A Proof-of-concept RCT of Version 3.0 of the Smoking Cessation Smartphone App "Smiling Instead of Smoking" (SiS)
Phase: NA
Conditions: Nondaily Smoking
Sponsor: Massachusetts General Hospital

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Version Date:  October 15, 2014 
 
  
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Study Protocol and 
Statistical Analysis Plan (SAP) 
 
 
A PROOF-OF-CONCEPT RCT OF VERSION 3.0 OF THE SMOKING CESSATION SMARTPHONE APP 
“SMILING INSTEAD OF SMOKING” (SIS) 
 
 
 
Principal Investigator: 
 
 
Bettina B. Hoeppner, PhD, MS 
Associate Professor of Psychology 
Massachusetts General Hospital & Harvard Medical School 
Boston, MA, United States of America 
 
 
Ethical approval:  
 
 
Mass General Brigham Institutional Review Boards  
(protocol # 2020P003466, approved on 12/08/2020) 
 
 
ClinicalTrials.gov identifier:  
 
NCT04672239 
 
 
Funding:  
This research was supported by a grant from the American Cancer 
Society (ACS Grant #RSG CPPB – 130323) to Dr. B. Hoeppner. 
 
 
Document Date:  
 
 
January 14, 2022 
 
 
 
 
 
 
 
 
 
 
 

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Filename: Protocol Summary 
Version Date:  October 15, 2014 
 
  
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I. 
BACKGROUND AND SIGNIFICANCE 
 
1. Why Nondaily Smoking Matters 
Cigarette smoking continues to be the leading cause of preventable disease and death in the 
United States, accounting for more than 480,000 deaths every year.1  While the prevalence of 
smoking has steadily declined over a number of years,2 an increasingly prevalent pattern of 
smoking is nondaily smoking.  Currently, 24.3% of all adult smokers are nondaily smokers, 
which constitutes a 27% increase in prevalence in the last decade.3   
Nondaily smoking poses substantial health risks,4,5 and is a recognized public health issue.6  
It poses significant carcinogenic exposure (i.e., 40-50% of that seen in daily smokers)7 and has 
been linked to total and cardiovascular mortality among men.8  Indeed, the risk for 
cardiovascular disease has been found to be nearly equal to that of daily smoking, given a highly 
non-linear dose-response relationship between tobacco exposure and cardiovascular mortality.9   
Untreated nondaily smoking contributes to persisting health disparities in smoking 
prevalence.  Nondaily smoking is disproportionally represented in ethnic minority groups,10-14 
and increasingly prevalent in adults with a mental health or substance use problem.15  Both of 
these groups have substantially higher smoking prevalence rates (e.g., 31.8% in American 
Indian/Alaska Natives,2  35.8% in adults with serious psychological distress,2 65% to 87% in 
individuals with substance use disorders16) compared to the general population (15.5%).2  Thus, 
a failure to provide smoking cessation support for nondaily smokers disproportionally impacts 
populations already systematically missed by current public health efforts.   
 
2. The Need for Smoking Cessation Support for Nondaily Smokers 
Nondaily smokers are motivated to quit smoking.  Indeed, epidemiological evidence 
demonstrates that compared to daily smokers, nondaily smokers have greater current intentions 
to quit smoking,11,17,18 and more recent and planned cessation efforts 18-21 than daily smokers.  
The fact that nondaily smokers regularly abstain from smoking from day-to-day suggests that 
they should have relatively little trouble quitting, but recent evidence demonstrates that most 
nondaily smokers (up to 82%) fail in their quit attempts.22  Together, the high motivation to quit 
coupled with a high failure rate demonstrate the need for smoking cessation support for nondaily 
smokers.   
 
3. Why Traditional Smoking Cessation Interventions Fail Nondaily Smokers 
Engaging nondaily smokers in treatment has been largely unsuccessful.  Despite being 
motivated to quit, nondaily smokers are less likely than heavier smokers to seek or receive 
treatment, leaving cessation efforts among nondaily smokers largely unaided.18,23  Treatment 
engagement is made difficult by nondaily smokers’ resistance to being thought of as smokers: 
nondaily smokers feel less addicted than daily smokers,24 do not consider themselves to be 
smokers,25,26 and will deny their smoking habit when asked by family, friends, and healthcare 
providers.27  In line with these self-perceptions are data from cross-sectional, naturalistic and 
laboratory studies that shown that nondaily smokers differ from daily smokers on important 
dimensions related to smoking cessation, including lower levels of dependence,28,29 higher levels 
of self-control,30,31 superior smoking-related error processing on neurocognitive tasks,32 and 
lower sensation-seeking impulses.33   
One reason traditional smoking cessation treatments fail to appeal to nondaily smokers may 
be that they are simply not applicable.  Existing treatments for smoking cessation are based on 
studies of daily smokers,34 and theoretical models of cigarette smoking assume daily smoking.35  

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Such models posit that smoking is primarily driven by nicotine dependence, such that smokers 
smoke in order to maintain nicotine levels above a certain level, thereby preventing the 
occurrence of withdrawal symptoms.36 Nondaily smokers, however, do not smoke continuously.  
Rather, they smoke on average 4 days per week, and 4 cigarettes per smoking day,37 and thus are 
not maintaining a specific level of nicotine.  Their reasons for smoking also tend to be different, 
when compared to daily smokers.  Nondaily smokers tend to smoke for social enhancement 
rather than to cope with negative affect,24,25 and tend to be driven by acute, situational motives 
(e.g., cue exposure, positive reinforcement) rather than nicotine dependence (e.g., tolerance, 
withdrawal symptoms).38-40  These data suggest that treatments emphasizing withdrawal and 
dependence are likely inappropriate for nondaily smokers. 
 
4. Smiling Instead of Smoking 
We developed a smartphone app that specifically addresses the characteristics of nondaily 
smoking.  To support smoking cessation, we use a positive psychology approach.  Positive affect 
enhancement is an empirically sound treatment target: positive affect is psychometrically and 
neurologically distinct from negative affect, and plays an important role in the days leading up to 
and following a quit attempt.  Enhancing positive affect with brief, self-administered exercises is 
entirely feasible: in recent years, a large number of positive psychology exercises have been 
developed that have consistently led to improvements in happiness, reductions in depression, and 
improvements in overall well-being.  Our smartphone app, “Smiling instead of Smoking” 
administers such positive psychology exercises to enhance and/or maintain positive affect, which 
is hypothesized to stimulate nondaily smokers to enact healthier alternatives to smoking by 
broadening their thought-action repertoire, increasing confidence, and decreasing craving and 
defensiveness about smoking-related health information (Figure 1).  
 
Positive
Psychology
Intervention
High Positive Affect
(maintained or increased)
- increased self-efficacy to refrain
  from smoking
- decreased defensive
  processing of self-relevant
  health information, which should
  lead to:
  - increased perceived
    importance of the cons of
    smoking
  - decreased valuing of the pros
    of smoking
  - increased motivation to quit
    smoking
- reduced desire / urge to smoke
- broadened thought-action
  repertoires to enact smoking
  alternatives
Smoking
Cessation
 
Figure 1. Theorized Mechanisms of Behavior Change 
 
The focus on happiness will help overcome treatment resistance, as the pursuit of happiness 
is generally appealing and non-stigmatizing.  To this end, we have worked closely with nondaily 

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smokers in Study 1 (#2017P001106)41 and Study 2 (#2018P002699) to develop Version 3.0 of 
our “Smiling Instead of Smoking” app.  In the current study (i.e., Study 3 in a series of 3 studies 
funded by the American Cancer Society (130323-RSG-17-021-01-CPPB)), we will conduct a 
proof-of-concept RCT of Version 3.0 of this app.  
 
 
II. 
SPECIFIC AIMS 
 
This is the third study in a series of 3 studies to develop a smartphone app to support 
nondaily smokers in quitting smoking, as funded by the American Cancer Society grant #RSG 
CPPB – 130323 (project dates: 07/01/2017 – 6/30/2021).  Study 1 (2017P001106) demonstrated 
feasibility and acceptability when smokers were onboarded in person41.  Study 2 (2018P002699) 
demonstrated feasibility and acceptability when smokers were onboarded remotely, nationwide.  
The present study is Study 3.  It is a 3-group proof-of-concept RCT, in which we seek to test if 
our app (i.e., Version 3 of our developed smartphone app, called ‘Smiling instead of Smoking’ 
(SiS)) is superior to treatment as usual (i.e., TAU; no treatment for nondaily smokers) and 
superior to a control app (i.e., the National Cancer Institute’s smartphone app “QuitGuide” (QG).  
Specifically, our aims are to: 
 
1. Test for differences between randomized groups on the primary outcome of this proof-of-
concept RCT, as measured at end of treatment (i.e., Week 6 post-quit): Self-efficacy to 
remain abstinent, as measured via the Smoking Self-Efficacy Questionnaire (SEQ)42: 
two-dimensional 12-item self-report scale measuring a person’s confidence in his or her 
ability to abstain from smoking when facing internal stimuli [e.g. feeling depressed] and 
external stimuli [e.g. being with smokers]. Participants rate each item on a sliding scale 
from 0 [not at all confident] to 100 [extremely confident]. Two subscale scores are 
created by averaging items assessing internal vs. external stimuli, respectively. We 
hypothesize that SiS > QG > TAU.   
 
2. Test for differences between randomized groups on secondary outcomes: 
a. Self-reported 30-day point-prevalence abstinence 6, 12 and 24 weeks post quit. 
We hypothesize that SiS > QG > TAU.    
b. Self-reported past week cigarette reduction at 2, 6, 12, and 24 weeks post quit, 
compared to baseline. We hypothesize that SiS > QG > TAU.   
c. Satisfaction with smoking cessation support, as self-rated on the Client 
Satisfaction Questionnaire (CSQ-8)43 at end of treatment.  We hypothesize that 
SiS > QG > TAU.   
d. Time spent applying content brought up by the apps/”Clearing the Air” at end of 
treatment (“During this past week, how much time did you spend applying or 
contemplating the content of the SiS app/QG app/”Clearing the Air”?” [in 
minutes]).  We hypothesize that SiS > QG > TAU.   
e. Use of smoking cessation strategies, as assessed at end of treatment.  We 
hypothesize that SiS > QG > TAU.   
f. Perceived impact of the provided materials on quitting (e.g., “reminded me to stay 
on track”), as assessed at end of treatment.  We hypothesize that SiS > QG > 
TAU.   
g. Appreciation, as measured via the Appreciation Scale44 at end of treatment. The 
Appreciation Scale is an 18-item scale which assesses the degree to which one is 
appreciative.  This is an important process outcome for this study, as the SiS app, 

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unlike the QG app or TAU, emphasizes the experience of positive emotions in 
order to support smoking cessation.  Ten of the items assess frequency of action 
(e.g., “I do things to remind myself to be thankful” 7-point Likert: 1 = More than 
once a day, 2 = About once a day, 3 = About once a week, 4 = About once a 
month, 5 = About once a year, 6 = A few times in my life, 7 = Never).  The 
remaining eight of the items assess level of agreement with appreciative 
statements (e.g., “I feel that it is a miracle to be alive” 7-point Likert: 1 = Strongly 
agree, 2 = Agree, 3 = Agree somewhat, 4 = Neither agree nor disagree, 5= 
Disagree somewhat, 6 = Disagree, 7 = Strongly disagree).  We hypothesize that 
SiS > QG > TAU.   
h. (SiS and QG only) Actual app usage – number of days participants used the 
assigned app during the prescribed period of app use (i.e., 7 weeks for both apps).  
Please note that we have a partnership agreement in place with the National 
Cancer Institute (see attached email) to obtain usage data of the NCI QuitGuide 
app for our research participants (using de-identified ID numbers), with 
participants’ explicit permission, as explained in the study facts sheet.  We 
hypothesize that SiS > QG.   
i. (SiS and QG only) Self-reported app usage – number of days used app, asked per 
week; if used, how many minutes per typical day used app 
j. (SiS and QG only) Likability rating of the app as measured at end of treatment 
(i.e., “How much did you like using the smoking cessation app we asked you to 
use?” 5-point Likert: 1 = I strongly disliked using the app, 2 = I somewhat 
disliked using the app, 3 = I neither liked nor disliked using the app; 4 = I 
somewhat liked using the app, and 5 = I strongly liked using the app). We 
hypothesize that SiS > QG.   
k. (SiS and QG only) Satisfaction rating of the smoking cessation support provided 
by the app (i.e., “How satisfied are you with the smoking cessation support this 
app provided you with?” 5-point Likert: 1 = very unsatisfied, 2 = somewhat 
dissatisfied, 3 = neither satisfied nor dissatisfied, 4 = somewhat satisfied, 5 = very 
satisfied).  We hypothesize that SiS > QG.   
l. (SiS and QG only) App usability ratings, as assessed via the System Usability 
Scale (SUS)45, a simple, ten-item attitude scale giving a global view of subjective 
assessments of usability, adapted to include language specific to the smoking app 
(e.g., “I found the smoking app unnecessarily complex” 5-point Likert: 1 = 
strongly disagree, 5 = strongly agree). We hypothesize that SiS > QG.   
3. (exploratory) To test, via mediational modeling, how treatment via the proposed app 
conferred benefit, or, if not effective, if failure is due to the treatment failing to impact 
hypothesized mechanisms of change, or because these mechanisms fail to impact 
outcome.  The outcome of interest in these mediational models is self-reported 30-day 
abstinence at the final follow-up, 6 months post quit.  The mediators to be tested, are: 
a. Self-efficacy as measured via the Smoking Self-Efficacy Questionnaire (SEQ); 
this is also our primary outcome variable, as described above. 
b. Emotional well-being 
i. Positive and negative affect, as measured via the positive affect subscale 
of the Positive And Negative Affect Schedule (PANAS)46:  For each 
subscale, both positive and negative, 10 mood adjectives are displayed. 
Participants rate to what extent they have felt each emotion on a 5-point 
scale [1 = very slightly or not at all, 5 = extremely].  In this study, the 
timeframe of reference is the past week. 

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ii. Happiness, as measured via two single-item measures, both rated on a 0-
100 slider, anchored at 0=not at all, 100=extremely: “In the PAST WEEK, 
how happy have you felt?”; “How happy are you feeling RIGHT NOW?”  
iii. Satisfaction with life, as measured via the Satisfaction with Life Scale 
(SWLS)47: 5 items rated on a 7-point Likert scale [e.g., “In most ways my 
life is close to my ideal]). 
iv. Subjective happiness, as measured via the Subjective Happiness Scale 
(SHS)48; 4 items rated on a 7-point Likert scale [e.g., “Some people are 
generally very happy. They enjoy life regardless of what is going on, 
getting the most out of everything. To what extent does this 
characterization describe you?”]). 
v. Stress and Coping, as measured via the stress and coping subscales of the 
Perceived Stress Scale (PSS10)49: 10-item self-report scale that measures 
the degree to which situations in one’s life are appraised as stressful.  
Items are worded both negatively (e.g., “In the last month, how often have 
you been upset because of something that happened unexpectedly?” and 
positively (e.g., “In the last month, how often have you felt that you were 
on top of things?” Traditionally, for a total score, positively worded items 
are reverse-scored, then sum-scored with the negatively worded items. 
More recently, the PSS-10 has been conceptualized as assessing two sub-
scales, perceived stress vs. perceived ability to cope with stressors,53 
which is how we will score this scale for this study. 
c. Desire to smoke, as measured via the Brief Questionnaire of Smoking Urges 
(QSU)50: a 10-item self-report measure of craving. Sample items include: “I have 
an urge for a cigarette” and “I would do almost anything for a cigarette now” and 
are rated on 7-point Likert scale [1 = strongly disagree, 7 = strongly agree]). 
d. Breadth of thought-action-repertoire, as measured via the Modified Twenty 
Statements Test (MTST)51: participants list any and all “actions” they can think of 
while experiencing a specific emotion.  We have modified Fredrickson’s scale to 
make it smoking-specific [e.g., at baseline, it states “Name the strongest emotion 
you feel when thinking about your upcoming quit attempt.  Take a moment to 
experience that emotion. Concentrate on it and live it as vividly and as deeply as 
possible.  Now recall the most recent cigarettes you have smoked. Given the 
feeling you just named ([piped]), please list all the things you could have done 
instead of smoking at those times.  You can list as many or as few things as come 
to mind in the lines below”). 
e. Processing of self-relevant health information 
i. Perceiving effects of smoking, as measured via the Attitudes Towards 
Smoking Scale (ATS)52:  an 18-item self-report measure assessing to what 
degree participants perceive adverse effects of smoking, psychoactive 
benefits of smoking, and pleasure of smoking.   
ii. Importance of the pros and cons of smoking, as measured via the 
Decisional Balance Inventory – short form (DCB)53 for Smoking: a 6-item 
scale which rates the perceived importance of pros and cons of smoking.  
iii. Single item pros (rated on a 0-10 slider scale [0 = not at all, 10 = 
extremely important]; “Think about all the things you LIKE/LOVE about 
quitting/being smoke-free; taken together, how important are those things 
to you RIGHT NOW?”) 

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iv. Single item cons (rated on a 0-10 slider scale [0 = not at all, 10 = 
extremely important]; “Think about all the things you DISLIKE/HATE 
about quitting/being smoke-free; taken together, how important are those 
things to you RIGHT NOW?”) 
v. Commitment to Quitting Smoking, as measured via the Commitment to 
Quitting Smoking scale (CQSS),54 an 8-item self-report measure capturing 
the extent to which persons feel personally obligated to persist in quitting 
smoking despite difficulties, craving and discomfort. 
vi. Single item how motivated (rated on a 0-10 slider scale [0 = not at all, 10 
= extremely motivated]; “How MOTIVATED are you to quit smoking/ 
stay quit?”) 
 
 
III. 
SUBJECT SELECTION 
 
Eligibility criteria includes the following: (a) 18+ years of age, (b) smartphone ownership 
(Android or iPhone only), (c) current nondaily smoker, who smokes at least weekly, and no more 
than 25 out of the past 30 days, and (d) lifetime history of having smoked 100+ cigarettes, and 
(e) is willing to make a smoking quit attempt as part of this study (f) currently residing in the 
United States of America. We will use both grass-root efforts (e.g., PI’s Harvard Scholar 
website, Craigslist, quit smoking forums) and commercial advertising (e.g., Facebook).  
In addition to the aforementioned recruitment methods, we will also recruit through the RPDR 
(Research Patient Data Registry) at Partners Healthcare. The Research Patient Data Registry 
(RPDR) is supported by the dedicated team of nearly a dozen developers and support personnel.  
RPDR is the centralized clinical data registry/warehouse directed by Research IS & Computing‘s 
Director, Shawn Murphy, M.D. PhD. The RPDR gathers data from hospital systems and stores it 
in one place, bringing clinical information to a researcher’s fingertips and ensuring the security 
of patient information. We will run bi-weekly queries for current nondaily cigarette smokers seen 
at Partners Healthcare primary care sites, and subsequently submit the appropriate data requests 
to receive the following identifiable information: MRN (medical record number), contact 
information (email address, phone number, and mailing address), and RODY answer (yes/no).  
We will only contact patients who are designated “yes” in the Epic system, for the column “okay 
to contact.” Under the new MGB opt-out system, this column designates “whether it is okay to 
contact the patient about research recruitment. This may be based on the patient's explicit 
preference, system default, or an override rule. The information displays in Yes/No format.  
In addition to the above mentioned recruitment efforts, research staff will use EPIC to assist 
in recruitment.  To this end, we have worked with the Partners eCare Research Core (PeRC) to 
set up the necessary steps. PeRC leverages the Epic EHR to assist researchers in identifying and 
recruiting patients for their research studies conducted at Partners HealthCare. PeRC will put 
together a report through EPIC based on a list of predetermined variables (please see attached list 
of variables to be extracted – this list includes contact information and smoking status).  After 
Epic training, and hands-on guidance from the PeRC team, study staff will run this automated 
report within Epic to identify patients who are smokers and recently completed a primary care 
visit at MGH.  For those who have RODY status = “yes”, study staff will send an opt-out email 
via Patient Gateway (please see attached letter). (A RODY “yes” designation in Epic means as 
shown in the report that the patient “okay to contact the patient about research recruitment. This 
may be based on the patient's explicit preference, system default, or an override rule.” )For those 
who do not opt out of hearing about the study, study staff will follow-up by phone to ask about 
their interest in participating in the study, and, if interested, will phone screen them. 

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We will use stratified enrollment to ensure that our final sample will (a) be equally balanced 
between men and women, and (b) reflect national prevalence rates of nondaily smoking in terms 
of ethnicity and race, where we will enroll no more than 54% non-Hispanic White participants, 
as per the 2014 National Health Interview Survey 
(http://www.cdc.gov/nchs/nhis/nhis_2014_data_release.htm), which shows that 54% of nondaily 
smokers are non-Hispanic White.   
 
 
IV. 
SUBJECT ENROLLMENT 
 
This is a nation-wide proof-of-concept randomized controlled trial conducted entirely 
remotely.  We will enroll 225 nondaily smokers based on the following eligibility criteria: (a) 
18+ years of age, (b) smartphone ownership (Android or iPhone only) (c) current nondaily 
smoker, who smokes at least weekly, and no more than 25 out of the past 30 days, and (d) 
lifetime history of having smoked 100+ cigarettes, and (e) is willing to make a smoking quit 
attempt as part of this study. 
Participants will participate in screening, consisting of (1) a phone screen, (2) an online 
screening survey, which will contain check-questions to verify that respondents are truly reading 
items (100% accuracy required; If less than 100% accuracy, participant is screened out unless 
there is a compelling reason to justify missed check items. This would only happen upon review 
with the PI and after a phone conversation with the study participant has taken place to review 
the missed item(s) and explain the situation. Examples would include survey glitch, otherwise 
thoughtful write-in answer indicating survey attention, careful review of other survey answers 
and length of time spent on survey); (3) provision of contact information for two collaterals who 
can assist research staff in locating participants; collaterals will be told that the participant is 
participating in a study tracking health behaviors; and (4) provision of their social security 
number to enable remuneration by check, as required by MGH.  We expect that 1/3 of 
participants who start the online survey will enroll in the study.   
 
During the phone screen, research staff will provide an overview of the study, and will 
answer any questions participants may have about the study.  If found eligible during the phone-
screen (see attached phone screen script), staff will email a pdf of the study fact sheet to the 
potential participant, using SEND SECURE or not, based on the potential participant’s 
preference, as indicated during the phone screen.  The study fact sheet provides an outline of the 
nature of the study, risks and benefits to participation, details on remuneration for participation, 
and how to contact with PI or IRB staff in case they have any concerns (see attached study fact 
sheet).  The same email will contain a person-specific link to the online survey and a general 
resource sheet. Participants are encouraged to ask questions about the study and anything they 
have read in the study fact sheet prior to clicking on the survey link.  When the participant starts 
the survey, they will be presented with the same study fact sheet in REDCap that they have 
received via email.  They must click “I agree to participate in this screening survey” in order to 
proceed to the survey.  The study fact sheet reminds participants that, at this point, they are 
agreeing to participating in the online survey:  “Once we have reviewed your survey responses, 
we will contact you to proceed with the remaining parts of the screening test.  If you are eligible 
to enroll in this study, and you decide you would like to participate in this study, we will ask you 
for your verbal consent to participate in the study during a phone call with study staff.” 
 
Staff will receive an automatic email from REDCap once the screening participant has 
completed the survey.  If the screening participant incorrectly responded to the check items 

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(please see attached for the specific check items), staff will inform the screening participant that 
they are ineligible for the study.  If the survey is complete and valid, staff will collect (via email, 
phone, and/or REDCap form) the contact information for collaterals the participant would like to 
specify for this study. Social security number (to enable payment by check) and a mailing 
address to which Accounts Payable can mail the check containing remuneration will be collected 
via phone, and only after participants have been enrolled in the study.  For screen participants 
who do not enroll in the study (i.e., because they are ineligible or because they decide against the 
study) study staff will ask for verbal consent (via phone) to allow us to collect their SSN (during 
the same phone call) and send them a check for completing the screening survey. 
 
At the end of this phone call, study staff will ask the screening participant to indicate the date on 
which they would like to quit smoking.  The enrollment call is then scheduled to occur 8 days 
before that date.  If the chosen quit date falls on a Monday or Sunday, meaning that the 
enrollment call should be on a Saturday or a Sunday, the enrollment call will be adjusted to fall 
on a weekday.  
 
During the enrollment call, staff will review the study fact sheet with the participant, and will 
invite the participant to ask any questions they may have about the study and all its procedures.  
Once all questions have been answered, study staff will ask the participant to give verbal consent 
to enroll in this study.  The date and time of this verbal consent will be documented by study 
staff in our REDCap dataset. 
 
After providing verbal consent, the participant is randomized.  This is an unblinded study.  
Randomization will occur via a randomization sheet, as generated using the PROC PLAN 
procedure in the statistical software package SAS.  Randomization will be in a 1:1:1 ratio (SiS3 
vs. QG vs. TAU), with a block size of 4.  Study staff will use the randomization sheet to 
determine the participant’s treatment group, document this randomized assignment in our 
REDCap dataset, and will then onboard the participant to the smoking cessation support they 
have been randomized to receive (i.e., our smartphone app SiS or NCI’s app QuitGuide or TAU, 
which consists of NCI’s written materials, “Clearing the Air”), using a time-matched, ~15 
minute script.     
 
We will stop enrollment when n=225 participants have been successfully onboarded to their 
randomized condition.  Based on our experience in Study 1 (#2017P001106) and Study 2 
(#2018P002699), we expect that 1/3 of participants who start the screening survey will enroll in 
the study.  Thus, we are estimating that n=675 will be necessary to start the screening survey in 
order for n=225 to be successfully enrolled to their randomized treatment condition. 
 
 
V. 
STUDY PRODECURES 
This is a single site study.  Participation will last 6 months (see Figure 2), and entails: 
• Completing a scripted onboarding call (approximately 30-45 minutes) 
• Making a quit attempt 
• Engaging with smoking cessation support (randomized) over the course of seven weeks, one week 
prior and 6 weeks following the originally chosen quit day 

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• Completing five online, REDCap-administered surveys, administered prior to the quit day (online, 
as part of a screening test), and at 2-week, 6-week, 3-month, and 6-month follow-ups of the 
participant’s chosen quit day  
 
 
 
Figure 2. Timeline of study participation 
 
 
After onboarding, participants will be asked to engage with the smoking cessation materials they receive 
as part of this study (i.e., smartphone apps or written materials) for a period of seven weeks (1 week before, 6 
weeks following the quit attempt).  They may choose to continue to use these materials thereafter.  
 
Treatment Condition: “Smiling Instead of Smoking” (SiS) smartphone app 
Participants randomized to the treatment condition will be asked to use Version 3 of our “Smiling 
Instead of Smoking” (SiS) smartphone app for a period of 7 weeks.  The SiS app is a smartphone app that 
engages participants in daily positive psychology habit-building exercises over the course of 7 weeks, as-needed 
happiness boost activities and ‘behavioral challenges’ every 2-3 days that are designed to engage participants 
with ad libitum tools offered by the app, which offer tracking functionality (i.e., log of smoked cigarettes), 
graphical summaries (i.e., pie chart of reason smoked for the past 20 cigarettes), reminders (i.e., a tool to send 
reminders to stay smoke-free at specific times), note keeping (i.e., personal reasons for quitting), distraction 
(i.e., a game called “Magma Bear”) and information (e.g., benefits of quitting, suggested strategies for specific 
situations).  Along the way, the app also provides participants with information about how positive affect is 
relevant to quitting smoking and health. 
 

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Screenshots from SiS Version 3: (1) a habit-building exercise is assigned, (2) its
completion is logged, and (3) science findings are shared to reinforce the value of
happiness.
 
 
Conceptual Model.  Our goal in using a positive psychology approach is two-fold: (1) to foster engagement 
with the app, which delivers tools and information recommended by United States Clinical Practice Guidelines 
(USCPG) for smoking cessation34, and (2) to protect against deficits in positive affect occurring during the quit 
attempt.  Based on previous findings on the role of positive affect in smoking cessation regarding desire to 
smoke55, smoking relapse56, self-efficacy57, and processing of self-relevant health information58, and based on 
the broaden-and-build theory59, we hypothesize that completing the app’s happiness exercises should protect 
against expected decreases in positive affect, and thereby provide smokers with the benefits associated with 
positive affect, namely, reduced desire to smoke, increased self-efficacy, and greater cognitive readiness to deal 
with the challenges of smoking cessation.  
 
The SiS app does not collect identifiable information.  It asks app users to click buttons to log when they 
smoke and for what reasons they smoke, and to enter text in text boxes describing their personal reasons for 
quitting smoking, the circumstances under which they smoke, and to describe their experiences in response to 
the happiness exercises (e.g., naming three good things they experienced that day; describing something 
beautiful they saw that day).  It uses push notifications to alert app users to new tasks (e.g., new behavioral 
challenge), remind them of tasks that still need to be completed (e.g., a happiness exercise that still needs to be 
done), and to notify them of challenging times (i.e., “Smoke Alarms” that app users scheduled for themselves 
within the app).  These push notifications are optional, and can be toggled off.  The onboarding script teaches 
participants how to toggle them on and off. 
 

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The “Smiling Instead of Smoking” (SiS) smartphone app provides information in graphical format, text, and
provides links to outside websites (users need to click “Read More” in the “Owl Wisdoms”, and are warned that
clicking that link exits the app).  App user’s progress through quitting is tracked with ‘badges’.
 
 
Control Condition #1: “QuitGuide” (QG) smartphone app 
Participants randomized to this control condition will be asked to use the National Cancer Institute’s 
“QuitGuide” (QG) smartphone app for a period of 7 weeks.  This smartphone app is one of two smartphone 
apps the NCI currently has publicly available for use on their smokefree.gov website.  Referral to this website is 
recommended for treating smokers in healthcare settings.60  QG is frequently used as a comparison app in 
smartphone app smoking cessation studies.61-66  While QG was not developed specifically for nondaily smokers, 
it targets both nondaily and daily smokers (i.e., when downloading the app, users are asked to specify their 
smoking pattern, which includes both nondaily and daily patterns of smoking).  Some SiS features have direct 
analogs in QG; others do not.  The onboarding script leads QG users through the QG content in the same order 
as for SiS, to the degree possible: setting the quit day (SiS & QG), happiness-promoting activities vs. tracking 
mood and craving (SiS vs. QG), guidance on quitting (via behavioral challenges in SiS, vs. “Learn to Quit” 
information in QG), logging cigarettes (SiS & QG), strategies for smoking triggers (pie chart in SiS, various 
graphs in QG), setting reminders (time-based in SiS, time and location based in QG), and as-needed tools 
(happiness-boost activities, suggested strategies in SiS vs. tips in response to reporting craving or negative 
affect in QG).         
 
The QG app does not collect identifiable information.  Upon install, the app asks app users to click buttons 
and to use sliders to describe their smoking (e.g., typically number of cigarettes smoked per day) and craving 
pattern (e.g., time of day of strongest craving).  Going forward, it uses buttons to allow users to describe their 
craving and mood any time as they are engaging in their quit attempt.   
 

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The QuitGuide (QG) smartphone app asks app users to track their craving and mood
as they quit smoking.  In response to their reports, they receive tips and tricks for
dealing with these triggers.
 
 
The QG app also contains a “Learn to Quit” guide, which largely mimics the information provided in the 
NCI’s booklet “Clearing the Air”. 
 
The QuitGuide (QG) smartphone app provides
information in line with the information contained in the
NCI booklet “Clearing the Air”.
 
 
The QG app also allows text entry so participants can name their personal reasons for quitting smoking, and 
so they can journal in response to craving or mood triggers.  The content of these textboxes is saved on the 
client but not the server side of this app, so that app users can see their typed in text (e.g., personal reason for 
quitting smoking), but the National Cancer Institute’s Smokefree Team does not have a record of this text. 
      
 
Control Condition #2: Treatment as Usual (TAU) 

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Participants in the treatment as usual (TAU) condition will be asked to make a naturalistic quit attempt, 
using any methods they feel might help them.  To time-match the onboarding experience of SiS and QG 
participants, study staff will use an onboarding script to lead TAU participants through the NCI booklet 
“Clearing the Air”,67 which encourages activities in the same order as implemented in the SiS behavioral 
challenges (i.e., reflecting on reasons to quit, informing about benefits of quitting, logging smoking and its 
triggers, formulating strategies for dealing with triggers).  Additionally, “Clearing the Air” provides information 
on smoking cessation support resources, such counseling and pharmacological approaches. 
 
 
At the end of treatment, participants complete an online survey via REDCap.  This is our primary study 
endpoint (see Specific Aims).  Participants complete two more online surveys via REDCap, occurring 12 and 24 
weeks post-quit, for secondary aims. 
 
Table 1 specifies which data are collected at which time points.  Please see attached for specific 
descriptions of each of these measures.   
 
 
Table 1. Data Collection Instruments per Time Point 
Type of Measure 
Timing of Assessment 
  Specific Measure 
BL 
Wk 2 
Wk 6 
Wk 12 
Wk 24 
Primary Outcome 
 
 
 
 
  
  Smoking Self-Efficacy Questionnaire (SEQ-12) 
X 
X 
X 
X 
X 
Secondary outcomes 
 
 
 
 
  
  Smoking status 
X 
X 
X 
X 
X 
  Recent cigarette use 
X 
X 
X 
X 
X 
  Client Satisfaction Questionnaire (CSQ-8) 
  
  
X 
  
  
  Time spent applying content 
 
 
X 
X 
X 
  Use of smoking cessation strategies 
  
  
X 
  
  
  Perceived impact of SiS/QG/TAU on quitting  
 
 
X 
 
  
  Appreciation Scale (AS) 
  
  
X 
  
  
  (SiS/QG only) Actual app usage - continuously recorded 
X 
X 
X 
X 
X 
  (SiS/QG only) Self-reported app usage: weeks -1 to 2 
  
X 
  
  
  
  (SiS/QG only) Self-reported app usage: weeks 3 to 6 
 
 
X 
 
  
  (SiS/QG only) App likeability & satisfaction 
  
  
X 
  
  
  (SiS/QG only) System Usability Scale (SUS) 
 
 
X 
 
  
Other outcomes to be explored in mediational analyses 
  
  
  
  
  
  Emotional well-being 
 
 
 
 
  
    PANAS Positive And Negative Affect Schedule (PANAS) 
X 
X 
X 
X 
X 
   
Happiness single-item measures  
X 
X 
X 
X 
X 
    Satisfaction With Life Scale (SWLS) 
X 
X 
X 
X 
X 
   
Subjective Happiness Scale (SHS) 
X 
X 
X 
X 
X 
    Perceived Stress Scale (PSS10) 
X 
X 
X 
X 
X 
  Desire to smoke 
 
 
 
 
  
    Brief Questionnaire of Smoking Urges (QSU) 
X 
X 
X 
X 
X 
  Thought action repertoire 
 
 
 
 
  
    Modified Twenty Statement Test (mTST) - Baseline 
X 
  
  
  
  
   
Modified Twenty Statement Test (mTST) - Follow-up  
 
X 
X 
X 
X 
  Processing of self-relevant health information 
  
  
  
  
  
   
Attitudes Towards Smoking (ATS) 
X 
X 
X 
X 
X 

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    Decisional Balance Inventory For Smoking (DCB-short) 
X 
X 
X 
X 
X 
   
Single-item pros and cons measures 
X 
X 
X 
X 
X 
    Commitment To Quitting Smoking Scale (CQSS) 
X 
X 
X 
X 
X 
   
Single-item motivation measure 
X 
X 
X 
X 
X 
Descriptors 
  
  
  
  
  
  Demographics 
X 
 
 
 
  
  Mental health diagnoses 
X 
  
  
  
  
  Smoking history 
X 
 
 
 
  
  Fagerström Test for Nicotine Dependence (FTND) 
X 
  
  
  
  
  Previous quit attempts 
X 
  
  
  
  
  Recent Quit Methods Used 
  
X 
X 
X 
X 
  E-cigarette use  
X 
X 
X 
X 
X 
  Alcohol use  
X 
X 
X 
X 
X 
  Smartphone use 
X 
 
X 
 
  
  Center of Epidemiologic Studies Depression Scale (CES-D-10) 
X 
X 
X 
X 
X 
  Generalized Anxiety Disorder Screener (GAD-7) 
X 
X 
X 
X 
X 
  Snaith-Hamilton Pleasure Scale (SHAPS) 
X 
X 
X 
X 
X 
   Life Orientation Test Revised (LOT-R) 
X 
X 
X 
X 
X 
  State Optimism Measure (SOM) 
X 
X 
X 
X 
X 
  Brief State Optimism Measure (BSOM) 
X 
X 
X 
X 
X 
  Generalized Self-efficacy Scale (GSES) 
X 
  
  
  
  
  Personality SIMP 
X 
  
  
  
  
  Brief COPE 
X 
X 
X 
X 
X 
 
 
As noted in Table 1, in addition to outcome variables, we are also collecting descriptive information to 
describe the participants in this study on constructs relevant to this study: 
• Demographics (at baseline, includes age, gender, ethnicity, race, education level, current student 
status, current employment status, total family/household income, and rurality of current 
residence) 
• Mental health diagnoses (at baseline, “Has a doctor, nurse, or counselor ever told you that you 
have a mental or psychological condition?” [yes, no]. If participants select “yes,” they asked to 
select all that apply from a list of Axis I and II psychiatric disorders, or to specify “other mental 
health diagnosis.”) 
• Smoking history (at baseline, captures estimated number of cigarettes participant smoked in 
lifetime, age when participant first tried smoking (even one or two puffs), age when participant 
first smoked an entire cigarette, and whether participant has ever smoked daily) 
• Fagerström Test for Nicotine Dependence (FTND),68 a 6-item questionnaire characterizing level 
of physiological nicotine dependence. Answer choices are assigned numerical values which can 
be sum-scored to obtain level of dependence [i.e., very low dependence, low dependence, 
medium dependence, high dependence, or very high dependence]) 
• Previous quit attempts (at baseline, captures whether participant has tried to quit smoking before, 
number of previous quit attempts, and types of quit methods previously used [e.g., group 
counseling/class, smoking cessation app]) 
• Recent quit methods used (at follow-up time points, captures any additional quit methods used 
since participant’s quit day [using the same check-box list as seen in Previous Quit Attempts]) 
• E-cigarette use (at all time points, captures whether participant has ever used electronic 
cigarettes, whether participant is currently using electronic cigarettes, number of “bouts” of 
vaping per vaping day, and number of puffs per “bout” of vaping) 

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• Alcohol use (at all time points, captures whether participant has drunk alcohol in past 30 days, 
number of drinks per drinking day, number of days in past 30 days having drunk 5+ drinks per 
drinking occasion [males], number of days in past 30 days having drunk 4+ drinks per drinking 
occasion [females], number of weeks in past month having drunk 14+ drinks per week [males], 
number of weeks in past month having drunk 7+ drinks per week [females], and number of 
drinks per weekday in past week) 
• Smartphone Use (5 item questionnaire captures self-reported frequency of smartphone use over 
the past 30 days, reason for smartphone use, whether push notifications from study app prompts 
unrelated smartphone use, whether unrelated smartphone use prompts study app use, and 
location of study app on smartphone)  
• Center of Epidemiologic Studies Depression Scale, 10-item version (CES-D-10),69 designed to 
assess degree of depressed mood [e.g., “I was bothered by things that usually don’t bother me.” 
4-point Likert: 0 = Rarely or none of the time (less than 1 day), 1 = Some or a little of the time 
(1-2 days), 2 = Occasionally or a moderate amount of time (3-4 days), 3 = Most of the time (5-7 
days)] 
• Generalized Anxiety Disorder Screener (GAD-7),70 a 7-item scale designed as a screening and 
severity measure for generalized anxiety disorder, “Over the last 2 weeks, how often have you 
been bothered by the following problems?” [e.g., “Feeling nervous, anxious, or on edge.” 4-point 
Likert: 0 = Not at all, 1 = Several days, 2 = More than half the days, 3 = Nearly every day], 
includes an additional COVID-19 impact question, “Compared to before COVID-19, how have 
the frequency and severity of these problems changed during the last 2 weeks?” Sliding scale: 
0=Much less, 50 = About the same, 100 = Much more”)  
• Snaith-Hamilton Pleasure Scale (SHAPS),71 a 14-item scale designed to measure the ability to 
experience pleasure [e.g., “I would enjoy my favorite television or radio program.” 4-point 
Likert: 1 = Strongly disagree, 2 = Disagree, 3 = Agree, 4 = Strongly agree]) 
• Life Orientation Test Revised (LOT-R),72 a standard psychological tool for measuring optimism 
consisting of 10 items [e.g., “In uncertain times, I usually expect the best.” 5-point Likert: 1 = I 
disagree a lot, 2 = I disagree a little, 3 = I neither agree nor disagree, 4 = I agree a little, 5 = I 
agree a lot]) 
• State Optimism Measure (SOM),73 a 7-item scale capturing in-the-moment optimism [e.g., “I am 
feeling optimistic about life’s challenges.” 5-point Likert: 1 = Strongly disagree, 2 = Disagree, 3 
= Neither agree nor disagree, 4 = Agree, 5 = Strongly agree) 
• Brief State Optimism Measure (BSOM), a two-item questionnaire capturing in-the-moment 
optimism in regards to longer-term events [e.g., “In thinking about the challenges in my life, I 
feel RIGHT NOW that ultimately:” Sliding scale: 0 = Things will get a lot worse, 50 = Things 
will stay the same, 100 = Things will get a lot better]) 
• General Self-Efficacy Scale74, a 10-item scale measuring self-efficacy [e.g., “I can always 
manage to solve difficult problems if I try hard enough.” 4-point Likert: 1 = Not at all true, 2 = 
Hardly true, 3 = Moderately true, 4 = Exactly true]) 
• Single-Item Measures of Personality,75 which consists of five single-item measures with bipolar 
response scales to measure the Big Five personality traits [e.g., “Generally, I come across as…” 
with a bipolar response scale between 1 and 9, anchors vary per question]) 
• Brief COPE,76 a 28-item scale designed to measure methods of coping with stress [e.g., “I’ve 
been getting emotional support from others.” 4-point Likert: 1 = I haven’t been doing this at all, 
2 = I’ve been doing this a little bit, 3 = I’ve been doing this a medium amount, 4 = I’ve been 
doing this a lot]) 
 
Participants will be remunerated according to the following remuneration schedule: 
 
Table 2. Remuneration Schedule 

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Payment will be paid by check, where participants will receive a total of five checks, corresponding to 
the five study assessments occurring at screening, 2-week, 6-week, 3-month and 6-month follow-up.  
Participants will receive $25 for each completed online survey, unless they fail to answer 100% of the randomly 
placed reading alertness check items correctly (e.g.: “Please answer "not at all confident”.”), in which case they 
receive $10 for a given survey.  (Correctly answering all check items is a screening criterion, which is explained 
to participants during the screening phone call).  At the primary endpoint, the 6-week assessment, participants 
receive an additional $25 for the survey, because this survey is longer than the other surveys. 
 
 
Risks are expected to be minimal, and include breach of confidentiality, subject discomfort 
from answering questions about smoking, and discomfort from quitting smoking.  We will 
minimize these risks by safeguarding electronic data capture by using HIPAA-compliant 
electronic data capture processes, assuring participants that they do not need to answer any 
questions they do not want to answer, and by providing information on how to manage smoking 
cessation.  
 
A subject will be removed from the study if he or she no longer wishes to participate for any 
reason.  A subject may also be removed from the study by the PI, if the participant cannot 
comply with study procedures (e.g., responds incorrectly to survey check items, cannot install 
the app on his/her smartphone) or causes undue distress to study staff (e.g., becomes belligerent 
towards study staff). 
 
 
VI. 
BIOSTATISTICAL ANALYSIS 
 
Statistical Power.  This is a proof-of-concept trial.  Therefore, our primary endpoint is a 
process variable, a shorter-term variable that is linked to subsequent change on the outcome of 
ultimate interest.  In this case, ultimately, the SiS app is hoped to have an effect on smoking 
cessation 6 months after the chosen quit day.  Typically, effect sizes for mHealth interventions 
for smoking cessation are very small; their public health importance lies in their potential reach, 
where a small effect in a large population can make a considerable impact on public health.  
Specifically, for interventions delivered via websites, meta-analyses have reported an overall 
odds ratio for point prevalence abstinence of 1.14 [1.07-1.22], and Cohen’s d=0.12.77,78  For text 
messaging, a Cochrane review estimated a relative risk of 1.54 [1.19-2.00] in favor of automated 
text messaging interventions compared to minimal smoking cessation support.79  Such effect 
sizes require large scale RCTs, which is beyond the scope of this proof-of-concept RCT.  Thus, 
as a process indicator of subsequent smoking cessation, we have selected self-efficacy to abstain 
from smoking as our primary outcome variable, because self-efficacy has been identified as the 
primary mediator by which a text-messaging intervention conferred smoking cessation benefit.  
Similar to our study, this trial used the “Clearing the Air” booklet as the control condition, and 

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showed that self-efficacy observed one month after the chosen quit day mediated group 
differences in smoking cessation at the 6-month follow-up.80   
In selecting the sample size for this proof-of-concept trial, we were guided by the effect 
observed in that text-messaging trial.  Namely, in the text-messaging study,80 the observed group 
difference between treatment and control at 1 month post quit day on self-efficacy was d=0.66.  
Thus, we conservatively powered our proof-of-concept RCT to detect an effect size of d=0.50.  
Using SAS PROC POWER, we calculated that we would need a sample size of n=64 per group 
to detect an effect of d≥0.50.  Assuming a retention rate of 85%, we would need to enroll n=75 
per group in order to retain n=64 by end of treatment.  Thus, the total number of participants to 
be enrolled into this trial is n=225 (3 randomized groups * 75 participants to be enrolled in each 
group = 225). 
 
Analytic Plan.  All successfully enrolled participants (i.e., passed the screening process, was 
successfully onboarded to the assigned smoking cessation materials) will be included in the 
outcome analyses.  For hypotheses only relevant to the SiS and QG conditions (marked in 
Specific Aims), only participants successfully onboarded to those conditions will be included in 
the analyses. 
 
1. Primary Outcome (Aim 1).  In this proof-of-concept RCT, the primary outcome is self-
efficacy to abstain from smoking, as measured by the SEQ-12.  The primary endpoint is end-
of-treatment, which occurs 6 weeks after the originally chosen quit day.  To test for 
differences between randomized groups, we will fit a fixed effects repeated measures model 
using PROC MIXED, where observations are modeled as nested within persons.  Predictors 
included in the model will be GROUP (i.e., SiS vs. QG vs. TAU), TIME (i.e., BL, Week 2, 
Week 6, Week 12 and Week 24), and the GROUP*TIME interaction effect.  A contrast 
statement will be used to derive the test statistic for the GROUP comparison at Week 6, our 
primary endpoint, given the overall longitudinal model.  This contrast statement will test the 
null hypothesis that SiS = QG = TAU.  If this null hypothesis is rejected (p<0.05), we will 
conduct pair-wise follow-up tests that compare the three possible pairwise comparisons (i.e., 
SiS vs. QG, SiS vs. TAU, and QG vs. TAU).    
 
2. Secondary Outcomes (Aim 2).  The secondary outcomes in this proof-of-concept RCT are 
exploratory.  Thus, we will not correct for multiple testing.  We will fit one model per 
secondary outcome, using an alpha of 0.05 for all analyses.   
 
2.1. To test for differences between randomized groups for outcomes that are assessed 
multiple times (Aims 2a, 2b), our overall modeling approach will be the same as for Aim 
1.  That is, for each outcome, we will fit a fixed effects repeated measures model, where 
observations are modeled as nested within persons.  Predictors included in the model 
will be GROUP, TIME, and the GROUP*TIME interaction effect.  However, for these 
secondary outcomes, the definitions of the TIME effect varies across these secondary 
outcomes, based on their assessment schedule. The distribution of the outcome variables 
also varies across these variables.  Thus, we will implement this overall modeling 
approach for these variables as follows: 
2.1.1. (Aim 2a) Self-reported 30-day point-prevalence abstinence: the dependent 
variable will be a binary outcome variable (1=self-reported abstinence for 30 days, 
0=not), which will be modeled over three timepoints (i.e., 6, 12 and 24 weeks post 
quit) using PROC GENMOD, where a binomial distribution with logit link function 
will be specified.  The GROUP effect will include all three groups (SiS vs. QG vs. 

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TAU), as this outcome will be assessed in all randomized groups.  Contrast 
statements will be used to derive the test statistics for the GROUP comparisons at 
Weeks 6, 12 and 24, given the overall longitudinal model.  These contrast 
statements will test the null hypothesis that SiS = QG = TAU at the tested 
timepoints (i.e., Weeks 6, 12 and 24).  If this null hypothesis is rejected (p<0.05), 
we will conduct pair-wise follow-up tests that compare the three possible pairwise 
comparisons (i.e., SiS vs. QG, SiS vs. TAU, and QG vs. TAU). 
2.1.2. (Aim 2b) Self-reported past week cigarette reduction: first, we will calculate 
reductions in cigarette consumption by subtracting the number of cigarettes smoked 
in the week leading up to the baseline assessment, as measured in the baseline 
survey, from the number of cigarettes smoked in the week leading up to the 2, 6, 12, 
and 24 week assessments, as assessed in these respective surveys.  The resulting 
change score will be the dependent variable in the fixed effects repeated measures 
model, which will be modeled over four timepoints (i.e., 2, 6, 12 and 24 weeks post 
quit).  We anticipate that this dependent variable will be normally distributed, but 
will also consider other possible distributions (e.g., Poisson).  If normally 
distributed, this model will be fit in SAS using the PROC MIXED procedure.  
Contrast statements will be used to derive the test statistics for the GROUP 
comparisons at Weeks 2, 6, 12 and 24, given the overall longitudinal model.  These 
contrast statements will test the null hypothesis that SiS = QG = TAU at the tested 
timepoints (i.e., Weeks 2, 6, 12 and 24).  If this null hypothesis is rejected (p<0.05), 
we will conduct pair-wise follow-up tests that compare the three possible pairwise 
comparisons (i.e., SiS vs. QG, SiS vs. TAU, and QG vs. TAU). 
 
2.2. To test for differences between randomized groups for outcomes that are only assessed 
at end of treatment (Aims 2c – 2l), for each outcome, we will use a fixed effects model, 
where GROUP is the only predictor, and score at end of treatment is the dependent 
variable.  Histograms will be used to guide selection of the most appropriate distribution.  
We anticipate that we will use the normal distribution for the CSQ-8 (Aim 2c), use of 
strategies (Aim 2e), perceived impact (Aim 2f), the AS (Aim 2g), actual app usage (Aim 
2h), self-reported app usage (Aim 2i), likeability of the app (Aim 2j), satisfaction with 
the app (Aim 2k), and the SUS (Aim 2l), as implemented via the PROC MIXED 
procedure in SAS.  We anticipate that we will use the Poisson distribution for time spent 
applying content (Aim 2d), as implemented via the PROC GENMOD procedure in SAS.  
If the GROUP effect is statistically significant (p<0.05), we will conduct pair-wise 
follow-up tests that compare the three possible pairwise comparisons (i.e., SiS vs. QG, 
SiS vs. TAU, and QG vs. TAU).  These follow-up analyses will not be necessary for 
secondary outcomes that are only assessed for the SiS and QG conditions (i.e., Aims 2j-
2l).    
 
3. Exploratory mediational models (Aim 3): We will use mediational modeling, using the 
product-of-coefficients approach81,82 and a fully lagged model83 to test if hypothesized 
within-person changes (see Figure 1) occur, and if they are linked to subsequent abstinence. 
The independent variable will be randomized group assignment (i.e., SiS vs. TAU), and the 
outcome variable will be self-reported 30-day point prevalence abstinence as measured at 6-
month follow-up).  The mediators will be our theorized mechanisms of change, as listed in 
the Aim 3 (i.e., self-efficacy, emotional well-being, desire to smoke, breadth of thought-
action-repertoire, processing of processing of self-relevant health information,).  Baseline 
values on these constructs will be included in the model to control for individual differences 

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on these measures.  The mediator will be scale scores observed at mid-treatment, at the 2-
week assessment, which marks the end of the cessation phase.84  We will use multiple 
mediation to determine the relative importance of each mechanism, and moderated multiple 
mediation to identify differences in mechanisms across subgroups (e.g., males vs. females, 
young adult vs. older adults), similarly to our approach in delineating mechanisms of 
behavior change in Alcoholics Anonymous.85-87 
 
 
VII. 
RISKS AND DISCOMFORTS 
 
Potential Risks: Participation will last 6 months, where surveys will be administered at 
enrollment, 2-week, 6-week, 3-month, and 6-month follow-up.  Participants will use the 
provided smoking cessation support materials for a strongly encouraged period of 7 weeks (1 
week before, 6 weeks following the quit attempt), and optional continued use thereafter.  As 
such, the potential risks in the study are considered minimal and include (1) potential discomfort 
related to completing questionnaires about potentially sensitive information such as smoking, (2) 
potential breach of confidentiality and/or privacy, and (3) potential discomfort in quitting 
smoking (i.e., withdrawal symptoms, craving, etc.). 
 
 
Protection Against Risks: For the possibility of subjective discomfort from answering 
questions, any distress will be minimized by assuring participants that they can refuse to answer 
any question that they do not feel comfortable addressing and that they may withdraw from the 
study at any time without penalty.  To protect against breach of confidentiality, we will assign a 
numeric study ID to each participant, which will be the primary identifier by which this person’s 
progress through the trial will be reviewed.  The database linking names and study identification 
numbers will be kept in REDCap, where staff access to this information can be monitored and is 
password protected.  Only study staff will have access to this database.  All staff are or will be 
fully trained in relevant ethical principles and procedures, including confidentiality.  All 
assessment and treatment procedures will be closely supervised by the PI.  All data will be 
captured electronically.  For surveys and data entry by study staff, we will be using Partners 
implementation of REDCap (Research Electronic Data Capture) https://redcap.partners.org, 
which is a secure, web-based application designed to support data capture for research studies, 
and which is fully compliant with HIPAA-Security guidelines. The data generated by using our 
SiS app (i.e., app usage data) will be kept on secure servers behind a firewall within the MGB 
network.  The app will be hosted by secure ERIS/Partners servers.  All data collected through the 
app will be transmitted using Transport Layer Security (TLS) encryption to prevent 
eavesdropping and tampering information while it is in the transmission pipeline.  All data for all 
participants will be kept strictly confidential, except as mandated by law.  Regarding the 
potential discomfort in quitting smoking, participants will receive information about how to 
alleviate cravings as part of their study participation.  Given that study participants are nondaily 
smokers, who regularly abstain from smoking for several days, these discomforts are expected to 
be minimal. 
 
 
VIII. POTENTIAL BENEFITS 
 
Potential Benefits:  All participants will receive smoking cessation support as part of their 
study participation.  Consequently, participants in this study may quit smoking as a result of their 
participation, which would have a positive impact on their health.  Furthermore, study 

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participation will provide generalizable knowledge about the process of smoking cessation in 
nondaily smokers, which can be used to guide the development of further treatments to support 
smoking cessation in this growing population of smokers.  
 
 
IX. 
MONITORING AND QUALITY ASSURANCE 
 
 
Oversight of internal monitoring of the participants’ safety will be conducted by the PI, Dr. 
B. Hoeppner.  Dr. S. Hoeppner will also participate in the development and administration of the 
plan.  The PI will meet weekly with study staff on the project, at which time she will evaluate the 
progress of the trial, review data quality, recruitment, and study retention, and examine other 
factors that may affect outcome.  She will review the rates of adverse events to determine any 
changes in participant risk and will consult with Co-I Dr. S. Hoeppner and named consultants on 
the grant (Drs. Christopher Kahler (Brown University), Dr. Elyse Park (MGH), as necessary.  
(Consultants will not have access to identifiable information, nor data other than in summary 
form, as prepared by study staff.)  A brief report will be generated annually for the study record 
and forwarded to Massachusetts General Hospital’s Institutional Review Board.  The 
Investigators will be available to meet outside of the weekly meetings, if necessary, due to 
concerns regarding a particular participant or any problems that may arise for participants.  If 
necessary, they will make appropriate recommendations for changes in protocol.  Dr. B. 
Hoeppner will conduct daily oversight of participant safety.   
 
Any adverse events that are observed and/or reported will be immediately reported to Dr. 
B. Hoeppner.  Adverse event reporting will follow the MGB IRB’s guidelines for reporting 
unanticipated problems, including adverse events. Reports of unanticipated problems and 
adverse events outlined in this policy that occur during the conduct of the study, after study 
completion, or after subject withdrawal or completion will be reported by the principal 
investigator, Dr. B. Hoeppner within 5 working days/7 calendar days of the date she first 
becomes aware of the problem through Insight/eIRB. SAEs will also be reported in writing to the 
American Cancer Society.  Adverse events will be reported to the Massachusetts General 
Hospital IRB and the American Cancer Society annually.   
 
The PI will oversee the collection, maintenance, and analysis of all data.  During weekly 
meetings with study staff and co-investigator, the PI will review the accuracy and completeness 
of the study questionnaires, consent forms, and app data. The study procedures and plans will 
also be reviewed during these meetings to ensure that they remain in line with the approved 
protocol.
To protect the privacy of each participant, we will assign a numeric study ID to each 
participant, which will be the primary identifier by which this person’s progress through the trial 
will be reviewed.  The database linking names and study identification numbers will be 
maintained in REDCap, which is password protected, and where access is limited to study staff, 
and access to study information is traceable.  Only study staff will have access to this database.  
All staff are or will be fully trained in relevant ethical principles and procedures, including 
confidentiality.  All assessment and treatment procedures will be closely supervised by the PI.  
All of the data will be captured electronically.  For surveys and data entry by study staff, 
REDCap (Research Electronic Data Capture) will be used, which is a secure, web-based 
application designed to support data capture for research studies, and which is fully compliant 
with HIPAA-Security guidelines. The data generated by using our SiS app (i.e., app usage data) 

Partners Human Subjects Research Application Form 
  
Filename: Detailed Protocol 
 
 
  
22 
will be kept on secure servers behind a firewall within the Partners network.  The app will be 
hosted by secure ERIS/Partners servers.  All data collected through the app will be transmitted 
using Transport Layer Security (TLS) encryption to prevent eavesdropping and tampering 
information while it is in the transmission pipeline. 
 
 
X. 
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