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HHS Public Access Author manuscript Author Manuscript Diabetes Educ

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HHS Public Access Author manuscript Author Manuscript Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Published in final edited form as: Diabetes Educ. 2019 April ; 45(2): 194–202. doi:10.1177/0145721718825342. Experiences of Adolescents and Emerging Adults Living With Type 1 Diabetes Karishma Datye, MD, MSCI, Kemberlee Bonnet, MA, David Schlundt, PhD, Sarah Jaser, PhD From Vanderbilt University Medical Center (Dr Datye, Dr Jaser) and Vanderbilt University (Ms Bonnet, Dr Schlundt), Nashville, Tennessee. Author Manuscript Abstract Purpose—The purpose of this study was to identify barriers to adherence in type 1 diabetes through adolescent focus groups and to use this information to determine how diabetes educators can have a positive impact on their patients’ diabetes management. Methods—Two focus groups were conducted with adolescents and young adults (n = 11) ages 17 to 21 with type 1 diabetes. A focus group script, which consisted of 4 open-ended questions about diabetes care and challenges associated with management of diabetes, was used to elicit discussion. The focus group transcripts were coded and analyzed using the inductive-deductive approach. Author Manuscript Results—Participants described unique barriers to and facilitators of self-care behaviors in their management of type 1 diabetes. A conceptual framework was developed to describe adherence to self-management in adolescents with type 1 diabetes. Biological, psychological, and environmental situational influences emerged that influence self-care behaviors. In addition, facilitators of self-care behaviors, including the health system and diabetes education, were identified, and together the interaction between situational influences, facilitators, and self-care behaviors influenced adherence to diabetes treatment. Conclusions—The conceptual framework based on these focus groups may help diabetes educators assess and address barriers to self-care behaviors in adolescents and young adults with type 1 diabetes. Author Manuscript Type 1 diabetes management during adolescence and the transition to adulthood is particularly difficult given the multiple stressors unique to this time period.1 The worsening glycemic control noted as youth progress through adolescence2 is very concerning given the complications associated with chronic uncontrolled hyperglycemia, including retinopathy and nephropathy.3,4 While diabetes management in this age group is exacerbated by physiologic changes (puberty and associated insulin resistance), several other factors are implicated in the worsening glycemic control of adolescents, notably poor adherence to therapy.5–8 As adherence9 to therapy increases, hemoglobin A1C decreases; thus, to improve glycemic control in adolescence, self-care behaviors should be identified and targeted.7 It is Correspondence to Karishma Datye, MD, MSCI, Ian M. Burr Division of Pediatric Endocrinology and Diabetes, Vanderbilt University Medical Center, 1500 21st Avenue South, Suite 1514, Nashville, TN 37212, USA (karishma.a.datye@vumc.org). Datye et al. Page 2 Author Manuscript critical, therefore, for the diabetes educator to understand the unique difficulties young people experience during this time period.6,10,11 Diabetes educators play a crucial role in the education and management of youth with type 1 diabetes. With younger children, diabetes educators focus on providing education to the family of the patient, but in the adolescent and young adult age group, educators and other providers must focus primarily on the patient, who may be treating their diabetes relatively independently. This age group is one of marked transition and independence, which has several unique barriers to adherence, including the transition to independent diabetes management, decreased parental involvement, involvement of peers, and psychosocial barriers, such as mood disorders, anxiety, and eating disorders.6,11 By understanding the unique barriers to adherence that adolescent and emerging adult patients may face, educators have increased ability to assess and address the barriers to improve adherence to therapy. Author Manuscript Author Manuscript While barriers to adherence in type 1 diabetes have been studied previously,6 and the association between adherence to therapy and improved glycemic control has been shown,7 much of the research in this age group has focused on self-report measures rather than qualitative focus group studies,12,13 which may limit our understanding of challenges and facilitators. While survey instruments and validated assessment tools14,15 are critical to understanding barriers to adherence, they do not allow for discussion about the barriers in question. Some studies have performed focused individual interviews with patients with type 1 diabetes; for example, Pyatak et al8 interviewed young adults with type 1 diabetes to explore psychosocial stressors to diabetes care. This study found their study population reported several psychosocial stressors, and these stressors were associated with worsening glycemic control, but further assessing these barriers in a group setting may shed more light on specific stressors. In addition, while some studies have used focus groups to facilitate discussion among patients with type 1 diabetes, these studies have primary focused on a particular barrier or a particular group of patients. Kennedy et al16 conducted a focus group of newly diagnosed patients with type 1 diabetes to understand barriers to exercise in this population, but this study was focused specifically on exercise and other barriers were not examined. Therefore, the purpose of this study is to identify barriers to adherence in type 1 diabetes through adolescent focus groups, to use this information to increase understanding of these barriers, and to determine how diabetes educators and other providers can have a positive impact on their patients’ diabetes management. Methods Research Design Author Manuscript Focus groups were conducted to explore barriers to adherence in youth with type 1 diabetes. Focus groups were chosen to allow for robust discussion between participants and to facilitate more in-depth discussion than may be possible with individual interviews. In addition, this study was primarily designed to understand barriers in youth, and focus groups were used to allow for discussion among peers that may not be possible in other research settings. Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 3 Sample/Setting Author Manuscript Author Manuscript Participants were recruited from the Vanderbilt Pediatric Diabetes Clinic, a busy urban center that cares for over 2700 youth patients with diabetes (primarily type 1 diabetes). The patient population is approximately half female, with ethnic breakdown as follows: 60% white, 10.4% black or African American, 1.6% Hispanic, 0.5% Asian or Pacific Islander, and 27.5% pediatric patients with unknown ethnic background. A prior study exploring barriers to adherence in type 1 diabetes had previously been conducted by the authors of this study, and participants in that study were asked whether they would like to participate in the current focus group-based study. Those participants who asked to be contacted about this study were informed about the study and invited to participate either over the phone or in the clinic itself, in accordance with the recruitment and consenting protocol approved by the institutional review board (IRB). Additional participants were recruited while being seen in the diabetes clinic for routine care once all previous study participants who were interested in the focus group study had been contacted. The study team followed a recruitment script that had been approved by the IRB, and participants were informed that participation was voluntary. See below for inclusion and exclusion criteria. Participants and Procedure Author Manuscript Two focus groups were conducted with adolescent patients diagnosed with type 1 diabetes receiving health care at Vanderbilt University Medical Center. Inclusion criteria consisted of (1) pediatric clinic patients ages 17 to 21 who had been diagnosed with type 1 diabetes for greater than 1 year (as defined by an endocrinologist), (2) treatment with basal/bolus insulin, and (3) English speaking. Adolescents with psychiatric comorbidities such as schizophrenia or bipolar disorder were excluded from participation, as these could exist as barriers to adherence to diabetes management that are outside the scope of this study. All participants were recruited following the protocol approved by the IRB. When participants arrived for the focus group, informed consent was obtained from the parents and assent from participants under 18 years of age. Participants 18 years and older provided informed consent. Demographic data were collected prior to starting the focus group (see Table 1). A trained focus group facilitator used a semistructured focus group guide consisting of openended questions to conduct the 2 focus groups. Questions were developed with input from a multidisciplinary team, including an endocrinologist, a pediatric psychologist, and experts in qualitative research. Participants were asked 4 primary questions about diabetes care and challenges: Author Manuscript 1. Think about a day when everything went well, and you were able to do everything you need and want to do to take care of your diabetes. What worked that day, what made it possible to do everything you needed to do to take care of your diabetes? 2. If you could change anything about how your doctor, nurse practitioner, dietician, nurse, etc. interacts (talks with you) and works with you, what would it be? Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 4 Author Manuscript 3. Talk us through your daily diabetes routine and tell us about what makes certain times of the day more or less challenging/hard to take care of your diabetes? We are hoping to learn what seem to be the most challenging/difficult issues in taking care of your diabetes, and what are the most challenging or hardest times of day for taking care of your diabetes. 4. We have spent some time talking about type 1 diabetes, and some of the things that may make it easier or harder to manage. Think back to 5 years ago (or middle school), what was different back then? Specifically, were there things that made it easier or harder to manage your diabetes? Are these things the same now, or have things changed? Specific prompts were developed for each question to facilitate detailed discussion of the 4 questions. Author Manuscript Two different focus groups were conducted; the first had 7 participants, and the second had 4 participants. Focus groups were digitally recorded, and transcription was performed by Rev.com. Focus groups were transcribed within 3 days of focus group completion. The first focus group was 79 minutes, and the second focus group was 68 minutes. Focus groups were led by a psychologist with experience in focus groups and youth with type 1 diabetes.17,18 Participants were compensated with a $20 gift card upon completion. Analysis Author Manuscript Qualitative data coding and analysis was managed by the Vanderbilt University Qualitative Research Core, led by a PhD-level psychologist. Data coding and analysis was conducted by following the COREQ guidelines,19 an evidence-based qualitative methodology. Experienced qualitative coders first established reliability in using the coding system, then independently coded both transcripts. Coding of each transcript was compared, and any discrepancies were resolved to create a single coded transcript. Each statement was treated as a separate quote and could be assigned up to 5 different codes. Transcripts were combined and sorted by code. Analysis consisted of interpreting the coded quotes and identifying higher-order themes, using an iterative inductive-deductive approach. Deductively, theoretical contributions to the analysis included (1) the AADE7 taxonomy of selfmanagement behaviors (the AADE7 is a framework for understanding the essential elements of diabetes self-management and includes healthy eating, physical activity, monitoring, medication, problem solving, risk reduction, and healthy coping),9 (2) social cognitive theory,20,21 and (3) a biopsychosocial framework.22 Inductively, the codes and themes from the focus groups were used to fill in the details of the conceptual framework. Author Manuscript Results Conceptual Framework Using the inductive-deductive approach, we developed a conceptual framework to describe adherence to self-management in adolescents with type 1 diabetes. A hierarchical coding system was developed and refined using the focus group guide and a preliminary review of 1 transcript. Major categories included (1) good/bad days, (2) lifestyle, (3) barriers to diabetes Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 5 Author Manuscript management, (4) interactions with the medical team, (5) self-care/general habits, (6) emotional experiences related to diabetes, (7) social support, (8) other topics, and (9) timing of diabetes challenges. Major categories were further divided from 1 to 9 subcategories, with each subcategory having additional levels of hierarchical divisions. Definitions and rules were written for the use of each category (https://healthbehavior.psy.vanderbilt.edu/datye/ DatyeCodingSystem.pdf). Author Manuscript Figure 1 illustrates that biological, psychological, and environmental factors influence selfcare behaviors. These situational influences sometimes make it harder to adhere to selfmanagement behaviors and other times serve as motivators to self-management. The center of the framework depicts self-management as a dynamic interaction of all 7 categories of self-care behaviors. Systems-level influences on self-care behaviors are conceptualized as the health system and diabetes education. The situational and systems-level influences can include both challenges and facilitators. The interactions among challenges, facilitators, and self-care behaviors are viewed as influencing adherence to diabetes self-management, thus affecting health outcomes. Health outcomes occur on a continuum from poor control to good control and may vary from time to time and situation to situation. In addition, adherence to self-management behaviors creates feedback. This feedback may affect the biological, psychological, and environmental influences; may change future self-management behaviors; or may change the individual’s receptivity to health care and diabetes education. In the following sections, we discuss each element of the conceptual framework. We give a general description and cite specific quotes that illustrate key themes. Situational Influences Author Manuscript Author Manuscript We identified biological, psychological, and environmental factors that function as situational influences on an individual’s diabetes self-care behavior. The dominant themes around biological challenges were centered on hypoglycemic episodes; these related to hunger, cravings, symptoms, time of day, and fatigue. Participants’ discussion of hypoglycemia and fatigue centered on waking up with a low level of glucose, which led to disrupted sleep, thus contributing to fatigue: “You wake up and honestly, I feel like I’m about to die. … Literally, I feel like I’m delirious, so I’m just in there grabbing everything I can get … I don’t like when I wake up in the morning, really early in the morning, because I feel like I’m missing out on sleep.” Participants also discussed episodes of hypoglycemia as related to cravings, expressed as loss of control: “I eat everything when it’s low. When I’m at work and I have my glucose tablets, I’ll just eat that, but if I’m at home I’ll just sit by a cabinet and eat until I can’t eat any more. … Yeah, but it’s like a craving for me.” Hypoglycemic episodes were also discussed in terms of feeling sick, causing inability to eat: “I don’t know if those [sic] goes for anybody but me, but sometimes when I’m low, I guess it’s maybe off a really high and just crashing rapidly, I refuse to eat. I feel like I can’t eat anything or drink anything. It’s almost like if I try just eating it, I’m going to throw it right back up. It’s almost like severe nausea, I guess.” Psychological challenges included 5 primary elements: knowledge, affect, cognition, motivation, and life goals. Participants also discussed self-deprecating humor, reframing, and setting goals as psychological strategies that facilitate better adherence. Discussions of Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 6 Author Manuscript affect focused primarily on fear of one’s future diabetes health status: “My dad is diabetic too and he has auditory hallucinations, so his stories scare me. I always get like if I’m too low that could happen or if I’m high, one of those days where you just can’t get it down I’m like, I’m going to go blind in a couple of years because of this. Or just thinking am I going to lose a foot, am I going to have all these medical problems—that fear.” Two primary coping strategies were discussed in focus groups, humor and reframing. Humor tended to be self-deprecating: “The other kids, when they joke about it, I’m laughing with them. I’m like, ‘Yeah, I got the beetus.’” Cognitive reframing was a way to turn a challenge into a benefit: “It sucks to have diabetes, but I guess it’s nice to look at the things you can do. I got to talk to my class and I babysit a little girl that has diabetes. … You got to make the best out of it.” Setting one’s life goals is also a challenge: “I think one of the bad things is I can’t do as many jobs. We can’t fly airplanes. My dad was in the military so I was like ‘oh, that sounds cool.’ And then they were like ‘you can’t go in the military.’” Author Manuscript Author Manuscript Environmental challenges to diabetes self-management included school, competing priorities, and peer relations. Peer relations in a school setting were seen as challenging, primarily centering on the risk of being bullied or avoiding attention from others when performing diabetes care: “I had a lot of problems in high school with it. I would eat and I wouldn’t take my insulin or I wouldn’t check my blood sugar, just because I didn’t want to draw attention to myself … you don’t want to get bullied about it. I just feel like people target you on anything. I felt like my diabetes was an easy target.” Interacting with teachers also created challenges to self-management: “One time, my blood sugar was low in class and I didn’t feel like it was real low, so I was just going to drink the juice in class. She [teacher] didn’t allow drinks or food or anything. I was like, ‘Can I drink this?’ She freaked out on me.” School, overall, was expressed as a competing priority with diabetes selfmanagement: “When school starts, I guess diabetes takes a backseat, because I’m worried about other things.” Systems Influences Author Manuscript The health system refers to the type and quality of health care. Adolescents with type 1 diabetes are typically treated by pediatric endocrinologists and also may receive care from dietitians, nurse practitioners, and mental health providers. In addition to the health system, diabetes education is also a facilitator of self-care behavior. Diabetes educators assist patients in acquiring the knowledge and skills they need to manage their diabetes. Highquality diabetes education can have positive influences on self-care behaviors. Participants discussed the planning piece of self-management with their diabetes providers: “It’s a like a game plan. He [diabetes provider] helps map it out, like, okay, if finals are here, it’s probably going to be a little bit higher in here. It’s where you need to just pay a little bit more attention. Not necessarily check it twice as much or anything. Just pay attention how I’m feeling. How I’m acting.” Providers helped participants review self-management strategies that could be improved: “In my [diabetes provider] appointments we go over what I need to do and what I’ve done wrong. If anything needs to change as far as my basal rate or anything. If I don’t change it I need to change myself and what I need to do as far as, like I said, taking medicine, check my blood sugar more often and whatnot.” Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 7 Author Manuscript Participants discussed the effective delivery of self-management education by diabetes providers: “Yeah, they do a good job at explaining it. I think because this is the pediatric side so they word it so you understand and then you learn it, the longer you have it and they just do a really good job of helping me understand what it is and how it works.” Diabetes providers are also effective in delivering the message to patients that serious consequences can occur from mismanagement: “They [diabetes providers] tell me all the bad things that can happen to me later on and I get that.” Self-Care Behaviors Diabetes self-management behaviors included diet, physical activity, monitoring, insulin, problem solving, coping, and reducing risks (based on the AADE7 taxonomy of selfmanagement behaviors9). Author Manuscript Participants discussed positive self-management in terms of steadiness of blood glucose levels without disruption to activities they enjoy and administration of proper insulin dosages: “I think a good day is when I can eat what I want and do what I want, and my blood sugar stays right where it needs to be. I’m giving insulin right when I need to or the exact dosage and all that. I don’t really experience any fluctuation.” Self-management was also discussed in terms of personal responsibility for self: “I think more about diabetes and planning out my day than I did before because I have to be responsible now since I’m an adult.” Author Manuscript Participants discussed planning ahead as a self-management strategy. In terms of hyperglycemia, this was discussed in terms of personal reminders: “I set alarms on my phone. Lantus time or ‘don’t forget to check your sugar’ or reminders on my pump if I need to do a bolus at certain times.” Regarding hypoglycemia, discussed in terms of adequate amounts of carbohydrates to treat hypoglycemia, “I just have to think more about it, what I’m doing and guess how that’s going to affect me in a couple hours and am I at a place, if I’m low is there going to be snacks or should I bring it?” Negative self-management behaviors were discussed in terms of eating and lack of blood glucose checking as risks for hyperglycemia: “When say I get home from school, I’m so tired that I just don’t even check my blood sugar and I eat something. That’s why in the afternoons my blood sugar’s always higher, because I don’t normally check my blood sugar even though I should” and “The snacks, I usually don’t check my blood sugar before eating it. I do take the insulin, but usually afterwards when I do take my blood sugar, it’s still high because I didn’t check it before eating.” Author Manuscript Feedback Discussion in this section centered on hyperglycemic situations. Successful adherence to self-management behaviors provides feedback on how to respond to future challenges and reinforces self-efficacy and motivation. On the other hand, poor adherence could lead the patient to “give up” and not try as hard in the future, reducing self-efficacy and lowering motivation: “A month or so ago, I was really high before I was going to bed and I was so tired because I’d already stayed up for two hours trying to get it down and it was three in the morning and I was finally like, ‘I don’t really care.’” There is also a sense of frustration in Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 8 Author Manuscript that he or she can adhere to self-management but not obtain desired results, which could also lead to giving up: “Bad days … I’ll wake up with a high blood sugar and then I’ll eat breakfast. I’ll do what I’m supposed to. Then my lunch. I’ll still have a high blood glucose. That I think will frustrate me just because I’m supposed to be doing what I’m supposed to, but … it’s still not in the range that I need it to be in, so I think that’s what frustrates me.” Adherence to diabetes self-management behaviors improves glycemic control; however, there is not a perfect relationship between adherence and diabetes control. Patients who are adherent to their diabetes care still experience hypoglycemia and hyperglycemia, which can result in feelings of frustration. Discussion Author Manuscript In this study, adolescents and young adults with type 1 diabetes described barriers to and facilitators of adherence (see Figure 1), classified as situational influences (biologic, psychologic, and environmental influences) and systems influences (including the health system and diabetes education). Several specific areas of concern emerged among youth participants (see below), and addressing these concerns may offer diabetes educators an opportunity to assess and address barriers to adherence in their patients. Author Manuscript Hypoglycemia was noted as a significant challenge (biological situational influence). Several participants mentioned the difficulties in treating hypoglycemia, how their environment made treatment challenging (ie, management in school), and the craving that many experience with low blood glucose. Participants also made several interesting observations about hypoglycemia, specifically stating that they did not want to draw attention to themselves in school when they experienced low blood glucose and that treating hypoglycemia could be difficult because they wanted to eat a large quantity of food. These observations provide an opportunity for diabetes educators to focus on hypoglycemia as a barrier to adherence. For example, understanding that adolescents do not want to call attention to themselves with hypoglycemia in school may be a reason to consider a continuous glucose monitor (and specifically a continuous glucose monitor that does not alarm), a device used less in adolescents than other age groups.23 In addition, diabetes educators can focus on appropriate management of hypoglycemia and practical suggestions, such as carrying appropriately portioned rapid-acting carbohydrates in small individual containers (ie, 4 glucose tabs or approximately 16 g of carbohydrates). Similarly, if patients feel that drinking juice in class may call attention to themselves while in school, diabetes educators may provide patients with a list of other rapid-acting carbohydrates that patients may carry with them. Author Manuscript It is also notable that, while several adolescents and young adults in our sample mentioned their difficulties with hypoglycemia, this is not traditionally thought of as a barrier to adherence. Although questionnaire measures to assess fear of hypoglycemia exist (eg, Hypoglycemia Fear Survey),24 validated measures of adherence, including the PRISM and Barriers to Diabetes Adherence scale, do not have specific questions about hypoglycemia. 14,15 In addition, if patients are worried about hypoglycemia, they may keep their blood glucose above their target range, causing hyperglycemia. Specific questions about fear of Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 9 Author Manuscript hypoglycemia and barriers to appropriate treatment of hypoglycemia may help the diabetes educator appropriately address this barrier during clinic visits. Author Manuscript Adolescents described their interactions with their providers during office visits as both positive and negative. For example, 1 participant described always feeling nervous on days of the diabetes appointment while waiting for the A1C result. Participants also noted that the medical team often focuses on what is wrong, what needs to be changed, and how poor diabetes control in the future can lead to bad outcomes. These findings are similar to those reported by Lowes and colleagues,25 in their study of adolescents’ and caregivers’ perceptions of clinical care in diabetes. However, adolescents in our study noted that focusing on the immediate effects of blood glucose levels and management is more important than discussing future outcomes and potential complications. This observation is in line with other pediatric studies that have shown focusing on what matters to the adolescent now is more likely to result in behavioral change.26 Interestingly, recent studies have also found that young adults with type 1 diabetes may want to talk about the difficulties they have in living with and managing their diabetes and that providers should make a point to discuss this at visits.27 Author Manuscript These points are key for diabetes educators—goal setting with the patient and working toward the patient’s goals may be an important motivating factor for adolescents. For example, for adolescent athletes, focusing on improving glycemic control to improve weight gain and muscle mass may be more helpful than focusing on long-term complications such as nephropathy and retinopathy. Furthermore, framing the visit in a positive light, providing feedback for patients about improved glycemic control helping to achieve their goals, rather than focusing primarily on negative aspects of diabetes management, may improve attitudes about clinic visits in this population. Health care providers could also acknowledge the frustration of performing self-care behaviors and not seeing results. Clinic visit attendance is notoriously poor during the adolescent and young adult transition period,28 and an increased focus on what matters to the patient, with joint goal setting and discussion of how the transition process works, may increase attendance.29 Some clinics have also considered group visits as a way to allow adolescents who may be struggling with similar issues to focus on their concerns together.30 Given that adolescents and young adults in our sample raised issues that are not typically covered in diabetes education (eg, skipping insulin when with peers, managing diabetes when using alcohol), group visits may be a unique way for diabetes educators to address some of the negative concerns participants have about clinic visits. Author Manuscript The current study contributes to our understanding of situational and health systems barriers to and facilitators of adherence in adolescents and young adults with type 1 diabetes, but limitations should be addressed. While each focus group led to robust discussion of management of type 1 diabetes, there were only 2 focus groups, and each group had a relatively small number of participants. In addition, all participants were treated at the same medical center, and therefore their diabetes education and clinical experience were likely similar (they were all treated by providers from the same clinic). It would be helpful to conduct focus groups with participants treated at different institutions to see if their diabetes education influenced the barriers or facilitators to adherence they noted. However, although Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 10 Author Manuscript participants were all treated at the same clinic, some lived over 2 hours away, demonstrating the broad catchment area of the clinic and the regional diversity of participants in the study. Acknowledgments: The authors thank Shuodan Zhang for her assistance in enrolling participants for the focus group during her Vanderbilt Medical Student Research Training Program. Funding: This publication was supported by CTSA award No. UL1 TR002243 from the National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. This work was also supported by the Endocrine Fellows Foundation. References Author Manuscript Author Manuscript Author Manuscript 1. Monaghan M, Helgeson V, Wiebe D. Type 1 diabetes in young adulthood. Curr Diabetes Rev. 2015;11(4):239–250. [PubMed: 25901502] 2. Miller KM, Foster NC, Beck RW, et al. Current state of type 1 diabetes treatment in the U.S.: updated data from the T1D Exchange clinic registry. Diabetes Care. 2015;38(6):971–978. [PubMed: 25998289] 3. 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The experience of living with type 1 diabetes and attending clinic from the perception of children, adolescents and carers: analysis of qualitative data from the DEPICTED study. J Pediatr Nurs. 2015;30(1):54–62. [PubMed: 25308399] 26. Yeager DS, Dahl RE, Dweck CS. Why interventions to influence adolescent behavior often fail but could succeed. Perspect Psychol Sci. 2018;13(1):101–122. [PubMed: 29232535] 27. Balfe M, Doyle F, Smith D, et al. What’s distressing about having type 1 diabetes? A qualitative study of young adults’ perspectives. BMC Endocr Disord. 2013;13:25. [PubMed: 23885644] 28. Lyons SK, Libman IM, Sperling MA. Clinical review: diabetes in the adolescent: transitional issues. J Clin Endocrinol Metab. 2013;98(12):4639–4645. [PubMed: 24152689] 29. Monaghan M, Baumann K. Type 1 diabetes: addressing the transition from pediatric to adultoriented health care. Res Rep Endocr Disord. 2016;6:31–40. [PubMed: 27812509] 30. Raymond JK, Shea JJ, Berget C, et al. A novel approach to adolescents with type 1 diabetes: the team clinic model. Diabetes Spectr. 2015;28(1):68–71. [PubMed: 25717281] Author Manuscript Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 12 Author Manuscript Implications Author Manuscript Findings from our study offer novel insights into the challenges in adhering to the recommended treatment regimen in this high-risk population, and this, in turn, has several implications for diabetes educators. Hypoglycemia appears to present a challenge in management of diabetes. Participants voiced fear of hypoglycemia, difficulties in managing hypoglycemia, and how the environment (eg, school) may influence management of hypoglycemia. Diabetes educators should be cognizant of these difficulties and focus on potential areas of concern preemptively. For example, reviewing available technologies such as continuous glucose monitors to aid in detection of hypoglycemia may be helpful to patients trying to minimize hypoglycemia while in school. In addition, practical recommendations can be given such as prepackaging snacks into 15 g of carbohydrates to make treatment of hypoglycemia easier and prevent patients from eating several tabs (or candy) at once, which may cause hyperglycemia. Talking about strategies to avoid drawing attention to them in the middle of class may be very relevant for some patients. As adolescents may be more focused on their current challenges (school, work, sports, etc) as opposed to long-term effects of hyperglycemia, joint goal setting to help adolescents meet their current goals may help engage adolescents more in their diabetes care. Finally, considering options such as group clinic visits may allow adolescents the opportunity to discuss their challenges in a group setting. Given concerns around poor clinic attendance in this age group, finding ways to engage adolescents in their care is crucial. Future studies are needed to understand how diabetes educators can best assess and address these barriers to adherence to help adolescents engage and improve their adherence to diabetes care. Author Manuscript Author Manuscript Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Datye et al. Page 13 Author Manuscript Author Manuscript Figure 1. Factors that influence adolescent self-care behaviors. Author Manuscript Author Manuscript Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Author Manuscript Author Manuscript 7 66 (range, 43–78) mmol/mol Abbreviation: MDI, multiple daily injections. 8.2 (range, 6.1–9.3) % Mean A1C 6 non-Hispanic/Latino, 1 Hispanic/Latino 5 white, 1 black, 1 other Ethnicity 100% insulin pump users Race 10.7 (range, 6–18) 71 18.1 (range, 17–20) MDI/insulin pump Duration of diabetes, y Sex, female, % Age, y Number of participants Focus Group 1 Author Manuscript 4 Focus Group 2 65 (range, 54–73) 8.1 (range, 7.1–8.8) 3 non-Hispanic/Latino, 1 Hispanic/Latino 4 white 25% insulin pump users 9 (range, 5–14) 75 17.8 (range, 17–20) Demographic Information of Focus Group Participants (n = 11) Author Manuscript Table 1 Datye et al. Page 14 Diabetes Educ. Author manuscript; available in PMC 2020 November 09. Lawton et al. BMC Endocrine Disorders (2018) 18:12 https://doi.org/10.1186/s12902-018-0239-1 RESEARCH ARTICLE Open Access Patients’ and caregivers’ experiences of using continuous glucose monitoring to support diabetes self-management: qualitative study J. Lawton1*, M. Blackburn1, J. Allen2,3, F. Campbell4, D. Elleri5, L. Leelarathna6, D. Rankin1, M. Tauschmann2,3, H. Thabit6 and R. Hovorka2,3 Abstract Background: Continuous glucose monitoring (CGM) enables users to view real-time interstitial glucose readings and provides information on the direction and rate of change of blood glucose levels. Users can also access historical data to inform treatment decisions. While the clinical and psychological benefits of CGM are well established, little is known about how individuals use CGM to inform diabetes self-management. We explored participants’ experiences of using CGM in order to provide recommendations for supporting individuals to make optimal use of this technology. Methods: In-depth interviews (n = 24) with adults, adolescents and parents who had used CGM for ≥4 weeks; data were analysed thematically. Results: Participants found CGM an empowering tool because they could access blood glucose data effortlessly, and trend arrows enabled them to see whether blood glucose was rising or dropping and at what speed. This predicative information aided short-term lifestyle planning and enabled individuals to take action to prevent hypoglycaemia and hyperglycaemia. Having easy access to blood glucose data on a continuous basis also allowed participants to develop a better understanding of how insulin, activity and food impacted on blood glucose. This understanding was described as motivating individuals to make dietary changes and break cycles of over-treating hypoglycaemia and hyperglycaemia. Participants also described how historical CGM data provided a more nuanced picture of blood glucose control than was possible with blood glucose self-monitoring and, hence, better information to inform changes to background insulin doses and mealtime ratios. However, while participants expressed confidence making immediate adjustments to insulin and lifestyle to address impending hypoglycaemia and hypoglycaemia, most described needing and expecting health professionals to interpret historical CGM data and determine changes to background insulin doses and mealtime ratios. While alarms could reinforce a sense of hypoglycaemic safety, some individuals expressed ambivalent views, especially those who perceived alarms as signalling personal failure to achieve optimal glycaemic control. Conclusions: CGM can be an empowering and motivational tool which enables participants to fine-tune and optimize their blood glucose control. However, individuals may benefit from psycho-social education, training and/or technological support to make optimal use of CGM data and use alarms appropriately. Keywords: Continuous glucose monitoring, Type 1 diabetes, Qualitative, Patient experience, Caregiver experience * Correspondence: j.lawton@ed.ac.uk 1 Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Lawton et al. BMC Endocrine Disorders (2018) 18:12 Background Continuous glucose monitoring (CGM) enables users to view real-time interstitial glucose readings and provides information on the direction and rate of change of blood glucose levels. Multiple alarms can be set to alert users if blood glucose either rises or falls (or is predicted to rise or fall) beyond predefined target ranges, and individuals are able to access historical data to inform diabetes self-management decisions. CGM is associated with reductions in glycated haemoglobin (HbA1c) levels in both adults and children, especially when used frequently [1–4]. CGM has also been shown to reduce hypoglycaemia and hyperglycaemia [2, 3, 5], severe hypoglycaemia [6]; and, improve treatment satisfaction [7–9] and quality of life outcomes [10, 11]. While the clinical and psychological benefits of CGM are well established, less is known about how individuals use CGM to make informed treatment decisions and why high levels of treatment satisfaction exist. Only limited qualitative research, focusing on user and/or caregiver experiences, has been conducted. This includes work exploring barriers to using, and reasons for discontinuing, CGM in adolescent [12] and adult groups [13]; adult users’ attitudes and characteristics which might help predict effective use of CGM [14]; and, how use of CGM may influence couple’s diabetes management and marital relationships [15]. More recently, Pickup et al. [16] used an open-ended survey question to explore user and caregiver experiences of CGM, including benefits and drawbacks encountered. While this is the most comprehensive study in terms of scope and sampling, Pickup et al.’s design did not permit user experiences to be explored in detail; hence, they recommended further, in-depth research be undertaken [16]. In line with this recommendation, we conducted in-depth interviews with individuals (adults, adolescents and parents) who made nonadjunctive use of CGM over ≥4 weeks in the initial training phase of a closed-loop study. The aim of this interview study was to understand and explore how participants used CGM to support diabetes selfmanagement and what they considered the main benefits and drawbacks to be. Our objectives were to aid interpretation of findings from earlier CGM studies; and, provide recommendations for supporting individuals using CGM. An additional objective was to collect data to allow comparisons to be drawn with participants’ later experiences of using a closed-loop system as part of the trial; these data will be reported separately. Methods Participants and devices Inclusion criteria for trial enrolment included a screening HbA1c ≥7.5% (58.5 mmol/mol) and ≤10% (86 mmol/ mol) and a diabetes duration of at least 6 months [17]. Page 2 of 10 Individuals were required to have used an insulin pump for at least 3 months, with good knowledge of insulin self-adjustment as judged by the investigator [17]. Individuals were ineligible for the trial if they had used CGM regularly in the previous three months. Following trial recruitment, participants were trained to use the study insulin pump (MiniMed™ 640G pump, Medtronic, Northridge, CA, USA) and glucose sensor (Guardian™ Sensor 3, Medtronic by health care professionals who followed a common outline curriculum. Key areas covered in the training included: an insertion and initiation of sensor session, using the sensor menu of the insulin pump and sensor calibrations, use of software to analyse CGM data and use of CGM data to optimise treatment. Written guidelines for the operation and use of the CGM device were also provided in the form of the manufacturer’s user manual. Alarm settings on the CGM device were initially standardized but participants were allowed to adjust these during the study period. Parents/caregivers were unable to remote access their child’s CGM data. Participants who took part in the interview study comprised: individuals aged ≥16 years; individuals aged 13– 15 years and their parent(s)/caregiver(s); and, parents/caregivers of those aged ≤12 years. The decision to interview parents/caregivers of those aged ≤12 years and those aged 13–15 years was made because, in younger groups, parents take responsibility for most diabetes management tasks [18], while supporting and sharing responsibility with adolescents [19]. Interviewees were invited to take part in the qualitative study by members of the clinical team in the four participating UK sites (Cambridge, Manchester, Leeds, and Edinburgh). The clinical team informed these individuals that the qualitative research was being conducted by an independent research team and gave them reassurances of confidentiality. Recruitment and data collection continued until there was representation of different age groups in the final sample and data saturation had occurred; that is, until no new findings were identified in new data collected. The study received approval from the independent Cambridge East Research Ethics Committee (REC ref. 15/ EE/0324). Participants aged ≥16 years and parents or guardians of participants aged < 16 years provided signed informed consent; written assent was obtained from minors before study-related activities. Qualitative study design In-depth interviews were used as the method of data collection, as these afforded the flexibility needed for participants to discuss issues they perceived as salient, including those unforeseen at the study’s outset [20], while use of topic guides helped ensure the data collected remained relevant to the study aims and objectives. An inductive approach was used informed by Lawton et al. BMC Endocrine Disorders (2018) 18:12 general principles of Grounded Theory research [21]. This entailed simultaneous data collection and analysis, with findings from early interviews informing areas explored in later ones. Page 3 of 10 Table 1 Characteristics of study participants Participants with type 1 diabetes (n = 15) Gender, female (n,%) Age at recruitment (years) Data collection and analysis Interviews were conducted by MB at a time and location of participants’ choosing (mostly in their own homes) immediately before they moved into the main phase of the trial, at which point they had used CGM in real-life situations for a minimum of 4 weeks. Topic guides were developed based on literature reviews, input from clinical team members, and revised in light of emerging findings, in line with an inductive approach. Key areas explored included: previous experience of using CGM and self-monitoring of blood glucose (SMBG); understandings and expectations of CGM and impact of CGM (if any) on diabetes selfmanagement; likes and dislikes of the technology; and views about information and training needed to support effective use of CGM. Patients aged 13–15 years old and their parents were interviewed separately. The interviews took place between July 2016 and May 2017. They typically lasted 1–2 h, were digitally recorded and transcribed in full for in-depth analysis. Data were analysed by three experienced qualitative researchers (JL, MB and DR) using a thematic approach informed by the method of constant comparison; this entailed cross-comparison of all interviews to identify recurrent themes, before a coding framework was developed to capture these themes and contextual information needed to aid data interpretation. Nvivo, a qualitative software package, was used to facilitate data coding and retrieval and coded datasets were subjected to further analyses to allow more nuanced interpretations of the data to be developed. Results The sample comprised 12 participants aged 16+ years, three participants aged 13–15 years and nine parents (see Table 1). A 100% opt-in was achieved. Eighteen interviewees (including six parents of child participants) described having had prior experiences of using CGM (e.g. to manage diabetes or as part of an earlier research study). Ease of access to continuous data A key benefit of CGM, as all participants highlighted, was the ease with which they were able to access information about their blood glucose levels. Indeed, it was precisely because this process was so effortless that participants said they were much more aware of what their (or their child’s) blood glucose levels were throughout the day than when only SMBG was used: 7(46.7) 13–15 3 16–20 2 21–30 1 31–40 6 41–50 2 51–60 60+ 1 Professional 5(33.3) Occupation/education (n,%) Self-reported diabetes duration (mean, SD, range - years) Sensor use run-in (% over 4 weeks) Semi-skilled 4(26.7) Retired 1(6.7) Higher education 2(13.3) Secondary school 3(20) ≤12 years 4 ± 2.9 (2–9) 13–17 9.25 ± 3.9 (4.5–13.75) 18+ 25 ± 11.1 (15–45) ≤12 years 81.2 ± 13.8 (64–99) 13–17 85.6 ± 10.8 (77–98) 18+ 89.9 ± 6.4 (77–97) Parents of paediatric patients (n = 9)a Gender, female (n,%) 7(77.8) Age at recruitment (years) 31–40 2 41–50 5 51–60 2 Professional 5(55.6) Occupation (n,%) Semi-skilled 3(33.3) Unemployed/Full time Carer 1(11.1) a This includes: parents who represented children aged ≤12 years (n = 5) and parents of children aged 13–15 (n = 4). In one instance, both parents of a child aged 13–15 participated in an interview “It’s so much easier with anything isn’t it, where you can just glance at it. It’s, you know, if to tell the time, rather than just glancing at your watch you had to sort of get something out, open it up, fiddle around with it, you wouldn’t worry so much about checking the time, would you?” (Parent 6) Lawton et al. BMC Endocrine Disorders (2018) 18:12 Page 4 of 10 Indeed, many participants drew a strong contrast between their experiences of using CGM and those of SMBG with Participant 3, like others, noting the limitations arising from the latter: planning, whether this be, as Participant 2 described, by changing the timing of a meal or, in Participant 7’s case, reducing the length of a walk, to avoid hypo- or hyperglycaemia: “it’s [SMBG] frustrating.. cause you don’t know what’s happening … it’s like walking around with a blindfold on. And you can walk into a room every now and then and take the blindfold off for 60 seconds. And then you have to put it back on.” “It’s easier to do the stuff I wanna do, because I can read my pump. I can see: am I going up? Am I going down? Should I have lunch before I do this? Or can I do this before lunch kind of thing?... [using CGM] I can say: oh we’ll have lunch in half an hour. Or I canI’ll just finish what I’m doing, or. So I think it’s giving me more personal freedom if you like.” (Participant 2) Predicting and managing the future As Participant 3 went on to elaborate, SMBG was of limited benefit not only because one could not instantly and effortlessly access one’s blood glucose levels, but also because it was not possible to establish “whether you’re going up or down, and how fast”. Indeed, a central benefit of CGM, as all participants observed, were the opportunities trend arrows presented to predict the future by virtue of being able to tell whether their blood glucose was rising or dropping and at what speed. This included Participant 1 who discussed how CGM data, when compared to SMBG results, enabled them to “make more informed decisions on what you’re going to do. And probably a lot sooner” because, as they explained, “I can see ok I’m actually going up. I’m going up really quickly. Or I’m coming down, I’m coming down fast, so I need to do something about it. As opposed to just a snapshot.” As various individuals noted, CGM thus helped enable them to pre-empt and prevent hypo- and hyperglycaemia, and thereby achieve more stable blood glucose levels, because, “obviously you’re ready before it happens” (Parent 2). Specifically, participants discussed how the predictive information provided by CGM prompted proactive use of corrective insulin doses or consumption of carbohydrate to prevent their (or their child’s) blood glucose levels moving out of target ranges: “Yes, the arrow- well that’s good for going low. Em, it’s a good- great indicator to see that it’s- my sugars are actually- they’re dropping a little bit faster than I expected. They’re maybe dropping according to the graphs, but dropping a lot faster. Em, it means I can get, if I’m out for a walk with the dog, I can think: okay. Right I need to cut the walk short, because I’m going to go low otherwise.” (Participant 7) While individuals described having received some instruction from health professionals on how to interpret and respond to the information provided by trend arrows, most emphasised that they found this information to be intuitive and easy to understand and as having prompted common-sense responses: “they told me what the arrows mean… But I‘ve- I’ve kind of taken it upon myself to interpret that into three arrows and active insulin, get something quick, and quick-acting. Em so I’ve kind of used what I think is my best judgement on that.” (Participant 9) Understanding the impact of lifestyle and insulin on blood glucose levels “if she [teenaged daughter] says: ‘oh I don’t feel quite right’, she can glance at it and think: ‘oh yeah I’m going high and I’ve got an arrow going straight up’. So she can then say: ‘oh yeah, actually I need to actually put a bolus in’. And equally if she’s got an arrow going straight down, she can say: ‘actually although I’m six, I’ve got an arrow going straight down. So I need something [to eat] within the next 20 minutes, half an hour, otherwise I’m gonna hypo’. So that’s good. You can almost stop things happening before they get to the critical point.” (Parent 6) Participants also described how having easy access to CGM data on a continuous basis had enabled them to develop a much better understanding of how insulin, food and physical activity impacted on their blood glucose levels. As several individuals noted, such information had been an informative and motivational tool which had prompted positive changes to how they had approached and managed their diabetes. This included Participant 10 who described how they had broken a pattern of over-treating hypoglycaemia after ‘real time’ CGM data had provided evidence and reassurance that a more restrained approached was more efficacious: Some individuals also discussed how the predictive information provided by CGM enabled short-term lifestyle “when I’d be treating a low, before I just thought I’ll just eat and eat. And, obviously the sensor showed me Lawton et al. BMC Endocrine Disorders (2018) 18:12 that when I did that I would just bounce way way back up, too high, because before, you know, I couldn’t physically see [this] on my pump with the arrows .. So now I know that I just- I can’t eat- I just don’t need to eat as much. I don’t need to panic as much.” Participant 14, likewise, described adopting a more “patient” approach to their diabetes self-management in light of information provided by CGM, one which meant they were now less likely to over-correct for hyperglycaemia: “So when I’ve used the pump to correct for it [high blood glucose] and I can see [from ‘real time’ CGM data], well actually I probably won’t need to, I can probably be a bit more patient and wait for it to catch up. And that’s quite helpful because that means I am less likely to have a hypo as a result of overcorrecting.” In another pertinent example, Parent 2 noted how her 12 year old daughter has been motivated to make dietary changes after CGM data had alerted her to how consumption of high sugar foods, such as breakfast cereals, were causing her blood glucose to spike: “she herself, off her own back, has been able to see, physically see on the line, where something has affected her blood sugar. Whereas before it will have affected it, and, you know, we treat it. But .. cause it’s a visual line she can see, that eating something’s gonna make her shoot up- it’s kind of- I think it’s struck a chord, in that she’s going: ‘well actually, that’s not really that good’. So she’s making conscious decisions in what she chooses to eat, without any kind of enforcement or- or guiding… changed the type of breakfast she has, so that she- she’s been having more smoothies rather than these high sugar, carby breakfasts.” Page 5 of 10 “And you can see what the history’s like and the trends and stuff. And I find that really, really helpful, because it’s like looking back over the period you’ve been asleep. And you can see what your blood sugar’s been doing... Sometimes you go to bed with a really normal blood sugar and you wake up and it’s normal. But over the night it’s just done this. And it’s like: ‘Wow’. Before I would have thought: ‘ah pretty good control really (laughs). But there’s something weird happening in the middle of the night.’” (Participant 14) As participants also discussed, having access to graphs which captured historical data provided useful information which could be used to inform changes to basal rates and/or mealtime ratios: “So you know, retrospectively you can look up the past couple of weeks and have a look at each day and you can see much better the patterns that come from your blood sugars and then you can adjust your insulin far more easily. … if you can see a pattern from the CGM charts I can change those instantly, the basal patterns and the ratios far more easily.. to get better stable control.” (Participant 3) Indeed, while participants did note that it was possible to generate data for retrospective analysis using SMBG, because CGM captured data at five minute intervals, it also allowed a much more nuanced and informative picture to be generated than could be captured through periodic snapshots: “Em, but since I’ve had the sensor, because I’ve got continuous points I’m getting a nice clean graph, rather than working off five or six points a day. So I’m able to make a lot better decision, rather than having to check my sugars every 30 minutes to try to get a nice trend pattern, I’m now getting a really good set of results that I can work off.” (Participant 7) Independent and dependent adjustments Using the past to improve the future; retrospective analysis of data Participants also discussed how the retrospective data provided by CGM enabled them to develop insight into their blood glucose control at times when they were much less likely to undertake SMBG, principally when they were asleep. In some cases, being able to examine graphs of night-time readings offered peace of mind that in target and stable blood glucose control was being achieved. In others, such as Participant 14, retrospective review of CGM data had alerted participants to unknown problems with their blood glucose control: However, while participants, including Participant 7, noted the value of the retrospective information provided by CGM, only a minority described having the confidence and ability to use this information to make independent adjustments to pump settings (basal rates) and/or meal time ratios. Indeed, in line with their earlier, pre-trial experiences of using insulin pumps (without CGM) where participants reported experiencing similar difficulties, the majority described both needing and expecting input and help from health professionals prior to changing basal rates and meal ratios. This was not only because participants questioned their own numeric Lawton et al. BMC Endocrine Disorders (2018) 18:12 skills and ability to analyse CGM data, but also because deferring to health professional expertise appeared, for many, to have been a habituated, taken-for-granted practice which pre-dated their use of CGM:. “It’s quite- a quite complicated set up. So yes I have different basal rates, for different times. And we do change that. I don’t change it on my own...it’s not something I’d do without talking to some other clever girls…. only because I think it is so fundamental of my regime, that I would be worried about changing it without understanding 100% if it should be up or down. So it’s more insecurity I think, of my own knowledge about the basal.” (Participant 2) “I see the consultant or the nurse often enough to do that with them…I wouldn’t feel that comfortable messing with- the insulin ratio- your insulin to carb ratios… because the ability to look at the data is less so than in the clinic, if that makes sense.” (Participant 4) Some individuals, however, highlighted a need for education and training to make effective and independent use of historical CGM data while others, including Participant 7, pointed to the potential benefits of including pattern recognition software with future CGM devices: “because I can see so many more variants in the line it makes me more determined to try and work out how to prevent, like monitor and check and find out why we have spikes and troughs … I’m at the stage- where at the moment I can do one change at a time. I know it just made me more determined to wanna be able to be in more control with her, working out what settings need changing, which is why I asked (names hospital) if they could give me that training.” (Parent 2) “But it’s difficult to sort of detect the trends, which is where it’s nice in some software where it- it actually highlights stuff that it’s noticed.” (Participant 7) Tolerating and experiencing glitches and inaccuracies In keeping with findings from previous studies [8, 13, 14, 16] participants reported various glitches and frustrations arising from using CGM. These included difficulties inserting and/or removing the device, finding a comfortable and discrete place on the body upon which to locate it, occasional loss of signal and challenges arising from needing to calibrate their devices at regular (12 hourly) intervals, especially when they did not lead routinized lives e.g. due to shift working. Participants, however, always tempered any criticisms with positive remarks and all emphasised that the Page 6 of 10 clinical and psychological benefits of CGM outweighed any challenges encountered: “Calibration’s a pain but, you know, I’ve just got to do it…. And sort of it’s worth the effort” (Participant 4). Participants also indicated that that their tolerance of “technical hitches” (Participant 5) arose partly from their understanding that they were in a clinical trial, and their expectation that, over time, CGM technology would improve. In some cases, this expectation appeared to have resulted from earlier experiences of using CGM and observing developments in its accuracy and usability: “and I’ve noticed.. as we’ve taken part in a lot of trials, these sensors are getting better.. the finger test and the sensor is becoming close and closer. I remember four, five years ago they were wide apart. And you thought, ‘well what’s the point, you know if it’s going to be so widely different.’ So we start seeing an improvement in the technology and how accurate the sensor’s becoming.” (Parent 5) Alarms In general, individuals pointed to clear clinical and psychological benefits to alarms alerting them to high/low blood glucose: “It beeps when you’re going high. Having that, just that- that knowledge that you’ve got something looking out for you, just in case you do miss it, is- is so relieving, like ridiculously good… it’s just- just another level of freedom. You just- you know you’re safe… yeah, just added security.” (Participant 9) Indeed, in one parent’s case, the existence of the alarm was believed to have saved her young child’s life: “So, for instance a week ago, em [child’s name has] never had a hypo at 11 o’clock at night, never. I heard an alarm going off and thought: what the hell was that? He’d dropped to 2.2. I wasn’t due to test [child’s name] until 12 o’clock and I think it was about 11 o’clock. So I would have left him another hour, before I tested him. By then, he could have died or gone into a coma.” (Parent 7) However, others noted how alarms could result in poor or interrupted sleep and/or unwelcomed distractions in the workplace or at school; with various children, including Parent 1’s daughter, reportedly switching alarms off in school due to concerns about drawing attention to themselves and distracting peers: Lawton et al. BMC Endocrine Disorders (2018) 18:12 “The thing is she can’t really have the alarms at school cause the teacher is not very happy about her beeping. So, and if she does she just stops it so the kids are not looking at her because she’s beeping. So it doesn’t really have any kind of positive effect, the alarms during the day. So she would just switch them off. She doesn’t even check why is it beeping… Just because she don’t want them going off in school cause it‘ll draw attention to her.” (Parent 1) Others described feeling that alarms ‘nagged’ them: “I suppose the worst of it would be the beeping… its beeping at you to tell you the sensor’s doing something, or it’s going too low, or something like that, so it nags” (Participant 3). This ‘nagging’ was described in particularly ambivalent ways by those, such as Participant 6, who suggested that she did not want to always lead a life dominated and dictated by her diabetes: “I kind of love it and I hate it, cause I hate the fact that it shouted at me all the time. And they’re like [names health professional] ‘that’s what you want, so you can make sure you’re ok’. I’m like: ‘not at 3 o’clock in the morning, I don’t care.’” (Participant 6) For similar reasons, Participant 10 also expressed ambivalence; in this individual’s case because the alarms acted as a tangible and difficult reminder not only that they had diabetes but also of their struggles to achieve optimal blood glucose control: “It goes off a lot, it will vibrate and vibrate, and then this big alarm will go off… And it wakes me up. And it goes off in lessons. And it really frustrates me. And it’s like any diabetic will know if something annoys you about your diabetes, it’s more than being annoyed, it’s deep anger…it’s telling me I am high or it’s telling me I’m low.” (Participant 10) Data lag Others noted how, by virtue of the lag between CGM readings and actual blood glucose levels, they were sometimes exposed to information which was unhelpful: “It alerts when I’m going low or I’m going high. So I do a sugar test: it says 13 the (CGM) reading says I’m 13.5 going up. So it’ll constantly beep… saying you’re 13.6, 13.7, you’re going up, you’re going up. And actually I’m going down. But it hasn’t caught up with it yet.” (Participant 13) Indeed due to this lag and other occasional inaccuracies, some participants emphasised the importance of Page 7 of 10 undertaking SMBG before addressing high/low blood glucose: “We don’t rely on it. You know if she’s [teenage daughter] having a hypo I’d still suggest that she tested” (Parent 6). Most participants, however, also described finding the lag relatively unproblematic because of how they actually made use of CGM data. For instance, it was noted that the small lag between actual blood glucose levels and CGM readings was unimportant when retrospective analysis of data was undertaken to spot patterns and trends which could inform changes to pump settings. In addition, when CGM data prompted participants to make more immediate changes to prevent high/low blood glucose, most noted how it was predictive information rather than actual blood glucose readings which they found most useful and informative: “in a way… the arrows are more useful to you than the actual number because it’s not about what you are right now, is it. It’s about what’s gonna happen while you’re asleep, or while you’re going for your run... or whatever it is, like in a way that’s more helpful to you in terms of what’s happening next.” (Participant 6) Discussion and conclusions This qualitative study has provided an in-depth understanding of participants’ experiences of, and views about, using CGM; and how, and why, CGM can be used to promote diabetes self-management. In doing so, we have offered a more detailed and nuanced perspective than is possible with quantitative/survey research. Specifically, our findings help explain why high levels of treatment satisfaction, reported in previous questionnaire studies [7–9], exist amongst CGM users. As we have shown, this is not only because CGM allows information about blood glucose to be accessed instantly and effortlessly, but also because trend arrows provide insightful information that enables diabetes to be managed in more proactive and effective ways than are possible with SMBG. Specifically, participants described using trend arrow information to pre-empt and prevent hyper- and hypoglycaemia by making proactive and appropriate use of carbohydrate consumption, corrective doses and short-term lifestyle planning. Such observations also help explain clinical research and trial findings that CGM can reduce hypo and hyperglycaemic excursions [2, 3, 5] and amplify and support findings of survey research undertaken with CGM users [22]. Participants also highlighted how CGM offered rich, informative data which enhanced knowledge of their blood glucose control at time points (e.g. night-time) when they were least likely to perform SMBG, and which could be used to adjust insulin basal rates and/or mealtime ratios to optimize or improve glycaemic Lawton et al. BMC Endocrine Disorders (2018) 18:12 control. However, while participants felt confident and able to make immediate, and what they saw as commonsense changes to lifestyle, food intake or insulin to address impending hypo- or hyperglycaemia, most described feeling much less confident and competent to undertake retrospective review of CGM data, spot patterns and trends and use these to inform independent adjustments to basal rates and mealtime ratios. While the former observation lends support to Bode and Battelino’s [23] suggestion that CGM usage remains largely intuitive, the latter raises important questions about whether the clinical benefits of CGM are always fully realised. Indeed, in keeping with observations and recommendations made by others [2, 11, 24] our findings point to a need for psycho-education and training amongst those using CGM to make optimal use of this technology. Specifically, as Ritholz et al. [14] have noted, we would recommend preparation and follow-up training about retrospective data use and analysis be given to individuals using CGM, a training need which has also been identified in other patient groups using flexible intensive insulin regimens [25, 26]. To address users’ education and training needs, staff training needs and workloads may also need to be taken into account [27]. The potential use of technologies, such as pattern recognition software, could also be considered [25]; indeed, such a recommendation was made by some of those who took part in this study. Another alternative may be to consider use of an individualised decision support system exploiting cloud-based technologies with or without health care professional input [28, 29]. Like others, we found that, while accounts of using CGM were overwhelmingly positive, participants encountered some difficulties and hassles using their devices [16]. These included calibration issues, equipment failure and problems inserting and/or removing the device [30]. While, in keeping with other studies, we found that disturbance caused by alarms could be a source of annoyance, especially to school-aged children [13, 30], our data reveal a richer and more complex picture. First, we have shown that, as well as causing frustration and disrupted sleep, alarms can also provide comfort and reassurance by alterting individuals to low (and high) blood glucose in a timely manner, thereby reinforcing a sense of hypoglycaemic safety [11]. Second, as our findings also suggest, some participants’ ambivalence about alarms appeared to arise from a more general dislike of having diabetes and an association made between alarming and what they saw as personal failure to achieve optimal blood glucose control. This is an issue which could be explored further in psychological work, to help determine whether some individuals, especially those with sub-optimal selfmanagement behaviours and/or a high HbA1c, would benefit from psychosocial support prior to initiation of Page 8 of 10 CGM to help maximise the benefits from alarms while preventing alarm fatigue [31]. However, on a more immediate and practical level, we would recommend that, as part of CGM training, individuals would benefit from instruction on how to switch alarms off and use different alarm profiles during different parts of the day. In addition, the snooze time of different alarms should be appropriately set to avoid repeated alarms. While concerns about sensor inaccuracies and the lag between recorded and actual blood glucose levels have been highlighted by others [13], these were not found to be unduly problematic in the current study. While this may be due to improvements in CGM technology over time, we have also shown that participants found CGM data useful even if, because of the lag, they questioned the accuracy of readings. This was largely due to participants valuing predictive (trend arrow) information over actual readings, and also because retrospective review of data was not seen as being compromised by a small data lag. Some participants also emphasised the value of undertaking SMBG before taking action to address high/ low blood glucose recorded by their sensors, a usage that may have been reinforced by the education and training they were given in the run up to the trial. A key study strength is our use of an open-ended exploratory design which, as already indicated, offered a level and depth of insight not possible in clinical and survey research. An additional strength is the multicentre study design and the inclusion of a diverse age range of individuals in our sample, together with parents of those aged 15 years and under. This potentially means our findings have greater generalizability than those of other qualitative studies undertaken to date, although it should be noted that there is a skew in the sample towards those aged 31–40 years. Like others, [11, 14] our sample, which was recruited from a clinical trial, was heavily skewed towards well-educated/ professional individuals, some of whom who had participated in earlier studies/trials of CGM. Consequently, such individuals may have been particularly motivated and interested in diabetes self-care and had an above average understanding of CGM. In addition, some participants’ earlier experiences of using CGM, and of seeing the technology improve over time, may have resulted in a form of ‘therapeutic optimism’ [32]. Specifically, participants may have hoped or believed that CGM technology will continue to improve, leading to overly positive and uncritical accounts. This may limit the generalizability of our findings; as may the fact that, in the currently study, only one particular CGM monitor was used and Polonsky et al.’s [11] observation that there are notable differences in usability, reliability and performance of CGM devices. In addition, we only focused on people’s experiences of Lawton et al. BMC Endocrine Disorders (2018) 18:12 using CGM for a limited number of weeks and it is possible that participants might have experienced fatigue had they used CGM for longer due to frustrations arising from alarms and CGM systems prompting action as soon as blood glucose moves out of predefined ranges [33, 34]. It should also be noted that, as we only interviewed people using insulin pumps, the findings may not be generalizable to those using injection regimens. For the aforementioned reasons, we would recommend further qualitative research be undertaken with more diverse socio-economic groups, recruited out with clinical trials, who use CGM for longer periods of time and/or who use multiple daily injection regimens. Abbreviations CGM: Continuous glucose monitoring; DAFNE: Dose Adjustment for Normal Eating; HbA1c: Glycated haemoglobin; SMBG: Self-monitoring of blood glucose Acknowledgments We would like to thank all of the individuals who took part in the interview study and the health professionals who assisted with recruitment and patient care. Additional thanks goes to Josephine Hayes, University of Cambridge, who provided administrative support and was the trial study coordinator. Funding Artificial Pancreas research at Cambridge is supported by JDRF, National Institute for Health Research Cambridge Biomedical Research Centre, National Institute of Diabetes and Digestive and Kidney Diseases, Horizon 2020, Helmsley Trust, and Wellcome Strategic Award (100574/Z/12/Z). Availability of data and materials The datasets generated and/or analysed during the current study are not publicly available because, even after removal of identifying information (e.g. names and locations) from the interview transcripts, it may still be possible for some individuals, such as health professionals who delivered the trial, to identify the people who took part in the study. This is because of the small number of people who participated and because they provided detailed accounts about using CGM in the context of their everyday (work and family) lives. Raw data are available from the corresponding author on reasonable request. Authors’ contributions JL conceived and designed the study, performed data analysis and interpretation, and drafted the manuscript. MB collected data, performed data analysis and interpretation, and contributed to drafting and revising the manuscript. DR performed data analysis and interpretation, and contributed to drafting and revising the manuscript. JA, FC, DE, LL, MT, HT and RH contributed to drafting and revising the manuscript. All authors read and approved the final manuscript. Ethics approval and consent to participate The study received approval from the independent Cambridge East Research Ethics Committee (REC ref. 15/EE/0324). Participants aged ≥16 years and parents or guardians of participants aged < 16 years signed informed consent; written assent was obtained from minors before study-related activities. Consent for publication Not applicable Competing interests RH reports having received speaker honoraria from Eli Lilly, Novo Nordisk and Astra Zeneca, serving on advisory panel for Eli Lilly and Novo Nordisk, receiving license fees from BBraun and Medtronic; having served as a consultant to BBraun; patents and patent applications. MT reports having received speaker honoraria from Novo Nordisk and Medtronic. LL reports having received speaker honoraria from Medtronic, Animas, Sanofi and Novo Nordisk, serving on advisory panel for Animas, Medtronic and Novo Nordisk. JL, DR, MB, JMA, DE and HT have no conflicts of interest to disclose. Page 9 of 10 Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Author details 1 Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK. 2Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK. 3Department of Paediatrics, University of Cambridge, Cambridge, UK. 4Leeds Children’s Hospital, Leeds, UK. 5Royal Hospital for Sick Children, Edinburgh, UK. 6Manchester Diabetes Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK. Received: 30 June 2017 Accepted: 8 February 2018 References 1. 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