Geo Smoking Study and Neural and Geospatial Examination of Smokers' Exposure to Retail Environments
Phase: NA
Conditions: Smoking, Tobacco, Smoking, Smoking, Cigarette
Sponsor: Abramson Cancer Center at Penn Medicine

 
  
 
 
 
 
GEOSCAN AND REMOTE GEO SMOKING STUDY: NEURAL AND BEHAVIORAL 
CORRELATES OF SMOKERS' EXPOSURE TO RETAIL ENVIRONMENTS 
 
 
 
 
Principal Investigator  
Emily Falk, Ph.D. 
Annenberg School for Communication 
University of Pennsylvania 
​3620 Walnut Street, Philadelphia, PA 19104  
​215-573-9901  
emily.falk@asc.upenn.edu  
 
 
 
Funding Sponsor 
National Cancer Institute (NCI) 
​National Institutes of Health (NIH) 
9609 Medical Center Dr, Rockville, MD 20850 
800-422-6237 
 
 
Protocol Number 
 
IRB Number 
ClinicalTrials.gov Identifier: NCT04279483   
IRB 850796 
ACC Identifier: UPCC# 08022 
 
NIH Grant Number 
 
1R01CA229305-01A1 
 
 
 
 
Version:​
​
​
​
Version 06/02/2025 
 
 
V2025-06 

 
Table of Contents 
● Background and Study Rationale​
5 
1 Introduction​
5 
1.1 Background and Relevant Literature​
5 
2 Study Objectives​
9 
2.1 Primary Objective​
9 
3 Investigational Plan​
9 
3.1 General Design​
9 
3.2 Allocation to Interventional Group​
9 
3.3 Study Measures​
9 
3.4 Study Endpoints​
11 
3.4.1 Primary Study Endpoint​
11 
3.4.2 Secondary Study Endpoints​
12 
4 Study Population and Duration of Participation​
12 
4.1 Duration of Study Participation​
12 
4.2 Total Number of Subjects and Sites​
12 
4.3 Inclusion Criteria​
12 
4.4 Exclusion Criteria​
12 
4.5 Subject Recruitment​
13 
5 Study Procedures​
14 
5.1 Screening​
14 
5.1.1 Screen A​
14 
5.1.2 Initial Call​
14 
5.1.3 Screen B​
15 
5.1.4 Mailing Materials​
15 
5.2 Study Observational Phase​
15 
5.2.1 Online Session 1 (S1)​
15 
5.2.2 Observational Phase​
15 
5.3 Study Interventional Phase​
16 
5.3.1 Online Session 2​
16 
5.3.2 Intervention Phase​
16 
5.3.3 Online Session 3​
16 
5.3.4 Optional fMRI session​
16 
5.4 Unscheduled Visits​
17 
5.5 Subject Withdrawal and Exclusion​
17 
5.5.1 Data Collection and Follow-up for Withdrawn Subjects​
18 
5.6 Early Termination Visits​
18 
5.7 Safety Evaluation​
18 
6 Statistical Plan​
19 
6.1 Sample Size and Power Determination​
19 
6.2 Statistical Methods​
19 
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6.3 Control of Bias and Confounding​
20 
6.3.1 Baseline Data​
20 
6.3.2 Analysis of Primary Outcome of Interest​
20 
6.3.3 Interim Analysis​
22 
7 Safety and Adverse Events​
23 
7.1 Definitions​
23 
7.1.1 Adverse Event​
23 
7.1.2 Serious Adverse Event​
23 
7.2 Recording of Adverse Events​
23 
7.3 Relationship of AE to Study​
24 
7.4 Reporting of Adverse Events and Unanticipated Problems​
24 
7.4.1 Follow-up Report​
24 
7.4.2 Investigator reporting: notifying the study sponsor​
24 
7.4.3 Data and Safety Monitoring Plan​
25 
8 Study Administration, Data Handling and Record Keeping​
26 
8.1 Confidentiality​
26 
8.2 Data Collection and Management​
27 
9 Study Monitoring, Auditing, and Inspecting​
29 
9.1 Study Monitoring Plan​
29 
9.2 Auditing and Inspecting​
30 
10 Ethical Considerations​
30 
10.1 Risks​
30 
10.2 Benefits​
31 
10.3 Risk Benefit Assessment​
31 
10.4 Informed Consent Process / HIPAA Authorization​
31 
11 Study Finances​
32 
11.1 Funding Source​
32 
11.2 Conflict of Interest​
32 
11.3 SUBJECT STIPENDS OR PAYMENTS​
32 
12 Publication Plan​
33 
13 References​
34 
 
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Study Summary 
 
Title 
Remote Geo Smoking Study: Behavioral and Geospatial Correlates of 
Smokers' Exposure to Retail Environments 
Short Title 
Remote Geo 
IRB Number 
850796 
Methodology 
This study will utilize a randomized trial to examine the effects of point-of-sale 
tobacco marketing on smoking behaviors and brain activity. After a two week 
observational period, participants will be randomized to one of three behavioral 
intervention conditions for the duration of a four week intervention period. 
 
Study Duration 
Five years 
 
Study Center(s) 
Single-center 
Objectives 
●​
The primary objectives of this study are to understand the effects of 
point-of-sale tobacco marketing (POST-M) on smoking behavior and cravings 
in smokers. We will examine whether experimental group assignment affects 
cigarette cravings and cigarette consumption during the intervention period 
relative to the baseline period.  
●​
For a subset of participants, we will examine brain responses during 
the smoking cue reactivity task. 
Number of Subjects 
343 [Actual] 
Main Inclusion and 
Exclusion Criteria 
Key Inclusion Criteria for remote participation: 
●​
Be between the ages of 21-65 
●​
Smoke at least 5 cigarettes a day for the past 6 months 
●​
Own an iPhone or Android smartphone that can be used on a daily 
basis 
●​
Be residents of Pennsylvania, New Jersey, or Delaware 
●​
Read and speak English fluently 
●​
Fully vaccinated against COVID-19 
Key Exclusion Criteria  for remote participation: 
●​
Current enrollment or plans to enroll in a smoking cessation program 
in the next 3 months 
●​
Plan to use nicotine substitutes or smoking cessation treatments in the 
next 3 months 
●​
Urine cotinine concentration below 200ng/mL 
●​
Pregnancy 
●​
Inability or refusal to complete study tasks 
 
The complete list of study inclusion and exclusion criteria, including exclusion 
criteria for the fMRI subset, is included within the Characteristics of the Study 
Population section of this protocol. 
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Intervention  
 
Random assignment of retail environment (high POSTM; low POSTM, control 
[no store]) to visit 5 times per week during the 4-week intervention period. 
Statistical 
Methodology 
 
We will use linear regression and multilevel models (in R) to test our 
hypotheses, as well as tools from nipype, SPM, and fmriprep to process 
and model fMRI data.  
 
Data and Safety 
Monitoring Plan  
The principal investigator will monitor the safety, privacy, and data 
integrity during the course of the study. In addition, we will 
provide the required project reports to the sponsor. 
 
●​
Background and Study Rationale 
 
This document is a protocol for a human research study. This study will be conducted in full accordance 
with all applicable University of Pennsylvania Research Policies and Procedures and all applicable 
Federal and state laws and regulations. 
1​
Introduction 
 
Cigarette smoking is the leading cause of preventable death and illness in the United States and 
throughout the developed world. Recent work suggests detrimental links between exposure to 
point-of-sale tobacco marketing (POSTM), increases in cigarette cravings, and the failure to quit 
smoking. Understanding how individuals are influenced by and react to environmental cues 
when making health decisions is critical to cancer control efforts and policymaking. We propose 
to use an innovative set of methods to test whether repeated, real-world exposure to POSTM 
affects smoking behavior, and whether this is mediated by changes in craving and neural 
responses to POSTM. Our approach combines mobile-phone based geolocation tracking, 
ecological momentary assessment (EMA), and functional magnetic resonance imaging (fMRI). 
Research using geospatial location tracking and surveys suggests that high levels of POSTM 
exposure may increase craving; however, correlational studies preclude causal inferences about 
POSTM effects. Relatedly, laboratory studies have documented neural and behavioral reactivity 
to standardized visual smoking cues, such as photographs of cigarettes in an ashtray, but the 
brain’s response to naturalistic POSTM exposure has not been explored. By adding the 
ecological validity of observational field methods to the mechanistic insight of neuroimaging, and 
causal inferences from an experimental pre-post design, we aim to significantly advance 
actionable insight about POSTM effects in cancer control.  
 
1.1​
Background and Relevant Literature  
 
Summary: 
The tobacco industry has come to rely increasingly on point-of-sale tobacco  marketing 
(POST-M), with  large displays near cash registers in retail outlets such as convenience stores 
and gas stations [1]. Recent  work utilizing geospatial location tracking has found that smoking 
V2025-06 

 
lapses while smokers are trying to  quit are more likely on days when smokers are exposed to 
POST-M, particularly when their general  tobacco craving levels are otherwise low [2]. This 
suggests that POST-M exposure may increase craving,  making abstinence more difficult. This 
finding converges with recent survey results demonstrating that  during quit attempts, a 
significant percentage of smokers experience urges to purchase cigarettes when  exposed to 
POST-M, and feel that the removal of POST-M would make quitting easier [3]. These reports  
indicating that incidental exposure to cigarette cues adversely affects smoking abstinence are 
supported  by laboratory studies. A typical laboratory cue reactivity paradigm involves 
presenting participants with pictures or video of  smoking cues, such as a hand holding a 
cigarette, followed by a measurement of participants' craving  intensity. Smoking abstinence has 
been found to potentiate  self-reported craving in response to cigarette cues [4-7,8],  suggesting 
a mechanism for the finding that exposure to POST-M during a quit attempt leads to poorer  
outcomes. No studies, however, have experimentally manipulated exposure to POST-M cues in 
vivo. To this end, we will examine whether assigning smokers to a high or low level of POST-M 
exposure as part of their daily routine affects  several smoking outcomes. A location tracking 
smartphone application (Google Maps) will be used to  document participants’ exposure to retail 
outlets and link each person to the retail environment.  Measurements will assess longitudinal 
tobacco-use patterns and perceptions across the study period, as  well as changes in cravings. 
If it is the case that low POST-M exposure reduces smoking, this emphasizes the importance of 
further regulation of retail advertising for  tobacco.  
 
In addition to the hypotheses and analysis plans described here, the study team has 
preregistered additional hypotheses and analysis plans which are not the focus of the clinical 
trial component of the study. These are available at https://osf.io/kyb64/registrations.  
 
Background: 
Tobacco dependence is a significant public health problem. Cigarette smoking is the 
leading cause of preventable death and illness in the United States and throughout the 
developed world1. Smoking increases the odds of developing the most frequently diagnosed 
cancers and other leading causes of death, accounting for 1 in 5 deaths in the US each year 2,3. 
Due to restrictions in other communication outlets, the tobacco industry currently concentrates 
over 80% of its $8.1 billion annual marketing budget on retail environments, including 
point-of-sale tobacco marketing (POSTM)4–8. Tobacco advertising and products are placed 
prominently in “power walls” near or behind cash registers in retail outlets like convenience 
stores and gas stations9,10,11, such that all customers are exposed to this marketing. This 
widespread and frequent exposure to POSTM in smokers and nonsmokers alike is of great 
interest in tobacco control and cancer prevention research worldwide, and has led to recent 
bans of POSTM in 42% of countries in Europe12. In this study, we aim to test whether repeated, 
real-world exposure to POSTM affects smoking behavior through heightened neural smoking 
cue reactivity and subjective craving. We will test both correlational (Aims 1-2) and causal (Aim 
3) pathways. To this end, we propose an innovative combination of geolocation tracking as an 
ecologically valid, objective measure of real-world POSTM exposure13,14;  ecological momentary 
assessment (EMA)15 to assess real-time behavior and craving; and functional magnetic 
resonance imaging (fMRI) to assess neural responses to cigarette cues16–18. Understanding both 
the neural (laboratory-based) and behavioral (real-world) consequences of exposure to POSTM 
will clarify the mechanisms of POSTM impact, and ultimately aid in the design of more effective 
cancer prevention and tobacco regulatory policies. 
 
How are smokers influenced by point-of-sale tobacco marketing (POSTM)? Past work 
suggests detrimental relationships between exposure to POSTM and other environmental 
smoking cues and smoking behavior in individuals (e.g.,19,20) and the larger population (e.g.,21) 
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across countries, measures and study designs (for a review:22). Within current and recently quit 
smokers, field work consistently reports associations between POSTM exposure in naturalistic 
settings, and increased smoking cravings, purchase urges, and impulse purchases23–28. The 
density of POSTM in an individual’s neighborhood, a proxy for exposure, also influences 
smoking behavior29–33; for example, longitudinal work finds that smokers are more likely to 
relapse during a quit attempt if they live near a POSTM store34. In a virtual store study, enclosing 
the POSTM display reduced smokers’ purchase attempts and urges to smoke35. This body of 
research thus suggests that further regulation of POSTM would be beneficial from a cancer 
control perspective; however, causal evidence linking longitudinal, naturalistic exposure and 
smoking outcomes, as well as neural evidence supporting the mechanisms of cumulative and 
causal effects, would substantially bolster science-based policy making. 
 
The significance of geolocation tracking and ecological momentary assessment. 
Geolocation tracking provides the unique ability to objectively and unobtrusively assess 
participants’ exposure to POSTM outlets. The recent ubiquity of geolocation tracking built-in to 
smartphones provides the opportunity for incorporating this methodology into experimental 
designs with reduced participant burden. This is a significant improvement over prior POSTM 
exposure work, which is limited by reliance on self-reports of the timing and degree of POSTM 
exposure, or by the need to initiate or observe single, non-representative exposures. In PA, DE, 
and NJ, where data collection will take place, obtaining a local cigarette dealer license is 
mandatory for cigarette retailers36 and listings of licensed outlets are publicly available and 
updated monthly37. Layering smokers’ geolocation tracks onto maps of tobacco retail outlets 
allows objective quantification of an individual’s exposure to POSTM in their natural 
environment. 38. In parallel with geolocation tracking, we will sample participants’ behaviors and 
craving throughout each day using EMA, to capture time-sensitive fluctuations in a 
representative manner15. EMA optimally complements the naturalistic geolocation tracking data 
by tagging participants’ location history with reports indicating natural smoking behavior and 
craving on a moment-to-moment basis. Thus, this project will link individuals’ smoking cravings 
and behavior to the POSTM environment in both time and location. Our team’s expertise with 
mobile device-based EMA collection41,42 makes us uniquely suited to conduct this multi-level 
integrative research. 
 
Combining responses to tobacco-related cues in the real world and cue-reactivity in the 
neuroimaging laboratory will provide a mechanistic understanding of how POSTM 
influences smokers. The scientific premise for this study derives from theoretical models and 
empirical studies of addiction, which suggest that exposure to drug-cues, such as images of 
drug paraphernalia, enhances craving and consumption behavior in drug users, including 
smokers43,44. Laboratory work has shown increased neural activity in regions associated with 
drug cue-reactivity as well as increased ratings of subjective craving in smokers after exposure 
to smoking cues such as pictures of cigarettes16,43. Craving ratings scale positively with neural 
cue-reactivity17,45,46, and both metrics predict smoking behaviors in a later ad-lib smoking 
session 18,47. Thus, laboratory experiments implicate neural smoking cue reactivity and cigarette 
craving as mechanisms linking exposure to smoking cues and behavior. In contrast to many 
other addictive substances, advertising for cigarettes is professionally produced, legal, and 
prevalent in smokers’ natural environments. Neural cue reactivity effects have been generalized 
from completely standardized cues to more naturalistic pictures of personal smoking 
environments, such that exposure to photographs of places where participants often smoke 
(e.g., one’s home) evokes stronger neural and behavioral craving responses than exposure to 
generic environmental photographs (e.g., an unfamiliar bus stop)18,48,49; however, the 
generalizability of such effects to POSTM cues and complex retail environments has not been 
tested. We will test whether baseline exposure to photographs of POSTM elicits activation in the 
V2025-06 

 
same brain regions as standardized, proximal smoking cues. A recent meta-analysis shows that 
a specific set of neural regions consistently responds more strongly to standard smoking cues 
as compared to neutral images, including the extended visual system, precuneus, posterior 
cingulate gyrus, anterior cingulate gyrus, dorsal and medial prefrontal cortex, insula, and dorsal 
striatum16.  
 
Brain activity as a key, mechanistic indicator of message impact over time. Functional 
neuroimaging allows an unobtrusive examination of both conscious and unconscious processes 
induced by exposure to standard smoking cues16 and mediated messages such as marketing 
materials50–52. Our team and others have developed multi-method approaches to test the 
generalizability and predictive validity of laboratory-based neural effects to real-world behaviors 
51–69. This work has shown that neural reactivity to persuasive messaging inside the fMRI 
scanner reliably predicts health behaviors, including reductions in smoking and sedentary 
behavior, above and beyond the predictive capacity of commonly used self-reports 
51,59,60,64,65,70–75. Further, findings obtained in small groups have been shown to be scalable, such 
that message-induced neural activity in small samples has been used to predict population-level 
message impact, including the generation of quitline calls 51 and sharing of health-related 
information 76,77. In a past experimental health intervention, our team successfully used brain 
activity to predict experimental effects on subsequent behavior at timepoints up to a month later 
62.  
 
Causal manipulation of exposure to tobacco marketing. Most extant field work focused on 
POSTM, despite including large samples and naturalistic settings, has been correlational, with a 
few notable exceptions. For example, Shadel et al created an experimental convenience store, 
and found that removal of the POSTM power wall reduced susceptibility to future cigarette 
smoking in adolescents78. The current study proposes to significantly extend these findings by 
manipulating adult smokers’ real-world, daily POSTM exposure over the course of one month, 
rather than assessing the impact of a single exposure in one experimental session. After an 
observation period of geolocation tracking and EMA, individuals will be randomly assigned to 1 
of 3 groups. Two groups enter and make small, non-tobacco purchases at a store which 
displays POSTM (tobacco retailer condition) or a store that displays pro-cessation messaging 
(nontobacco retailer condition). Approaching the register for this purchase constitutes an 
exposure to POSTM (tobacco retailer condition) or pro-cessation marketing (nontobacco retailer 
condition). A third group receives no instruction to change their routine exposure to POSTM.  
 
 
 
2​
Study Objectives 
2.1​
Primary Objective 
 
The primary objectives are to examine the relationships between smoking behavior, cigarette 
cravings, and exposure to point-of-sale tobacco marketing. We will examine whether 
experimental group assignment affects cigarette cravings and cigarette consumption during the 
intervention period relative to the baseline. For the subset of participants who undergo fMRI 
scanning, we will compare craving ratings and brain activity during different task conditions.  
V2025-06 

 
3​
Investigational Plan  
3.1​
General Design 
Study Type:​
Interventional 
Primary Purpose:​
Other 
Study Phase:​ N/A 
Interventional Study Model:​ Parallel Assignment 
Random assignment of retail environment (tobacco retailer, non-tobacco retailer, no store) to 
visit 5 times per week during the 4-week intervention period 
 
Number of Arms:​
3 
Masking:​
Single (Investigator) 
Investigator will not know the condition assignment of individual participants unless 
reassessment is triggered by the stopping rule. 
 
Allocation:​
Randomized 
Enrollment:​
343 [Actual] 
 
3.2​
Allocation to Interventional Group  
 
Participants who completed the required tasks during the baseline period were 
randomized within blocks [blocked by gender (male, female, other) and smoking level (high, 
low; high was 20 cigarettes or greater per day)]. At the beginning of data collection, condition 
assignment was fully random; blocked-randomization was implemented part-way through the 
study on 12/01/2022. 
3.3​
Study Measures 
 
 
SCREEN ​
A 
SCREEN​
 B 
INITIAL 
CALL 
SURVEY 
1 
BASELINE SURVEY 
2 
INTERVENTIO
N 
SURVEY 
3 
FMRI 
Measures 
 
 
 
Day 0 
Day 1 – 15 Day 15 
Day 15 – 45 
Day 45 
 
 
 
 
 
 
 
 
 
 
 
File submissions  
 
 
 
 
 
 
 
 
Vaccination card 
(photo) 
 
X 
 
 
 
 
 
 
 
Location tracking 
(timeline export)  
X 
 
 
 
X 
 
 
 
Urine cotinine test 
(photo) 
 
 
 
X 
 
 
 
 
X 
Receipts (photos)  
 
 
 
 
 
20X 
 
 
Screening and 
Covariates 
 
 
 
 
 
 
 
 
 
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Eligibility 
screening 
X 
X 
 
 
 
 
 
 
 
Smoking 
behavior survey 
 
 
 
X 
 
X 
 
X 
1 item 
Nicotine 
dependence 
survey (FTND) 
 
 
 
X 
 
X 
 
X 
X 
Smoking habits 
survey 
 
 
 
X 
 
 
 
X 
 
Smoking 
cessation 
intentions survey 
 
 
 
X 
 
 
 
X 
 
Smoking info 
exposure 
questionnaire 
 
 
 
X 
 
X 
 
X 
 
Smoking beliefs 
survey 
 
 
 
X 
 
 
 
X 
 
Smoking 
attitudes survey 
 
 
 
X 
 
 
 
X 
 
Social smoking 
norms survey 
 
 
 
X 
 
 
 
X 
 
Smoking 
motivation 
survey 
 
 
 
X 
 
 
 
 
 
Tobacco policy 
support 
questionnaire  
 
 
 
X 
 
 
 
X 
 
Social 
interactions & 
smoking survey 
 
 
 
 
 
X 
(weekly 
survey) 
4X (weekly 
survey) 
 
 
Demographics 
survey  
 
 
 
X 
 
 
 
 
 
Stressful Life 
Experiences 
Inventory  
 
 
 
 
 
X 
 
 
 
Microaggression
s survey 
 
 
 
X 
 
X 
(weekly 
survey) 
4X (weekly 
survey) 
X 
 
Purpose in life 
survey 
 
 
 
X 
1 item 
daily 
 
1 item daily 
 
 
Smoker 
self-concept 
survey 
 
 
 
X 
 
 
 
X 
 
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Perceived stress 
scale 
 
 
 
X 
 
 
 
X 
 
CES-D 
Depression 
scale 
 
 
 
X 
 
 
 
X 
 
Code switching 
survey 
 
 
 
X 
 
 
 
X 
 
Mindfulness 
(MAAS) 
 
 
 
 
 
 
 
 
X 
Impulsiveness 
(BIS-11) 
 
 
 
 
 
 
 
 
X 
Alcohol 
consumption 
 
 
 
 
 
 
 
 
X 
Outcomes 
 
 
 
 
 
 
 
 
 
Cigarette 
consumption- 
self-report 
 
 
 
X 
 
X 
 
X 
 
EMA text surveys 
- smoking and 
craving  
 
 
 
 
X 
 
X 
 
 
Cue reactivity task  
 
 
 
 
X 
 
X 
X 
​
 
​
 
3.4​
Study Endpoints  
3.4.1​ Primary Study Endpoint 
 
 
The primary endpoints will be cigarette smoking and craving at the end of the intervention 
period, measured through EMA multiple times daily. The primary endpoints for the fMRI scan 
session will be measured through fMRI scanning (brain activity). 
3.4.2​ Secondary Study Endpoints 
 
4​
Study Population and Duration of Participation  
 
The target population is current smokers, ages 21-65, who have smoked at least 5 cigarettes a 
day for the past 6 months, are smartphone users, and live in PA/NJ/DE. 
4.1​
Duration of Study Participation  
The target behaviors (smoking frequency, cravings for cigarettes) will be assessed for an 
approximately 2 week baseline period and for an approximately 4 week intervention period. 
Thus, total study participation is expected to be approximately 6 weeks of active participation, 
with possible breaks in between the baseline and intervention periods. Total duration of 
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participation will thus be approximately 2 months, with some exceptions (such as pauses in 
active participation because of the University’s special winter vacation, or as requested by 
participants due to external constraints). A subset of participants will be invited to complete an 
optional fMRI scan after their final online session; flexibility will be allowed in the timing of the 
scan session, which can be as long as 6 months after the final online session. This subset of 
participants will participate for a longer duration (total duration of participation can be up to 8 
months [2 months of active participation, with a scan session up to 6 months later]. 
4.2​
Total Number of Subjects and Sites  
 
Our initial recruitment plan specified that “Recruitment will end when approximately 400 
participants have been enrolled. It is expected that 400 enrolled participants will produce 180 
evaluable subjects after attrition and data issues. Penn is the only site.” See 6.1 for final plan, 
adjusting for COVID and other constraints. 
4.3​
Inclusion Criteria 
 
●​
Be between the ages of  21-65 
●​
Smoke at least 5 cigarettes a day for the past 6 months 
●​
Own an iPhone or Android smartphone that can be used on a daily basis 
●​
Be residents of Pennsylvania, New Jersey, or Delaware 
●​
Read and speak English fluently 
●​
Fully vaccinated against COVID-19 
4.4​
Exclusion Criteria 
●​
Current enrollment or plans to enroll in a smoking cessation program in the next 3 
months   
●​
Plan to use nicotine substitutes or smoking cessation treatments in the next 3 months   
●​
Pregnancy   
●​
Refusal to install Google Maps or LifeData applications on mobile phone  
●​
Inability or refusal to upload Google Timeline data after receiving instructions and 
guidance during or after the initial intake call   
●​
During the ﬁrst two weeks of the study, failure to complete the study tasks (response to 
at least 75% of the brief EMA survey questions)  
●​
Urine cotinine testing at Session 1 indicates a non-smoker level of cotinine  
●​
The phones of potential participants will be assessed by trained recruiters during a 
phone call used to invite eligible participants who completed Screen A to participate in the study. 
Speciﬁcally, recruiters will assess whether phones' functionality allows easy reception and 
sending of text messages, the use of the geolocation tracking and LifeData applications and 
whether phones have an adequate battery life to allow participants to fulﬁll study requirements.  
●​
Inability to provide informed consent or complete any of the study tasks as determined 
by the Principal Investigator and/or Study Physician.   
●​
Any physical or visual impairment that may prevent the individual from using a computer 
keyboard or completing any study tasks. 
Additional criteria for fMRI component: 
●​
Demonstrate urine cotinine concentration below 200 ng/mL at scanning session 
●​
Currently or recently (within the last 5 years) receiving medical treatment for substance 
abuse (e.g., alcohol, opioids, cocaine, marijuana, or stimulants). Treatment of substance use 
disorders that occurred greater than 5 years prior to study participation is acceptable if 
participants are in stable condition 
V2025-06 

 
●​
Report consuming any of the following drugs within the past two weeks or indicate plans 
to do so within the coming 6 weeks during the screening call: Benzodiazepines, Amphetamines, 
Methamphetamines, Cocaine, MDMA, Methadone, Barbiturates, PCP, Heroin, Oxycodone, 
Opiates (e.g., morphine, heroin), Buprenorphine  
●​
Test positive for any of the above drugs at the scan appointment 
●​
Schizophrenia or psychosis, regardless of treatment status. 
●​
History of stroke or other neurological disorder likely to affect cognition  
●​
Psychiatric hospitalization within the past year  
●​
Propensity to experience claustrophobia  
●​
Ferromagnetic metal in the body, including anything that might set off a metal detector. 
Examples include bullet shrapnel, metal shavings (e.g., from welding without protection), or any 
implant that may be attracted to or damaged by magnets. Dental fillings are generally 
acceptable.  
●​
Metal in the body of an unverifiable origin.  
●​
Non-removable piercings.  
●​
Non-removable retainers or other dental work not compatible with fMRI.  
●​
Any orthopedic implant above the neck.  
●​
Due to constraints of the fMRI scanner, participants whose weight exceeds 350 pounds 
also will be excluded. The size of the scanner will be discussed with all participants during the 
consent addendum procedure.  
●​
Any medical condition or concomitant medication that could compromise participant 
safety or treatment, as determined by the Principal Investigator and/or Study Physician. 
●​
Unable to schedule a scan within 6 months after completing the third Online Session 
4.5​
Subject Recruitment  
 
Direct recruitment may occur through newsletters, fliers, online ads/posts (e.g., Craigslist, 
Facebook, Instagram), newspaper listings, and/or ads on TV (or streaming media services). 
Recruitment materials may be posted by the study team or by BuildClinical. We will also 
collaborate with another smoking research group at the University of Pennsylvania which has 
IRB approval for passing on contact information of interested participants to other research 
teams. Only participants who have indicated that they are interested in being contacted for 
future studies will be approached. Upon contact, it will be made clear to participants that there is 
a possibility for them to participate in the study and they will be provided with IRB-approved 
recruitment materials such as flyers, text, and/ or oral information about the study, depending on 
the mode of contact. All recruitment material will include links (e.g., URLs, QR codes) directing 
potential participants to the screening survey (Screen A). The study email address and/or phone 
number may be included, depending on the recruitment medium. Interested individuals will 
complete Screen A on their own device at a time that is convenient to them. 
 
 
Vulnerable Populations:  
 
Not applicable 
5​
Study Procedures  
 
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5.1​
Screening  
5.1.1​ Screen A 
Those who express interest in the study by reacting to the recruitment efforts will be directed 
towards an online screening survey (Screen A) where they answer questions relevant to their 
eligibility for the study and provide their contact information. Screen A will also include a 
question that asks about the participants’ interest in receiving information on opportunities to 
participate in other remote and/or in-person studies.  
●​
Screen A will be administered online via RedCap or BuildClinical and is estimated to 
take less than 5 minutes to complete.  
●​
[Note: If one’s screening survey responses indicate that they are not eligible to 
participate in this study, they will receive an email informing them of this.]  
●​
[Note: If one's screening survey responses indicate that they are interested in, and 
potentially eligible for, the in-person version of this study (protocol 822815), they may be 
provided a link to that study’s screening survey and will be filtered through the process outlined 
in the 822815 protocol. If they are then found to be ineligible for the in-person study, they may 
be redirected to this remote study.]  
 
Survey respondents who are potentially eligible to participate in the remote study will be emailed 
and/or texted a link to Calendly (appointment booking system) to allow participants to sign up for 
a time for an initial phone call to find out more about the study.  
 
5.1.2​ Initial Call 
During the initial call, participants will be informed about the study, including the risks and 
benefits of participation, and will be given the opportunity to ask questions. Eligibility criteria will 
be confirmed on this call as needed.  
●​
The initial call will be conducted over the phone (Google Voice) and is expected to take 
approximately 30 minutes. The researcher conducting the call will enter participant responses 
into RedCap. 
 
At the end of the initial call, potential participants who are still eligible and interested will be 
invited via email to complete Screen B at a time of their choosing within 1 month of the initial 
call. 
5.1.3​ Screen B 
Screen B begins with a RedCap e-consent form for the screening survey, which will guide 
potential participants to provide their shipping address and submit a picture of their COVID-19 
vaccination card. The instructions will then guide them through downloading and/or setting up 
Google Maps on their phone, then exporting and uploading their Google timeline (location 
history) data.  
●​
Screen B will be administered online using RedCap and Qualtrics (with Penn Box as a 
back-up method for submitting location data, if needed). The screen is expected to take 5 - 15 
minutes of active participation, which excludes the passive time (when participants are not 
asked to do anything) while Google is compiling the participants Timeline data for export. 
●​
Potential participants who have difficulty with the Google Maps set-up or timeline export 
will be able to sign up for an additional phone/video call at a later time to receive help from a 
researcher.  
 
V2025-06 

 
Researchers will then confirm A) that potential participants live in the study area (PA, NJ, or DE) 
using the uploaded timeline data and shipping address and B) that the potential participant is 
fully vaccinated against COVID-19, both of which are required to be eligible to participate in this 
study.  
●​
[Note: Those who are unable/unwilling to complete any component of Screen B, live 
outside of the specified study area, or are not fully vaccinated will be ineligible for this study and 
will not be given the opportunity to enroll. The team will inform them of their ineligibility, delete 
their geolocation data, and provide them with instructions for turning off Google Timeline and 
uninstalling Google Maps.]  
●​
[Note: If potential or enrolled participants are no longer interested in enrolling in the 
study at any point during or after the Google Maps set up, they will be provided with instructions 
for turning off Google Timeline and uninstalling the app.] 
5.1.4​ Mailing Materials 
Eligible individuals will then be mailed a box containing study materials, including items such as 
the urine cotinine test, KN95/KF94 or N95 masks, and a Greenphire Clincard. Upon receipt of 
the study materials, participants will be given instructions to enroll in the study and begin their 
participation by completing Session 1.  
5.2​
Study Observational Phase  
5.2.1​ Online Session 1 (S1) 
In Session 1, participants will read through the consent form and provide electronic consent via 
RedCap to participate in the full study and provide information required for payment (legal 
name, date of birth, and Social Security number). Participants will then follow the survey 
instructions to: complete physiological measurements (urine cotinine) and self-report measures; 
receive instructions for the Baseline period EMA task and answer questions assessing their 
comprehension of the task; and install, set up, and practice using RealLife Exp (the EMA app) 
on their smartphone. 
●​
Session 1 will be administered over RedCap and Qualtrics, and is expected to take 
30-60 minutes. 
●​
If a participant’s urine cotinine test result is not above the threshold required for eligibility, 
the participant will be excluded from continuing in the study. 
5.2.2​ Observational Phase  
The baseline period will begin after completion of Session 1, and will last for 14 days. During the 
baseline period, participants will complete EMA and location tracking.  
●​
Participants will be excluded for non-compliance at the end of the baseline period if they 
have not responded to at least 75% of EMA prompts.  
●​
Following the baseline period, participants will be assigned to an experimental condition.   
 
 
5.3​
Study Interventional Phase 
5.3.1​ Online Session 2 
Participants will be invited to complete Session 2 online after completing the baseline 
observational period. They are encouraged to complete the session within 4 days and no longer 
than 1 week (with possibility for exceptions at experimenters discretion) after receiving the 
invitation. Participants complete self-report measures; an image rating task; geolocation data 
V2025-06 

 
export and upload; EMA setup and practice; and instructions and practice for the Intervention 
tasks. 
●​
Session 2 will be administered over Qualtrics, and is expected to take 30-60 minutes.   
5.3.2​ Intervention Phase  
The Intervention Period will begin after completion of Session 2. During the 4 week intervention 
period, all participants will complete EMA, location tracking, and weekly surveys. The speciﬁc 
study-related tasks participants are asked to carry out during the intervention period depends on 
which experimental group they have been randomized to. The two experimental groups 
(tobacco retailer and nontobacco retailer) will be asked to enter a speciﬁc store 5 times per 
week for 4 weeks. The control group will not be asked to enter a store.  
5.3.3​ Online Session 3 
Following the Intervention Period, participants will be invited to complete Session 3 online, 
which they are encouraged to complete within 4 days and no longer than 1 week (with 
possibility for exceptions at experimenters' discretion) of receiving the invitation. Participants will 
complete surveys; an image rating task; and geolocation data export and upload. At the end of 
the session, participants will be instructed on how to uninstall study-related smartphone 
applications and turn off smartphone location tracking, as desired. If not interested in and/or 
potentially eligible for the scan session, participants will also be provided with a debrieﬁng form, 
which includes details about the study procedure and research goals, and may request a phone 
call or video call to go over the content of the form.  They will be provided with a Quit Resources 
document, which contains information about services that provide smoking cessation 
assistance. For participants interested in being screened for the scan, debriefing and provision 
of the quit resources document will occur after the scan or as soon as scan session ineligibility 
is determined. 
5.3.4​ Optional fMRI session 
●​
fMRI Screening: Participants who complete Session 3 and are potentially eligible to 
participate in the optional, in-person fMRI session (as determined by self-report questions in 
previous screening surveys and online sessions) may be informed of the opportunity and invited 
to complete an additional, optional fMRI screening survey. The fMRI screen will contain 
questions relevant to their eligibility for the in-person component of the study. 
●​
fMRI session: This is a 2 hour session. After confirming that the participant meets any 
COVID-19 screening requirements (e.g., symptom screen, temperature check), during the 
in-person session, researchers will review the consent addendum document with participants. 
After providing written informed consent, participants will complete any required forms (e.g., 
W-2, additional metal screen) and provide a urine sample to confirm eligibility. Eligible 
participants will receive safety and task-related instructions/training before completing the fMRI 
scan. During the 1-hour scan component of the session, participants will complete an image 
rating task. Depending on time of arrival, participants may be asked to complete a brief survey 
before and/or after the scan.  
 
5.4​
Unscheduled Visits 
 
At the end of Screen B and at the end of each online session, participants will be invited to 
provide feedback on their experience in the study to that point, via an open answer text box. We 
may follow up with participants by email or phone to clarify feedback as needed. 
 
V2025-06 

 
5.5​
Subject Withdrawal and Exclusion  
 
Subjects may withdraw from the study at any time without penalty. Participation in the study may also be 
stopped at the discretion of the Investigator for lack of adherence to study instructions, or if the 
Investigator determines exclusion is best for subject safety or health. Specific exclusion criteria are 
detailed below. 
ONLINE SESSION 1: If a participant's cotinine test result is not above the threshold required for 
eligibility, the participant will be excluded from continuing in the study. Participants who are 
found to be ineligible during Session 1 (e.g. due to the results of their cotinine tests) will be paid 
$75 on their Clincard for the tasks they completed but will be excluded from continuing their 
participation in this study. 
BASELINE PERIOD: If participants are excluded (e.g., for responding to less than 75% of EMA) 
or withdraw during the baseline or intervention periods, they will be issued payment on their 
Clincard at the rate of $4 per day that they responded to at least 75% of EMA surveys.  
INTERVENTION PERIOD: Participants in the experimental group who discontinue participation 
during the intervention period will also be paid according to the standard schedule for EMA 
compliance ($4/day at 75% or higher) and receipt submission ($5 per veriﬁed daily receipt). 
Participants who do not complete required study tasks during the intervention (e.g., submitting 
fewer than 20 store receipts, EMA compliance below 75%) will not receive the study completion 
bonus. 
Withdrawn and excluded participants who complete an optional offboarding call will be 
compensated for their time at a rate of $15/hour.   
FMRI SESSION: Participants who must be excluded or asked to reschedule by the 
experimenter after arriving for the in-person session will be paid $15 for their time via their 
ClinCard or petty cash. 
 
In the event of lateness, technical issues, unexpected ineligibility for specific components of the 
protocol, or any reason that a participant is unable to complete a specific portion of the protocol, 
the study team may have them complete all other portions for which they are eligible to 
complete at the experimenters discretion and pay them the standard compensation rate. 
 
5.5.1​ Data Collection and Follow-up for Withdrawn Subjects 
  
All withdrawn and excluded participants are sent instructions to turn off location tracking & delete 
the RealLife Exp app. They are also informed that they can contact us to schedule an optional 
offboarding call if they would like assistance with this process. This optional offboarding call will be 
compensated for their time at a rate of $15/hour. These participants will also be sent a link to 
submit geolocation data for a final time for an additional $5 payment (estimated 20 minutes at a rate 
of $15/hour). 
5.6​
Early Termination Visits   
 
All withdrawn and excluded participants are sent instructions to turn off location tracking & delete 
the RealLife Exp app. They are also informed that they can contact us to schedule an optional 
offboarding call if they would like assistance with this process. This optional offboarding call will be 
V2025-06 

 
compensated for their time at a rate of $15/hour. These participants will also be sent a link to 
submit geolocation data for a final time for an additional $5 payment (estimated 20 minutes at a rate 
of $15/hour). 
5.7​
Safety Evaluation  
 
We evaluated safety according to our original plan: 
1.​
 After collection of 60 participants (approximately 20 in each group) and 120 participants 
(approximately 40 in each group), we will use EMA data to identify:  
a.​
The distribution (histogram) of each participant’s daily cigarette consumption (𝑐𝑖𝑔/𝑑𝑎𝑦)
during the baseline period (b0) 
i.​Including each ppt’s mean baseline consumption (
)& standard deviation (
 
𝑐𝑖𝑔𝑠/𝑑𝑎𝑦𝑏0
𝑆𝐷𝑏0)
b.​
The distribution (histogram) of each participant’s daily cigarette consumption (𝑐𝑖𝑔/𝑑𝑎𝑦)
during weeks 3 and 4 of the intervention period (i3-4) 
i.​Including each ppt’s mean consumption (
) & standard deviation 
for 
𝑐𝑖𝑔𝑠/𝑑𝑎𝑦𝑖3−4
(𝑆𝐷𝑖3−4)
intervention weeks 3 and 4 
 
2.​
Participants will be identified as “increased smokers” if their average daily cigarette 
consumption during the final 2 weeks of the intervention period is more the 3 standard 
deviations above their baseline mean 
a.​
Increased smokers:         
 >  ( 
+ 3SD) 
𝑐𝑖𝑔𝑠/𝑑𝑎𝑦𝑖3−4
𝑐𝑖𝑔𝑠/𝑑𝑎𝑦𝑖3−4
 
3.​
If the number of “increased smokers” in the Tobacco retailer condition is significantly (p≤
.01) greater than the number of “increased smokers” in the control condition, this will trigger the 
study team to reconvene for a reassessment with members of the study team, the Primary 
Investigator, the Co-Investigators who have expertise in tobacco research, and the external 
stakeholders. This may result in the termination of this arm of the study and reassignment of 
future participants to the other two groups. Additionally, as part of this review, we will reach out 
to the participants in all conditions who met the criteria for an “increased smoker” to offer 
additional counseling on smoking cessation resources.  The group will further make a plan to 
mitigate future risks to participants.  
 
6​
Statistical Plan 
6.1​
Sample Size and Power Determination 
 
Our initial target was to obtain 60 complete datasets (meaning that participants finished Online 
Session 3, two fMRI sessions [before and after the intervention period], and also completed all 
20 store visits) per intervention condition (total N = 180). Due to pandemic-related resource 
constraints and time delays, we were unable to reach this goal. We collected the maximum 
number of participants possible with the resources available from our grant. Prior to looking at 
the data, we elected to randomize more individuals into the experimental conditions than to the 
control condition, since less than 50% of participants typically completed all 20 store visits and 
provided fully complete datasets. Before we conducted any hypothesis testing, we reassessed 
power in consultation with our study team’s biostatistician to determine which original 
hypotheses would be adequately powered with the available data and planned analysis 
V2025-06 

 
methods. Using PANGEA, we estimated that with at least 40 complete datasets (participants 
who completed all 20 store visits) in each intervention condition, we could detect interaction 
effects (time * group) sized d = 0.1 with 95% power. We ultimately randomized 105 to the 
Non-tobacco retailer condition, 107 participants to the Tobacco retailer condition, and 70 
participants to the Control condition resulting in 175 complete datasets. We scanned as many 
participants as we were able to obtain within constraints of the larger study. Power analysis 
suggests that with N=32 and at least 10 observations per condition in the fMRI dataset, per 
participant, we have >80% power to detect effects of d = .2 (i.e., a small effect size) within 
person. 
 
6.2​
Statistical Methods 
 
Behavioral data (ecological momentary assessment, smoking behavior) as well as neural 
activity aggregates from regions of interest will be analyzed using the statistical software R. 
Data will be analyzed using multi-level regression and repeated measures ANOVA, or 
alternative appropriate statistics, given observed distributions.  
 
fMRI data will be analyzed using Statistical Parametric Mapping (SPM; Wellcome Trust Centre 
for Neuroimaging) and NiPype. We will examine neural responses to tobacco marketing and to 
other smoking-related images, and how these responses relate to tobacco marketing exposure 
in the real-world, as well as group differences in these responses. 
Prior to analysis, we will apply standard data screening/cleaning procedures to: (a) screen for 
data-entry errors, (b) check for outliers, (c) assess the extent and pattern of missing data, (d) 
create all summary scores needed for analysis, and (e) check that appropriate assumptions of 
normality are met. The assumptions underlying the application of all the statistical methods that 
are used will be examined, principally through the use of standardized residuals, influence 
diagnostics, and graphical displays. Neuroimaging analysis will be done in nipype and SPM12, 
beginning with slice-time correction, realignment, coregistration of functional and structural 
images, and normalization to the standard Montreal Neurological Institute (MNI) brain. This 
processing will include image quality assessment (QA) procedures that examine global and ROI 
based raw and processed temporal signal-to-noise ratio, absolute and relative motion, and 
visual inspection. Response amplitude (percent signal change) within each ROI will be extracted 
using SPM or nipype tools; primary tests of our aims will be performed in R, α=.05, two tailed. 
Whole-brain exploratory analyses will be performed in SPM12, thresholded to correspond to 
p<.05, FDR-corrected. 
6.3​
Control of Bias and Confounding  
 
Participants who complete the required tasks during the baseline period (Period 1) will be 
randomized. All participants must be able to complete tasks in any condition to participate, and 
so all participants have an equal chance to be in any of the conditions. Conditions are coded 
with a numeric value so they can be analyzed by researchers blinded to the participants’ 
specific group assignment. 
 
6.3.1​ Baseline Data 
Baseline and demographic characteristics will be summarized by standard descriptive statistics 
(including mean and standard deviation for continuous variables such as age and standard 
percentages for categorical variables such as gender). 
 
V2025-06 

 
6.3.2​ Analysis of Primary Outcome of Interest 
 
 
Daily cigarette and craving analyses 
 
Hypothesis 1: Reported craving will be higher for those in the Tobacco retailer condition, 
relative to the Control and Nontobacco retailer conditions, during the intervention phase, but not 
the baseline phase. To test hypothesis 1, we will use a linear mixed effects model (in R). To 
examine associations between study phase and craving, we will create a binary Study Phase 
variable indicating whether an observation for a participant occurred during the baseline (0) 
versus intervention (1) phase. To examine associations between condition assignment and 
craving, we will create two dummy coded variables indicating the condition assignment for each 
participant. A Control condition variable indicates whether the condition assignment is the 
Control condition (1) or the other two conditions (i.e., Tobacco and nontobacco retailer) (0). A 
Nontobacco retailer condition variable indicates whether the condition is the Nontobacco retailer 
condition (1) or the other two conditions (i.e., Control and Tobacco retailer conditions) (0). Thus, 
the Tobacco retailer condition is indicated when both the Control condition and Nontobacco 
retailer condition variables are equal to 0. We will test the interactions between study phase and 
condition assignment. 
 
At level 1, the formal model is constructed as: 
 
Cravingit =  β0i + β1iStudyPhaseit + eit ​ 
 
where β0 is the intercept, indicating the average level of craving for the prototypical participant in 
the sample; β1i  indicates the difference in the level of craving between the baseline phase and 
intervention phase; and eit are residuals that are allowed to autocorrelate. 
 
Person-specific intercepts and associations (from the Level 1 model) are specified (at Level 2) 
as: 
 
 β0i = γ00 + γ01ControlConditioni+γ02NontobaccoRetailerConditioni + u0i 
 β1i = γ10 +γ11ControlConditioni+γ21NontobaccoRetailerConditioni + u1i          
                                                                                                   ​
                                
where the γs are sample-level parameters and the us are residual between-person differences 
that may be correlated with each other but are uncorrelated with eit. Parameters γ11 and γ21 test 
the key hypotheses that craving will be higher for those in the Tobacco retailer condition, relative 
to the Control condition, during the intervention phase but not the baseline phase (γ11) and that 
craving will be higher for those in the Tobacco retailer condition, relative to the Nontobacco 
retailer condition, during the intervention phase but not the baseline phase (γ21). 
 
 
Hypothesis 2: Reported cigarettes smoked will be higher for those in the Tobacco retailer 
condition, relative to the Control and Nontobacco retailer conditions, during the intervention 
phase, but not the baseline phase. To test hypothesis 2, we will use a linear mixed effects model 
(in R). To examine associations between study phase and cigarettes smoked, we will create a 
binary Study Phase variable indicating whether an observation for a participant occurred during 
the baseline (0) versus intervention (1) phase. To examine associations between condition 
assignment and cigarettes smoked, we will create two dummy coded variables indicating the 
condition assignment for each participant. A Control condition variable indicates whether the 
V2025-06 

 
condition assignment is the Control condition (1) or the other two conditions (i.e., Nontobacco 
retailer and Tobacco retailer conditions) (0). A Nontobacco retailer condition variable indicates 
whether the condition is the Nontobacco retailer condition (1) or the other two conditions (i.e., 
Control and Tobacco retailer conditions) (0). Thus, the Tobacco retailer condition is indicated 
when both the Control condition and Nontobacco retailer condition variables are equal to 0. We 
will test the interactions between the study phase and condition assignment. 
 
At level 1, the formal model is constructed as: 
 
Smokingit =  β0i + β1iStudyPhaseit + eit ​
 
 
where β0 is the intercept, indicating the average number of cigarettes smoked per day for the 
prototypical participant in the sample; β1i  indicates the difference in the level of craving between 
the baseline phase and intervention phase; and eit are residuals that are allowed to 
autocorrelate. 
 
Person-specific intercepts and associations (from the Level 1 model) are specified (at Level 2) 
as: 
 
 β0i = γ00 + γ01ControlConditioni+γ02NontobaccoRetailerConditioni + u0i 
 β1i = γ10 +γ11ControlConditioni+γ21NontobaccoRetailerConditioni + u1i          
                                                                                                   ​
                                
where the γs are sample-level parameters, and the us are residual between-person differences 
that may be correlated with each other but are uncorrelated with eit. Parameters γ11 and γ21 test 
the key hypotheses that the number of cigarettes smoked will be higher for those in the Tobacco 
retailer condition, relative to the Control condition, during the intervention phase but not the 
baseline phase (γ11) and that the number of cigarettes smoked will be higher for those in the 
Tobacco retailer condition, relative to the Nontobacco retailer condition, during the intervention 
phase but not the baseline phase (γ21). 
 
for fMRI-related analyses:  
Hypothesis 1: To test hypothesis 1 - that neural activity in smoking cue reactivity regions will be 
greater in response to standardized images of cigarette cues (standard smoking cues) than in 
response to standardized, approximately compositionally matched sets of images of 
non-cigarette cues (standard nonsmoking cues) - we will average neural activation across 
voxels in the aggregate craving ROI to assess differences in neural cue reactivity between 
standardized smoking cue blocks and standardized non-smoking cue blocks. Specifically, we 
will extract contrast estimates of each condition compared to rest, from the aggregate craving 
ROI. We will then use a linear mixed effects model (in R), to account for some participants 
having two sets of fMRI scans. To examine associations between neural activity in the cue 
reactivity ROI and the two task conditions (standard smoking and nonsmoking cues), we will 
create a binary TaskCondition variable indicating whether an observation occurred during the 
standard smoking cue blocks (1) vs standard non-smoking cue blocks (0). If we do not find a 
significant difference between these conditions in the ROIs defined in the pilot dataset using this 
approach, we will examine whole-brain effects using MarsBaR and will define cue reactivity 
ROIs for hypotheses 5 and 6 based on prior meta-analyses (e.g., Engelmann et al., 2012; Lin et 
al., 2020). 
 
Lme (ROI ~ TaskCondition, random = ~ 1 | Participant / Session) ) 
​
Where TaskCondition represents standard smoking cues vs standard nonsmoking cues. 
V2025-06 

 
 
Hypothesis 2: To test hypothesis 2 - that neural activity in smoking cue reactivity regions will be 
greater in response to viewing photos of the cash register area at a convenience store with 
tobacco marketing and products (tobacco retail images), than to photos of the cash register 
area at a pharmacy store without tobacco marketing and products (nontobacco retail images) - -  
we will use a parallel model to the model specified for Hypothesis 1, where for Hypothesis 2, the 
TaskCondition variable represents tobacco retail images vs nontobacco retail images. 
6.3.3​ Interim Analysis  
At two time points during data collection, we will assess whether the study is producing 
unexpectedly positive or negative effects on participant outcomes. After collection of 60 
participants (approximately 20 in each group) and 120 participants (approximately 40 in each 
group), we will test whether individuals in the Tobacco retailer condition have significantly 
changed the number of cigarettes that they smoke per day (as described in 5.7). If this group of 
participants changes their cigarette consumption by a clinically significant level, we will stop 
assigning participants to that group and assign all further participants equally to the other 
groups. 
 
7​
Safety and Adverse Events 
7.1​
Definitions 
7.1.1​ Adverse Event 
An adverse event (AE) is any symptom, sign, illness or experience that develops or worsens in 
severity during the course of the study.  Intercurrent illnesses or injuries should be regarded as 
adverse events.   
 
Incidental findings in the fMRI component of this study  are considered to be adverse events if 
the finding: 
●​
results in study withdrawal 
●​
is associated with a serious adverse event 
●​
is associated with clinical signs or symptoms 
●​
leads to additional treatment or to further diagnostic tests 
●​
is considered by the investigator to be of clinical significance 
7.1.2​ Serious Adverse Event 
 
Serious Adverse Event 
Adverse events are classified as serious or non-serious.  A serious adverse event is any AE that 
is:  
●​
fatal 
●​
life-threatening 
●​
requires or prolongs hospital stay 
●​
results in persistent or significant disability or incapacity 
●​
required intervention to prevent permanent impairment or damage 
●​
a congenital anomaly or birth defect 
●​
an important medical event 
 
 
V2025-06 

 
7.2​
Recording of Adverse Events 
 
Smoking behavior will be self-reported at each study session and multiple times daily during the 
baseline and intervention periods. This data will be used at set points as described in section 
5.7. Experimenters will record medical or other life events that may be considered adverse 
events as reported by participants (e.g., hospitalization or injury in between study sessions). 
Information on all adverse events will be recorded in the source document immediately upon 
discovery, and also in the appropriate adverse event module of the case report form (CRF).  All 
clearly related signs, symptoms, and abnormal incidental findings results will be recorded in the 
source document. 
 
All adverse events occurring during the study period will be recorded.  The clinical course of 
each event will be followed until resolution, stabilization, or until it has been determined that the 
study intervention or participation is not the cause.  Serious and related adverse events that are 
still ongoing at the end of the study period will be followed up to determine the final outcome.  
Any serious adverse event that occurs during an in-person session and is considered to be 
possibly related to the study intervention or study participation will be recorded and reported. 
 
7.3​
Relationship of AE to Study  
•  ​
Definitely Related – There is clear evidence to suggest a causal relationship, and other 
possible contributing factors can be ruled out. The clinical event, including an abnormal 
laboratory test result, occurs in a plausible time relationship to study procedures administration 
and cannot be explained by concurrent disease or other drugs or chemicals. The response to 
withdrawal of the study procedures should be clinically plausible. The event must be 
pharmacologically or phenomenologically definitive. 
•  ​
Probably Related – There is evidence to suggest a causal relationship, and the 
influence of other factors is unlikely. The clinical event, including an abnormal laboratory test 
result, occurs within a reasonable time after administration of the study procedures, is unlikely to 
be attributed to concurrent disease or other drugs or chemicals, and follows a clinically 
reasonable response on withdrawal. 
•  ​
Potentially Related – There is some evidence to suggest a causal relationship (e.g., the 
event occurred within a reasonable time after administration of study procedures). However, 
other factors may have contributed to the event (e.g., the participant’s clinical condition, other 
concomitant events). Although an AE may rate only as “possibly related” soon after discovery, it 
can be flagged as requiring more information and later be upgraded to “probably related” or 
“definitely related”, as appropriate. 
•  ​
Unlikely to be related – A clinical event, including an abnormal laboratory test result, 
whose temporal relationship to study procedures administration makes a causal relationship 
improbable (e.g., the event did not occur within a reasonable time after administration of the 
study procedures) and in which other drugs or chemicals or underlying disease provides 
plausible explanations (e.g., the participant’s clinical condition, other concomitant treatments). 
•  ​
Not Related – The AE is completely independent of study procedures administration, 
and/or evidence exists that the event is definitely related to another etiology.  
 
The PI will make this determination. 
 
7.4​
Reporting of Adverse Events and Unanticipated Problems 
 
V2025-06 

 
The Investigator will promptly notify the Penn IRB of all on-site unanticipated, Serious Adverse 
Events that are related to the research activity. Other unanticipated problems related to the 
research involving risk to subjects or others will also be reported promptly. Written reports will be 
filed using the HS-ERA and in accordance with the Penn IRB timeline of 10 working days.  All 
instances of related SAEs will be reported to the appropriate IRB and the NCI Program Officer 
within 24-hours of discovery, whereas probably or definitely related SAEs will be reported to the 
appropriate IRBs within 10 days of occurrence using the on-line system. 
 
7.4.1​ Follow-up Report 
If an AE has not resolved at the time of the initial report and new information arises that 
changes the investigator’s assessment of the event, a follow-up report including all relevant new 
or reassessed information (e.g., concomitant medication, medical history) should be submitted 
to the IRB. The investigator is responsible for ensuring that all SAEs that are probably or 
definitely related to the study are followed until either resolved or stable.  
7.4.2​ Investigator reporting: notifying the study sponsor 
 
The procedures for adverse event reporting are consistent with NIH and UPenn-specific 
guidelines and are as follows: 
1)​ Report all instances of related SAEs to the NCI Program Officer (in addition to the IRB, 
as mentioned above) within 24-hours of occurrence or discovery.2) Inform all members 
of the study team actively involved in data collection about any and all reports of adverse 
events; and 
2)​ Notify the NCI Program Officer of any suspension/termination of IRB approval and any 
actions taken by the IRBs with regard to data safety monitoring within 5 days of IRB 
notification or approval. 
 
7.4.3​ Data and Safety Monitoring Plan 
 
During the course of the study, data and safety monitoring were performed on an ongoing basis 
by the Principal Investigator, project staff and IRB at the University of Pennsylvania. The IRB 
reviewed the study, including any adverse events (AEs) and serious adverse events (SAEs). 
The Principal Investigator, Dr. Emily Falk, Ph.D., was responsible for overseeing and completing 
the monitoring process in collaboration with the Research Director, Dr. Nicole Cooper, Ph.D.  
Any deviations and potentially serious and related adverse events were reviewed by Dr. Falk 
and Dr. Cooper. The research staff members were responsible for collecting and recording all 
data, as well as maintaining subject privacy and data privacy. Any inconsistencies/deviations 
were documented. 
  
Our original target was that enrollment would be complete when 180 subjects were consented 
and completed the study with usable data (see section 6.1 for an updated explanation of 
practical constraints that arose during final data collection). Individuals were screened prior to 
admission into the study and those at risk for adverse reactions were excluded. Participants 
enrolled were monitored closely for AEs.  
   
The following monitoring activities were conducted by Dr. Falk and study staff according to 
standard operating procedures. 
  
V2025-06 

 
Protocol Monitoring: Protocol monitoring includes a survey of those activities that are associated 
with protocol adherence such as study visit deviation, and violation of inclusion/exclusion 
criteria. All accrued cases will be subjected to protocol monitoring throughout the duration of the 
study.  
  
Data Auditing: Dr. Falk will review safety and efficacy. All accrued cases will be subjected to 
auditing throughout the duration of the study. A Study Binder Review will include the following 
essential documents: IRB Protocol, Consent Form and Amendment Approvals, IRB Closure 
Letter, Human Subjects Certifications, Protocol and Amendment Signature Pages, Curriculum 
Vitae, Financial Disclosure Questionnaires, and Monitoring Log. Additional monitoring may 
include: source documentation verification; adverse event documentation; and facility 
assessment. During the course of the study, safety and data quality monitoring will be performed 
on an ongoing basis by the Research Coordinators, Research Director, and Principal 
Investigator.  The Research Coordinators will be responsible for collecting and recording all 
data. 
▪​
Assessing Adverse Events: Monitoring for adverse events will be conducted in real time 
by the study team under the supervision of Dr. Falk and Dr. Cooper. Based on previous 
experience, we do not expect there to be SAEs or persistent adverse events. However, it is 
possible that injuries will occur as a result of fMRI scanning, for example if participants do not 
fully disclose the presence of metal implants in their body. It is possible that our experimental 
manipulation will have unexpectedly large effects on participant outcomes. As described above, 
we will institute a stopping rule to protect against unexpected risk to participants. The PI and 
study team will follow all subjects who are discontinued due to a serious and related adverse 
event and will refer subjects to a physician (i.e., specialist) as clinically indicated. All AEs and 
SAEs will be documented on an Adverse Event Report Form. This information will, in turn, be 
reported immediately to all necessary regulatory committees. 
o​
Adverse Event Reporting: Any serious and related adverse event case will be reviewed 
by Dr. Falk.  After removal of identification information, all serious adverse events will be 
reported to the University of Pennsylvania Institutional Review Board, the CTSRMC, and the 
funding agency.  All adverse events will be recorded. 
  
Incidental Findings: The fMRI scans conducted in this study are not indicated to be clinically 
diagnostic. However, if any incidental findings are noted by the study team or scanning 
technician, the subject will be advised to consult a neurologist. 
  
Data Security: Using network firewall technologies, the database is designed to prevent the 
three major sources of data security problems: unauthorized internal access to data, external 
access to data, and malicious intent to destroy data and systems. Controlled user access will 
help ensure that only appropriate and authorized personnel are able to view, access, and modify 
study data. 
  
Staff Training: Staff training will consist of an explanation and review of the protocol, and a 
training period, during which all sessions conducted by the staff member in training will be 
observed by a senior staff member. The duties of each staff person will be outlined and all 
applicable regulations will be reviewed. A manual of Standard Operating Procedures will be 
used for staff training. Senior personnel will supervise junior staff and provide re-training in the 
study protocol as needed. 
V2025-06 

 
▪​
Evidence of Training in Human Subject Research: All research personnel associated 
with this study have completed (or successfully transferred credit for) the University of 
Pennsylvania’s Collaborative Institutional Training Initiative (CITI program), or their respective 
university equivalent, or the NIH patient oriented research training program, as well as HIPAA 
Compliance Training. 
  
 
8​
Study Administration, Data Handling and Record Keeping 
8.1​
Confidentiality 
Information about study subjects will be kept confidential and managed according to the 
requirements of the Health Insurance Portability and Accountability Act of 1996 (HIPAA).  Those 
regulations require a signed subject authorization informing the subject of the following:  
●​
What protected health information (PHI) will be collected from subjects in this study 
●​
Who will have access to that information and why 
●​
Who will use or disclose that information 
●​
The rights of a research subject to revoke their authorization for use of their PHI.  
 
In the event that a subject revokes authorization to collect or use PHI, the investigator, by 
regulation, retains the ability to use all information collected prior to the revocation of subject 
authorization.  For subjects that have revoked authorization to collect or use PHI, attempts 
should be made to obtain permission to collect at least vital status (i.e. that the subject is alive) 
at the end of their scheduled study period. 
 
Information about study subjects will be kept confidential and managed according to the 
requirements of the Health Insurance Portability and Accountability Act of 1996 (HIPAA).  Those 
regulations require a signed subject authorization informing the subject of the following:  
●​
What protected health information (PHI) will be collected from subjects in this study 
●​
Who will have access to that information and why 
●​
Who will use or disclose that information 
●​
The rights of a research subject to revoke their authorization for use of their PHI.  
 
In the event that a subject revokes authorization to collect or use PHI, the investigator, by 
regulation, retains the ability to use all information collected prior to the revocation of subject 
authorization. 
 
Wherever feasible, identifiers will be removed from study-related information. Computer-based 
files will only be made available to personnel involved in the study through the  use of access 
privileges and passwords. Precautions are in place to ensure the data is secure by using 
passwords and encryption. Participants and screened respondents names and contact 
information will be stored in order to permit the researchers to: (1) contact the subjects during 
the study; (2) re-contact the subjects after the study to clarify any information provided; and (3) 
re-contact the subjects to invite them to participate in future studies if they choose to be 
recontacted. Participants will be informed that this research is covered by a Certiﬁcate of 
Conﬁdentiality from the National Institutes of Health. This means that the researchers cannot 
release or use information, documents, or samples that may identify the participant in any action 
or suit unless the participant approves. Authorities also cannot provide any information, 
documents, or samples from this study as evidence unless the participant has agreed. This 
V2025-06 

 
protection includes federal, state, or local civil, criminal, administrative, legislative, or other 
proceedings. An example would be a court subpoena.  Participants will also be informed that no 
data will become part of a participant's permanent record outside of the Communication 
Neuroscience Lab, such as employment records or academic records. There are no 
repercussions of participation/non participation for Penn-afﬁliated staff or students. Participants 
will be given the opportunity to opt out of having their location history from before the study 
period used for research purposes, other than for the purpose of establishing study eligibility 
(see opt-out section of the screening B consent form). 
 
8.2​
Data Collection and Management  
The team uses a variety of tools to protect participant data.  We review these by platform and 
study component, below: 
●​
GENERAL:  All information collected through this study will be treated as strictly 
conﬁdential. Identifying information will be removed from the data as much as possible and will 
be accessible only to study staff. Data that is de-identiﬁed will be coded using this study’s dual 
ID system: Survey A automatically assigns a RedCap record ID number to each screen 
respondent who expresses interest in participating. This number is different from the study ID 
number, which is only assigned to enrolled participants (those who have signed the full 
electronic informed consent on RedCap that begins Session 1).   
●​
GREENPHIRE: In order to pay participants through the Greenphire ClinCard system, we 
will be required to enter their information (required: name, date of birth, address, and Social 
Security Number; optional: email address and/or cell phone number for notiﬁcations). For more 
information on this system, please see 
https://www.ﬁnance.upenn.edu/wp-content/uploads/Greenphire-Clincard-Human-Subject-Paym
ents.pdf.  
●​
REDCAP: RedCap is an online database system and survey platform: 
https://ascRedCap.asc.upenn.edu/. Access to the RedCap database will only be provided to 
authorized study staff included in this IRB application. Screen A will collect identiﬁable 
information (names, phone numbers, and e-mail addresses) through a RedCap (or 
BuildClinical) survey. Information collected via BuildClinical will be transferred securely to 
RedCap. Eligible participants will be automatically identiﬁed through a built-in reporting feature 
on the RedCap database (i.e., there will be no need to download identiﬁable data from RedCap 
on a regular basis). RedCap will serve as the location for linking categories of subject identiﬁers 
and subject names. Electronic consents for Screen B, the main study (at the beginning of 
Online Session 1), and the optional fMRI Session (after completion of Online Session 3) will 
also be recorded and stored using RedCap. For participants who complete the optional fMRI 
session, results of the urine drug screen and drug use questions will be recorded in RedCap. 
●​
BUILDCLINICAL: BuildClinical is a data-driven software platform that helps academic 
researchers recruit participants for research studies more efﬁciently using social media, 
software, and machine learning. BuildClinical has worked with IRBs in the USA to ensure they 
adhere to all the appropriate guidelines and procedures. They utilize study-speciﬁc 
advertisements to engage participants on digital platforms such as Facebook, Google, WebMD, 
etc., and redirect them to a study-speciﬁc landing page should they click it. On the landing page, 
the person can complete an online pre-screen questionnaire that gets routed into BuildClinical's 
platform. BuildClinical's Secure Socket Layer (SSL) software, which encrypts all inputted 
information, keeps information private and HIPAA compliant. BuildClinicals backend servers are 
stored in the USA at some of the most secure data centers in the world. 
●​
PARTICIPANT CONTACT. Participants will be provided with the phone number of the 
study Google Voice account and the study GMail address, both of which exist within the lab’s 
V2025-06 

 
GSuite of Falklab.org. These accounts will be used for participant recruitment calls, scheduling, 
and other contact as needed. Account passwords are shared only with members of the study 
team.   
●​
QUALTRICS: Only authorized study staff will be granted access to Qualtrics surveys. 
Survey data that are collected through Qualtrics will be coded with a study identiﬁer. Qualtrics 
will contain a link between email addresses and study identiﬁers for creation of survey 
distribution links. Qualtrics surveys will not contain identiﬁable data, other than indirect 
identiﬁers that could be gleaned upon extensive analysis of the ﬁles [photographs and 
geolocation data] that participants may submit.  
●​
LIFEDATA: LifeData is a third-party tool for collecting ecological momentary 
assessments (EMA) through their proprietary RealLife Exp smartphone application, 
(https://www.lifedatacorp.com/mobile-app/). developed by LifeData to request and store (1) 
responses to EMA and (2) pictures of store purchase receipts. The app does not require any 
identiﬁable information; all data collected and stored by LifeData will be coded with the study ID 
and a unique, LifeData-generated user number.  
●​
GOOGLE MAPS: Geolocation data will be collected through the Google Maps app and 
Google Timeline, which is Google’s location tracking service. These apps might already be 
active on some participants’ phones as they come pre-installed on Android phones. If approved 
by the user, Google Maps automatically tracks geolocation. Google will be able to access and 
use the mobility data collected through these apps per their data agreement with the user. The 
data can be downloaded by the user in the form of a .json or .kml ﬁle which includes all location 
data collected by Google. Participants will have the option to upload their location data via 
Qualtrics survey or PennBox. This downloaded ﬁle will be what the participants submit as part 
of Screen B and Sessions 2 and 3. If the participant opts out of providing their location history 
from before the study period, other than for the purpose of establishing study eligibility (see 
opt-out section of the main study consent form), all data which was collected by Google outside 
of the timespan between Session 1 and Session 3 will not be included in data analysis, other 
than for the purpose of establishing study eligibility.   
●​
fMRI DATA: Neuroimaging data are collected at scanners located on Penn's campus. 
Imaging data is standardly stored and archived on (1) a secured, password protected computer 
located at the scanner site, which is only accessible with specific access rights, and (2) on 
Flywheel, a cloud-based research platform, only accessible with specific access rights. Data for 
this study will additionally be stored on the ASC server (details below).  
●​
ASC SERVER: The study team will store the submitted location data ﬁles and 
neuroimaging data, tagged with the participant's study ID, on a secure server that is maintained 
by the Annenberg School for Communication (ASC) and is accessible only to the study team 
(including approved collaborators at New York University, as detailed in the Data Disclosure 
section). As this server is our most secure platform for data storage, it may also serve as a 
back-up location for data that is collected by and/or stored on any of the platforms mentioned in 
this section.  
●​
PENNBOX: PennBox (aka Penn+Box; http://box.upenn.edu/) is a cloud-based 
collaboration service for securely managing and sharing ﬁles and folders within the Penn 
community and externally. Files containing coded data, such as EMA data and survey 
responses, will be stored on PennBox in folders that are only shared with the individuals 
mentioned in the Study Personnel and Data Disclosure sections of this protocol. Any ﬁles on 
PennBox that contain identiﬁable data will be stored in a separate folder and will be 
password-protected for an additional level of security.   
●​
STUDY LOGISTICS: We will keep track of participants' study progress through a 
spreadsheet logging study appointments and the completion of the various measures. This 
spreadsheet will be coded by study identiﬁers and study staff is trained to not include any 
personally identiﬁable information (e.g., names, emails, phone numbers) in this spreadsheet. 
V2025-06 

 
The spreadsheet will be stored using Google Drive, Qualtrics, RedCap, and/or Box in a manner 
such that it is only accessible to authorized study staff. The study’s Google account will also be 
associated with a study calendar which will include information about study appointments. All 
appointments will be coded by study ID and will not include personally identiﬁable information. 
Only Communication Neuroscience Lab members and collaborators will have access to this 
calendar. We may use a booking system such as https://simplybook.me or calendly to allow 
participants to sign up for a time for their intake call. Participants will have the option to include 
their contact information in the reservation, but we will explicitly recommend that they not do so, 
as sharing contact information to a third-party platform can incur minimal additional risks to 
conﬁdentiality, and if they choose to include their contact information, they accept that risk. In 
addition, some of the systems and services we use (such as BuildClinical and e-Ship) may send 
non-optional notiﬁcation emails to staff Penn or GSuite email accounts that include participant 
contact information (such as name and address). Those notiﬁcation emails will be deleted from 
all staff accounts immediately, but will be saved for documentation purposes on the study email 
account, which already contains participant information (for contact purposes). 
 
9​
Study Monitoring, Auditing, and Inspecting 
9.1​
Study Monitoring Plan 
 
The study PI will be responsible for the ongoing quality and integrity of the research study, in 
collaboration with the Research Director. 
9.2​
Auditing and Inspecting 
The investigator will permit study-related monitoring, audits, and inspections by the EC/IRB, the 
sponsor, government regulatory bodies, and University compliance and quality assurance 
groups of all study related documents (e.g. source documents, regulatory documents, data 
collection instruments, study data etc.).  The investigator will ensure the capability for 
inspections of applicable study-related facilities (e.g. pharmacy, diagnostic laboratory, etc.). 
 
10​
Ethical Considerations 
10.1​
Risks 
 
●​
There may be a risk of unintentional breach of conﬁdentiality, but we will take all 
necessary steps to prevent this from happening. Internet data transfers between mobile device 
users and the study web-server will be based on a session ID unique to the user and the date 
and time of access. All information collected via the Internet will be kept secure in transit using 
the Secure Socket Layer (SSL) protocol, the same technology used to encrypt credit card 
numbers during transmission over the Internet. All data will be stored in a database subject to 
both physical and electronic protection.  
●​
Past literature suggests that there may be negative consequences of increased 
exposure to POST-marketing, such as increased difﬁculty in quitting and increased craving 
during a quit attempt. However, our manipulation does not involve a quit attempt, and does not 
go beyond a level of POST-marketing exposure that participants may be expected to have in 
their normal daily lives. At most, participants are asked to enter a POST-marketing store, such 
as a common convenience store, once per day. Thus, the study design poses risk to 
participants on par with everyday life.   
●​
For the duration of the COVID-19 pandemic, entry into retail stores as part of this study 
V2025-06 

 
may increase participants' risk of being exposed to and spreading SARS-COV-2, the virus that 
causes COVID-19 disease. To reduce transmission risks, the study team will send participants 
KN95/KF94 or N95 respirators (masks) in their box of study materials, which they will be 
strongly encouraged to wear during study-related store visits (in accordance with local 
guidelines) and in their daily life. Participants are also required to be vaccinated against 
COVID-19. 
●​
For optional fMRI session component: Safety concerns in MR environment: The 
magnetic field of the MRI environment has the potential to cause burns or bodily injury if ferrous 
metal objects are implanted in the body or if personal articles containing ferrous material are 
brought into the MR environment. Because we are excluding subjects with contraindications for 
MR studies (e.g., metallic implants such as pacemakers, surgical aneurysm clips, or known 
metal fragments embedded in the body) using a standard screening form, the risk of damage 
due to implanted metal is low. Investigators and personnel of the MRI unit have extensive 
experience with standard safety precautions, including safety screening on paper and verbally 
by a trained technologist. These considerations minimize the risk of accident or injury in the MR 
environment. Psychological discomfort secondary to MRI acquisition may occur in some 
subjects due to claustrophobia. Claustrophobia is also part of the exclusion criteria, and 
participants are informed that they may stop the study at any time without consequences to 
them. Risk of discomfort due to fMRI scanner noise will be minimized by providing earplugs for 
participants. The level of noise is not great enough to pose a health risk, with or without 
earphones. There is a risk that the magnetic resonance image will reveal a minor or significant 
lesion in the brain, e.g. a tumor, previously unknown to the subject. Structural MRI scans will not 
be read by a radiologist, and subjects will be informed of this. No diagnostic or clinical 
information will be provided, and participants will be informed of this before consenting to 
participate. We exclude subjects with contraindications for MR studies (e.g., metallic implants 
such as pacemakers, surgical aneurysm clips, or known metal fragments embedded in the 
body) using a standard screening form. Investigators and personnel of the MRI unit have 
extensive experience with standard safety precautions, including safety screening on paper and 
verbally by a trained technologist. These considerations minimize the risk of accident or injury in 
the MR environment. Claustrophobia is also part of the exclusion criteria, and participants are 
informed that they may stop the study at any time without consequences to them. The risk of 
discomfort due to fMRI scanner noise will be minimized by providing earplugs for participants. 
Thus, the risk of discomfort will be minimized. Participants will be provided with a 
hand-squeezable pneumatic signaling device for communicating with investigators during 
scanning should they experience intolerable discomfort of any kind. 
10.2​
Benefits 
 
There are no direct beneﬁts to subjects as a result of participation in this study other than 
monetary and gift card compensation. Participants may beneﬁt from heightened awareness of 
the way point-of-sale marketing affects their smoking behavior and decision-making about the 
use of tobacco products. 
10.3​
Risk Benefit Assessment 
 
Given the minimal risk of the study and the great potential beneﬁt for understanding the 
relationship between the brain and behavior, the potential beneﬁts to society outweigh the risks.  
10.4​
Informed Consent Process / HIPAA Authorization  
 
V2025-06 

 
●​
SCREEN B CONSENT: Screen B will begin with a consent that explains the purpose 
and nature of this screening. (See ScreeningSurveyBConsent.docx) To continue into the 
screening survey, participants will have to indicate that they have read and understood this 
consent. This includes an optional section that gives participants the opportunity to opt out of 
having their location history from before the study period used for data analysis, meaning the 
study team would only use the data uploaded in this survey for the purpose of establishing 
study eligibility (not for any further analysis or publication). This section explicitly states that 
declining to consent to analysis of their full history does not preclude participation in the rest of 
the study.  The Screen B consent also explains that individuals who are found to live outside of 
the speciﬁed study area or are not fully vaccinated will be informed that they are ineligible for 
this study, and that the study team will delete their geolocation data and provide them with 
optional instructions for turning off Google Timeline and uninstalling Google Maps.  
●​
FULL STUDY CONSENT: If eligible following screens A and B, participants will be 
invited to consent electronically to the full study. Participants will read, and be sent a PDF 
version of, the informed consent form to be signed electronically (or not). Please see the 
attached ﬁle for the content of the consent form for the full study. Experimenters will talk through 
this consent form with participants during the intake call and will answer any questions. Consent 
will be deemed provided if after reading the consent document, the prospective participant 
electronically signs it using RedCaps HIPAA compliant system for e-signature. 
●​
OPTIONAL fMRI SESSION CONSENT: After confirming that the participant meets any 
COVID-19 screening requirements (e.g., symptom screen, temperature check), at the in-person 
session, researchers will review the consent document with participants. Participants will 
provide informed consent via RedCap. 
 
11​
Study Finances 
11.1​
Funding Source 
 
This study is financed by an R01 grant from the National Cancer Institute at the US National 
Institute of Health. 
11.2​
Conflict of Interest 
 
The investigators declare no conflicts of interest. 
 
11.3​
Subject Stipends or Payments 
Each participant can earn compensation of up to $500.00 through a Greenphire ClinCard by 
participating in this study and by fulfilling all the study requirements. Some participants may be eligible for 
an optional in-person fMRI scan session, with additional compensation of $95, paid through ClinCard.  
Please consult the compensation schedule (table) below for detailed descriptions of subject 
compensation. 
 
Conditions 1 & 2 = Tobacco and Nontobacco retailer conditions 
Condition 3 = Control 
 
KEY: 
All conditions Cond. 1 & 2 
Cond. 3  
 
Period of task 
Task 
completed 
Payment Rate 
Max 
possibl
e 
Max Total 
STORE 
Max Total 
CONTROL 
V2025-06 

 
Online Session 1 
Cumulative payment for 
Screens A & B, initial call, and Online 
Session 1 
$95 
$95 
at Online 
Session 1 
$95 
at Online 
Session 1 
Baseline 
(2 weeks) 
EMA 
response 
$28/week * 2 weeks 
for 75% compliance 
$55 
$90 
at Online 
Session 2 
$75 
at Online 
Session 2 
Online Session 2 Session 2 
$20 
Intervention 
(4 weeks) 
Store 
purchase 
funds (week 
1) 
$3/visit * 5 visits/week 
$15 
Store 
purchase 
funds (week 
2) 
$3/visit * 5 visits/week 
$15 
$15 after 
Intervention 
Week 1 
n/a 
Store 
purchase 
funds (week 
3) 
$3/visit * 5 visits/week 
$15 
$15 after 
Intervention 
Week 2 
n/a 
Store 
purchase 
funds (week 
4) 
$3/visit * 5 visits/week 
(cond. 1 or 2) 
$15 
$15 after 
Intervention 
Week 3 
n/a 
EMA 
response 
$28/week * 4 weeks 
for 75% compliance 
$110 
$270 
at Online 
Session 3 
$330 
at Online 
Session 3 
Store receipt 
photographs 
$5/receipt * 20 receipts 
(cond. 1 or 2) 
$100 
Weekly 
survey 
$2.50 each for 
completion of 
4 weekly surveys 
$10 
Online Session 3 
Session 3 
$20 
Study 
completion 
$30 for cond. 1 or 2 
$190 for cond. 3 
$30 
$190 
 
 
 
 
 
 
 
 
 
Maximum payment for completing all remote tasks $500 
$500 
$500 
OPTIONAL 
In-Person 
Session 
2-hour session  (includes 1-hour fMRI 
scan) 
$95 
$95 
at the optional 
In-Person 
Session 
$95 
at the optional 
In-Person 
Session 
Maximum total payment for all remote AND 
in-person tasks 
$595 
$595 
$595 
 
V2025-06 

 
 
12​
Publication Plan 
 
This study will be conducted in accordance with the following publication and data sharing 
policies and regulations: 
 
National Institutes of Health (NIH) Public Access Policy, which ensures that the public has 
access to the published results of NIH funded research. It requires scientists to submit final 
peer-reviewed journal manuscripts that arise from NIH funds to the digital archive PubMed 
Central upon acceptance for publication. 
 
This study will comply with the NIH Data Sharing Policy and Policy on the Dissemination of 
NIH-Funded Clinical Trial Information and the Clinical Trials Registration and Results 
Information Submission rule. As such, this trial has been registered at ClinicalTrials.gov, and 
results information from this trial will be submitted to ClinicalTrials.gov. In addition, every attempt 
will be made to publish results in peer-reviewed journals.  
 
Final research data, with all identity-related information deleted and in consultation with the 
relevant IRBs, will be made available to the scientific community for collaborative research with 
members of the study team, upon request, in spreadsheet format for all non-imaging data and in 
NIFTI format for fMRI data.  These data will be shared upon request in consultation with 
relevant IRBs for further analysis once the study’s primary results have been published. 
Qualified investigators who wish to access the study materials will be able to complete a form on 
the main project website, which describes the proposed study and delineates the data specifics 
of data use.  The requests will be reviewed and approved by the investigators and by the 
relevant IRBs. Data that may be difficult to de-identify (including geolocation data) will be shared 
at an aggregate level, with restrictions as developed in consultation with the IRB, to protect 
participant privacy. The requested research data files will be accompanied by a description of 
variables and how they were collected.  We will also share protocols relevant to data collection 
procedures, as useful and in consultation with other interested researchers. 
Imaging data files will be made available to researchers following the procedures outlined above 
through a secure file-sharing interface once the main findings have been published, in 
consultation with the relevant IRBs; alternative requests regarding format of imaging data will 
also be considered and honored to the extent possible within practical constraints. 
Study tasks and code to reproduce analyses will be made available on the Falk Lab GitHub 
account (https://github.com/cnlab/). 
13​
References 
 
Summary 
1. Center for  Public Health Systems Science. Point-of-sale report to the nation. State and 
Community Tobacco  Control Research 
2. Kirchner, T. R. et al. Geospatial Exposure to Point-of-Sale Tobacco. AMEPRE 45,  379385 
(2013).  
3. Wakefield, M., Germain, D. & Henriksen, L. The effect of retail cigarette pack  displays on 
impulse purchase. Addiction 103, 322328 (2008).  
4. Jasinska, A. J., Stein, E. A., Kaiser, J.,  Naumer, M. J. & Yalachkov, Y. Factors modulating 
neural reactivity to drug cues in addiction: A survey  of human neuroimaging studies. 
V2025-06 

 
Neuroscience & Biobehavioral Reviews 38, 116 (2014).  
5. Engelmann,  J. M. et al. Neural substrates of smoking cue reactivity: A meta-analysis of fMRI 
studies. NeuroImage  60, 252262 (2012).  
6. Janes, A. C. et al. Brain Reactivity to Smoking Cues Prior to Smoking Cessation  Predicts 
Ability to Maintain Tobacco Abstinence. BPS 67, 722729 (2010).  
7. McClernon, F. J., Kozink,  R. V., Lutz, A. M. & Rose, J. E. 24-h smoking abstinence 
potentiates fMRI-BOLD activation to  smoking cues in cerebral cortex and dorsal striatum. 
Psychopharmacology 204, 2535 (2008).  
8. Bedi,  G. et al. Incubation of Cue-Induced Cigarette Craving During Abstinence in Human 
Smokers. BPS 69,  708711 (2011).  
 
Study background 
1.​
US Department of Health and Human Services. The Health Consequences of Smoking - 
50 Years of Progress: A Report of the Surgeon General. (2014). Available at: 
http://www.surgeongeneral.gov/library/reports/50-years-of-progress/50-years-of-progress-by-sec
tion.html. (Accessed: 31st October 2016) 
2.​
National Center for Chronic Disease Prevention and Health Promotion (US) Office on 
Smoking and Health. The Health Consequences of Smoking—50 Years of Progress: A Report 
of the Surgeon General. (Centers for Disease Control and Prevention (US), 2014). 
3.​
Smoking, C. O. on & Health. Smoking and Tobacco Use; Fact Sheet; Tobacco-Related 
Mortality. 
4.​
Federal Trade Commission. Cigarette Report for 2011. (2013). Available at: 
<http://www.ftc.gov/sites/default/files/documents/reports/federal-trade-commissioncigarette-. 
5.​
Wakefield, M. A. et al. Tobacco industry marketing at point of purchase after the 1998 
MSA billboard advertising ban. Am. J. Public Health 92, 937–940 (2002). 
6.​
Henriksen, L. Comprehensive tobacco marketing restrictions: promotion, packaging, 
price and place. Tob. Control 21, 147–153 (2012). 
7.​
Truth Initiative. How big is Big Tobacco’s marketing budget? Truth Initiative (2016). 
Available at: https://truthinitiative.org/news/how-big-big-tobaccos-marketing-budget. (Accessed: 
6th October 2017) 
8.​
Center for Public Health Systems Science. Point-of-Sale Report to the Nation: The 
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9.​
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