical Center Information Technology 

 
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16 
(MCIT) to use CloudResearch for recruitment. The online survey is already developed (and 
uploaded to Research Navigator). 
To incentivize participation and truthful responses, we will also notify participants prior to the 
experiment that they are automatically entered into a lottery to have the items in their 
shopping cart delivered to their household if they complete both the survey and the shopping 
trip task. 
 
6 - Study Procedures  
The people participating in the study will complete an online survey about what factors 
motivate or prevent them from shopping for groceries online. After completing the survey, all 
participants will participate in an online randomized controlled experiment. At the end of the 
survey, participants will be directed to click the link to our web-based supermarket. 
Participants will be asked to select a typical week's worth of food for their household and 
assume they need to buy the most important things, including the fruits and vegetables they 
typically buy. Participants will be randomized to one of four conditions. To mimic existing 
double-dollar incentive programs, participants randomized to receive discounts will receive 
half-off qualifying fruits and vegetables. The discount will be applied directly to participants' 
online shopping cart items at point of selection. Participants randomized to healthy bundle 
defaults with no discount will be offered a bundle of food and beverage items pre-loaded in 
their online shopping cart (i.e., a healthy default). This bundle will be determined by 
participants’ answers to two questions in the online survey asking which fruits and 
beverages they purchase most often. Participants randomized to healthy bundle defaults 
plus a discount will receive a half-off discount on an identical tailored bundle. Participants will 
be allowed to remove the bundle from their shopping cart. Prior to shopping, participants will 
be given instructions regarding the discount and/or bundles.  
We will recruit a nationwide non probability panel of 2,692 low-income adults >18 years 
through CloudResearch, an online surveying company that recruits volunteer research 
participants through their online panels and other online communities. Participants who 
complete CloudResearch's online surveys receive points that can be redeemed for various 
incentives, including cash, lotteries, or donations to charity. Potential participants will click 
the link for our online study and complete an online consent. After providing consent, 
potential participants will complete four pre-screening questions to determine their eligibility. 
The pre-screening questions include those related to 1) age; 2) the ability to read and speak 
English; 3) receipt of SNAP benefits (ever), and 4) the number of household members (we 
do not explicitly ask about access to a personal computer, laptop, tablet, or mobile phone, 
since they are using Qualtrics to access our survey, which requires access to such devices). 
All questions in the survey, including the pre-screening questions, will be completed on a 
personal computer, laptop, tablet, or mobile phone and will take approximately 10-15 

 
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minutes to complete. We will use Qualtrics to create and distribute the survey. At the end of 
the survey, participants will be asked to simulate one grocery shopping trip in a web-based 
supermarket and to select a typical week's worth of food for their household, including fruits 
and vegetables, which will take an additional 10-15 minutes.  
We will assess hypothetical purchases, so no payment will be taken and participants will be 
informed that they will not normally receive the shopping cart items. To incentivize 
participation and truthful responses, however, participants will be notified prior to the 
experiment that they are automatically entered into a lottery to have the items in their 
shopping cart delivered to their household if they complete both the survey and the shopping 
trip task. Our budget allows us to offer delivery of shopping cart items to one in ten 
participants. At the end of the study, CloudResearch will reveal to participants who win the 
lottery that they will be provided with a gift card with the equivalent amount of money loaded 
onto it that they spent in the study (rather than having the groceries delivered). This 
approach will mitigate potential issues related to delivery and avoid complications associated 
with changing grocery stock items. We also anticipate that participants would prefer money 
they can spend on anything, rather than being restricted to grocery items. CloudResearch 
will also debrief participants about the purpose of the study, including the justification for 
providing lottery winners a gift card instead of groceries. The participants who do not win the 
lottery will also be debriefed. 
After completing the online survey, we will randomize all participants from Aim 2 to one of 
four conditions, including 1) no intervention, 2) discount on eligible fruits and vegetables, 3) 
healthy bundle defaults with no discount, and 4) healthy bundle defaults plus a discount. All 
participants will answer the same set of questions in the online survey on Qualtrics. After 
clicking the link to access the web-based supermarket platform on the “Gorilla” platform, 
participants will be randomized to one of the four experimental conditions outlined in Aim 3. 
The “Gorilla” platform has a randomization function built into its design. No blinding will be 
done. 
Adherence to the protocol will be assessed by completion of the online survey data and the 
"checking out" of our online grocery store with a minimum of two items in the cart (no 
payment will be taken).  
 
 
 
 

 
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7 - Study Intervention Discontinuation and 
Participant Discontinuation/Withdrawal 
7.1 Discontinuation of Study Intervention 
Study modification will occur in the event of an unexpected problem or any necessary 
change to the protocol. Study team members put in charge of IRB communications will work 
with the Principal Investigator to prepare, submit, and address comments on modifications. 
This study may be discontinued in the event that participants find the gift card instead of 
delivering grocery items from their shopping cart is too upsetting, although we do not think 
this is likely since participants would likely prefer money they can spend on anything rather 
than being restricted to grocery items. 
 
7.2 Participant Discontinuation/Withdrawal from the Study 
The participants are allowed to withdraw from the online survey and online grocery shopping 
experience at any point, with no penalty. 
 
7.3 Lost to Follow-Up 
Not applicable. 
 
 

 
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9 - Statistical Considerations 
9.1 Statistical Hypotheses 
We will test the working hypothesis that the likelihood of shopping online for groceries is 
higher among adults who are male, White, and younger; and that adults who shop online will 
have higher adjusted odds of consuming at least 5 daily servings of fruits and vegetables 
than those who do not shop online. We also hypothesize that participants exposed to 
healthy bundle defaults plus a discount will spend more on fruits and vegetables than 
controls; and that the effect size will be larger relative to arms with only discounts or only 
bundles. 
 
9.2 Sample Size Considerations 
Based on previous work (40), we require 158 participants in each of the four arms (total 
n=632) to adequately power our analysis. This sample size provides power to detect a 9% 
difference between any experimental condition and controls. To allow examination of 
potential interaction effects by demographic characteristics, we plan a total sample size of 
2,692 participants (the rule of thumb that four times the sample size is needed to assess 
interactions compared to main effects requires us to enroll at least 2,528 participants). 
 
9.3 Populations for Analyses 
The study population is a sample of low-income adults aged >18 years who have ever 
received SNAP benefits, read and speak English, live with fewer than 5 people, and have 
access to a personal computer, laptop, tablet, or mobile phone. Low-income adults are the 
target subject population because disparities in healthy food purchases and dietary intake 
are linked to the growing prevalence of obesity among low-income adults. In addition, low-
income consumers participating in SNAP are able to use their SNAP benefits in online 
transactions with participating retailers in select geographies (19). 
 
9.4 Statistical Analyses 
For Aim 1, we will measure the frequency of food and beverage purchases in FoodAPS, to 
enable us to determine the most frequent healthy food purchases by category (e.g., fruits, 
vegetables) among low-income households by household size, gender, and race/ethnicity. 
For Aim 2, we will report our results using averages and standard deviations, or median and 
interquartile range. In exploratory analyses, we will use logistic regression to compare 
differences between groups, adjusting for relevant covariates. To determine whether the 
distribution of demographics is equivalent between our groups of comparison, we will use 
independent samples T-tests and Chi-square tests. We will do the same for comparing the 
distribution of demographics and grocery shopping behaviors between our sample and the 

 
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20 
FoodAPS sample. We will use a two-sided alpha of 0.05 as the threshold for statistical 
significance. 
For Aim 3, we will perform a linear regression to assess balance of demographic 
characteristics across the four study conditions; because of randomization, these 
characteristics should be balanced. To assess differences in the proportion of real dollars 
spent on total fruits and vegetables across experimental conditions, we will regress the 
outcome variable on indicator variables for the experimental conditions, with the control 
condition as the reference group; if necessary, we will also adjust for any respondent 
characteristics that may be unbalanced by condition. We will test for potential interaction 
effects by age group, gender, and race/ethnicity. We will also conduct a sensitivity analysis 
excluding participants who report that they would never consider shopping online for 
groceries. The design and methods proposed will achieve robust and unbiased results 
because a randomized controlled experiment is a gold standard approach. 
 
9.4.1 General Approach 
For Aim 1, we will measure the frequency of food and beverage purchases in FoodAPS, to 
enable us to determine the most frequent healthy food purchases by category (e.g., fruits, 
vegetables) among low-income households by household size, gender, and race/ethnicity. 
For Aim 2, we will report our results using averages and standard deviations, or median and 
interquartile range. In exploratory analyses, we will use logistic regression to compare 
differences between groups, adjusting for relevant covariates. To determine whether the 
distribution of demographics is equivalent between our groups of comparison, we will use 
independent samples T-tests and Chi-square tests. We will do the same for comparing the 
distribution of demographics and grocery shopping behaviors between our sample and the 
FoodAPS sample. We will use a two-sided alpha of 0.05 as the threshold for statistical 
significance. 
For Aim 3, we will perform a linear regression to assess balance of demographic 
characteristics across the four study conditions; because of randomization, these 
characteristics should be balanced. To assess differences in the proportion of real dollars 
spent on total fruits and vegetables across experimental conditions, we will regress the 
outcome variable on indicator variables for the experimental conditions, with the control 
condition as the reference group; if necessary, we will also adjust for any respondent 
characteristics that may be unbalanced by condition. We will test for potential interaction 
effects by age group, gender, and race/ethnicity. We will also conduct a sensitivity analysis 
excluding participants who report that they would never consider shopping online for 
groceries. The design and methods proposed will achieve robust and unbiased results 
because a randomized controlled experiment is a gold standard approach. 
 

 
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9.4.2 Analysis of the Primary Efficacy Endpoint(s) 
The primary outcome for Aim 1 is the healthy food item per category (fruits and vegetables) 
purchased most often per subgroup by household size (1-4 persons), gender (female, male), 
and race/ethnicity (Black, Hispanic/Latino, White). We will measure the frequency of food 
and beverage purchases in FoodAPS, to enable us to determine the most frequent healthy 
food purchases by category (e.g., fruits, vegetables) among low-income households by 
household size, gender, and race/ethnicity. 
The primary outcomes for Aim 2 will be 1) whether participants report shopping for groceries 
online, and 2) whether participants report consuming at least 5 daily servings of fruits and 
vegetables. Among those who shop online for groceries, we will estimate the frequency of 
online grocery shopping, types of groceries purchased online, types of online retailers, and 
methods of delivery; and amount ($ and %) spent on online grocery shopping relative to the 
amount spent on in-store grocery shopping per week. We will also calculate the frequency 
(%) of reasons that participants choose as motivating or preventing them from purchasing 
groceries online (e.g., price, quality).  We will report our results using averages and standard 
deviations, or median and interquartile range. In exploratory analyses, we will use logistic 
regression to compare differences between groups, adjusting for relevant covariates. To 
determine whether the distribution of demographics is equivalent between our groups of 
comparison, we will use independent samples T-tests and Chi-square tests. We will do the 
same for comparing the distribution of demographics and grocery shopping behaviors 
between our sample and the FoodAPS sample. We will use a two-sided alpha of 0.05 as the 
threshold for statistical significance. 
The primary outcome for Aim 3 is the proportion of real dollars spent on total fruit and 
vegetables per basket (i.e., shopping cart items) across conditions. We will perform a linear 
regression to assess balance of demographic characteristics across the four study 
conditions; because of randomization, these characteristics should be balanced. To assess 
differences in the proportion of real dollars spent on total fruits and vegetables across 
experimental conditions, we will regress the outcome variable on indicator variables for the 
experimental conditions, with the control condition as the reference group; if necessary, we 
will also adjust for any respondent characteristics that may be unbalanced by condition. The 
design and methods proposed will achieve robust and unbiased results because a 
randomized controlled experiment is a gold standard approach. 
 
9.4.3 Analysis of the Secondary Endpoint(s) 
We will test for potential interaction effects by age group, gender, and race/ethnicity. We will 
also conduct a sensitivity analysis excluding participants who report that they would never 
consider shopping online for groceries. 
 
9.4.4 Safety Analyses 

 
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Not applicable. 
 
9.4.5 Baseline Descriptive Analyses (if applicable) 
Not applicable. 
 
9.4.6 Planned Interim Analyses (if applicable) 
Not applicable. 
 
9.4.7 Tabulation of Individual Participant Data 
Individual participant data will not be listed by measure and time point. Only aggregated data 
will be presented. 
 
9.4.8 Exploratory Analyses 
We will explore whether online shopping behaviors differ by sociodemographic factors and 
diet in Aim 2. 
 
 

 
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10 – Ethical Considerations 
10.1 Regulatory, Ethical, and Study Oversight Considerations 
The investigator will ensure that this study is conducted in full conformity with Regulations for 
the Protection of Human Subjects of Research codified in 45 CFR Part 46. The protocol, 
informed consent form(s), recruitment materials, and all participant materials will be 
submitted to the IRB for review and approval. Approval of both the protocol and the consent 
form must be obtained before any participant is enrolled. Any amendment to the protocol will 
require review and approval by the IRB before the changes are implemented to the study. All 
changes to the consent form will be IRB approved; a determination will be made regarding 
whether previously consented participants need to be re-consented. 
 
10.1.1.1 Consent/Assent and Other Informational Documents Provided to Participants 
The consent based on the IRB template has been uploaded to the CONSENT FORMS 
section of submission in Research Navigator. 
 
10.1.1.2 Consent Procedures and Documentation 
Potential participants consent to participate in CloudResearch studies when they first 
respond to a CloudResearch advertisement. Potential participants also provide consent at 
the start of each survey using a computer-based consent form. Participants will be asked to 
read a consent form on the first page of the online survey, and click "yes" to consent and 
begin the survey or "no" to end the survey. Before obtaining consent, we will inform potential 
participants of the potential risks, which are minimal because we are not collecting 
personally identifiable information. To mitigate the risk of coercion, participants will receive 
compensation whether or not they complete the survey questions, and will be informed of 
this at the beginning of the survey. 
 
10.1.2 Study Discontinuation and Closure 
The study will be terminated or temporarily suspended based on PI decision, IRB decision in 
the event of an Unanticipated Problem. If an unanticipated problem is recognized, data 
collection will stop and any corrective action or explanation that can be given to participants 
experiencing this issue will be administered. Then, a modification to rectify the issue will be 
submitted to the IRB (and details sent to the sponsor if applicable) and new methods to 
avoid the problem will be used going forward. The study team will work with the IRB to 
ensure that any problems participants experienced prior to the change are ethically 
addressed. The consent process also includes text that informs the participants they can call 
or email the Principal Investigator with any questions. We will also inform participants that 
any questions, concerns, suggestions, or complaints that have not been or cannot be 

 
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addressed by the researcher, or if they wish to report research-related harm, they can 
contact the IRB. 
 
10.1.3 Data Confidentiality and Participant Policy 
We are not collecting personally identifiable information at any point, including participants' 
names and home addresses. CloudResearch will send the debriefing document to all people 
who participate in the online grocery shopping task about the purpose of the task, including 
the justification for providing lottery winners a gift card. 
The “Gorilla” web-based supermarket platform is fully compliant with data protection and 
security policies. All traffic to and from the “Gorilla” platform is encrypted and the database is 
encrypted using industry-standard cryptography. The PI will also own the research data that 
has been collected using the “Gorilla” platform, and he will be able to delete all data for an 
experiment or data pertaining to an individual participant.  
 
10.1.4 Future Use of Stored Data 
Study data will be retained for the longer of 3 years after close out or 5 years after final 
reporting/publication. We are not storing data beyond the current studies for future research 
and publications. 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. 
 
10.1.5 Study Oversight 
The research team will only ever have access to unique ID numbers for all participants, 
which will allow for linkage between participants’ responses in Qualtrics and participants’ 
selections from the “Gorilla” web-based supermarket platform.  
 
10.1.6 Key Roles and Study Governance 
The Principal Investigator is Pasquale Rummo, PhD, MPH, NYU School of Medicine, 180 
Madison Ave, Room 3-54, 646-501-3371, pasquale.rummo@nyulangone.org. The PI also 
has a Mentoring Committee. A K01 award from the NIH is a training grant, which requires 
training and mentorship from a team of mentors and co-mentors. My mentors and co-
mentors include Brian Elbel, PhD, MPH; Joshua Chodosh, MD, MSHS; Christina Roberto, 
PhD; Lorna Thorpe, PhD, MPH; and Andrea Troxel, ScD. My mentors and co-mentors are 
not a part of the study team and will not interact with data at any point. 
 

 
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10.1.8 Quality Assurance and Quality Control 
We will do a soft launch of both the online survey and the web-based supermarket shopping 
experience, to ensure quality of collected data. To prevent subjects from entering multiple 
survey responses, the Qualtrics survey will prevent multiple submissions. The research team 
will also monitor the data collected from participants from the online survey, including 
identifying short duration time. CloudResearch will identify repeat IP addresses. 
 
10.1.9 Data Handling and Record Keeping 
10.1.9.1 Data Collection and Management Responsibilities 
Data will be collected from a national sample of 2,692 low-income adults aged >18 years 
who read and speak English and have ever received SNAP benefits. We will collect online 
survey responses using Qualtrics, and grocery shopping selections using the “Gorilla” web-
based supermarket platform. Participants will be able to access our online survey and the 
web-based supermarket platform via personal computer, laptop, tablet, or mobile phone. 
 
10.1.9.2 Study Records Retention 
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. 
 
10.1.10 Protocol Deviations 
If a protocol deviation occurs, data collection will stop and any corrective action or 
explanation that can be given to participants experiencing this issue will be administered. 
Then, a modification to rectify the issue will be submitted to the IRB (and details sent to the 
sponsor if applicable) and new methods to avoid the problem will be used going forward. 
The study team will work with the IRB to ensure that any problems participants experienced 
prior to the change are ethically addressed. 
 
10.1.11 Publication and Data Sharing Policy 
The Principal Investigator, Pasquale Rummo, holds primary responsibility for publishing the 
study results. The plan is to generate at least 5 manuscripts with work from this award by 
June 2025. 
 
10.1.12 Conflict of Interest Policy 

 
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Any investigator who has a conflict of interest with this study (patent ownership, royalties, or 
financial gain greater than the minimum allowable by their institution, etc.) must have the 
conflict reviewed by the NYU Langone Conflict of Interest Committee with a Committee-
sanctioned conflict management plan that has been reviewed and approved by the study 
sponsor prior to participation in this study.  All NYULH investigators will follow the applicable 
conflict of interest policies. 
 
10.2 Additional Considerations 
The Research Assistant will go through a variety of training to ensure understanding of the 
study protocol and their responsibilities. First, the Principal Investigator will set up an 
individual training session with the Research Assistant to discuss in detail the study aims, 
recruitment methods, confidentiality, and study procedures. Secondly, the study team 
member will shadow the Principal Investigator while they do a test run of the online survey 
and the grocery shopping task and data collection procedures. Thirdly, the Research 
Assistant will do a test run of the online survey and the grocery shopping task and data 
collection procedures with the Principal Investigator shadowing them. 
 
11 – Study Finances 
11.1 Funding Source 
NIH/NIA 
 
11.2 Costs to Subjects 
There are no costs to subjects for being in this study.  
 
11.3 Subject Payment 
Every one in ten participants will be selected randomly and CloudResearch will distribute gift 
cards to winners with money loaded on to it equivalent to the amount of money they spent in 
the study. The PI will randomly select lottery winners using participant ID’s, which are not 
linked to personally identifiable information at any point in the study.   
We will adhere to NYULH Human Subjects Payment Policy.  
 
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