Participants were recruited from the pediatric endocrinology department of a hospital located in Michigan’s Upper Peninsula. Michigan’s Upper Peninsula is composed of 15 counties, all of which are designated as rural by the US Census Bureau [33,34]. EAs meeting the following criteria were eligible: (1) age 16-25 years, (2) diagnosed with T1D for ≥6 months, (3) no comorbid medical conditions altering diabetes management, (4) no comorbid mental health conditions altering cognitive state, and (5) no learning disability precluding participation in study activities.

In total, 10 EAs were identified and agreed to participate; however, one did not complete the study. Of the 9 participants, most identified as non-Hispanic White (89%), half were male (56%), and the mean age was 18.8 (SD 2.7) years. In total, 6 (67%) were in high school, and 6 worked part-time. All 9 lived with their parents and rated their relative socioeconomic status as 5.6 (SD 1.4) out of 10 on the McArthur scale, reflecting a lower-than-average socioeconomic status [35]. The mean duration of diabetes was 8.6 years (SD 4.3) and most managed diabetes with a CGM (89%, n=8) and an insulin infusion pump (89%, n=8). On average, EAs traveled 48.2 (SD 58.7) miles to attend a diabetes clinic at the recruitment site.

Study details are summarized in the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile HEalth Applications and onLine TeleHealth) checklist available in Multimedia Appendix 1.

Participants were identified by a diabetes clinic nurse who reviewed their medical chart for inclusion. The nurse contacted eligible patients by phone to request permission to share their contact information with the research team. Research staff followed up with patients to explain study details and enroll them in the study. Eligible participants completed 2 study visits via Zoom. In the first, a research assistant obtained informed consent, after which participants completed a brief Qualtrics survey to record demographic information (eg, age, race, and gender) and diabetes treatment regimen. The second was the focus group discussion. One participant completed an individual interview.

In total, 2 focus groups with 3 and 5 participants each were led by 2 trained research assistants (RAs). One RA took notes and provided technological support. The second used a semistructured interview guide developed for the study to direct the discussions through 5 segments over 120-150 minutes. The first asked participants to describe their experiences living with T1D in a rural community, including barriers and challenges to diabetes management at the individual, family, peer, health care setting, and community levels. The next 4 segments introduced each intervention and solicited EAs’ impressions, feedback, and recommendations. One participant was unable to attend a focus group but agreed to complete an individual interview. This participant responded to the same questions from the focus group semistructured interview guide. The notetaker verified the Zoom focus group and interview transcriptions for accuracy.

Data were hand-coded by 2 coding teams. The first was led by the lead author (AIC, female), a qualitative expert and developer of the MES, TXT, and QPL interventions, and included 4 coders, a paid RA, and 3 student volunteers. This team analyzed EAs’ feedback on living with T1D in rural communities and the MES, TXT, and QPL interventions using conventional content analysis [40]. During the initial training period, coders became familiar with the study aims and background, data collection methods, and analytic approach. They developed the initial coding framework based on the content of the interview guide and an initial review of all transcribed data. Coders independently coded each transcript, then met to review and discuss their coding, identifying and resolving coding discrepancies through discussion and collaboratively developing consensus-coded transcripts. The coding framework was refined and supplemented with examples throughout this iterative process. Data saturation was not a goal of this exploratory study. The secondary team coded feedback on MyT1DHero following a similar procedure. Coders were 2 RAs with previous experience with MyT1DHero, led by its principal investigator (BH).

The primary author’s institutional review board (IRB) approved all procedures (IRB protocol #071318B3E reviewed by the Wayne State University Institutional Review Board B3- Social, Behavioral, Education Committee [IRB00000327]). All research participants provided informed consent via an information sheet as part of the study enrollment process. For participants who were <18 years old, research staff obtained parental consent and youth assent. All study data were collected using a coded identifier to protect participants’ identities; the linkage to participants’ identities was stored securely and accessible only to IRB-approved research staff until the data analysis concluded, then it was destroyed. Participants received a US $50 gift card after the second visit.

EAs explained because they live in a small community “everyone already knows” they have diabetes, but people in their community do not understand the different types of diabetes: “It’s really hard to get anyone my age, or anyone in general, to understand the difference between type 1 and type 2. Even my really close friends still relate me to one of their grandparents that have type 2.” EAs reported that community members did not understand how they must live and care for their diabetes. This included voicing concerns about food and sometimes going even further and attempting to limit their eating behavior: “I deal with it every time there's a birthday or any sort of snack or something. People are like, can you eat that? Are you sure you can eat that?“ Because of this knowledge deficit, EAs reported experiencing diabetes stigma. “People just assume, ‘Oh, you didn’t take care of yourself, so you got diagnosed with diabetes.” These experiences contributed to feelings of self-consciousness. EAs reported feeling hyperaware or “on stage” when in a public context, leading to anxiety and sometimes changes in their diabetes care practices: “I wouldn’t leave class even though I could feel that my blood sugar was low because I didn’t want to have to ask.”

In contrast to those moments, EAs also recounted experiencing diabetes-specific social support. Not unexpectedly, family was a primary source of support for diabetes. EAs described their parents providing support in the day-to-day management of diabetes: “Sometimes, if I don't feel it [low/high blood glucose] or I don't notice, my dad's connected to mine, so he'll text me and let me know.” EAs reported that their parents also continued to play a key role in communicating with their diabetes care provider and coordinating their diabetes supplies: “My mom helps with the carb counting and servings, and, actually ordering the prescriptions and everything that I need.” Friends were another source of support, such as prompting EAs to check blood sugar after noticing a change in behavior or mood: “I have one best friend who if I'm mad or I'm upset or I'm going pale, she’ll be like, ‘what's your blood sugar right now?’” Finally, some described experiencing support from other members of the community. To illustrate, one EA explained, “I'm involved with a martial arts group that helps me take care of my diabetes a lot.”

Rural EAs described medical care challenges, including continuity of care, location and accessibility of diabetes care providers, and concerns about the affordability of medical care. For continuity of care, EAs’ discussed the challenge of trying to maintain the same team of medical care providers over time: “the hospital cycles through diabetes related personnel, every couple of years or sometimes even every year there’s new people.” EAs reported frequent changes in clinic personnel affected their relationship with providers: “For the past 5 years, I've had mostly the same diabetes doctor. But when I first got diagnosed, I saw all of them like one after the other and it felt like I was like resetting every single time because I would have to explain to them all these different things over and over again. By keeping with the same doctor, we can build upon things instead of restarting every time.”

Another challenge of clinical care in a rural setting was provider location and accessibility. EAs explained that they must travel long distances, which requires extended periods of time to receive their diabetes medical care: “For the past 14 years, I’ve had to drive 3 and a half hours for an endocrinologist, 4 times a year.” EAs reported limited access to diabetes support services in their local community: “It's a 2-hour drive there and at our clinic here there's not much diabetes education at all. We used to have a diabetic educator, but she retired and so there's no one.” EAs found accessing primary health care services was also a challenge: “I’ve been trying to see a primary care physician for the past year, just because everyone’s full up because there’s only so many doctors in the area. I’ve had to wait a while until the doctor will let me in.” Local providers were also unfamiliar with T1D: “a lot of people in the clinic, they know what it [T1D] is, but they don’t really know much about it.” EAs also described limited access to emergency services: “Back in 2020 something was wrong with my blood and I ended up passing out. I was seizing a little bit and we had to call the paramedics. Because we’re so far outside of town it probably took about 25 minutes for them to get to my house. I was fine but that was a realization for my family, that was pretty scary for us.” EAs also reported the scarcity of medical care impacted their transition to adult health care: “They very clearly said, we're not kicking you out, but you do have to look. You have to find someone else because their spots are limited too.”

Finally, EAs shared concerns about medical insurance and maintaining their current coverage: “I'm on Medicaid and every time I get my run down at the end of the quarter, I got that dread. There's no reason they should be kicking me off, but it's still that worry in the back of my head, giving me some anxiety.” They also voiced worries about insurance coverage after turning 26 and were no longer eligible for their parents’ insurance: “Having insurance is the biggest worry for all of us subconsciously. I originally went to school for pharmacy and now I switched over to education. Trying to focus on a career that has health insurance is huge. That’s everybody’s worry after 25.”

This study examined the experiences of a high-risk population of EAs with T1D living in rural communities [14,15]. EAs reported diabetes challenges in their community and medical care. Firstly, EAs felt stigmatized because of their diabetes. More than half of adolescents [41] and EAs [42] with T1D report feeling stigmatized in their communities. Adults with diabetes living in rural communities also report greater stigma than those in non-rural settings [43]. The visibility of diabetes wearable technologies, that is, pumps and CGMs, may contribute to the experience of stigma [43]. Diabetes stigma is associated with poor diabetes quality of life [41], poor glycemic control [42], health complications [44], and poor psychosocial functioning [45], which were also reported by rural EAs in this study. While mental health screening and referral to behavioral services are standard practices [46,47], the assessment of stigma and its negative sequelae may be underrecognized. Conversely, rural EAs also reported perceiving social support related to caring for their diabetes from family, friends, and other trusted community members, a protective factor that may offset the detrimental effects of stigma [48]. Positive role models who provide health advice can be a critical source of social support for youth [49], but may be limited in rural communities [49].

EAs described challenges in their diabetes medical care due to traveling long distances to receive medical care and a limited number of providers in their local community, which impacted the continuity and quality of their diabetes medical care. These concerns are consistent with previous reports of reduced access to health care providers and specialty care providers specifically [4,10,11,49], frequent provider turnover [10], and limited resources for diabetes education [12] and ancillary services [7,8]. While telehealth may be a useful supplement to in-person care, EAs in other contexts have stressed the importance of in-person care for high-quality diabetes care [50]. EAs are also worried about their pending transition from the pediatric to adult health care system and their ability to afford medical care. A T1D Exchange study [51] found financial stress to be a significant predictor of having an elevated hemoglobin A_1c amongst EAs with T1D, suggesting a need for supportive interventions during this transition.

Despite the elevated risk experienced by EAs with T1D living in rural communities with scarce resources for diabetes management, few interventions have been designed specifically to meet the needs of this population. EAs themselves have reported that the transition to adulthood and the assumption of responsibility for diabetes care are significant challenges [52], reinforcing the need for support during this developmental period. The EAs in this study viewed the mHealth interventions examined as user-friendly and acceptable. They identified strengths and weaknesses of the reviewed interventions that could be applied to future interventions developed for the EA population.

As digital natives, EAs are early adopters, savvy users, and innovators of technology use, having grown up with technology integrated into their social ecology [53]. Thus, it is unsurprising that EAs described technology-delivered interventions as a good fit for their age group and recommended further integration with technology, such as linking intervention components to the electronic medical record. For EAs living in rural communities, technology-based interventions may offer critical support in a setting where resources are low and barriers to supportive services are great [54].

In addition to digital delivery, EAs highlighted aspects of the interventions’ that increased accessibility, individualization, and applicability of the intervention content to their own lives and those of other EAs living with T1D. A recent systematic overview of 18 systematic reviews and meta-analyses of digital interventions for adolescents and young adults with mental health conditions similarly found design elements that were credible, engaging and interactive, relatable, and flexible were associated with acceptability [54]. In addition to being acceptable, mHealth interventions demonstrate promise for improving glycemic control [55,56].

Consistent with their developmental stage, EAs found aspects of the intervention that supported their independence appealing and suggested ways to further support their growing independence. For example, they suggested augmenting the MyT1DHero intervention’s communication feature to allow for friends, roommates, or significant others to support their diabetes care rather than exclusively relying on parental support. Additionally, EAs recommended that the intervention broaden its social support component by facilitating connections with peers beyond their local community. They believed that expanding their social network in this manner would help mitigate the feelings of isolation and stigma often associated with T1D. Other studies conducted with urban adolescents have supported the value of peer support beyond one’s local community [57,58].

This study has limitations. First, EAs in this study were all using state-of-the-art diabetes care technology (ie, insulin pumps and CGMs) and self-described themselves as well-managed and independent in their diabetes care, which differs from reports that EAs are less likely than other age groups to use diabetes technologies consistently [20,21] and more likely to experience suboptimal adherence [16,17], glycemic control [18], and higher rates of diabetic ketoacidosis [19]. Furthermore, they were all from a small rural area of Michigan. Thus, their diabetes care experiences, needs, and perceptions of the interventions presented may differ from those of EAs not using the same diabetes technology, with the same high level of glycemic control, or living in different rural communities. A methodological limitation may be the use of video conferencing to conduct the focus groups. While video conferencing enabled EAs living in geographically distant communities to come together for the focus groups, the dynamics of the discussions may have been attenuated in the digital domain, although others have found no impact on data quality [59]. Finally, given the limited sample and small number of focus groups, these results may not reflect data saturation.

mHealth intervention is a promising strategy to support EAs with T1D living in rural communities. EAs found a variety of approaches to optimizing diabetes management acceptable and well-aligned with their developmental needs for autonomy and independence. Each approach was seen as offering critical support for diabetes management in communities where social support and tangible resources were limited. Their feedback highlights the importance of tailoring supportive interventions to the specific needs and preferences of EAs in rural communities [60,61]. Next steps could include refining these intervention approaches based on this feedback and testing their impact on diabetes management and glycemic outcomes among EAs living in rural contexts.