A Mobile App Based Cognitive Dissonance Intervention for Smoking Cessation
Phase: NA
Conditions: Smoking Cessation
Sponsor: Oregon Research Behavioral Intervention Strategies, Inc.

 
 
 
 
 
 
 
 
 
A Mobile App Based Cognitive Dissonance Intervention  
for Smoking Cessation (CoQuit) 
 
DP006495-01 
 
Study Protocol and Analysis: 4/4/2019 
Informed Consent: 5/5/2020 
 
 

 
 
A. SPECIFIC AIMS 
Despite overall declines in the rate of tobacco use in the United States over the past 30 years, current daily 
smokers continue to be of great concern due to their extremely high risk for long-term health problems and 
death.1,2 There has been extensive research evaluating a wide range of smoking cessation approaches over 
the past 40 years. Recent reviews note that there has been significant progress in the application of both 
clinical and public health interventions to help smokers quit. They also concluded that the overall success rate 
of smokers quitting had not significantly improved.3 New and innovative, theory-driven approaches are needed 
to both increase the reach of effective interventions and to improve the overall abstinence and long-term quit 
rates. Individual, group and public health interventions, both with or without adjunctive aids such as nicotine 
replacement therapy, have generally used some combination of cognitive behavioral interventions in varying 
combinations, but there remains a need for novel, theory-driven approaches to enhance quit rates and 
increase reach and engagement, such as those offered via computer or mobile app. 
One approach that has demonstrated preliminary success in improving smoking cessation rates is 
cognitive dissonance induction,4-6 which is based on the premise that behavior change can be elicited through 
exposure to high levels of cognitive inconsistencies between their beliefs and behaviors.7 For example, having 
an individual who smokes present a verbal argument to a young person, outlining specific reasons why he/she 
should avoid smoking initiation is a cognitive dissonance induction strategy that has been examined in prior 
studies.4 Cognitive dissonance has been widely researched and applied in the physical and mental health 
arenas, and has been shown to be successful at treating obesity,8 improving healthy eating,9 reducing 
fears,10,11 treating chronic illness,12 improving safe sex practices,13 and has been used as a preventive measure 
in the development of eating disorders.14 In addition to its effectiveness in improving overall health, cognitive 
dissonance approaches have also shown success in treating substance use,15,16 reducing the initiation of 
smoking,17 and improving outcomes for smoking cessation.6 
Computer-based and mobile app-based interventions have been successfully utilized for behavior change 
and for a number of physical and mental health problems,18,19 as well as smoking and smokeless tobacco 
cessation.20-22 Computer- and internet-based interventions offer increased accessibility and flexibility, as well 
as increased confidentiality and anonymity, all of which increase the number of individuals that can be 
treated.23-25 
Given the preliminary success of cognitive dissonance approaches at treating tobacco and substance use, 
and other health-related problems, coupled with positive outcomes and increased accessibility of mobile-based 
app interventions, the current proposal is aimed at adapting and testing the feasibility of a cognitive dissonance 
intervention (CDI) delivered via a mobile app for current daily smokers that is based on a previously piloted 
computerized cognitive dissonance intervention for smoking cessation. Our group has a long history of 
developing and implementing successful interventions with high-risk, substance-using adults and youth, and 
testing successful tobacco cessation interventions.26-28 Our group also has expertise in developing, 
implementing and testing successful cognitive dissonance intervention protocols,4,29 and in developing and 
testing the use of mobile apps.20,21 The proposed CDI mobile app will be based on the primary cognitive 
dissonance cessation components tested in our previous work with adult smokers, and on intervention 
components shown to be central to smoking cessation. Given the need for innovative, theory-driven 
approaches to augment current smoking cessation treatment, the potential public health impact of the 
proposed intervention is very high – especially given the use of a mobile app format that can reach high risk, 
underserved populations of smokers and can be broadly implemented at minimal expense. 
Specific aims are as follows: 
1. Design and create a prototype mobile app that uses a cognitive dissonance induction approach (CDI) 
that targets daily adult smokers who are interested in quitting. An iterative approach using focus groups 
of adult smokers will be used to inform the design and functionality of the first 3 modules of the CDI 
mobile app. 
2. Assess program navigation and usability testing on the first 3 modules of the CDI mobile app with daily 
adult smokers, and prepare the final prototype for pilot testing and evaluation. 
3. Evaluate the prototype app by having 60 daily adult smokers recruited through social media to complete 
the first 3 modules. Usability data, system log data on program use, and participant satisfaction data will 
also be analyzed. Input from participants will be gathered to incorporate additional features to be 
developed during Phase II. Significant changes in quit attempts, number of days without smoking 
(smokefree days) and changes in smoking attitudes and behavior will be used to determine the efficacy 
of the Phase I program and evidence for proceeding to Phase II development and evaluation. 

 
Research Strategy 
 
 
 
B. SIGNIFICANCE 
 
B.1. Importance of smoking cessation 
Smoking is the leading cause of preventable death in the U.S.,1,2 accounting for approximately 443,000 
deaths, which is 20% of all deaths annually.1,23 Despite overall declines in the rate of tobacco use in the United 
States over the past 30 years, improving quit rates among current smokers continues to be a significant public 
health focus given the high risk for long-term negative health outcomes.2 There has been extensive research 
evaluating a wide range of smoking cessation approaches over the past 40 years, and the 2008 Clinical 
Practice Guideline for treatment of tobacco use and dependence summarized the efficacy of smoking 
cessation approaches based on more than 8700 research articles. Although there has been significant 
progress in the application of both clinical and public health interventions aimed at smoking cessation, 
researchers have concluded that the overall success rate of these interventions has not shown significant 
improvement.3 New, innovative, theory-driven approaches are needed to both improve the overall abstinence 
and long-term quit rates, as well as to increase the reach of effective interventions. 
B.2. Cognitive Dissonance-based intervention approaches 
One theory-driven approach that has shown promise as a basis for intervention development is cognitive 
dissonance induction. Cognitive dissonance theory is based on the premise that individuals strive toward 
consistency between their beliefs and behaviors.7 When inconsistencies between attitudes, beliefs or 
behaviors occur, individuals tend to adjust their beliefs or behaviors in order to reduce the discomfort of the 
dissonance that is elicited by the inconsistency. Reducing cognitive dissonance can be achieved in one of 
three ways: 1) adjusting one or more attitudes or behaviors to make the relationship between the two 
consistent, 2) acquiring new information that offsets the dissonant belief, or 3) reducing the importance of the 
attitudes or beliefs so that the inconsistent behavior can continue. 
Interventions that use cognitive dissonance to elicit behavior change do so through situations that create 
high levels of cognitive dissonance. Regardless of the behavior being targeted, there are several common 
concepts that are central to effective cognitive dissonance induction. First, participation in the induction activity 
must be voluntary. Voluntary participation requires the individual to attribute the inconsistency between beliefs 
and behaviors as existing within themselves, rather than being due to demands of a given situation.7 Effortful 
involvement (i.e., actively engaging in treatment exercises) is also required, and is believed to result in greater 
dissonance and greater motivation for change.30 And finally, public statements of beliefs (i.e., counter- 
attitudinal advocacy) are thought to elicit heightened dissonance responses.31 In fact, Roehrig et al32 have 
shown counter-attitudinal advocacy to be successful in isolation of the other dissonance-inducing components 
(voluntariness, effortful involvement). Counter-attitudinal advocacy activities that are often used to induce 
dissonance include preparing and delivering speeches or statements about personal beliefs, role-plays where 
individuals act out a particular behavior, or making public commitments. Given the central role that counter- 
attitudinal activities appear to play in eliciting cognitive dissonance, these activities are a core component of 
the proposed cognitive dissonance mobile app intervention (CDI). 
Cognitive dissonance has been widely researched and applied in the physical and mental health arenas. In 
particular, increasing cognitive dissonance has been shown to be successful at treating obesity,8 improving 
healthy eating,9 reducing fears,11,12 treating chronic illness,13 improving safe sex practices,14  and has been 
used as a preventive measure in the development of eating disorders.10 In their study of eating disorders, Stice 
and colleagues33 showed that participants in a cognitive dissonance induction intervention who voluntarily 
critique the thin beauty ideal in verbal, written, and behavioral exercises (voluntariness, counter-attitudinal 
advocacy) resulted in significant reductions in the thin-ideal internalization, which putatively decreased body 
dissatisfaction, unhealthy dietary behaviors, negative affect, and eating disorder symptoms. 
Of particular relevance, cognitive dissonance approaches have also shown success in treating substance 
use,15,16 reducing the initiation of smoking,17 and improving short-term outcomes for smoking cessation.4-6 In 
one study, Simmons et al.4 demonstrated greater quit rates at one-month follow up for smokers who engaged 
in video-taped discussions of the consequences of smoking delivered via computer. Although prior study 
results are promising, no long-term significant outcomes have been found, which suggests that increased 
exposure to dissonance induction activities (dosage) and reach of cognitive dissonance induction approaches 
might yield improved smoking abstinence outcomes. Guided by prior research, the proposed CDI intervention 
specifically provides increased opportunity for exposure to cognitive dissonance by including dissonance 
induction activities in each of the proposed CDI modules. In particular, we propose to offer the participant 
multiple opportunities for counter-attitudinal activities and public statements. Additionally, the mobile app 
format allows for increased access and reach of the intervention. The CDI app will be based on prior cognitive 

 
Research Strategy 
 
 
 
dissonance intervention activities that have demonstrated effectiveness and will specifically build on Consultant 
Simmons’ prior work with cognitive dissonance induction via video-recorded tasks for smoking cessation.4-6 
B.3. Mobile behavioral health-based interventions 
The utilization of mobile applications for smoking cessation and other addictive behaviors has increased 
over the past several years due to the low cost, ease of use, and increased availability via smartphones. 
Smartphone use has grown considerably in recent years, with more than 90% of adults in the U.S. currently 
estimated to be relying on smartphones daily,34 and as mobile phone data plans have become less costly, 
many of these individuals have turned to their mobile devices as their primary internet connection.35 Use of 
mobile apps has continually increased over the past several years and it is currently estimated that US adults 
spend an average of nearly 3 hours per day doing non-voice related activities on their smartphones and have 
an average of 80 apps. In addition, within the past three years, watching and recording videos has become 
commonplace on mobile phones, with an estimated 75% of people using their smartphones to record and 
access video.36 
One of the primary benefits of mobile app interventions is the ability to provide support for introducing new 
skills and for mobile content to be more readily delivered (pushed) to participants when and where they need it. 
Mobile interventions proactively push content to participants without requiring them to visit a computer.37 The 
proactive outreach of mobile interventions is especially critical given the limited use (engagement) of websites 
found in tobacco cessation interventions.38-40 
The term mHealth has even been coined to refer to programs that are delivered via mobile communication 
devices.41,42 While the term “mobile” has come to describe portable technology devices, Beale has asserted 
that the user is mobile, not just the technology: “…it is about computing for users who are not in a single 
location, but are moving around…computing whilst on the go as well as when at their destinations.”43 We 
propose to use automated calls and text messaging to extend the reach and impact of the intervention. 
Little research has been reported on the effects of mobile behavioral-health-based interventions for 
smoking cessation, but the results that are available have been promising.44 Although NCI public health 
initiatives (e.g., QuitGuide, QuitSTART) are currently available, they have not been evaluated for efficacy. 
Given the increased reach of mobile-based interventions, coupled with evidence that internet-based delivery 
systems might be an effective method for delivering cognitive dissonance interventions, suggests that a 
cognitive dissonance mobile app for smoking cessation might be a feasible and novel treatment approach. It is 
important to note that even modest absolute abstinence rates can translate into very significant public health 
impact (reach X efficacy) given the large number of tobacco users who could be reached through mobile 
interventions.45,46 
B.4. Using technology-based delivery methods 
Overall, the high cost and labor-intensive nature of face-to-face interventions has made the development 
and testing of electronically-delivered treatments an attractive modality due to their affordability and potential 
for dissemination. Such interventions have been successfully utilized for behavior change and for the treatment 
of mental health problems, including depression,19 fears,47 healthy eating18 and smoking cessation.20-22 
Computer and mobile app-based interventions offer increased accessibility and flexibility, as well as greater 
confidentiality and anonymity, all of which increase the number of individuals that can be treated.24,25 
There is a growing body of reports and published studies that have described encouraging results for web- 
based interventions for smoking cessation48-51 and a recent meta analysis of RCTs for smoking cessation 
concluded that there is sufficient clinical evidence to support the use of web- and computer-based smoking 
cessation programs for adult smokers.52 Additionally, a number of computer-based cognitive dissonance 
interventions have been developed and tested. For example, in their study of female college students with 
body dissatisfaction, Stice, Durant, Rohde & Shaw53 evaluated the use of an internet-based program for the 
prevention of eating disorders. This study found that the internet-based participants showed significant 
reductions in eating disorder risk factors and symptoms compared to the control conditions at 1- and 2-year 
follow-ups. More recently, Chithambo and Huey54 developed and tested an eating disorder prevention 
intervention delivered in a web-based format. Results indicated that both of the internet-based interventions 
produced significantly greater reductions in body dissatisfaction, thin-ideal internalization, and depression 
compared to the no intervention control condition. 
Although it is difficult to draw strong conclusions from the emerging research on electronically delivered 
interventions because of the limited number of studies and differences in methodologies – including the extent 
to which online programs were supplemented by counseling (in-person or phone calls) or pharmaceutical 
supplements – overall conclusions of these meta-analyses support the superiority of web-based interventions 
compared to non-web-based interventions across a broad range of health behaviors.52,55 However, despite 

 
Research Strategy 
 
 
 
positive preliminary evidence supporting computerized smoking cessation interventions, further research is 
needed. In fact, a recent Cochrane meta-analysis of web-based cessation studies concluded that “…more 
rigorous studies comparing the long-term effects of Internet interventions with non-Internet interventions or no 
intervention at all are needed in order to determine the true long-term effectiveness of the internet as a tool for 
smoking cessation.”56 
B.5. Commercialization Potential of the Product 
The primary markets for the proposed CDI mobile app are entities that offer smoking cessation services to 
their customers. While there is a very large number of smokers in the United States estimated at more than 34 
million adults, targeting smokers directly is challenging. We would focus our marketing to hospitals, clinics, VAs 
and other entities that could offer this efficacious intervention to smokers in their care. As part of our efforts in 
Phase I we will further assess the potential customer base and highlight the unique motivational aspects of the 
CDI intervention. We expect to license the use of the mobile app and charge fees based on the number of 
users for the licensee. 
C. INNOVATION 
The proposed project is innovative in three primary ways. First, the proposed CDI mobile app will be the 
first dissonance induction-based mobile app for smoking cessation. Second, the proposed study focuses on 
both the initiation of quit attempts, as well as overall quit rates. The dual focus on increasing quit attempts and 
smoking cessation rates will help to inform the scientific knowledge of proximal outcomes that might inform 
intervention efforts aimed at more distal outcomes. And finally, the mobile app-based format – if shown to be 
successful at improving smoking quit rates – lends itself to improved accessibility across all classes of 
smokers. One significant limitation of existing face-to-face cognitive dissonance-based programs is cost and 
limited access to treatment for individuals without transportation. We believe that our program will be very 
attractive, as the mobile app-based format can greatly expand reach – both as a standalone program and as 
an adjunct to existing interventions. The mobile app intervention is also likely to appeal to underserved 
smokers and younger smokers who use their mobile phones for internet access and who frequently download 
apps for various personal interests and supports. Given the need for innovative smoking cessation programs 
that are low-cost and easy to access, the social impact of the proposed CDI intervention is high. 
D. APPROACH 
D.1. Overview 
The primary goal of the proposed Phase I project is to develop and evaluate a cognitive dissonance mobile 
app intervention for smoking cessation (CDI). The CDI app will build upon previous tobacco cessation 
treatment conducted by Co-I Severson and Consultant Simmons, on the substance abuse cessation and 
mobile-app treatment research conducted by PI Smith and Co-I Severson, and on the cognitive dissonance 
intervention research conducted by Co-I Yokum. Given our extensive experience developing and testing 
successful smoking cessation and cognitive dissonance interventions, as well as developing and testing mobile 
app interventions, we will focus our energy on effectively integrating these areas of study into an easy-to- 
administer mobile app intervention program that is attractive and engaging. 
D.2. Research and Development Team 
Dana K. Smith, PhD, Principal Investigator, is a Research Scientist at Oregon Research Institute and 
Oregon Research Behavioral Intervention Strategies. Dr. Smith’s research has focused primarily on the 
development and treatment of co-occurring substance use and criminal behavior. Dr. Smith has taken the lead 
in developing three R01 interventions aimed at reducing co-occurring problems in substance-abusing 
participants. In addition, she and Dr. Severson have worked together to develop and test a mobile app for the 
treatment of substance use (see NIH biosketch). 
Herb Severson, PhD, Co-Investigator, is a Senior Scientist at Oregon Research Institute and has 
developed and authored several interventions for tobacco cessation and other health-related interactive media 
programs. He has received national recognition for his work in health promotion and in research to practice 
activities and recently received the Research to Practice Award from the Society for Behavioral Medicine. Dr. 
Severson has been an investigator on more than 50 NIH funded research grants and has published more than 
150 research reports in professional journals. A recent study was the development and evaluation of a mobile 
app for smoking cessation (Grant #R01CA172205) and he is recognized as an expert in tobacco cessation. 
Sonja Yokum, PhD, Co-Investigator for this project, is a Research Scientist at the Oregon Research 
Institute. Her program of research focuses on the understanding of neural and biological risk- and maintenance 
factors for eating pathology and addictive behaviors. Dr. Yokum has conducted several randomized eating 
disorder and obesity treatment trials involving the development and testing of cognitive dissonance 
interventions. 

 
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Vani Simmons, PhD, Consultant for this project, is an Associate Member at the Moffitt Cancer Center and 
Professor at the University of South Florida, and has conducted successful RCTs of cognitive dissonance 
interventions for smoking cessation among young adults. In particular, she is focused on developing and 
testing experiential, theory-based, web-interventions for college smokers. Dr. Simmons has also conducted 
research on the development of culturally appropriate smoking prevention and intervention efforts. 
Richard Brown, PhD, Consultant for this project, is an expert in tobacco cessation and has conducted 
extensive work in innovative smoking cessation studies. He has collaborated with Dr. Severson on several 
previous grants, including both web and mobile app programs for tobacco cessation. 
D.3. Contractors 
Twenty Ideas. Mike Biglan and the Twenty Ideas team have a successful history of developing computer- 
and mobile-app based interventions. Team members at Twenty Ideas have designed and built hundreds of 
web-based and mobile apps, including those funded by NIH, the Department of Education and the National 
Science Foundation. They have been involved in developing several health-related mobile apps, and have 
extensive experience utilizing the SBIR funding mechanism. 
D.4. Phase I SBIR Project Timeline, Benchmarks, and Procedures 
This Phase I SBIR will be conducted in two stages: 1) Product development and usability testing, and 2) 
pilot testing. Stage 1 and Stage 2 are outlined below and are expected to take approximately 6 months each. 
D.4.a. Stage 1: Product Development 
Our approach to developing the CDI mobile app is informed by three previous areas of our work: (1) the 
work of Drs. Smith and Severson in developing and testing innovative computer- and mobile-app based 
approaches for tobacco and substance cessation programs, (2) the prior research of Dr. Yokum in designing 
and examining cognitive dissonance interventions, and (3) the considerable prior work of Dr. Simmons in 
developing and assessing computerized cognitive dissonance interventions for tobacco cessation. 
The proposed CDI intervention will consist of 9 modules that will be delivered via mobile app. During Stage 
1, we plan to develop the initial 3 modules of the CDI app in order to examine the feasibility and usability of the 
app; the remaining 6 modules are proposed to be developed during a Phase II SBIR application. As outlined 
previously, three concepts are central to eliciting cognitive dissonance: voluntariness, effortful involvement, and 
counter-attitudinal advocacy. Building on the cognitive dissonance work by Co-I Yokum and Consultant 
Simmons, we have carefully integrated these concepts into the proposed session modules. We have included 
each of the three components into each module. Based on the strong relationship between counter-attitudinal 
advocacy and cognitive dissonance found in previous studies,6,7 we included the need to make a public 
statement – either in letter format or verbal statements to family and friends – in each module as well. Given 
that Consultant Simmons found reduced smoking rates after one two-hour intervention with unmotivated 
smokers who made one public video statement of their negative beliefs of smoking, we believe that the 
proposed format of implementing all three components into each of nine modules will sufficiently increase the 
opportunity for dissonance induction. An overview of the core components and their relationship to dissonance 
induction is outlined in the Curriculum Table in Human Subjects. 
Investigators will work with the technical team at Twenty Ideas, a trusted and experienced technology 
vendor who has a team that has developed previously-tested substance use cessation programs. Twenty 
Ideas will build a complete program with new infrastructure, logic, and information architecture using and 
JavaScript scripting combined with HTML and CSS. Animation and interactive content will use DHTML 
(Dynamic HTML). During development and deployment, the project database will be housed at a secure web 
facility on Amazon Web Services in a PostgreSQL database on a server running a Linux-based operating 
system. Data from the mobile app will interface with the project database through TLS (Transport Layer 
Security) encrypted by the server. Researchers will have secure access to project data—including participant 
reports and management utilities—through an administrative interface built on Node.js technologies. These 
fully automated, stand-alone, technology-based interventions will work appropriately on popular, modern Web 
browsers on both Macintosh and Windows computers. 
In order to maximize reach with our intervention, we have structured the primary experience for the users 
to be on their mobile smartphone. A core piece of this experience is for a participant to watch a video, post it in 
a small public support group forum that we assign them to that includes approximately 8 participants, and then 
easily respond to their small group with encouraging and supportive comments. In addition, this model works 
well even if the group lives in various parts of the country and doesn't require geographically proximate groups. 
Groups of participants will be designated on a rolling basis, where a “group” will be assigned for every 8 
participants enrolled. Twenty Ideas has extensive experience creating “work groups” and chat rooms for web- 
and mobile-app programs. 

 
Research Strategy 
 
 
 
To implement the platform, Twenty Ideas has provided an architectural schematic that fits the necessary 
participant experience for the study, the data needs, as well as the budget submitted. With over fifteen years of 
experience designing and developing web and mobile applications, including numerous behavioral 
interventions, the Twenty Ideas team is confident with this approach. In addition, the team has experience in 
the development of video playback and recording solutions such as the Marco Polo video chat that works with 
millions of users. For this project, we plan to use the framework Ionic that works on both iOS (i.e. iPhones) as 
well as Android devices. To support easy video recording embedded into the App, our plan is to use the Ziggeo 
video recording Software Development Kit (SDK). Lastly, as participants use the App, their information will be 
stored off of the devices so we will use the Node.js framework and PostgreSQL database to collect, store, and 
make accessible key study data. 
D.4.1.a. Focus groups (N=20) 
We will incorporate an iterative formative process involving two focus groups of 10 participants each. The 
focus groups will be conducted at ORI by PI Smith and Co-I Severson. Because of our extensive experience in 
developing and testing cognitive dissonance and smoking cessation interventions, we have well-developed 
ideas for the “look and feel” of the program, which will aid in our initial mockups of the concepts, and graphics 
for the intervention modules. We will present these ideas and graphics to the initial focus group and use their 
feedback to refine the materials for a second focus group of participants that are representative of the target 
audience for the program. 
Based on feedback from the first focus group, we will develop prototype versions of the program using 
Marvel, a design and rapid prototype development tool that yields functional mockups for users to interact with 
before any programming takes place. During an iterative process we will refine the mockups, present them to 
five test users, solicit their feedback, and continue to modify and refine the mockups until we arrive at an 
acceptable design and feature set. Session transcripts will be assessed both manually and using Atlast.ti,57,58 a 
computer aided qualitative data analysis software program to identify themes. Next, we will finalize and create 
all the media assets for the app, including text and graphics, images, narration or other audio elements, and 
build all program screens and user controls. We will incorporate a simple user registration component to allow 
for tracking of app usage while also ensuring security of user-collected data. Throughout the development 
process, Twenty Ideas designers and programmers will create and iterate rapid prototypes of the app to make 
sure the content, functionality, and look and feel of the app conforms to the overall research goals of the 
project. Participants will receive a $30 gift card for their participation in focus groups or usability testing. 
D.4.1.b. Usability Testing (N=5) 
We will present the initial prototype to five test users for preliminary usability testing in which the participant 
will be observed using the program and then asked to talk aloud about their experience to help us better 
understand ease of navigation and program use. Observations and interviews with usability participants is a 
great help in discovering potential problems with program navigation comprehension of key concepts and 
interactive activities. Mobile app-based components will embody established usability standards and will 
adhere to their recently emerging usability guidelines. Individual test sessions will be held, with hands-on use 
of functioning program components. Based on our observations and interviews we will move on to conduct a 
more complete programming of the proposed intervention and prepare for pilot testing. One unique feature of 
the CDI program will be the use of video for making public statements about attitudes, beliefs and intentions. 
The usability testing will allow us to fully test the use of the video feature with adult participants who currently 
smoke. The program will be used by the participants on their own mobile devices to emulate the way that the 
program will be used in the evaluation study. The key features that need testing will be the video components 
that are recorded and posted by participants. We will test the ability of participants to upload video to the app 
and our ability to view and upload the video to their support group. The platform will allow us to view and 
monitor the video before it is shared with the support group of peers. 
D.4.2. Stage 2: Product Evaluation (N=60) 
We will conduct a pilot test of the CDI mobile app with 30 male and 30 female adult smokers (N=60). 
Feasibility, usability, participant satisfaction, and pre-/post- intervention outcomes of smoking will be evaluated 
in the pilot study. Data on: 1) frequency and duration of app use, 2) number of modules completed, 3) cognitive 
dissonance and motivation to quit, and 4) smoking attitudes and behavior, including motivation to quit, quit 
attempts, and number of days without smoking (smokefree days), will be examined pre- and post-intervention. 
Participants will be compensated using gift cards to Amazon in the following increments: $30 for the baseline 
assessment, $35 for the 1-month assessment, and $40 for the 3-month assessment. 
D.4.2.a. Participants. Details regarding sample characteristics, eligibility criteria, recruitment and retention 
are described in the Human Subjects. Briefly, participants will include both male and female adult smokers 
recruited from the United States. We have a long history of successful recruitment of smokers, and have 
 

 
extensive experience utilizing recruitment efforts to enroll smokers and tobacco users in mobile app-
based intervention programs. Inclusion criteria will be as follows: 1) age 18 or older, 2) self-reported daily 
smoking, 3) having a valid home mailing address, 4) English-speaking, 5) access to a smartphone with 
video capability for the duration of the project, 6) not currently enrolled in or participating in any tobacco 
cessation programs, and 
7) expressed desire to quit smoking. 
D.5. Data Collection Procedures 
D.5.1. Overview and timeline for the pilot study. In the proposed evaluation study, a total of 60 
participants will be recruited and baseline assessed during Year 1. We anticipate that approximately 10-
25% of these will fail to complete the study; however, we will employ an intent-to-treat analysis strategy, 
which will include all participants. We will conduct baseline assessments immediately after enrollment 
and consent; all measures completed at 1-, and 3-month follow-up assessments will be provided online. 
The baseline assessment will primarily measure participant risk factors, as well as past and current 
cigarette and other tobacco use, readiness to quit, quit attempts and cessation in the past year, and will 
consist of questionnaires administered using Qualtrics; none of the assessments will be done via the 
mobile app. 
The 1-month assessment will focus on usability, cognitive dissonance, motivation to quit, and short 
term outcomes such as making a quit attempt, use of the app (dosage), number of cigarettes smoked, 
and days abstinent from smoking. For the 3-month assessment, the focus will be on cessation outcomes, 
including both point prevalence (i.e., no smoking in the past 7 days; no smoking in the past 30 days) and 
sustained abstinence, which is defined as sustained abstinence between the 1- month and 3- month 
assessment. We will also assess quit attempts at each assessment. Non-responders to the request to 
complete a follow up assessment will be sent email and text messages to encourage completion of the 
assessment. We will continue to prompt completion for 14 days following the initial request for the one 
month assessment and there will be a 30 day window for completion of the 3-month assessment. 
D.5.2. Pilot Study Measures. Program navigation and usability will be assessed during usability 
testing and for the evaluation participants over the one month of use, and will include reports of: 1) ease 
of use, 2) perceived benefits of using the app, and 3) suggestions for product development 
modifications. Participants will also provide ratings on product satisfaction and usability on a 7-point 
Likert Scale. Qualitative data gathered from the focus groups will be recorded and evaluated with the 
goal of identifying challenges to using the app, product satisfaction, and suggested modifications. This 
information will then be used to guide adaptations in a Phase II SBIR application. In addition to 
qualitative data, login tracking information from the app will be used to assess each participant’s: 1) 
frequency and duration of app use, 2) number of modules completed, and 3) type and frequency of 
substance use. These data will be used to evaluate treatment engagement and adherence, as well as 
pre- and post- changes in tobacco use. 
A full description of measures is included in the Human Subjects. Briefly, the following will be used to 
examine pre- and post- changes in smoking behavior, cognitive dissonance, and motivation to quit: 1) 
Nicotine Dependence, 2) Past and Current Tobacco Use, 3) Motivation to Quit, 4) Quit Attempts, and 5) 
Cognitive Dissonance. Nicotine dependence will be measured at baseline and at each follow-up 
assessment using the Fagerström Test for Nicotine Dependence58 and items that assess withdrawal 
experiences. Past and current tobacco use will be assessed at each time point, including type, 
frequency, and duration of use. Motivation to quit will be assessed at baseline by asking participants if 
they want to quit within the next 30 days and at follow-up assessments in terms of stages of change.59 
We will also use an adaptation of the Contemplation Ladder60 that we have used extensively in our prior 
research40,61 and have found in predicting tobacco cessation.61,62 Quit attempts will be measured by the 
number of intentional quit attempts that last at least 24 hours, duration of quitting, and use of 
pharmacological adjuncts at each time point. Cognitive dissonance will be measured using the 
Dissonance Thermometer.63,64 Prior research63 has shown that the 3- item discomfort factor of the 
Dissonance Thermometer represents the affective expression of cognitive dissonance. 
D.5.3. Statistical Design and Power Overview. 
This project will test the promise of efficacy of the CDI mobile app with a pre-training, post-training, 
and 3- month follow-up non-experimental design with 60 adult daily smokers. We hypothesize that after 
use of the CDI mobile app participants will show increases in quit attempts and number of non-smoking 
days, and improvement in smoking attitudes and behaviors. We will use random effects growth models to 
test change in normally distributed outcomes and the Wilcoxon signed-rank test for non-normally 
distributed outcomes. We also propose ancillary analysis (e.g., dose-response) to bolster our confidence 
in the non-experimental design. Details of our analytic approach, approach to missing data, power 
analysis (power >.80 to detect medium effects (d=.39) for pre-post change), and feasibility benchmarks 
are provided in Statistical Design and Power in the Human Subjects. 

 
 
1776 Millrace Drive  Eugene, Oregon 97403-2536 
                        541-484-2123  Fax 541-484-1108  TDD Relay 1-800-735-2900 
 
 
Informed Consent for Participation  
 
Study Title: CoQuit Study 
Principal Investigators: Dana Smith, Ph.D. and Herb Severson, Ph.D. 
Sponsor: NIH 1 R43DP006495-01-00 
 
 
You are invited to participate in a research study that will test a new program designed to provide support to adults 
who smoke and want to reduce or discontinue their use of cigarettes.  This study is being conducted by Dana Smith, 
Ph.D., Herb Severson, Ph.D., and Sonja Yokum, Ph.D. of Influents Innovations in Eugene, Oregon and is funded by 
the National Institute of Health (NIH 1 R43DP006495-01-00). We want everyone in the study to understand what it is 
about.  Please read this form and ask any questions you may have before agreeing to participate in the study.   
 
What You Will Be Asked to Do 
If you decide to participate, you will be asked to complete a survey and use an app that is being developed as a tool 
to help adults decrease or stop smoking. This survey will take about 20 minutes and can be done on your phone or 
mobile device. The survey consists of questions about your past and current use of cigarettes and your motivation to 
stop smoking. There are also questions about you, such as your age, living situation, education and employment.  
 
In the month following the first survey, you will be asked to use the CoQuit app and make an effort to reduce or 
discontinue your use of cigarettes. The app contains short videos of a narrator introducing online activities designed 
to help you stop smoking.  As part of this program, you will be connected to an online group of about 8 other study 
participants. The study activities involve making and posting videos so that you can provide and receive support 
around reducing or discontinuing cigarettes. These videos can only be seen by study staff and other adults in your 
online support group. After each activity, there will be a brief survey that will take less than 5 minutes to complete. 
After 3 months, you will receive a link for the second survey about using and quitting cigarettes. This survey will take 
about 20 minutes to complete. You will be asked how much you liked the app and if you found it to be helpful. You 
can also share any ideas you have about improving it.   
 
You will receive a check or Amazon gift card for completing surveys and study activities. You will get: 
 
 
 
$30 for the first survey 
 
 
 
$5 for each activity (there are 3 total) 
 
 
 
$60 for the second survey 
 
Use of Video-recordings 
One feature of this smoking cessation program is being part of an online group of adults who can support 
and encourage each other around their shared goal of reducing or stopping their use of cigarettes. You will 
be connected to about 8 other adults who are also in this study. Study activities include the group members 
making and sharing videos that focus on avoiding cigarettes. Study staff will control access to these groups 
and monitor activity for appropriateness and confidentiality. Videos must be appropriate for public viewing, 
may not contain any other people, and may not contain profanity or sexual references.  
 
Risks and What Will Be Done to Reduce the Risks 
There are some possible risks involved for participants.  We will be asking you questions about your thoughts and 
actions related to tobacco use and asking you to share some of these thoughts and actions with other adults who are 
also working to reduce their tobacco use. We will also ask for your opinion about the app after you use it. You might 
feel a little embarrassed or uncomfortable sharing information about yourself or your opinions. Remember, you are 
not required to answer any questions or complete any activity. 
 
We will be getting personal information from you. There is always the possibility that someone who is not authorized 
might see it. We take the following precautions to prevent any unauthorized person from having any access to the 
information you give us: 

 
 
• 
Any information you give us will be kept strictly confidential. All information will be kept in locked electronic 
files. We will remove all names from all the information we get (except the Informed Consent).  ID numbers 
will be assigned to the information you give us and only authorized staff will have access to the locked 
electronic file that links your name to your ID number.  
• 
We will do all we can to protect your confidentiality. However, because you will be using your phone to 
answer questions, take videos and watch videos, others near you might be able to figure out that you are in a 
study related to substance use.  
• 
We have a “Certificate of Confidentiality" which is a legal assurance from the federal government, which will 
help us protect your privacy even if the records are subpoenaed.  We will not give any information about you 
to anyone, unless you give us your written permission to do so. 
A description of this clinical trial will be available on http://www.ClinicalTrials.gov . This website will not 
include information that can identify you. At most, the website will include a summary of the research 
results. At the very end of the project, we will post a study consent form to the same website. The consent 
form will not have names on it. You can search this website at any time. 
Storage & Future Use of Your Information  
We may keep information about you forever. We do not know what studies we might do in the future. We 
would like your permission now to use or share your personal information without having to ask you again 
in the future. We will only use your information in other studies about smoking cessation.  
We will remove your name and any other information that identifies you before we use it in a new study. 
There is still a chance that someone could figure out that the information is about you.  
 
Benefits to You for Your Participation 
There are some benefits to you for taking part in this research project. You will contribute to the design of an app that 
will help efforts to reduce dependency on tobacco. Using this app may help you reduce or discontinue your use of 
cigarettes, which could have significant health benefits. 
 
Alternative Procedures 
There are other programs available to help you stop smoking. This study is testing a new program. You could 
explore other methods of reducing your use of tobacco instead of being in this study. 
 
Your Right to Withdraw from the Project 
Your participation is entirely voluntary and your decision whether or not to participate will involve no penalty or loss of 
benefits you might otherwise receive.  If you decide to participate, you can stop participating any time without 
penalty. You will receive checks or gift cards for each survey that you  complete. 
 
If you have questions about the research at any time, or if you have a visual or other impairment and require this 
material in another format, please call Holly Chedester or Erika James at 541-484-2123.  If you have questions about 
your rights as a research subject and/or research-related injury, call the Office for the Protection of Human Subjects, 
Oregon Research Institute, 541-484-2123.  ORI’s TDD number is 800-735-2900.  You will receive a copy of this form 
to keep. 
 
Your signature below indicates that you: 
• 
have read and understand the information provided above 
• 
willingly agree to participate 
• 
may withdraw your consent at any time and stop participating at any time without penalty 
• 
will receive a signed copy of this consent form via email  
 
I understand the research project as described above and I agree to participate. 
__________________________ 
________________________________     __ __/__ __/__ __ 
Signature 
 
 
 
Name (Please Print) 
 
 
Date 
 

 
 
Reference List 
 
1. 
CDC. Smoking-attributable mortality, years of potential life lost, and productivity losses -- United States, 
2000--2004. MMWR Weekly. 2008;57(45):1226-1228. 
2. 
USDHHS. The health consequences of smoking: A report of the Surgeon General. Atlanta, Georgia: 
U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National 
Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2004. 
3. 
Zhu S-H, Lee M, Zhuang Y-L, Gamst A, Wolfson T. Interventions to Increase Smoking Cessation at the 
Population Level: How Much Progress Has Been Made in the Last Two Decades? Tobacco control. 
2012;21(2):110-118. 
4. 
Simmons VN, Heckman BW, Fink AC, Small BJ, Brandon TH. Efficacy of an experiential, dissonance- 
based smoking intervention for college students delivered via the internet. J Consult Clin Psychol. 
2013;81(5):810-820. 
5. 
Simmons VN, Webb MS, Brandon TH. College-student smoking: an initial test of an experiential 
dissonance-enhancing intervention. Addictive behaviors. 2004;29(6):1129-1136. 
6. 
Simmons VN, Brandon TH. Secondary smoking prevention in a university setting: a randomized 
comparison of an experiential, theory-based intervention and a standard didactic intervention for 
increasing cessation motivation. Health psychology. 2007;26(3):268-277. 
7. 
Festinger L. A Theory of Cognitive Dissonance. Stanford: Stanford University Press; 1957. 
8. 
Axsom D, Cooper J. Reducing weight by reducing dissonance: The role of effort justification in inducing 
weight loss. 3rd ed. San Francisco, CA: Freeman; 1981. 
9. 
Stice E, Rohde P, Shaw H, Gau JM. Clinician-led, peer-led, and internet-delivered dissonance-based 
eating disorder prevention programs: Acute effectiveness of these delivery modalities. Journal of 
consulting and clinical psychology. 2017;85(9):883-895. 
10. 
Stice E, Marti N, Shaw H, O'Neil K. General and program-specific moderators of two eating disorder 
prevention programs. International Journal of Eating Disorders. 2008;41(7):611-617. 
11. 
Cooper J. Reducing fears and increasing assertiveness: The role of dissonance reduction. Vol 16; 
1980. 
12. 
Cooper J, Axsom D. Effort justification in psychotherapy. New York: Oxford; 1982. 
13. 
Leake R, Friend R, Wadhwa N. Improving adjustment to chronic illness through strategic self- 
presentation: an experimental study on a renal dialysis unit. Health psychology : official journal of the 
Division of Health Psychology, American Psychological Association. 1999;18(1):54-62. 
14. 
Stone J, Aronson E, Crain AL, Winslow MP, Fried CB. Inducing hypocrisy as a means of encouraging 
young adults to use condoms. Personality and Social Psychology Bulletin. 1994;20(1):116-128. 
15. 
Barnett LA, Far JM, Mauss AL, Miller JA. Changing perceptions of peer norms as a drinking reduction 
program for college students. Journal of Alcohol and Drug Education. 1996;41(2):39-62. 
16. 
Ulrich J. A Motivational Approach to the Treatment of Alcoholism in the Federal Republic of Germany. 
Alcoholism Treatment Quarterly. 1991;8(2):83-92. 
17. 
Killen JD. Prevention of adolescent tobacco smoking: The social pressure resistance training approach. 
Child Psychology & Psychiatry & Allied Disciplines. 1985;26(1):7-15. 
18. 
Oenema A, Brug J, Lechner, L. Web-based tailored nutrition education: results of a randomized 
controlled trial. Health education research. 2001;16(6):647-660. 
19. 
Selmi PM, Klein MH, Greist JH, Sorrell SP, HP E. Computer-administered cognitive-behavioral therapy 
for depression. Am J Psychiatry. 1990;147(1):51-56. 
20. 
Severson HH. Tobacco control research: A journey of discovery in prevention and cessation. Am J 
Health Behavior. 2006;30(6):567-579. 
21. 
Danaher BG, Severson HH, Crowley R, et al. Randomized controlled trial examining the adjunctive use 
of nicotine lozenges with MyLastDip: An eHealth smokeless tobacco cessation intervention. Internet 
Interventions. 2015;2(1):69-76. 
22. 
Graham AL, Carpenter KM, Cha S, et al. Systematic review and meta-analysis of Internet interventions 
for smoking cessation among adults. Substance Abuse and Rehabilitation. 2016;7:55-69. 
23. 
CDC. Health, United States. 2011; http://www.cdc.gov/nchs/hus/previous.htm. Accessed 14 December, 
2011. 
24. 
Leibert T, Archer Jr J, Munson J, York G. An Exploratory Study of Client Perceptions of Internet 
Counseling and the Therapeutic Alliance. Journal of Mental Health Counseling. 2006;28(1):69-83. 

 
 
 
25. 
Moore MJ, Soderquist J, C W. Feasibility and efficacy of a binge drinking prevention intervention for 
college students delivered via the Internet versus postal mail. Journal of American College Health. 
2005;54(1):38-44. 
26. 
Danaher BG, Severson HH, Andrews JA, et al. Randomized controlled trial of MyLastDip: a Web-based 
smokeless tobacco cessation program for chewers ages 14-25. Nicotine & tobacco research : official 
journal of the Society for Research on Nicotine and Tobacco. 2013;15(9):1502-1510. 
27. 
Severson HH, Gordon JS, Danaher BG, Akers L. ChewFree.com: evaluation of a Web-based cessation 
program for smokeless tobacco users. Nicotine & tobacco research : official journal of the Society for 
Research on Nicotine and Tobacco. 2008;10(2):381-391. 
28. 
Gordon JS, Severson HH, Seeley JR, S C. Development and evaluation of an interactive tobacco 
cessation CD-ROM educational program for dental students. Journal of Dental Education. 
2004;68(3):361-369. 
29. 
Stice E, Yokum S, Veling H, Kemps E, NS L. Pilot test of a novel food response and attention training 
treatment for obesity: Brain imaging data suggest actions shape valuation. Behaviour Research and 
Therapy. 2017;94(1):60-70. 
30. 
Green M, Scott N, Diyankova I, Gasser C, Pederson E. Eating Disorder Prevention: An Experimental 
Comparison of High Level Dissonance, Low Level Dissonance, and No-Treatment Control. Eating 
Disorders: The Journal of Treatment & Prevention. 2005;13(2):157-169. 
31. 
Aronson E, Fried C, Stone J. Overcoming denial and increasing the intention to use condoms through 
the induction of hypocrisy. American Journal of Public Health. 1991;81(12):1636-1638. 
32. 
Roehrig M, Thompson JK, Brannick M, van den Berg P. Dissonance-based eating disorder prevention 
program: a preliminary dismantling investigation. The International journal of eating disorders. 
2006;39(1):1-10. 
33. 
Stice E, Butryn ML, Rohde P, Shaw H, Marti CN. An Effectiveness Trial of a New Enhanced 
Dissonance Eating Disorder Prevention Program among Female College Students. Behaviour research 
and therapy. 2013;51(12):862-871. 
34. 
Lenhart A. A majority of American teens report access to a computer, game console, smartphone and a 
tablet. Teens, Social Media & Technology Overview 2015 2015; 
http://www.pewinternet.org/2015/04/09/a-majority-of-american-teens-report-access-to-a-computer- 
game-console-smartphone-and-a-tablet/. Accessed 4 April, 2019. 
35. 
Pew Research Center. Mobile Face Sheet. 2018; https://www.pewinternet.org/fact-sheet/mobile/. 
Accessed 2 April, 2019. 
36. 
Statista. Mobile share of global digital video plays from 3rd quarter 2013 to 1st quarter 2018. 2018; 
https://www.statista.com/statistics/444318/mobile-device-video-views-share/. Accessed 4 April, 2019. 
37. 
Klasnja P, Pratt W. Healthcare in the pocket: Mapping the space of mobile-phone health interventions. 
Journal of Biomedical Informatics. 2012. 
38. 
Christensen H, Mackinnon A. The law of attrition revisited. Journal Med Internet Res. 2006;8(3):e20. 
39. 
Eysenbach G. The law of attrition. Journal Med Internet Res. 2005;7(1):e11. 
40. 
Ritterband LM, Thorndike FP, Cox DJ, Kovatchev BP, Gonder-Frederick LA. A behavior change model 
for internet interventions. Annals of Behavioral Medicine. 2009;38(1):18-27. 
41. 
Wikipedia. mHealth. 2011; http://en.wikipedia.org/wiki/MHealth. Accessed 4 April, 2019. 
42. 
USDHHS. HHS announces Text4Health task force recommendcations and global partnership. 
https://www.infodocket.com/2011/09/21/hhs-announces-text4health-task-force-recommendations-and- 
global-partnership/. Accessed 4 April, 2019. 
43. 
Beale R. What does mobile mean? International Journal of Mobile Human Computer Interaction. 
2009;1(3):1-8. 
44. 
Whittaker R, Borland R, Bullen C, Lin RB, McRobbie H, Rodgers A. Mobile phone-based interventions 
for smoking cessation. The Cochrane Database of Systematic Reviews. 2009;Oct 7(4):CD006611. 
45. 
Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: 
The RE-AIM framework. American Journal of Public Health. 1999;89(9):1322-1327. 
46. 
Glasgow RE. eHealth evaluation and dissemination research. American Journal of Preventive 
Medicine. 2007;32(5 Suppl):S119-126. 
47. 
Ghosh A, Marks IM. Self-treatment of agoraphobia by exposure. Behavior Therapy. 1987;18(1):3-16. 
48. 
Cobb NK, Graham AL, Bock BC, Papandonatos G, Abrams DB. Initial evaluation of a real-world 
Internet smoking cessation system. Nicotine & tobacco research : official journal of the Society for 
Research on Nicotine and Tobacco. 2005;7(2):207-216. 
 

 
 
49. 
Etter JF. Comparing the Efficacy of Two Internet-Based, Computer-Tailored Smoking 
Cessation Programs: A Randomized Trial. J Med Internet Res. 2005;7(1):e2. 
50. 
Lenert L. Automating smoking cessation on the web. 2005; 
http://www.wati.net/presentations/watiII.lenert.pres.20050607.pdf. Accessed 6 December, 
2011. 
51. 
Strecher VJ, Shiffman S, West R. Randomized controlled trial of a web-based computer-tailored 
smoking cessation program as a supplement to nicotine patch therapy. Addiction (Abingdon, 
England). 2005;100(5):682-688. 
52. 
Myung SK, McDonnell DD, Kazinets G, Seo HG, Moskowitz JM. Effects of Web- and computer-
based smoking cessation programs: meta-analysis of randomized controlled trials. Archives of 
internal medicine. 2009;169(10):929-937. 
53. 
Stice E, Durant S, Rohde P, Shaw H. Effects of a Prototype Internet Dissonance-Based Eating 
Disorder Prevention Program at 1- and 2-Year Follow-up. Health psychology : official journal of 
the Division of Health Psychology, American Psychological Association. 2014;33(12):1558-1567. 
54. 
Chithambo TP, Huey SJ, Jr. Internet-delivered eating disorder prevention: A randomized 
controlled trial of dissonance-based and cognitive-behavioral interventions. The International 
journal of eating disorders. 2017;50(10):1142-1151. 
55. 
Wantland DJ, Portillo CJ, Holzemer WL, Slaughter R, McGhee EM. The Effectiveness of Web-
Based vs. Non-Web-Based Interventions: A Meta-Analysis of Behavioral Change Outcomes. J 
Med Internet Res. 2004;6(4):e40. 
56. 
Civljak M, Sheikh A, Stead LF, Car J. Internet-based interventions for smoking cessation. 
Cochrane Database of Systematic Reviews 2010;8(9):CD007078. 
57. 
Akre C, Michaud PA, Berchtold A, Suris JC. Cannabis and tobacco use: where are the 
boundaries? A qualitative study on cannabis consumption modes among adolescents. Health 
education research. 2010;25(1):74-82. 
58. 
Brooke J. SUS: A quick and dirty usability scale. In: Jordon PW, Thomas B, 
Weerdmeester BA, McClelland IL, eds. Usability evaluation in industry. London: Taylor & 
Francis; 1996:189-194. 
59. 
Danaher BG, Lichtenstein E, McKay HG, Seeley JR. Use of non-assigned smoking cessation 
programs among participants of a Web-based randomized controlled trial. J Med Internet Res. 
2009;11(2):e26. 
60. 
Glasgow RE, Mullooly JP, Vogt TM, et al. Biochemical validation of smoking status: pros, 
cons, and data from four low-intensity intervention trials. Addictive behaviors. 1993;18(5):511-
527. 
61. 
Danaher BG, Seeley JR. Methodological issues in research on web-based behavioral interventions. 
Ann Behav Med. 2009;38(1):28-39. 
62. 
Brendryen H, Kraft P, Schaalma H. Looking Inside the Black Box: Using Intervention Mapping 
to Describe the Development of the Automated Smoking Cessation Intervention ‘Happy 
Ending’. Journal of Smoking Cessation. 2010;5(1):29-56. 
63. 
Elliot AJ, Devine PG. On the motivational nature of cognitive dissonance: Dissonance as 
psychological discomfort. Journal of Personality and Social Psychology. 1994;67:382-394. 
64. 
Devine PG, Tauer JM, Barron KE, Elliot AJ, Vance KM. Moving beyond attitude change in the 
study of dissonance-related processes. In: Cognitive dissonance: Progress on a pivotal theory in 
social psychology. Washington, DC, US: American Psychological Association; 1999:297-323.