OBJECTIVE -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.RESEARCH DESIGN AND METHODS -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 ϭ 200), waiting room at a diabetes specialty clinic (n ϭ 179), a diabetes management study program (n ϭ 167), and an ongoing diabetes management program (n ϭ 158).RESULTS -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 ϭ 0.99). The mean correlation between the 17-item total score (DDS) and the four subscales was high (r ϭ 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 (␣ Ͼ 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 Ͻ 0.001).CONCLUSIONS -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. Diabetes Care 28:626 -631, 2005L iving with diabetes can be tough. In the face of a complex, demanding, and often confusing set of self-care directives, patients may become frustrated, angry, overwhelmed, and/or discouraged. Diabetes-related conflict with loved ones may develop, and relationships with health care providers may become strained. The risk of depression is elevated (1,2). As a result, motivation for self-care may be impaired. To investigate the nature and breadth of such distress, a number of self-report instruments have been developed, including the ATT39 (3), Questionnaire on Stress in Patients with Diabetes-Revised (QSD-R) (4), and Problem Areas in Diabetes scale (PAID) (5). These measures aim to tap the range of emotional responses to diabetes and to serve as screening measures for clinical and research use. The PAID has been the most widely used of the measures and has been recently translated into several other languages (6 -8). PAID scores have ...

OBJECTIVE -Although prior research demonstrated that improving diabetes self-efficacy can improve self-management behavior, little is known about the applicability of this research across race/ethnicity and health literacy levels. We examined the relationship between diabetes self-efficacy and self-management behavior in an urban, diverse, low-income population with a high prevalence of limited health literacy. RESEARCH DESIGN AND METHODS -We administered an oral questionnaire inSpanish and English to patients with type 2 diabetes at two primary care clinics at a public hospital. We measured self-efficacy, health literacy, and self-management behaviors using established instruments. We performed multivariate regressions to explore the associations between self-efficacy and self-management, adjusting for clinical and demographic factors. We tested for interactions between self-efficacy, race/ethnicity, and health literacy on selfmanagement.RESULTS -The study participants were ethnically diverse (18% Asian/Pacific Islander, 25% African American, 42% Latino/a, and 15% white), and 52% had limited health literacy (short version of the Test of Functional Health Literacy in Adults score Ͻ23). Diabetes self-efficacy was associated with four of the five self-management domains (P Ͻ 0.01). After adjustment, with each 10% increase in self-efficacy score, patients were more likely to report optimal diet (0.14 day more per week), exercise (0.09 day more per week), self-monitoring of blood glucose (odds ratio 1.16), and foot care (1.22), but not medication adherence (1.10, P ϭ 0.40). The associations between self-efficacy and self-management were consistent across race/ethnicity and health literacy levels. CONCLUSIONS -Self-efficacy was associated with self-management behaviors in this vulnerable population, across both race/ethnicity and health literacy levels. However, the magnitude of the associations suggests that, among diverse populations, further study of the determinants of and barriers to self-management is warranted. Policy efforts should be focused on expanding the reach of self-management interventions to include ethnically diverse populations across the spectrum of health literacy. Diabetes Care 29:823-829, 2006T ype 2 diabetes is one of the most common diseases in the U.S., affecting Ͼ16 million individuals (1). Diabetes disproportionately affects lowincome and racial/ethnic minorities (2), and there is an urgent need to improve quality of care and lower rates of avoidable complications for these populations (3). Patients with diabetes are expected to perform daily self-management activities to help avoid diabetes-related morbidity and mortality. Self-management is a cornerstone of diabetes care, and it is believed that improving patient self-efficacy is a critical pathway to improved selfmanagement.The concept of self-efficacy is based on social cognitive theory, which describes the interaction between behavioral, personal, and environmental factors in health and chronic disease. The theory of self-efficacy pro...

OBJECTIVETo identify the pattern of relationships between the 17-item Diabetes Distress Scale (DDS17) and diabetes variables to establish scale cut points for high distress among patients with type 2 diabetes.RESEARCH DESIGN AND METHODSRecruited were 506 study 1 and 392 study 2 adults with type 2 diabetes from community medical groups. Multiple regression equations associated the DDS17, a 17-item scale that yields a mean-item score, with HbA1c, diabetes self-efficacy, diet, and physical activity. Associations also were undertaken for the two-item DDS (DDS2) screener. Analyses included control variables, linear, and quadratic (curvilinear) DDS terms.RESULTSSignificant quadratic effects occurred between the DDS17 and each diabetes variable, with increases in distress associated with poorer outcomes: study 1 HbA1c (P < 0.02), self-efficacy (P < 0.001), diet (P < 0.001), physical activity (P < 0.04); study 2 HbA1c (P < 0.03), self-efficacy (P < 0.004), diet (P < 0.04), physical activity (P = NS). Substantive curvilinear associations with all four variables in both studies began at unexpectedly low levels of DDS17: the slope increased linearly between scores 1 and 2, was more muted between 2 and 3, and reached a maximum between 3 and 4. This suggested three patient subgroups: little or no distress, <2.0; moderate distress, 2.0–2.9; high distress, ≥3.0. Parallel findings occurred for the DDS2.CONCLUSIONSIn two samples of type 2 diabetic patients we found a consistent pattern of curvilinear relationships between the DDS and HbA1c, diabetes self-efficacy, diet, and physical activity. The shape of these relationships suggests cut points for three patient groups: little or no, moderate, and high distress.

PURPOSE Previous research has documented that diabetes distress, defi ned as patient concerns about disease management, support, emotional burden, and access to care, is an important condition distinct from depression. We wanted to develop a brief diabetes distress screen instrument for use in clinical settings. METHODSWe assessed 496 community-based patients with type 2 diabetes on the previously validated, 17-item Diabetes Distress Scale (DDS17) and 6 biobehavioral measures: glycated hemoglobin (HbA 1c ); non-high-density-lipoprotein (non-HDL) cholesterol; kilocalories, percentage of calories from fat, and number of fruit and vegetable servings consumed per day; and physical activity as measured by the International Physical Activity Questionnaire.RESULTS An average item score of ≥3 (moderate distress) discriminated highfrom low-distressed subgroups. The 4 DDS17 items with the highest correlations with the DDS17 total (r = .56-.61) were selected. Composites, comprised of 2, 3, and 4 of these items (DDS2, DDS3, DDS4), yielded higher correlations (r = .69-.71). The sensitivity and specifi city of the composites were .95 and .85, .93 and .87, and .97 and .86, respectively. The DDS3 had a lower sensitivity and higher percentages of false-negative and false-positive results. All 3 composites significantly discriminated subgroups on HbA 1c , non-HDL cholesterol, and kilocalories consumed per day; none discriminated subgroups on fruit and vegetable servings consumed per day; and only the DDS3 yielded signifi cant results on the International Physical Activity Questionnaire. Because of its psychometric properties and brevity, the DDS2 was selected as a screening instrument.CONCLUSIONS The DDS2 is a 2-item diabetes distress screening instrument asking respondents to rate on a 6-point scale the degree to which the following items caused distress: (1) feeling overwhelmed by the demands of living with diabetes, and (2) feeling that I am often failing with my diabetes regimen. The DDS17 can be administered to those who have positive fi ndings on the DDS2 to defi ne the content of distress and to direct intervention.

Aims To identify the unique sources of diabetes distress (DD) for adults with type 1 diabetes (T1D). Methods Sources of DD were developed from qualitative interviews with 25 T1D adults and 10 diabetes health care providers. Survey items were then developed and analyzed using both exploratory (EFA) and confirmatory CFA) analyses on two patient samples. Construct validity was assessed by correlations with depressive symptoms (PHQ8), complications, HbA1C, BMI, and hypoglycemia worry scale (HWS). Scale cut-points were created using multiple regression. Results An EFA with 305 U.S. participants yielded 7 coherent, reliable sources of distress that were replicated by a CFA with 109 Canadian participants: Powerlessness, Negative Social Perceptions, Physician Distress, Friend/Family Distress, Hypoglycemia Distress, Management Distress, Eating Distress. Prevalence of DD was high with 41.6% reporting at least moderate DD. Higher DD was reported for women, those with complications, poor glycemic control, younger age, without a partner, and non-White patients. Conclusions We identified a profile of seven major sources of DD among T1D using a newly developed assessment instrument. The prevalence of DD is high and is related to glycemic control and several patient demographic and disease-related patient characteristics, arguing for a need to address DD in clinical care.

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BackgroundMobile health (mHealth) interventions may improve heart failure (HF) self-care, but standard models do not address informal caregivers’ needs for information about the patient’s status or how the caregiver can help.ObjectiveWe evaluated mHealth support for caregivers of HF patients over and above the impact of a standard mHealth approach.MethodsWe identified 331 HF patients from Department of Veterans Affairs outpatient clinics. All patients identified a “CarePartner” outside their household. Patients randomized to “standard mHealth” (n=165) received 12 months of weekly interactive voice response (IVR) calls including questions about their health and self-management. Based on patients’ responses, they received tailored self-management advice, and their clinical team received structured fax alerts regarding serious health concerns. Patients randomized to “mHealth+CP” (n=166) received an identical intervention, but with automated emails sent to their CarePartner after each IVR call, including feedback about the patient’s status and suggestions for how the CarePartner could support disease care. Self-care and symptoms were measured via 6- and 12-month telephone surveys with a research associate. Self-care and symptom data also were collected through the weekly IVR assessments.ResultsParticipants were on average 67.8 years of age, 99% were male (329/331), 77% where white (255/331), and 59% were married (195/331). During 15,709 call-weeks of attempted IVR assessments, patients completed 90% of their calls with no difference in completion rates between arms. At both endpoints, composite quality of life scores were similar across arms. However, more mHealth+CP patients reported taking medications as prescribed at 6 months (8.8% more, 95% CI 1.2-16.5, P=.02) and 12 months (13.8% more, CI 3.7-23.8, P<.01), and 10.2% more mHealth+CP patients reported talking with their CarePartner at least twice per week at the 6-month follow-up (P=.048). mHealth+CP patients were less likely to report negative emotions during those interactions at both endpoints (both P<.05), were consistently more likely to report taking medications as prescribed during weekly IVR assessments, and also were less likely to report breathing problems or weight gains (all P<.05). Among patients with more depressive symptoms at enrollment, those randomized to mHealth+CP were more likely than standard mHealth patients to report excellent or very good general health during weekly IVR calls.ConclusionsCompared to a relatively intensive model of IVR monitoring, self-management assistance, and clinician alerts, a model including automated feedback to an informal caregiver outside the household improved HF patients’ medication adherence and caregiver communication. mHealth+CP may also decrease patients’ risk of HF exacerbations related to shortness of breath and sudden weight gains. mHealth+CP may improve quality of life among patients with greater depressive symptoms. Weekly health and self-care monitoring via mHealth tools may identify intervention effec...

QW glucose-lowering medications are viewed positively by patients with type 2 diabetes, especially if they are current injection users or are dissatisfied with their current treatments or outcomes. Greater convenience, better medication adherence and improved QOL are commonly endorsed attributes. Clinicians may need to review both the positive attributes of QW medications as well as common patient concerns, when considering this option.