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Smoking rates in the United States have been reduced in the past decades to 15% of the general population. However, up to 88% of people with psychiatric symptoms still smoke, leading to high rates of disease and mortality. Therefore, there is a great need to develop smoking cessation interventions that have adequate levels of usability and can reach this population.
The objective of this study was to report the rationale, ideation, design, user research, and final specifications of a novel smoking cessation app for people with serious mental illness (SMI) that will be tested in a feasibility trial.
We used a variety of user-centered design methods and materials to develop the tailored smoking cessation app. This included expert panel guidance, a set of design principles and theory-based smoking cessation content, development of personas and paper prototyping, usability testing of the app prototype, establishment of app’s core vision and design specification, and collaboration with a software development company.
We developed Learn to Quit, a smoking cessation app designed and tailored to individuals with SMI that incorporates the following: (1) evidence-based smoking cessation content from Acceptance and Commitment Therapy and US Clinical Practice Guidelines for smoking cessation aimed at providing skills for quitting while addressing mental health symptoms, (2) a set of behavioral principles to increase retention and comprehension of smoking cessation content, (3) a gamification component to encourage and sustain app engagement during a 14-day period, (4) an app structure and layout designed to minimize usability errors in people with SMI, and (5) a set of stories and visuals that communicate smoking cessation concepts and skills in simple terms.
Despite its increasing importance, the design and development of mHealth technology is typically underreported, hampering scientific innovation. This report describes the systematic development of the first smoking cessation app tailored to people with SMI, a population with very high rates of nicotine addiction, and offers new design strategies to engage this population. mHealth developers in smoking cessation and related fields could benefit from a design strategy that capitalizes on the role visual engagement, storytelling, and the systematic application of behavior analytic principles to deliver evidence-based content.
Smoking rates in the United States have been reduced to 15% in the past decades [
Survey research indicates that this population has rates of adoption of mobile technology that range between 72% and 81% [
Despite the increasing number of digital interventions developed for people with SMI [
This lack of reports on the user-centered design process of mHealth interventions for smoking cessation is problematic, because (1) the determination of the active therapeutic ingredients delivered by an app should be the result of a careful design process, (2) poorly designed software systems have an impact on their ultimate efficacy and when not usable can be a waste of resources [
People with SMI can have very low levels of adherence to digital interventions [
In previous research, we found a direct link between key demographic factors and engagement with SmartQuit, a smoking cessation app designed for the general population. Specifically, we demonstrated that experiencing mental health symptoms, being female, and having low levels of educational attainment predicted low levels of engagement with the app at a 3-month follow-up [
From these initial studies, we planned to develop Learn to Quit, a smoking cessation app tailored to this often neglected and vulnerable population. Consistent with the need to report the user-centered design process of mHealth interventions, the aim of this paper was to describe the rationale, ideation, prototyping, design, user research, and final feature set of Learn to Quit, a smoking cessation app tailored to individuals with SMI that will be subsequently tested in a randomized controlled feasibility trial (clinicaltrials.gov NCT03069482).
Our user-centered design methods and materials are summarized in
Phases VI and VII are not part of the user-centered design process per se, but are important steps in design implementation, which are also documented in the user-centered design literature [
Methods and materials.
To better understand the needs of our target population, we sought to get the perspective of patients from this population and their providers. Expert guidance has been used in prior work to inform app development efforts [
Before designing the app, we prespecified 2 sets of design principles: (1) general learning principles based on applied behavior analysis and (2) design principles specific to individuals with SMI. Applied behavior analysis is a scientific discipline focused on developing strategies and behavior modification techniques in areas of social relevance based on principles of learning. Use of these principles has shown promise for the treatment of addiction in people with SMI [
Smoking cessation app content was selected from behavior change interventions supported by the empirical literature (eg, clinical trials) and from process research suggesting a theoretical link between intervention components and the symptoms typically experienced by our target population (see below “Evidence-Based Smoking Cessation Content” subheading in the Results section). This process ensured the theoretical grounding of the app and its evidence-based foundation.
We used several user-centered design tools to ideate a prototype of the app. This included (1) the creation of personas, a technique aimed at increasing the designer’s emotional understanding of the end user by creating a short narrative of their motivations, context, and personal characteristics [
Sketches and images developed during the ideation and paper prototyping phase provided the basis for usability testing. To simulate the app experience, we used app prototyping software (POP, Marvel, London, UK). The software was installed on iPod Touch devices, and the prototype was presented to smokers with SMI during a single 45 min session. Our key inclusion criteria were as follows: (1) being an adult who smokes at least 5 cigarettes per day, (2) receiving outpatient mental health treatment and medication by a psychiatric provider, and (3) being fluent in
Usability testing procedures included (1) completing a series of tasks with the simulated app, (2) evaluation of user experience with semistructured interviews, and (3) rating the prototype using the system usability scale (SUS) [
Our usability testing tasks evaluated the following elements of the app prototype: (1) an introductory tutorial, (2) overall Home Screen navigation (
The SUS is a valid and reliable 10-item 5-point Likert scale with scores that range from 0 to 100. Higher scores indicate higher levels of usability, with scores above 68 indicating above-average usability [
We created a design specifications document that laid out the app’s overall vision, look and feel of the interface, and its basic components and features [
In this final phase, we worked with a software vendor to materialize the vision and design specifications that resulted from our formative study.
These wireframes represent how our app’s initial Home Screen evolved throughout our design process. From left to right: (a) Home Screen sketch, (b) pre-14 Home Screen, and (c) post-14 Home Screen. Wireframes (b) and (c) are examples of the 2 types of Home Screen status: dark green, indicating that the user is still completing the 14 modules of Learn to Quit, and light blue, indicating that the user already completed the Learn to Quit lessons and is ready for his first quit attempt.
These wireframes represent how our app’s initial Play Screen evolved throughout our design process. From left to right: (a) Play Screen sketch, (b) pre-14 journey map, and (c) post-14 journey map. Wireframe (a) presents a character that needs to “jump” from stone to stone to “pick up” skills for quitting while navigating through a “swamp of urges.” In wireframe (b), the user has completed the “Finding Your North Star” lesson and practiced the “Your North Star for Quitting” skills module. Wireframe (c) presents a user who has completed all levels of the Learn to Quit journey and motivated by his values for quitting has metaphorically reached “Learn to Quit Land”.
In this section, we describe the results of our formative study by focusing on a summary of our expert panel feedback, describing an initial paper prototype of the app and the results of its usability testing. This formative study resulted in a clearer definition of the app’s core vision and helped define the scope of work to be conducted by a software development company. Results from the remaining user-centered design processes and materials (ie, design principles, theory-based content, paper prototyping) are presented throughout a final section that lays out the app’s final characteristics and features and how they were informed by those processes and materials.
The panel emphasized the specific challenges faced by this population when trying to quit (
To solve this lack of motivation and concerns about the process of quitting, the panel outlined a series of strategies that could engage the users with this app. One of them was the use of meaningful images and storytelling. Some level of gamification was viewed as important to engage users with SMI. In addition, the panel argued that as a way to compensate for the overwhelming task of quitting smoking, the system should include progressive disclosures, make sure it rewards small victories, and add external motivation (eg, money saved). Social networking and monitoring of medication aids were also mentioned. Finally, a few other themes emerged during our discussion, including challenges related to the use of technology in this population, the social context of these patients (eg, risk of having their smartphone being stolen), and the benefits of personalization and provider support during the initial stages of nicotine withdrawal and beyond.
On the basis of input from our expert panel and the authors’ experience as clinical providers, we created 3 personas: (1)
These personas were used as inspiration to sketch our first wireframes (ie, sets of images displaying the functional elements of a website or app) and the overall app prototype, which was limited to a few basic components: A Home Screen (see
Expert panel themes. Each of the insights of our expert panel are organized by a question and accompanied by a short description.
Questions and themes | Description | |
Motivation to quit | Life expectancy is not generally a motivation to quit in this population | |
Quitting without preparation | Early attempts to quit without enough preparation, and/or lacking a step-down quitting process | |
Withdrawal symptoms | Fear of experiencing withdrawal symptoms days after quitting | |
Mental health symptoms | Ongoing anxiety, depression, stress, and psychotic symptoms during the quitting process | |
Meaningful visuals | The ability to display pictures of inspiring objects, people, sites, or pets | |
Having a “video game” feel | The appeal of video games or “game like” features (eg, “bingo”) | |
Social networking | The possibility of sharing with peers | |
Storytelling | The use of interactive characters (eg, dog) for storytelling | |
Encouraging activation | The importance of increasing activation (eg, exercise) to facilitate quitting and cope with withdrawal | |
Progressive disclosure | Unlocking bits and pieces of the app, such as a picture or a message, as the user makes progress | |
Rewarding small victories | Reinforcing small victories toward quitting (eg, one day without smoking) | |
Money savings motivation | Small money savings (eg, a few extra dollars a week) | |
Medication aids | Medication education and a system to help patients adhere to medication intake | |
Technological literacy | Lack of smartphone knowledge was viewed as a potential barrier to app use | |
Predominant use of Android | The need to build an app in Android was viewed as important to secure access in this population | |
Provider check-ins | Flexible check-ins (eg, text messages) were emphasized to enhance engagement with the app | |
Need for personalization | An app that was customizable to each patient was deemed as important | |
Stealing | Concern that some patients with serious mental illness might have their devices stolen |
These wireframes represent how our initial tracking feature evolved. From left to right: (a) tracking feature sketch, (b) cigarette tracking, and (c) personalized cigarette use feedback. As opposed to wireframe (a), in which we planned to use a single wireframe to collect all desirable tracking dimensions, in the final app, we used separate wireframes for each dimension (eg, smoking, mood). Note in (b) that users could report smoking half cigarette. Wireframe (c) is an example of personalized feedback following a user who reported smoking between 5 and 10 cigarettes.
Wireframe examples of an initial sketch of a “Review Quiz” and a final Learning Module Quiz. Quizzes were presented at the end of the learning modules, and contained 3 questions each. From left to right: (a) Review Quiz sketch, (b) example of question for the “Key to Quitting” module, (c) feedback to correct answer that is followed by game reward sound, and (d) summary of quiz results, which indicates number of correct answers, best answer of all times, and number of practice stars gained (1 for each practice with a total of 3 per module).
Selection of wireframes of a smoking cessation skill (ie, Use Your Five Senses) designed to encourage self-awareness of our 5 senses. From top to bottom: (a) sketch of Use Your Five Senses skill and (b) final Use Your Five Senses skill module. Wireframes in panel (b) include five 10-second timers to assist the user focus their attention. They provide visual and tactile cues to mark the end of each practice of focused attention.
Key baseline features of usability testing subjects and corresponding system usability scale (SUS) scores. Scores above the usability standard cut-off (>68) are indicated in italics.
Participant number | Mental health treatment | Years in mental health (mean=25) | Years smoking (mean=20) | Cigarettes per day (mean=11) | SUS usability (mean= |
SUS learnability (mean=60) | SUS total (mean= |
P1 | Case manager, psychiatric nurse | 25 | 9 | 13 | |||
P2 | Case manager, psychiatric nurse | 29 | 10 | 7 | |||
P3 | Case manager, psychiatrist | 20 | 32 | 10 | 44 | 25 | 40 |
P4 | Case manager, psychiatrist | 39 | 35 | 15 | 50 | ||
P5 | Case manager, psychiatrist | 12 | 14 | 10 |
A total of 5 daily smokers recruited from an outpatient mental health clinic participated in usability testing of the app prototype. They averaged 44 years of age (standard deviation [SD] 7.5), and the majority were female (4/5) and had less than a college education (4/5). Of the 5 participants, 1 was multiracial, 1 African American, and the rest were white. Our sample group smoked an average of 11 cigarettes per day (SD 3), and most had an extended smoking history (mean 20 years, SD 13). Although we did not conduct diagnostic interviews, all participants were patients from a community mental health clinic, had an assigned psychiatric case manager and a psychiatric provider, were currently taking psychiatric medication, and on average had received mental health treatment for 25 years (SD 10). See
Overall, participants’ levels of usability with the prototype were above the standard cutoff, suggesting that the initial prototype had promise. This was reflected in both the overall scale and the usability subscale. Conversely, the learnability subscale of the SUS did not reach the standard cutoff, although it reached high levels for 3 out of 5 individuals (see
Key learnings from usability testing can be organized in 3 areas: support for app design features, critical usability errors, and minor usability errors. First, we found that the following app design features improved the apps usability: (1) the prototype’s reduced number of app layers, (2) removing the need to use a keypad to enter and save information in the app, and (3) overall prototype’s simplicity. Although Learn to Quit’s simple app structure and navigation features were the result of a previous user-centered design study we conducted in the same population [
Second, usability testing identified a critical usability error with our paper prototype. Specifically, it revealed that our original Home Screen was confusing to most users (see
Finally, we identified minor usability problems with the prototype, including small font in the subpanels and confusion about specific language. These usability errors led to a final Home Screen that had a simpler layout and removed most of its original displays and content (see
Usability testing results for Learn to Quit prototype (n=5) matched with comparable usability testing results from a previous user-centered design study (n=5) we conducted in a smoking cessation app designed for the general population (QuitPal) [
Theme | Quote/Observation/Feature | |
Smoking cessation app (QuitPal); (SUSa=65.5) | ||
Difficulty entering information in the app | Unable to “pull up the keypad” | The need to use the keypad was removed from the prototype |
Difficulty saving information | Failure to identify and press “save” button at the top of screen | The need to use a “save” button was removed from the prototype |
Getting lost in app layers | “It took me a long time to get back to that menu frame” | No observed confusion about how to return to the Home Screen |
Tremor and fine motor skills | “[buttons were] too close together” | P5b: “I like how the letters are big” |
aSUS: System Usability Scale; scores above the usability standard cut-off (>68) are indicated in italics.
bP: Participant.
Themes identified during usability testing of the Learn to Quit app prototype (n=5).
Representative quotea | |
Interested in gamification of smoking cessation skills | P1: “That would be so cool! A point every day” |
Drawn by cartoons and storytelling | P3: “The cartoons, the whole thing. It’s got great spirit” |
Appreciating simplicity | P2: “It was simple, informative, easy to use” |
Proof of concept: Acceptance and Commitment Therapy module showed promise | P1: “I wish you guys could send it to me so that I could practice it and learn it” |
Home Screen confusion | P1: “It’s very small and I can’t see what it is.” |
aP: Participant.
On the basis of this formative study, we created a technical document laying out the app’s structure and its core screens and features. We named the app Learn to Quit and synthesized the app’s core vision with the following: learn, practice, and play. Learning referred to the process of being exposed to daily modules that explain different smoking cessation concepts. Brief quizzes would help the user retain and learn those materials. Practice referred to the actual practice of smoking cessation skills in the form of brief daily exercises. Practice should lead to “mastery” of the learned materials. Play referred to the user’s opportunity to participate in a game comprising completing learning and practice modules and earning rewards along the way. The role of play was to promote higher levels of app engagement and commitment to learn.
In May 2015, we filed a Report of Innovation at the University of Washington (ROI#47274) with the design specifications document of the app and proceeded to approach a company to develop a software-coded version of the app. Learn to Quit was built between August 2015 and October 2015. Smashing Ideas Inc. [
Learn to Quit’s main active ingredient is Acceptance and Commitment Therapy (ACT) [
ACT has 3 components relevant to smoking cessation:
We adapted ACT to a mobile format by creating 14 modules of ACT+USCPG content and 14 modules of exercises to practice smoking cessation skills (see
Completion of skills modules was optional to increase the user’s perceived behavioral control [
To address the cognitive deficits observed in this population, we incorporated feedback from our formative study and followed recommendations from previous literature [
The Play Screen (
Consistent with our expert panel’s feedback, usability testing, and the empirical literature on the use of games not for entertainment, such as health or education (ie, serious games) [
Behavioral principles (see
In addition, the app used a combination of antecedent and consequential control strategies [
A rewards scheme was also implemented to increase the reinforcing effect of responding correctly to lesson quizzes (see
Because our expert panel and usability testing strongly supported the use of simple cartoons and visual storytelling, we created a gender-neutral character that rotated across the different stories and metaphors presented in each module (see
Our expert panel indicated that “technological illiteracy” was common in patients with SMI (
This paper reports the rationale, ideation, design, user research, and final features of a novel smoking cessation app developed for people with SMI, a population in great need of novel smoking cessation treatment. Building this app involved a user-centered design process that carefully considered a series of design principles to maximize comprehension and retention of smoking cessation concepts, minimize the impact of known challenges in people with SMI, and ensure the effective delivery of evidence-based smoking cessation content.
Results from our user-centered design process informed the features included in the final app. First, informed by our formative study and as suggested by the literature [
Second, as suggested by the literature [
Third, input from a panel of experts in SMI led to the idea of incorporating app gamification, visual engagement, and storytelling [
Fourth, we implemented a number of applied behavior analysis principles to maximize retention and comprehension of app content [
Finally, our development effort took into account implementation considerations: (1) it used an Android operating system, which according to our panel was a common platform among people with SMI and tends to dominate the market among people with lower socioeconomic status (eg, individuals with disabilities) [
The study reported in this paper is consistent with user-centered design research of mobile apps for depression [
To date, many apps have focused on the use of sensors and algorithms to track user context and provide personalized feedback [
As stated in the introduction, we believe that the determination of the active therapeutic ingredients delivered by an app should be the result of a careful design process. However, user-centered design research could lead to stakeholder recommendations that are not consistent with evidence-based practices or theory-based principles of change. Adherence to evidence-based practices or theory-based principles of change might not always be emphasized in user-centered design research, yet it is a key activity of the design process inherent in the original user-centered design guidelines [
Finally, a relevant aspect of this app is that it could be a good example of the concept of universal design [
This study had several limitations. First, the number of patients with SMI in the expert panel group (n=2) and the usability testing study (n=5) could have been small, leaving to question whether a larger sample of people with SMI could have led to more feedback and opportunities for innovation. There is debate among user-centered design researchers about the most cost-efficient number of subjects to identify usability errors [
Second, our methods could have been more rigorous in several aspects. Specifically, results from our expert panel were not transcribed and analyzed using a complete set of qualitative methods, which could have led to the identification of additional themes. However, rather than a thorough and comprehensive analysis of provider input, the goal of this expert panel was to quickly gather initial insights and impressions that would orient our imminent design process. Additionally, usability testing did not include observational coding of user behavior. As reported in similar studies [
Third, the app’s tracking feature provided personalized feedback based on participants’ responses to self-reported ratings of mood and smoking behavior. However, this level of personalization did not take into consideration each individual’s baseline (eg, certain smoking reductions could be large or small depending on the individual’s baseline), limiting its impact for personalization. Likewise, the current app system does not take into account a variety of quitting scenarios (eg, individuals who quit before the end of the program) and how these scenarios interact with app content. Future versions could take into account these personal scenarios to strengthen Learn to Quit’s usefulness and level of personalization.
Finally, this paper focuses on the user-centered design research of a paper prototype leading to the development of the Learn to Quit app. Although this report does not provide data about the usability and user experience of the final Learn to Quit app, it allowed us to transparently report in more detail its user-centered design process. A separate report of Learn to Quit’s usability and user experience in its target population is under review elsewhere.
This is the first paper to systematically describe the rationale, ideation, design, and user research of a smoking cessation app specifically designed for people with SMI, a population with alarmingly high rates of nicotine addiction and in high need of novel smoking cessation treatments. The feasibility and acceptability of this app will be subsequently tested in a randomized controlled feasibility trial (clinicaltrials.gov NCT03069482).
User-centered design is a critical process for the development of mobile interventions for individuals with SMI. However, because emotional and cognitive challenges are present in less severe forms of mental illness or can be present in other health conditions (eg, cancer patients), the results of this study might be generalizable to other areas of mHealth research. Therefore, while ideating and designing digital interventions, mHealth developers might consider capitalizing on the role of visual engagement, storytelling, and the systematic application of behavior analytic principles to deliver evidence-based content.
Primary and secondary personas that guided Phase IV of the user-centered design process.
Evidence-based smoking cessation content of Learn to Quit app.
Design principles.
Acceptance and Commitment Therapy
National Cancer Institute
serious mental illness
system usability scale
US Clinical Practice Guidelines
The authors thank Francis J McClernon, PhD, for comments and feedback that greatly improved the final manuscript. Roger Vilardaga received funding support from the National Institute of Drug Abuse (K99DA037276 and R00DA037276). Learn to Quit is the intellectual property of the University of Washington (© 2015-2016 University of Washington). Julie A. Kientz’s spouse is the cofounder of Senosis Health, a start-up company in the area of health technologies for diagnosis, monitoring, and treatment, which was recently acquired by Google.
RV envisioned the app rationale and intervention, ideated app design and features, sketched imagery, conducted research activities, interpreted results, and wrote this manuscript. JR coordinated research activities, sketched imagery to be included in each module, and contributed to the overall conduct of design and research activities. EZ transcribed the recordings of the usability testing procedure, conducted thematic analysis of the interviews, discussed emerging themes with first author, and sketched imagery to be included in each module. JK provided user-centered design expertise in the development of the software app for behavior change and smoking cessation and contributed to early drafts of this manuscript. RR contributed to form the expert panel, provided serious mental illness expertise and feedback about the overall app design, and contributed to late drafts of this manuscript. CO created high-fidelity designs and illustrations and contributed to improvements in interaction design and the final user experience of the app. KH contributed to late drafts of this manuscript and to the layout of the manuscript structure and sections.
None declared.