scholarly journals From Wary Wearers to d-Embracers: Personas of Readiness to Use Diabetes Devices

2018 ◽  
Vol 12 (6) ◽  
pp. 1101-1107 ◽  
Author(s):  
Molly L. Tanenbaum ◽  
Rebecca N. Adams ◽  
Esti Iturralde ◽  
Sarah J. Hanes ◽  
Regan C. Barley ◽  
...  
Keyword(s):  
Glucose Monitoring ◽  
Diabetes Duration ◽  
Diabetes Distress ◽  
Psychosocial Variables ◽  
Psychosocial Needs ◽  
Chi Square ◽  
High Distress ◽  
Technology Attitudes ◽  
Readiness To Adopt ◽  
Device Use

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.

scholarly journals Using Cluster Analysis to Understand Clinician Readiness to Promote Continuous Glucose Monitoring Adoption

2018 ◽  
Vol 12 (6) ◽  
pp. 1108-1115 ◽  
Author(s):  
Molly L. Tanenbaum ◽  
Rebecca N. Adams ◽  
Monica S. Lanning ◽  
Sarah J. Hanes ◽  
Bianca I. Agustin ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Diabetes Care ◽  
Glucose Monitoring ◽  
Patient Characteristics ◽  
Care Providers ◽  
Additional Time ◽  
Chi Square ◽  
Technology Attitudes ◽  
Descriptive Names ◽  
Technology Advances

Background: Many people with type 1 diabetes (T1D) report barriers to using continuous glucose monitoring (CGM). Diabetes care providers may have their own barriers to promoting CGM uptake. The goal of this study was to develop clinician “personas” with regard to readiness to promote CGM uptake. Methods: Diabetes care providers who treat people with T1D (N = 209) completed a survey on perceived patient barriers to device uptake, technology attitudes, and characteristics and barriers specific to their clinical practice. K-means cluster analyses grouped the sample by CGM barriers and attitudes. ANOVAs and chi-square tests assessed group differences on provider and patient characteristics. The authors assigned descriptive names for each persona. Results: Analyses yielded three clinician personas regarding readiness to promote CGM uptake. Ready clinicians (20% of sample; 24% physicians, 38% certified diabetes educators/CDEs) had positive technology attitudes, had clinic time to work with patients using CGM, and found it easy to keep up with technology advances. In comparison, Cautious clinicians (41% of sample; 17% physicians, 53% CDEs) perceived that their patients had many barriers to adopting CGM and had less time than the Ready group to work with patients using CGM data. Not Yet Ready clinicians (40% of sample; 9% physicians; 79% CDEs) had negative technology attitudes and the least clinic time to work with CGM data. They found it difficult to keep up with technology advances. Conclusion: Some diabetes clinicians may benefit from tailored interventions and additional time and resources to empower them to help facilitate increased uptake of CGM technology.

scholarly journals Investigating the Association Between Diabetes Distress and Self-Management Behaviors

2018 ◽  
Vol 12 (6) ◽  
pp. 1116-1124 ◽  
Author(s):  
Aneesah Khan ◽  
Pratik Choudhary
Keyword(s):  
Glycemic Control ◽  
Glucose Monitoring ◽  
Self Management ◽  
Diabetes Distress ◽  
Self Monitoring ◽  
High Distress ◽  
Future Work ◽  
Distress Scale ◽  
The Impact ◽  
Management Behaviors

Background: Diabetes distress has been linked with suboptimal glycemic control in patients with type 1 diabetes. We evaluated the effect of diabetes distress on self-management behaviors in patients using insulin pumps. Methods: We analyzed the impact of diabetes distress on self-management behaviors using pump downloads from 129 adults treated with continuous subcutaneous insulin infusion (CSII) at a single hospital clinic. Exclusion criteria were CSII treatment <6 months, pregnancy, hemoglobinopathy, and continuous glucose monitoring/sensor use. People were categorized into three groups based on the Diabetes Distress Scale-2 (DDS-2) score: < 2.5, 2.5-3.9, > 4. Results: Participants had a mean age of 45.2 ± 19.0 years; duration of diabetes 26.6 ± 16.2 years; duration of CSII 6.0 ± 3.5 years; HbA1c 8.0 ± 1.2%; and DDS-2 score 2.7 ± 1.3. Self-monitoring blood glucose (SMBG) frequency and bolus wizard usage was similar between groups. Patients with higher distress had higher HbA1c (7.7 ± 0.9 vs. 8.0 ± 0.9 vs. 8.7 ± 1.8; P = 0.004), lower frequency of set changes (4.7 ± 1.3vs. 4.8 ± 1.9 vs. 3.8 ± 1.1; P = .025), a greater number of appointments booked (5.8 ± 4.4 vs. 8.6 ± 4.8 vs. 8.1 ± 6.9; P = .021), and a greater number of appointments missed (1.9 ± 1.3 vs. 2.5 ± 1.5 vs. 3.8 ± 4.1; P = .004). Conclusions: Although in some patients, high distress may be caused by reduced self-management, in our highly trained, pump-using patients, high distress was associated with suboptimal biomedical outcomes despite appropriate self-management behaviors. Future work should further explore the relationships between diabetes distress, self-management, and glycemic control.

scholarly journals Diabetes related distress is high in inpatients with diabetes

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Nadine Kuniss ◽  
Guido Kramer ◽  
Ulrich A. Müller ◽  
Gunter Wolf ◽  
Christof Kloos
Keyword(s):  
Metabolic Diseases ◽  
Severe Hypoglycaemia ◽  
Glucose Monitoring ◽  
Cross Sectional Study ◽  
Diabetes Type ◽  
Diabetes Duration ◽  
Cross Sectional ◽  
Patients With Diabetes ◽  
High Distress ◽  
Design And Methods

Abstract Objective The aim of the present study was to assess diabetes-related distress in inpatients and its association with metabolic control in people with diabetes type 1 (DM1) and type 2 (DM2). Research design and methods In a cross-sectional study, 107 inpatients with DM1 (age 45.9 years, diabetes duration 18.7 years, HbA1c 8.4%/67.8 mmol/mol) and 109 with DM2 (age 62.0 years, diabetes duration 16.2 years, HbA1c 8.9%/74.3 mmol/mol) from a University department for endocrinology and metabolic diseases (Germany) were included over 2 years. Diabetes-related distress was assessed with the PAID questionnaire (range 0–100, higher scores imply higher diabetes-related distress, cut-off ≥ 40). The PAID questionnaire was completed by 214 of 216 participants. Results Fifty-one of 214 individuals (23.8%) showed high distress (PAID score ≥ 40). The mean PAID score was 28.1 ± 17.5 in all participants with no difference between DM1 and DM2 (28.1 ± 17.4 vs. 26.2 ± 16.9, p = 0.532). Individuals with DM2 on insulin scored higher than patients without insulin (27.8 ± 17.6 vs. 18.7 ± 8.5, p = 0.004). Additionally, people with DM1 treated with a system for continuous glucose monitoring (n = 50, 33.1 ± 18.8) scored higher than participants without such system (n = 32, 20.6 ± 13.3, p = 0.001). HbA1c was not correlated with the PAID score in both, DM1 (r = 0.040, p = 0.684) and DM2 (r = − 0.024, p = 0.804). Participants with DM2 and severe hypoglycaemia/last 12 months scored higher than people without (PAID score 43.0 ± 20.4 vs. 25.1 ± 16.5, p = 0.026). Frequency of non-severe hypoglycaemia was not associated with the PAID score in DM1 and DM2. Conclusions Patients with diabetes treated in hospital for problems with diabetes suffer frequently from diabetes-related distress (~ 24%) regardless of diabetes type.

scholarly journals CGM Benefits and Burdens: Two Brief Measures of Continuous Glucose Monitoring

2019 ◽  
Vol 13 (6) ◽  
pp. 1135-1141 ◽  
Author(s):  
Laurel H. Messer ◽  
Paul F. Cook ◽  
Molly L. Tanenbaum ◽  
Sarah Hanes ◽  
Kimberly A. Driscoll ◽  
...  
Keyword(s):  
Self Efficacy ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Diabetes Distress ◽  
Internal Reliability ◽  
Confirmatory Factor Analyses ◽  
Targeted Interventions ◽  
Positive Attitudes ◽  
Technology Attitudes ◽  
Continuous Glucose Monitors

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.

335-OR: Flash Sensor-Based Glucose Monitoring Accompanied by Structured Education Is More Effective in Reducing HbA1c and Diabetes Distress

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 335-OR
Author(s):  
BERNHARD KULZER ◽  
LILLI PRIESTERROTH ◽  
NORBERT HERMANNS ◽  
THOMAS HAAK ◽  
DOMINIC EHRMANN
Keyword(s):  
Glucose Monitoring ◽  
Diabetes Distress ◽  
Structured Education

Relationship between oxidative stress and blood glucose fluctuations evaluated with daily glucose monitoring in children with type 1 diabetes mellitus

2016 ◽  
Vol 29 (4) ◽  
Author(s):  
Ayça Altıncık ◽  
Birsen Tuğlu ◽  
Korcan Demir ◽  
Gönül Çatlı ◽  
Ayhan Abacı ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Glucose Monitoring ◽  
Insulin Requirement ◽  
Diabetes Duration ◽  
Oxidative Stress Marker ◽  
Entire Group ◽  
Anthropometric Data ◽  
Glucose Fluctuations ◽  
The Relationship

AbstractThe aim of this study is to determine the relationship between oxidative stress marker (8-iso-prostaglandine FThirty-one children and adolescents with T1DM (median age 12.2 years) and healthy subjects (median age 11.7 years) were enrolled into the study. Anthropometric data were recorded for the entire group before the study. In addition, diabetes duration, insulin requirement, lipid values, microalbuminuria, HbAMedian diabetes duration was 5 years, hemoglobin AThis study showed that, 8-iso-prostoglandine F

scholarly journals SELF-GLUCOSE MONITORING AND HYPOGLYCEMIA RISK IN OLDER RURAL VETERANS WITH TYPE 2 DIABETES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S263-S263
Author(s):  
Willy Marcos Valencia ◽  
Kaicheng Wang ◽  
Kiranmayee Muralidhar ◽  
Stuti Dang
Keyword(s):  
Primary Care ◽  
Glucose Monitoring ◽  
Multivariate Logistic Regression Model ◽  
High Risk Population ◽  
Diabetic Patients ◽  
Chi Square ◽  
Self Monitoring ◽  
Frequent Monitoring ◽  
Primary Care Teams

Abstract Hypoglycemia evaluation is expected in every encounter with diabetic patients. However, self-monitoring and self-management may not be complete at home, and limited by geriatric syndromes. Furthermore, hypoglycemia risk increases with age, and rurality may limit access to frequent monitoring. We identified 112 rural veterans with high hypoglycemia risk, using the local medication database (sulfonylureas and insulin), combined with age and glycated hemoglobin (HbA1c). Statistical analyses were conduct using SAS 9.4 (Cary, NC). We used Chi-square, Fisher’s, One-way ANOVA for baseline variables, and a multivariate logistic regression model to assess the association of hypoglycemia and risk factors, including age, HbA1c%, self-monitoring, and knowledge. Hypoglycemia was reported in 30.4% of cases, of whom the majority were younger than those not reporting hypoglycemia (72.0±4.3 vs 75.0±6.5 years, p=.015). Baseline HbA1c% was higher in cases with hypoglycemia compared to those without (7.7±1.6% versus 7.3±1.2%, not statistically significant). There were no significant differences between pharmacologic regimens, self-monitoring, and general knowledge. Veterans who knew hypoglycemia symptoms were 6 times more likely to reported hypoglycemia, compared with veterans who did not know any symptoms. We contacted primary care teams (PCT) for whom medications were adjusted. Hypoglycemia risk is high in the older population, and telemedicine programs can support primary care teams to improve management of their patients. Poor symptom knowledge needs to be addressed, while considering special attention for hypoglycemia unawareness in the oldest age group. We are implementing a project using continuous glucose monitoring in this high-risk population.

scholarly journals Spousal Influence on Diabetes Self-care: Moderating Effects of Distress and Relationship Quality on Glycemic Control

2020 ◽  
Author(s):  
Emily C Soriano ◽  
James M Lenhard ◽  
Jeffrey S Gonzalez ◽  
Howard Tennen ◽  
Sy-Miin Chow ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Glycemic Control ◽  
Relationship Quality ◽  
Self Care ◽  
Glucose Variability ◽  
Diabetes Distress ◽  
Sample Mean ◽  
Spousal Influence ◽  
High Distress

Abstract Background Spouses often attempt to influence patients' diabetes self-care. Spousal influence has been linked to beneficial health outcomes in some studies, but to negative outcomes in others. Purpose We aimed to clarify the conditions under which spousal influence impedes glycemic control in patients with type 2 diabetes. Spousal influence was hypothesized to associate with poorer glycemic control among patients with high diabetes distress and low relationship quality. Methods Patients with type 2 diabetes and their spouses (N = 63 couples) completed self-report measures before patients initiated a 7-day period of continuous glucose monitoring. Mean glucose level and coefficient of variation (CV) were regressed on spousal influence, diabetes distress, relationship quality, and their two- and three-way interactions. Results The three-way interaction significantly predicted glucose variability, but not mean level. Results revealed a cross-over interaction between spousal influence and diabetes distress at high (but not low) levels of relationship quality, such that spousal influence was associated with less variability among patients with low distress, but more among those with high distress. Among patients with high distress and low relationship quality, a 1 SD increase in spousal influence predicted a difference roughly equivalent to the difference between the sample mean CV and a CV in the unstable glycemia range. Conclusions This was the first study to examine moderators of the link between spousal influence and glycemic control in diabetes. A large effect was found for glucose variability, but not mean levels. These novel results highlight the importance of intimate relationships in diabetes management.

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