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Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an “artificial pancreas” that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system.

Parents of young children with type 1 diabetes (T1D) experience unique, developmental challenges in managing their child's T1D, resulting in psychosocial distress. Only a small portion of young children reach glucose goals and adherence to diabetes devices that help improve T1D management have historically been low in this population. The purpose of this study is to test four interventions that couple developmentally tailored behavioral supports with education to optimize use of diabetes devices, improve glucose control, and reduce psychosocial distress for parents of young children with T1D. The study team designed four behavioral interventions, two aimed at improving glucose control and two aimed at optimizing use of diabetes devices. The goal of this paper is to describe the behavioral interventions developed for this study, including the results of a pilot test, and describe the methods and analysis plan to test this intervention strategy with ninety participants in a large-scale, randomized trial using a sequential multiple assignment randomization trial (SMART) design. A SMART design will permit a clinically relevant evaluation of the intervention strategy, as it allows multiple randomizations based on individualized assessments throughout the study instead of a fixed intervention dose seen in most traditional randomized controlled trials.

Aims The current study sought to identify patient-level factors related to health care use among White and minority men and women with diabetes. Methods A sample of 447 of non-pregnant individuals with diabetes, ages 18–64, was drawn from the 2015–2016 National Health and Nutrition Examination Surveys dataset. Poisson regression models tested associations between health care use and self-rated health, depression, medical comorbidities, body mass index, marital status, number of children, income, insurance coverage, and age, stratified by gender and racial/ethnic minority status. Results Poorer self-rated health was the only significant correlate of increased health care use among White men with diabetes whereas income and insurance were significant correlates of increased use among minority men. Among White and minority women, higher levels of depression and being single were correlated with greater health care use. Comorbid medical conditions and insurance coverage were also related to use among minority women. Conclusions Among individuals with diabetes, health care use among White men appeared to be driven by subjective health whereas financial factors were critical among minority men. Family structure and mental health were instrumentally associated with health care use among all women. These factors can be targeted to promote equitable access to care.

Background:Continuous glucose monitors (CGM) are underutilized by individuals with type 1 diabetes (T1D), particularly during the adolescent years. Little is known about perceptions of CGM benefit and burdens, and few tools exist to quantify this information.Methods:Two questionnaires were developed and validated—Benefit of CGM (BenCGM) and Burdens of CGM (BurCGM)—in a sample of adolescents ages 12-19 years involved in the T1D Exchange Registry. We chose to start the validation process with adolescents given their low CGM uptake and high risk for suboptimal glycemic outcomes. Exploratory and confirmatory factor analyses were conducted to confirm factor structure and select items. The resultant scales were tested for internal reliability and convergent/divergent validity with critical diabetes and quality of life outcomes: age, depression, diabetes distress, self-efficacy, technology attitudes, and diabetes technology attitudes.Results:A total of 431 adolescents with T1D completed the questionnaires (51% female, mean age 16.3 ± 2.26, 83% white non-Hispanic, 70% having used CGM). Two single factor scales emerged, and scales were reduced to 8 items each. Those who perceived higher benefit of CGM exhibited lower diabetes distress, higher self-efficacy, and more positive attitudes toward technology. Those who perceived higher burden of CGM exhibited higher diabetes distress, lower self-efficacy, and less positive technology attitudes.Conclusion:The BenCGM and BurCGM questionnaires each comprise 8-items that demonstrate robust psychometric properties for use in adolescents with T1D, and can be used to develop targeted interventions to increase CGM wear to improve diabetes management.

The landmark Diabetes Control and Complications Trial (DCCT) identified the relationship between intensive diabetes management for those with type 1 diabetes (T1D) and a delay in the onset or progression of microvascular complications, shifting the paradigm of clinical care for this chronic medical condition (1). Importantly, the data from that trial continue to have a lasting legacy as they can now be analyzed to inform present-day questions. An example of this comes from the article by Beck et al. in this issue of Diabetes Care (2) that concisely states the primary implication of the article in its title, “Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials.” In recent years, and with increasing use of continuous glucose monitoring (CGM), the ability to classify sensor glucose levels into various ranges has been feasible. Yet, some have questioned the validity of using these measures as a surrogate outcome measure in ongoing and future clinical trials. Indeed, some have called for a “modern-day” DCCT assessing whether CGM and a greater time in range (TIR) would result in fewer microvascular end points compared with self-monitoring of blood glucose (with intermittent masked CGM). Unfortunately, the duration of time, funds required, and ethical concerns given clinical equipoise regarding the benefits of the technology would make completion of a rigorous randomized controlled trial a near-impossible feat. Recognizing the wealth of data that the DCCT affords, Beck et al. (2) found a creative solution to assess the hypothesis of whether TIR could serve as an outcome measure for future trials. Specifically, they capitalized on the glucose values captured seven times daily every 3 months during the course of the 6+ years of the DCCT. This allowed them to calculate the percent TIR of glucose values between 70 and 180 mg/dL and show a robust …

Aims: This study examined the psychosocial impact of Loop, an open-source automated insulin dosing system that has emerged from the diabetes technology “Do-It-Yourself” (DIY) movement. Methods: Subsamples of 239 adults, 115 children, and 243 parents completed data collection at the time of Loop initiation and 3 and 6 months later. Surveys collected demographic and clinical information, percent time-in-range, HbA1c, and validated psychosocial measures. Analyses included paired t tests and McNemar’s tests to compare psychosocial functioning at 3 and 6 months and regression models to assess baseline predictors of psychosocial outcomes at 6 months. Results: Adults reported significant improvements in diabetes distress ( t = −7.20 P < .001; t = −8.01, P < .001), sleep quality ( t = 6.81, P < .001; t = 2.98, P = .003), fear of hypoglycemia ( t = −4.42, P < .001; t = −4.97, P < .001), and hypoglycemia confidence ( t = 8.68, P < .001; t = 7.96 P < .001) from baseline to 3 months and 6 months, respectively. Significant improvements in parents’ and children’s sleep quality and parents’ fear of hypoglycemia were also observed. Several baseline characteristics were associated with psychosocial outcomes at 6 months. Conclusions: The current findings support the broad and sustained benefits of Loop across multiple aspects of psychosocial well-being. Advancement and dissemination of such technologies has the potential to improve mental and physiological health among people living with type 1 diabetes.

Aim This study aimed to capture the experience of parents of youth with recent onset Type 1 diabetes who initiated use of continuous glucose monitoring (CGM) technology soon after diagnosis, which is a new practice. Methods Focus groups and individual interviews were conducted with parents of youth with Type 1 diabetes who had early initiation of CGM as part of a new clinical protocol. Interviewers used a semi-structured interview guide to elicit feedback and experiences with starting CGM within 30 days of diagnosis, and the benefits and barriers they experienced when adjusting to this technology. Groups and interviews were audio recorded, transcribed and analysed using content analysis. Results Participants were 16 parents (age 44.13 ± 8.43 years; 75% female; 56.25% non-Hispanic White) of youth (age 12.38 ± 4.15 years; 50% female; 50% non-Hispanic White; diabetes duration 10.35 ± 3.89 months) who initiated CGM 11.31 ± 7.33 days after diabetes diagnosis. Overall, parents reported high levels of satisfaction with starting CGM within a month of diagnosis and described a high level of reliance on the technology to help manage their child's diabetes. All participants recommended early CGM initiation for future families and were committed to continue using the technology for the foreseeable future, provided that insurance covered it. Conclusion Parents experienced CGM initiation shortly after their child's Type 1 diabetes diagnosis as a highly beneficial and essential part of adjusting to living with diabetes.

Background Cost is a major consideration in the uptake and continued use of diabetes technology. With increasing use of automated insulin delivery systems, it is important to understand the specific cost-related barriers to technology adoption. In this qualitative analysis, we were interested in understanding and examining the decision-making process around cost and diabetes technology use. Materials and methods Four raters coded transcripts of four stakeholder groups using inductive coding for each stakeholder group to establish relevant themes/nodes. We applied the Social Ecological Model in the interpretation of five thematic levels of cost. Results We identified five thematic levels of cost: policy, organizational, insurance, interpersonal, and individual. Equitable diabetes technology access was an important policy-level theme. The insurance-level theme had multiple sub-themes which predominantly carried a negative valence. Participants also emphasized the psychosocial burden of cost specifically identifying diabetes costs to their families, the guilt of diabetes related costs, and frustration in the time and involvement required to ensure insurance coverage. Conclusion We found broad consensus in how cost is experienced by stakeholder groups. Cost considerations for diabetes technology uptake extended beyond finances to include time, cost to society, morality, and interpersonal relationships. Cost also reflected an important moral principle tied to the shared desire for equitable access to diabetes technology. Knowledge of these considerations can help clinicians and researchers promote equitable device uptake while anticipating barriers for all persons living with type 1 diabetes and their families.

OBJECTIVE Limited research has examined the impact of technology on intimacy and relationships among individuals with type 1 diabetes (T1D). The current study examined the experiences of individuals with T1D and their partners and evaluated the expectations for how advances in technology such as automated insulin delivery systems may impact physical intimacy. METHOD The Insulin Delivery Systems: Perceptions, Ideas, Reflections and Expectations (INSPIRE) study is a multisite study examining expectations for automated insulin delivery systems among adults and youth with T1D as well as partners and caregivers. For the current analysis, data regarding the impact of diabetes on relationship intimacy were extracted from focus groups or individual semistructured interviews with adults with T1D (n = 113) and partners of individuals with T1D (n = 55). RESULTS Three independent coders conducted thematic analysis utilizing NVivo software. Two primary themes were identified: vulnerability in romantic relationships because of managing diabetes and the unique challenges of physical intimacy because of the use of diabetes technology. CONCLUSIONS Participants expressed the hope that diabetes technology, and automated insulin delivery systems in particular, will offer opportunities for flexibility in their diabetes management. These options may decrease their sense of vulnerability through provision of greater control over diabetes management and when/whether to disclose diabetes, minimizing discomforts in the context of sexual intimacy, and reduction of fear about diabetes complications. Patient-reported outcomes and expectations for diabetes technology should be incorporated into patient-provider conversations about sensitive issues. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Each January, the editors of Diabetes Care look back at the last year and forward to the next. In January 2021 we have much to be thankful and happy about. The journal continues to publish outstanding scientific reports together with illuminating and provocative Commentary, Perspective, and Review articles. We are indebted to the authors who submit their manuscripts, the reviewers who evaluate them, and the editorial and production group that manages the process. They make it all possible. In 2020, Diabetes Care ’s impact factor increased once again, from 15.27 to 16.02. Accumulating scientific evidence presented by our journal and others continues to improve understanding of the pathophysiology of diabetes and add to the array of treatments. And yet . . . it’s been a hell of a year in other ways. The coronavirus disease 2019 (COVID-19) pandemic started a year ago and still has the world in its grip. It has tested all of us and brought many activities nearly to a halt. Countless people have fallen ill, sadly many have died, and the daily routines of most families are disturbed. The lockdown to prevent spread of the virus keeps people at home, limits travel, harms businesses, closes schools, and interferes with diagnosis and treatment of other ailments. Acute medical facilities have been overwhelmed in some regions. Fierce debates about controlling the spread of COVID-19 and mitigating its human and economic costs have ensued. Yet, in this crisis we see much heroism. Medical personnel and those who support …

Background: Closed-loop insulin delivery systems have the potential to address the issue of suboptimal glucose control in children and adolescents with type 1 diabetes. We compared safety and efficacy of Cambridge hybrid closed-loop algorithm with usual care over six months in this population. Methods: In a multicentre, multinational, one-period, parallel randomised controlled trial, participants aged 6-18 years using insulin pump therapy were recruited at seven UK and five US paediatric diabetes centres. We randomly assigned participants to closed-loop insulin delivery or to usual care (control) for six months. The Cambridge closed-loop algorithm running on a smartphone was used with either (i) modified Medtronic 640G pump, Medtronic Guardian 3 sensor, and Medtronic prototype phone enclosure (FlorenceM configuration) or (ii) Sooil Dana RS pump and Dexcom G6 sensor (CamAPS FX configuration). Primary endpoint was change in HbA1c at six months combing data from both configurations. Analysis was by intention-to-treat. Trial registration ClinicalTrials.gov, NCT02925299. Findings: We randomised 133 participants (mean±SD baseline HbA1c 8·2±0·7% vs 8·3±0·7%), 65 to closed-loop and 68 to control. At six months, HbA1c was 0·32% lower with closed-loop compared to control (95%CI 0·04 to 0·59; p=0·02). Closed-loop usage was low with FlorenceM due to failing phone enclosures (40% [26, 53]; median [IQR]), but consistently high with CamAPS FX (93% [88, 96]). In post-hoc analysis, HbA1c in the CamAPS FX closed-loop cohort (n=21) was 1·05% lower (95%CI 0·67 to 1·43; p

The purpose of this study was to determine clinician attitudes about the distinct barriers to uptake of continuous glucose monitoring (CGM) among people with diabetes. Survey data were collected measuring individual barriers, prerequisites to CGM, confidence in addressing barriers, and clinic staff resources. Results show that clinicians commonly report barriers to using CGM among people with diabetes in their clinic. Furthermore, clinicians who report a high number of barriers do not feel confident in overcoming the barriers to CGM. Interventions that attempt to empower clinicians to address concerns about CGM among people with diabetes may be warranted because low uptake does not appear to be directly related to available resources or prerequisites to starting CGM.

Objectives In this study, we examined the indirect effects of anxiety on glycated hemoglobin (A1C) via automatic negative thinking and diabetes distress among adolescents with type 1 diabetes (T1D) during the follow-up interval of a randomized controlled trial of an intervention targeting resilience promotion/depression prevention. Methods Adolescents (N=264) participating in the Supporting Teen Problem Solving clinical trial were included and assessed at 8, 12, 16 and 28 months postbaseline. A serial, double-mediation model was used to examine path effects from anxiety to A1C through automatic negative thinking, through diabetes distress and through both automatic negative thinking and diabetes distress. Relevant demographic and clinical covariates were included. Results Anxiety significantly predicted increases in both automatic negative thinking and diabetes distress. Automatic negative thinking was not found to mediate the association between anxiety and A1C, but diabetes distress did mediate the association. The double-mediation path through automatic negative thinking and diabetes distress together was significant. The indirect effect of anxiety on A1C through diabetes distress was significant and greater than the indirect effect of the double-mediator path. Anxiety did not predict A1C independent of its effects on automatic negative thinking and diabetes distress. Inclusion of demographic covariates did not substantively change the results. Conclusions Analyses suggest that automatic negative thinking and diabetes distress mediate the relationship between anxiety and A1C among adolescents with T1D. Diabetes distress appears to be a robust factor linking anxiety to A1C. Diabetes distress should be further examined as a mediator of glycemic variability in anxious youth with T1D.

INTRODUCTION: Chronic pain conditions are common among children and engender cascading effects across social, emotional, and behavioral domains for the child and family. Mobile health (mHealth) describes the practice of delivering healthcare via mobile devices and may be an ideal solution to increase access and reach of evidence-based behavioral health interventions. AREAS COVERED: The aim of this narrative review is to present a state-of-the-art overview of evidence-based mHealth efforts within the field of pediatric chronic pain and consider new and promising directions for study. Given the nascent nature of the field, published mHealth interventions in all stages of development are discussed. Literature was identified through a non-systematic search in PubMed and Google Scholar, and a review of reference lists of papers that were identified as particularly relevant or foundational (within and outside of the chronic pain literature). EXPERT OPINION: mHealth is a promising interventional modality with early evidence suggesting it is primed to enhance behavioral health delivery and patient outcomes. There are many exciting future directions to be explored including drawing inspiration from digital health technology to generate new ways of thinking about the optimal treatment of pediatric chronic pain.

Aims Psychosocial screenings are recommended and increasingly common in pediatric subspecialty clinics, though little is known about their acceptability. This study seeks to uncover profiles of acceptability and assess demographic and clinical correlates among adolescents with diabetes. Methods A sample of 124 adolescents (57.7% female) ages 12–21 years (M = 16.2 ± 2.3) completed screenings during routine diabetes appointments. K-means clustering of responses to acceptability items derived profiles; Analysis of Variance (ANOVA) and Chi-square tests assessed correlates. Results Adolescents with the most common profile (72.6%) placed high importance on medical providers’ awareness of their emotions and reported no difficulties/discomfort with the screener. These youth had moderate depressive symptoms, low diabetes distress, and low A1c. Those who fit a less common profile (18.5%) were uncomfortable with the screener and had the highest depressive symptoms and lowest A1c. Youth who fit a smaller profile (6.5%) endorsed technical difficulties and had high depressive symptoms and lowest diabetes distress. The smallest profile (2.4%, N = 3) had difficulty understanding and experienced discomfort with the screening and had the lowest depressive symptoms and the highest diabetes distress and A1c. These differences in depressive symptoms (F = 3.54, p = .017), A1c values (F = 4.03, p = .009), and diabetes distress (F = 3.27, p = .036) were significant though differences in age, gender, and diabetes duration were not. Conclusions Most youth responded favorably to in-clinic psychosocial screenings. Youth who were less satisfied were at increased risk for psychosocial and medical complications. Findings highlight areas of need, such as enhanced support with and an emphasized rationale for screenings, which may improve patient experience in subspecialty care.

Optimal glycemic control is associated with improved T1D outcomes. However, in the U.S. over the last decade, glycemic control has worsened. We aimed to monitor glucose time-in-range (TIR) in the first year after diagnosis in pediatric T1D to identify the time when glucose control worsens. Newly diagnosed patients (N=67) with T1D were commenced on continuous glucose monitoring (CGM). Data was uploaded to Dexcom Clarity and analyzed retrospectively. Sample size differences at each time period vary due to patient enrollment start dates. All data was analyzed by mixed model and Tukey’s multiple comparison test. In 67 children (mean age 10±5 yrs, A1c at onset 12.1±1.9%) glucose TIR decreased from 64±21% to 55±18% at 10±9 days to 361±23 days post-diagnosis (P=0.03, Table). Mean glucose increased from 146±28 mg/dL at nadir to 172±29 mg/dL at 361±23 days post-diagnosis (P=0.001). CGM wear time also increased from 83±20% to 95±9% at 10±9 days to 361±23 days post-diagnosis (P=0.04). Time spent Disclosure D. Zaharieva: Speaker’s Bureau; Self; Ascensia Diabetes Care, Insulet Corporation, Medtronic. P. Prahalad: None. A. Addala: None. D. Scheinker: None. M. Desai: None. K.K. Hood: Research Support; Self; Dexcom, Inc. Speaker’s Bureau; Self; LifeScan, Inc., MedIQ. B. Leverenz: None. D.M. Maahs: Advisory Panel; Self; Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S. Consultant; Self; Abbott, Sanofi. Research Support; Self; Bigfoot Biomedical, Dexcom, Inc., Roche Diabetes Care, Tandem Diabetes Care.

Disparities in the use of CGMs and insulin pumps in T1D based on socioeconomic status (SES) and race/ethnicity are pronounced. However, systematic reports of perspectives from patients in vulnerable communities are limited. To better understand barriers, focus groups were conducted in Florida and California with adults with T1D. Selection criteria included hospitalization for DKA, HbA1C >9%, or receiving care at a Federally Qualified Health Center. A total of 16 focus groups were conducted in English or Spanish with 86 adults (Table 1). Transcript themes and pre-focus group demographic survey data were analyzed. In order of frequency, barriers to diabetes technology included: (1) provider-level (overtly blocked/discouraged by provider) (2) system-level (financial barriers related to coverage) and (3) individual-level (difficulty with use or preference issues). In Florida there was less technology use overall (38% had used CGMs in FL, 63% in CA; 43% had used pumps in FL, 69% in CA) and significant differences in pump use by SES (P=0.02 in FL, P=0.08 in CA) and race/ethnicity (P=0.01 in FL, P=0.80 in CA). In California there were significant differences in CGM use by race/ethnicity (P=0.05 in CA, P=0.56 in FL) and education level (P=0.02 in CA, P=0.90 in FL). These findings provide novel insights and demonstrate the need for multi-level interventions and further research on variations in technology use based on geographic location. Disclosure A.F. Walker: None. N. Cuttriss: None. M.J. Haller: Advisory Panel; Self; SAB Biotherapeutics, Inc. S.L. Filipp: None. K. Yabut: None. C. Anez-Zabala: None. K.K. Hood: Research Support; Self; Dexcom, Inc. Speaker’s Bureau; Self; LifeScan, Inc., MedIQ. X. Roque: None. D. Naranjo: None. G. Aulisio: None. A. Addala: None. S. Look: None. M.J. Gurka: None. D.M. Maahs: Advisory Panel; Self; Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S. Consultant; Self; Abbott, Sanofi. Research Support; Self; Bigfoot Biomedical, Dexcom, Inc., Roche Diabetes Care, Tandem Diabetes Care. Funding The Leona M. and Harry B. Helmsley Charitable Trust

Project ECHOTM (Extension for Community Healthcare Outcomes) is a hub-spoke telehealth outreach model that democratizes specialty knowledge to reduce disparities and improve health outcomes. Limited access to endocrinologists forces many primary care providers (PCPs) to manage patients with type 1 diabetes (T1D) without specialty support. As such, Stanford and the University of Florida partnered to develop and pilot “ECHO T1D”, a teleECHOTM clinic focused on T1D in California (CA) and Florida (FL), respectively. Our goal was to demonstrate the feasibility of ECHO T1D and improve PCPs’ abilities to manage patients with T1D. Primary care spokes were recruited targeting Federally Qualified Health Centers (FQHCs) where vulnerable T1D patient populations more likely rely on PCPs for care. In CA, 11 spokes enrolled with 37 clinics serving ∼900 patients with T1D who do not receive routine specialty T1D care. In FL, 12 spokes enrolled with 67 clinics serving ∼1,000 patients with T1D. Multidisciplinary hub team specialists were recruited and a 6-month curriculum was developed. Weekly 1-hour teleECHO sessions consisting of didactic presentations and case reviews were offered for 27 sessions. Weekly engagement of the 70 participating PCPs (69% in CA) ranged from 0 to 27 (mean 14) sessions and 65 completed both baseline and exit surveys. Baseline data demonstrated low confidence in providing T1D care, especially related to diabetes technology. Pre/post surveys demonstrated statistically significant improvements in provider confidence in T1D management and knowledge (p=0.02). PCPs who attended ≥ 50% sessions had the largest improvements. Over 90% of PCPs reported changes in medical practice (e.g., insulin and pump adjustments) and 95% would recommend the program to colleagues. The ECHO model can be applied to T1D to improve PCPs’ ability to manage patients with T1D. Future directions include evaluating influence on patient level outcomes and applying the model to insulin-requiring T2D patients. Disclosure N. Cuttriss: None. C. Anez-Zabala: None. L.G. Baer: None. S.L. Filipp: None. M. Basina: None. M.J. Gurka: None. L. Figg: None. M.J. Haller: Advisory Panel; Self; SAB Biotherapeutics, Inc. K.K. Hood: Research Support; Self; Dexcom, Inc. Speaker’s Bureau; Self; LifeScan, Inc., MedIQ. X. Roque: None. R. Lal: Consultant; Self; Abbott, Biolinq. S.C. Westen: None. D.M. Maahs: Advisory Panel; Self; Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S. Consultant; Self; Abbott, Sanofi. Research Support; Self; Bigfoot Biomedical, Dexcom, Inc., Roche Diabetes Care, Tandem Diabetes Care. M. Town: Other Relationship; Self; Insulet Corporation. C. Wang: None. J.J. Wong: None. K. Yabut: None. A.F. Walker: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust

CGM technology allows care teams to remotely monitor glucose levels of people with diabetes. Provider availability to monitor and contact people is limited. Individuals respond differently to CGM review calls; some people improve glucose control while others disengage. No mathematical framework exists to optimize population-level care while accounting for provider constraints and differences in people’s responses. We hypothesize that a care team’s call schedule can be optimized using predictive modeling and personalized recommendations. We designed a recommendation tool that ranks people based on expected improvement in glucose management due to a call, incorporating people’s responsiveness. Individuals’ short- and long-term improvements after simulated previous calls were used to calculate the expected decrease in mean glucose due to a new call. The tool is designed with 724,672 hours of CGM data from 120 individuals with T1D (63% new diagnosis, 57% ≤ 18 years), through Tidepool. For a daily capacity of 5 calls, the recommendation has a 29.1 mg/dL expected decrease in mean glucose in contacted people, while current practice has a 4.7 mg/dL decrease. The tool allows for customizable care team constraints and adaptively learned responsiveness parameters. CGM and call data are currently being collected from pediatric patients with newly diagnosed T1D in our clinic, to tune and test the tool in a clinical setting. Disclosure J. Vallon: None. A.T. Ward: None. P. Prahalad: None. K.K. Hood: Research Support; Self; Dexcom, Inc. Speaker’s Bureau; Self; LifeScan, Inc., MedIQ. D.M. Maahs: Advisory Panel; Self; Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S. Consultant; Self; Abbott, Sanofi. Research Support; Self; Bigfoot Biomedical, Dexcom, Inc., Roche Diabetes Care, Tandem Diabetes Care. D. Scheinker: None.

Objective: To document rates of elevated depressive symptoms endorsed during routine screening for adolescents and young adults (AYA) with type 2 diabetes (T2D), review clinical actions taken in response to screening results, and evaluate associations of depressive symptoms with AYA characteristics. Research Design and Methods: The Patient Health Questionnaire (PHQ) was administered to 218 AYA with T2D using the PHQ-2 or PHQ-9 in routine pediatric diabetes care at 4 academic medical centers. Data from electronic health records were collected from the screening date and 12 months prior. Results: The mean age was 16.77 (SD 2.10 years); 56% male; 74% non-Hispanic White; Mean T2D duration 3.48 (SD 2.51 years). On the PHQ, 21.6% of AYA with T2D endorsed elevated depressive symptoms (PHQ score≥10) and 15.2% endorsed thoughts of self-harm. Older age, shorter T2D duration, not on insulin, and more blood glucose checks per day were significantly associated with more depressive symptoms. Of those AYAs endorsing the harm-to-self item, 8.3% were in mental health treatment. For AYAs expressing harm-to-self who were not in treatment (91.7%),18.2% did not have a documented referral for mental health treatment in the medical record. Conclusions: Screening for depressive symptoms identifies individuals in need of referral for mental health treatment; however, a focus on self-harm assessment, standardized methods for documentation of symptoms, mental health referrals and increased referral resources are needed. Disclosure J.Y. Stone: None. S.A. Mulvaney: None. C.A. Mara: None. J.C. Kichler: None. S. Majidi: Advisory Panel; Self; Companion Medical. K.A. Driscoll: None. S.C. Westen: None. A. Rawlinson: None. L.M. Jacobsen: None. K.K. Hood: Research Support; Self; Dexcom, Inc. Speaker’s Bureau; Self; LifeScan, Inc., MedIQ. M. Monaghan: Research Support; Self; American Diabetes Association. R.N. Adams: Employee; Self; Virta Health Corp. Funding National Center for Advancing Translational Sciences (UL1TR002243, UL1TR001427)

Background: Psychosocial screening is recommended and increasingly common, but little is known about youths’ perspectives on screenings. Methods: One hundred and twenty-four adolescents (57.7% female) ages 12-21 years (M=16.2±2.3) completed routine, clinic-integrated screenings. K-means clustering derived profiles and ANOVA assessed correlates profiles. Results: Four distinct profiles emerged (Table 1). Profiles varied by depression (F=3.54, p=0.017), diabetes distress (F=3.27, p=0.036), and A1c values (F=4.03, p=0.009). Majority (72.6%) placed high importance on diabetes teams awareness about their emotions and reported no difficulties/discomfort (Embracers). Those uncomfortable with screening (Avoiders) were most depressed and had lowest A1C. Youth who endorsed difficulties with tablet and placed low importance about team awareness about their emotions (Skeptics) had relatively high depression but least diabetes distress. A small fourth group (Strugglers; n=3) must be interpreted with caution due to size. No differences were found for age, gender, diabetes duration/type, race/ethnicity, self-rated global health, or anxiety. Conclusions: Most youth responded favorably to in-clinic psychosocial screenings. Those less satisfied may have increased mental health risk and may benefit from technical support and an emphasized rationale for screenings. Disclosure J.J. Wong: None. S. Hanes: None. M.S. Lanning: None. M.L. Tanenbaum: None. D. Naranjo: None. K.K. Hood: Research Support; Self; Dexcom, Inc. Speaker’s Bureau; Self; LifeScan, Inc., MedIQ.

CGM use is associated with lower HbA1c in people with T1D. We hypothesize early CGM initiation will improve longer term HbA1c. Youth with newly diagnosed T1D from July 2018 to May 2019 (pilot cohort, n=65), were offered CGM initiation in the 1st month of T1D diagnosis with 62 initiating CGM. We compared HbA1c outcomes in this pilot cohort with those diagnosed in 2014-2016 (control cohort, n=272) with follow-up duration restricted to 15 months. HbA1c trajectories were visualized using locally estimated scatter plot smoothing (Figure 1) and compared using a generalized mixed effects regression model adjusted for baseline characteristics (HbA1c at onset, age, sex, race and insurance type). Mean HbA1c at diagnosis was higher in the pilot cohort (12.0% vs. 10.7%). Over the first 15 months of T1D, CGM was initiated in 95% of the pilot cohort (78.5% within 30 days), whereas 56% initiated in the control cohort (1.8% within 30 days). Adjusting for baseline characteristics, mean HbA1c levels were 0.5% lower (95%CI: -1.0, -0.1) in the pilot cohort at 3 months and 1.7% lower (95% CI: -2.6, -0.8) at 6 months compared to the control cohort. Differences beyond 6 months were also in the expected direction and statistically significant at the 0.05 level. Early initiation of CGM in the new onset period was associated with lower HbA1c compared to historic controls. These data suggest that early CGM initiation should be considered a part of standard new onset T1D care. Disclosure P. Prahalad: None. V. Ding: None. A. Addala: None. C. New: None. B.P. Conrad: None. A. Chmielewski: None. E. Geels: None. J. Leverenz: None. A. Martinez-Singh: None. P. Sagan: None. J. Senaldi: None. A. Freeman: None. D. Scheinker: None. K.K. Hood: Research Support; Self; Dexcom, Inc. Speaker’s Bureau; Self; LifeScan, Inc., MedIQ. M. Desai: None. D.M. Maahs: Advisory Panel; Self; Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S. Consultant; Self; Abbott, Sanofi. Research Support; Self; Bigfoot Biomedical, Dexcom, Inc., Roche Diabetes Care, Tandem Diabetes Care.

Primary care providers (PCPs) manage type 1 diabetes (T1D) and complex diabetes for people who lack access to multispecialty care. Project ECHOTM (Extension for Community Healthcare Outcomes) is a low-dose, high frequency workforce development hub-spoke model that leverages telehealth to connect multidisciplinary specialists (“hub”) with PCPs across regional clinic sites (“spokes”). Applying the ECHO model, we piloted the model for T1D (Project ECHO T1D) in the states of California (CA) and Florida (FL) targeting PCPs managing adult and pediatric patients with T1D. Weekly hour-long teleECHOTM sessions were led by each hub in CA and FL over a 6 month pilot period. Each session included 1 to 2 case presentation. Prior to each teleECHO session, PCPs uploaded de-identified case presentations for discussion via REDCap®. Recommendations were provided by other participants and the multidisciplinary hub teams. Characteristics of case presentations were tracked in CA and FL. During the 6 month intervention, 47 new and follow-up cases were presented in CA and 45 in FL. Middle age adults (33.9±17.4 years-old, 20% pediatric) with poorly controlled diabetes (HbA1c 9.6±2.2% in CA and 10.4±2.8% in FL) were frequent cases. Common thematic questions submitted by PCPs in CA and FL, respectively, included: insulin dose adjustments (49%, 47%), social concerns (37%, 47%), behavioral health (29%, 34%), diabetes devices (44%, 13%), and diabetes education (15%, 38%). Patients commonly had depression (29.3%, 28.1%), recent hospitalizations (27%, 17%) and ER visits (33%, 26%) in the past year. Greatest barriers to care were social support (34%, 28%), financial (29%, 22%), diabetes knowledge (22%, 25%), attitudes and beliefs (27%, 16%) and psychiatric issues (20%, 19%). Findings illustrate the complexity of diabetes being managed by PCPs and the need for healthcare delivery innovation in diabetes education to support PCPs and primary care clinics who manage patients with complex diabetes who lack access to diabetes specialty care. Disclosure N. Cuttriss: None. C. Anez-Zabala: None. L.G. Baer: None. S.L. Filipp: None. M. Basina: None. M.J. Gurka: None. L. Figg: None. M.J. Haller: Advisory Panel; Self; SAB Biotherapeutics, Inc. K.K. Hood: Research Support; Self; Dexcom, Inc. Speaker’s Bureau; Self; LifeScan, Inc., MedIQ. X. Roque: None. R. Lal: Consultant; Self; Abbott, Biolinq. S.C. Westen: None. D.M. Maahs: Advisory Panel; Self; Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S. Consultant; Self; Abbott, Sanofi. Research Support; Self; Bigfoot Biomedical, Dexcom, Inc., Roche Diabetes Care, Tandem Diabetes Care. M. Town: Other Relationship; Self; Insulet Corporation. C. Wang: None. J.J. Wong: None. K. Yabut: None. A.F. Walker: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust

The purpose of this study was to evaluate feasibility of initiating continuous glucose monitoring (CGM) through telehealth as a means of expanding access. Adults with type 1 diabetes (N = 27) or type 2 diabetes using insulin (N = 7) and interest in starting CGM selected a CGM system (Dexcom G6 or Abbott FreeStyle Libre), which they received by mail. CGM was initiated with a certified diabetes care and education specialist providing instruction via videoconference or phone. The primary outcome was days per week of CGM use during the last 4 weeks. Hemoglobin A1c (HbA1c) was measured at baseline and 12 weeks. Participant self-reported outcome measures were also evaluated. All 34 participants (mean age, 46 ± 18 years; 53% female, 85% white) were using CGM at 12 weeks, with 94% using CGM at least 6 days per week during weeks 9 to 12. Mean HbA1c decreased from 8.3 ± 1.6 at baseline to 7.2 ± 1.3 at 12 weeks (P

IntroductionManagement of newly diagnosed type 1 diabetes (T1D) in children and adolescents is challenging for patients, families and healthcare professionals. The objective of this study is to determine whether continued intensive metabolic control using hybrid closed-loop (CL) insulin delivery following diagnosis of T1D can preserve C-peptide secretion, a marker of residual beta-cell function, compared with standard multiple daily injections (MDI) therapy.Methods and analysisThe study adopts an open-label, multicentre, randomised, parallel design, and aims to randomise 96 participants aged 10–16.9 years, recruited within 21 days of diagnosis with T1D. Following a baseline mixed meal tolerance test (MMTT), participants will be randomised to receive 24 months treatment with conventional MDI therapy or with CL insulin delivery. A further 24-month optional extension phase will be offered to all participants to continue with the allocated treatment. The primary outcome is the between group difference in area under the stimulated C-peptide curve (AUC) of the MMTT at 12 months post diagnosis. Analyses will be conducted on an intention-to-treat basis. Key secondary outcomes are between group differences in time spent in target glucose range (3.9–10 mmol/L), glycated haemoglobin (HbA1c) and time spent in hypoglycaemia (Ethics and disseminationEthics approval has been obtained from Cambridge East Research Ethics Committee. The results will be disseminated by peer-reviewed publications and conference presentations.Trial registration numberNCT02871089; Pre-results.

For people with type 1 diabetes (T1DM), regular exercise can be highly beneficial. Although\ud exercise has been shown to improve quality of life and health for people living with T1DM,\ud there are common barriers. To examine such issues, we explored the perceived impact that\ud automated insulin delivery systems could have on people with T1DM and their families.\ud One common theme found was hopes, expectations and impact on sports and exercise. Four\ud sites (United States: three; UK: one) were involved in this study. Two hundred and eighty-four\ud participants were recruited across all sites; participants comprised: children (9–11 years);\ud adolescents (12–18 years); parents/caretakers of children and adolescents with T1DM; adults\ud with T1DM (18–77 years); and their significant others/partners. Between May and December\ud 2015, focus groups and semi-structured interviews were conducted and analysed using\ud content analysis. Three themes found related to the benefits of automated insulin delivery\ud systems: (a) more freedom and spontaneity in the individual’s ability to exercise; (b) relief\ud from worry of hypoglycaemia as a result of exercise; (c) removing the ‘guesswork’ of\ud adjusting insulin for exercise. Two further themes emerged relating to potential concerns\ud with regard to safely exercising while wearing an automated insulin delivery system. Further\ud research is encouraged with a view to providing accurate algorithms and increasing\ud confidence for those using automated insulin delivery systems and, in turn, for their exercise\ud colleagues and loved ones.

Digital health is capturing the attention of the healthcare community. This paradigm whereby healthcare meets the internet uses sensors that communicate wirelessly along with software residing on smartphones to deliver data, information, treatment recommendations, and in some cases control over an effector device. As artificial intelligence becomes more widely used, this approach to creating individualized treatment plans will increase the opportunities for patients, even if they are in remote settings, to communicate with and learn from healthcare professionals. Simple design is needed to promote use of these tools, especially for the purpose of increased adherence to treatment. Widespread adoption by the healthcare industry will require better outcomes data, which will most likely be in the form of safety and effectiveness results from robust randomized controlled trials, as well as evidence of privacy and security. Such data will be needed to convince investors to direct resources into and regulators to clear new digital health tools. Diabetes Technology Society and Sansum Diabetes Research Institute launched the Digital Diabetes Congress in 2017 because of great interest in determining the potential benefits, metrics of success, and appropriate components of mobile applications for diabetes. The second annual meeting in this series took place on May 22-23, 2018 in San Francisco. This report contains summaries of the meeting’s 4 plenary lectures and 10 sessions. This meeting report presents a summary of how 55 panelists, speakers, and moderators, who are leaders in healthcare technology, see the current and future landscape of digital health tools applied to diabetes.

The recent development of reliable systems for continuously monitoring interstitial glucose levels has set the stage for a revolution in diabetes research and care. The ability to obtain real-time and summary displays of glycemic patterns of individuals with diabetes, together with rapidly obtained agreement on various definitions and ways of handling the resulting data (1,2), has led to both rapid acceptance of continuous glucose monitoring (CGM) devices and incorporation of CGM into clinical research studies. At the clinical level, some practical and quality-of-life–related benefits of CGM are well documented (3,4). Newer systems offer improved accuracy, fewer (or no) fingersticks, and remote monitoring of potentially dangerous glycemic events. While access to and use of CGM are increasing, some important questions remain. Which groups of people with diabetes will benefit the most from CGM use? When is the best time to introduce CGM systems to diabetes care? How should use of CGM systems be taught and adjusted? What specific outcomes are most critical to improve and document? How can this technology be used most cost-effectively? All members of the diabetes community—people with diabetes themselves, caregivers of persons with diabetes, diabetes care providers, payers, and health system managers—will benefit from objective data addressing all these questions. The collection of articles presented in this issue of Diabetes Care offers information on some of these questions for people with type 1 diabetes. Three reports describe CGM experiences in diverse populations. Miller et al. (5) display the recent dramatic increases in CGM use by both youth and adults with type 1 diabetes in the T1D Exchange in the U.S. (6) and the DPV (Diabetes Patienten Verlaufdocumentation) registry in Germany and Austria (7). CGM use among those

Background: Diabetes devices such as insulin pumps and continuous glucose monitoring (CGM) are associated with improved health and quality of life in adults with type 1 diabetes (T1D). However, uptake remains low. The aim of this study was to develop different “personas” of adults with T1D in relation to readiness to adopt new diabetes technology. Methods: Participants were 1498 T1D Exchange participants who completed surveys on barriers to uptake, technology attitudes, and other psychosocial variables. HbA1c data was available from the T1D Exchange for 30% of the sample. K-means cluster analyses grouped the sample by device barriers and attitudes. The authors assigned descriptive labels based on cluster characteristics. ANOVAs and chi-square tests assessed group differences by demographic and psychosocial variables (eg, diabetes duration, diabetes distress). Results: Analyses yielded five distinct personas. The d-Embracers (54% of participants) endorsed few barriers to device use and had the highest rates of device use, lowest HbA1c, and were the least distressed. The Free Rangers (23%) had the most negative technology attitudes. The Data Minimalists (10%) used pumps but had lower CGM use and did not want more diabetes information. The Wary Wearers (11%) had lower overall device use, were younger, more distressed, endorsed many barriers, and had higher HbA1c. The High Distress (3%) group members were the youngest, had the shortest diabetes duration, reported the most barriers, and were the most distressed. Conclusion: These clinically meaningful personas of device readiness can inform tailored interventions targeting barriers and psychosocial needs to increase device uptake.

OBJECTIVES: The primary objective was to investigate the mediating effects of diabetes management in the relationship between diabetes symptoms and generic health-related quality of life (HRQOL) in adolescents and young adults (AYAs) with type 1 diabetes. The secondary objective explored patient health communication and perceived treatment adherence barriers as mediators in a serial multiple mediator model. METHODS: The PedsQL 3.2 Diabetes Module 15-item diabetes symptoms summary score, 18-item diabetes management summary score, and PedsQL 4.0 generic core scales were completed in a 10-site national field test study by 418 AYA aged 13 to 25 years with type 1 diabetes. Diabetes symptoms and diabetes management were tested for bivariate and multivariate linear associations with overall generic HRQOL. Mediational analyses were conducted to test the hypothesized mediating effects of diabetes management as an intervening variable between diabetes symptoms and generic HRQOL. RESULTS: The predictive effects of diabetes symptoms on HRQOL were mediated in part by diabetes management. In predictive analytics models utilizing multiple regression analyses, demographic and clinical covariates, diabetes symptoms, and diabetes management significantly accounted for 53% of the variance in generic HRQOL (P < 0.001), demonstrating a large effect size. Patient health communication and perceived treatment adherence barriers were significant mediators in an exploratory serial multiple mediator model. CONCLUSIONS: Diabetes management explains in part the effects of diabetes symptoms on HRQOL in AYA with type 1 diabetes. Patient health communication to healthcare providers and perceived treatment adherence barriers further explain the mechanism in the relationship between diabetes symptoms and overall HRQOL.

Background: Integration of momentary contextual and psychosocial factors within self-management feedback may provide more specific, engaging, and personalized targets for problem solving. Methods: Forty-four youth ages 13–19 with type 1 diabetes (T1D) were provided a Bluetooth meter and completed the 30-day protocol. Participants were randomized to “app + meter” or “meter-only” groups. App + meter participants completed mealtime and bedtime assessment each day. Assessments focused on psychosocial and contextual information relevant for self-management. Graphical feedback integrated self-monitored blood glucose (SMBG), insulin, and Bluetooth-transmitted blood glucose data with the psychosocial and contextual data. App + meter participants completed an interview to identify data patterns. Results: The median number of momentary assessments per participant was 80.0 (range 32–120) with 2.60 per day. By 2 weeks participants had an average of 40.77 (SD 12.23) assessments. Dose–response analyses indicated that the number of app assessments submitted were significantly related to higher mean daily SMBG (r = −0.44, P

The objective was to investigate the patient-reported diabetes symptoms predictors of generic health-related quality of life (HRQOL) in adolescents and young adults (AYA) with type 1 or type 2 diabetes. The 15-item PedsQL™ 3.2 Diabetes Module Diabetes Symptoms Summary Score and PedsQL™ 4.0 Generic Core Scales were completed in a 10-site national field test study by 513 AYA ages 13–25 years with type 1 (n = 424) or type 2 (n = 89) diabetes. Diabetes symptoms were tested for bivariate and multivariate linear associations with generic HRQOL. Diabetes symptoms were associated with decreased HRQOL in bivariate analyses. In predictive analytics models utilizing hierarchical multiple regression analyses controlling for relevant demographic and clinical covariates, diabetes symptoms accounted for 38 and 39% of the variance in patient-reported generic HRQOL for type 1 and type 2 diabetes, respectively, reflecting large effect sizes. The diabetes symptoms facets hyperglycemia symptoms, hypoglycemia symptoms, and nonspecific diabetes symptoms individually accounted for a significant percentage of the variance in separate exploratory predictive analytics models after controlling for demographic and clinical covariates, with small-to-large effect sizes. Diabetes symptoms are potentially modifiable predictors of generic HRQOL in AYA with diabetes. Identifying specific diabetes symptoms or symptoms facets that are the most important predictors from the patient perspective facilitates a patient-centered approach in clinical research, clinical trials, and practice designed to enhance overall generic HRQOL in AYA with diabetes.

With the evolution of diabetes technology, those living with Type 1 diabetes are given a wider arsenal of tools with which to achieve glycaemic control and improve patient-reported outcomes. Furthermore, the use of these technologies may help reduce the risk of acute complications, such as severe hypoglycaemia and diabetic ketoacidosis, as well as long-term macro- and microvascular complications. In addition, diabetes technology can have a beneficial impact on psychosocial health by reducing the burden of diabetes. Unfortunately, diabetes goals are often unmet and people with Type 1 diabetes too frequently experience acute and long-term complications of this condition, in addition to often having less than ideal psychosocial outcomes. Increasing realization of the importance of patient-reported outcomes is leading to diabetes care delivery becoming more patient-centred. Diabetes technology in the form of medical devices, digital health and big data analytics have the potential to improve clinical care and psychosocial support, resulting in lower rates of acute and chronic complications, decreased burden of diabetes care, and improved quality of life.

Aims Self-compassion (SC), or treating oneself with kindness when dealing with personal challenges, has not been rigorously examined in people with T1D. SC has been shown to buffer against negative emotions and to be linked to improved health outcomes, but diabetes-specific SC has not been studied. This study aimed to adapt the Self-Compassion Scale and validate it for a diabetes-specific population. Methods We developed and validated a diabetes-specific version of the Self-Compassion Scale (Neff, 2003) in a sample of adults with T1D (N = 542; 65% female; 97% non-Hispanic White; M age 41, SD = 15.7; M A1c = 7.3, SD = 1; 72% insulin pump users; 50% continuous glucose monitoring [CGM] users). Confirmatory factor analyses (CFA), and reliability and construct validity analyses were conducted. Validity measures included diabetes distress, diabetes empowerment, diabetes numeracy, and A1c. Results A two-factor bi-factor structure showed best fit, providing support for use of the adapted scale (SCS-D) as a unitary construct. The 19-item unidimensional SCS-D demonstrated excellent internal consistency (ɑ = 0.94; range of item-total correlations: 0.52–0.71) and construct validity. As hypothesized, higher SCS-D was associated with less distress, greater empowerment, and lower A1c, and was not associated with numeracy. Conclusions The SCS-D is a reliable and valid measure of diabetes-specific self-compassion in adults with T1D.

Objective This study adds to the literature on the psychometric properties of the Problem Areas in Diabetes-Teen (PAID-T) and Parent (P-PAID-T) Versions. It also aims to shorten the measures of diabetes-specific distress, determine construct validity, and establish cutoff scores. Methods Data are from two independent studies (N = 1,265). Adolescent-caregiver dyads completed measures of emotional distress, diabetes strengths, hemoglobin A1c, blood glucose checks, and average blood glucose. Exploratory and confirmatory factor analyses assessed factor structures for each measure. Correlational analyses provided support for concurrent validity. Receiver-operating characteristic curves identified cutoff scores based on clinically meaningful groups identified with latent profile analysis. Results Analyses supported a 14-item PAID-T and a 15-item P-PAID-T, with preliminary cutoff scores ≥44 and ≥54, respectively. Measures were associated with emotional and health outcomes as hypothesized. Conclusions The PAID-T and P-PAID-T are valid, reliable, and useful measures of diabetes-specific distress for teenagers with type 1 diabetes and parents of teenagers.

Aims The purpose of this study was to explore preferences that adults with type 1 diabetes (T1D) have for training and support to initiate and sustain optimal use of continuous glucose monitoring (CGM) technology. Methods Twenty-two adults with T1D (M age 30.95 ± 8.32; 59.1% female; 90.9% Non-Hispanic; 86.4% White; diabetes duration 13.5 ± 8.42 years; 72.7% insulin pump users) who had initiated CGM use in the past year participated in focus groups exploring two overarching questions: (1) What helped you learn to use your CGM? and (2) What additional support would you have wanted? Focus groups used a semi-structured interview guide and were recorded, transcribed and analyzed. Results Overarching themes identified were: (1) “I got it going by myself”: CGM training left to the individual; (2) Internet as diabetes educator, troubleshooter, and peer support system; and (3) domains of support they wanted, including content and format of this support. Conclusion This study identifies current gaps in training and potential avenues for enhancing device education and CGM onboarding support for adults with T1D. Providing CGM users with relevant, timely resources and attending to the emotional side of using CGM could alleviate the burden of starting a new device and promote sustained device use.

IntroductionProject ECHO (Extension for Community Healthcare Outcomes) is a tele-education outreach model that seeks to democratize specialty knowledge to reduce disparities and improve health outcomes. Limited utilization of endocrinologists forces many primary care providers (PCPs) to care for patients with type 1 diabetes (T1D) without specialty support. Accordingly, an ECHO T1D program was developed and piloted in Florida and California. Our goal was to demonstrate the feasibility of an ECHO program focused on T1D and improve PCPs’ abilities to manage patients with T1D.Research design and methodsHealth centers (ie, spokes) were recruited into the ECHO T1D pilot through an innovative approach, focusing on Federally Qualified Health Centers and through identification of high-need catchment areas using the Neighborhood Deprivation Index and provider geocoding. Participating spokes received weekly tele-education provided by the University of Florida and Stanford University hub specialty team through virtual ECHO clinics, real-time support with complex T1D medical decision-making, access to a diabetes support coach, and access to an online repository of diabetes care resources. Participating PCPs completed pre/post-tests assessing diabetes knowledge and confidence and an exit survey gleaning feedback about overall ECHO T1D program experiences.ResultsIn Florida, 12 spoke sites enrolled with 67 clinics serving >1000 patients with T1D. In California, 11 spoke sites enrolled with 37 clinics serving >900 patients with T1D. During the 6-month intervention, 27 tele-education clinics were offered and n=70 PCPs (22 from Florida, 48 from California) from participating spoke sites completed pre/post-test surveys assessing diabetes care knowledge and confidence in diabetes care. There was statistically significant improvement in diabetes knowledge (p≤0.01) as well as in diabetes confidence (p≤0.01).ConclusionsThe ECHO T1D pilot demonstrated proof of concept for a T1D-specific ECHO program and represents a viable model to reach medically underserved communities which do not use specialists.

As the prevalence of obesity in Type 1 diabetes rises, the effects of emerging therapy options should be considered in the context of both weight and glycaemic control outcomes. Artificial pancreas device systems will ‘close the loop’ between blood glucose monitoring and automated insulin delivery and may transform day-to-day dietary management for people with Type 1 diabetes in multiple ways. In the present review, we draw directly from cognitive restraint theory to consider unintended impacts that closed-loop systems may have on ingestive behaviour and food intake. We provide a brief overview of dietary restraint theory and its relation to weight status in the general population, discuss the role of restraint in traditional Type 1 diabetes treatment, and lastly, use this restraint framework to discuss the possible behavioural implications and opportunities of closed-loop systems in the treatment of Type 1 diabetes. We hypothesize that adopting closed-loop systems will lift the diligence and restriction that characterizes Type 1 diabetes today, thus requiring a transition from a restrained eating behaviour to a non-restrained eating behaviour. Furthermore, we suggest this transition be leveraged as an opportunity to teach people lifelong eating behaviour to promote healthy weight status by incorporating education and cognitive reappraisal. Our aim was to use a transdisciplinary approach to highlight critical aspects of the emerging closed-loop technologies relating to eating behaviour and weight effects and to promote discussion of strategies to optimize long-term health in Type 1 diabetes via two key outcomes: glycaemic control and weight management.

OBJECTIVE The purpose of this study was to rigorously explore psychosocial factors associated with automated insulin delivery systems among people living with type 1 diabetes. RESEARCH DESIGN AND METHODS Across four sites in the U.S. and U.K., 284 participants completed structured interviews or focus groups on expectations, desired features, potential benefits, and perceived burdens of automated insulin delivery systems. Recorded audio files were transcribed and analyzed using NVivo. RESULTS Three themes were identified as critical for uptake of automated insulin delivery: considerations of trust and control, system features, and concerns and barriers to adoption. Children and adolescents with type 1 diabetes primarily identified needs specific to their life stage and social contexts (e.g., school). Adults with type 1 diabetes, parents of youth with type 1 diabetes, and partners of adults with type 1 diabetes were most concerned about the accuracy, adaptability, and algorithm quality alongside expectations that systems stabilize glucose levels and reduce risk for long-term complications. CONCLUSIONS Incorporating stakeholder perspectives on use of automated insulin delivery systems will improve the adoption of devices, quality of life, and likelihood of optimal health. Efforts to build trust in systems, optimize user-system interactions, and provide clear guidance about device capabilities and limitations may help potential users achieve optimal glycemic outcomes.

Automated closed loop systems will greatly change type 1 diabetes management; user trust will be essential for acceptance of this new technology. This qualitative study explored trust in 32 individuals following a hybrid closed loop trial. Participants described how context-, system-, and person-level factors influenced their trust in the system. Participants attempted to override the system when they lacked trust, while trusting the system decreased self-management burdens and decreased stress. Findings highlight considerations for fostering trust in closed loop systems. Systems may be able to engage users by offering varying levels of controls to match trust preferences.

Objective Despite the challenges of managing type 1 diabetes, many adolescents achieve optimal outcomes. A validated measure of diabetes-specific strengths is needed to measure adaptive behaviors and attitudes associated with overcoming challenges and achieving "resilient" outcomes. Methods Baseline data from 260 adolescents (age 14-18 years, M = 15.7 ± 1.1, 60% female, 33% Non-Caucasian, M A1c = 9.1 ± 1.9%) and caregivers in a behavioral intervention trial were analyzed to evaluate psychometric properties of the 12-item self-report Diabetes Strengths and Resilience measure for adolescents (DSTAR-Teen). Reliability and validity were examined in relation to measures of related constructs, regimen adherence, and glycemic outcomes, and confirmatory factor analysis was conducted. Results Reliability was good (internal consistency: α = .89; item-total correlations: r range = .55-.78). Significant correlations demonstrated construct and criterion validity. A two-factor structure reflecting intrapersonal and interpersonal processes fit the data better than a one-factor solution. Conclusions The DSTAR-Teen has strong psychometric properties, captures adaptive aspects of adolescents' diabetes management (i.e., "strengths"), and is related to clinical outcomes.

Purpose The first hybrid closed loop (HCL) system, which automates insulin delivery but requires user inputs, was approved for treatment of type 1 diabetes (T1D) by the US Food and Drug Administration in September 2016. The purpose of this study was to explore the benefits, expectations, and attitudes of individuals with T1D following a clinical trial of an HCL system. Methods Thirty-two individuals with T1D (17 adults, 15 adolescents) participated in focus groups after 4 to 5 days of system use. Content analysis generated themes regarding perceived benefits, hassles, and limitations. Results Some participants felt misled by terms such as “closed loop” and “artificial pancreas,” which seemed to imply a more “hands-off” experience. Perceived benefits were improved glycemic control, anticipated reduction of long-term complications, better quality of life, and reduced mental burden of diabetes. Hassles and limitations included unexpected tasks for the user, difficulties wearing the system, concerns about controlling highs, and being reminded of diabetes. Conclusion Users are willing to accept some hassles and limitations if they also perceive health and quality-of-life benefits beyond current self-management. It is important for clinicians to provide a balanced view of positives and negatives to help manage expectations.

Objective Adolescents with Type 1 diabetes (T1D) are vulnerable to diabetes-related distress and often struggle to complete self-management tasks needed to maintain blood glucose values in target range. One way that youth with T1D handle problems is through avoidant coping. The current study examined cross-time associations between avoidant coping style and diabetes outcomes and tested the possible mediating role of diabetes-related distress. Method Adolescents with T1D (N = 264) were assessed 4 times over 1 year to measure avoidant coping style, diabetes-related distress, adherence (on the basis of glucometer data and self-report), and glycemic control (hemoglobin A1c). Mediation and direct effects were tested across time using time-lagged autoregressive path models, making use of the repeated measurement of all constructs. Results The hypothesized mediation effect was found for all 3 diabetes outcomes. Higher levels of avoidant coping style were associated with greater diabetes-related distress at the subsequent time point, which was related in turn to fewer blood glucose checks, less frequent self-care behaviors, and poorer glycemic control (higher A1c) at the next assessment. Conclusions In the context of diabetes, an avoidant coping style may contribute to greater diabetes-specific distress followed by deterioration in self-management and glycemic control over time. Maladaptive coping styles are modifiable factors that offer an entry point into intervention before further difficulties can take hold. (PsycINFO Database Record

Insulin pumps and continuous glucose monitors (CGM) can improve glycemic control for individuals with type 1 diabetes (T1D). Device uptake rates continue to show room for improvement, and consistent adherence is needed to achieve better outcomes. Diabetes health care providers have important roles to play in promoting device use and adherence.We surveyed 209 clinicians who treat people with type 1 diabetes to examine perceptions of barriers to device uptake, attitudes toward diabetes technology, and resources needed for clinicians to improve device uptake. We compared findings with our survey of adults with T1D.Younger clinicians treated more patients using insulin pumps ( r = -.26, P.001) and CGM ( r = -.14, P = .02), and had more positive attitudes about diabetes technology ( r = -.23, P = .001). The most frequently endorsed modifiable barriers were perceptions that patients dislike having the device on their body (73% pump; 63% CGM), dislike the alarms (61% CGM), and do not understand what to do with device information or features (40% pump; 46% CGM). Clinicians wanted lower cost and better insurance coverage for their patients, and they recommended counseling and education to help address barriers and improve adherence to devices.Clinicians perceive many barriers to their patients initiating and adhering to diabetes devices. Findings highlight opportunities for intervention to improve clinician-patient communication around device barriers to help address them.

Diabetes Care ’s editorial committee customarily presents a midyear report of activities and progress. At the midpoint of 2018 we can describe, in addition to a satisfying array of original scientific reports, important feature articles of current interest and a significant new initiative. In the first half of this year, the journal published several feature articles related to our core responsibility as a journal representing the American Diabetes Association (ADA). An update to the ADA’s “Standards of Medical Care in Diabetes” (Standards of Care [SOC]) appeared as a supplement to the January issue (1). The SOC is prepared by the Professional Practice Committee of the ADA and contains guidance on various aspects of care of those with or at risk for diabetes, together with summaries of published data supporting these statements. Because scientific information is accumulating faster than ever before, the ADA announced a new policy in the March 2018 issue (2). The yearly January supplement to Diabetes Care will continue as before, but the SOC will now be updated more frequently. The ADA now uses a web annotation tool to update and revise the online version throughout the year, whenever new evidence or regulatory changes merit immediate incorporation. Already in 2018 new information has been added regarding two medications recently approved by the U.S. Food and Drug Administration (semaglutide and ertugliflozin) and an update on the definitions of hypoglycemia. Changes of this kind will be communicated by the ADA through its print, online, and social media channels. Additional consensus statements and commentaries on new or controversial topics will continue to appear in Diabetes Care . Unlike the SOC, they are not official guidance statements but generally reflect the ADA’s thinking. For example, a joint statement by representatives of the ADA and the European Association for the Study of Diabetes …

The majority of youth with type 1 diabetes are above hemoglobin A1c (HbA1c) targets. Continuous glucose monitoring (CGM) has been shown to improve clinical outcomes, and use early in the course of diabetes has the potential to improve glycemic outcomes and improve quality of life. In our clinic, youth with new-onset type 1 diabetes were offered the opportunity to start on CGM (Dexcom G6) soon after diabetes diagnosis. Ongoing CGM coverage was subsequently applied for through the patient’s insurance. Following CGM initiation, youth had a 1-week follow-up with a nurse practitioner. Per clinic standard of care, youth were seen again at 1 month post-diagnosis and every 3 months thereafter. We prospectively collected data on HbA1c, continued CGM use, days of CGM wear, method of viewing CGM data, time in range (TIR), and time in hypoglycemia. Institutional review board approval was obtained for the prospective data collection. From July 2018 to April 2019, we approached 44 youth with newly diagnosed type 1 diabetes to initiate CGM. Forty-one youth (at onset: mean age 9.7 ± 4.1 years, 56% male, 90% with private insurance, 41% non-Hispanic white, HbA1c 12.2 ± 1.8% [110 mmol/mol]) were started on CGM at a mean of 9.0 ± 8.8 days post–diabetes diagnosis (Table 1). Three adolescent youth declined CGM, stating they did …

Effective diabetes problem solving requires identification of risk factors for inadequate mealtime self-management. Ecological momentary assessment was used to enhance identification of factors hypothesized to impact self-management. Adolescents with type 1 diabetes participated in a feasibility trial for a mobile app called MyDay. Meals, mealtime insulin, self-monitored blood glucose, and psychosocial and contextual data were obtained for 30 days. Using 1472 assessments, mixed-effects between-subjects analyses showed that social context, location, and mealtime were associated with missed self-monitored blood glucose. Stress, energy, mood, and fatigue were associated with missed insulin. Within-subjects analyses indicated that all factors were associated with both self-management tasks. Intraclass correlations showed within-subjects accounted for the majority of variance. The ecological momentary assessment method provided specific targets for improving self-management problem solving, phenotyping, or integration within just-in-time adaptive interventions.