Abstract
Introduction:
The Closing the Loop in Adults With Type 1 Diabetes (CLEAR) randomized crossover study compared a novel fully closed-loop insulin delivery system with no carbohydrate entry or mealtime bolusing (CamAPS HX), with standard insulin pump therapy and glucose sensor in adults with type 1 diabetes and suboptimal glycemic outcomes. This qualitative substudy aimed to understand the psychosocial impact of using the fully automated system.
Materials and Methods:
Adults participating in the CLEAR study were invited to take part in a virtual semistructured interview after they had completed 8 weeks using the fully closed-loop system. Recruitment continued until there was adequate representation and data saturation occurred. Interviews were anonymized and transcribed for in-depth thematic analysis using an inductive-deductive approach. Study participants were also asked to complete questionnaires assessing diabetes distress, hypoglycemia confidence, and closed-loop treatment satisfaction.
Results:
Eleven participants (eight male and three female; age range 26–66 years) were interviewed. After an initial adjustment period, interviewees reported enjoying a reduction in diabetes burden, freed-up mental capacity, and improved mood. All were happy with overnight glycemic outcomes, with the majority reporting benefits on sleep. Although experiences of postprandial glucose outcomes varied, all found mealtimes easier and less stressful, particularly when eating out. Negatives raised by participants predominantly related to the insulin pump hardware, but some also reported increased snacking and challenges around resuming carbohydrate counting at trial closeout.
Conclusions:
In adults with type 1 diabetes, use of a fully closed-loop insulin delivery system had significant quality-of-life benefits and provided a welcome break from the day-to-day demands of living with diabetes.
Clinical Trial Registration:
NCT04977908.
Introduction
Intensive insulin therapy represents a significant management burden for people with type 1 diabetes, contributing to burnout, diabetes distress, and reduced quality of life. 1 Hybrid closed-loop insulin delivery systems, which automatically calculate and adjust insulin rates, are transforming the management of type 1 diabetes. They have been shown to improve both glycemic outcomes 2 and quality of life. 3 However, all current commercially available systems still require users to count carbohydrates and manually input insulin boluses before meals and snacks.
Accurate carbohydrate counting can be challenging and adds significantly to the burden of day-to-day diabetes management. 4,5 It can negatively affect quality of life, making people with type 1 diabetes feel restricted in food choices and more socially anxious among peers. 6
Newer ultrarapid insulins are now available, which make a fully closed-loop approach, without the need for carbohydrate counting or premeal bolusing, feasible. We recently reported significantly improved glucose outcomes without increasing hypoglycemia when using a novel fully closed-loop system (CamAPS HX) with ultrarapid insulin lispro (Lyumjev) compared with insulin pump therapy with a glucose sensor in adults with type 1 diabetes and suboptimal glycemic outcomes (glycated hemoglobin [HbA1c] ≥8.0%). 7
To complement the glycemic data, this psychosocial substudy used semistructured interviews and validated questionnaires to understand the lived experience of using the fully closed-loop system. There have been no previous qualitative evaluations of fully automated insulin delivery systems, and this is an important aspect of research in this field, with quality-of-life impacts of diabetes technology often being as important to users as glycemic benefits. 3
Materials and Methods
We interviewed and collected questionnaire data from participants who took part in the CLEAR study. This was a single-center randomized crossover trial involving 26 adults with type 1 diabetes using insulin pump therapy and with a glycated hemoglobin ≥8.0% (64 mmol/mol) at baseline. 7 In the CLEAR trial, participants were randomized to 8-week use of a fully closed loop system (CamAPS HX; CamDiab, Cambridge, UK) with Lyumjev insulin (Lilly UK, Basingstoke, UK) or 8 weeks of their usual insulin pump therapy with glucose sensor, before crossing over to the other arm.
The CamAPS HX system comprised a control algorithm residing on an app on an unlocked Android smartphone, receiving sensor glucose data from a Dexcom G6 glucose sensor (Dexcom, San Diego) and directing insulin delivery on a Dana RS insulin pump (Sooil, Seoul, South Korea). During the fully closed-loop period, participants were advised not to announce, enter carbohydrates or bolus for any meals or snacks. Users could adjust the glucose target on the app (customizable between 4.4 and 11.0 mmol/L), and also use the “Boost” and “Ease Off” function on the app to temporarily increase or decrease insulin delivery. There was a bolus calculator available on the app that participants were trained to use for safety.
Recruitment and data collection
On completion of the study, participants were invited to take part in a virtual in-depth interview through Zoom (Zoom, San Jose, California) at a time of their choosing. Interviews averaged 40 min and were conducted by a researcher trained in qualitative research methods. The researcher was not involved in the clinical care of trial participants and participants were reassured of confidentiality and encouraged to share negative experiences as relevant.
Interviews were informed by a topic guide (Table 1), to ensure the key study objectives were covered, while also allowing participants to raise themes they considered important. The topic guide was developed based on literature review, input from patient representatives and members of the clinical team and was revised in light of emergent findings. Recruitment continued until there was adequate representation in terms of age, gender, and educational status and data saturation had occurred.
Topic Guide
Topic added in light of interviewees suggesting that certain characteristics of their lifestyle made the system particularly helpful.
Two validated questionnaires were given to all participants on completion of both study periods to evaluate hypoglycemia confidence 8 and diabetes distress. 9 An additional two questionnaires, a validated questionnaire to evaluate closed-loop treatment satisfaction, 10 and a “closed-loop experience” questionnaire were administered to participants on completion of the fully closed-loop period. Participants were asked to complete the questionnaires at home and return them to the research team.
Data analysis
Interviews were transcribed in full, anonymized, and then analyzed thematically using an inductive-deductive approach. Interview transcripts were reviewed and cross-compared with look for recurrent themes. Four members of the research team were involved in data analysis, and together developed a coding framework to capture all key themes. The qualitative analysis software package NVivo 12 (QSR International, Doncaster, Australia) was used to facilitate data coding and retrieval. We followed the Standards for Reporting Qualitative Research. 11
Analyses of questionnaire data were carried out using SPSS Statistics software, version 28 (IBM Software, Hampshire, UK).
Ethics
Before commencement, approval for the CLEAR study and interview substudy was received from an independent research ethics committee in the United Kingdom.
Results
Eleven participants were interviewed, demographics are shown in Table 2. The key themes cut across the data set, so we have not separated reporting according to individual characteristics such as gender or age; however, these details are reported after each participant quotation.
Demographic Characteristics of Participants Taking Part in Interviews
Data are mean ± SD, n = 11.
CGM, continuous glucose monitoring; HbA1, glycated hemoglobin; SD, standard deviation.
Initial thoughts: excitement, expectations, and adjustment
When discussing their motivations for taking part in the trial, all interviewees stated altruistic reasons, wanting to contribute to “anything that would benefit others in the future” (2_M_55Y). There was also overwhelmingly a sense of excitement about fully closed loop, that “it was incredible to be part of the future of diabetes” (9_M_33Y). For example, one participant described the first time not-bolusing for a meal: “That's when all the feelings kick in of this is genuinely here now. We've always said oh ten years, ten years, ten years. It's like it's happening now. It was not overwhelming, I guess. But it was like a moment. That first time” (10_M_28Y).
Although some interviewees described extremely high hopes of the study system going in “before I tried out, I was thinking sort of great, I'm normal for a while” (3_M_53Y), the majority were “a bit apprehensive at first” (4_M_32Y). Several described considerable worry about handing over full control to the closed-loop system: “Especially with the diabetes, especially if you've had it for a long period of time, you think you're the only person who can control it. And even though you might not be controlling it well, you don't want to give that control up” (9_M_33Y).
Reassuringly, all interviewees did find they were able hand over control and trust the fully closed-loop system by the end of the 8-week period. A few participants found the change very easy “well of course not having to do something is easier to adjust to than having to do something” (11_M_46Y) however, the majority described a transition period during which they had to adjust to a “whole new way of thinking and doing” (3_M_53Y).
This generally lasted from a few days to a couple of weeks: “It was a bit odd initially. I kept looking at the pump and I was also checking manually. After one or two days I was like, oh, I'm very impressed with the technology…. And then I didn't have to do anything. I didn't have to worry because I knew the pump was doing the right thing” (1_F_42Y).
Further quotations on participants' initial thoughts and adjustment to the fully closed-loop system are captured in Table 3.
Initial Thoughts on the Fully Closed-Loop System
A break from diabetes without compromising control
A break from diabetes
A universal theme was that the fully closed-loop system represented a welcome break from the day-to-day demands of living with diabetes: “I did not have to do anything. Which was fantastic. And it just made my life so so much easier… I just felt I was on a holiday when I was on that.” (1_F_42Y). “Obviously the fully closed loop it is literally you can live your normal life if you know what I mean. You can just cook what you want for dinner, eat it and sit down and not have to work everything out. Because it picks up and sorts itself out… It was just nice to have a little break” (8_M_26Y)
Although some participants did reference ongoing user responsibilities relating to insulin pump therapy, these were invariably presented as minimal compared with what they were doing before: “Oh it was liberating actually. I didn't have to think, I didn't have to look at a plate and count. I didn't have to check my blood glucose levels…I just genuinely felt like I was a non-diabetic. I could do whatever I wanted when I wanted and know that I was within control. I guess the only consideration was how much insulin is left in the vial, do I need to take a backup or whatever. But other than that.” (6_M_44Y).
Satisfactory glucose outcomes
Importantly, this “holiday” from the demands of diabetes came without a perception of compromising glucose outcomes. Although not perfect, almost all participants reported subjective improvements in glucose levels. For some participants the improvement was dramatic: “The one thing I noticed was my blood sugars were completely under control” (1_F_42Y).
Several pointed out the beneficial effect of the system learning over time: “I thought the algorithm, for me particularly sort of six weeks in was absolutely fantastic. Looking at my results from what I can remember, I didn't have a massive deviation between low and high. It was pretty flat all day, with the exception of when you have your main meals you peak a little bit, but those peaks were nowhere near as high as what they would've been previously (4_M_32Y).”
For others, postprandial hyperglycemia was more of an issue, but in general participants described how “sustained highs, [were] lot less on the trial” (10_M_28Y). They also described how the high levels after eating became less of a problem when overnight control was invariably good. “So yes, there was a little bit of an increase [post meals], but then the thing that is most important to remember is that come seven o'clock in the morning when I get up and get going, I'm in target” (2_M_55Y). However, one participant did report a perceived negative effect on overall glucose outcomes, saying that the Lyumjev insulin “just didn't work quick enough. So more time than not, I was high.” (3_M_53Y).
Hypoglycemia
Fear of hypoglycemia was a theme in more than half of interviews. For example, one participant explained he “often ran higher so I've avoided hypos because I really don't enjoy having them,” and in this context “had a lot more hypos on the [fully closed-loop system] than I did normally” (10_M_28Y).
However, for the majority of participants, including those who previously ran high to avoid hypos, the hypoglycemia burden was similar or lower while on the fully closed-loop system: “I do get very nervous around hypos. So if I see my sugar pushing low and I know I'm physically busy, I will actually have a coke or I will have something to try pre-empt that low… I would say I was less worried about lows on the system. Quite simply because it just has that cut-off [for insulin delivery] where the closed loop is already doing its job by the time you start thinking about it or doing it. So it's quite great” (9_M_33Y).
“I used to worry, especially before driving, before going to exercise, and if I don't eat a meal for a couple of hours… what should I do, should I check my blood sugar, should I eat something? I'm very cautious about these things. I don't want hypoglycemia and things like that. But with the pump I didn't have to worry” (1_F_42Y).
Two participants reported a transient period of increased hypoglycemia when starting the fully closed-loop system: “I think at the beginning, probably more frequently than before I was on the study because it was getting used to me. But I would say within a couple of weeks my level of hypos was significantly lower than normal” (6_M_44Y).
Further participant quotes relating to these themes can be seen in Table 4.
A Break from Diabetes Without Compromising Glucose Control
Improved quality of life: greater flexibility around food, improved sleep and productivity
Improved quality of life
Another key theme reported by interviewees was that reduced practical burden of diabetes was associated with improved mood. As one participant put it: “So burnout is a real thing. You don't realise it until actually a chance to step back and realise actually wow” (11_M_46Y). Participants described feeling “happier and much more relaxed” (1_F_42Y) and described how this improved mood also had “a positive impact on the people around [them]” because “The diabetes can be super stressful, so if the system is taking off any of the load, then it is relieving something off my load. It ultimately makes me a less grumpy person to be honest” (9_M_33Y).
Greater freedom around food
The biggest quality-of-life impact appeared to be around eating out with one participant explaining “Very easy and very free. Takes a lot of the stress and worry, especially when you are going out and eating, the actual concept of it is brilliant” (3_M_53Y). Again, this benefit extended beyond the user themselves “being able to just [go out and eat] and not worry about it… I didn't feel like I had to say no because oh we've eaten out three times this week and I've had really bad blood sugar control for the whole week as a result. So, eating out is obviously an important thing for my partner, so to be able to do that more frequently was good for us” (10_M_28Y).
Most participants reported that they “didn't at any point feel like [the closed-loop system] was limiting [them] or changing [their] meal choices” (4_M_32Y), and indeed provided “a bit more freedom to eat when [they] wanted without having to worry about the impact” (6_M_44Y). One participant actually reported a negative impact of this flexibility “Psychologically, the fact that I knew all of a sudden, I could eat the things that I wanted to eat without thinking about it… made me tend towards more junkie food. I think that there is an interesting risk in a way of falling into that trap of now not looking after yourself as well as you could. Because suddenly you don't have to make all these decisions which do put you into a position of making better choices” (10_M_28Y).
However, another participant reported snacking more, but on healthier foods and yet another, who was new to glucose sensors, reported looking at blood glucose levels made her “very careful what [she] was eating, which is a good thing” (1_F_42Y).
Sleep
The majority of participants reported improvements in sleep while on the system, secondary to reduced hyperglycemia; one participant who previously woke up six nights a week described how “without the overnight high you sleep right through. So, I could actually sleep for the time I was on the [fully closed-loop] system” (8_M_26Y). Another reported “I felt better in the morning because I hadn't had to get up at four o'clock to go to the toilet. I wasn't feeling lethargic” (2_M_55Y). In contrast, three participants did report “waking up in the night [due to] getting the low glucose alarm” (4_M_32Y), but in two cases this was resolved by increasing the personal glucose target overnight.
Daytime productivity
Another finding from more than half the interviewees was that using the system had positive impacts on work and productivity. One participant, who has a physically active job, described that with the automation it was “quite comforting to know that, okay, I could take my hands off the wheel a bit and I could focus on the job and not have to constantly think, what is my sugar doing right now” (9_M_33Y). This was also true beyond work, another participant described: “My output in general has increased a lot. Not having all the decisions that I normally have to make. And I did find that I was doing more in the evenings and exploring more of my hobbies in the evenings and doing new things. Cause yeah, I just wasn't using all that brain power all the time on this one thing.” (10_M_28Y).
However, this only came after the initial period of algorithm adaptation and users developing trust in the system. One participant described how “for that first two weeks when it was kind of learning me and my behaviours and my blood glucose levels I would've deliberately not done as much client facing or putting myself in an environment where a hypo would've been an inconvenience” (6_M_44Y).
Other quotations relating to quality-of-life impacts are outlined in Table 5.
Improved Quality of Life
System-specific features: appreciated opportunities for modulating insulin delivery, disliked hardware
Modulating insulin delivery
All users found options to modulate insulin delivery through the “Boost” and “Ease Off” function helpful. Boost was used variably from every day to just once during the 8-week period, but most participants described using it occasionally if “feeling unwell or if [they'd] had something that was very high GI or very high in fat” (4_M_32Y). They also described benefits when eating out: “If you know you're going to be eating a lot of carbs hit the boost when you've ordered your food. That did bring it all down and keep it down” (8_M_26Y).
The “Ease-Off” function was primarily used for exercise, but also found useful by those who had active jobs: “If I'm on my way to a job where I know I'm going to be busy for a few hours, I'll ease off, because I know generally that's when I'm going to push low” (9_M_33). Although most participants liked the simplicity of “just pressing a button to make the algorithm more or less aggressive” (9_M_33), one user indicated they would have liked more prescriptive guidance on “how long to Boost or Ease Off for certain things” (10_M_28Y).
Hardware
Almost all the negative comments about the fully closed-loop system were concerning the study hardware. There was a strong consensus that “the worst thing about all the technology was the pump” (2_M_55Y). Participants found that compared with the pumps they had used previously “it was quite clunky” and “quite a faff changing the insulin every time” (7_F_32Y).
Another common issue reported was the “device-specific battery” that “failed quite a number of times without warning” (4_M_32Y). Participants liked the CamAPS HX app, which was “really user friendly, it was very visual” (4_M_32Y); however, most had to carry a separate study phone as the app is currently not iOS compatible. More than half of the participants reported that “having to carry around two phones is a bit of an annoyance” (11_M_46Y).
Trial closeout: initial difficulties going back to bolusing, interest in continued use of fully closed loop, and ideas for improvement
Back to bolusing
At trial closeout, most participants struggled with going back to carbohydrate counting and bolusing. As one user described “I probably got a little bit lazy in my actual carbohydrate counting because the machine was doing it for me” (2_M_55Y). For almost all participants these skills came back within a few days; however, one participant reported that several months after completing the study “even now I sometimes forget to bolus, whereas [with fully closed loop] it wasn't a fault… So I adjusted really well to that idea, but it was hard adjusting back to normal normality” (9_M_33Y).
Future use of fully closed loop
Participants all expressed interest in using the fully closed-loop system if it were commercially available, saying “I was quite enjoying it at the end – it stopped too soon” (5_F_66Y) and “I'd love to stay on it forever” (7_F_32Y). Interestingly, five participants went on to use a hybrid closed-loop system after finishing the study and four of these preferred the fully closed-loop system: “So being on the fully automated system, it worked far better than being on a hybrid closed loop for me… I'd say to you, if it's available tomorrow I'll take it. Even over the hybrid, yeah definitely” (4_M_32Y).
Another described, “Don't get me wrong, I'm very happy with the [hybrid closed-loop system]. It does its job. It doesn't do the job that that system does. I do think that that system is a bit golden…. I do think it gave better control, less stressful. That system is literally like the dream” (9_M_33Y).
The most common drawback to using the system was the insulin pump, with one participant saying “I'd probably think twice around the hardware pieces. But I think the advantages outweigh that as a disadvantage” (6_M_44Y). Two participants suggested they would prefer a little more interaction with the system around mealtimes to help with postprandial glucose excursions: “Keep the idea about it essentially carb counting for you. But I would really like to tell it that I'm about to eat something sugary or a big meal or something with a significant amount of carbs just so it could be ahead of the game” (11_M_46Y).
The other participant similarly described they would like “the opportunity to be able to say, look, I'm about to have a big meal, give it a little bit more information to help it make better decisions” (10_M_28Y). However, he also described wanting to keep the full automation some of the time: “If I'm out for dinner, I don't know what I'm eating. And then that's where the magic of the algorithm comes in” or “where I can't be bothered to weigh my food… if you want a night off you can have a night off.”
Who could benefit
When asking participants who they thought would most benefit from the fully closed-loop system the themes were those who struggle with carbohydrate counting, but also those who had unpredictable lifestyles or were busy with priorities other than managing diabetes: “I think for me, because I've got quite an unpredictable lifestyle, that's where it works really well. Somebody who's active like me, sort of sporty does things like that, that's good. And people who just generally struggle with carb counting and control I would say would benefit too” (6_M_44Y).
“To be honest, I think people who are busy, it'll help a lot with, because as we've said, it kind of removes a part of the strain on your mind. It frees your mind up to deal with some other things” (9_M_33Y). And as one participant observed “yes, you should really make time for your diabetes because it's the one thing that's keeping you alive, but it would make life a lot easier for people who are totally beholden to running around for other people” (2_M_55Y).
Further quotes around trial closeout and future use of fully closed loop are reported in Table 6.
Trial Closeout and Future Directions for Fully Closed Loop
Questionnaire results
Table 7 reports the results of the closed-loop experience questionnaire, which was returned by 19 study participants. Everyone was happy to have their glucose levels controlled automatically, 94% of responders would recommend closed loop to others, 89% spent less time managing their diabetes, and 78% slept better. Many of the themes identified in the free text of the questionnaire are similar to those identified in the interviews, including improved mood and reduction in burnout as well as the negatives raised around postprandial glucose excursions and the study pump.
Responses to Closed-Loop Experience Questionnaire (n = 18)
BG, blood glucose; BM, blood glucose; HCP, Health Care Practitioner.
There was no significant difference in hypoglycemia confidence or diabetes distress during the fully closed-loop period compared with the usual care period. Results of the INsulin Dosing Systems: Perceptions, Ideas, Reflections, and Expectations (INSPIRE) questionnaire indicate high fully closed-loop participant satisfaction (Table 8).
Questionnaire Scores
Data are presented as median (IQR). Values were winsorized at the 10th and 90th percentiles before statistical analysis with paired sample t-test.
IQR, interquartile range.
Discussion
To our knowledge, this is the first psychosocial evaluation of a fully automated closed-loop insulin delivery system. Interviewees universally reported a reduction in diabetes burden describing a sense of “normalcy,” “liberation,” and being “on holiday from diabetes.” They described improved mood and quality-of-life benefits, including reduced worry around mealtimes, improved sleep, and freed-up mental capacity for other priorities.
Although several of these quality-of-life impacts including “time off” from diabetes demands and improved sleep have been reported for commercially available hybrid closed-loop systems, 3 users highlighted how much they enjoyed the added benefit of not having to carbohydrate count and bolus, and the greater freedom this offered around mealtimes. One unintended consequence noted was that fully closed-loop technology could perhaps lead to unhealthier eating habits (increased snacking and less consideration of carbohydrate intake). This has also been reported with hybrid closed-loop systems, 12 and suggests individuals might benefit from additional nutritional education when using the system to help promote healthy eating.
In keeping with their expectations, users reported taking a few days to a few weeks to develop trust in the fully closed-loop system. This corresponds with what has been described for hybrid closed-loop systems, 13 and is important to take into account when planning the timing of transitioning to closed-loop therapy. Warning users that there will be an adjustment period, during which the algorithm will adjust to their insulin requirements and they in turn will build confidence in the system, would be useful to avoid initial worry.
Almost all participants felt the system improved their glucose outcomes; this is consistent with the trial findings where fully closed-loop increased the proportion of time glucose was in target range 3.9–10.0 mmol/L by 13.2% points (mean ± standard deviation 50.0% ± 9.6% with fully closed-loop vs. 36.2% ± 12.2% with usual care; P < 0.001). 7 Although 50% is still below the recommended time in target glucose range, 14 it is perhaps related to the significant hypoglycemia fear reported by this population, who had high HbA1c levels at baseline. Generally, interviewees seemed satisfied with improved but imperfect postprandial glucose outcomes if it meant reduced diabetes burden and more time to focus on other aspects of their busy lives.
That being said, participants did appreciate opportunities to collaborate with the system through the “Boost” and “Ease Off” function. Some users wanted additional interaction through simplified meal announcements; such systems are being tested clinically by several groups. 15,16 In contrast, other users preferred the greater freedom from diabetes demands provided by a fully automated system.
Looking forward, an option may be to have the fully closed-loop algorithm as a setting within a hybrid closed-loop system that users could turn on when they were particularly busy with other priorities, burnt out or just needed a break. Perhaps the biggest barrier to this would be the challenges reported around resuming carbohydrate counting and bolusing at the end of the 8 week fully closed-loop period. Although in most cases participants re-skilled quickly, it would be important to adequately support users through the transition period, including providing some refresher education.
Most of the negatives raised by participants related to the insulin pump. We are currently examining the CamAPS HX fully closed-loop algorithm in adolescents with an alternative insulin pump, so the qualitative data from this follow-up study will be informative in terms of hardware burden.
Feedback from the closed-loop experience questionnaires broadly mirrors that from the interviews. The questionnaires are from a slightly larger sample size supporting the generalizability of our findings across the study population. The lack of improvement in diabetes distress and hypoglycemia confidence scores during fully closed loop is surprising given the high closed-loop treatment satisfaction (INSPIRE questionnaire) and quality-of-life benefits reported in interviews. It is possible that improvements may have been seen with a longer duration using the fully closed-loop system; 8 weeks is relatively short, especially factoring in the initial adjustment period.
Limitations of this study include the incompleteness of questionnaire data, as not all participants posted back completed questionnaires. It is possible that those who did complete questionnaires were not representative of the overall study population, and the same may be true of those who consented to be interviewed. Those interviewed were predominantly of white ethnic background and had higher levels of education.
Although this is reflective of the demographics of the overall study population, results may not be generalizable to the wider population with type 1 diabetes. Although the researcher conducting the interviews was not involved in the participants' clinical care, there is still a possibility that participant's responses were influenced by knowing they were part of the same research team.
Conclusions
This research demonstrates that alongside its glycemic benefits, use of a fully closed-loop insulin delivery system had significant quality-of-life benefits in adults with type 1 diabetes and suboptimal glucose outcomes. These included providing a welcome break from the day-to-day demands of living with diabetes, reduced worry around mealtimes, and better sleep. Drawing on participant feedback and interview responses, we have also identified ways in which the technology could be refined, and education tailored to optimize use.
Footnotes
Authors' Contributions
R.L., C.K.B., and R.H. codesigned the study. C.K.B., S.H., R.L., M.N., J.W., and J.M.A. were responsible for screening and enrolment of participants, arranged informed consent from the participants, and/or provided patient care. R.L. and C.K.B. wrote the report. R.L., C.K.B., J.M.A., J.W., and R.H. contributed to data analysis and to the interpretation of the results. R.H. designed and implemented the glucose controller. All authors critically reviewed the report.
Statement of Guarantor
R.L., C.K.B., and R.H. had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Disclaimer
The views expressed are those of the author(s) and not necessarily those of Novo Nordisk the NIHR, the Department of Health and Social Care, or other funders.
Author Disclosure Statement
C.K.B. has received consultancy fees from CamDiab and speaker honoraria from Ypsomed. S.H. reports speaker and advisory board fees from Dexcom, Medtronic, Sanofi, and Ypsomed; being director at ASK Diabetes Ltd and receiving consulting/training fees from CamDiab. M.N. has received travel grant support from Sanofi, Janssen, and Eli Lilly and was previously chair of the Young Diabetologists' and Endocrinologists' Forum in the United Kingdom, which uses unrestricted sponsorship from industry partners to deliver educational programs for health care professionals. M.E.W. reports receiving license fees from B. Braun, patents related to closed loop, and being a consultant at CamDiab. J.W. reports receiving speaker honoraria from Ypsomed and Novo Nordisk. J.M.A. reports training fees from CamDiab. M.L.E. has been a member of advisory panels and/or received speaker's fees from NovoNordisk, Eli Lilly, Abbott Diabetes Care, Medtronic, Ypsomed, Pila Pharma, and Zucara. R.H. reports having received speaker honoraria from Eli Lilly, Dexcom, and Novo Nordisk, receiving license fees from B. Braun; receiving consultancy fees from Abbott Diabetes Care, patents related to closed loop, and being director at CamDiab. R.L. declares no duality of interest associated with this article.
Funding Information
This study was funded by a grant from the Novo Nordisk UK Research Foundation. Dexcom supplied discounted continuous glucose monitoring devices and sensors for the study. Supported by National Institute for Health Research Cambridge Biomedical Research Centre. The University of Cambridge has received salary support for M.L.E. through the National Health Service in the East of England through the Clinical Academic Reserve.