Designing the Future of Children's Mental Health Services.

Advancements in evidence-based psychosocial interventions, digital technologies, and implementation strategies (i.e., health services research products) for youth mental health services have yet to yield significant improvement in public health outcomes. Achieving such impact will require that these research products are easy to use, useful, and contextually appropriate. This paper describes how human-centered design (HCD), an approach that aligns product development with the needs of the people and settings that use those products, can be leveraged to improve youth mental health services. We articulate how HCD can advance accessibility, effectiveness, and equity, with specific consideration of unique aspects of youth mental health services.

The use of model constructs to design collaborative health information technologies: A case study to support child development.

OBJECTIVE: Health information technology could provide valuable support for inter-professional collaboration to address complex health issues, but current HIT systems do not adequately support such collaboration. Existing theoretical research on supporting collaborative work can help inform the design of collaborative HIT systems. Using the example of supporting collaboration between child development service providers, we describe a deductive approach that leverages concepts from the literature and analyzes qualitative user-needs data to aid in collaborative system design. MATERIALS AND METHODS: We use the Collaboration Space Model to guide the deductive qualitative analysis of interviews focused on the use of information technology to support child development. We deductively analyzed 44 interviews from two separate research initiatives and included data from a wide range of stakeholder groups including parents and various service providers. We summarized the deductively coded interview excerpts using quantitative and qualitative methods. RESULTS: The deductive analysis method provided a rich set of design data, highlighting heterogeneity in work processes, barriers to adequate communication, and gaps in stakeholder knowledge in supporting child development work. DISCUSSION: Deductive qualitative analysis considering constructs from a literature-based model provided useful, actionable data to aid in design. Design implications underscore functions needed to adequately share data across many stakeholders. More work is needed to validate our design implications and to better understand the situations where specific system features would be most useful. CONCLUSIONS: Deductive analysis considering model constructs provides a useful approach to designing collaborative HIT systems, allowing designers to consider both empirical user data and existing knowledge from the literature. This method has the potential to improve designs for collaborative HIT systems.

Understanding pivotal experiences in behavior change for the design of technologies for personal wellbeing.

Most health technologies are designed to support people who have already decided to work toward better health. Thus, there remains an opportunity to design technologies to help motivate people who have not yet decided to make a change. Understanding the experiences of people who have already started to make a health behavior change and how they made a pivotal decision can be useful in understanding how to design such tools. In this paper, we describe results from data collected in 2 phases. Phase 1 consisted of 127 surveys and 13 interviews with adults who have already accomplished behavior change(s). Phase 2 consisted of 117 surveys and 12 interviews with adults who have either already accomplished their behavior change(s) or are currently working toward them. We identified four factors that lead to pivotal experiences: (1) prolonged discontent and desire to change, (2) significant changes that increase fear or hope of future, (3) increased understanding of one's behavior and personal data, and (4) social accountability. We also describe a design space for designing technology-based interventions for encouraging people to decide to make a change to improve their health. Based on feedback from participants, we discuss opportunities for further exploration of the design space for people who are not yet motivated to change and for ethical considerations for this type of intervention.

Lessons from Practice: Designing Tools to Facilitate Individualized Support for Quitting Smoking.

Many health care providers, with a variety of trainings, counsel clients on quitting smoking on a day-to-day basis. In their clinical practice, they draw from and adapt guidelines and research-based strategies to fit individual client situations and challenges. Designers of technologies to support quitting smoking can learn from these real world practices to create tools that better adapt to individual differences. We present findings from interviews with 28 providers with diverse experiences in smoking cessation counselling. Through analysis of their individualization strategies, challenges, and perceptions of technology, we find that providers: (1) individualize context appropriate coping strategies by involving clients in brainstorming, (2) emphasize the need to support nicotine withdrawal in clients, (3) mitigate social triggers and mediate social support for clients, and (4) need to navigate dependencies with other providers for managing medications and comorbid health conditions of clients. With this empirical understanding, we extend the discussion on the design of technology to support quitting smoking, highlight current barriers to individualization, and suggest future opportunities to address these barriers.

User Experience Evaluation of a Smoking Cessation App in People With Serious Mental Illness.

INTRODUCTION: Smoking rates among people with serious mental illness are 3 to 4 times higher than the general population, yet currently there are no smoking cessation apps specifically designed to address this need. We report the results of a User Experience (UX) evaluation of a National Cancer Institute smoking cessation app, QuitPal, and provide user centered design data that can be used to tailor smoking cessation apps for this population. METHODS: Two hundred forty hours of field experience with QuitPal, 10 hours of recorded interviews and task performances, usage logs and a self-reported usability scale, informed the results of our study. Participants were five individuals recruited from a community mental health clinic with a reported serious mental illness history. Performance, self-reports, usage logs and interview data were triangulated to identify critical usability errors and UX themes emerging from this population. RESULTS: Data suggests QuitPal has below average levels of usability, elevated time on task performances and required considerable amounts of guidance. UX themes provided critical information to tailor smoking cessation apps for this population, such as the importance of breaking down "cessation" into smaller steps and use of a reward system. CONCLUSIONS: This is the first study to examine the UX of a smoking cessation app among people with serious mental illness. Data from this study will inform future research efforts to expand the effectiveness and reach of smoking cessation apps for this highly nicotine dependent yet under-served population. IMPLICATIONS: Data from this study will inform future research efforts to expand the effectiveness and reach of smoking cessation apps for people with serious mental illness, a highly nicotine dependent yet under-served population.

Feature-level analysis of a novel smartphone application for smoking cessation.

BACKGROUND: Currently, there are over 400 smoking cessation smartphone apps available, downloaded an estimated 780,000 times per month. No prior studies have examined how individuals engage with specific features of cessation apps and whether use of these features is associated with quitting. OBJECTIVES: Using data from a pilot trial of a novel smoking cessation app, we examined: (i) the 10 most-used app features, and (ii) prospective associations between feature usage and quitting. METHODS: Participants (n = 76) were from the experimental arm of a randomized, controlled pilot trial of an app for smoking cessation called "SmartQuit," which includes elements of both Acceptance and Commitment Therapy (ACT) and traditional cognitive behavioral therapy (CBT). Utilization data were automatically tracked during the 8-week treatment phase. Thirty-day point prevalence smoking abstinence was assessed at 60-day follow-up. RESULTS: The most-used features - quit plan, tracking, progress, and sharing - were mostly CBT. Only two of the 10 most-used features were prospectively associated with quitting: viewing the quit plan (p = 0.03) and tracking practice of letting urges pass (p = 0.03). Tracking ACT skill practice was used by fewer participants (n = 43) but was associated with cessation (p = 0.01). CONCLUSIONS: In this exploratory analysis without control for multiple comparisons, viewing a quit plan (CBT) as well as tracking practice of letting urges pass (ACT) were both appealing to app users and associated with successful quitting. Aside from these features, there was little overlap between a feature's popularity and its prospective association with quitting. Tests of causal associations between feature usage and smoking cessation are now needed.

Refinement of a Parent-Child Shared Asthma Management Mobile Health App: Human-Centered Design Study.

BACKGROUND: The school-age years, approximately ages 7 through 11, represent a natural transition when children begin assuming some responsibility for their asthma management. Previously, we designed a theoretically derived, tailored parent-child shared asthma management mobile health app prototype, Improving Asthma Care Together (IMPACT). OBJECTIVE: The purpose of this study was to use human-centered design (HCD) to iteratively refine IMPACT to optimize user experience and incorporate evidence-based longitudinal engagement strategies. METHODS: This study used a mixed methods design from December 2019 to April 2021. Our app refinement used the HCD process of research, ideation, design, evaluation, and implementation, including 6 cycles of design and evaluation. The design and evaluation cycles focused on core app functionality, child engagement, and overall refinement. Evaluation with parent-child dyads entailed in-person and remote concept testing and usability testing sessions, after which rapid cycle thematic analyses identified key insights that informed future design refinement. RESULTS: Twelve parent-child dyads enrolled in at least one round of this study. Eight of the 12 child participants were male with a mean age of 9.9 (SD 1.6) years and all parent participants were female. Throughout evaluation cycles, dyads selected preferred app layouts, gamification concepts, and overall features with a final design prototype emerging for full-scale development and implementation. CONCLUSIONS: A theoretically derived, evidence-based shared asthma management app was co-designed with end users to address real-world pain points and priorities. An 8-week pilot study testing app feasibility, acceptability, and preliminary efficacy is forthcoming.

Lessons learned from designing an asynchronous remote community approach for behavioral activation intervention for teens.

Adolescent depression is common; however, over 60% of depressed adolescents do not receive mental health care. Digitally-delivered evidence-based psychosocial interventions (EBPIs) may provide an opportunity to improve access and engagement in mental health care. We present a case study that reviews lessons learned from using the Discover - Design - Build - Test (DDBT) model to create, develop, and evaluate a high-fidelity prototype of an app to deliver an EBPI for depression, behavioral activation (BA), on an Asynchronous Remote Communities (ARC) platform (referred to as ActivaTeen). We review work at each stage of the DDBT framework, including initial formative work, iterative design and development work, and an initial feasibility study. We engaged teens with depression, mental health clinicians, and expert evaluators through the process. We found that the DDBT model supported the research team in understanding the requirements for our prototype system, ActivaTeen, and conceiving of and developing specific ideas for implementation. Our work contributes a case study of how the DDBT framework can be applied to adapting an EBPI to a new, scalable and digital format. We provide lessons learned from engaging teens and clinicians with an asynchronous approach to EBPIs and human centered design considerations for teen mental health.

Improving Asthma Care Together (IMPACT) mobile health intervention for school-age children with asthma and their parents: a pilot randomised controlled trial study protocol.

INTRODUCTION: Asthma is an incurable, lifelong condition that places children at increased risk for exacerbation, hospitalisation and school absences. Most paediatric asthma interventions target parents alone and are overly prescriptive. Improving Asthma Care Together (IMPACT) is a novel shared management system comprised of a mobile health (mHealth) application, symptom watch and tailored health intervention that pairs parent and child together as an asthma management team. IMPACT helps families monitor asthma status, tailor asthma management strategies and facilitate intentional transition of asthma management to the child. The purpose of this study is to determine the feasibility, acceptability and preliminary efficacy of the IMPACT intervention. METHODS AND ANALYSIS: This pilot randomised controlled trial will recruit 60 children with asthma (7-11 years) and one parent. All parent-child dyads will complete data collection sessions at baseline, postintervention and follow-up. Dyads randomised to the intervention group (IMPACT) will complete the 8-week intervention comprised of weekly activities including symptom monitoring, goal setting and progress monitoring. Dyads randomised to the control group will receive usual care but then be provided access to IMPACT at the end of the study. Feasibility will be measured by the proportion of eligible dyads enrolled and retained. Acceptability of IMPACT will be assessed using the Acceptability of Intervention Measure, the System Usability Scale and a semistructured interview. Preliminary efficacy is determined based on change in primary outcomes, parent-reported and child-reported asthma responsibility and asthma self-efficacy scores, from baseline. ETHICS AND DISSEMINATION: This study has been approved by the University of Washington Institutional Review Board; study ID: STUDY00010461. Participants gave informed consent to participate in the study before taking part. Study results will be disseminated in peer-reviewed journals and scientific conferences. A lay summary will be provided to study participants. TRIAL REGISTRATION NUMBER: NCT04908384 (ClinicalTrials.gov identifier).

Using Health Concept Surveying to Elicit Usable Evidence: Case Studies of a Novel Evaluation Methodology.

BACKGROUND: Developers, designers, and researchers use rapid prototyping methods to project the adoption and acceptability of their health intervention technology (HIT) before the technology becomes mature enough to be deployed. Although these methods are useful for gathering feedback that advances the development of HITs, they rarely provide usable evidence that can contribute to our broader understanding of HITs. OBJECTIVE: In this research, we aim to develop and demonstrate a variation of vignette testing that supports developers and designers in evaluating early-stage HIT designs while generating usable evidence for the broader research community. METHODS: We proposed a method called health concept surveying for untangling the causal relationships that people develop around conceptual HITs. In health concept surveying, investigators gather reactions to design concepts through a scenario-based survey instrument. As the investigator manipulates characteristics related to their HIT, the survey instrument also measures proximal cognitive factors according to a health behavior change model to project how HIT design decisions may affect the adoption and acceptability of an HIT. Responses to the survey instrument were analyzed using path analysis to untangle the causal effects of these factors on the outcome variables. RESULTS: We demonstrated health concept surveying in 3 case studies of sensor-based health-screening apps. Our first study (N=54) showed that a wait time incentive could influence more people to go see a dermatologist after a positive test for skin cancer. Our second study (N=54), evaluating a similar application design, showed that although visual explanations of algorithmic decisions could increase participant trust in negative test results, the trust would not have been enough to affect people's decision-making. Our third study (N=263) showed that people might prioritize test specificity or sensitivity depending on the nature of the medical condition. CONCLUSIONS: Beyond the findings from our 3 case studies, our research uses the framing of the Health Belief Model to elicit and understand the intrinsic and extrinsic factors that may affect the adoption and acceptability of an HIT without having to build a working prototype. We have made our survey instrument publicly available so that others can leverage it for their own investigations.

Designing Asynchronous Remote Support for Behavioral Activation in Teenagers With Depression: Formative Study.

BACKGROUND: Many teenagers in the United States experience challenges with symptoms of depression, and they lack adequate resources for accessing in-person mental health care. Involving teens and clinicians in designing technologies that use evidence-based practices that reduce barriers to accessing mental health care is crucial. Interventions based on behavioral activation (BA) help teens understand the relationship between mood and activity, help them practice goal-directed behaviors to improve mood, and may be particularly well-suited to delivery via internet-based platforms. OBJECTIVE: This study aims to understand the needs and challenges that teens and mental health clinicians face in depression management and involve them in the design process of a remote intervention that uses asynchronous remote communities. Our goal is to understand the benefits and challenges of adapting BA to an internet-based platform that supports the asynchronous remote community approach as a delivery tool for teen depression management. METHODS: We enrolled mental health clinicians (n=10) and teens (n=8) in separate, private, internet-based groups on Slack (Slack Technologies Inc). They participated in 20-minute design activities for 10 weeks and were then invited to interviews about their experiences in the study. RESULTS: Both teen and clinician participants wanted internet-based support for BA as a supplement to in-person therapy. Although participants perceived the asynchronous format as conducive to supporting accessible care, teens and clinicians raised concerns about safety, privacy, and the moderating of the internet-based group. Design decisions that address these concerns need to be balanced with the potential benefits of learning coping skills, increasing access to mental health care, and promoting asynchronous human connection to support teens. CONCLUSIONS: We discuss considerations for balancing tensions in privacy and safety while designing and selecting internet-based platforms to support remote care and integrating evidence-based support when designing digital technologies for the treatment of teens with depression.

Why Should I Trust You? Supporting the Sharing of Health Data in the Interprofessional Space of Child Development.

Many stakeholders can be involved in supporting a child's development, including parents, pediatricians, and educators. These stakeholders struggle to collaborate, and experts suggest that health information technology could improve their communication. Trust, based on perceptions of competence, benevolence, and integrity is fundamental to supporting information sharing, so information technologies should address trust between stakeholders. We engaged 75 parents and 60 healthcare workers with two surveys to explore this topic. We first elicited the types of information parents and healthcare workers use to form perceptions of competence, benevolence, and integrity. We then designed and tested user profile prototypes listing the elicited information to see if it builds trust in previously unknown professionals. We discovered that providing information related to personal characteristics, relationships, professional experience, and workplace practices can support trust and the sharing of information. This work has implications for designing informative electronic user interfaces to support interprofessional trust.

DreamCatcher: Exploring How Parents and School-Age Children Can Track and Review Sleep Information Together.

Parents and their school-age children can impact one another's sleep. Most sleep-tracking tools, however, are designed for adults and make it difficult for parents and children to track together. To examine how to design a family-centered sleep tracking tool, we designed DreamCatcher. DreamCatcher is an in-home, interactive, shared display that aggregates data from wrist-worn sleep sensors and self-reported mood. We deployed DreamCatcher as a probe to examine the design space of tracking sleep as a family. Ten families participated in the study probe between 15 and 50 days. This study uses a family systems perspective to explore research questions regarding the feasibility of children actively tracking health data alongside their parents and the effects of tracking and sharing on family dynamics. Our results indicate that children can be active tracking contributors and that having parents and children track together encourages turn-taking and working together. However, there were also moments when family members, in particular parents, felt discomfort from sharing their sleep and mood with other family members. Our research contributes to a growing understanding of designing family-centered health-informatics tools to support the combined needs of parents and children.

The Importance of Starting With Goals in N-of-1 Studies.

N-of-1 tools offer the potential to support people in monitoring health and identifying individualized health management strategies. We argue that elicitation of individualized goals and customization of tracking to support those goals are a critical yet under-studied and under-supported aspect of self-tracking. We review examples of self-tracking from across a range of chronic conditions and self-tracking designs (e.g., self-monitoring, correlation analyses, self-experimentation). Together, these examples show how failure to elicit goals can lead to ineffective tracking routines, breakdowns in collaboration (e.g., between patients and providers, among families), increased burdens, and even designs that encourage behaviors counter to a person's goals. We discuss potential techniques for eliciting and refining goals, scaffolding an appropriate tracking routine based on those goals, and presenting results in ways that advance individual goals while preserving individual agency. We then describe open challenges, including how to reconcile competing goals and support evolution of goals over time.

A Patient-Centered Proposal for Bayesian Analysis of Self-Experiments for Health.

The rise of affordable sensors and apps has enabled people to monitor various health indicators via self-tracking. This trend encourages self-experimentation, a subset of self-tracking in which a person systematically explores potential causal relationships to try to answer questions about their health. Although recent research has investigated how to support the data collection necessary for self-experiments, less research has considered the best way to analyze data resulting from these self-experiments. Most tools default to using traditional frequentist methods. However, the US Agency for Healthcare Research and Quality recommends using Bayesian analysis for n-of-1 studies, arguing from a statistical perspective. To develop a complementary patient-centered perspective on the potential benefits of Bayesian analysis, this paper describes types of questions people want to answer via self-experimentation, as informed by 1) our experiences engaging with irritable bowel syndrome patients and their healthcare providers and 2) a survey investigating what questions individuals want to answer about their health and wellness. We provide examples of how those questions might be answered using 1) frequentist null hypothesis significance testing, 2) frequentist estimation, and 3) Bayesian estimation and prediction. We then provide design recommendations for analyses and visualizations that could help people answer and interpret such questions. We find the majority of the questions people want to answer with self-tracking data are better answered with Bayesian methods than with frequentist methods. Our results therefore provide patient-centered support for the use of Bayesian analysis for n-of-1 studies.

Communicating Bad News: Insights for the Design of Consumer Health Technologies.

BACKGROUND: As people increasingly receive personal health information through technology, there is increased importance for this information to be communicated with empathy and consideration for the patient's experience of consuming it. Although technology enables people to have more frequent and faster access to their health information, it could also cause unnecessary anxiety, distress, or confusion because of the sensitive and complex nature of the information and its potential to provide information that could be considered bad news. OBJECTIVE: The aim of this study was to uncover insights for the design of health information technologies that potentially communicate bad news about health such as the result of a diagnosis, increased risk for a chronic or terminal disease, or overall declining health. METHODS: On the basis of a review of established guidelines for clinicians on communicating bad news, we developed an interview guide and conducted interviews with patients, patients' family members, and clinicians on their experience of delivering and receiving the diagnosis of a serious disease. We then analyzed the data using a thematic analysis to identify overall themes from a perspective of identifying ways to translate these strategies to technology design. RESULTS: We describe qualitative results combining an analysis of the clinical guidelines for sharing bad health news with patients and interviews on clinicians' specific strategies to communicate bad news and the emotional and informational support that patients and their family members seek. Specific strategies clinicians use included preparing for the patients' visit, anticipating patients' feelings, building a partnership of trust with patients, acknowledging patients' physical and emotional discomfort, setting up a scene where patients can process the information, helping patients build resilience and giving hope, matching the level of information to the patients' level of understanding, communicating face-to-face, if possible, and using nonverbal means. Patient and family member experiences included internal turmoil and emotional distress when receiving bad news and emotional and informational support that patients and family members seek. CONCLUSIONS: The results from this study identify specific strategies for health information technologies to better promote empathic communication when they communicate concerning health news. We distill the findings from our study into design hypotheses for ways technologies may be able to help people better cope with the possibility of receiving bad health news, including tailoring the delivery of information to the patients' individual preferences, supporting interfaces for sharing patients' context, mitigating emotional stress from self-monitoring data, and identifying clear, actionable steps patients can take next.

Connected Personas: Translating the Complexity of Older Adult Personal Health Information Management for Designers of Health Information Technologies.

Human-centered design (HCD) can be used to communicate research study findings to designers of health information technologies (HIT). We used the HCD approach to develop personas, scenarios, and design guidelines for designers with the aim that it would lead to new HIT designs that support the autonomy and health of older adults. The foundation of the personas, scenarios, and design guidelines was a study that focused on understanding how older adults manage their health information and the role that stakeholders play in that process. In this paper, we describe how we carried out a HCD approach and how it led us to expand the persona process to create a network of connected personas. The connected personas allowed us to show the complexities of personal health information management for older adults and emphasize the importance of relationships with family, friends, and providers.

Formative, multimethod case studies of learn to quit, an acceptance and commitment therapy smoking cessation app designed for people with serious mental illness.

Despite public health efforts, individuals with serious mental illness (SMI) still have very high rates of tobacco smoking. Innovative approaches to reach this population are needed. These series of case studies aimed to descriptively evaluate the usability, user experience (UX), and user engagement (UE) of Learn to Quit (LTQ), an acceptance and commitment therapy smoking cessation app designed for people with SMI, and to compare it with an app designed for the general population, NCI (National Cancer Institute) QuitGuide (QG). Both apps were combined with nicotine replacement therapy and technical coaching. Inspired by the ORBIT model, we implemented two case studies with crossover AB interventions, two B-phase training designs, and three bi-phasic AB single-case designs with Start-Point and Order randomization (A = QG, B = LTQ). Study outcomes were measured using the System Usability Scale, UX interviews, and background analytics. LTQ's usability levels were above the standard cutoff and on average higher than QG. UX outcomes suggested the relative benefits of LTQ's visual design, gamification and simple design structure. LTQ's overall UE was high; the app was opened for an average of 14 min per day (vs. QG: 7 min). However, users showed low levels of UE with each of the app's tracking feature. Measures of psychiatric functioning suggested the safety of LTQ in people with SMI. LTQ appears to be a usable and engaging smoking cessation app in people with SMI. An optimized version of LTQ should be tested in a Phase II study.

Engaging Teenagers in Asynchronous Online Groups to Design for Stress Management.

Teenagers have unique needs for mental wellbeing that can be supported by interactive technologies. Teens also have valuable input in the design of technology, so designers and researchers must seek new methods for involving them in the design process. We enrolled 23 unacquainted teenagers in an Asynchronous Remote Communities (ARC) study consisting of two private online groups. Teens participated in 10 weekly design activities on stress management across three months. We found that teens sought support from technology tailored to their perception of control in stressful contexts, developing sense of self, and varying social needs, including asking for no intervention from others. Teens appreciated that the ARC design experience allowed for flexibility in participation and supported selective disclosure. However, there were limited interactions between teenagers online. Reflecting on our study, we provide design implications for tools to support teenager mental health and discuss how the ARC method can be adapted for designing with teenagers.

User-Centered Design of Learn to Quit, a Smoking Cessation Smartphone App for People With Serious Mental Illness.

BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.