Remember to Abstain: Assessment of Working Memory Training on Delay Discounting in Low-SES Cigarette Smokers
Phase: NA
Conditions: Tobacco Use Disorder/Cigarette Smoking
Sponsor: University of Kansas Medical Center

 
KUMC – HRPP- 03/12/2015 
 
Page 1 of 20 
v.2 
                                                                           Eff 9/21 
 
 
Research Protocol 
 
 
Version date: 9/28/21 
Principal Investigator: Anahi Collado, Ph.D. 
Study Title: Remember to abstain: Assessment of working memory training on delay discounting in low-
SES cigarette smokers 
NCT #: NCT05210608 
Co- Investigator(s): N/A 
  
 
I. 
Purpose, Background and Rationale 
A. Aim and Hypotheses  
1. Brief Introduction: Despite widespread awareness of significant negative health 
consequences, cigarette smoking remains the leading cause of preventable morbidity and 
mortality in the US (Creamer et al., 2019; Jamal, 2018). Moreover, the highest rate of 
smoking and heaviest burden of smoking-related illness occurs among low-socioeconomic 
status (SES) individuals relative to higher SES groups (Businelle et al., 2010; Clegg et al., 
2009). Low SES individuals are also 40% less likely to succeed in quitting smoking when 
they attempt to do so (National Center for Chronic Disease Prevention and Health Promotion 
(US) Office on Smoking and Health, 2014). One potential explanation for the disparity in rate 
of smoking and successful quit attempts may be differences in individual rates of delay 
discounting (DD), i.e., the degree to which rewards loses their value as the delays to their 
receipt increase (Odum, 2011). A proposed way to reduce steep DD and, potentially, 
substance use has been computer training for working memory, which has shown favorable 
results in a sample of individuals with stimulant dependence (Bickel et al., 2011) and 
substance use broadly (Felton et al., 2019), with the latter even showing decreases in cigarette 
smoking in a subset of the sample. 
 
2. Aims: The current study will assess delay discounting (DD), working memory (WM) training, 
and cigarette smoking cessation outcomes. The aims of the project are the following: 
 
 Assess efficacy of WM training  
o Assess efficacy of WM training on cigarette smoking 
o Assess efficacy of WM training on DD 
 

 
KUMC – HRPP- 03/12/2015 
 
Page 2 of 20 
v.2 
                                                                           Eff 9/21 
 
 
B. Background and Significance 
1. Study Significance: The development of effective, theoretically coherent interventions 
addressing cigarette smoking is imperative, particularly interventions that would be feasible, 
efficacious, and acceptable in low-SES individuals. The proposed research is an innovative 
approach that capitalizes on previous findings showing reductions in delay discounting and 
even cigarette smoking. If working memory training is found to improve smoking cessation 
outcomes as a function of reductions in delay discounting, the project results could be helpful 
in future development of low-cost interventions for cigarette smoking. 
 
2. The highest rate of smoking and heaviest burden of smoking-related illness occurs among 
low-SES individuals (Businelle et al., 2010; Clegg et al., 2009). One explanation for this 
disparity may be differences in individual rates of DD, which have been showed to be reduced 
with working memory training. (Bickel et al., 2011; Felton et al., 2019). Given the low cost of 
administering working memory training, such an intervention may be favorable for low-SES 
populations to improve smoking cessation outcomes. 
 
3. Literature Review: DD has significant associations with: 
 Cigarette smoking (smokers tend to have higher rates of DD compared to non-smokers; 
Bickel et al., 1999); 
 Smoking treatment outcome (individuals who remained smoke free after a smoking 
cessation intervention had lower DD compared to those who didn’t; González-Roz et al., 
2019; Krishnan-Sarin et al., 2007; MacKillop & Kahler, 2009; Yoon et al., 2007); 
 SES (individuals with lower education and income have higher DD rates compared to 
those who are more educated and affluent; de Wit et al., 2007; Reimers et al., 2009). 
An innovative way to reduce DD that has been proposed is via working memory (WM) 
training. WM refers to one’s capacity to hold information while engaging in complex mental 
tasks, including reasoning, comprehension, and learning (Baddeley, 2010). Previous research 
has shown that DD and WM correlate negatively (Shamosh et al., 2008), that individuals with 
higher DD rates show neural deficits in WM (Herting et al., 2010), and that acute nicotine 
abstinence is associated with WM deficits (Mendrek et al., 2006; Patterson et al., 2010). 
Furthermore, previous studies targeting WM to reduce DD have shown favorable results in a 
sample of individuals with stimulant dependence (Bickel et al., 2011) and substance use 
broadly (Felton et al., 2019), with the latter even showing decreases in cigarette smoking in a 
subset of the sample. 
 
C. Rationale 
1. Although previous research has shown WM training to reduce DD, and cigarette use in a 
small subsample, the hypotheses of this study are largely exploratory. However, given the 
theoretical connections between DD, SES, and WM, it is expected that the hypotheses of this 
project will be supported. 
 

 
KUMC – HRPP- 03/12/2015 
 
Page 3 of 20 
v.2 
                                                                           Eff 9/21 
 
 
2. The performance of this project may advance our knowledge of the relevant clinical targets 
for smoking cessation in low-SES individuals. In particular, this project is expected to shed 
light on DD as the putative mechanism in smoking for low-SES individuals and the durability 
of reductions in smoking as a result of reductions in DD through WM training. 
 
3. Despite the evidence for some successful techniques for reducing DD, little of this work has 
been translated into intervention approaches to target clinical outcomes. This application 
seeks to capitalize on the emerging literatures indicating (1) WM training may be an effective 
and efficient way to reduce DD, and (2) DD is associated with SES, cigarette smoking, and 
treatment outcomes. Though WM training has been successfully implemented in laboratory-
controlled experiments to reduce DD, we are not aware of any interventions for clinical 
disorders that specifically seek to do so and potentially enhance treatment outcomes. 
 
II. 
Research Plan and Design 
 
A. Study Objectives: The main aims of this project are to examine the observed efficacy of WM 
training.  
B. Study Type and Design: This study is an open-label trial longitudinal (participants will be 
assessed through their 1-month quit date) trial.  
 
C. Sample size, statistical methods, and power calculation 
1. Consistent with Stage 1a pilot trials, the current trial included a small sample size of 
completers (N = 15) to determine the initial outcomes of the WM intervention and its 
perceived feasibility/acceptability.  
2. DD will be estimated by fitting the hyperbolic function specified in Eq. 1 to the indifference 
points computed during the task in order to estimate each individual’s discount rate, where v 
represents the discounted value of an outcome, V is the undiscounted value, D is the delay and 
k is the discounting parameter, which specifies the degree to which the value of a given 
reward is discounted when it is delayed (with higher values representing greater discounting).  
 
 
 
While k distributions tend to be skewed, post-hoc natural logarithmic transformations will be 
performed, which have been shown to approximate normal distributions. We will calculate k 
values for each magnitude ($50, $200, $1000). Due to varying degrees of goodness-of-fit 
associated with nonlinear regression functions, we will also calculate area-under-the-curve 
(AUC) estimates (Borges et al., 2016). Hypotheses encompassed will be tested using 
Hierarchical Linear Modeling (HLM; Raudenbusch & Bryk, 2002), which allows the analysis 
of repeated measures and has been recommended because of its ability to: 1) accommodate 
missing data, 2) examine individual change over time in outcomes, and 3) include the average 
change and the individual variation around this average change which is especially important 

 
KUMC – HRPP- 03/12/2015 
 
Page 4 of 20 
v.2 
                                                                           Eff 9/21 
 
 
in a small sample (Raudenbusch & Bryk, 2002; Singer. & Willett, 2003), even in smaller 
samples (Collado et al., 2019). Hypotheses encompassed within Aim 1 will be tested using 
Hierarchical Linear Modeling (HLM; Raudenbusch & Bryk, 2002), which allows the analysis 
of repeated measures and has been recommended because of its ability to: 1) accommodate 
missing data, 2) examine individual change over time in outcomes, and 3) include the average 
change and the individual variation around this average change which is especially important 
in a small sample (Raudenbusch & Bryk, 2002; Singer. & Willett, 2003), even in smaller 
samples (Collado et al., 2019).  
 
3. Individuals who smoke cigarette and who are low in SES and receptive to a future quit 
attempt will be recruited for this study. Participants will be recruited from the greater Kansas 
City area.  
 
D. Subject Criteria (See Vulnerable Populations appendix, if applicable): The subject age range 
will be over 18 years old. Participants will be able to participate in the study regardless of gender and 
race. Special populations, such as minors and pregnant women, will not be targeted for inclusion.  
 
1. Inclusion criteria: To be included in this study, a participant must be 18 years of age or 
older, who have smoked at least four cigarettes per day for at least 6 months, are interested in 
quitting cigarette smoking, are at or below the federal poverty line based on persons in 
family/household and annual household income: 
 1 -- $12,880 
 2 -- $17,420 
 3 -- $21,960 
 4 – $26,500 
 5 -- $31,040 
 6 -- $35,580 
 7 -- $40,120 
 8 -- $44,660 
  9 – add $4,540 for each additional person, 
OR they or their child(ren) utilize a federal program for low-income individuals, and are 
willing to participate in a 5-week working memory training program as a pretreatment adjunct 
to behavioral group therapy. 
 
2. Exclusion criteria: Participants must not indicate a severe substance use disorder according 
to the DSM-V with any substance other than tobacco or have any significant medical or 
psychiatric condition. Such conditions could include traumatic brain injury, dementia, 
significant learning disability, or psychotic symptoms. Participants must be at least at a 5th-
grade reading level. In case that participants are excluded, they will be provided with 

 
KUMC – HRPP- 03/12/2015 
 
Page 5 of 20 
v.2 
                                                                           Eff 9/21 
 
 
resources in the community and provided with contact information for the Kansas Tobacco 
Quitline.  
 
3. Withdrawal/Termination criteria: Participants may withdraw from the study at any time 
without penalty. The researcher reserves the right to discontinue individuals who evidence 
inability to comply to study conditions. The researcher will also exclude participants if they 
seem at risk for COVID-19 infection. 
 
4. Participants can partake in other studies while participating in this research study if it does not 
interfere with their method of smoking cigarettes. 
 
E.  Specific methods and techniques used throughout the study: 
 
1. Laboratory tests: Participants will provide breath and saliva samples to confirm smoking 
abstinence. Breath samples will be collected using the coVita Micro+ basic Smokerlyzer and 
saliva samples will be collected using the NicConfirm mouth swab tests. Timing of the samples 
are described in the Study Procedures section. Amount cannot be readily estimated for either 
test. Saliva samples will only be labeled using participant ID #’s, and breath samples will be 
stored on the Smokerlyzer. Saliva samples will be photographed for study records and then 
discarded. 
 
 
 
Study Procedures 
 
COVID-19 safety procedures: These procedures will be followed for each in-person study session, and 
study staff will be trained prior to any data collection. Prior to departing, the project coordinator (PC) and/or 
research assistant (RA) will be screened for COVID-19 risk and will make sure all items and equipment 
(e.g., pens, laptop computers) are sanitized. The PC/RA will also wash and sanitize their hands as well as  
wear a surgical mask. The PC/RA will bring surgical masks and sanitizing wipes to the study location as 
well. The PC/RA will screen participants 24 hours before a session and at the study location prior to entering 
the building. 
 
High-touch surfaces and chairs would have been sanitized before any individuals enter the space. 
Participants and will have been screened according to aCOVID screening form. Social distancing (6 feet or 
more) will be enforced at all parts of the study session unless close contact is absolutely necessary. All 
individuals will wear a face mask unless participants need to provide breath/saliva samples.  
Note: If at any point a participant displays behavior inconsistent with COVID-19 safety procedures (e.g., not 
wearing their mask properly for extended periods of time, not social distancing), they will be reminded of the 
procedures. If the person refuses to engage in COVID-19 safety procedures, their participation will be 
terminated for the day. Individuals whose participation is terminated for the day will be asked if they are 
willing to follow COVID-19 safety procedures for future appointments. If participants deny their intention to 
meet the safety procedures, their participation in the study will be terminated. These participants will be 
provided with resources in the community as well as with contact information for the Kansas/Missouri 
Quitline. In the event that a participant reports any COVID-like symptoms, participants will be asked to 
leave the study location and reach out to Swope Health Services for further guidance.  

 
KUMC – HRPP- 03/12/2015 
 
Page 6 of 20 
v.2 
                                                                           Eff 9/21 
 
 
 
Upon session conclusion, the RA will collect the laptop computer from the participant and disinfect. 
All high-touch surfaces and chairs will also be sanitized. 
After participants complete 5 or more of the working memory trainings, they can begin attending a 
weekly 60-minute group based on an evidence-based behavioral treatment manual (MacPherson et al., 2016, 
2017). Group topics include identifying values and goals within a variety of life areas (including achieving a 
non-smoking lifestyle), structuring and scheduling activities according to these personal values, identifying 
high-risk situations and developing appropriate coping strategies, enlisting social support assertively, 
discussing the benefits of a non-smoking lifestyle, receiving social support from the group, and managing 
lapses in smoking. Participants can attend as many sessions as they would like and join groups on a rolling 
basis.  
Screener call: Interested individuals will take part in a phone call (~10 minutes) with the proje 
 coordinator to determine their eligibility. The project coordinator will ensure that participants do not 
meet exclusion criteria, which include: not being a smoker who has smoked 4 cigarettes/day for at least 6 
months, not being interested in quitting smoking, not qualifying as low-income, having significant medical 
or psychiatric conditions, having severe substance use disorder for any substance other than tobacco, or 
being below a 5th grade reading level (asked via a self-report of educational attainment). Participants would 
qualify as low-income if they are at or below the federal poverty line for their respective household size OR 
if they or their child utilize a federal program for low-income individuals (e.g., Supplemental Security 
Income, Supplemental Nutrition Assistance Program, Children’s Health Insurance Program, etc.; 
https://aspe.hhs.gov/topics/poverty-economic-mobility/poverty-guidelines/frequently-asked-questions-
related-poverty-guidelines-poverty). Participants will be screened on any alcohol and drug use within the 
past 12 months and DSM-5 SUD symptoms will be assessed for any frequent substance use (2-4 times a 
week or more for any non-prescribed drug, 3-5 times a week or more for alcohol) other than tobacco. 
Participants who do not meet eligibility requirements will be informed that they will not be able to continue 
with the study, but the reason for this will not be disclosed. This is to ensure that participants do not attempt 
to alter their responses on disqualifying criteria in order to continue with the study. Contact information, in 
whatever medium the participant chooses (e.g., email, phone call, SMS text), and contacting preferences 
(e.g., medium, time of day) will also be collected for future session scheduling purposes. All individuals will 
be provided with a referral document which lists medical, substance use, and case management services in 
the Kansas City area. Individuals will be asked if they would like to receive the document over email, sent 
through mail, texted via SMS, or have it read out loud to them over a phone call. 
Baseline session: This session will take approximately 1 to 1.5 hour to complete and will include 
informed consent and initial assessments. Participants will complete an informed consent process, which will 
include time and space to read the informed consent form (ICF), followed by thorough discussion with a 
study staff member about the nature of the study, potential risks and benefits, and participant rights. If the 
individual wishes to continue following this discussion, they will digitally sign the ICF via Qualtrics. At the 
point at which the ICF is signed by the individual, s/he will be considered an enrolled participant. 
Participants will also report demographic information (age, sex, race/ethnicity, current income, employment, 
and education level) and report on their cigarette smoking behavior. If at any point during the study a 
participant reports elevated suicidality, they will be thoroughly assessed for suicidality risk by the PI, who 
was extensive clinical experience, and participants will be referred to immediate care (e.g., Emergency 
department, Kansas City crisis response) depending on level of risk. All individuals will be provided with a 
referral document which lists medical, substance use, and case management services in the Kansas City area. 
Participants will also complete a reading test (Wide Range Achievement Test-4; WRAT-4) to confirm 
reading level from self-reported educational attainment. 

 
KUMC – HRPP- 03/12/2015 
 
Page 7 of 20 
v.2 
                                                                           Eff 9/21 
 
 
Participants will also complete baseline assessments of DD, WM, and health-relevant behaviors and 
outcomes (Measures described in detail below). DD will be assessed using computerized binary choice tasks 
that asks participants to choose between smaller, immediate (either money or cigarettes) and larger, delayed 
(money) amounts after a specified delay and which adjusts the amount of the smaller, immediate amount 
based on participant choices. Point prevalence of tobacco smoking in the prior 7 days will be assessed using 
the semi-structured Timeline Followback (TLFB). WM will be assessed using the Tower of Hanoi task 
(TOH; asks participants to sequentially move a series of disks of varying sizes across 3 pegs), Hopkins 
Verbal Learning Test-Revised (HVLT-R; asks participants to recall and recognize a series of words), and 
Letter Number Sequencing task (LNS; asks participants to recall a set of numbers and letters). Participants 
will also be asked to provide an expired breath carbon monoxide (CO) sample using a coVita Micro+basic 
Smokerlyzer to biochemically verify smoking status/abstinence. 
Training sessions: Participants will then be scheduled for the first of 10 training sessions. For each 
of the 10 training sessions, participants will complete four EF training programs. These programs have been 
used successfully to decrease DD (Bickel et al., 2011). These programs are: Sequenced Recall of Digits – 
Auditory, Sequenced Reverse Recall of Digits – Auditory, Sequenced Recall of Words – Visual, Verbal 
Memory – Visual. Each session will take 30 minutes to complete. For the control training program, the tasks 
will be matched on all essential features (e.g., stimulus, response, feedback) with four exceptions: (1) correct 
answers are provided or indicated to participants within each trial as part of the program interface, and (2) 
instruction indicates how to identify and respond to the stimulus that indicates the correct response. This will 
ensure that the sensory/motor experience of participants in the active training vs control training conditions 
are as similar as possible, with the exception of the memory requirement. Participants will also be given a set 
of noise-cancelling headphones during the training sessions to help offset any ambient noise in the 
environment. 
Training sessions will take approximately 30 minutes to complete, will occur 2–3 times per week, 
and completed in 3-5 weeks in most instances. Each participant will be assigned a unique computer login for 
the self-guided training sessions, and progress (attendance, performance) will be monitored.  
BA groups: Once participants complete 50% or more of their training sessions, the project 
coordinator will work with participants to find a time to begin the behavioral group sessions with the PI (i.e., 
Clinician), who will administer the intervention, over Zoom.  
1. Session 1: Clinician will let everyone introduce themselves, go over group guidelines 
(including confidentiality), explain program rationale (engaging in pleasurable, smoke-free 
activities improves chances of quitting smoking), make note of barriers and benefits to 
quitting smoking, provide a copy of the National Cancer Institute Clearing the Air pamphlet, 
discuss previous quit attempts with the group participants as well as the upcoming quit 
attempt as part of the program, and introduce the Daily Activity, Mood, and Smoking Log, 
which asks participants to list hour-by-hour what they did during each day, the enjoyment of 
activity/event, the importance of it, the number of cigarettes smoked during each 
activity/event, and the overall mood of the day. 
2. Session 2: Clinician will go over participants’ use of the Daily Activity, Mood, and Smoking 
log, explain Life Areas, Values, and Activities (LAVA; major life areas, such as social 
relationships, and activities to strengthen those areas, such as spending more time with family 
on weekends), and ask participants to choose 15 activities related to their life areas and rank 
them by difficulty to accomplish. 

 
KUMC – HRPP- 03/12/2015 
 
Page 8 of 20 
v.2 
                                                                           Eff 9/21 
 
 
3. Session 3 (1 week pre-quit date): Clinician will go over participants’ use of the Daily 
Activity, Mood, and Smoking log, review participants’ LAVA inventory, explain how to plan 
activities and integrate them with their daily log, discuss high-risk situations for relapse and 
how to identify them, and scheduling the quit date (and what to do in case of a “slip,” i.e., 
smoking after quit date). 
4. Session 4 (quit week): Clinician will go over participants’ use of the Daily Activity, Mood, 
and Smoking log, discuss quit dates and quitting experience (e.g., withdrawal and immediate 
plans) for each participant, discuss success in accomplishing LAVA activities, identify 
obstacles to abstinence, offer support, talk about maintaining a healthy lifestyle (i.e., proper 
diet and exercise), and highlight social support, particularly by encouraging participants to 
form a “Contract” with a supportive person in their life (i.e., ask someone to take part in an 
activity with them to help them remain abstinent, such as riding bicycles together).  
5. Session 5: Clinician will go over participants’ use of the Daily Activity, Mood, and Smoking 
log, participants’ contracts, quitting experience (e.g., withdrawal symptoms), strategies to 
avoid smoking, perceived benefits and disadvantages to quitting smoking, and identifying 
high-risk situations. 
6. Session 6: Clinician will go over participants’ use of the Daily Activity, Mood, and Smoking 
log, quitting experience (e.g., withdrawal symptoms), strategies to avoid smoking, perceived 
benefits and disadvantages to quitting smoking, discuss time management as a tool for 
abstinence, help identify high-risk situations, and offer support. 
7. Session 7: This session will mirror Session 6. 
8. Session 8: This session will mirror Sessions 6 & 7, and will include a discussion on 
developing a post-program plan to maintain abstinence by engaging and monitoring activities 
after the BA group and dealing with negative feelings, triggers, and immediate cravings. The 
clinician will also review the overall program progress and remind participants about the 
upcoming follow-up sessions. 
Post-training session: This session is expected to take 1 to 1.5 hours to complete. 2-3 days following 
their last training session, participants will complete the DD task, TLFB, TOH, HVLT-R, LNS, and provide 
a CO breath sample. Participants will be asked to set a quit date for their cigarette smoking at this session 
and will be encouraged to connect to the tobacco quitline (1-800-QUIT-NOW).  
1-week post quit date session: This session is expected to take about 30 minutes to complete. 
Around 7 days after their quit date, participants will complete the DD task, TLFB, and provide a CO breath 
sample. Participants will also provide a saliva sample to test for salivary cotinine, a metabolite of nicotine to 
biochemically verify smoking status/abstinence. 
1-month post quit date session: This session is expected to take about 45 minutes to complete. 
Around 30 days after their quit date, participants will complete the DD task, TLFB, TOH, HVLT-R, LNS, 
provide a CO breath sample, and provide a saliva sample.  
 
Measures 
SCID DSM-5.  If a participant reports frequent drug or alcohol use, they will fill out questionnaires on 
their DSM-5 symptoms for the respective substance (other than tobacco). Data will be recorded on Qualtrics, 
only identified by participant ID. 

 
KUMC – HRPP- 03/12/2015 
 
Page 9 of 20 
v.2 
                                                                           Eff 9/21 
 
 
Wide Range Achievement Test 4 (WRAT 4). A reading survey to measure participant’s grade-level 
equivalent reading ability.  This will be administered at the baseline session. Data will be recorded on paper, 
only identified by participant ID. 
Single Commodity Delay Discounting (DD). A binary choice procedure will be conducted on a 
personal computer to assess DD. On each DD trial, two hypothetical money rewards will be presented on the 
screen. One outcome will be an amount of money available immediately; the other outcome will be a larger 
amount of money ($50, $1,000) available after some specified delay (1 week, 1 month, 6 months, 1 year, 5 
years). Participants will indicate the preferred alternative with a mouse-click, and the computerized 
algorithm (Holt et al., 2003) will adjust the immediate reward over 6 trials to determine an indifference point 
for each amount/delay pairing, resulting in 7 indifference points (corresponding to the 7 delays) for each of 2 
amounts ($50$1,000). Indifference points will be used to calculate delay discounting rates. Participants will 
be told to indicate preference on the task as if the outcomes were for real money; previous research has 
established the validity and reliability of DD tasks for hypothetical rewards (Matusiewicz et al., 2013). The 
results of this assessment will be recorded on a laptop computer, only identified by participant ID. 
Timeline Follow-Back (TLFB; Sobell & Sobell, 1992). A 7-day TLFB methodology will be 
employed to assess point prevalence of tobacco use. Participants will be asked to report number of cigarettes 
smoked for each day. Participants will also be asked to report nicotine vape and marijuana use. Data will be 
recorded on Qualtrics, only identified by participant ID. 
Tower of Hanoi (ToH). This assessment consists of a board with 3 pegs and 4 disks of differing 
sizes. Participants must move the stack of disks from one peg to another while following specific rules (i.e., 
all pegs must end up on the farthest peg and at no point can a larger disk be placed on top of a smaller disk). 
Task will be completed with a research assistant and data will be recorded on Qualtrics, only identified by 
participant ID. 
Hopkins Verbal Learning Test – Revised (HVLT-R; Brandt & Beneditc, 2001). This standardized 
assessment of verbal learning and memory requires participants to memorize a list of words presented 
auditorily. Participants are then asked to recall or recognize as many words as possible, either immediately or 
following a delay. Task will be completed with a research assistant and data will be recorded on Qualtrics, 
only identified by participant ID. 
Letter Number Sequencing (LNS). This measure of working memory is in the Adult Intelligence 
Scales–III (Wechsler, 1997). The participant is given a mixed string of letters and numbers that they must 
then put into a sequential order of numbers followed by a sequential order of letters. The string presentation 
increases in difficulty until the participant is no longer able to correctly sequence three strings of equivalent 
difficulty. Task will be completed with a research assistant and data will be recorded on Qualtrics, only 
identified by participant ID. 
Fagerstrom Test for Nicotine Dependence (FTND; Heatherton et al., 1991). Nicotine dependence 
will be measured using the 6-item FTND, a standard instrument for assessing intensity of physical addiction 
to nicotine as it relates to smoking. Data will be recorded on Qualtrics, only identified by participant ID. 
Expired Breath Carbon Monoxide (CO). Smoking status will be measured with an expired carbon 
monoxide (CO) level using a coVita Micro+basic Smokerlyzer monitor 
(https://www.covita.net/product/microbasic-smokerlyzer/). A CO level below 9 parts per million will 
indicate smoking abstinence for 12 hours or less. Trained research staff will administer this measure. 
Disposable mouthpieces will be used for each individual, and the results will be shared with the participants 
immediately following completion if they are interested. Data will be recorded on the CO monitor and on 
Qualtrics, only identified by participant ID. 
Salivary Cotinine. Smoking status will also be measured with a salivary cotinine measure (saliva 
sample) using NicConfirm mouth swab cotinine tests (https://www.confirmbiosciences.com/products/retail-
brands/nicconfirm-swab-cotinine-test/). A cotinine level below 30 ng/ml will indicate smoking abstinence 
for 1 week or less. The results will be shared with the participants immediately following completion if they 

 
KUMC – HRPP- 03/12/2015 
 
Page 10 of 20 
v.2 
                                                                           Eff 9/21 
 
 
are interested. Data will be recorded on Qualtrics, and a picture will be taken of the salivary cotinine test for 
record-keeping, only identified by participant ID. 
 
Timeline 
 
 
Measure 
Screener 
Call 
Baseline 
Computer 
Training (CT) 
[~3-5 weeks] 
Post-CT 
1-week Post-
Quit Date 
1-Month Post-
Quit Date 
Screener 
X 
 
 
 
 
 
Demographics 
 
X 
 
 
 
 
DD Tasks 
 
X 
 
X 
X 
X 
Saliva Sample 
 
 
 
X 
X 
X 
Breath Sample 
 
X 
 
X 
X 
X 
Timeline 
Followback 
 
X 
 
X 
X 
X 
WM Measures  
 
X 
 
X 
 
X 
 
 
 
 
 
F. Risk/benefit assessment:  The risks associated with participation are minor, but there may be some 
risks possible: 1) Loss of confidentiality. This risk will be minimized by removing any link between 
personal information and data collection. 2) Embarrassment or negative feelings regarding their 
health behaviors or concerns. Participants can choose not to answer any questions. Information 
collected will be used for research purposes only. Participants will also be reminded that participation 
is completely voluntary and that they may withdraw at any time without penalty or losing any 
benefits to which they would otherwise qualify. 3) Minor physical discomfort from when giving 
saliva sample and carbon monoxide breath sample. We will do our best to minimize discomfort. 
 
1. Physical risk: N/A 
 
2. Psychological risk: N/A 
 
3. Social risk: N/A 
 
4. Economic risk: N/A 
 
Behavioral Activation Groups 

 
KUMC – HRPP- 03/12/2015 
 
Page 11 of 20 
v.2 
                                                                           Eff 9/21 
 
 
5. Potential benefit(s) of participating in the study:  
 
i. Participants are not guaranteed any benefits but may benefit from WM training and/or 
behavioral therapy centered on smoking cessation.  
ii. N/A. 
iii. This study may provide scientific and societal benefits by supporting this novel approach 
to improving health behaviors and outcomes via working memory training training. 
 
G. Location where study will be performed: Research activities will take place at the Mazuma 
building in Kansas City (4001 Blue Parkway, Kansas City, MO 64130) in office space currently 
rented out by KUMC staff (including Tricia Snow). The behavioral activation groups will occur 
remotely on Zoom. 
H. Collaboration (with another institution, if applicable): N/A. 
I. Single IRB Review for a Multi-site study (if applicable): N/A. 
 
J. Community-Based Participatory Research (if applicable): N/A. 
 
 
K. Personnel who will conduct the study, including: 
1. Indicate, by title, who will be present during study procedure(s): Dr. Anahi Collado, Ph.D., or 
the project coordinator, Sergej Grunevski, will facilitate the behavioral activation groups, the 
project coordinator and research assistant will be present as well. Project coordinator, Sergej 
Grunevski, will be present during consent and eligibility determination, the initial data 
collection, and the follow-up data collection. Research assistant, Archana Sundar, will be 
maintaining participant research records, managing study databases, and will be trained on 
conducting tests and procedures.  
 
2. Primary responsibility for the following activities, for example:  
a. Determining eligibility: Sergej Grunevski and Archana Sundar 
b. Obtaining informed consent: Sergej Grunevski and Archana Sundar 
c. Providing on-going information to the study sponsor and the IRB: Dr. Anahi Collado 
and Sergej Grunevski 
d. Maintaining participant's research records: Sergej Grunevski and Archana Sundar 
e. Completing physical examination: N/A 
f. Taking vital signs, height, weight: N/A 
g. Drawing / collecting laboratory specimens: Sergej Grunevski and Archana Sundar 

 
KUMC – HRPP- 03/12/2015 
 
Page 12 of 20 
v.2 
                                                                           Eff 9/21 
 
 
h. Performing / conducting tests, procedures, interventions, questionnaires: Dr. Anahi 
Collado, Sergej Grunevski, and Archana Sundar 
i. Completing study data forms: Sergej Grunevski and Archana Sundar 
j. Managing study database: Sergej Grunevski and Archana Sundar 
 
L. Assessment of Subject Safety and Development of a Data and Safety Monitoring Plan 
 
1. Details of the plan include: 
a.   Persons/groups who will review the data (study team; independent safety monitor, 
data monitoring committee or formal DSMB). Dr. Anahi Collado, Sergej Grunevski, 
and Archana Sundar. 
b. Data/events that will be reviewed. Dates and events will be reviewed by the PI’s and 
the research coordinator. 
c. Frequency of review will occur biweekly. 
d. Safety-related triggers that would cause the PI to stop or alter the study include 
COVID-19 infection or increased risk and cases in the greater Kansas City area. 
 
2. Events will be determined as serious if they adversely impact the mental or physical health of 
the participant. Any AE will be reported to the PI immediately, and the PI will make the 
determination if the event is an AE or SAE and related or unrelated to the study. Any SAE 
that is related to the study will be reported within 24 hours of the determination to the IRB as 
well as funding agency. AE/SAEs that are unrelated to the study will be reported during 
regular reporting intervals. 
 
3. If a participant has an adverse experience during the study, study participation will be 
discontinued for the participant. 
 
III. 
Subject Participation 
 
A. Recruitment: Participants will be recruited through the KUMC’s collaborator site (Swope Health 
Services), via posted fliers, Craigslist fliers, announcements, and word-of-mouth referrals. Once 
participants contact the study team, the project coordinator will reply with a brief description of 
the study procedures and try to schedule the individual’s baseline session.  
 
B. Screening Interview/questionnaire: Participants will be screened out using questionnaires if 
they indicate a severe substance use disorder according to the DSM-V with any substance other 
than tobacco or have any significant medical or psychiatric condition. Such conditions could 
include traumatic brain injury, dementia, significant learning disability, or psychotic symptoms. 
Participants will be consented prior to screening procedures. 
  
C. Informed consent process and timing of obtaining of consent: 

 
KUMC – HRPP- 03/12/2015 
 
Page 13 of 20 
v.2 
                                                                           Eff 9/21 
 
 
1. The project coordinator (Sergej Grunevski) will give subjects detailed and comprehensive 
information about the study and obtain their written consent. 
 
2. The project coordinator (Sergej Grunevski) will summarize study procedures, risks, 
compensations, and other relevant information to the participant. Then, the participant will be 
allowed to fully read the ICF in as much time as they need. The participant may ask questions 
at any point before or after reading the ICF, after which they will have the chance to sign the 
document. Participants will be given a copy for their records and will be able to withdraw 
their consent at any point without penalty.  
 
3. Individuals who are cognitively or decisionally impaired (e.g., dementia, psychosis) will be 
screened out over a phone call prior to consent procedures. The project coordinator (Sergej) 
will screen interested individuals over the phone. 
 
D. Alternatives to Participation: The alternative to participation is to not participate. 
E. Costs to Subjects: There will be no costs to participants during this study. 
F. How latest information will be conveyed to the study subject and how it will be 
documented: Latest information regarding the participants in the study will be conveyed via 
email. This will be documented in a spreadsheet to ensure that all participants received all 
necessary information for the study. 
Payment, including a prorated plan for payment: Participants will be compensated using a 
prepaid debit card (ClinCard) for their participation in this study. They will receive $25.00 for 
completing all assessments at the baseline session. For the weekly training sessions, they will be 
receive a minimum of $17.50 for every session they complete. If they complete at least 5 computer 
training sessions, they will receive $10.00, and if they complete an additional 5 (i.e., all 10 session), 
they will be given an additional $20.00. They will receive $35.00 for completing the post-training 
session, $30.00 for completing the 1-week post-quit date session, and $30.00 for completing the 1-
month post-quit date session. The payment for each of the assessment sessions reflects a $10 amount 
to compensate individuals for transportation to the study site.  
 
A. Payment for a research-related injury: N/A 
IV. 
Data Collection and Protection 
A. Data Management and Security: Data will primarily be collected using Qualtrics. Digital data 
files that contain identifiable information will be kept on a KU SharePoint site. Pictures of saliva 
sample test results will also be kept on the SharePoint. 
 
1. 
The research team, including Dr. Anahi Collado, Sergej Grunevski, and Archana Sundar will 
have access for study data.  

 
KUMC – HRPP- 03/12/2015 
 
Page 14 of 20 
v.2 
                                                                           Eff 9/21 
 
 
2. 
Data will be stored on a KU-owned SharePoint site. Only study staff will have access to the 
data for this study. All study data will be de-identified and given a numerical identification 
number. 
3. 
Study staff will maintain a database with identifiable information of participants, but 
participants will be identified using a unique identifier throughout study participation.  
4. 
All study team members will have access to the key code for de-identified data. 
5. 
Each subject will get one numerical identification code that will be used only for this subject. 
6. 
Data files will be maintained in a secure KU-owned SharePoint site. 
7. 
Mobile devices will not be used for data collection or storage. 
8. 
N/A. 
 
B. Sample / Specimen Collection: Saliva samples will be collected using mouth swab tests, after 
which a picture will be taken of the test and the test will be discarded. The sample will be 
identified only by unique participant identifiers. 
C. Tissue Banking Considerations: N/A 
D. Procedures to protect subject confidentiality: Participant data will be coded with a numerical 
identification code and all data, including subject identifiers, ICFs, and contact information will 
be digitally stored on a KU-operated SharePoint folder (in addition to storage on Qualtrics). The 
data will be accessible only to study staff who are involved with the study. The data will be held 
for a maximum of 10 years after the primary results are published.  After said period, all data will 
be erased. 
 
E. Quality Assurance / Monitoring 
1. 
The data will be updated every time a new participant is added to the study. Data collected 
and added will be checked using documents that the participant filled out to ensure that all 
data is correctly entered. All data will be checked weekly to ensure that the data is 
consistent and complete. Following any contact with a participant, additional information 
from the meeting will be added to the data. 
 
2. 
There are no plans to have an ongoing third-party monitoring. 
 
 
V. Data Analysis and Reporting 
A. Statistical and Data Analysis:  Hypotheses encompassed within Aim 1 will be tested using 
Hierarchical Linear Modeling (HLM; Raudenbusch & Bryk, 2002), which allows the analysis of 
repeated measures and has been recommended because of its ability to: 1) accommodate missing 
data, 2) examine individual change over time in outcomes, and 3) include the average change and 
the individual variation around this average change which is especially important in a small 
sample (Raudenbusch & Bryk, 2002; Singer. & Willett, 2003), even in smaller samples (Collado 
et al., 2019).  

 
KUMC – HRPP- 03/12/2015 
 
Page 15 of 20 
v.2 
                                                                           Eff 9/21 
 
 
B. Outcome: The study will conclude once we collect full data from 10 participants. It is expected 
that study hypotheses will be supported, with success/failure determined by results from WM 
training on cigarette use over time.  
C. Study results to participants: Participants will be given information on their breath/saliva 
samples results immediately following testing if they are interested. 
D. Publication Plan: Data will be used to support a subsequent NIH grant application. Attempts to 
publish in relevant peer-reviewed journal will made if hypotheses are sufficiently supported. 
 
 
 
Bibliography / References / Literature:  
 
Baddeley, A. (2010). Working memory. Current Biology: CB, 20(4), R136-140. 
https://doi.org/10.1016/j.cub.2009.12.014 
Bickel, W. K., Odum, A. L., & Madden, G. J. (1999). Impulsivity and cigarette smoking: Delay discounting 
in current, never, and ex-smokers. Psychopharmacology, 146(4), 447–454. 
https://doi.org/10.1007/PL00005490 
Bickel, W. K., Yi, R., Landes, R. D., Hill, P. F., & Baxter, C. (2011). Remember the Future: Working 
Memory Training Decreases Delay Discounting Among Stimulant Addicts. Biological Psychiatry, 
69(3), 260–265. https://doi.org/10.1016/j.biopsych.2010.08.017 
Borges, A. M., Kuang, J., Milhorn, H., & Yi, R. (2016). An alternative approach to calculating Area-Under-
the-Curve (AUC) in delay discounting research: ALTERNATIVE TO AUC. Journal of the 
Experimental Analysis of Behavior, 106(2), 145–155. https://doi.org/10.1002/jeab.219 
Brandt, J., & Beneditc, R. H. B. (2001). Hopkins verbal learning test—Revised. Psychological Assessment 
Resources. 
Businelle, M. S., Kendzor, D. E., Reitzel, L. R., Costello, T. J., Cofta-Woerpel, L., Li, Y., Mazas, C. A., 
Vidrine, J. I., Cinciripini, P. M., Greisinger, A. J., & Wetter, D. W. (2010). Mechanisms linking 
socioeconomic status to smoking cessation: A structural equation modeling approach. Health 

 
KUMC – HRPP- 03/12/2015 
 
Page 16 of 20 
v.2 
                                                                           Eff 9/21 
 
 
Psychology: Official Journal of the Division of Health Psychology, American Psychological 
Association, 29(3), 262–273. https://doi.org/10.1037/a0019285 
Carvalho, J. P., Gawrysiak, M. J., Hellmuth, J. C., McNulty, J. K., Magidson, J. F., Lejuez, C. W., & Hopko, 
D. R. (2011). The Reward Probability Index: Design and Validation of a Scale Measuring Access to 
Environmental Reward. Behavior Therapy, 42(2), 249–262. 
https://doi.org/10.1016/j.beth.2010.05.004 
Clegg, L. X., Reichman, M. E., Miller, B. A., Hankey, B. F., Singh, G. K., Lin, Y. D., Goodman, M. T., 
Lynch, C. F., Schwartz, S. M., Chen, V. W., Bernstein, L., Gomez, S. L., Graff, J. J., Lin, C. C., 
Johnson, N. J., & Edwards, B. K. (2009). Impact of socioeconomic status on cancer incidence and 
stage at diagnosis: Selected findings from the surveillance, epidemiology, and end results: National 
Longitudinal Mortality Study. Cancer Causes & Control: CCC, 20(4), 417–435. 
https://doi.org/10.1007/s10552-008-9256-0 
Collado, A., Zvolensky, M., Lejuez, C., & MacPherson, L. (2019). Mental health stigma in depressed 
Latinos over the course of therapy: Results from a randomized controlled trial. Journal of Clinical 
Psychology, 75(7), 1179–1187. https://doi.org/10.1002/jclp.22777 
Creamer, M. R., Wang, T. W., Babb, S., Cullen, K. A., Day, H., Willis, G., Jamal, A., & Neff, L. (2019). 
Tobacco Product Use and Cessation Indicators Among Adults—United States, 2018. Morbidity and 
Mortality Weekly Report, 68(45), 1013–1019. https://doi.org/10.15585/mmwr.mm6845a2 
de Wit, H., Flory, J. D., Acheson, A., McCloskey, M., & Manuck, S. B. (2007). IQ and nonplanning 
impulsivity are independently associated with delay discounting in middle-aged adults. Personality 
and Individual Differences, 42(1), 111–121. https://doi.org/10.1016/j.paid.2006.06.026 
Felton, J. W., Collado, A., Ingram, K. M., Doran, K., & Yi, R. (2019). Improvement of Working Memory is 
a Mechanism for Reductions in Delay Discounting Among Mid-Age Individuals in an Urban 

 
KUMC – HRPP- 03/12/2015 
 
Page 17 of 20 
v.2 
                                                                           Eff 9/21 
 
 
Medically Underserved Area. Annals of Behavioral Medicine, 53(11), 988–998. 
https://doi.org/10.1093/abm/kaz010 
González-Roz, A., Secades-Villa, R., Pericot-Valverde, I., Weidberg, S., & Alonso-Pérez, F. (2019). Effects 
of Delay Discounting and Other Predictors on Smoking Relapse. The Spanish Journal of Psychology, 
22. https://doi.org/10.1017/sjp.2019.11 
Heatherton, T. F., Kozlowski, L. T., Frecker, R. C., & Fagerström, K. O. (1991). The Fagerström Test for 
Nicotine Dependence: A revision of the Fagerström Tolerance Questionnaire. British Journal of 
Addiction, 86(9), 1119–1127. https://doi.org/10.1111/j.1360-0443.1991.tb01879.x 
Herting, M. M., Schwartz, D., Mitchell, S. H., & Nagel, B. J. (2010). Delay discounting behavior and white 
matter microstructure abnormalities in youth with a family history of alcoholism. Alcoholism, 
Clinical and Experimental Research, 34(9), 1590–1602. https://doi.org/10.1111/j.1530-
0277.2010.01244.x 
Holt, D. D., Green, L., & Myerson, J. (2003). Is discounting impulsive?. Evidence from temporal and 
probability discounting in gambling and non-gambling college students. Behavioural Processes, 
64(3), 355–367. https://doi.org/10.1016/s0376-6357(03)00141-4 
Jamal, A. (2018). Current Cigarette Smoking Among Adults—United States, 2016. MMWR. Morbidity and 
Mortality Weekly Report, 67. https://doi.org/10.15585/mmwr.mm6702a1 
Krishnan-Sarin, S., Reynolds, B., Duhig, A. M., Smith, A., Liss, T., McFetridge, A., Cavallo, D. A., Carroll, 
K. M., & Potenza, M. N. (2007). Behavioral Impulsivity Predicts Treatment Outcome in a Smoking 
Cessation Program for Adolescent Smokers. Drug and Alcohol Dependence, 88(1), 79–82. 
https://doi.org/10.1016/j.drugalcdep.2006.09.006 
MacKillop, J., & Kahler, C. W. (2009). Delayed reward discounting predicts treatment response for heavy 
drinkers receiving smoking cessation treatment. Drug and Alcohol Dependence, 104(3), 197–203. 
https://doi.org/10.1016/j.drugalcdep.2009.04.020 

 
KUMC – HRPP- 03/12/2015 
 
Page 18 of 20 
v.2 
                                                                           Eff 9/21 
 
 
MacPherson, L., Collado, A., Lejuez, C. W., Brown, R. A., & Tull, M. T. (2016). Behavioral Activation 
Treatment for Smoking (BATS) in smokers with depressive symptomatology. Advances in Dual 
Diagnosis, 9(2/3). https://doi.org/10.1108/ADD-02-2016-0005 
MacPherson, L., Collado, A., Ninnemann, A., & Hoffman, E. (2017). Development of a behavioral 
activation–based intervention for cigarette-smoking young adults. Cognitive and Behavioral Practice, 
24(1), 101–114. https://doi.org/10.1016/j.cbpra.2016.03.004 
Manos, R. C., Kanter, J. W., & Luo, W. (2011). The behavioral activation for depression scale-short form: 
Development and validation. Behavior Therapy, 42(4), 726–739. 
https://doi.org/10.1016/j.beth.2011.04.004 
Matusiewicz, A. K., Carter, A. E., Landes, R. D., & Yi, R. (2013). Statistical equivalence and test-retest 
reliability of delay and probability discounting using real and hypothetical rewards. Behavioural 
Processes, 100, 116–122. https://doi.org/10.1016/j.beproc.2013.07.019 
Mendrek, A., Monterosso, J., Simon, S. L., Jarvik, M., Brody, A., Olmstead, R., Domier, C. P., Cohen, M. 
S., Ernst, M., & London, E. D. (2006). Working memory in cigarette smokers: Comparison to non-
smokers and effects of abstinence. Addictive Behaviors, 31(5), 833–844. 
https://doi.org/10.1016/j.addbeh.2005.06.009 
National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. 
(2014). The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon 
General. Centers for Disease Control and Prevention (US). 
http://www.ncbi.nlm.nih.gov/books/NBK179276/ 
Odum, A. L. (2011). Delay Discounting: I’m a K, You’re a K. Journal of the Experimental Analysis of 
Behavior, 96(3), 427–439. https://doi.org/10.1901/jeab.2011.96-423 
Patterson, F., Jepson, C., Loughead, J., Perkins, K., Strasser, A. A., Siegel, S., Frey, J., Gur, R., & Lerman, 
C. (2010). Working Memory Deficits Predict Short-term Smoking Resumption Following Brief 

 
KUMC – HRPP- 03/12/2015 
 
Page 19 of 20 
v.2 
                                                                           Eff 9/21 
 
 
Abstinence. Drug and Alcohol Dependence, 106(1), 61. 
https://doi.org/10.1016/j.drugalcdep.2009.07.020 
Raudenbusch, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis 
methods (Second Edition). Sage Publishing. 
Reimers, S., Maylor, E. A., Stewart, N., & Chater, N. (2009). Associations between a one-shot delay 
discounting measure and age, income, education and real-world impulsive behavior. Personality and 
Individual Differences, 47(8), 973–978. https://doi.org/10.1016/j.paid.2009.07.026 
Rounsaville, B. J., Carroll, K. M., & Onken, L. S. (2001). A stage model of behavioral therapies research: 
Getting started and moving on from stage I. Clinical Psychology: Science and Practice, 8(2), 133–
142. https://doi.org/10.1093/clipsy.8.2.133 
Shamosh, N. A., Deyoung, C. G., Green, A. E., Reis, D. L., Johnson, M. R., Conway, A. R. A., Engle, R. W., 
Braver, T. S., & Gray, J. R. (2008). Individual differences in delay discounting: Relation to 
intelligence, working memory, and anterior prefrontal cortex. Psychological Science, 19(9), 904–911. 
https://doi.org/10.1111/j.1467-9280.2008.02175.x 
Singer., J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event 
Occurrence. 
Sobell, L. C., & Sobell, M. B. (1992). Timeline follow-back: A technique for assessing self-reported alcohol 
consumption. In Measuring alcohol consumption: Psychosocial and biochemical methods (pp. 41–
72). Humana Press. https://doi.org/10.1007/978-1-4612-0357-5_3 
Wechsler, D. (1997). Wechsler Adult Intelligence Scale-III (WAIS-III) manual. The Psychological 
Corporation. 
Yoon, J. H., Higgins, S. T., Heil, S. H., Sugarbaker, R. J., Thomas, C. S., & Badger, G. J. (2007). Delay 
discounting predicts postpartum relapse to cigarette smoking among pregnant women. Experimental 
and Clinical Psychopharmacology, 15(2), 176–186. https://doi.org/10.1037/1064-1297.15.2.186 

 
KUMC – HRPP- 03/12/2015 
 
Page 20 of 20 
v.2 
                                                                           Eff 9/21 
 
 
 
 
 
 
 
 
 
APPENDIX I: VULNERABLE POPULATIONS 
 
I.     Cognitively or decisionally impaired individuals: Cognitively or decisionally impaired individuals 
will be excluded from the study. 
 
II.     Children: Children (below 18 years of age) will be excluded from the study. 
 
III.     Pregnant women: Pregnant women will will not be targeted for inclusion. 
 
IV.     Prisoners: Prisoners will not be targeted for inclusion. 
 
V.     Students and/or Employees: Students and employees will not be targeted for inclusion.