Tobacco Cessation Treatment Preferences Among Veteran Smokers (CDA 17-005)
Phase: PHASE4
Conditions: Tobacco Use
Sponsor: VA Office of Research and Development

 Tobacco Cessation Treatment Preferences among Veteran Smokers 
NCT05277207 
07/25/2022 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 1 of 25 
 
 
Research Protocol: Tobacco Cessation Treatment Preferences among Veteran Smokers 
Principal Investigator: Sarah M. Wilson, Ph.D. (Clinician; Clinical Psychologist) 
PURPOSE 
 
The overall goal of this study is to understand and improve tobacco abstinence rates among Veteran 
smokers receiving specialty medical care. The specific aims of the study are to: 
AIM 1a: To qualitatively explore smoking cessation treatment preferences among Veteran smokers 
living with HIV, and to quantitatively evaluate perspectives on relapse-prevention messages among 
Veterans and smokers living with HIV. 
AIM 1b: To quantitatively evaluate satisfaction with relapse-prevention messages among a de-identified 
online sample of Veterans and smokers living with HIV, and general-population smokers. 
 
AIM 1c: To qualitatively explore smoking cessation treatment perspectives among ID health care staff 
who serve Veterans living with HIV. 
AIM 2: To quantitatively examine trends and determine health disparities by HIV status and 
demographic characteristics in use of smoking cessation aids among patients receiving VHA clinical care. 
 
AIM 3: To use a successive cohort design to develop a technology-assisted health (eHealth) smoking 
cessation intervention tailored for Veterans living with HIV. 
AIM 4: To conduct a randomized clinical trial of an eHealth smoking cessation intervention in medical 
specialty care clinics. 
BACKGROUND AND SIGNIFICANCE 
 
There are significant barriers to tobacco cessation treatment for patients and providers in specialty care 
clinical settings (Rojewski et al., 2019). Specialty providers in general cite several prominent barriers to 
delivering evidence-based tobacco cessation care, including insufficient time, lack of training in tobacco 
cessation, a perception of low motivation in their patients, and concerns about tobacco cessation 
discussions being a sensitive topic to discuss (Meijer et al., 2019). There is also great variability in the 
extent to which specialty providers believe that tobacco cessation care is consistent with their specific 
medical role (Meijer et al., 2019). Beyond difficulties accessing cessation services, a large proportion of 
patients who are prescribed NRT or initiate behavioral treatment do not achieve initial abstinence 
(Piper, Vasilenk, Cook, & Lanza, 2016). Given the reality of treatment non-response, it could be 
immensely effective to offer smoking cessation treatment plans that can be personalized to patients as 
they progress through treatment. Use of healthcare technology (i.e., telehealth, electronic health 
record, and computerized treatment algorithms based on patient data) to personalize treatment has the 
potential to increase patient engagement and proactively address treatment non-response. 
There is a lack of research on strategies to bring patient-centered care to tobacco cessation in specialty 
clinics. Given that tobacco cessation is most efficacious using an intensive, combined pharmacological- 
counseling approach, this new care model has the potential to increase long-term tobacco abstinence 
rates within specialty care clinical populations. This study will design and pilot test a novel model of care 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 2 of 25 
 
 
for tobacco cessation in two specialty care VA clinics, the Infectious Disease Clinic and the Cardiology 
Section. 
Rationale for Infectious Disease Clinic 
Among the over 1 million people living with HIV in the U.S., the smoking rate is two to three times 
higher than in the general U.S. population (Kariuki et al., 2016; Moscou-Jackson, Commodore-Mensah, 
Farley, & DiGiacomo, 2014). Similarly, people living with Hepatitis C smoke at three times the rate of 
those without Hepatitis C (Kim et al., 2018). Estimates from studies of VHA patients indicate that 63% of 
HIV-positive Veterans currently smoke cigarettes (Crothers et al., 2005) and 58% of Veterans living with 
Hepatitis C currently smoke cigarettes (Lynch et al., 2018). Tobacco use disproportionately increases 
health risks for people living with HIV and/or hepatitis C (Mallat et al., 2008; Pacek & Cioe, 2015). Given 
the health risks of smoking for individuals with chronic infectious diseases, it is imperative to address 
tobacco use for this population. 
 
Few smoking cessation interventions have been rigorously tested in people living with HIV or in people 
living with hepatitis C, and to date there have been no randomized controlled (RCT) trials of eHealth 
smoking cessation interventions for Veterans living with HIV and/or hepatitis C. One RCT tested the 
effectiveness of an NP-led counseling/NRT intervention, but tobacco abstinence at follow up was not 
biochemically verified (Reid et al., 2020). According to two recent systematic reviews, there are only five 
known large randomized smoking cessation trials among smokers with HIV (Moscou-Jackson et al., 
2014; Cooperman, 2016). One of the most promising smoking cessation interventions for people living 
with HIV to date consisted of telehealth CBT (Vidrine, Marks et al., 2012), but did not show long-term 
efficacy. Despite a nearly 80% session completion rate (Vidrine, Marks et al., 2012), at 6-month follow- 
up, the smoking abstinence rate was only 5% (Gritz et al., 2013). This high treatment adherence and low 
quit rate indicate that this population would likely benefit from an approach that is more accessible and 
more intensive. Thus, there is a need for novel, intensive eHealth approaches to smoking cessation in 
this population. 
 
Veterans living with HIV and/or Hepatitis C face numerous barriers to both treatment access and 
smoking abstinence. In groups who experience marginalization, common barriers to abstinence include 
lack of support for quitting from health care providers, high prevalence of smoking in the community, 
difficulties with stress management, and chronic pain (Twyman, Bonevski, Paul, & Bryant, 2014). For 
smokers with HIV specifically, barriers to abstinence include poor access to smoking cessation 
treatment, social networks that support smoking, alcohol and drug use, poor health, and mental health 
comorbidity (Karuiuki et al., 2016). Additionally, Veterans living with HIV have reported in qualitative 
interviews that referral to substance use treatment outside of the ID or primary care setting is 
burdensome (Minick et al., 2016). These patients further note that receiving HIV-specific care for 
addictions would help overcome this barrier (Minick et al., 2016). Individually tailored and HIV-targeted 
approaches to follow-up messaging have been recommended in the literature (Moscou-Jackson et al., 
2014; Pacek & Cioe, 2015), but are yet to be tested as part of a multi-component approach for smokers 
with chronic infectious disease. 
 
Rationale for Cardiology Section 
The causal link between tobacco use and cardiovascular disease is well-established (Burns, 2003). 
Nationally representative data indicates that while a recent myocardial infarction increases motivation 
to quit tobacco, it has no effect on likelihood of tobacco cessation (Gaalema et al., 2018). Although many 
cardiac patients are motivated to quit tobacco, meta-analytic data suggests that low-intensity 
counseling for hospitalized patients does not significantly increase the odds of tobacco cessation (Rigotti 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 3 of 25 
 
 
et al., 2012). Rather, intensive counseling in addition to adaptive pharmacotherapy are indicated to be 
most effective for tobacco cessation among cardiac patients (Benowitz & Prochaska, 2013). There is also 
evidence that intensive counseling for tobacco cessation among cardiac patients is both effective and 
cost-effective (Lapado et al., 2011). 
 
In the VA-BEST Trial, an implementation package designed to increase delivery of the 5 A’s tobacco 
cessation intervention for hospitalized Veterans (Katz et al., 2014). Although adherence to the 5 A’s 
increased, and more Veterans in the implementation arm received tobacco cessation care, there was no 
significant difference in likelihood of tobacco cessation. In this study, the authors concluded that “more 
intensive interventions are needed to promote long-term cessation” (Katz et al., 2014). 
 
Despite these calls for personalized, intensive counseling, there is a lack of intensive care models 
designed to optimize integration into existing clinical care models while promoting highly effective, 
intensive tobacco cessation interventions. 
 
AIM 1 METHODS – QUALITATIVE FORMATIVE ANALYSIS 
A qualitative patient sample (N = 20 or until saturation is reached) will include VHA patients with HIV 
who currently smoke or recently quit smoking. These patients will complete in-person qualitative 
interviews. A separate qualitative sample of ID health care staff who serve Veterans living with HIV will 
be collected (N = 15). 
 
In qualitative coding and analysis, two complementary methodologies will be used: conventional 
content analysis (Hsieh & Shannon, 2005) and inductive thematic analysis (Braun & Clarke, 2006). Using 
these two sequential, complementary approaches will maximize the validity of findings and minimize 
researcher bias (Miles, Huberman, & Saldaña, 2014). 
 
QUALITATIVE SAMPLE RECRUITMENT. Purposive sampling will be used to identify participants for the 
qualitative patient sample (N = 20). We anticipate that we will have to screen 30 participants to reach 20 
completers. The sample will include 20 HIV-positive VHA patients who either currently smoke ≥ seven 
cigarettes per week or are lifetime smokers (smoked ≥ 100 lifetime cigarettes) who quit within the past 
2 years. Veteran patients with an HIV diagnosis and documented tobacco use within the past 2 years will 
be identified from patient records of the Durham VAHCS via a data pull from VA’s Regional Data 
Warehouse. We will sample VHA patients with diverse backgrounds with respect to gender identity, 
sexual orientation, race/ethnicity, age, and medical/psychiatric comorbidities. Potential participants will 
be sent an introductory letter signed by the PI that describes the study and invites participation. 
Veterans who do not decline will be called to determine interest in the study and basic study eligibility. 
We will also recruit by presenting information about the study to clinicians throughout the medical 
center, who can then provide a referral to Dr. Wilson by adding her as a co-signer to CPRS notes. The 
third recruitment method will involve pre-screening potential participants who have clinic appointments 
in the Infectious Diseases clinic (8A). Study staff will monitor whether pre-screened patients have 
arrived in the clinic via VetLink. Study staff will indicate potential participants to 8A clinic staff, and clinic 
staff will inquire whether patients interested in hearing about an observational, single-visit research 
study about smoking. If a patient affirmatively indicates to their provider that they would like to hear 
about the study, they will be approached by a study staff member for screening and informed consent. 
The sample size has a high likelihood of reaching data saturation, which we define as the point in data 
collection when additional interviews do not result in new themes (Guest, Bunce, & Johnson, 2006). 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 4 of 25 
 
 
Guest et al. have experimentally demonstrated that after 12 interviews, there are diminishing returns on 
new themes; furthermore, at 18 interviews, 96% of themes are coded (Guest, Bunce, & Johnson, 2006). 
A convenience sample of 15 local ID health care staff will be recruited from the Durham VA Health Care 
System. A wide variety of staff will be contacted in order to gather diverse opinions and perspectives 
regarding smoking cessation care, including physicians, nurse practitioners, physician assistants, social 
workers, psychologists, nurses, and pharmacists. A number of recruitment methods will be used: 1) 
recruitment email sent to clinic staff, 2) recruitment brochures and flyers displayed in the staff room in 
the 8A clinic, 3) announcements made during the ID clinic staff meeting, and 4) clinic staff will be 
approached during the 8A ID clinic (after receiving an email) to ascertain whether they would be willing 
to participate. 
 
QUALITATIVE PROCEDURES. All interviews will be completed by either Dr. Wilson or trained study staff. 
For patients following informed consent, the interviewer will complete a 60-minute semi-structured 
interview with the participant. The format of the interview is funnel-shaped (Brinkman & Kvale, 2015), 
such that interview questions are initially broad and gradually narrow. An example of initial broad 
questions includes “For you personally, what would [be/have been] the best treatment to get to help 
you quit smoking?” Later interview questions will elicit feedback on specific examples of treatment 
options and relapse-prevention messages. For example, participants will be asked, “I’d like for you to tell 
me about the pros and cons of some different types of messages (I’ll give examples of each type).” The 
qualitative interviewers will take notes during each interview, and all interviews will be audio recorded 
and transcribed by members of the study team at Durham. Veteran participants will be compensated 
$30 for completing the interview. Based on the first interview transcript, a codebook will be developed 
under the following categories: areas for expansion/tailoring for Veteran smokers with HIV; new themes 
for relapse-prevention messages; and reactions to messages. Following creation of the codebook, the 
coding scheme will be updated as necessary following each of the first three participant interviews. 
Once the final codebook is established, interview transcripts will be dually coded by the PI and another 
study staff member, with coding discrepancies resolved by consensus. 
 
The medical records of participants will be reviewed to determine HIV disease status, use of smoking 
cessation medications and/or specialty clinic visits, comorbid diagnoses, and healthcare utilization 
patterns. 
 
For clinic staff, documentation of informed consent will be waived. No HIPAA authorization will be 
collected, as no protected health information is being collected by clinicians. At the beginning of each 
interview, the interviewer will capture consent on the audio record. Interviews will last approximately 
30 minutes, and will consist of questions derived from the Consolidated Framework for Implementation 
Research (CFIR; Damschroder et al., 2009). Questions will center on the following CFIR constructs: 
intervention characteristics, outer setting, and inner setting. Based on the first interview transcript, a 
codebook will be developed under the following categories: evidence strength and quality, relative 
advantage, adaptability, complexity, patient needs and resources, structural characteristics, tension for 
change, and compatibility. Once the final codebook is established, interview transcripts will be dually 
coded by the PI and another study staff member, with coding discrepancies resolved by consensus. 
 
QUANTITATIVE PROCEDURES. The study team will receive a dataset from Duke University Health 
System, where Dr. Wilson will collect data from Amazon Mechanical Turk (MTURK; 
https://www.mturk.com). Data from MTurk will be collected by the Duke team via an anonymous survey 
hosted by Duke Qualtrics. Data will be moved to VA from Duke in accordance via a VA-owned 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 5 of 25 
 
 
thumbdrive. All data will be de-identified, such that the study team will neither collect nor retain any PII 
or PHI. Data will include: HIV, smoking, and veteran status; demographic information (age; race; 
ethnicity; relationship status; sexual orientation; gender identity; U.S. state/territory; education; 
income; VHA patient status); and for HIV-positive participants only, age at HIV diagnosis, last CD4 count, 
and last viral load). Data will also include participants’ ratings of satisfaction with 148 relapse prevention 
text messages used in the SmokefreeVET library, as well as additional messages developed by the Duke 
research team. 
AIM 2 METHODS – QUANTITATIVE GAP IN VHA CARE ANALYSIS 
To identify potential treatment moderators and further understand current health services for smoking 
cessation among Veterans, it is essential to determine existing health disparities in cessation treatment 
among VHA patients with a variety of chronic care conditions. 
 
For this study aim, the data source will be a data request from Corporate Data Warehouse (CDW). We 
will create two complimentary datasets. First, we will investigate predictors of tobacco cessation 
pharmacotherapy fills among a cohort of Veteran tobacco users (FY 2018). Second, we will investigate 
overall rates of tobacco cessation pharmacotherapy fills over time (2011 to present). 
 
Pharmacotherapy Disparities among a Cohort of Tobacco Users 
Veteran health data, which may include PHI (e.g., dates of care and patient address), will be gathered 
starting from FY18 (pre-pandemic). After requesting data access via the Data Access Request Tracker 
(DART), Veterans who have positive tobacco use health factors will be identified from VA’s Regional 
and/or Corporate Data Warehouse. During the retrospective observation period, tobacco use will be 
determined based on a validated algorithm for identifying smoking status from the EMR (Calhoun et al., 
2017; McGinnis et al., 2011). Data will be extracted on tobacco use health factors, pharmacy records of 
medications dispensed, primary care/ID clinic outpatient healthcare encounters, pain intensity vital sign 
data, history of positive homelessness screening, history of positive food insecurity screening, patient 
demographics (race, ethnicity, service-connected disability, birth sex, gender identity, county, address), 
and diagnosis codes for comorbid disorders of interest (including but not limited to HIV, Hepatitis C 
coinfection, cardiovascular disease, cancer, and psychiatric disorders). Number of clinic visits attended in 
the 12-month period prior to the positive health factor will be collected as a control variable. Patient 
county and address will be used to extract data on neighborhood deprivation (Bhavsar et al., 2018) and 
economic inequality (GINI; Bee, 2012). 
 
For each the year12-month period following each patient’s positive tobacco use health factor, in which 
patients are determined to be smoking, three outcomes will be assessed: pharmacotherapy orders for 
any tobacco cessation pharmacotherapy (NRT, bupropion, or varenicline), pharmacotherapy orders for 
best-practice tobacco cessation pharmacotherapy (dual pharmacy dispensation of NRT [patch plus 
lozenge/gum/inhaler] or varenicline), and pharmacotherapy fills for any tobacco cessation 
pharmacotherapy, bupropion, or any smoking cessation pharmacotherapy (NRT, bupropion, or 
varenicline). Specifically, pharmacotherapy dispensation prescriptions will be coded dichotomously 
(yes/no) based on presence/absence of a pharmacy record within each 12-month observation period. 
Among those who received any pharmacotherapy prescriptions, pharmacotherapy fills will also be 
coded dichotomously. 
 
We will examine a range of variables to detect disparities in pharmacotherapy utilization prescriptions 
and fills. Demographic information will include age, race, and ethnicity, and service-connected disability. 
Social determinants of health will include food insecurity, homelessness, neighborhood deprivation, and 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 6 of 25 
 
 
neighborhood economic inequality. HIV, Hepatitis C, and psychiatric disorder will be based upon the 
ICD-9 and ICD-10 codes. Given previous work in the area of treatment access disparities, we will include 
the following psychiatric disorders as variables: psychotic disorder, bipolar disorder, PTSD, other 
anxiety/mood disorder, and any substance use disorder (all time-invariant, coded in year 1). Pain is 
coded 0-10 at each VHA healthcare visit as the fifth vital sign, and will be averaged over each 12-month 
monitoring period and dichotomized as severe (≥ 7) vs. mild/moderate (0-6) (Volkman et al., 2015). 
Pharmacotherapy Prescriptions Over Time 
Veteran health data, which may include PHI (e.g., dates of care), will be gathered starting from FY15 
through present. After requesting data access via the Data Access Request Tracker (DART), Veterans 
who have positive tobacco use health factors will be identified from VA’s Regional and/or Corporate 
Data Warehouse. 
 
The population of tobacco users will be determined by fiscal year using health factors. For each fiscal 
year, the pharmacotherapy prescription rate will be calculated for each type of pharmacotherapy by 
dividing the total number of Veterans receiving a prescription for tobacco cessation pharmacotherapy 
by the total number of Veterans who meet criteria for current tobacco use. 
 
We will examine trends over time, as well as systems-level determinants, including geographical region, 
facility-level proportion of Veteran patients who live rurally (extracted by year and by facility from the 
Rural Veterans Health Care Atlas), and state-level tobacco use prevalence. 
 
AIM 3 METHODS – SUCCESSIVE COHORT DESIGN FOR TREATMENT REFINEMENT 
We will use a successive cohort design to integrate and user-test the proposed intervention. The 
successive cohort design is an iterative process that is designed to refine behavioral treatments in the 
initial development stage (Epstein et al., 2007). This design involves multiple steps of development: 1) 
identifying theoretically-supported treatment models; 2) identifying key intervention elements; 3) 
developing preliminary intervention materials; and 4) revising the intervention iteratively based upon 
qualitative and quantitative data collected during successive patient cohorts. See below for proposed 
preliminary intervention methodology, as well as methodology for iteratively revising the intervention 
based upon patient qualitative feedback. 
 
SAMPLE RECRUITMENT 
A total of 3 cohorts of 5 patients each (N = 15) will complete the intervention and provide feedback after 
the treatment phase is complete. Participants will be recruited from the Durham VAHCS. Inclusion 
criteria are: VHA patient, HIV positive serostatus, currently smoking ≥ 7 cigarettes per week, and willing 
to complete study procedures. Exclusion criteria are: current hospitalization, acute risk for suicide 
documented in the medical record, or inability to complete study procedures. 
 
We will primarily recruit by presenting information about the study to clinicians in the Infectious Disease 
(ID) Clinic, who can then provide a referral to Dr. Wilson by adding her as a co-signer to CPRS notes. In 
order to facilitate provider referral, Veteran patients with an HIV diagnosis and documented tobacco use 
within the past 2 years who have clinic appointments in the Infectious Diseases clinic (8A) will be 
identified from patient records of the Durham VAHCS via chart review in the Computerized Patient 
Reporting System (CPRS). Study staff will indicate potential participants to 8A clinic staff, and clinic staff 
will inquire whether patients interested in hearing about the study. If a patient affirmatively indicates to 
their provider that they would like to hear about the study, they will be approached by a study staff 
member for screening and informed consent. If an insufficient number of patients are recruited in this 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 7 of 25 
 
 
manner, potential participants with an HIV diagnosis and documented tobacco use within the past 2 
years will be sent an introductory letter signed by the PI that describes the study and invites 
participation. Veterans who do not decline will be called to determine interest in the study and basic 
study eligibility. 
 
PROCEDURES 
Immediately following screening and informed consent (Session 0), patients will complete baseline 
measures and will begin the active treatment, Mesh (see below for details). Table 2 describes the 
measures that will be used in Aim 3 as well as their administration schedule. Whenever possible, we 
have selected Common Data Elements from the PhenX Toolkit (Hamilton et al., 2011; Version 13.3) in 
order to maximize the impact of the proposed study. Participants will be scheduled for counseling 
session 1 with a stop smoking interventionist within 7 days of study enrollment. 
Participants enrolled in the first cohort will be invited to utilize SmokefreeVET, a mobile text messaging 
service for military Veterans trying to quit smoking. SmokefreeVET was developed by a joint effort of the 
National Cancer Institute and the U.S. Department of Veterans Affairs. The program was created to 
provide 24/7 encouragement, advice, and tips to help smokers quit smoking and stay quit. It is a 6 to 8 
week program, depending on when you set your quit date. Users will receive 1-5 messages per day and 
can receive additional quit support at critical points in the quit process by using one of SmokefreeVET’s 
keywords (URGE, STRESS, or SMOKED). Participants can opt out of supportive text messaging at any time 
by sending the keyword STOP. Consistent with the structure of SmokefreeVET, participants interested in 
utilizing it will be assisted in signing up for the program within two weeks before their planned quit date. 
Participants will not be required to use the texting program. Participants of cohort 2 and 3 and in the 
RCT (Aim 4) will be invited to sign up for personalized text messaging support (see details of this 
treatment component below) using the VA Annie app. Annie is an automated, short message service 
(SMS) text message system designed to promote Veteran self-care. At the baseline session, Veterans will 
be asked to complete an agreement to use Annie, and will be walked through the process of registering 
a personal phone number and setting message preferences. The SMS feature of Annie will function on 
either a basic cell phone or a smartphone. During this time, Veterans will be informed that Annie is not 
designed for direct communication with a provider, and should a medical emergency arise to contact 
their provider or emergency services through traditional means. 
 
Treatment sessions with the interventionist and the qualitative interview will be audio recorded. These 
recordings will be used to develop a fidelity system as a secondary goal of the cohort design. 
 
Following completion of all intervention components (through end of treatment), each participant will 
complete a structured interview. Post-treatment interviews will include questions regarding strengths 
and weaknesses of the intervention as well as suggestions for ways to improve the overall treatment 
approach. See Data Analysis section for details on qualitative coding and analysis. 
 
Participants will also be followed up at 3-months and at 6-months to assess clinical outcomes and 
treatment acceptability. Study measures are shown in Table 1. Secondary smoking outcomes will include 
7- and 30-day point prevalence abstinence at each assessment. Abstinence will be verified by salivary 
cotinine assay (≤ 10 ng/ml), which improves self-report validity. When in-person visits are allowed post- 
COVID-19 pandemic, participants will also be asked to provide expired carbon monoxide (CO) breath 
readings at baseline, post-treatment, and 3- and 6-month follow-up. 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 8 of 25 
 
 
Following treatment completion for each cohort of n = 5 participants, qualitative data will be analyzed 
and based upon results, the intervention structure and content will be revised. Intervention content that 
may be subject to revision includes the computerized algorithms, CBT module content, and content and 
timing of SMS text messages. 
 
Table 1. Aim 3 Measures 
Measure 
No. 
Items 
Completed by 
Month 
Sessions 
0 
Quit 
Date 
3 
6 
BACKGROUND AND PROCESS VARIABLES 
1. 
Demographics 
32 
Self-report 
X 
- 
- 
- 
- 
2. 
Smoking history/current 
smoking 
6 
Self-report 
X 
- 
- 
- 
- 
3. 
HIV Disease Progression – 
CD4, Viral Load (EMR) 
- 
Self-report 
X 
- 
- 
- 
- 
4. 
Fagerstrom Test for 
Nicotine Dependence 
7 
Self-report 
X 
- 
- 
- 
- 
5. 
The Everyday 
Discrimination Scale 
10 
Self-report 
X 
- 
- 
- 
- 
6. 
Pain, Enjoyment of Life, 
and General Activity (PEG) 
Scale 
3 
Self-report 
X 
- 
X 
X 
- 
7. 
Smoking and Nicotine 
Knowledge 
14 
Self-report 
X 
- 
X 
- 
- 
8. 
Non-VA Treatment 
Utilization 
9 
Self-report 
X 
- 
X 
X 
- 
TREATMENT PERSONALIZATION MEASURES 
9. 
Smoking Cessation 
Motivation 
1 
Self-report 
X 
X 
X 
X 
- 
10. Smoking Cessation Self- 
Efficacy 
1 
Self-report 
X 
X 
X 
X 
- 
11. Stages of Change 
2 
Self-report 
X 
- 
X 
X 
- 
12. PTSD Checklist of DSM-5 
(PCL-5) 
20 
Self-report 
X 
- 
X 
X 
- 
13. Patient Health 
Questionnaire (PHQ-9) 
9 
Self-report 
X 
- 
X 
X 
- 
14. Alcohol Use Disorders 
Identification Test (AUDIT- 
C) 
3 
Self-report 
X 
- 
X 
X 
- 
15. Non-Cigarette Smoking 
Behavior 
6 
Self-report 
X 
- 
X 
X 
- 
16. Smoking Cessation 
Weight-Grain Concerns 
2 
Self-report 
X 
- 
- 
- 
- 
17. Smoking to Cope with Pain 
1 
Self-report 
X 
- 
- 
- 
- 
18. Exposure to Smoking Cues 
1 
Self-report 
X 
- 
- 
- 
- 
19. Pharmacotherapy 
Adherence – Visual Analog 
Scale (personalized to 
pharmacotherapy use) 
1-3 
Self-report 
- 
X 
X 
X 
- 
20. Tobacco Exposure 
Questionnaire 
6 
Self-report 
X 
- 
X 
X 
- 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 9 of 25 
 
 
 
CLINICAL MEASURES 
21. 7-day, 30-day Point 
Prevalence Abstinence 
2 
Research 
Interventionist 
X 
- 
X 
X 
- 
22. Prolonged Abstinence 
2 
Research 
Interventionist 
- 
- 
X 
X 
- 
23. Timeline Follow-back 
(cigarettes per day) 
1 
Research 
Interventionist 
- 
- 
X 
X 
- 
OUTCOME MEASURES 
24. Patient Recruitment 
- 
Research 
Interventionist 
X 
- 
- 
- 
- 
25. Treatment Retention 
- 
Research 
Interventionist 
- 
X 
X 
X 
- 
26. Withdrawals 
- 
Research 
Interventionist 
X 
X 
X 
X 
- 
27. Patient Satisfaction – 
Treatment Acceptability 
8 
Self-report 
- 
X 
X 
28. Therapist Satisfaction – 
Treatment Feasibility 
7 
Research 
Interventionist’s Self- 
report 
- 
X 
X 
29. Clinician Time 
4 
Research 
Interventionist 
X 
X 
- 
- 
- 
 
Mesh Treatment Components 
Treatment Personalization Algorithm. During session 1, the interventionist will complete a treatment 
personalization algorithm with the participant. This algorithm requires participant self-report data in 
addition to data from the electronic health record. Data inputs are shown in Table 2. 
 
Table 2. Treatment Personalization Algorithm Components 
ALGORITHM 
CONSTRUCT 
MEASURE 
Baseline CBT Algorithm 
Motivation; Self-efficacy, Social 
influences; Substances and 
Alcohol; Mental Health; Pain; 
Pharmacotherapy 
Smoking Cessation Motivation; 
Smoking Cessation Self-Efficacy; 
Stages of Change; PTSD 
Checklist of DSM-5 (PCL-5); 
Patient Health Questionnaire 
(PHQ-9); Alcohol Use Disorders 
Identification Test (AUDIT); 
Non-Cigarette Smoking 
Behavior; Smoking to Cope with 
Pain; Exposure to Smoking Cues 
Quit Week CBT Algorithm 
Relapse prevention; Weight 
gain; Self-efficacy; Motivation; 
Pharmacotherapy adherence; 
Relapse Situation Efficacy 
Questionnaire (RSEQ); Smoking 
Cessation Weight-Grain 
Concerns; Pharmacotherapy 
Adherence – Visual Analog Scale 
(personalized to 
pharmacotherapy use); 
If necessary: Smoking Cessation 
Motivation; Smoking Cessation 
Self-Efficacy; Stages of Change 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 10 of 25 
 
 
 
Post-Quit Relapse-Prevention 
Messaging Algorithm 
Preferences regarding message 
type: Inspirational; Medication 
reminders; Help with lapses; 
Trigger information; Behavioral 
skills 
Preference ratings 
Baseline Pharmacotherapy 
Willingness; Preference; 
Contraindications 
Self-report 
Quit Week Pharmacotherapy 
Status; Adherence; Willingness 
Self-report 
Quit Week Algorithm for 
Revising Pharmacotherapy 
Regimen (Initially Prescribed 
Dual-NRT) 
Willingness; Contraindications 
Self-report 
Quit Week Algorithm for 
Revising Pharmacotherapy 
Regimen (Initially Prescribed 
Varenicline) 
Willingness; Preference 
Self-report 
Quit Week Algorithm for 
Revising Pharmacotherapy 
Regimen (Initially Prescribed 
Bupropion) 
Willingness; Preference 
Self-report 
Quit Week Algorithm for 
Revising Pharmacotherapy 
Regimen (Initially Prescribed 
Single-Formulation NRT) 
Willingness; Preference; 
Contraindications 
Self-report 
 
Personalized Smoking Cessation Facilitation Meetings. Mesh facilitators will meet with participants 
between 5 to 7 sessions. For completion of stop smoking facilitation sessions, participants will be 
offered the choice of whether to complete sessions using a personal telephone, a personal digital device 
(i.e., tablet, laptop, or desktop computer with webcam), or a VA-issued digital device (i.e., 4G-enabled 
tablet with webcam). For those who request a VA-issued personal digital device, a consult will be placed 
to Prosthetics Service to issue the Veteran a 4G-enabled tablet in order to complete subsequent 
counseling sessions via VA Video Connect. 
 
Core CBT modules include: identifying reasons for quitting, setting a quit date, breathing relaxation 
technique, identifying smoking triggers, identifying social support, and education about relapse 
prevention. We will also use the Session 1 treatment personalization algorithm to individually tailor 
counseling to provide an adaptable selection of discrete counseling modules in addition to core modules 
that all participants will receive. CBT treatment personalization algorithms are based upon the following 
assessments: self-efficacy, motivation for quitting, depression, PTSD, alcohol use, comorbid non- 
cigarette smoking, tobacco exposure, smoking to cope with pain, adherence to pharmacotherapy, and 
concerns about weight gain. Two to three of these 5- to 15-minute modules will be included in each 
session, and modules will focus on building each participant’s skills that are needed to achieve cessation 
and long-term abstinence. Optional modules will address low motivation to quit, low self-efficacy for 
quitting and relapse prevention, comorbid psychiatric concerns, alcohol/drug use, tobacco exposure and 
poly-tobacco use, pain management, pharmacotherapy adherence, and healthy eating/exercise. Each 
session will last 30-60 minutes. 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 11 of 25 
 
 
At Session 3 (1 week post-quit), the participant will be asked several treatment personalization 
questions (see Table 1). These responses will be entered into the treatment personalization algorithm to 
determine additional post-quit modules depending on the following: self-reported quit status at Session 
3 (defined as complete abstinence since most recent quit date), self-efficacy, motivation, 
pharmacotherapy adherence, and barriers to abstinence. Additional modules to be added to counseling 
include: relapse prevention, motivational interviewing, decisional balance, pharmacotherapy adherence 
(or pharmacotherapy motivational interviewing), and review of barriers and protective factors. 
Personalized Smoking Cessation Pharmacotherapy. Participant pharmacotherapy recommendations will 
be based upon the study treatment personalization algorithm and will be sent to the participant’s clinic 
team. All pharmacotherapy prescriptions will be managed as part of routine clinical care by the 
participant’s VA healthcare providers, who may choose to follow study pharmacotherapy 
recommendations at their discretion. 
 
At the baseline session, a study staff member will ask questions regarding tobacco cessation 
pharmacotherapy preferences and contraindications directly to the study participant. The 
interventionist will also review the participant’s electronic medical record to note any additional 
potential contraindications to pharmacotherapy. Pharmacologic recommendations will be based upon a 
recent meta-analysis of smoking cessation pharmacotherapy as well as VA Pharmacy Benefits 
Management Services guidelines (Cahill et al., 2013). Similar to Cropsey et al.’s (2015) algorithm 
methodology, participants will be followed 1 week post-quit to assess abstinence and pharmacotherapy 
adherence. If they are using tobacco and have poor adherence (<70% adherence) and are willing to 
increase pharmacotherapy use, then adherence will be more heavily targeted in CBT. If, however, they 
are using tobacco in the context of adherent use, the algorithm will suggest an alternative medication 
regimen if possible (e.g., switching from single-formulation NRT to dual-NRT). 
 
Personalized Annie Messaging Support. If the participant has a working cell phone and is willing to 
receive SMS text messages, supportive SMS text messages will be sent to the participant starting after 
Session 1 and extending through 6 months post-quit. Individual tailoring of follow-up messages will be 
based upon the post-quit patient mHealth survey, which will measure the following: desired frequency 
of messages (1-3 per day); specific abstinence-related concerns (i.e., weight gain, difficulty coping with 
stress); preferred types of messages (skills-focused, health informational, encouragement); and 
personalized reasons for staying quit. Participants can opt out of follow-up messaging at any point. All 
messages will be sent via the VA Annie texting capability. As stated above, Annie is a standard VA SMS 
text message capability designed to promote Veteran self-care. 
 
AIM 4 – PILOT FEASIBILITY RANDOMIZED CONTROL TRIAL (RCT) 
 
The proposed RCT is a two-arm experimental design to demonstrate the feasibility of a larger trial and 
the acceptability of the intervention design. Participants (N = 30) will be stratified by clinic and 
randomized to either the active treatment or to standard of care VA Quitline (telehealth intervention 
including 5 sessions of CBT) plus SmokefreeVET (text-messaging intervention). The comparison group 
was selected in order to assess the feasibility of recruitment, retention, and randomization procedures. 
We will assess acceptability of the active treatment among patients, providers, and key VA stakeholders. 
 
SAMPLE RECRUITMENT 
A total of N = 30 will be enrolled in the study. Participants will be recruited from the Durham VAHCS. 
Inclusion criteria are: Durham VA patient, willing to complete study procedures, appointment in Durham 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 12 of 25 
 
 
VA Infectious Disease (ID) Clinic or Durham VA Cardiology Section within the past 12 months, and 
currently smoking ≥ 7 times per week (cigarettes, cigars, cigarillos, hookah, etc.) and/or using ≥ 1 can of 
smokeless tobacco per week. Exclusion criteria are: participation in Aim 3 (already received the 
intervention), current hospitalization (recent hospitalization is acceptable), currently not using 
combustible or smokeless tobacco (vaping only), acute risk for suicide documented in the medical 
record, or inability to complete study procedures. 
We will recruit in several different ways. First, clinicians in the ID Clinic and Cardiology Section can 
provide a direct study referral by adding the PI and/or Project Coordinator as a co-signer to a CPRS 
notes. Second, study information sheets will be made available in ID Clinic and Cardiology Service clinical 
spaces for potential participants to peruse and self-refer to the study. Third, potential participants with 
documented tobacco use within the past 2 years who have been seen within the past 2 years in the ID 
Clinic or Cardiology Service will be sent an introductory letter signed by the PI that describes the study 
and invites participation. Veterans who do not decline will be called to determine interest in the study 
and basic study eligibility. 
 
PROCEDURES 
Screening 
Veterans who are interested in study participation will be screened via telephone or in clinic for study 
inclusion criteria. Potential participants will be asked questions regarding current weekly tobacco use 
and current hospitalization at any location, and CPRS documentation will be screened to ensure the 
Veteran is a patient in one or both of the identified clinics, is not currently hospitalized at Durham VA, 
and does not have a high-risk suicide flag in their chart. Potential participants will then complete 
informed consent with a trained study staff member. Where possible, we will utilize DocuSign to obtain 
informed consent and HIPAA authorization. Immediately following screening and informed consent 
(Session 0), patients will complete baseline measures and randomization. 
 
Communication with Enrolled Participants 
Communication with enrolled participants will take place via mail, telephone, VA Video Connect, 
another approved telehealth platform (http://vaww.telehealth.va.gov/technology/covid19-tech.asp), or 
Azure RMS (in accordance with guidance issued in VA document “Use of Protected Health Information in 
Microsoft Office Applications”). 
 
Measures 
Table 3 describes the measures that will be used in Aim 4 as well as their administration schedule. 
Whenever possible, we have selected Common Data Elements from the PhenX Toolkit (Hamilton et al., 
2011; Version 13.3) in order to maximize the impact of the proposed study. 
 
Table 3. Aim 4 RCT Measures 
Measure 
Completed by 
Time Point 
Baseline 
3- 
Month 
Follow 
Up 
6- 
Month 
Follow 
Up 
BACKGROUND AND PROCESS VARIABLES 
1. 
Demographics 
Self-report 
X 
- 
- 
2. 
Tobacco use history/current 
tobacco use 
Self-report 
X 
- 
- 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 13 of 25 
 
 
 
3. 
Fagerstrom Test for Nicotine 
Dependence (Cigarette and ST 
Versions) 
Self-report 
X 
- 
- 
4. 
The Everyday Discrimination Scale 
Self-report 
X 
- 
- 
5. 
Pain, Enjoyment of Life, and 
General Activity (PEG) Scale 
Self-report 
X 
X 
X 
6. 
Smoking and Nicotine Knowledge 
Self-report 
X 
X 
- 
7. 
Non-VA Treatment Utilization 
Self-report 
X 
X 
X 
8. 
Stages of Change 
Self-report 
X 
X 
X 
9. 
Smoking Cessation Motivation* 
Self-report 
X 
X 
X 
10. Smoking Cessation Self-Efficacy* 
Self-report 
X 
X 
X 
11. PTSD Checklist of DSM-5 (PCL-5)* 
Self-report 
X 
- 
- 
12. Patient Health Questionnaire (PHQ- 
9)* 
Self-report 
X 
- 
- 
13. Alcohol Use Disorders Identification 
Test (AUDIT-C)* 
Self-report 
X 
X 
X 
14. Non-Tobacco Smoking Behavior* 
Self-report 
X 
X 
X 
15. Smoking Cessation Weight-Grain 
Concerns* 
Self-report 
X 
- 
- 
16. Smoking to Cope with Pain* 
Self-report 
X 
- 
- 
17. Exposure to Smoking Cues* 
Self-report 
X 
- 
- 
18. Pharmacotherapy Adherence – 
Visual Analog Scale* 
Self-report 
- 
X 
X 
CLINICAL MEASURES 
19. Tobacco Exposure Questionnaire 
Self-report 
X 
X 
X 
20. Timeline Follow-back (TLFB; 
tobacco used per day, tobacco 
cessation medication used per day, 
quit attempts, control group 
treatment sessions) 
Study Staff Member 
- 
X 
X 
21. Abstinence Outcomes (7-day, 30- 
day, Prolonged) 
Study Staff Member, 
based on TLFB 
- 
X 
X 
22. Exhaled Carbon Monoxide (CO) 
Biochemical Measure 
- 
X 
X 
23. Salivary Cotinine 
Biochemical Measure 
- 
X 
X 
OUTCOME MEASURES 
24. Patient Recruitment 
Study Staff Member 
X 
- 
- 
25. Treatment Retention 
Study Staff Member 
- 
X 
X 
26. Withdrawals 
Study Staff Member 
X 
X 
X 
27. Patient Satisfaction – Treatment 
Acceptability 
Self-report 
- 
X 
X 
28. Therapist Satisfaction – Treatment 
Feasibility 
Research 
Interventionist 
Immediate Post-Treatment 
29. Clinician Time 
Research 
Interventionist 
During Treatment Period 
CPRS DATA EXTRACTION 
30. HIV Disease Progression – CD4, 
Viral Load 
Study Staff Member 
X 
- 
- 
31. Tobacco Cessation Medication 
Prescriptions and Fills 
Study Staff Member 
- 
X 
X 
* Measure also used for treatment personalization in Mesh intervention 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 14 of 25 
 
 
Randomization 
Immediately following completion of baseline measures, participants will be randomized 1:1 to either 
the active treatment (Mesh) or to a best practice comparison condition (described below). 
Randomization will be concealed, stratified, and blocked. Given the two separate recruitment settings, 
randomization will be stratified by clinical setting (ID clinic and cardiology). For participants who are 
involved in both clinical settings, stratification arm will be decided by a virtual coin toss 
(https://cgi.cs.duke.edu/~des/vct/vct.cgi). In order to ensure consistent referrals for sessions with 
intervention facilitators, randomization will be blocked for every five participants recruited. Allocation to 
study condition will be computer-generated in random blocks of four and six, with the allocation block 
sizes and sequence only accessible by a non-investigator study staff member who is not involved in 
study recruitment or treatment delivery. 
Intervention Arms 
Participants randomized to the Mesh treatment arm will be scheduled for a first session with a quit 
facilitator within 10 business days of randomization. See section above “Mesh Treatment Components” 
for a description of the intervention arm, which includes personalized recommendations for tobacco 
cessation pharmacotherapy, 5 to 7 sessions, and Annie messaging. Participants will be asked to select 
their preferred frequency of Annie messaging: standard (about 3 times per day) or low (about 1 time per 
day). Study therapists will be asked to audio record a selection of sessions. A random sample of sessions 
will be selected for fidelity rating by a PhD-level study staff member. 
 
Participants randomized to the best practice comparison condition arm will receive best-practice VA 
telehealth. This includes information on medications, referral to VA quitline, and referral for tobacco 
cessation text messaging. Study staff will provide the participant with a VA information sheet on tobacco 
cessation medications (copied directly from https://www.mentalhealth.va.gov/quit-tobacco/how-to- 
quit.asp). Participants will also be offered a warm handoff to Quit Vet, VA’s Quitline 1-855-QUIT-VET (1- 
855-784-8838). If they are not interested in a warm handoff during the baseline session, they will be 
provided with an information sheet about Quit Vet and encouraged to call as soon as possible to initiate 
counseling. Participants will be asked to sign up for SmokefreeVET. Participants will be informed that 
standard text messaging rates apply for this texting program. Veterans will not be required to 
participate in SmokefreeVET. Participants can also opt out of text messaging at any time by sending the 
keyword STOP. Participants will be signed up for SmokefreeVET during the initial visit either by visiting 
https://veterans.smokefree.gov/tools-tips-vet/smokefreevet or by texting VET to 47848 on the 
participant’s mobile phone. If the Veteran declines at the baseline session to be signed up for 
SmokefreeVET, they will be provided with an information sheet on how to sign up. 
Participant Compensation 
Participants will receive $50 for the baseline visit. For the 3- and 6-month follow-up visits, participants 
will receive $100 for coming in for CO and cotinine sample. If a participant is not able to attend the 
follow-up in person, they will receive $50 for a telephone-only follow-up and mailed saliva sample (with 
payment contingent upon receiving saliva sample via mail). 
COVID-19 Temporary Study Procedures 
Participants in the study will be asked to follow medical center procedures for mitigation of COVID-19 
risk (e.g., mask-wearing, physical distancing). When possible, participants will be asked to complete 
study procedures via phone, VA Video Connect, another approved telehealth platform 
(http://vaww.telehealth.va.gov/technology/covid19-tech.asp), or via Azure RMS (in accordance with 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 15 of 25 
 
 
guidance issued in VA document “Use of Protected Health Information in Microsoft Office 
Applications”). 
 
 
PRIVACY, CONFIDENTIALITY, AND INFORMATION SECURITY 
 
1. Lists of Data Reviewed and/or Collected for Screening/Recruitment and Conduction of Study: 
The Personal Health Information that will be obtained, used, and/or shared for this study includes: 
Identifier(s) 
Source(s) of Health Information 
 Names 
 Medical history & physical exam 
information 
 All geographic subdivisions smaller than a State, 
including street address, city, county, precinct, and 
zip code. Describe: Participants’ addresses will be 
collected during the study in order to pay them for 
participation. 
 Photographs, videotapes, audiotapes, or 
digital or other images 
 All elements of dates (except year) for dates 
directly related to an individual, including birth 
date, admission date, discharge date, visit or 
treatment dates, etc.; and all ages over 89, 
Describe: Date of participation will be collected. In 
addition, treatment records, laboratory results, etc. 
will be collected. 
 Biologic specimens (e.g., blood, tissue, urine, 
saliva). Describe: Collection of saliva samples 
for salivary assay. 
 Telephone numbers 
 Progress notes 
Fax numbers 
 Diagnostic / Laboratory test results 
 Electronic mail addresses 
Operative reports 
 Social Security Numbers 
Imaging (x-ray, CT, MRI, etc.) 
 Medical record numbers 
Discharge summaries 
Health plan beneficiary numbers 
 Survey / Questionnaire responses 
 Account numbers 
Billing records 
Certificate and/or license numbers 
 HIV testing or infection records 
Vehicle identifiers and serial numbers, including 
license plate numbers 
Sickle cell anemia information 
Device identifiers and serial numbers 
 Alcoholism or alcohol use information 
Web Universal Resource Locators (URLs) 
 Drug abuse information 
Internet Protocol (IP) address numbers 
Mental health (not psychotherapy) notes 
Biometric identifiers, including finger & voice 
prints 
Psychological test results 
Full-face photographic images and any 
comparable images 
Genetic testing 
 Any other unique identifying number, linked 
study ID, characteristic, or code, describe: study ID 
number 
Other, describe: 
 
 
2. Data and/or Specimen Acquisition: 
Data for this study will be collected through (check all that apply): 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 16 of 25 
 
 
 Prospective data and/or specimen collection obtained from participants. Aim 1 patient data will be 
obtained through a 60-minute, semi-structured interview. Aim 1 VA staff data will be obtained through a 
30-minute, structured interview. No data collection is involved in Aim 2. 
 Retrospective data collection and/or specimens obtained from medical chart review/data access. 
Describe how data will be obtained (e.g., fileman, CDW, etc.): 
Aim 1: In accordance with a Waiver or Alteration of HIPAA Authorization, names, addresses, telephone 
numbers, social security numbers, and diagnostic information of potential participants will be obtained 
from the VA’s Regional Data Warehouse. For study Aim 2, health data will be obtained from VA’s 
Corporate Data Warehouse. 
 Retrospective data collection and/or specimens obtained from an IRB-approved data and/or 
specimen repository. Indicate the repository source including name, VA location, and IRB number: Aim 
1b: Survey data from Duke University Health System will be shared with the VA team via a VA-owned 
thumbdrive. 
Note: for data and/or specimens obtained from a VA approved data repository, a Data Use Agreement 
(DUA) must be executed prior to obtaining data and/or specimens. See VHA Handbook 1200.12 for 
further information. 
3. Level of Data: 
The following level(s) of data will be acquired/maintained for this study (check all that apply): 
 Identified (e.g., names, addresses or other identifiers included) 
 Coded (direct and/or all identifiers removed, but study code/ID included) 
 De-Identified (all HIPAA 18 and study ID/code removed): 
 Verified Statistically 
OR 
 Verified by Absence or Removal of HIPAA 18 and study ID 
 Limited Data Set 
 Other: Describe: 
 
4. Location of Data and/or Specimens, and Data Retention Plan: 
A. Data and/or Specimen Location: 
Aims 1, 3, and 4: 
Data will be stored electronically in \\vhadurhsmcifs01.v06.med.va.gov\Mesh. For Aim 1, data that will 
be stored electronically include name, address, phone number, social security number, amount of study 
payment earned, and date of visits (in Study Logbooks location). The study logbook will contain the key 
connecting PHI and the study identification number. Paper records of data include study consent form 
and HIPAA authorization (identified) and interview notes (coded); these will be stored in a locked filing 
cabinet in a locked office suite in Bldg. 1, Room C10006; Building 8, Room 206 of the main Durham VA 
Health Care System campus; or in Legacy Tower Suite 600 (HSR&D). Audio recordings of qualitative 
interviews and to establish interrater reliability will be captured using VA’s WebEx. Recordings will be 
moved from WebEx to the “Study Logbooks” location listed above. For long term storage, audio 
recordings may be moved to an encrypted DVD that is password-protected. Any encrypted DVDs will be 
stored in a locked filing cabinet in a locked office. Transcriptions from the study interviews will be 
stored electronically at the Study Logbooks location listed above. Data received from Duke University 
Health System will be moved to \\vhadurhsmcifs01.v06.med.va.gov\Mesh for storage and analysis. 
 
Aim 2: 
Data collected via a DART pull will be stored locally at \\v06.med.va.gov\DUR\Mesh. 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 17 of 25 
 
 
 Data will be also be placed at the VA Informatics and Computing Interface (VINCI; 
http://vaww.vinci.med.va.gov/vincicentral/VINCIWorkspace.aspx). The VA Informatics and Computing 
Infrastructure is a partnership between the VA Office of Information Technology and the Veterans’ 
Health Administration Office of Research and Development. Researchers and operations staff can use 
VINCI to access data and statistical analysis tools in a virtual working environment through a certified 
VHA network computer using the VA Intranet or Virtual Private Network (VPN). 
B. Data Retention Plan 
 Research records will be maintained and destroyed according to the National Archives and Records 
Administration, Records Schedule Number: DAA-0015-2015-0004. Records destruction, when 
authorized, will be accomplished using the then current requirements for the secure disposal of paper 
and electronic records. Currently, destruction of research records (see DAA-0015-2015-0004, section 
7.6 “Research Investigator Files” for materials included in research records) is scheduled for 6 years after 
the cut-off (the cut-off is the completion of the research project) and may be retained longer if required 
by other federal agencies. Records will not be destroyed without pre-notification to the facility records 
manager. 
 Other data retention plan, describe: 
5. 
Data Access and Data Recipients: 
Aims 1, 3, and 4: 
Only members of our DVAMC research team will have access to identifiers and coded data. All VA 
research personnel who have access to VHA records are instructed, in accordance with VA policy, on the 
requirements of Federal privacy and information laws and regulations, VA regulations and policies, and 
VHA policy. All study personnel who are VA employees working within the VA system have fulfilled all 
required HIPAA and other VA security and privacy policy training requirements and have agreed to 
follow guidelines pertaining to the protection of patient data. All research staff sign VA Rules of 
Behavior, and all study staff are up-to-date with VHA Privacy Policy Training and the VA Office of Cyber 
and Information Security Awareness Training Course. The data security and privacy procedures 
summarized in that course include logging off or locking the computer when walking away from it; no 
sharing of access codes, verify codes or passwords; not allowing anyone else to use the computer under 
one’s password; and disposing of sensitive information using VA-approved methods (e.g., shredder 
bins). Access to study data will be removed for all study personnel when they are no longer part of the 
research team. 
 
Aim 2: 
Only Dr. Wilson (PI) and study statistician will have access to identifiers and coded data. All VA research 
personnel who have access to VHA records are instructed, in accordance with VA policy, on the 
requirements of Federal privacy and information laws and regulations, VA regulations and policies, and 
VHA policy. All study personnel who are VA employees working within the VA system have fulfilled all 
required HIPAA and other VA security and privacy policy training requirements and have agreed to 
follow guidelines pertaining to the protection of patient data. All research staff sign VA Rules of 
Behavior, and all study staff are up-to-date with VHA Privacy Policy Training and the VA Office of Cyber 
and Information Security Awareness Training Course. The data security and privacy procedures 
summarized in that course include logging off or locking the computer when walking away from it; no 
sharing of access codes, verify codes or passwords; not allowing anyone else to use the computer under 
one’s password; and disposing of sensitive information using VA-approved methods (e.g., shredder 
bins). Access to study data will be removed for all study personnel when they are no longer part of the 
research team. 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 18 of 25 
 
 
 
6. Data and/or Specimen Transportation and/or Transmission for all data and/or specimens involved 
in the study: 
I. 
 
 Data and/or specimens will not be transported or transmitted outside of Durham VAMC 
environment. Please note: Data will not be transported outside the Durham VA environment. 
Specimens will, see item IIIb below. 
II. 
 
 Data and/or specimens will be transported BETWEEN sites that are under the auspices of 
the Durham VA Medical Center. Please describe what is being transported, who will be 
responsible for transporting (study titles rather than names) how it will be secured during 
transport, and whether additional stops will be made while transporting the data/specimens. 
Study mail and correspondence will either be stored in Legacy Tower, Suite 600 (HSR&D space) 
or will be moved from HSR&D space at Legacy Tower to DVAMC, Building 1, C10006. The study 
coordinator will be responsible for moving these documents. Data will be secured in a briefcase 
or lock bag with the notice below attached. No stops will be made while transporting the 
documents. 
 
a.  
 Local DVAMC memorandum “Authorization to Use, Process, Store, or Transmit VA 
Sensitive Information Outside VA Owned or Managed Facilities” has been pre-filled out for 
each study team member who may transport the data and/or specimens off-site. This 
(these) forms are included with the IRB materials. 
b.  
 Containers (e.g., briefcase, bin) are labeled with the following notice (label placed on 
the outside of container): 
NOTICE!!! 
Access to these records is limited to: AUTHORIZED PERSONS ONLY. 
Information may not be disclosed from this file unless permitted by all applicable legal 
authorities, which may include the Privacy Act; 38 U.S.C. §§ 5701, 5705, 7332; the Health 
Insurance Portability and Accountability Act; and regulations implementing those provisions, at 
38 C.F.R. §§ 1.460 – 1.599 and 45 C.F.R. Parts 160 and 164. Anyone who discloses information in 
violation of the above provisions may subject to civil and criminal penalties. 
 
III. 
 Data and/or specimens will be transmitted to other VA sites using the following method(s): 
A. Data 
 Data are de-identified and thus will be sent via unencrypted e-mail or unencrypted disk 
(encryption is optional). 
 Data are coded or contain identifiers and thus will be sent 
 Other, describe: 
B. Specimens 
 Specimens are de-identified and thus will be sent via standard carrier (tracking is 
optional). 
 Specimens are coded or contain identifiers and thus will be sent via VA-authorized 
carrier with tracking. 
 Other, describe: 
IV. 
 
 Data and/or specimens will be transported to non-VA/VHA sites (e.g., academic affiliates, 
laboratories, etc.) using the following method(s): 
A. Data 
 Data are de-identified and thus will be sent via unencrypted e-mail or unencrypted CD. 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 19 of 25 
 
 
 Data are coded or contain identifiers and thus will be sent via <chose method of transfer 
such as FIPS 140-2 encrypted CD or FIPS 140-2 encrypted hard drive/flash drive> using VA— 
approved carrier with tracking. 
 Data are coded or identified and will be uploaded to sponsor website using electronic 
case report form (eCRF) <insert information including sponsor name and URL and the 
encryption the site uses.> 
 Other, describe: 
B. Specimens 
 Specimens are de-identified and thus will be sent via standard carrier (tracking is 
optional) or will be hand-delivered by research study personnel. Specify method of delivery: 
 
 Specimens are coded and thus will be sent via VA-approved carrier with tracking or will 
be hand-delivered by research study personnel. Specify method of delivery: 
 
In accordance with the HIPAA and the Privacy Act, for any coded or identifiable data or specimens 
released from the Durham VAMC (with the exception of Limited Data Sets), an Accounting of Disclosure 
(AOD) will be maintained (e.g., in a database or spreadsheet) that includes the participant’s name, date 
of the disclosure, description of the nature of the Individually Identifiable Information (III) disclosed, 
purpose of each disclosure, and the name and address of the person/agency to whom the disclosure 
was made. 
 
7. Risk Mitigation Strategies: 
 Data are fully de-identified (stripped of HIPAA 18 and study ID/code) before being shared outside of 
Durham VAMC. 
 Specimens are fully de-identified (stripped of HIPAA 18 and study ID/code before being shared 
outside of Durham VAMC. 
 Direct identifiers will be maintained separately from data and or specimens by using a code to 
“identify” subjects. In a separate database (i.e., a “linking” or “cross-walk” database) this code will be 
linked to identifying subject information. 
 Other, specify: 
8. Suspected Loss of VA Information: 
Should any incident such as theft or loss of data, unauthorized access of sensitive data or non- 
compliance with security controls occur it will be immediately reported according to VA policy. All 
incidents regarding information security/privacy incidents will be reported to the ISO and PO within 1 
hour of acknowledgement of issue and done so using the VHADUR Research Events Report e-mail group 
(VHADURResearchEventReport@va.gov). 
 
9. Reporting of Results: 
 Reporting of results, such as in scientific papers and presentations, will never identify individual 
subjects. Data will be presented in aggregate and individual-level data will not be published. 
 Other results reporting plan, describe: 
 
10. Future Use of Data: 
 Data will be retained for future use. This is described elsewhere in the protocol and is noted in the 
HIPAA authorization. 
 Future Use of data is optional (i.e., not required by the research subject). 
 Future Use of data is required for participation in the study. 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 20 of 25 
 
 
 No future use of data is currently planned. 
11. Use of Mail Merge Technology 
 Mail merge programs will be used to generate letters and/or address labels for mailings to potential 
or already enrolled research subjects. The study team is aware that to reduce risk of mail merge related 
privacy incidents, use of mail merge programs requires a 25% accuracy check to verify that (potential) 
research subject name and mailing address are properly “matched”. If discrepancies are found, a 100% 
accuracy check is required before letters may be mailed. 
 
DATA ANALYSES 
Aim 1: 
Sequential Exploratory Mixed Analysis. Qualitative data collection will constitute the initial idea- 
generation step in treatment development, and thus findings will be used to do the following: 1) 
conceptualize ways to adapt intervention content to increase its specificity and appropriateness for a 
population of Veteran smokers living with HIV; 2) identify additional CBT content needed to increase 
relevance to the population; and 3) generate relapse-prevention message content specifically needed 
for this population. After qualitative data collection and analysis are completed, appropriate updates 
will be made to the CBT treatment manual and relapse-prevention message library. 
Qualitative Analysis. Data will be analyzed in two phases – an initial phase of conventional content 
analysis followed by an inductive, thematic approach to identify patterns in the data. Coded data will be 
analyzed for emergent patterns and themes that may adhere to or contradict the investigators’ 
expectations. Data management and coding will use NVivo8 software on VA VINCI website, or ATLAS.ti 
on a VA secured computer. 
 
Quantitative Analysis. Regarding quantitative data received from Duke, data from veterans who smoke, 
people living with HIV who smoke, and members of the general public who smoke will be analyzed 
separately. First, data will be cleaned. Participants will be excluded from analysis if they meet any of the 
following criteria: greater than 2 endorsed bogus items, self-reported “very little” or “no” effort or 
attention, or a “no” response to the question “In your honest opinion, should we use your data in our 
analyses in this study?” After data cleaning, the following descriptive statistics will be calculated for 
satisfaction ratings on each SmokefreeVET message: range, mean, and standard deviation. Items falling 
below an 8 on mean satisfaction will be reviewed by the study staff in the context of qualitative findings 
to make final decisions regarding their inclusion in the final relapse-prevention message library. 
 
Aim 2: 
In order to examine disparities in healthcare delivery of smoking cessation prescriptions, we will use a 
longitudinal retrospective design. Generalized linear mixed modeling (GLMM) with a logit link and 
binomial variance will be used to determine differences by variables of interest in likelihood of 
pharmacotherapy dispensation following positive tobacco health factors screening. GLMMs 
appropriately accommodate multi-level data structures with unbalanced design for analyzing repeated 
observations across multiple individuals nested within clinics. Clinic- and person-level random effects 
will be included in statistical models to account for correlation among patients within the same clinic 
and repeated measurements on the same individual over time, respectively. Covariates will be assessed 
for collinearity before entering them simultaneously into the GLMM. 
 
Aim 3: 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 21 of 25 
 
 
We will use rapid qualitative analytic methods to analyze participant feedback from post-treatment 
qualitative interviews (Watkins, 2017). For each study cohort of 5 participants, study staff will complete 
written summaries of interview audio recordings, and will enter these summaries into a study database. 
Interview summaries across participants will be displayed by their structural content (i.e., intervention 
strength, intervention weaknesses, and areas for improvement). Then, thematic analysis will be used to 
code emergent themes and patterns within each content area. Given the sample size for this successive 
cohort study (N = 15), it is estimated that we will identify and be able to address 97% of usability 
problems in the treatment personalization program (Faulkner, 2003). 
 
Aim 4: 
Analysis and interpretation will focus on describing the acceptability of the intervention and the 
feasibility of the trial approach. Given power limitations of using a small sample in a two-group study, it 
is not appropriate to perform any efficacy analyses. Regarding feasibility, we will describe patient 
recruitment, treatment retention, the proportion of patients who withdraw after randomization, and 
the proportion of patients who withdraw from treatment. In order to ascertain acceptability of the 
intervention, we will describe patient satisfaction, therapist satisfaction, and app utilization metrics. We 
will describe the proportion of patients that quit in each arm (but will not test group differences in 
abstinence). 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 22 of 25 
 
 
References 
Bee, A. (2012). Household income inequality within US counties: 2006-2010. US Department of 
Commerce, Economics and Statistics Administration, US Census Bureau. 
Benowitz, N. L., & Prochaska, J. J. (2013). Smoking cessation after acute myocardial infarction. Journal of 
the American College of Cardiology, 5, 533-535. 
Bhavsar, N. A., Gao, A., Phelan, M., Pagidipati, N. J., & Goldstein, B. A. (2018). Value of neighborhood 
socioeconomic status in predicting risk of outcomes in studies that use electronic health record 
data. JAMA network open, 1(5), e182716-e182716. 
Braithwaite, R. S., Fang, Y. X., Tate, J., Mentor, S. M., Bryant, K. J., Fiellin, D. A., & Justice, A. C. (2016). Do 
alcohol misuse, smoking, and depression vary concordantly or sequentially? A longitudinal study 
of HIV-infected and matched uninfected veterans in care. Aids and Behavior, 20(3), 566-572. 
doi:10.1007/s10461-015-1117-8 
Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 
3, 77-101. 
Brinkman, S. & Kvale, S. (2015). Interviews: Learning the Craft of Qualitative Research Interviewing. 3rd 
ed. London: Sage Publications, Inc. 
Burns, D. M. (2003). Epidemiology of smoking-induced cardiovascular disease. Progress in cardiovascular 
diseases, 46(1), 11-29. 
Cahill, K., Hartmann-Boyce, J., & Perera. R. (2015). Incentives for smoking cessation. Cochrane Database 
of Systematic Reviews, (5). 
Cahill K, Stevens S, Perera R, & Lancaster, T. (2013). Pharmacological interventions for smoking 
cessation: An overview and network meta-analysis. Cochrane Database of Systematic Reviews, 
(5). 
Calhoun, P. S., Wilson, S. M., Hertzberg, J. S., Kirby, A. C., McDonald, S. D., Dennis, P. A., . . . Beckham, J. 
C. (2017). Validation of veterans affairs electronic medical record smoking data among Iraq- and 
Afghanistan-era veterans. Manuscript submitted for review. 
Centers for Disease Control and Prevention. (2008). Smoking-attributable mortality, years of potential 
life lost, and productivity losses - United States, 2000-2004. Morbidity and Mortality Weekly 
Report, 57, 1226-1228. 
Christofferson, D.E., Hertzberg, J.S., Beckham, J.C., Dennis, P.A., & Hamlett-Berry, K. (2016). Engagement 
and abstinence among users of a smoking cessation text message program for veterans. 
Addictive Behaviors, 62, 47-53. 
Cooperman, N.A. (2016). Current research on cigarette smoking among people with HIV. Current 
Addiction Reports, 3, 19-26. 
Cropsey KL, Jardin BF, Burkholder GA, et al. (2015). An algorithm approach to determining smoking 
cessation treatment for persons living with HIV/AIDS: Results of a pilot trial. JAIDS, 69, 291-298. 
Crothers, K., Griffith, T.A., McGinnis, K.A. et al. (2005). The impact of cigarette smoking on mortality, 
quality of life, and comorbid illness among HIV-positive veterans. Journal of General Internal 
Medicine, 20, 1142-1145. 
Department of Veterans Affairs. (2012). The State of Care for Veterans with HIV/AIDS. In. Washington, 
D.C.: Public Health, Veterans Health Administration, Department of Veterans Affairs; 2012. 
Dunn, K.E., Sigmon, S.C., Reimann, E.F., Badger, G.J., Heil, S.H., & Higgins, S.T. (2010). A contingency- 
management intervention to promote initial smoking cessation among opioid-maintained 
patients. Experimental and Clinical Psychopharmacology, 18, 37-50. 
Epstein EE, McCrady BS, Morgan TJ, et al. (2007). The successive cohort design: A model for developing 
new behavioral therapies for drug use disorders. Addictive Disorders & Their Treatment, 6, 1-19 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 23 of 25 
 
 
Faulkner L. (2003). Beyond the five-user assumption: Benefits of increased sample sizes in usability 
testing. Behavior Research Methods, Instruments, & Computers, 35, 379-383. 
Fu, S.S., McFall, M., Saxon, A.J. et al. (2007). Post-traumatic stress disorder and smoking: A systematic 
review. Nicotine and Tobacco Research, 9, 1071-1084. 
Gaalema, D. E., Pericot-Valverde, I., Bunn, J. Y., Villanti, A. C., Cepeda-Benito, A., Doogan, N. J., ... & 
Higgins, S. T. (2018). Tobacco use in cardiac patients: perceptions, use, and changes after a 
recent myocardial infarction among US adults in the PATH study (2013–2015). Preventive 
medicine, 117, 76-82. 
Gritz, E. R., Danysh, H. E., Fletcher, F. E., Tami-Maury, I., Fingeret, M. C., King, R. M., . . . Vidrine, D. J. 
(2013). Long-term outcomes of a cell phone-delivered intervention for smokers living with 
HIV/AIDS. Clinical Infectious Diseases, 57(4), 608-615. doi:10.1093/cid/cit349 
Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? Field Methods, 18(1), 59- 
82. doi:doi:10.1177/1525822X05279903 
Haskell, S. G., Brandt, C. A., Krebs, E. E., Skanderson, M., Kerns, R. D., & Goulet, J. L. (2009). Pain among 
Veterans of Operations Enduring Freedom and Iraqi Freedom: do women and men differ? Pain 
Med, 10(7), 1167-1173. doi:10.1111/j.1526-4637.2009.00714.x 
Hoerster, K.D., Lehavot, K., Simpson, T., McFall, M., Reiber, G., & Nelson, K.M. (2012). Health and health 
behavior differences: U.S. Military, veteran, and civilian men. American Journal of Preventive 
Medicine, 43, 483-489. 
Hsieh, H.F. & Shannon, S.E. (2005). Three approaches to qualitative content analysis. Qualitative Health 
Research, 15, 1277-1288. 
Justice, A. C., Dombrowski, E., Conigliaro, J., Fultz, S. L., Gibson, D., Madenwald, T., . . . Bryant, K. (2006). 
Veterans Aging Cohort Study (VACS) - Overview and description. Medical Care, 44(8), S13-S24. 
doi:10.1097/01.mlr.0000223741.02074.66 
Kariuki, W., Manuel, J.I., Kariuki, N., Tuchman, E., O’Neal, J., &Lalanne, G.A. (2016). HIV and smoking: 
Associated risks and prevention strategies. HIV/AIDS, 8, 17-36. 
Katz, D. A., Holman, J. E., Johnson, S. R., Hillis, S. L., Adams, S. L., Fu, S. S., ... & Vander Weg, M. W. 
(2014). Implementing best evidence in smoking cessation treatment for hospitalized veterans: 
results from the VA-BEST Trial. The Joint Commission Journal on Quality and Patient 
Safety, 40(11), 493-AP1. 
Kim, R. S., Weinberger, A. H., Chander, G., Sulkowski, M. S., Norton, B., & Shuter, J. (2018). Cigarette 
smoking in persons living with hepatitis C: The National Health and nutrition examination survey 
(NHANES), 1999-2014. The American journal of medicine, 131(6), 669-675. 
Ladapo, J. A., Jaffer, F. A., Weinstein, M. C., & Froelicher, E. S. (2011). Projected cost-effectiveness of 
smoking cessation interventions in patients hospitalized with myocardial infarction. Archives of 
internal medicine, 171(1), 39-45. 
Lifson, A.R. & Lando, H.A. (2012). Smoking and HIV: Prevalence, health risks, and cessation strategies. 
Current HIV/AIDS Report, 9, 223-230. 
Lynch, S. M., Wilson, S. M., DeRycke, E. C., Driscoll, M. A., Becker, W. C., Goulet, J. L., ... & Bastian, L. A. 
(2018). Impact of cigarette smoking status on pain intensity among veterans with and without 
hepatitis C. Pain Medicine, 19(suppl_1), S5-S11. 
Mallat, A., Hezode, C., & Lotersztajn, S. (2008). Environmental factors as disease accelerators during 
chronic hepatitis C. Journal of hepatology, 48(4), 657-665. 
McGinnis, K. A., Brandt, C. A., Skanderson, M., Justice, A. C., Shahrir, S., Butt, A. A., . . . Crothers, K. 
(2011). Validating smoking data from the Veteran's Affairs health factors dataset, an electronic 
data source. Nicotine & Tobacco Research, 13(12), 1233-1239. doi:10.1093/ntr/ntr206 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 24 of 25 
 
 
Mdodo, R., Frazier, E.L., Dube. S.R. et al. (2015). Cigarette smoking prevalence among adults with HIV 
compared with the general adult population in the United States. Annals of Internal Medicine, 
162, 335-344. 
Meijer, E., Van der Kleij, R. M. J. J., & Chavannes, N. H. (2019). Facilitating smoking cessation in patients 
who smoke: a large-scale cross-sectional comparison of fourteen groups of healthcare 
providers. BMC health services research, 19(1), 1-16. 
Miles, M.B., Huberman, A.M., & Saldaña, J. (2014). Qualitative Data Analysis: A Methods Sourcebook, 3 
ed. Los Angeles, CA: Sage Publications, Inc. 
Minick, S.G., Stafford, C.L., Kertz, B.L. et al. (2016). Veterans’ perspectives on interventions to improve 
retention in HIV care. PLoS ONE, 11(2), e0148163. 
Moadel, A.B., Bernstein, S.L., Mermelstein, R.J., Arnsten, J.H., Dolce, E.H., & Shuter, J. (2012). A 
randomized controlled trial of a tailored group smoking cessation intervention for HIV-infected 
smokers. Journal of Acquired Immune Deficiency Syndromes, 61, 208-215. 
Moscou-Jackson, G., Commodore-Mensah, Y., Farley, J., & DiGiacomo, M. (2014). Smoking-cessation 
interventions in people living with HIV infection: A systematic review. Journal of the Association 
of Nurses in AIDS Care, 25, 32-45. 
Pacek, L.R. & Cioe, P.A. ( 2007). Tobacco use, use disorders, and smoking cessation interventions in 
persons living with HIV. Current HIV/AIDS Reports, 12, 413-420. 
Petry, N. (2010). Contingency management treatments: Controversies and challenges. Addiction, 105, 
1507-1509. 
Piper, M.E., Vasilenko, S.A., Cook, J.W., & Lanza, S.T. (2017). What a difference a day makes: Differences 
in initial abstinence response during a smoking cessation attempt. Addiction, 112, 330-339. 
Rasmussen, L.D., Helleberg, M., May, M. et al. (2015). Myocardial infarction among Danish HIV-infected 
individuals: Population attributable fractions associated with smoking. Clinical Infectious 
Diseases, 60, 1415-23. 
Reid, C., Fenech, M., Jones, L., & Salehi, N. (2020). Nurse practitioner interventions for smokers with 
chronic hepatitis C. Journal of the American Association of Nurse Practitioners, 32(5), 380-389. 
Rigotti, N. A., Clair, C., Munafò, M. R., & Stead, L. F. (2012). Interventions for smoking cessation in 
hospitalised patients. Cochrane Database of Systematic Reviews, (5). 
Rojewski, A. M., Bailey, S. R., Bernstein, S. L., Cooperman, N. A., Gritz, E. R., Karam-Hage, M. A., ... & 
Warren, G. W. (2019). Considering systemic barriers to treating tobacco use in clinical settings in 
the United States. Nicotine and Tobacco Research, 21(11), 1453-1461. 
Scott-Sheldon, L.A.J., Lantini, R., Jennings, E.G. et al. (2016). Text messaging-based interventions for 
smoking cessation: A systematic review and meta-analysis. Jmir Mhealth and Uhealth, 4, 337- 
360. 
Shelley, D., Tseng, T.Y., Gonzalez, M. et al. (2015). Correlates of adherence to varenicline among HIV plus 
smokers. Nicotine and Tobacco Research, 17, 968-974. 
Tesoriero, J.M., Gieryic, S.M., Carrascal, A., & Lavigne, H.E. (2010). Smoking among HIV positive New 
Yorkers: Prevalence, frequency, and opportunities for cessation. AIDS Behavior, 14, 824-835. 
Twyman, L., Bonevski, B., Paul, C., & Bryant, J. (2014). Perceived barriers to smoking cessation in 
selected vulnerable groups: a systematic review of the qualitative and quantitative literature. 
BMJ Open, 4(12), e006414. 
Vidrine, D.J., Arduino, R.C., Lazev, A.B., & Gritz, E.R. (2006). A randomized trial of a proactive cellular 
telephone intervention for smokers living with HIV/AIDS. AIDS, 20, 253-260. 
Vidrine, D.J., Marks, R.M., Arduino, R.C., & Gritz, E.R. (2012). Efficacy of cell phone-delivered smoking 
cessation counseling for persons living with HIV/AIDS: 3-month outcomes. Nicotine and Tobacco 
Research, 14, 106-110. 

Tobacco Cessation Treatment Preferences among Veteran Smokers 
Research Protocol, version date 7/25/2022 
Page 25 of 25 
 
 
Volkman, J. E., DeRycke, E. C., Driscoll, M. A., Becker, W. C., Brandt, C. A., Mattocks, K. M., . . . Bastian, L. 
A. (2015). Smoking Status and Pain Intensity Among OEF/OIF/OND Veterans. Pain Medicine, 
16(9), 1690-1696. doi:10.1111/pme.12753 
Watkins DC. (2017). Rapid and rigorous qualitative data analysis: The “RADaR” technique for applied 
research. International Journal of Qualitative Methods, 16(1), 1609406917712131.