We used purposive sampling to recruit potentially eligible participants from a single large community mental health center in New England between May 2019 and August 2019. Recruitment occurred via flyers posted in waiting rooms and clinician referral. Eligible participants were 18 to 35 years old, English-speaking, stable in their outpatient mental health treatment for serious mental illness (ie, no hospitalization in past 30 days per chart review), and smoked daily. We chose the age range of 18 to 35 years to focus on adults for whom quitting smoking has the greatest potential long-term mortality benefit. While the National Young Adult Health Survey found that cessation attitudes were similar among 18- to 24-year-old and 25- to 34-year-old adults [34], it also demonstrated that smoking trajectories differ between these age groups [35]. Thus, we stratified patients by age into 2 groups—18 to 24 years and 25 to 35 years—to better characterize participants’ cessation needs. This paper presents findings from the 25 to 35-year-old age group. Patients were excluded if they were pregnant or had a current, unstable substance use disorder (per chart review or per the participant’s mental health center clinician).

Prior to each focus group, research staff read the study information sheet aloud with the participants and discussed the purpose of the study with them. All eligible participants were deemed competent to give consent, which participants provided verbally. Participants received a US $30 gift card to a retail store after completing the focus group. The New Hampshire State Institutional Review Board approved and monitored all study activities.

Transcripts were iteratively analyzed using thematic analytic techniques [39]. Three researchers (MG, NK, and AM) independently coded each transcript using ATLAS.ti (version 8, ATLAS.ti Scientific Software Development GmbH). After conducting an immersive review of the data set, an initial set of codes was generated using a deductive-inductive approach. This approach allowed us to generate codes based on prior empirical data on facilitators and barriers to quitting smoking, while also allowing new codes to emerge from the data set. The 3 researchers met regularly to refine the code definitions until reaching a final code structure, which they each independently applied to the entire data set. Additional meetings were held to discuss discrepancies in applying the final codes to the data set until consensus was reached through negotiation [40]. Memoing was used throughout the coding process to facilitate a deeper understanding of how the codes relate to each other, and how codes could be represented by unifying themes [41]. The themes were then developed into thematic statements, and emblematic quotations where chosen to illustrate how the themes developed from the data. Negative case analysis was used to ensure the entire data set was represented in the emerging themes.

Participants (n=22) were individuals who smoked daily and who were stable in their community mental health treatment. Almost half of participants (10/22, 46%) self-identified as female, most (18/22, 82%) self-identified as white, and 9/22 (41%) were diagnosed with psychotic disorders. Technology use data are presented in Table 1.

Many participants described interest in health-related apps such as fitness trackers or mood trackers but noted varying degrees of benefit during their prior experiences with these types of apps. Participants discussed using the apps to review information about their personal habits (ie, their “stats”), but altering a behavior based on this feedback was rare. For example, a participant using a step tracker said,

Only one participant described increasing her activity level to achieve goals in her step tracker; others simply reviewed their steps without this leading to change in behavior. Another participant found a symptom tracker useful to bring to her clinicians so they could change her treatment plan but did not utilize the information herself.

Participants felt that while motivation to quit is a prerequisite for using a smoking cessation app, the app would need to provide features that could facilitate ongoing motivation. Participants suggested a number of ways that apps could motivate them, such as receiving support from other people within the app, feedback about progress (such as cigarettes avoided or money saved), and rewards such as financial incentives or badges. They also mentioned the importance of distraction to avoid cigarettes and suggested that an app could offer distraction by providing suggestions for alternate activities instead of smoking or by including games within the app.

While one participant was concerned that an app would lead to missed social interactions and reduced social support for quitting, others discussed desire for the app to incorporate social support. Multiple participants suggested the ability to connect with other smokers for support within the app. One person suggested a chat feature:

Other participants recommended group challenges, similar to those seen in popular fitness apps:

While most of the participants who valued social support in their quit attempt mentioned other smokers or peers, one suggested involving family members as part of the quit plan in the app:

A prominent theme across focus groups was the desire to track the number of cigarettes smoked per day. Many participants wanted to track cigarettes to increase their awareness of how much they smoke. Others added that they would like to record additional information about their smoking so they could learn their typical smoking patterns:

Some participants noted that quitting all at once can feel insurmountable, but suggested that tracking cigarettes could be motivating by allowing them to see progress toward quitting:

Most participants cited money as a major motivator to quit or reduce their smoking and would want the app to provide a feature that tracks money spent on cigarettes or money saved by avoiding cigarettes:

While tracking was a common theme, fewer participants suggested skill-based features for behavioral change. One participant recommended that an app include

Another stated that

However, such statements were far less common than recommendations for tracking.

A common theme across focus groups was the desire for rewards within the app. Some participants mentioned financial rewards such as gift cards for using the apps while others recommended that the app award badges for progress, based on their experience with other health behavior change apps:

Another prominently mentioned feature across focus groups was the benefit of distraction during a quit attempt. Many participants described using distraction as a tool for avoiding cigarettes during prior quit attempts and felt that a smartphone app would be well-suited to providing distraction. Some participants suggested that the app could provide games to play to avoid smoking. Others felt that the app could provide suggestions for alternative activities to smoking:

Most participants felt that the biggest barrier to using an app to quit or reduce smoking was a lack of motivation to change smoking behavior in general, and that once motivated, there were few barriers other than practical issues related to any mobile technology (eg, limited phone battery, inability to use phone if lost or broken, limited cellular or wireless internet service in certain locations). However, two main concerns arose regarding the limitations of apps during a quit attempt—a lack of external accountability and the potential to trigger cravings.

A prominent theme across focus groups was the need for external accountability during a quit attempt and concern that an app would not be able to provide this. Related to their discussion of the importance of monitoring progress, participants voiced concerns about the temptation to report false information to an app. One participant, who had previously used a cigarette tracking app, noted:

In another focus group, a similar sentiment arose:

Other participants felt that apps might have limited benefit without a method of confirming smoking status. One participant stated:

Despite general agreement that entering information into the app on an honor system is a limitation, participants who mentioned biochemical verification as a means to achieve this did so unfavorably. In one group, a participant described mistrust of the accuracy of breath carbon monoxide monitoring. In another focus group, a participant who mentioned concern about false reporting to the app went on to consider breath carbon monoxide monitoring, but then immediately discounted it, saying,

Participants made few recommendations about features that should be avoided in a smoking cessation app, but a common concern was the possibility that the app could trigger cravings. Based on their prior experiences with smoking triggers, they were concerned that any mention of cigarettes in the app could increase their desire to smoke:

In this study, we explored the attitudes of young adults with serious mental illness who smoke toward quitting smoking and the use of apps for this purpose. Overall, our findings share significant overlap with those of prior early phase trials in middle-aged adults with serious mental illness [30,33]. We found that young adults with serious mental illness who smoke shared similar reasons for quitting or continuing to smoke as those in other populations and were interested in using apps during a quit or reduction attempt. Participants voiced a desire for apps to provide ongoing motivational content during a quit attempt, features to increase awareness of smoking habits and money spent, content that could be used as a distraction from smoking, reward features, and social support for quitting smoking. They also described potential app limitations, such as the temptation to enter false information into the tracking features, and an app’s potential to trigger cravings. This group’s concern about psychiatric side effects of cessation pharmacotherapy is an additional important characteristic that could be countered or monitored with digital technology.

Our analysis revealed a tension between participants’ desire to see progress via tracking features and their fear of seeing personal failure via the same features. Similar to qualitative findings in studies of middle-aged adults with and without mental illness [30,33,42-44], participants in our study voiced a strong desire for cigarette- and money-tracking features that could demonstrate progress and enhance motivation during a quit attempt. However, participants also described using other apps with similar features that had not affected their patterns of behavior. Additionally, and similar to other adults with and without mental health issues [33,45], they expressed concern that recording information that suggests a lack or loss of progress might be demotivating and could lead to relapse or to the temptation to enter false information into the app. Although tracking smoking and viewing progress were popular features noted by this study group and those in other research [30,42,43,46], in one study of general population adult daily smokers [43], these features were not associated with improved abstinence.

Similar to other studies of adults with serious mental illness, in general [10,12,13,33], and young people with mental health conditions, in particular [47], participants described their main barriers to quitting as inability to resist cravings, using smoking to manage mental health symptoms, and smoking out of habit. Yet, only a few suggested that apps could teach strategies to overcome these barriers. Instead, most participants conveyed the common perception that it just takes “will power” to quit, rather than the application of skills to tolerate stress and urges without smoking. Skills training, such as advice on changing routines and improving coping strategies for cravings, has been shown to improve abstinence outcomes for both in-person [48] and app-based [43] interventions. Taken together, these data suggest that tracking features are appealing and may enhance engagement or motivation, but other skill building or clinical support features for cessation skills would need to be prominent and engaging to ensure use within the apps.

Many participants in this study recommended that cessation apps include financial rewards or badges awarded by the app for progress. There is a growing body of literature to support the use of rewards in the form of praise [48] and financial incentives [49,50] for smoking cessation. Inclusion of rewards features in smoking cessation apps, therefore, has promise to improve both engagement and abstinence outcomes.

While prior studies assessing users’ desire for specific features in smoking cessation apps demonstrate mixed results regarding the role of social support for quitting within apps [33,42,44,45], participants in our study clearly valued this feature. In line with prior findings regarding the role of social influence on smoking behavior in people with serious mental illness [10,51], our participants highlighted the importance of the effects of social environment and peer interaction on their smoking behaviors and described the potential benefit of an alternative smoke-free support system within the app. They specifically voiced a desire for peer support through chat functions and competitions, as opposed to smoking cessation coaching or technology coaching that has been described in other studies [30,32]. This desire for peer support is similar to preferences described by young adults with serious mental illness in a study [52] assessing the possible role of digital support for mental health diagnoses and highlights the perceived importance of peer-to-peer interaction for overcoming the stigma and challenges associated with smoking as well as living with mental illness. Although one study [53] demonstrated the potential of a motivational intervention delivered by peers, Dickerson and colleagues [54] described numerous challenges to cessation associated with a peer mentoring approach for people with serious mental illness. While this feature may improve engagement in the app and promote overall well-being, its effect on smoking behaviors requires further study.

The landscape of smoking cessation apps is rapidly changing. Currently available apps are variable in their content and features [27,29,55-58], and few contain content that adheres to clinical practice guidelines [27,55-57,59-61]. A recent literature review [29] found that most smoking cessation apps included self-tracking features, but only one-third included social support and one-third included rewards systems. Furthermore, most apps included three or fewer features, which typically involved education, tracking, and a variable third feature [29]. Another recent review [58] found that less than half of available apps included advice on changing routines or coping with cravings. Apps that include high-quality, evidence-based content as well as an array of both desired features and features previously found to be effective should be tested in this population.

Compared to other populations of smokers, the young adults with serious mental illness in this study voiced similar reasons for smoking, quitting smoking, and relapsing after a quit attempt [34,62,63], but they expressed specific concerns regarding medication safety in relation to their mental health conditions. A wide body of evidence has demonstrated the safety and efficacy of cessation pharmacotherapy in the setting of mental illness [3,11,15-17]. Thus, improving utilization of these treatments can substantially impact quit rates. Our findings suggest that content in a smoking cessation app tailored for young adults with serious mental illness can likely overlap substantially with content in other smoking cessation apps, with additional information about medication safety for people with mental illness.

Several study limitations merit consideration. First, participants were not required to be interested in quitting smoking in order to participate in the study; individuals who are actively engaged in an attempt to quit smoking may ultimately prefer different app features. Second, participants were predominantly White residents in a small New England city, and may not be representative of smokers with serious mental illness who have other demographic characteristics or are from other geographic regions. Yet the substantial overlap between our findings and those of research in other populations [30,33,42,43] supports the validity and generalizability of the themes conveyed here. Lastly, most participants had not previously used apps for smoking cessation, and therefore, relied on anticipated future desires for their responses. While anticipation of future desires can be subject to a number of biases, assessing participants’ preferences prior to exposure to specific apps is important to understanding how they will appraise apps during initial use. Future work should assess responses to cessation apps in this population.

Young adults with serious mental illness expressed similar reasons for quitting smoking or continuing to smoke compared to those expressed by other populations of individuals who smoke, but low cessation treatment utilization rates and quit rates suggest that other treatment modalities are needed. Apps have the potential to support quit or reduction attempts for young adults with serious mental illness in a number of ways, such as providing ongoing motivation during a quit attempt, increasing awareness of smoking habits and money spent, and providing information and support for using cessation skills. However, while young adult with serious mental illness who smoke are interested in using apps, further tailoring, optimization, and clinical support may be necessary to effectively promote cessation in this population.