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      Home Telemedicine (CoYoT1 Clinic): A Novel Approach to Improve Psychosocial Outcomes in Young Adults With Diabetes

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          To assess the impact of a home telemedicine clinic model (CoYoT1 Clinic) on psychosocial and behavioral outcomes designed for young adults (YAs) with type 1 diabetes (T1D).


          YAs self-selected to participate in the CoYoT1 Clinic or serve as a usual care control. CoYoT1 Clinic visits consisted of an individual appointment with a provider and a group appointment with other YAs with T1D using home telemedicine. Psychosocial and behavioral functioning was assessed by 4 measures: Diabetes Distress Scale, Self-Efficacy for Diabetes Scale, Self-Management of Type 1 Diabetes in Adolescence Scale, and Center for Epidemiologic Studies Depression Scale.


          Forty-two patients participated in the CoYoT1 Clinic and 39 patients served as controls. CoYoT1 participants reported lower levels of distress ( P = .03), increased diabetes self-efficacy ( P = .01), and improved ability to communicate with others about diabetes ( P = .04) over the study period compared to controls. YA males in the control group reported increases in depressive symptoms ( P = .03) during the study period, but CoYoT1 participants showed no changes.


          Group home telemedicine for YAs with T1D positively affects diabetes distress, self-efficacy, and diabetes-specific communication. These positive findings have the potential to also affect the YAs’ long-term diabetes outcomes. Further investigation of the model is needed.

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          Most cited references 44

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          Current state of type 1 diabetes treatment in the U.S.: updated data from the T1D Exchange clinic registry.

          To examine the overall state of metabolic control and current use of advanced diabetes technologies in the U.S., we report recent data collected on individuals with type 1 diabetes participating in the T1D Exchange clinic registry. Data from 16,061 participants updated between 1 September 2013 and 1 December 2014 were compared with registry enrollment data collected from 1 September 2010 to 1 August 2012. Mean hemoglobin A1c (HbA1c) was assessed by year of age from 75 years. The overall average HbA1c was 8.2% (66 mmol/mol) at enrollment and 8.4% (68 mmol/mol) at the most recent update. During childhood, mean HbA1c decreased from 8.3% (67 mmol/mol) in 2-4-year-olds to 8.1% (65 mmol/mol) at 7 years of age, followed by an increase to 9.2% (77 mmol/mol) in 19-year-olds. Subsequently, mean HbA1c values decline gradually until ∼30 years of age, plateauing at 7.5-7.8% (58-62 mmol/mol) beyond age 30 until a modest drop in HbA1c below 7.5% (58 mmol/mol) in those 65 years of age. Severe hypoglycemia (SH) and diabetic ketoacidosis (DKA) remain all too common complications of treatment, especially in older (SH) and younger patients (DKA). Insulin pump use increased slightly from enrollment (58-62%), and use of continuous glucose monitoring (CGM) did not change (7%). Although the T1D Exchange registry findings are not population based and could be biased, it is clear that there remains considerable room for improving outcomes of treatment of type 1 diabetes across all age-groups. Barriers to more effective use of current treatments need to be addressed and new therapies are needed to achieve optimal metabolic control in people with type 1 diabetes.
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            Assessing psychosocial distress in diabetes: development of the diabetes distress scale.

            The purpose of this study was to describe the development of the Diabetes Distress Scale (DDS), a new instrument for the assessment of diabetes-related emotional distress, based on four independent patient samples. In consultation with patients and professionals from multiple disciplines, a preliminary scale of 28 items was developed, based a priori on four distress-related domains: emotional burden subscale, physician-related distress subscale, regimen-related distress subscale, and diabetes-related interpersonal distress. The new instrument was included in a larger battery of questionnaires used in diabetes studies at four diverse sites: waiting room at a primary care clinic (n = 200), waiting room at a diabetes specialty clinic (n = 179), a diabetes management study program (n = 167), and an ongoing diabetes management program (n = 158). Exploratory factor analyses revealed four factors consistent across sites (involving 17 of the 28 items) that matched the critical content domains identified earlier. The correlation between the 28-item and 17-item scales was very high (r = 0.99). The mean correlation between the 17-item total score (DDS) and the four subscales was high (r = 0.82), but the pattern of interscale correlations suggested that the subscales, although not totally independent, tapped into relatively different areas of diabetes-related distress. Internal reliability of the DDS and the four subscales was adequate (alpha > 0.87), and validity coefficients yielded significant linkages with the Center for Epidemiological Studies Depression Scale, meal planning, exercise, and total cholesterol. Insulin users evidenced the highest mean DDS total scores, whereas diet-controlled subjects displayed the lowest scores (P < 0.001). The DDS has a consistent, generalizable factor structure and good internal reliability and validity across four different clinical sites. The new instrument may serve as a valuable measure of diabetes-related emotional distress for use in research and clinical practice.
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              Barriers to diabetes management: patient and provider factors.

              Despite significant advances in diagnosis and treatment, the persistence of inadequate metabolic control continues. Poor glycemic control may be reflected by both the failure of diabetes self-management by patients as well as inadequate intervention strategies by clinicians. The purpose of this systematic review is to summarize existing knowledge regarding various barriers of diabetes management from the perspectives of both patients and clinicians. A search of PubMed, CINAHL, ERIC, and PsycINFO identified 1454 articles in English published between 1990 and 2009, addressing type 2 diabetes, patient's barriers, clinician's barriers, and self-management. Patients' adherence, attitude, beliefs, and knowledge about diabetes may affect diabetes self-management. Culture and language capabilities influence the patient's health beliefs, attitudes, health literacy, thereby affecting diabetes self-management. Other influential factors include the patient's financial resources, co-morbidities, and social support. Clinician's attitude, beliefs and knowledge about diabetes also influence diabetes management. Clinicians may further influence the patient's perception through effective communication skills and by having a well-integrated health care system. Identifying barriers to diabetes management is necessary to improve the quality of diabetes care, including the improvement of metabolic control, and diabetes self-management. Further research that considers these barriers is necessary for developing interventions for individuals with type 2 diabetes. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

                Author and article information

                The Diabetes Educator
                Diabetes Educ
                SAGE Publications
                May 10 2019
                August 2019
                June 27 2019
                August 2019
                : 45
                : 4
                : 420-430
                [1 ]Children’s Hospital Los Angeles, University of Southern California, Keck School of Medicine, Los Angeles, California
                [2 ]Chan Division of Occupational Science and Occupational Therapy, Ostrow School of Dentistry, University of Southern California, Los Angeles, California
                [3 ]Barbara Davis Center for Diabetes, University of Colorado, Department of Pediatrics, Anschutz Medical Campus, Aurora, Colorado
                [4 ]Department of Telehealth, School of Medicine, University of Colorado, Aurora, Colorado
                [5 ]Department of Psychiatry, School of Medicine, University of Colorado, Aurora, Colorado
                [6 ]Department of Epidemiology, School of Public Health, University of Colorado, Aurora, Colorado
                © 2019


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