Reductions In Diabetes Distress Research Articles

EMBARK: A Randomized, Controlled Trial Comparing Three Approaches to Reducing Diabetes Distress and Improving HbA1c in Adults With Type 1 Diabetes.

To compare the effectiveness of three interventions to reduce diabetes distress (DD) and improve HbA1c among adults with type 1 diabetes (T1D). Individuals with T1D (n = 276) with elevated DD (a score >2 on the total Type 1 Diabetes Distress Scale) and HbA1c (>7.5%) were recruited from multiple settings and randomly assigned to one of three virtual group-based programs: 1) Streamline, an educator-led education and diabetes self-management program; 2) TunedIn, a psychologist-led program focused exclusively on emotional-focused DD reduction; or 3) FixIt, an integration of Streamline and TunedIn. Assessments of the primary outcomes of DD and HbA1c occurred at baseline and at 3, 6, and 12 months. All three programs demonstrated substantive and sustained reductions in DD (Cohen's d = 0.58-1.14) and HbA1c (range, -0.4 to -0.72) at 12-month follow-up. TunedIn and FixIt participants reported significantly greater DD reductions compared with Streamline participants (P = 0.007). Streamline and TunedIn participants achieved significantly greater HbA1c reductions than did FixIt participants (P = 0.006). DD can be successfully reduced among individuals with T1D with elevated HbA1c using both the educational/behavioral and emotion-focused approaches included in the study. Although both approaches are associated with significant and clinically meaningful reductions in DD and HbA1c, TunedIn, the emotion-focused program, had the most consistent benefits across both DD and HbA1c. The study findings suggest the overall value of group-based, fully virtual, and time-limited emotion-focused strategies, like those used in TunedIn, for adults with T1D.

Efficacy of a Digital Diabetes Logbook for People With Type 1, Type 2, and Gestational Diabetes: Results From a Multicenter, Open-Label, Parallel-Group, Randomized Controlled Trial.

In a randomized controlled trial, the efficacy of a digital diabetes diary regarding a reduction of diabetes distress was evaluated. A randomized controlled trial with a 12-week follow-up was conducted in 41 study sites across Germany. Key eligibility criteria were a diagnosis of type 1, type 2, or gestational diabetes and regular self-monitoring of blood glucose. Participants were randomly assigned (2:1 ratio) to either use the digital diabetes logbook (mySugr PRO), or to the control group without app use. The primary outcome was the reduction in diabetes distress at the 12-week follow-up. All analyses were based on the intention-to-treat population with all randomized participants. The trial was registered at the German Register for Clinical Studies (DRKS00022923). Between February 11, 2021, and June 24, 2022, 424 participants (50% female, 50% male) were included, with 282 being randomized to the intervention group (66.5%) and 142 to the control group (33.5%). A total of 397 participants completed the trial (drop-out rate: 6.4%). The median reduction in diabetes distress was 2.41 (interquartile range [IQR]: -2.50 to 8.11) in the intervention group and 1.25 (IQR: -5.00 to 7.50) in the control group. The model-based adjusted between-group difference was significant (-2.20, IQR: -4.02 to -0.38, P = .0182) favoring the intervention group. There were 27 adverse events, 17 (6.0%) in the intervention group, and 10 (7.0%) in the control group. The efficacy of the digital diabetes logbook was demonstrated regarding improvements in mental health in people with type 1, type 2, and gestational diabetes.

Carbohydrate Counting vs. Fixed Meal Plan in Indian Children with Type 1 Diabetes Mellitus: A Randomized Controlled Trial.

To study the impact of carbohydrate counting vs. fixed-meal plan on glycemic control, quality of life (QoL) and diabetes-related emotional distress in children with Type 1 diabetes mellitus (T1DM). Children aged 6-18 y with T1DM of duration >1 y were eligible for the study if they were on multiple daily injections of insulin and regularly monitoring blood glucose. Those with celiac disease, hypothyroidism, any underlying chronic renal/liver/systemic disease or HbA1c >13% were excluded. Both groups received education on diabetes management and healthy diet. In the intervention arm, parents were taught to quantify carbohydrate content and modify insulin doses according to insulin-carbohydrate ratio. The control arm had dietary prescription according to recommended dietary allowance and food exchange list. Standard validated questionnaires were used to assess the QoL and emotional distress related to diabetes. One hundred twenty five patients (61 intervention, 64 controls) were enrolled and 91.8% and 84.3%, respectively, completed 6-mo follow-up. There was a reduction in HbA1c in both the groups, but was not statistically significant within or between groups {Intervention: 8.9 (1.4) to 8.6 (1.5) vs. control: 9.1 (1.6) to 8.8 (1.9), [95% CI 8.3-9.3 vs. 8.3-9.0, intention to treat (ITT), p= 0.63]}. There was a significant reduction in diabetes distress in the intervention group; DAWN Problem Areas in Diabetes Questionnaire (PAID) score with a median (interquartile range) of 21 (11-33) vs. control: 27 (20-40), (p=0.04). Patients in the carbohydrate-counting group demonstrated lower diabetes distress scores and less emotional burnout compared to fixed-meal plan over a 6 mo period though overall glycemic control was comparable between groups.

Explaining improvement in diabetes distress: a longitudinal analysis of the predictive relevance of resilience and acceptance in people with type 1 diabetes

AimsTo analyze if midterm improvement in diabetes distress can be explained by resilience, diabetes acceptance, and patient characteristics.MethodsN = 179 adults with type 1 diabetes were enrolled during their stay at a tertiary diabetes center (monocentric enrolment) and followed up over three months in a prospective, observational study (‘DIA-LINK1’). Improvement in diabetes distress was assessed as reduction in the Problem Areas in Diabetes Scale score from baseline to follow-up. Resilience (Resilience Scale-13), acceptance (Diabetes Acceptance Scale), and patient characteristics were analyzed as predictors of improvement in diabetes distress using hierarchical multiple regression.ResultsGreater reductions in diabetes distress were significantly explained by lower diabetes acceptance at baseline (β = −0.34, p < 0.01), while resilience, diabetes complications, and other person-related variables were not significantly related to changes in diabetes distress (all p > 0.05). When change in diabetes acceptance from baseline to follow-up was added to the model, improved diabetes distress was explained by increasing diabetes acceptance (β = 0.41, p < 0.01) and a shorter duration of diabetes (β = -0.18, p = 0.03), while baseline diabetes acceptance was no longer significantly associated (β = −0.14, p > 0.05).ConclusionsDiabetes acceptance is inversely related to diabetes distress, and increasing acceptance explained greater improvement in diabetes distress. These findings suggest that increasing diabetes acceptance may facilitate the reduction of diabetes distress. Treatment approaches targeting acceptance might be useful for the mental healthcare of people with type 1 diabetes and clinically elevated diabetes distress.

Significant reduction in diabetes distress and improvements in psychosocial outcomes: A pilot test of an intervention to reduce diabetes distress in adults with type 1 diabetes and moderate-to-severe diabetes distress (REDUCE).

To pilot-test an intervention, co-designed with people with type 1 diabetes (T1DM) and diabetes specialist nurses, to reduce diabetes distress (DD) in adults with T1DM and moderate-to-severe DD. A group-based programme to reduce DD in people with T1DM and moderate-to-severe DD (REDUCE) was pilot-tested in four groups with five bi-weekly two and a half-hour meetings facilitated by two trained diabetes specialist nurses. Data collection included baseline and post-intervention questionnaires measuring DD and psychosocial outcomes and semi-structured interviews with participants post-intervention (n = 18). Data were analysed using descriptive statistics and systematic text condensation. Twenty-five adults with T1DM participated in the study. The median age and diabetes duration of participants were 50 (IQR: 32;57.5) years and 26 (IQR: 18;45) years, respectively. Seventeen (68%) were women. The pilot study showed a significant reduction in DD (measured by Type 1 Diabetes Distress Scale) between baseline and post-intervention from 2.6 ± 0.7 to 1.9 ± 0.6 (mean ± SD) (p < 0.001). The largest reductions were seen on the subscales: powerlessness 1.2 ± 1.1, eating distress 0.9 ± 1.2 and fear of hypoglycaemia 0.8 ± 1.0 (mean ± SD). Significant improvements were also seen for quality of life, diabetes empowerment and emotion regulation. Qualitative data showed that REDUCE supported participants in verbalizing emotions and seeing worries in a more constructive perspective. Acknowledgement of negative diabetes experiences eased negative self-judgments. Sharing experiences among peers increased relatedness and reduced loneliness. Participation in REDUCE was associated with significant reduction in DD and significant increase in quality of life. Larger scale studies are planned to determine sustained effectiveness of REDUCE.

698-P: Interoperability as an Important Factor for Achieving the Full Potential of a Digital Diabetes Logbook

A randomized controlled trial (RCT) has demonstrated the efficacy of a digital diabetes logbook (mySugr) in reducing diabetes distress compared to a control group without such an app. In a sub-group analysis, we analyzed whether those who have paired their glucose meter (glucose values were directly imported into the app) benefit differently than those who manually entered their glucose values. A total of 282 people were randomized to the intervention group using the app for 3 months (2:1 randomization; age: 51.2±14.6 years; 13.1% type 1, 66.7% type 2, 20.2% gestational diabetes). The per protocol population within the intervention group consisted of 232 participants who completed the 3-month follow-up and have used the app on ≥10% of the study days. Analysis of covariance was conducted with diabetes distress at the 3-month follow-up at dependent variable and connected glucose meter (yes/no) as independent variable, controlled for diabetes distress at baseline. Diabetes distress was measured with the Problem Areas in Diabetes (PAID) questionnaire. Within the per protocol population, 134 participants of the intervention group (57.8%) have used a connected glucose meter. Participants with a connected meter had significantly less diabetes distress at follow-up compared to participants who manually entered their glucose values (16.9±1.05 vs. 20.5±1.2, p = 0.027). There was no significant difference in demographic characteristics between the two groups. Participants with a connected meter had significantly more meal logs (3.3±2.2 vs. 2.0±1.2, p = 0.01) on days they have used the app. Overall, the digital diabetes logbook was able to reduce diabetes distress over a 3-month period. This reduction in diabetes distress was more pronounced in participants who used an interoperable glucose meter that automatically transferred glucose data into the app. Interestingly, there seems to be an increased interaction with the app regarding logging of meals in participants with a connected meter. Disclosure B.Kulzer: Advisory Panel; Berlin-Chemie AG, Abbott Diabetes, Bayer Inc., Dexcom, Inc., Novo Nordisk, Insulet Corporation, embecta, Research Support; Sanofi, Roche Diabetes Care. D.Ehrmann: Advisory Panel; Roche Diabetes Care, mySugr, Dexcom, Inc., Speaker's Bureau; Berlin-Chemie AG, Dexcom, Inc. N.Hermanns: Advisory Panel; Insulet Corporation, Research Support; Sanofi-Aventis Deutschland GmbH, Roche Diagnostics, Becton, Dickinson and Company, Speaker's Bureau; Dexcom, Inc., Berlin-Chemie AG. I.Vesper: None. V.L.Schaefer: Employee; Roche Diabetes Care. S.Silbermann: Employee; Roche Diabetes Care. J.Kober: Employee; mySugr. K.Finke-groene: None. T.Roos: None. E.Bingol: Employee; Roche Diabetes Care. Funding Roche Diabetes Care GmbH (DC000097)

641-P: Diabetes Distress and Blood Glucose in the Function and Emotion in Everyday Life with Type 1 Diabetes (FEEL-T1D) Study—Which Comes First, the Chicken or the Egg?

Introduction: Diabetes Distress (DD) has been consistently linked with suboptimal blood glucose in T1D. However, prior studies have rarely used methods that can adequately evaluate the directionality of this relationship. This study paired ecological momentary assessment (EMA) and continuous glucose monitoring (CGM) to examine the relative strength of lagged effects of blood glucose (BG) on DD and vice versa. Methods: FEEL-T1D participants (N=182, 40±14 yrs, 54% women, 41% Latino, 29% White, 15% Black) wore blinded CGM for 10-14 days and completed 5-6 smartphone EMA surveys per day. Using multilevel cross-lagged panel modeling, we evaluated within-person lagged effects from momentary ratings of DD (scale: 0-100) to various BG metrics (BG average, Time in Range [TIR, 70-180 mg/dL], % time 181-250 mg/dL, % time &amp;gt; 250 mg/dL, % time 54-69 mg/dL, % time &amp;lt;54 mg/dL, and coefficient of variation [CV]) over the subsequent 3 hours and between 3 hours of BG metrics and subsequent DD ratings. Results: Unstandardized within-person parameter estimates and 95% confidence intervals for lagged effects of BG on subsequent DD ratings were significant for average BG (0.01; 0.01, 0.02), TIR (−0.01; −0.02, −0.004), % time 181-250 mg/dL (0.01; 0.001, 0.02), and % time &amp;gt; 250 mg/dL (0.02; 0.01, 0.04), but not for CV or % time in low BG; as expected, higher BG predicted subsequently higher DD. Lagged effects of DD ratings on subsequent 3-hour BG metrics were only significant for % time 54-69 mg/dL (−0.02; −0.04, −0.002); unexpectedly, DD was predictive of less % time with low BG. Conclusion: These novel findings reveal that the experience of DD is significantly influenced by preceding suboptimal BG levels, particularly high BG, even when individuals are blinded to their BG values. Results suggest that interventions that improve BG levels may reduce DD but do not support the hypothesis that reductions in DD will conversely lead to improvements in BG. Disclosure J.S.Gonzalez: Consultant; Virta Health Corp. P.Lee: None. S.Schneider: None. E.Pyatak: Research Support; Abbott Diabetes. R.Hernandez: None. D.Spruijt-metz: None. C.J.Hoogendoorn: None. G.Crespo-ramos: None. S.Agarwal: Advisory Panel; Medtronic, Consultant; Beta Bionics, Inc., Research Support; Abbott Diabetes, Dexcom, Inc. J.P.Crandall: Research Support; Abbott Diabetes. A.L.Peters: Advisory Panel; Abbott Diabetes, Medscape, Novo Nordisk, Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Research Support; Abbott Diabetes, Dexcom, Inc., Insulet Corporation, Stock/Shareholder; Omada Health, Inc., Livongo. L.T.Pham: None. Funding National Institutes of Health (R01DK121298, P30DK111022)

Reducing social diabetes distress with a conversational agent support system: a three-week technology feasibility evaluation.

People with diabetes mellitus not only have to deal with physical health problems, but also with the psycho-social challenges their chronic disease brings. Currently, technological tools that support the psycho-social context of a patient have received little attention. The objective of this work is to determine the feasibility and preliminary efficacy of an automated conversational agent to deliver, to people with diabetes, personalised psycho-education on dealing with (psycho-)social distress related to their chronic illness. In a double-blinded between-subject study, 156 crowd-workers with diabetes received a social help program intervention in three sessions over three weeks. They were randomly assigned to receive support from either an interactive conversational support agent () or a self-help text from the book "Diabetes burnout" as a control condition (). Participants completed the Diabetes Distress Scale (DDS) before and after the intervention, and after the intervention, the Client Satisfaction Questionnaire (CSQ-8), Feeling of Being Heard (FBH), and System Usability Scale (SUS). Results indicate that people using the conversational agent have a larger reduction in diabetes distress (, ) than the control group (, ) and this difference is statistically significant (, ). A hypothesised mediation effect of "attitude to the social help program" was not observed. An automated conversational agent can deliver personalised psycho-education on dealing with (psycho-)social distress to people with diabetes and reduce diabetes distress more than a self-help book. This study has been preregistered with the Open Science Foundation (osf.io/yb6vg) and has been accepted by the Human Research Ethics Committee - Delft University of Technology under application number 1130. The data and analysis script are available: https://surfdrive.surf.nl/files/index.php/s/4xSEHCrAu0HsJ4P.

Reduction in Diabetes Distress and Improvement in Sleep Quality correlating with Better Glycemic Control Within 90 Days on Fitterfly Diabetes Program

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Abstract 13360: Impact of Goal Setting in a Digital Health Coaching Program for Participants With Type 2 Diabetes

Introduction: Cardiovascular disease remains one of the most common causes of death in people with diabetes. We retrospectively explored how a digital health coaching (DHC) program with goal-driven engagement for individuals with type 2 diabetes mellitus (T2DM) influenced outcomes at 3 months. Methods: This retrospective analysis included de-identified results from overweight/obese individuals who participated in a 3-month DHC program tailored for people with diabetes, whose main goal was medication adherence. Participants were referred through employer programs, payor programs, or physicians. Changes in biometric variables and diabetes-related quality of life were assessed at 3 months. Results: Over one year (January 1, 2021, to December 31, 2021), 182 participants engaged and completed the DHC program. Participants were predominantly women (79%), with an average age of 50, and racially/ethnically diverse (51% white, 49% non-white). Of this cohort, 24% lived in rural areas, and 44 participants had low medication adherence scores at baseline. At 3 months, there were significant decreases in diabetes distress score (27.14% reduction in diabetes distress; 2.91 to 2.12, p&lt;0.001) and HbA1c (6.44% improvement; 7.61 to 7.12, p-0.0017). In addition, members with low medication adherence scores had a larger improvement than all members, with the main cohort improving the medication adherence score by 5.4% (10.34 to 10.90, p=0.058) and the low medication adherence group improving by 18.07% (7.55 to 8.91, p=0.007). Members with low medication adherence scores at baseline had significantly larger improvement than all other members, with 12.67% more improvement than members overall. Conclusions: Participants in the program showed improved outcomes for HbA1c and diabetes-related quality of life measures at 3 months. Engaging patients in DHC can help improve outcomes in populations at-risk of low adherence.

601-P: Participation in Diabefly Program and Significant Reduction in Diabetes Distress and Improvement in Motivation and Attitude towards Changing Health among People with Type 2 Diabetes

Introduction: Diabetes distress is a unique, often hidden, emotional burden and worry that an individual experiences while managing diabetes. Enhanced motivation and willingness are important components of one’s ability to manage the increasing demands of diabetes. Aim of this study is to analyse the effectiveness of digital therapeutics programs in providing evidence-based care that can help in better management of diabetes through long-term behaviour change. Methods: This study was conducted with 100 participants diagnosed with type 2 DM across India. They were enrolled in the Diabefly® digital therapeutics program for 90 days. Highly customized virtual stress management and behaviour therapy sessions were given to each participant along with nutrition and fitness sessions. Various digital interventions were shared at regular intervals. Initial and final assessment was done using Diabetes Distress Scale and Motivation and Attitude towards Changing Health. t - test was used to analyse the data. Results: Motivation levels among participants improved significantly by 9.39% from a baseline score of 33.70±4.24 to 37.42±4.50 (p=0.001) . Distress levels among participants decreased significantly by 24.21% from a baseline score of 1.90±0.77 to 1.35±0.45 (p=0.001) . Participants from joint families have higher interpersonal distress as compared to nuclear families (p=0.008) . Participants having diabetes for more than 5 years have higher physician distress (p=0.001) and interpersonal distress (p=0.005) as compared to newly diagnosed ones. Participants who are on insulin along with medications have higher physician distress (p=0.031) and interpersonal distress (p=0.020) in comparison to those who are just on medication or not on any medication. Conclusion: Remote behavioural interventions as part of a comprehensive 90 days Diabefly® program can be very effective in managing diabetes adequately. Disclosure N.Verma: Employee; Fitterfly HealthTech Private Limited. K.Samudra: None. T.Lathia: Advisory Panel; Abbott, AstraZeneca, Biocon, Boehringer Ingelheim International GmbH, Novartis Pharmaceuticals Corporation, Novo Nordisk, Sanofi. P.Vasan: Employee; Fitterfly Health Tech Pvt Ltd. N.Gupta: Employee; Fitterfly HealthTech Pvt Ltd. R.Verma: Employee; Fitterfly Healthtech Pvt Ltd, Wellthy Therapeutics Pvt Ltd. S.Kalra: Speaker's Bureau; Boehringer Ingelheim International GmbH, Novo Nordisk A/S, Sanofi. M.V.Padsalge: None. V.Methil: None. A.K.Singal: Other Relationship; Fitterfly Healthtech Pvt Ltd.

Diabetes distress, emotional regulation, HbA1c in people with diabetes and A controlled pilot study of an emotion-focused behavioral therapy intervention in adults with type 2 diabetes

AimOne potential barrier for people with diabetes to reach glycemic goals is diabetes distress. Accumulating evidence suggests diabetes distress may be linked to individuals’ emotion regulation capacities. Thus, we conducted two studies to elucidate a model for how emotion regulation impacts diabetes distress and A1c levels and determine preliminary effect size estimates for an intervention targeting poor emotion regulation on glycemic control. MethodsStudy I used structural equation modeling to assess the cross-sectional relationships between these variables in a sample of 216 individuals with Type 1 and Type 2 diabetes. Study II built on findings from Study I that highlighted the role of emotion regulation capacities in diabetes distress and A1c by conducting a pilot study of an emotion-focused behavioral intervention compared to treatment as usual in a sample of individuals with Type 2 diabetes. ResultsStudy I examined two potential explanatory models with one of the models (Model II) showing a more comprehensive view of the data revealing a total effect of poor emotional regulation of 42% of all effects on A1c levels. Study II tested an emotion-focused behavioral intervention in patients with Type 2 diabetes compared to treatment as usual and found medium sized reductions in A1c levels and smaller reductions in diabetes distress that correlated with changes in emotion regulation. ConclusionsThese studies suggest that, in people with diabetes, elevated A1c levels and diabetes distress are linked with poor emotion regulation. While the effect sizes from Study 2 are preliminary, an emotion-focused behavioral intervention may reduce both A1c and diabetes distress levels, through improvements in emotion regulation. Overall, these data suggest that targeting difficulties in emotion regulation may hold promise for maximizing improvement in diabetes distress and A1c in individuals with diabetes.

Using path analysis to model the process of change in HbA1c among African Americans and Latinos in a community health worker diabetes intervention

ObjectiveTo examine which components of a culturally tailored community health worker (CHW) intervention improved glycemic control and intermediate outcomes among Latina/o and African American participants with diabetes. MethodsThe sample included 326 African American and Latina/o adults with type 2 diabetes in Detroit, MI. CHWs provided interactive group diabetes self-management classes and home visits, and accompanied clients to a clinic visit during the 6-month intervention period. We used path analysis to model the processes by which each intervention component affected change in diabetes self-efficacy, diabetes-related distress, knowledge of diabetes management, and HbA1c. ResultsThe group-based healthy lifestyle component was significantly associated with improved knowledge. The group-based self-management section was significantly associated with reduced diabetes-related distress. Intervention class attendance was positively associated with self-efficacy. Diabetes self-management mediated the reductions in HbA1c associated with reductions in diabetes distress. ConclusionsPath analysis allowed each potential pathway of change in the intervention to be simultaneously analyzed to identify which aspects of the CHW intervention contributed to changes in diabetes-related behaviors and outcomes among African Americans and Latinas/os.Practice Implications: Findings reinforce the importance of interactive group sessions in efforts to improve diabetes management and outcomes among Latina/o and African American adults with diabetes.

ONBOARD: A Feasibility Study of a Telehealth-Based Continuous Glucose Monitoring Adoption Intervention for Adults with Type 1 Diabetes

Background: Continuous glucose monitoring (CGM) can improve glycemic control for adults with type 1 diabetes (T1D) but certain barriers interfere with consistent use including cost, data overload, alarm fatigue, physical discomfort, and unwanted social attention. This pilot study aimed to examine feasibility and acceptability of a behavioral intervention, ONBOARD (Overcoming Barriers and Obstacles to Adopting Diabetes Devices) to support adults with T1D in optimizing CGM use. Methods: Adults (18-50 years) with T1D in their first year of CGM use were invited to participate in a tailored, multicomponent telehealth-based intervention delivered over four 60-min sessions every 2-3 weeks. Participants completed surveys (demographics; diabetes distress, Diabetes Distress Scale for adults with type 1 diabetes; satisfaction with program) and provided CGM data at baseline and postintervention (3 months). Data were analyzed using paired t-tests and Wilcoxon signed-rank tests. Results: Twenty-two participants (age = 30.95 ± 8.32 years; 59% women; 91% non-Hispanic; 86% White, 5% Black, 9% other; 73% pump users) completed the study. ONBOARD demonstrated acceptability and a high rate of retention. Moderate effect sizes were found for reductions in diabetes distress (P = 0.01, r = -0.37) and increases in daytime spent in target range (70-180 mg/dL: P = 0.03, r = -0.35). There were no significant increases in hypoglycemia. Conclusions: Findings show preliminary evidence of feasibility, acceptability, and efficacy of ONBOARD for supporting adults with T1D in optimizing CGM use while alleviating diabetes distress. Further research is needed to examine ONBOARD in a larger sample over a longer period.

Reductions in Management Distress Following a Randomized Distress Intervention Are Associated With Improved Diabetes Behavioral and Glycemic Outcomes Over Time.

OBJECTIVETo explore associations between reductions in diabetes distress (DD) and improvements in glycemic outcomes among adults with type 1 diabetes (T1D) in the context of a DD randomized clinical trial.RESEARCH DESIGN AND METHODSAdults with T1D (N = 301) participated in a two-arm trial aimed at reducing DD (DD-focused OnTrack group vs. education-oriented KnowIt group). Mean age was 45.1 years; mean baseline HbA1c was 8.8% (73 mmol/mol). Individuals were assessed at baseline and 9 months later on DD, self-care, HbA1c, and frequency of hypoglycemia. Structural equation models evaluated hypothesized pathways among changes in DD, self-care, and glycemic outcomes in the total sample and by intervention group.RESULTSReductions in DD were significantly and independently associated with better self-care, including fewer missed insulin boluses, more frequent insulin adjustment, improved problem-solving skills, more blood glucose monitoring, and greater adoption of continuous glucose monitoring (all P < 0.05). In turn, better self-care was linked with better glycemic outcomes, including fewer episodes of hypoglycemia and improved HbA1c over time. Fit indices indicated good fit of the model to the data (confirmatory fit index = 0.94, root mean square error of approximation = 0.05), with stronger and more meaningful associations for OnTrack than for KnowIt.CONCLUSIONSIn the context of an intervention to reduce DD for adults with T1D, results indicate that reductions in DD do not affect glycemic outcomes directly but through improvements in self-care behavior. Findings support the importance of integrating disease management with DD interventions to maximize improvements in glycemic outcomes.

Alleviating diabetes distress and improving diabetes self-management through health coaching in a primary care setting

Considering the rising global burden of diabetes and its complications, effective interventions for addressing barriers to diabetes self-management are needed. Diabetes distress, a psychological barrier to diabetes self-management, has become...

Change in Hemoglobin A1c and Quality of Life with Real-Time Continuous Glucose Monitoring Use by People with Insulin-Treated Diabetes in the Landmark Study.

Background: Initiating continuous glucose monitoring (CGM) can affect hemoglobin A1c (HbA1c) levels and patients' relationship with their diabetes. We used real-world HbA1c data to quantify short-term changes in glycemia and validated psychosocial questionnaires to assess changes in quality-of-life indicators in people during their first few months of CGM use.Methods: Eligibility was assessed during calls to Dexcom sales regarding its G6 CGM System. Eligibility criteria included ages 25–65 years, type 1 (T1D) or type 2 diabetes (T2D) on intensive insulin therapy (IIT), and no prior CGM use. Participants used a web-based portal to complete the 17-item Diabetes Distress Scale (DDS) and the 14-item Hypoglycemia Attitudes and Behavior Scale (HABS); provided validated HbA1c measurements; and shared their CGM data pre- and 3–5 months post-CGM initiation. Satisfaction and ease of use with the G6 System were also assessed.Results: Data were available from 248 patients (182 with T1D, 66 with T2D; 57% male, 88% non-Hispanic white). Mean (standard deviation) HbA1c fell significantly from 8.2% (1.9%) at baseline to 7.1% (1.1%) at the end of the study (P < 0.001); more than half (54.4%) of those with initial HbA1c values >7% experienced absolute HbA1c reductions of >1%. Significant reductions in diabetes distress (DDS) and hypoglycemic concerns (HABS) were observed (P < 0.001). Most (93%) participants were satisfied or very satisfied with the G6 System and 73% found it very easy to use.Conclusions: The first 3 months of CGM use was correlated with improvements in psychosocial outcomes and improved HbA1c levels for people with T1D or T2D who use IIT.

Mobile-Enhanced Peer Support for African Americans with Type 2 Diabetes: a Randomized Controlled Trial.

Peer support has been shown to improve diabetes self-management and control, but no standard exists to link peer support interventions to clinical care. To compare a community-based diabetes self-management education (DSME) plus mobile health (mHealth)-enhanced peer support intervention to community-based diabetes self-management education (DSME) alone for African American adults with poorly controlled type 2 diabetes. A randomized controlled trial. African American adults, age> 19years, receiving care within a safety-net healthcare system in Jefferson County, Alabama, with a diagnosis of type 2 diabetes and a hemoglobin A1c (A1C) ≥ 7.5%. Participants in the intervention group received community-based diabetes self-management education (DSME) plus 6months of mHealth-enhanced peer support, including 12 weekly phone calls, then 3 monthly calls from community health workers, who used a novel web application to communicate with participants' healthcare teams. In the control group, participants received community-based DSME alone. The primary outcome was A1C; secondary outcomes included diabetes distress, depressive symptoms, self-efficacy or confidence in their ability to manage diabetes, and social support. We used mixed models repeated measures analyses to assess for between-arm differences and baseline to follow-up changes. Of 120 participants randomized, 97 completed the study. Participants in intervention and controlgroups experienced clinically meaningful reduction in A1C, 10.1 (SD 1.7) to 9.6 (SD 1.9) and 9.8 (SD 1.7) to 9.1 (SD 1.9) respectively, p= 0.004. Participants in the intervention group experienced a significantly larger reduction in diabetes distress compared to the control, 2.7 (SD 1.2) to 2.1 (1.0) versus 2.6 (SD 1.1) to 2.3 (SD 1.0) p = 0.041. Community-based DSME with and without peer support led to improved glycemic control. Peer support linked to clinical care led to a larger reduction in diabetes distress, which has important implications for the overall wellbeing of adults with type 2 diabetes.

Effect of Flash Glucose Monitoring on Glycemic Control, Hypoglycemia, Diabetes-Related Distress, and Resource Utilization in the Association of British Clinical Diabetologists (ABCD) Nationwide Audit.

OBJECTIVEThe FreeStyle Libre (FSL) flash glucose-monitoring device was made available on the U.K. National Health Service (NHS) drug tariff in 2017. This study aims to explore the U.K. real-world experience of FSL and the impact on glycemic control, hypoglycemia, diabetes-related distress, and hospital admissions.RESEARCH DESIGN AND METHODSClinicians from 102 NHS hospitals in the U.K. submitted FSL user data, collected during routine clinical care, to a secure web-based tool held within the NHS N3 network. The t and Mann-Whitney U tests were used to compare the baseline and follow-up HbA1c and other baseline demographic characteristics. Linear regression analysis was used to identify predictors of change in HbA1c following the use of FSL. Within-person variations of HbA1c were calculated using .RESULTSData were available for 10,370 FSL users (97% with type 1 diabetes), age 38.0 (±18.8) years, 51% female, diabetes duration 16.0 (±49.9) years, and BMI of 25.2 (±16.5) kg/m2 (mean [±SD]). FSL users demonstrated a −5.2 mmol/mol change in HbA1c, reducing from 67.5 (±20.9) mmol/mol (8.3%) at baseline to 62.3 (±18.5) mmol/mol (7.8%) after 7.5 (interquartile range 3.4–7.8) months of follow-up (n = 3,182) (P < 0.0001). HbA1c reduction was greater in those with initial HbA1c ≥69.5 mmol/mol (>8.5%), reducing from 85.5 (±16.1) mmol/mol (10%) to 73.1 (±15.8) mmol/mol (8.8%) (P < 0.0001). The baseline Gold score (score for hypoglycemic unawareness) was 2.7 (±1.8) and reduced to 2.4 (±1.7) (P < 0.0001) at follow-up. A total of 53% of those with a Gold score of ≥4 at baseline had a score <4 at follow-up. FSL use was also associated with a reduction in diabetes distress (P < 0.0001). FSL use was associated with a significant reduction in paramedic callouts and hospital admissions due to hypoglycemia and hyperglycemia/diabetic ketoacidosis.CONCLUSIONSWe show that the use of FSL was associated with significantly improved glycemic control and hypoglycemia awareness and a reduction in hospital admissions.

873-P: Flash Glucose Monitoring: Effect on Glycaemic Control, Hypoglycaemia, Diabetes-Related Distress, and Resource Utilization: A Nationwide Study

Aim: The FreeStyle Libre (FSL) flash glucose monitoring device was made available on the UK National Health Services (NHS) drug tariff in 2017. This study aims to explore the UK real-world experience of FSL and the impact on glycaemic control, hypoglycaemia, diabetes-related distress and hospital admissions. Methods: Clinicians from 102 National Health Service hospitals in the United Kingdom submitted FSL user data, collected during routine clinical care, to a secure web-based tool. T-tests and Mann-Whitney-U tests were used to compare the baseline and follow-up HbA1c and other baseline demographic characteristics. Linear regression analysis was used to identify predictors of change in HbA1c following the use of FSL. Within-person variations of HbA1c calculated adj-HbA1c-SD=SD/sq. Root [n/(n−1)]. Results: Data were available for 10,370 (97% with type 1 diabetes) FSL users; age 38 (±18.7) years, 54% female, diabetes duration 16 (±49) years, and BMI of 25.2 (±16.5) kg/m2. The baseline HbA1c was 69.8 (±18.2) (8.5%), and after a mean follow-up of 7.6 (±23)months (n=3182) HbA1c reduced to 62.3 (±18.5) (7.9%) mmol/l (P&amp;lt;0.0001)). HbA1c reduction was greater in those with initial HbA1c ≥69.5 (&amp;gt;8.5%) mmol/mol, HbA1c reduced from 85.5mmol/mol (±16.07) (10%) to 73.1 mmol/mol (±15.8) (8.8%)) (P&amp;lt;0.0001). The baseline Gold score (score for hypoglycaemic unawareness) was 2.7 (±1.8) and reduced to 2.4 (±1.7) (P&amp;lt;0.0001) at follow-up. 53% of those with a Gold score of ≥4 at baseline, regained hypoglycaemic awareness at follow-up. FSL use was also associated with a reduction in diabetes distress (P&amp;lt;0.0001). Use of FSL was associated with significantly reduced paramedic callouts and hospital admissions due to hypoglycaemia and to hyperglycaemia/Diabetic Ketoacidosis (DKA). Conclusion: We show that the use of FSL was associated with significantly improved glycaemic control and hypoglycaemia awareness, and a reduction in hospital admissions. Disclosure H. Deshmukh: None. E.G. Wilmot: Advisory Panel; Self; Abbott, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic. Speaker’s Bureau; Self; Abbott, Eli Lilly and Company, Insulet Corporation, Novo Nordisk Inc., Sanofi. J. Patmore: None. C. Walton: Speaker’s Bureau; Spouse/Partner; Celgene, LEO Pharma, Novartis Pharmaceuticals Corporation. R. Herring: None. R.E. Ryder: Consultant; Self; GI Dynamics Inc. Other Relationship; Self; Novo Nordisk A/S. T. Sathyapalan: Research Support; Self; Amgen, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Novo Nordisk A/S. Other Relationship; Self; Ipsen Biopharmaceuticals.