Study 2: Impact of Nicotine Messaging on Nicotine Beliefs and Tobacco Use Behavior
Phase: NA
Conditions: Smoking Behaviors, Cigarette Smoking
Sponsor: Andrew Strasser

NCT05108649 
Impact of Nicotine Messaging on Beliefs and Behavior 
Document date: August 13, 2025 
 
Contents 
Study Protocol............................................................................................................................ 2 
Study Measures ......................................................................................................................... 4 
Statistical Analysis Plan ............................................................................................................. 5 
References ................................................................................................................................ 8 
 
 
 
 
 

NCT05108649 
 
2 
Study Protocol 
The current study tested the impact of multiple exposures to a brief nicotine corrective 
messaging intervention and nicotine content of study cigarettes on nicotine beliefs and 
subsequent use of tobacco and nicotine products in a 28-day lab-based study of 74 adults who 
smoke cigarettes daily. Data were collected at the University of Pennsylvania Center for 
Interdisciplinary Research on Nicotine Addiction. A parallel population-based study of exposure 
to nicotine corrective messaging was conducted in adult smokers and non-smokers followed for 
12 weeks (NCT04805515).  
The lab-based study was a prospective, randomized factorial trial of nicotine corrective 
messaging (NCM vs. control) and nicotine content of cigarettes (normal vs. reduced) in current 
daily adult cigarette smokers (minimum 5 daily cigarettes for the past year, carbon monoxide 
(CO) at least 5 parts per million at Week 0, and no current use of other tobacco or nicotine 
containing products) for a 35-day protocol. Recruitment occurred through community and 
campus bulletin boards, local newspapers, radio and television ads, and previous participants 
who agreed to be re-contacted for non-cessation or non-treatment studies. At the baseline visit 
(Week 0), eligible, consenting participants provided a CO sample, complete demographic and 
smoking history measures, and measures of nicotine beliefs and intentions/use of nicotine and 
tobacco products (see Study Measures). They also provided breath and urine samples for 
biomarker assessment and continued to smoke their usual brand cigarettes to assess their 
baseline cigarette smoking behavior. Participants were instructed to continue smoking their own 
brand cigarettes and collect used filters as a verified count of daily smoking using re-sealable 
bags provided, while also recording their smoking in a calendar. Participants returned on Day 7 
(Week 1; end of baseline), returned used cigarette filters, and were randomized to one of four 
groups: 1) Nicotine Corrective Messaging (NCM) + RNC cigarettes, 2) NCM + normal nicotine 
content (NNC) cigarettes, 3) Control + RNC cigarettes, or 4) Control + NNC cigarettes. 
Participants receiving normal nicotine content or reduced nicotine content cigarettes were 
explicitly told which product they have been given (i.e., unblinded).  
The Nicotine Corrective Messaging (NCM) intervention condition was based on messages 
tested in our team’s pilot study.1 It included six original messages and two new messages 
addressing nicotine in cigarette and e-cigarette products that were adapted from several 
evidence-based sources to be more accessible to a lay audience. The sources consisted of 
FDA’s 2017 comprehensive plan for tobacco and nicotine regulation,2 FDA’s 2013 modifications 
to labeling of NRT products for over-the-counter human use,3 the 2014 U.S. Surgeon General’s 
Report on the Health Consequences of Smoking,4 reports on carcinogens from the International 
Agency for Research on Cancer,5-7 and the NASEM report on the “Public Health Consequences 
of E-cigarettes.8  Participants in the NCM condition were exposed to all eight messages in the 
same order at each exposure. 
Participants in the NCM condition received their first exposure to the study messages on Day 7 
in the lab. Eye tracking was assessed during a five-second exposure to each educational message, 
equating to a minimum 40-second exposure. At the end of the session, all participants left with study-
provided cigarettes to last until the next visit. Participants continued to collect used filters and record 
daily number of study cigarettes, non-study cigarettes, and other nicotine or tobacco products used 
each day for the duration of the study. At lab visits on Days 14 (Week 2), 21 (Week 3), and 28 (Week 
4), daily nicotine/tobacco use calendars and used filters were collected at the start of the visit. At the 
Week 2 visit, all participants completed the first post-exposure measures of nicotine beliefs and 
intentions/use of nicotine and tobacco products. In visits at Weeks 2-4, participants smoked their study 
product with CO collected at the start and each smoking session videotaped to extract smoking 

NCT05108649 
 
3 
behavior. Participants in the NCM conditions were then be exposed to the nicotine corrective 
messages in the lab and eye-tracking data collected. At the end of the session, all participants left with 
study-provided cigarettes to last until the next visit, collect used cigarette filters, and asked to track 
their nicotine and tobacco use via their calendars. The Week 5 visit (Day 35) began with the collection 
of daily nicotine/tobacco use calendars and used filters and include the final assessment of nicotine 
beliefs and intentions/use of nicotine and tobacco products in all participants. Participants also 
provided breath and urine samples for biomarker assessment. Upon completion of assessments, 
participants in the control conditions (control + NNC cigarettes, control + RNC cigarettes) were 
exposed to the nicotine corrective messages and all participants were directed to resources on quitting 
smoking. 
 
 

NCT05108649 
 
4 
Study Measures 
 
  
  
Aim 1:   
Population 
study 
Aim 2:  
Lab study 
Intervention/Exposure 
  
  
  
Nicotine messaging vs. control 
Wave 1 
Week 1 
  
Normal nicotine vs. RNC cigarette 
  
Week 1 
  
Heatmapping 
Waves 1-4 
  
 
Perceived message effectiveness 
Wave 4 
Week 5 
 
Message credibility 
Wave 4 
Week 5 
  
Eye-tracking 
  
Weeks 1-4 
  
Biomarkers 
  
Weeks 0, 5 
Outcomes 
  
  
  
Nicotine beliefs 
Waves 1, 2, 4 
Weeks 0, 2, 5 
  
Intention to use nicotine/tobacco 
products 
Waves 1, 2, 4 
Weeks 0, 2, 5 
  
Nicotine/tobacco use and behavior 
Waves 1, 2, 4 
Weeks 0, 2, 5 
  
Subjective rating of study cigarette 
  
Weeks 1-5 
 
Manipulation check 
Waves 1, 2, 4 
Weeks 0, 2, 5 
Moderators 
  
  
  
Sociodemographics 
Wave 1 
Week 0 
  
Literacy 
Wave 1 
Week 0 
  
Cancer risk beliefs 
Wave 1 
Week 0 
  
Cancer risk behaviors 
Wave 1 
Week 0 
 
Fagerstrom test for nicotine dependence 
Wave 1 
Week 0 
Other key constructs 
  
  
  
Attitudes about nicotine 
Waves 1, 2, 4 
Weeks 0, 2, 5 
  
Nicotine-related norms 
Waves 1, 2, 4 
Weeks 0, 2, 5 
  
Behavioral control 
Waves 1, 2, 4 
Weeks 0, 2, 5 
 
Stages of change 
Wave 1, 4 
Week 0, 5  
 
Policy support 
Wave 4 
Week 5 
 
 
 

NCT05108649 
 
5 
Statistical Analysis Plan 
Sample Size. Power for Aim 2 was calculated for 160 adult current daily cigarette smokers 
using an ANCOVA framework to detect differences between any two study conditions; with n=40 
in each of the four conditions in the trial, we will have 80% power to detect medium effect sizes 
(Cohen’s f = 0.33) in continuous outcomes (i.e., nicotine beliefs, behavior, subjective ratings), 
assuming three covariates in the model (i.e., age, gender, cigarettes per day at baseline). In 
addition, using a two-way analysis of variance framework, 40 participants in each study condition 
provides 85% power to detect a statistically significant moderation of these same outcomes by 
the nicotine content of the study cigarettes, assuming that the responses by those in the NCM + 
NNC condition differ from those in the other three conditions by 1 standard deviation. Sample size for 
the eye tracking analyses is based on our earlier work that recruited 200 participants to a 2 x 2 factorial 
design and used the same outcomes (i.e., dwell time, time to first area of interest).9 
Data Preparation. We will conduct data screening steps similar to Aim 1 including assessing 
outliers, missing data presence/patterns, and normality/equality of variance assumptions. Non-
normal data will be transformed as needed. In all analyses, the assumptions underlying the 
application of all the statistical methods that are used will be examined, principally using 
standardized residuals, influence diagnostics, and graphical displays. Where needed, appropriate 
transformations will be applied to ensure that data meet model assumptions. Descriptive analyses 
will characterize participants overall and by study condition. Aim 2 eye tracking data will be 
cleaned and pre-processed using standard procedures from our previous work. Descriptive 
analyses will characterize participants overall and by study conditions. Bivariate tests will assess 
for differences in participant characteristics by conditions and examine if any baseline variables 
that are imbalanced between study groups are associated with primary and secondary outcomes 
(p <.10). Any such variables will be accounted for in analyses as covariates. 
Analytic Approach.  
Aim 2: Test the impact of NCM (messaging vs. control) and nicotine content of 
cigarettes (normal vs. reduced) on nicotine beliefs and subsequent use of tobacco and 
nicotine products using a 2 x 2 factorial design in a sample of 160 adult current smokers 
followed for 4 weeks.  
Hypothesis 2a: Adult smokers in the NCM + normal nicotine content (NNC) cigarette condition 
will report the fewest false beliefs about nicotine compared to those in the NCM + RNC and 
control conditions (Control + RNC cigarettes, Control + NNC cigarettes); those in the Control + 
NNC cigarette condition will report the highest study cigarette use. 
Hypothesis 2b: Lower subjective ratings of study cigarettes (e.g., strength) will predict greater 
false beliefs about RNC cigarettes. 
Analyses for Aims 1 and 2 employ common measures and a common analytic framework to 
test the impact of nicotine education on nicotine beliefs and behavior. Primary analyses will use 
an intention-to-treat approach, employing a general linear mixed model to accommodate missing 
data.10,11 Outcomes for Aim 2 focus on continuous outcomes (primary outcome: nicotine beliefs; 
secondary outcomes: frequency and intensity of nicotine/tobacco use), with the primary 
hypotheses (Hypotheses 2a) focused on the effect of the two interventions (nicotine education 
and nicotine content of study cigarettes) on these outcomes. Preliminary analyses will examine 
differences in these outcomes across study conditions at the first post-exposure time point (Week 
2) and at the final timepoint (Week 5) using ANCOVA controlling for covariates that are 
differentially distributed between study groups. These outcomes as well as measures of tobacco 
use (study cigarette use, topography patterns, CO) will then be analyzed using the general linear 
model approach to repeated measures analysis. Of primary interest in Aim 2, we will evaluate 

NCT05108649 
 
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whether using study cigarettes with a known nicotine content (i.e, normal or reduced) moderates 
the effect of NCM on our primary and secondary outcomes by incorporating an interaction 
between NCM condition (NCM/control) and study cigarette condition (NNC/RNC) through the 
following steps: 1) bivariate analyses, to determine if outcomes vary by these variables; 2) testing 
whether study cigarette condition moderates (p <.05) experimental effects in the models above; 
if so, performing post-hoc statistical testing to examine the direction and magnitude of the 
moderation; 3) if no evidence of moderation exists, including study cigarette condition as a 
covariate. 
Our previous work highlights that assessing perceptions of RNC cigarettes that find an 
association between participants perceiving that their assigned product is low nicotine and 
reporting lower harm perceptions of the product.12,13 To address Hypothesis 2b, we will also use 
autoregressive, cross-lagged panel analysis14 to examine the direction of the relationships 
between subjective ratings and nicotine beliefs over three timepoints (Weeks 0, 2, and 5) and 
whether the regression paths vary in magnitude by study condition. 
As in Aim 1, our exploratory analyses will focus on three areas: 1) potential moderators of the 
relationship between intervention condition and the study outcomes; 2) nicotine beliefs as a 
potential mediator of the relationship between intervention condition and constructs identified in 
the Theory of Planned Behavior (i.e., nicotine-related attitudes, norms, behavioral control, and 
nicotine/tobacco intentions and use); and 3) the relationship between visual attention to nicotine 
education messages and nicotine beliefs in the participants exposed to the NCM intervention.  
For the first area (moderation), we will conduct exploratory analyses using the same steps 
described for Hypothesis 2a to determine whether there are potential moderators of the 
relationship between the study condition (NCM + RNC, NCM + NNC, Control + RNC, Control + 
NNC) and outcomes, specifically age, gender, baseline cancer beliefs and cancer risk behaviors.   
For the second area (mediation), we will draw from traditional mediation frameworks and use 
robust methods to explore the relationships outlined in our theoretical framework and whether 
changes in nicotine beliefs post-exposure (Weeks 2, 3, 4) influence nicotine-related attitudes, 
norms, behavioral control, intention, and behavior at the final assessment (Week 5). To 
complement Aim 1 analyses, we will examine whether nicotine beliefs at Week 2 are associated 
with these Week 5 outcomes using bivariate statistics and the general linear model-based 
analysis accounting for any covariates as described above. Where these preliminary steps 
indicate potential correlation between nicotine beliefs and study outcomes (p <.05), we will test 
for mediation by estimating the indirect effects of nicotine beliefs on follow-up outcomes via the 
study condition using a bias-corrected bootstrapping method with 1,000 resamples. This 
approach estimates indirect (i.e., mediation) effects and produces bias-corrected asymmetric 
95% CIs correcting for non-normality of the distribution of indirect effects and providing higher 
power and better control over the Type I error rate versus traditional approaches to test mediation. 
Asymmetric 95% confidence intervals around indirect effect estimates for nicotine beliefs that do 
not include zero will be interpreted to indicate significant mediation.  
For the third area (visual attention), we will identify the regions of interest (ROIs) in each 
nicotine education message based on responses to the Aim 1/Wave 1 heatmapping task. Using 
eye-tracking, we will explore whether attention to the ROIs (i.e., dwell time, fixations) is correlated 
with scores on the nicotine beliefs scales (i.e., nicotine, NRT, e-cigarette, RNC cigarette beliefs) 
at the same assessment (Weeks 1-4). Given the content of messages in the nicotine education 
condition, we will be able to assess whether attention to specific ROIs is correlated with specific 
beliefs (i.e., whether attention to a specific ROI within the “Nicotine does not cause cancer” is 
correlated with response to the nicotine belief item regarding nicotine causing cancer). We will 
also be able to explore the prospective relationship between visual attention to the nicotine 

NCT05108649 
 
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education messages (e.g., duration spent viewing messages, attention to ROIs) and nicotine 
beliefs and whether there are differences in visual attention in the NCM intervention condition 
over the four weeks of data collection. These data will inform potential refinements to nicotine 
education messages for future studies. 
Missing data: The most effective approach to eliminating biases and inefficiency caused by 
missing data is to collect complete data. In both aims of our study, we will use several tools 
available to maintain contact and verify that forms are complete. Use of computerized survey 
platforms (e.g., Qualtrics) in this study will provide additional mechanisms to improve 
completeness of survey responses, but even so, some participants may refuse to answer 
certain questions. We anticipate that one cause of missing data will be item non-response on 
self-report questionnaires; another will be missing assessments.  Finally, missing data can arise 
through attrition; however, the steps outlined in the proposal are meant to minimize this. The 
general/generalized linear mixed model that we will be using for analysis for Aim 2 is a 
maximum likelihood approach to repeated measures analysis of variance that does not rely on 
imputation, which may give differing results depending upon the exact imputation procedure 
used. Rather, this approach estimates the parameter values that would maximize the probability 
of observing the data collected.  In the event of missing variables, the likelihood for a given 
individual is the probability of observing the non-missing variables.  Thus, the maximum 
likelihood approach allows the use of data from subjects for the time period for which data is 
available, but not for time periods for which the data is missing.  This procedure uses 
information from earlier time periods to estimate the effects of later time periods, while also 
accounting for the uncertainty of the projection in the computation of standard errors and test 
statistics.  Maximum likelihood estimation is considered superior to imputation methods for the 
treatment of missing data in clinical trials.15 
 
 

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