Given the importance of glycemic control in the development of diabetes complications, the plethora of tools now available to monitor the day-to-day trends in glycemia is remarkable. In this regard, self-monitoring of blood glucose (SMBG) has been considered a key component of patient management. Arguably, there remains almost universal agreement that SMBG should be available to all diabetic patients regardless of current treatment strategy. However, recently there have been reports that have challenged the current paradigm that all patients should use SMBG and concluded that SMBG for type 2 diabetic patients not on insulin may not be beneficial on glycemic control and must be weighed against the expense and inconvenience. In the counterpoint narrative following the contribution by Malanda et al., Drs. Polonsky and Fisher provide a compelling argument suggesting that while it is evident that implementing SMBG in unstructured ways without training patients and clinicians is likely to be a waste of resources, there are effective and powerful ways to use structured SMBG in insulin-naïve type 2 diabetic patients. -William T. Cefalu, MD Editor in Chief, Diabetes Care.

Aims

To describe the effects of the COVID-19 pandemic on adults with T1D or T2D in the U.S.

Methods

Participants, recruited from the Taking Control of Your Diabetes Research Registry, were ≥19 years old and diagnosed with either T1D or T2D for ≥12 months. Participants completed an online survey on a HIPAA-protected platform.

Results

Completed surveys were received from 763 T1Ds and 619 T2Ds. Average T1D age was 53.3 (SD = 15.3); average T2D age was 64.9 (SD = 10.3). Both samples were predominantly female, non-Hispanic white and well-educated. Average self-reported HbA1c was 6.9 (SD = 1.0; 52 mmol/mol) for T1Ds and 7.1 (SD = 1.1; 54 mmol/mol) for T2Ds. About 40% of respondents reported that all of their diabetes healthcare appointments at the time were cancelled or postponed, 40% reported a switch to telehealth appointments and almost half reported lower overall satisfaction with these visits (compared to pre-pandemic). There were widespread increases in general and diabetes-related stress and social isolation, and negative effects on disease management. About 25% reported increases in highs, lows, and glucose variability in both groups.

Conclusion

There has been a substantive increase in level of diabetes-related and general life stress and social isolation due to the pandemic, with a significant impact on disease management.

Objective

To 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 methods

Recruited 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 HbA(1c), 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.

Results

Significant quadratic effects occurred between the DDS17 and each diabetes variable, with increases in distress associated with poorer outcomes: study 1 HbA(1c) (P < 0.02), self-efficacy (P < 0.001), diet (P < 0.001), physical activity (P < 0.04); study 2 HbA(1c) (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.

Conclusions

In two samples of type 2 diabetic patients we found a consistent pattern of curvilinear relationships between the DDS and HbA(1c), 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.

Aims

To assess between-group differences in participant experiences in a two-arm diabetes distress (DD) reduction RCT and to determine their relationship to clinical outcomes (reductions in DD and HbA1C).

Methods

For high DD adults with Type 1 diabetes and HbA1c ≥7.5% participating in T1-REDEEM, we evaluated post intervention 5-point ratings of overall program "helpfulness" and program component "helpfulness," along with open-ended feedback statements using 10 qualitative codes. We compared responses of those in OnTrack, a distressed-focused intervention, with KnowIt, an education/management intervention.

Results

Those in OnTrack reported significantly higher levels of overall program helpfulness and greater helpfulness of each component of the program, greater group support, far fewer negative experiences, and more active and meaningful group engagement than those who participated in KnowIt. Ratings of helpfulness were unrelated to reductions in DD and HbA1C in both study arms. As previously reported, these findings occurred despite significant reductions in both DD and HbA1C in both arms with no between-group differences.

Conclusions

Findings highlight the importance of addressing the personal experience of diabetes interventions in clinical care as separate, distinct outcomes. Personal experience may not always be related to changes in traditional clinical indicators.

Aims

This study evaluated the implementation costs of two group interventions, one focused on diabetes education (KnowIt) and one focused directly on diabetes distress (OnTrack), that reduced diabetes distress and HbA1C in adults with poorly controlled type 1 diabetes (T1DM) in the T1-REDEEM trial.

Methods

Resources used to provide interventions were enumerated using activity-based micro-costing methods. Costs were assigned to resources in 2017 US dollars. US median wage and benefit rates were used to calculate costs of staff time. Cost per unit change was calculated for diabetes distress and HbA1C.

Results

For both interventions, per participant implementation costs were approximately $250 and cost per 1.0 percentage point (11 mmol/mol) change in HbA1C was $1400. Cost per unit change in diabetes distress was $364 for KnowIt and $335 for OnTrack. No statistically significant differences in costs were observed.

Conclusions

This is the first study to examine the costs of implementing interventions targeting diabetes distress in the context of T1DM. Both interventions had per participant implementation costs in the lower end of the range of previously examined diabetes self-management interventions ($219 to $5390). These inventions and their costs merit further attention because reducing diabetes distress may impact long term T1DM outcomes.

Clinical trials registration

ClinicalTrials.govNCT02175732.

Objective

To demonstrate how maladaptive emotion regulation (ER) can lead to diabetes distress (DD), with subsequent effects on management and metabolic outcomes among adults with type 1 diabetes.

Methods

Data are based on pre-intervention assessment for a random controlled trial to reduce DD. Patients were recruited in California, Oregon, Arizona and Ontario, Canada. After screening and consent, patients completed an online assessment and released their most recent laboratory HbA1C. Structural equation modeling was used to define an ER measurement model and test for significant pathways.

Results

Three ER mechanisms combined into a single construct: emotion processing, non-judgment of emotions, non-reactivity to emotions. Models indicated a significant pathway from ER and cognitions to DD to disease management to metabolic control.

Conclusions

As hypothesized, the three ER mechanisms formed a single, coherent ER construct. Patients with poor ER reported high DD; and high DD was linked to poor diabetes management and poor metabolic control.

Practice implications

Identifying both the level of DD and the ER mechanisms that lead to high DD should be explored in clinical settings. Helping T1Ds to become more aware, less judgmental and less reactive behaviorally to what they feel about diabetes and its management may reduce DD.

Aims

To document the prevalence and 9-month incidence of elevated diabetes distress (DD) and the stability of DD over time using both single threshold and minimal clinically important differences (MCID) approaches.

Methods

Adults with type 1 diabetes (T1D) (N=224) completed the 28-item T1-Diabetes Distress Scale (T1-DDS) at baseline and 9months. A T1-DDS threshold was identified with spline analysis and MCID was calculated from the standard error of measurement.

Results

Analyses supported a cut-point of ≥2.0 for elevated DD. The prevalence and 9-month incidence of elevated DD was 42.1% and 54.4%, respectively. MCID was ±0.19 but varied by subscale (.26 to .50). Elevated DD was stable: only 20% crossed 2.0 over 9months. MCID analyses showed that change also occurred among those who remained either below or above 2.0 over time. Change varied by source of distress, with Powerlessness the most prevalent and stable. Using MCID, only participant age, gender and number of complications predicted change.

Conclusions

The prevalence, 9-month incidence and stability of elevated DD are high among adults with T1D, with change based on source of DD. We propose a combined cut-point/MCID framework for measuring change in DD, since each approach reflects unique characteristics of change over time.

Objective

We tested three models to determine how improvements in emotion regulation (ER) and cognitive skills (CS) as a result of intervention operate to affect reductions in diabetes distress DD.

Methods

Change data were drawn from the baseline and 9-month T1-REDEEM trial. Adults with type 1 diabetes were recruited from several U.S. states and Toronto, Canada. A primary and two alternative structural equation models were tested to explore the directionality of effect: primary model - changes in ER and CS drive changes in DD; reverse model - changes in DD drive changes in ER and CS; and bidirectional model - changes in ER, CS and DD occur together with no directionality.

Results

All three models displayed a good fit to the data. The primary model indicated 7 significant directional pathways: improvements in ER and CS operate together to drive reductions in DD. The reverse model only indicated that reductions in DD affected changes in one CS variable; and the bidirectional model indicated only that these results were bidirectional. Reductions in all tested domains of DD occurred together.

Conclusions

Improvements in ER and CS drive reductions in DD.

Practice implications

Interventions to reduce high DD should focus on improving ER and CS.

Abstract Background The value and utility of self-monitoring of blood glucose (SMBG) in non-insulin treated T2DM has yet to be clearly determined. Findings from studies in this population have been inconsistent, due mainly to design differences and limitations, including the prescribed frequency and timing of SMBG, role of the patient and physician in responding to SMBG results, inclusion criteria that may contribute to untoward floor effects, subject compliance, and cross-arm contamination. We have designed an SMBG intervention study that attempts to address these issues. Methods/design The Structured Testing Program (STeP) study is a 12-month, cluster-randomised, multi-centre clinical trial to evaluate whether poorly controlled (HbA1c ≥ 7.5%), non-insulin treated T2DM patients will benefit from a comprehensive, integrated physician/patient intervention using structured SMBG in US primary care practices. Thirty-four practices will be recruited and randomly assigned to an active control group (ACG) that receives enhanced usual care or to an enhanced usual care group plus structured SMBG (STG). A total of 504 patients will be enrolled; eligible patients at each site will be randomly selected using a defined protocol. Anticipated attrition of 20% will yield a sample size of at least 204 per arm, which will provide a 90% power to detect a difference of at least 0.5% in change from baseline in HbA1c values, assuming a common standard deviation of 1.5%. Differences in timing and degree of treatment intensification, cost effectiveness, and changes in patient self-management behaviours, mood, and quality of life (QOL) over time will also be assessed. Analysis of change in HbA1c and other dependent variables over time will be performed using both intent-to-treat and per protocol analyses. Trial results will be available in 2010. Discussion The intervention and trial design builds upon previous research by emphasizing appropriate and collaborative use of SMBG by both patients and physicians. Utilization of per protocol and intent-to-treat analyses facilitates a comprehensive assessment of the intervention. Use of practice site cluster-randomisation reduces the potential for intervention contamination, and inclusion criteria (HbA1c ≥ 7.5%) reduces the possibility of floor effects. Inclusion of multiple dependent variables allows us to assess the broader impact of the intervention, including changes in patient and physician attitudes and behaviours. Trial Registration Current Controlled Trials NCT00674986.

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.