Diabetes Distress, Emotional Regulation, HbA_1c in People with Diabetes and A Controlled Pilot Study of an Emotion-Focused Behavioral Therapy Intervention in Adults with Type 2 Diabetes

Abstract

Aim.

One 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 A_1c levels and determine preliminary effect size estimates for an intervention targeting poor emotion regulation on glycemic control.

Methods.

Study 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 A_1c 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.

Results.

Study 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 A_1c 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 A_1c levels and smaller reductions in diabetes distress that correlated with changes in emotion regulation.

Conclusions.

These studies suggest that, in people with diabetes, elevated A_1c 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 A_1c 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 A_1c in individuals with diabetes.

INTRODUCTION

Diabetes affects over 34.2 million Americans and is currently the 7th leading cause of death in the US [1]. Despite advances in medication and device technology, less than 50% of people with diabetes achieve a glycemic target of A_1C < 7.0% (< 53 mmol/mol) [2, 3]. One potential barrier to glycemic management is diabetes distress, the emotional distress associated with living with diabetes (e.g., chronic illness and burden of treatment tasks). Diabetes distress is common, with nearly 42% reporting elevated diabetes distress scores, is inversely related with both quality of life [4] and diabetes self-care behaviors [3] and manifests an independent association with A_1C, over time [5, 6].

Options for treating diabetes distress have traditionally included diabetes education and psychological interventions based on cognitive behavioral therapy, typically targeting depressive symptoms [3, 7] even though diabetes distress is only modestly associated with depression scores [8]. Unfortunately, these approaches have resulted in only modest effects on A_1c levels [7]. One missing element to addressing diabetes distress may be a lack of acknowledgement of individual differences in the ability to regulate one’s negative emotions.

Emotional regulation consists of the experience, processing, understanding, and coping with emotion [9]. Problems in emotion regulation are manifest by feeling too much (or too little) emotion in response to daily life events, and/or in the reactivity/lability of emotion referred to as Emotion Regulation-Experience. Difficulty in identifying, evaluating, and controlling the expression of emotion in an appropriate manner is referred to as skill in emotion management. Emotion Regulation-Experience and Emotion Regulation-Skill are inversely related, and the presence of poor Emotion Regulation-Skill increases as Emotion Regulation-Experience (i.e., negative emotionality) since the sub-optimal degree of Emotion Regulation-Skill cannot “reign in” the experience of negative emotion.

A relationship between emotion regulation and glycemic management is supported by studies on the impact of emotional states, and chronic stress on circulating glucose levels [10, 11]. Specific to Emotion Regulation-Skill, one study in = adults without diabetes reported that enhancing positive emotional states reduce, while enhancing negative emotional states increase, circulating glucose, specifically in those “Poor” Emotion Regulation [12]. Consistent with these findings, recent studies in individuals with Type 1 diabetes (T1D) [13] and Type 2 diabetes (T2D) [14] report significant correlations with measures of negative emotional experience and skill at modulating negative emotion. In a larger sample, we have also shown that poor emotion regulation is strongly associated with diabetes distress [15]. If so, an explicit focus on emotion regulation skills may improve outcomes for diabetes distress interventions. To date only the T1REDEEM [16] study in individuals with Type 1 diabetes included a psychological intervention (OnTrack) involving an explicit focus on emotion management. OnTrack contained four hour-long videos over the course of the trial. While it yielded a large reduction in diabetes distress (d = 1.06) it was only associated with a small relationship between change in diabetes distress and A_1C (r = 0.14, p = 0.01). Later analysis [17] suggested that “emotion management” may be critical to reducing diabetes distress and, possibly, A_1C levels and that such interventions likely require a more intense emotion regulation intervention [7] and that should be targeted to individuals with difficulties in emotion regulation [17].

In this paper, we report on two studies. The aim of Study 1 was to further explicate the relationships between variables of A_1c, diabetes distress, emotion regulation, and self-care variables through the analysis of cross-sectional data from individuals with Type 1 and Type 2 diabetes. Study 2 was a natural extension of our findings from Study 1 and its aim was to conduct a pilot study to determine preliminary estimates of effect sizes of an emotion regulation focused behavioral therapy intervention on diabetes distress and A_1c levels in individuals with Type 2 diabetes.

METHODS: STUDY 1

Study Participants.

Participants were recruited from individuals with Type 1 and Type 2 diabetes receiving care at the Kovler Diabetes Center program at the University of Chicago Medical Center between 2012 and 2016 and have been previously described [15]. After giving informed consent agreeing that their data would be used for research purposes without identifying them, study participants were evaluated by clinical psychology externs and interns with a structured clinical assessment and a series of other assessments relevant to diabetes (see below). The study was approved by the University of Chicago Institutional Review Board.

Assessments.

Assessment of Glycosylated Hemoglobin (A_1c).

A_1c levels were assessed, by finger-stick, in the Kovler Diabetes Program using a point of care instrument (Siemens) as in our previous study [14]. A_1c levels were not normally distributed and were log transformed for analysis.

Assessment of Diabetes Distress.

Three items from the Diabetes Distress Scale [18] and three from the Problem Areas in Diabetes [19] and were used to screen for Diabetes Distress. This screen demonstrated very good internal consistency (α = 0.89) and correlated significantly with a quality of life measure (r = −0.41, p < 0.001) as does the full Diabetes Distress Scale [3].

Assessment of Diabetes Self-Care.

Both studies included a questionnaire related to diabetes self-care which was assessed with the Self-Care Inventory-Revised (SCI-R) [20]. The SCI-R is a 15-item questionnaire, scored on a 0–4 Likert scale (ranging from “never” to “always”), assessing diabetes self-care in the past one to two months.

Assessment of Emotional Regulation.

Four questionnaires related to negative emotionality and skill at regulating negative emotion were used in this study. Negative emotionality was assessed with the six-item “Negative Emotional Intensity”; e.g., “my friends would probably say I’m a tense or ‘high-strung’ person”) scale of the Affect Intensity Measure (AIM) [21] and the eight-item “Anxiety-Depression Lability” (e.g., “there are times when all I can think about is how worthless I am and then very soon afterwards all I can think about are the things that I am worried about”) scale form the Affect Lability Scales (ALS) [22]. Skill at regulating negative emotion was assessed by using the “Clarity of Emotion” (11 items; e.g., “I usually know my feels about a matter”) and “Repair of Emotion” (6 items; e.g., “When I become upset I remind myself of all the pleasures in life”) from the Trait-Meta Mood (TMM; [9]) questionnaire.

Statistical Analysis.

Study 1 involved a series of analyses including a descriptive analysis, a Bayesian graphic model, and a comparison of two hypothesized models. For the descriptive analysis, a negative Emotion Regulation-Experience variable was created by taking the mean of Z-scores for AIM “Negative Emotional Intensity” and ALS “Anxiety/Depression Lability”. An Emotion Regulation-Skill variable was created by taking the mean of Z-scores of TMM “Clarity of Emotion” and TMM “Repair of Emotion”). In turn, these were similarly combined into a composite variable reflecting Emotional Regulation with high scores reflecting poor emotion regulation. Statistical analysis of these data involved chi-square, t-test, ANOVA, all at a two-tailed alpha level of 0.05. For the Bayesian analysis we tested the fit of hypothesized relationships between Emotion Regulation, Diabetes Distress, Self-Care, A_1c levels in the context of a Bayesian network model. The model jointly estimated each edge in the graph as a linear regression model adjusted for age, sex, and ethnicity. Non-informative flat prior distributions were used for all regression coefficients and gamma prior distributions with shape and scale parameter of 0.1 were used for all precision parameters. All continuous variables were standardized to have mean 0 and variance 1 to allow regression coefficients to be interpreted as estimates of partial correlation. Analogous to frequentist significance testing at the 0.05 level, associations were noted as significant if the posterior probability that the coefficient was greater than 0 was less than 0.025 (negative association) or greater than 0.975 (positive association). Models were fit using a Markov chain Monte Carlo algorithm implemented in R using NIMBLE [23]. The algorithm was run for 50,000 iterations, discarding the first 20,000 as burn-in. Convergence was assessed visually using trace plots. Posterior distributions were summarized using the posterior mean, 95% credible interval (CI), and the posterior probability the effect is greater than 0. Finally, we tested two hypothesized models. The first model tested was a linear model from poor emotion regulation to diabetes distress to self-care to A_1c levels (fig 1a). The second model tested included poor emotion regulation to diabetes distress with self-care as a mediating variable between poor emotion regulation and diabetes distress to A_1c level (fig 1b).

Figure 1.

Model I (1a) and Model II (1b) with correlation and standardized regression coefficients. Asterisks indicate a statistically significant result in the standard error of the mean (SEM).

RESULTS: STUDY 1

Participant Characteristics.

Two-hundred-sixteen adult study participants took part in this study. The sample was split between those with Type 2 (n = 136) and Type 1 (n = 80) diabetes and their characteristics are listed in Table 1. While participants with Type 2 diabetes differed from those with Type 1 diabetes, in age, ethnicity, current income, years with diabetes, insulin dependence, and self-care, no significant differences were observed between the groups in sex, A_1c levels, or in diabetes distress, emotion regulation-experience, or emotion regulation-skill scores.

Table 1.

Characteristics of Adult Study Participants with Type 1 and 2 Diabetes in Study 1

VARIABLES	ALL (N = 216)	T2D (N = 136)	T1D (N = 80)	P (T2D vs. T1D)
DEMOGRAPHIC VARIABLES
Age (Years)	49.3 ± 17.5	58.1 ± 12.8	34.3 ± 13.9	< 0.001
Sex (% Female)	59.8	60.3	56.3	= 0.560
Race (% Non-White)	51.9	69.9	21.3	< 0.001
Income (% < $20K / $20–60K / > $60K)	38 / 27 / 35	42 / 32 / 26	31 / 19 / 50	= 0.012
DIABETES RELATED VARIABLES
A1c Level	7.9 ± 1.8	7.8 ± 1.6	8.0 ± 1.9	= 0.583
Years With Diabetes	34.3 ± 19.2	45.3 ± 13.6	15.7 ± 11.5	< 0.001
Insulin Dependent (%)	76.9	63.2	100.0	< 0.001
Diabetes Distress Screen	6.7 ± 6.0	6.8 ± 6.6	6.4 ± 4.9	= 0.551
Diabetes Self-Care (SCI-R)	49.7 ± 9.0	48.0 ± 8.7	52.7 + 8.8	< 0.001
EMOTION REGULATION VARIABLES
Global Negative Emotionality (Emotion Regulation-Experience)	32.7 ± 8.9	32.7 ± 8.5	32.5 ± 9.6	= 0.420
Global Emotional Skills (Emotion Regulation-Skill)	46.3 ± 8.5	45.9 ± 8.3	46.9 ± 8.9	= 0.585

Descriptive Analyses.

Zero-order correlations (Table 2) suggested highly significant, medium-sized, relationships between poor emotional regulation and diabetes distress and A_1c, and between self-care and A_1c levels. Given the inter-relationships among these variables we proceeded to fit the data to two models.

Table 2.

Zero-Order Correlations for Poor Emotion Regulation, Diabetes Distress Screen, Diabetes Self-Care, and HbA_{1c i}n Study 1

	Poor Emotion Regulation	Diabetes Distress Screen	Diabetes Self-Care
Diabetes Distress Screen	0.41 (p < 0.001)
Diabetes Self-Care	−0.13 (p = 0.05)	− 0.12 (p = 0.07)
A1c	0.03 (p = 0.698)	0.31 (p < 0.001)	− 0.21 (p = 0.002)

Network Model Analyses.

A simple linear model (Model I), demonstrated a significant PATH coefficient from poor emotion regulation to diabetes distress (0.39, 95% CI: 0.26 to 0.51), a smaller, but non-significant, PATH coefficient for diabetes distress to self-care (−0.15, 95% CI: −0.01 to −0.28), and a statistically significant, PATH coefficient from self-care to A_1c (−0.22, 95% CI: −0.09 to −0.35); fig 1a. A second model (Model II) allowing for mediation effects among the variables also fit these data. This model demonstrated a significant Direct PATH coefficient from poor emotion regulation to A_1C of 0.14 (95% CI: 0.02 to 0.28) and a significant Indirect Path coefficient from poor emotion regulation to A_1C via diabetes distress of 0.13 (95% CI: 0.06 to 0.20) for a Total Effect of poor emotion regulation on A_1C of 0.27 (95% CI: 0.10 to 0.44). The model also demonstrated a significant Direct Path coefficient from diabetes distress to A_1C of 0.32 (95% CI: 0.18 to 0.46) and a significant Direct PATH coefficient from self-care to A_1C of 0.19 (95% CI: 0.06 to 0.32). Compared with Model I, poor emotion regulation and diabetes distress have less relevance on A_1C via self-care (0.10 and 0.11, respectively). More so than Model I, Model II suggests that the total effect of poor emotion regulation on A_1C (0.14 direct and 0.12 indirect via diabetes distress) is: (a) substantial (0.26) and almost as large as the direct effect of diabetes distress on A_1C (0.32), (b) together, poor emotion regulation and diabetes distress account for 71% (0.46/0.65) of direct effects on A_1C, (c) the direct effect of self-care on A_1C accounts for 29% (0.19/0.65) of all direct effects on A_1C and, (d) the indirect effect from poor emotion regulation and diabetes distress to A_1c is very small (i.e., 0.019 and 0.021, respectively).

METHODS: STUDY 2

Because results of previous studies [24] (including Study 1) suggest that levels of A_1c and diabetes distress have important relationships with poor emotion regulation, we conducted a pilot randomized clinical trial of an emotion regulation focused behavioral therapy intervention in adults with Type 2 diabetes of at least one year duration.

Study Participants.

Between October 2017 and September 2018, forty adults of both sexes between ages 21 and 65 years, with Type 2 diabetes, and persistently elevated A_1c levels (> 7.0% as documented in the medical record), were identified and approached to participate in a pilot, randomized, clinical trial to assess the effect of an emotion regulation focused behavioral therapy intervention, compared with treatment as usual, on A_1c levels and diabetes distress. All potential participants received their diabetes care at the Kovler Diabetes Center at the University of Chicago. The trial was approved by the University of Chicago Institutional Review Board and was registered with ClinicalTrial.gov (NCT03553680).

Assessments.

Assessments for Study 2 were the same as in Study 1 except that the full Diabetes Distress Scale was used in this second study.

Screening, Entry, and Randomimzation for Pilot Clinical Trial.

After initial identification, potential study participants were consented for study and further screened with the Diabetes Distress Scale [18] to identify participants with elevated Regimen-Related Diabetes Distress scores, and with the four emotion regulation assessments, described above, to identify participants with elevated Emotion Regulation-Experience, and reduced Emotion Regulation-Skill, scores. Regimen-Related Diabetes Distress scores > 2 were designated as elevated as in previous studies [6]; Emotion Regulation-Experience scores > 25 were designated as elevated, and Emotion Regulation-Skill scores < 48 were designated as reduced (n.b., respectively, these cut-off scores were above, and below, the mean scores of 247 medically and psychologically healthy controls in our research program). Based on these data, thirty participants met study entry criteria (i.e., elevated A_1c levels, elevated Regimen-Related Diabetes Distress, elevated Emotion Regulation-Experience, and reduced Emotion Regulation-Skill, scores) and were randomized 1:1 to receive an emotion regulation focused therapy intervention or to continue with treatment as usual (control).

Emotion Regulation Focused Behavioral Therapy Intervention.

Our emotion regulation focused therapy intervention was developed and manualized by adapting materials targeting Emotion Regulation-Experience and Emotion Regulation-Skill [25–27]. The intevention was designed to cover a wider range of skills than typical cognitive behavioral therapy by targeting specific deficits in emotional awareness and emotion management that likely underlie diabetes distress. Each of the ten (45 minute) sessions was delivered by a masters-level clinical psychologist (TP) trained in its use and supervised by doctoral-level clinical psychologists (TD, AB). The intervention began with psychoeducation regarding events, thoughts, feelings, and behaviors and how these relate to diabetes management. More specifically, this intervention teaches participants to identify emotions and understand their purpose; to use specific cognitive restructuring strategies to change negative thoughts into more adaptive, realistic thinking; to reduce emotional reactivity through mindfulness and acceptance of emotional experiences along with relaxation and distress tolerance strategies; and to appropriately express and communicate their thoughts and feelings, strategies that are practiced and role-played with participants. Each session was followed by homework assignments that were reviewed at the beginning of the next session (manual is attached in Supplemental Materials).

Statistics.

The focus of the Study 2 pilot clinical trial was to determine preliminary effect sizes (Cohen’s d) for the comparison of the emotion regulation focused behavioral therapy intervention, vs. treatment as usual, on both A_1c levels and Regimen-Related Diabetes Distress Scale scores, and to explore relationships between changes in A_1c levels and Regimen-Related Diabetes Distress Scale, Emotion Regulation-Experience, Emotion Regulation-Skill, and Self-Care scores by Pearson correlation.

RESULTS: STUDY 2

Participant Characteristics.

Of the thirty study participants screening positive for Study 2, twenty began the trial and completed A_1c level and behavioral assessments at baseline and end of trial (or ten weeks later for treatment as usual participants). The remaining ten, equally randomized to the two intervention groups, did not return for baseline assessments or intervention, and were lost to follow-up; see Consort diagram in supplemental file. At baseline, the twenty study participants had high A_1c levels (9.5 ± 2.1%), high Regimen-Related Diabetes Distress Scale scores (3.6 ± 1.4), high Emotion Regulation-Experience scores (37.3 ± 8.3), and low Emotion Regulation-Skill scores (42.1 ± 7.9). No differences between intervention groups were observed in demographic or in other variables of interest (Table 3).

Table 3.

Baseline Characteristics of Adult Study Participants with Type 2 Diabetes in Study 2

	EFBT (N = 10)	TAU (N = 10)
Demographic Variables
Age	54.5 ± 10.8	54.2 ± 13.5
Sex (F / M)	8 / 2	7 / 3
Ethnicity (AA / White)	9 / 1	10 / 0
Income (< $20K / > $20K)	6 / 4	4 / 6
Variables Relevant to T2D
Glycosylated Hb (A1c)	9.8 ± 1.5	9.3 ± 2.6
Years with Diabetes	14.3 ± 11.1	17.5 ± 12.3
Insulin-Dependent (Yes / No)	9 / 1	6 / 4
Regimen-Related Diabetes Distress (R-DD)	3.6 ± 1.4	3.6 ± 1.5
Diabetes Self-Care (SCI-R)	45.0 ± 7.5	44.2 ± 7.9
Behavioral Variables
Emotion Regulation-Exp (Negative Emotional Experience)	38.2 ± 9.0	36.3 ± 7.9
Emotion Regulation-Skill (Emotional Regulatory Skill)	40.4 ± 10.2	43.8 ± 4.6

Response to Emotion Regulation Focused Behavioral Therapy and Treatment as Usual.

At endpoint, Regimen-Related Diabetes Distress Scale scores (mean ± sd) fell by 4.0 ± 8.6 points (vs. 1.4 ± 4.5 points) resulting in a smaller than medium-sized (d = 0.38) net improvement favoring the emotion regulation focused behavioral therapy intervention (figure 2, left). Similarly, A_1c levels fell by 1.3 ± 1.4% in the intervention (vs. 0.6 ± 1.4% with treatment as usual) participants resulting in a medium-sized (d = 0.53) net improvement in A_1c levels favoring the emotion regulation focused behavioral therapy intervention (figure 2, right). Changes in A_1c levels were significantly correlated with changes in Regimen-Related Diabetes Distress Scale [r = 0.48 (CI: 0.05 to 0.76), p < 0.032], in Emotion Regulation-Skill [r = −0.58 (CI: −0.18 to −0.81), p = 0.007] and in Emotion Regulation-Experience [r = 0.45 (CI: 0.01 to 0.74), p = 0.048] scores but non-significant for changes in Self-Care [r = 0.09 (CI: −0.37 to 0.51), p = 0.712], scores.

Figure 2.

Effect of Emotion Regulation Focused Behavioral Therapy (EFBT) vs. Treatment as Usual (TAU): Change from Baseline to End-Trial for Regimen-Related Diabetes Distress Scale scores (left) and A_1c levels (right) and as a function of effect size (d).

DISCUSSION

The data from Study 1 suggest that a linear model from poor emotional regulation to elevated diabetes distress, to reduced self-care, to elevated A_1c levels is a viable model for the relationship between these variables and A_1c. As such, these results are replicative of the same model tested with T1-REDEEM study data which reported coefficients of 0.36 from “poor emotion management” to diabetes distress, 0.19 from diabetes distress to “skipped insulin boluses”, and of 0.23 from “skipped boluses” to A_1c [17]. However, the more comprehensive, interactive, model (Model II) provides greater explanatory power regarding the effects of these variables on A_1c. Specifically, the effect of poor emotion regulation (indirect only) effect on A_1c was 0.013 in Model I, while its total (direct and indirect) effect on A_1c was twenty-fold higher, at 0.26, in Model II. Similarly, the effect of elevated diabetes distress (indirect only) on A_1c was 0.033 in Model I while its total effect was 0.34 in Model II. Reduced self-care’s (direct) effect on A_1c was significant in both models at 0.22 in Model I and 0.19 in Model II. Model II, however, demonstrates that both poor emotional regulation and elevated diabetes distress are also associated with increased A_1c at a level, respectively, 42%, and 79% greater than that for reduced self-care. If so, it is likely that interventions targeting poor emotion regulation and/or elevated diabetes distress should have an effect on reducing A_1c levels, which set the stage for the pilot clinical trial in Study 2.

The data from Study 2 suggest our emotion-focused behavioral therapy intervention may have clinically meaningful effects on both Regimen-Related Diabetes Distress scores and A_1c levels in adults with Type 2 Diabetes, likely by improving emotional regulation as assessed in these studies. Changes in A_1c, overall, were significantly correlated with changes in Regimen-Related Diabetes Distress, Emotion Regulation-Experience, and Emotion Regulation-Skill scores but not with changes in Self-Care scores. While changes in the latter had no effect on A_1c, it is possible that our emotion-focused behavioral therapy intervention improves self-care through behaviors not reflected by the measure we used.

A limitation of Study 1 is that it is a cross-sectional study and inferences from the model-fitting analyses and need to be confirmed in a longitudinal study. Limitations for Study 2 include its small sample size, and the fact that one-third of the randomized participants were lost to follow-up before actual entry in the trial. Accordingly, the results of Study 2 must be seen as preliminary and subject to Type 1 Error. This said, the results of Study 2 are consistent with Model II in Study 1.

These findings are consistent with previously reported relationships between A_1C and measures reflective of skill at emotion regulation in adults with Type 2 [14] and Type 1 diabetes [13] as well as results from another small study reporting improvements in Emotion Regulation-Skill scores [25] with reductions in A_1c levels [28] in adults with Type 2 diabetes using a group emotional regulation skill behavioral therapy based intervention. In addition to what improved emotion regulation skill might do in reducing glucose levels [12], enhancement of emotion regulation skill may also lead to a more healthy psychological state enabling adults with Type 2 diabetes to better use positive coping strategies to improve glycemic management. Further study in a larger sample, using a non-emotion focused attentional control, to evaluate the efficacy and generalizability of these findings are warranted.

CONCLUSION

Data from both studies, above, suggest that diabetes distress in adults is linked with heightened negative emotionality (Emotion Regulation-Experience) and reduced skill at emotional regulation (Emotion Regulation-Skill) in adults, both of which are related to elevated A_1c levels and that these relationships are stronger than that with diabetes self-care. Given other studies examining the construct of emotionality [17, 29], and preliminary results from small treatment studies targeting emotionality/emotional regulation [25, 28], these data suggest that diabetes distress and A_1c may be improved, especially, in those with diabetes and difficulties with emotionality.

HIGHLIGHTS.

• Diabetes-related distress is directly related to one’s reduced ability to regulate negative emotional regulation.

• In Study 1, both diabetes distress and regulation of negative emotion are related and both influence A_1c levels to a greater degree than general diabetes self-care.

• In Study 2, preliminary data suggests that an emotion-focused intervention can reduce both A_1c levels and diabetes distress.