Free
Original Contribution  |   September 2019
High Prevalence of Diabetes Distress in a University Population
Author Notes
  • From the Department of Family Medicine at Ohio University Heritage College of Osteopathic Medicine in Athens (Drs Beverly, Rennie, and Guseman); the Diabetes Institute at Ohio University in Athens (Drs Beverly, Guseman, and Healy); the Department of Medicine at Ohio University Heritage College of Osteopathic Medicine in Athens (Ms Rodgers); the Department of Specialty Medicine at Ohio University Heritage College of Osteopathic Medicine in Athens (Dr Healy); and the OhioHealth Physician Group Heritage College Diabetes & Endocrinology in Athens (Dr Healy). 
  • Financial Disclosures: None reported. 
  • Support: This study was funded by American Osteopathic Association Grant No. 1291708718. 
  •  *Address correspondence to Elizabeth A. Beverly, PhD, Associate Professor, Department of Family Medicine, Ohio University Heritage College of Osteopathic Medicine, Athens, OH 45701. Email: beverle1@ohio.edu
     
Article Information
Endocrinology / Psychiatry / Diabetes
Original Contribution   |   September 2019
High Prevalence of Diabetes Distress in a University Population
The Journal of the American Osteopathic Association, September 2019, Vol. 119, 556-568. doi:10.7556/jaoa.2019.099
The Journal of the American Osteopathic Association, September 2019, Vol. 119, 556-568. doi:10.7556/jaoa.2019.099
Abstract

Context: Diabetes distress is an affective condition that addresses an individual's frustrations, worries, and concerns about living with diabetes. It is associated with fewer self-care behaviors, suboptimal glycemic control, and lower quality of life (QOL). For these reasons, diabetes care guidelines recommend routine assessment of diabetes distress.

Objective: To assess diabetes distress in a university population.

Methods: This study was conducted using a descriptive, cross-sectional design. Researchers assessed diabetes distress and other psychosocial factors via an electronic anonymous survey among students, faculty, and staff at a large university in the Midwest.

Results: A total of 173 participants completed the survey (mean [SD] age, 35.1 [16.7] years), with 108 [62.4%] female and 142 [82.1%] white participants). Eighty-five participants had type 1 diabetes mellitus (T1DM), and 88 had type 2 diabetes mellitus (T2DM). Of the 85 T1DM participants, 23 (27.4%) reported high diabetes distress, and 27 (30.7%) T2DM participants reported high diabetes distress. Sixteen T1DM (18.8%) and 15 T2DM (17.0%) participants screened positive for severe depression. Severe depression was associated with high distress for both T1DM and T2DM participants (T1DM: χ2=28.845, P<.001; T2DM: χ2=20.679, P<.001). Participants with T1DM reported more frequent self-care behaviors (mean [SD], 62.3 [17.1] vs 52.2 [19.2]; P<.001), but lower diabetes QOL (63.3 [14.1] vs 68.5 [15.5]; P=.021) compared with T2DM participants. No differences were observed in depressive symptoms, diabetes self-efficacy, and coping styles. Linear regression models showed that high diabetes distress scores (standardized β=.323, P=.025; standardized β=.604, P<.001) were independently associated with higher hemoglobin A1C levels and lower diabetes QOL after controlling for depressive symptoms, age, and gender in T1DM participants. Similarly, high diabetes distress scores (standardized β=.434, P<.001) were associated with lower diabetes QOL in T2DM participants after controlling for the same variables.

Conclusion: High diabetes distress levels were associated with lower diabetes QOL for both T1DM and T2DM participants. These findings suggest that attending or working at a university may be associated with high diabetes distress scores and lower diabetes QOL. Additional research with a larger, more diverse sample from multiple universities is needed to confirm these findings.

Diabetes is one of the most significant chronic health problems in the United States, affecting approximately 9.4% of the population or 30.3 million people.1 Diabetes management requires people with diabetes to follow specific self-care recommendations, including engaging in regular physical activity, following a healthy diet, adopting appropriate diabetes technology, frequently monitoring blood glucose levels and acting appropriately on results, taking diabetes medication, and attending clinical appointments.2,3 These behaviors are critically linked to improved glycemic control and the prevention of complications; however, incorporating them into daily life can be challenging.2-4 Nearly half of US adults with diabetes are not meeting recommended targets for diabetes care.4 Frustration with meeting recommended glycemic and behavioral targets may be reflected in new or existing psychosocial difficulties that further impede people's efforts to manage diabetes.5-12 One important psychosocial difficulty unique to people with diabetes is diabetes distress. 
Diabetes distress refers specifically to the negative emotional experience of living with diabetes.13,14 It is not a proxy for depression or anxiety.15 Diabetes distress does not assume psychopathology and it is not considered a comorbid psychiatric disorder.16 Distress reflects (1) frustration with self-care (eg, diet, exercise, medications, blood glucose monitoring); (2) apprehensions about the future and the possibility of complications developing; (3) concerns about the quality and cost of medical care; and (4) perceived lack of support from family members and/or friends.16-18 High levels of diabetes distress are common, with a prevalence of 22% in research populations.19 High levels of diabetes distress are associated with fewer self-care behaviors,10,18 suboptimal glycemic control,16,18,20,21 increased morbidity,22 and lower quality of life (QOL).23,24 For these reasons, the American Diabetes Association recommends routine assessment of diabetes distress in all populations of people with diabetes.25 
One population that has not been assessed for diabetes distress, to our knowledge, is the university population. Approximately 20.2 million students attended the 6834 Title IV degree-granting institutions of higher education in the fall of 2016.26 These US colleges and universities employed roughly 4 million faculty and staff.26 For students, college is an exciting, challenging, and anxiety-provoking time that introduces new barriers to diabetes, such as inconsistent schedules, time-management difficulties, stress, changes to diet and exercise routines, and social support issues. Faculty and staff also may experience similar barriers given the shared social context, heavy workloads, and increased expectations of the demanding academic environment.27 For these reasons, assessment of diabetes distress in the university population is needed. Thus, in the present study, we sought to determine the prevalence of diabetes distress in a large university population in the Midwest. We hypothesized that high diabetes distress scores would be associated with higher hemoglobin A1c (HbA1C) levels, fewer diabetes self-care behaviors, and lower diabetes QOL in students, faculty, and staff with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). 
Methods
The University Office of Research Compliance approved the protocol and all recruitment procedures and materials. Participants were recruited from a large public university located in the Midwest. Adults with type 1 or type 2 diabetes diagnosed by a physician; aged 18 years or older; able to read and speak English; and a current student, faculty member, or staff at the university were eligible to participate in the study. An electronic, anonymous survey was distributed to all students, faculty, and staff via the university LISTSERV. A total of 24,155 undergraduate, graduate, and professional students were enrolled in the fall of 2017 at the main campus of the university,28 and 1505 faculty and 1082 staff were employed by the university.29 The survey opened on December 14, 2017, and a reminder email was sent on January 3, 2018. Participation in the study was completely voluntary. Participants received a $15.00 gift card as compensation for participating. After completing the survey, participants clicked on a new Qualtrics link where they could provide their personal information to receive a gift card. This process ensured that their responses were not linked to their name or email address. Due to the anonymous nature of the study, a participant did not have to complete the entire survey to receive the gift card. 
Measures
In addition to sociodemographic factors (eg, age, sex, race/ethnicity, education level, marital status, occupation) and health factors (eg, duration of diabetes, self-reported HbA1C, diabetes medications, height, weight), participants completed the following measures: 
Type 1 Diabetes Distress Scale (T1-DDS)30
This 28-item measure assesses 7 sources of diabetes distress common among adults with T1DM. The 7 subscales include: (1) Powerlessness; (2) Negative Social Perceptions; (3) Physician Distress; (4) Friend/Family Distress; (5) Hypoglycemia Distress; (6) Management Distress; and (7) Eating Distress. Patients are asked to indicate the degree to which each item may have been a problem using a 6-point scale, ranging from “not a problem” to “a very serious problem.” Mean cut points for scoring are little or no distress (1.0-1.4), low distress (1.5-1.9); moderate distress (2.0-2.9); and high distress (≥3).18 The scale demonstrates good reliability (α=.91; subscale range α=.76-.88) and strong test-retest reliability (r=0.74). High distress is associated with poor glycemic control. 
Type 2 Diabetes Distress Scale (T2-DDS)31
This 17-item scale assesses diabetes distress via 4 factors: (1) emotional burden, (2) physician-related distress, (3) regimen-related distress, and (4) interpersonal distress. Patients are asked to consider the degree to which each of the 17 items may have distressed or bothered them in the past month using a 6-point scale, ranging from “not a problem” to “a very serious problem.” Mean cut points for scoring are little or no distress (<2.0); moderate distress (2.0-2.9); and high distress (≥3.0).19 A mean item score of 3 or higher for the total score or for each of the 4 subscales indicates a level of distress worthy of clinical attention. The scale demonstrates good reliability (α=.93; subscales range, α=.88-.90).31 High diabetes distress scores are associated with worsening glycemic control, reduced self-care, and low self-efficacy.19 
Patient Health Questionnaire-9 (PHQ-9)32
This 9-item questionnaire pertains to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria for major depressive disorder: (1) anhedonia; (2) depressed mood; (3) trouble sleeping; (4) feeling tired; (5) change in appetite; (6) guilt, self-blame, or worthlessness; (7) trouble concentrating; (8) feeling slowed down or restless; and (9) suicidal ideation.33 Scores range from 0 to 27. A cutoff score of 9 has a sensitivity of 88% and a specificity of 88% for detecting major depressive disorder compared with the clinical interview for depression. The following cutoff scores were used to represent minimal depression, moderate depression, and moderately severe to severe depression: ≤4, 5–14, and >14. 
Self-care Inventory-R (SCI-R)33
This 15-item survey measures the self-reported frequency of self-care behaviors on a 5-point Likert scale and has been validated for use with T2DM populations. Four additional items inquiring about checking feet, eating heart healthy foods, looking at blood glucose patterns, and knowing about blood pressure, HbA1C, and lipids were included. 
Coping Styles34
This 15-item measure assesses emotional coping and self-controlled coping. Emotion-based coping strategies include anger, impatience, and anxiety, indicated by angry statements, impulsive actions, anxious behaviors (nervous, worried, upset, difficulty relaxing), and avoidant behaviors (not doing something or giving up). Self-controlled coping strategies include stoicism and pragmatism, indicated by statements of controlling one's emotions and problem-solving to alleviate frustration. Patients are asked to rate each item on a 4-point scale, ranging from “not at all like me” to “very much like me.” This measure has been validated in diabetes populations. 
Confidence in Diabetes Self-Care Scale (CIDS)35
This validated 21-item measure assessing self-efficacy in patients with diabetes, specifically, the confidence individuals have in their ability to perform self-care tasks.36 Patients rate each item on a 5-point scale ranging from “No, I am sure I cannot” to “Yes, I am sure I can.” The CIDS has high internal reliability (α=.90).36 
Diabetes Quality of Life Scale (DQOL)37
This survey has 39 core items rated on a 5-point Likert scale and yields a total score with subscales (life satisfaction, diabetes impact, diabetes-related worry). The questions are negatively worded; therefore, higher scores indicate lower QOL. The psychometric properties of the DQOL are well-established,37-39 and it has been tested in both T1DM and T2DM patients.38 
Survey scores for the SCI-R, Coping Styles, CIDS, and DQOL were converted to a 0 to 100-point scale for ease of interpretation by subtracting the minimum possible item score from the individual's averaged raw score, multiplied by 100. This value is then divided by the difference of the minimum possible item score subtracted from the maximum possible item score ([mean raw score − minimum] × 100)/(maximum − minimum).40 Data are expressed as the mean (SD) unless otherwise indicated. 
Data Collection
Participants completed the survey via the online questionnaire service Qualtrics. To consent, participants clicked a radio button indicating “Yes, I consent to participate in this study. I may withdraw my participation at any time.” To decline, participants clicked a radio button indicating “I decline to participate.” To avoid coercion, the online screen to the survey and the informed consent document both specified the voluntary nature of participation. No researchers were present when potential participants decided to participate or decline and, thus, they may have felt less pressure than in a face-to-face consent process. Participants with questions about the study were directed to email or telephone the research investigators. Completion of the survey took approximately 30 to 45 minutes. Qualtrics permitted the research team to download participants’ survey responses into a spreadsheet without including identifying information to ensure anonymity. 
Data Analysis
Basic sociodemographic characteristics of participants were assessed using descriptive statistics. Frequencies of individual question responses were also calculated. The SCI-R, Coping Styles, CIDS, and DQOL survey scores were converted to a 0- to 100-point scale for ease of interpretation by subtracting the minimum possible item score from the respondent's averaged raw score, multiplied by 100. The value was then divided by the difference of the minimum possible item score ([mean raw score – minimum] × 100)/(maximum – minimum).33 
Independent sample t tests were conducted to examine differences in survey scores by type of diabetes. In addition, χ2 tests or Fisher exact tests and independent sample t tests were conducted to examine differences in sociodemographic factor and health characteristics by type of diabetes. Finally, 6 linear regression analyses controlling for age, gender, and depressive symptoms in each model were conducted for T1DM and T2DM participants to assess the relationship between diabetes distress and glycemic control, self-care, and diabetes QOL. Statistical significance was defined as P<.05. All analyses were conducted with SPSS statistical software version 25.0 (IBM). 
Results
A total of 207 students, faculty, and staff consented to participate in the study. Thirty-four participants did not complete the surveys and were removed from the analyses. The final sample included 173 participants (56 students and 117 faculty/staff) with complete data (Table 1). The mean (SD) age of participants was 35.1 (16.7) years, 108 (62.4%) identified as female, 142 (82.1%) were white, and 74 (42.8%) had a 4-year degree or higher (Table 1). Of the 173 participants, 85 (49.1%) self-reported a diagnosis of T1DM and 88 (50.9%) self-reported a diagnosis of T2DM. Overall, the participants had an average HbA1C of 7.3% (1.4%) and a diabetes duration of 10.5 (9.5) years. The average body mass index (BMI) was 30.0 (7.6) kg/m2, 43.4% reported taking insulin, and 98.3% had insurance coverage. Participants with T1DM were younger (24.5 [9.3] vs 45.4 (15.8) years, t =−10.567, P<.001), had a longer diabetes duration (12.8 [8.8] vs 8.2 [9.6] years, t=3.203, P=.002), a higher HbA1C (7.8% [1.6%] vs 6.8% (1.0%); t=5.022, P<.001), and a lower BMI (26.6 [6.6] kg/m2 vs 33.2 (7.0) kg/m2; t=−6.293, P<.001) compared with the participants with T2DM. Also, participants with T1DM differed by type of diabetes medication (χ2=127.780, df=4, P<.001) and level of education (χ2=58.149, df=8, P<.001) compared with participants with T2DM. No differences were observed by gender, race, ethnicity, or insurance coverage. No gender differences in high diabetes distress scores (χ2=0.023, df=1, P=.880) or severe depression (P=.514) were observed. 
Table 1.
Diabetes Distress in a University Population: Participant Demographic and Health Characteristicsa
Variable Total (N=173) Type 1 (n=85) Type 2 (n=88) P Value
Age, y 35.1 (16.7) 24.5 (9.3) 45.4 (15.8) <.001
Gender       .241
Female 108 (62.4) 59 (69.4) 49 (55.7)  
Male 62 (35.8) 25 (29.4) 37 (42.0)  
Other 2 (1.2) 1 (1.2) 1 (1.1)  
Prefer not to answer 1 (0.6) 0 (0) 1 (1.1)  
Race       .074
 American Indian 1 (0.6) 0 (0) 1 (1.1)  
 Asian 13 (7.5) 3 (3.5) 10 (11.4)  
 Black 10 (5.8) 3 (5.5) 6 (9.2)  
 Mixed 3 (1.7) 1 (1.1) 2 (2.3)  
 Other 3 (1.7) 2 (2.4) 1 (1.1)  
 Pacific Islander 1 (0.6) 0 (0) 1 (1.1)  
 White 142 (82.1) 77 (90.6) 65 (73.9)  
Ethnicity       .669
 Hispanic/Latino 5 (2.9) 2 (2.4) 3 (3.4)  
Education       <.001
 High school 8 (4.6) 3 (3.5) 5 (5.7)  
 Current undergraduate 62 (35.8) 52 (61.2) 10 (11.4)  
 Some college 16 (9.2) 5 (5.9) 11 (12.5)  
 2-year degree 13 (7.5) 2 (2.4) 11 (12.5)  
 4-year degree 18 (10.4) 10 (10.6) 9 (10.2)  
 Current graduate student 9 (5.2) 5 (5.9) 4 (4.5)  
 Some graduate work 4 (2.3) 1 (1.26) 3 (3.4)  
 Master's degree 18 (10.4) 6 (7.1) 12 (13.6)  
 Doctoral/professional degree 25 (14.5) 2 (2.4) 23 (26.1)  
Health Insuranceb       .816
 No coverage 3 (1.7) 1 (1.2) 2 (2.3)
 Medicaid and/or Medicare 23 (13.3) 13 (15.3) 10 (11.4)
 Private 134 (77.5) 64 (75.3) 70 (79.5)
 Other 11 (6.4) 5 (5.9) 6 (6.8)
Hemoglobin A1c, % 7.3 (1.4) 7.8 (1.6) 6.8 (1.0) <.001
Body Mass Index 30.0 (7.6) 26.6 (6.6) 33.2 (16.7) <.001
Diabetes Duration, y 10.5 (9.5) 12.8 (8.8) 8.2 (9.6) .002
Diabetes Treatment <.001
 Diet and exercise 24 (13.9) 6 (7.1) 18 (20.5)
 Oral medication 50 (28.9) 1 (1.2) 49 (55.7)
 Insulin 750 (43.4) 73 (85.9) 2 (2.3)
 Insulin and oral medication 16 (9.2) 4 (4.7) 12 (13.6)
 Other 8 (4.6) 1 (1.2) 7 (8.0)

a Data are presented as No.(%) unless otherwise indicated.

b Values were missing for health insurance for 2 participants.

Table 1.
Diabetes Distress in a University Population: Participant Demographic and Health Characteristicsa
Variable Total (N=173) Type 1 (n=85) Type 2 (n=88) P Value
Age, y 35.1 (16.7) 24.5 (9.3) 45.4 (15.8) <.001
Gender       .241
Female 108 (62.4) 59 (69.4) 49 (55.7)  
Male 62 (35.8) 25 (29.4) 37 (42.0)  
Other 2 (1.2) 1 (1.2) 1 (1.1)  
Prefer not to answer 1 (0.6) 0 (0) 1 (1.1)  
Race       .074
 American Indian 1 (0.6) 0 (0) 1 (1.1)  
 Asian 13 (7.5) 3 (3.5) 10 (11.4)  
 Black 10 (5.8) 3 (5.5) 6 (9.2)  
 Mixed 3 (1.7) 1 (1.1) 2 (2.3)  
 Other 3 (1.7) 2 (2.4) 1 (1.1)  
 Pacific Islander 1 (0.6) 0 (0) 1 (1.1)  
 White 142 (82.1) 77 (90.6) 65 (73.9)  
Ethnicity       .669
 Hispanic/Latino 5 (2.9) 2 (2.4) 3 (3.4)  
Education       <.001
 High school 8 (4.6) 3 (3.5) 5 (5.7)  
 Current undergraduate 62 (35.8) 52 (61.2) 10 (11.4)  
 Some college 16 (9.2) 5 (5.9) 11 (12.5)  
 2-year degree 13 (7.5) 2 (2.4) 11 (12.5)  
 4-year degree 18 (10.4) 10 (10.6) 9 (10.2)  
 Current graduate student 9 (5.2) 5 (5.9) 4 (4.5)  
 Some graduate work 4 (2.3) 1 (1.26) 3 (3.4)  
 Master's degree 18 (10.4) 6 (7.1) 12 (13.6)  
 Doctoral/professional degree 25 (14.5) 2 (2.4) 23 (26.1)  
Health Insuranceb       .816
 No coverage 3 (1.7) 1 (1.2) 2 (2.3)
 Medicaid and/or Medicare 23 (13.3) 13 (15.3) 10 (11.4)
 Private 134 (77.5) 64 (75.3) 70 (79.5)
 Other 11 (6.4) 5 (5.9) 6 (6.8)
Hemoglobin A1c, % 7.3 (1.4) 7.8 (1.6) 6.8 (1.0) <.001
Body Mass Index 30.0 (7.6) 26.6 (6.6) 33.2 (16.7) <.001
Diabetes Duration, y 10.5 (9.5) 12.8 (8.8) 8.2 (9.6) .002
Diabetes Treatment <.001
 Diet and exercise 24 (13.9) 6 (7.1) 18 (20.5)
 Oral medication 50 (28.9) 1 (1.2) 49 (55.7)
 Insulin 750 (43.4) 73 (85.9) 2 (2.3)
 Insulin and oral medication 16 (9.2) 4 (4.7) 12 (13.6)
 Other 8 (4.6) 1 (1.2) 7 (8.0)

a Data are presented as No.(%) unless otherwise indicated.

b Values were missing for health insurance for 2 participants.

×
Of the 85 participants with T1DM, 23 (27.4%) reported high diabetes distress (Table 2). The subscales with the highest distress scores included Powerlessness (27 [48.8%]), Management Distress (31 [36.9%]), and Eating Distress (29 [34.5%]). For the 88 T2DM participants, 27 (30.7%) reported high diabetes distress (Table 2). The subscales with the highest distress scores included Regimen-Related Distress (39 [44.3%]), Emotional Burden (28 [31.8%]), and Interpersonal Distress (27 [30.7%]). Of importance, 16 (18.8%) T1DM participants and 15 (17.0%) T2DM participants also screened positive for severe depression. For both T1DM and T2DM participants, severe depression was associated with high distress (T1DM: χ2=28.845, df=1, P<.001; T2DM: χ2=20.679, df=1, P<.001). Additional analyses revealed that severe depression was associated with all 7 T1DM distress subscales and 3 of the 4 T2DM subscales, with the exception being High Physician-Related Distress (χ2=2.279, df=1, P=.131). No gender differences in high diabetes distress scores (P=.239) or severe depression (P=.226) were observed. 
Table 2.
Type 1 and Type 2 Diabetes Mellitus Participants’ Psychosocial Assessment Results (N=173)
Assessment Total Mean (SD) Type 1 Diabetes Mean (SD) Type 2 Diabetes Mean(SD) P Value
Depressive Symptoms 7.8 (6.4) 7.8 (6.5) 8.0 (6.4) .865
Diabetes Self-care 57.4 (18.9) 62.3 (17.1) 52.2 (19.2) <.001
Diabetes Self-efficacy 69.1 (23.5) 67.7 (25.9) 70.4 (20.9) .462
Coping
  Emotional 43.0 (21.3) 45.4 (19.9) 40.7 (22.5) .151
  Controlled 50.5 (16.7) 52.5 (16.5) 48.5 (16.78) .120
Diabetes Quality of Life 36.2 (16.6) 38.5 (15.8) 34.0 (17.1) .075
Table 2.
Type 1 and Type 2 Diabetes Mellitus Participants’ Psychosocial Assessment Results (N=173)
Assessment Total Mean (SD) Type 1 Diabetes Mean (SD) Type 2 Diabetes Mean(SD) P Value
Depressive Symptoms 7.8 (6.4) 7.8 (6.5) 8.0 (6.4) .865
Diabetes Self-care 57.4 (18.9) 62.3 (17.1) 52.2 (19.2) <.001
Diabetes Self-efficacy 69.1 (23.5) 67.7 (25.9) 70.4 (20.9) .462
Coping
  Emotional 43.0 (21.3) 45.4 (19.9) 40.7 (22.5) .151
  Controlled 50.5 (16.7) 52.5 (16.5) 48.5 (16.78) .120
Diabetes Quality of Life 36.2 (16.6) 38.5 (15.8) 34.0 (17.1) .075
×
On average, participants did not exhibit clinical levels of depression (7.8 [6.4]; Table 2). Regarding diabetes management, they reported carrying out the majority of their self-care behaviors as recommended (57.4 [18.9]) and felt moderately confident in their ability to manage their diabetes (69.1 [23.5]). Participants reported moderately low diabetes QOL (36.2 [16.6]), with life satisfaction showing the most negative subscale score (46.2 [23.8]). Participants expressed both emotional (43.0 [21.3]) and self-controlled (50.5 [16.7]) coping strategies, with neither strategy dominating. Comparisons between participants revealed that participants with T1DM reported more frequent self-care behaviors (62.3 [17.1] vs 52.2 [19.2]; P<.001) but lower diabetes impact (33.9 [15.0] vs 25.2 [14.8], P<.001) and lower diabetes-related worry (37.3 [21.8] vs 26.2 [20.0], P=.001) on the diabetes QOL subscales. No differences were observed in depressive symptoms, diabetes self-efficacy, emotional coping, or self-controlled coping. 
Finally, linear regression models presented in Table 3 examined associations among diabetes distress, HbA1C levels, diabetes self-care, and diabetes QOL in participants with T1DM and T2DM. For participants with T1DM, high scores of diabetes distress (standardized β= .323, P=.025) were independently associated with higher HbA1C levels after controlling for depressive symptoms, age, and gender; this model accounted for 19% of the variation in HbA1C. Also, high scores of distress (standardized β=.604, P<.001) were independently associated with lower diabetes QOL after controlling for depressive symptoms, age, and gender; this model accounted for 65% of the variation in diabetes QOL. Furthermore, analyses revealed that high scores of diabetes distress were associated with the 3 QOL subscales: Lower Diabetes Life Satisfaction (standardized β= .632, P<.001, R2=0.50), Diabetes Impact (standardized β=.438, P<.001, R2=0.48), and Diabetes-Related Worry (standardized β=.462, P<.001, R2=0.47) after controlling for depressive symptoms, age, and gender (Table 3). Diabetes distress was not associated with diabetes self-care behaviors in participants with T1DM. 
Table 3.
Linear Regression Models Examining Associations Among Diabetes Distress and Glycemic Control, Self-Care, and Diabetes Quality of Life in Adults With Type 1 and Type 2 Diabetes Mellitus
Predictors Standardized β. P Value
Type 1 Diabetes Mellitus (n=85)
Model 1: Glycemic Control, R2=0.19
 Age −0.231 .029
 Gender −0.218 .038
 Depressive symptoms −0.092 .524
 Diabetes distress score 0.323 .025
Model 2: Diabetes Self-Care, R2=0.08
 Age 0.714 .478
 Gender −0.078 .483
 Depressive symptoms 0.053 .729
 Diabetes distress score −0.290 .056
Model 3: Diabetes Quality of Life, R2=0.65
 Age 0.023 .730
 Gender −0.045 .507
 Depressive symptoms 0.234 .013
 Diabetes distress score 0.604 <.001
Model 3a: Diabetes Quality of Life Subscale: Life Satisfaction, R2=0.50
 Age −0.013 .872
 Gender 0.004 .962
 Depressive symptoms 0.104 .353
 Diabetes distress score 0.632 <.001
Model 3b: Diabetes Quality of Life Subscale: Diabetes Impact, R2=0.48
 Age 0.083 .321
 Gender −0.103 .219
 Depressive symptoms 0.295 .012
 Diabetes distress score 0.438 <.001
Model 3c: Diabetes Quality of Life Subscale: Diabetes-Related Worry, R2=0.47
 Age −0.044 .599
 Gender −0.091 .278
 Depressive symptoms 0.258 .027
 Diabetes distress score 0.462 <.001
Type 2 Diabetes Mellitus (n=88)
Model 4: Glycemic Control, R2=0.12
 Age 0.317 .009
 Gender 0.024 .830
 Depressive symptoms 0.102 .431
 Diabetes distress score 0.249 .062
Model 5: Diabetes Self-Care, R2=0.12
 Age −0.047 .680
 Gender −0.034 .748
 Depressive symptoms −0.159 .207
 Diabetes distress score −0.248 .055
Model 6: Diabetes Quality of Life, R2=0.67
 Age −0.132 .059
 Gender 0.033 .617
 Depressive symptoms 0.443 <.001
 Diabetes distress score 0.434 <.001
Model 6a: Diabetes Quality of Life Subscale: Life Satisfaction, R2=0.67
 Age −0.060 .384
 Gender 0.004 .951
 Depressive symptoms 0.465 <.001
 Diabetes distress score 0.450 <.001
Model 6b: Diabetes Quality of Life Subscale: Diabetes Impact, R2=0.45
 Age −0.183 .043
 Gender 0.097 .247
 Depressive symptoms 0.357 <.001
 Diabetes distress score 0.312 .002
Model 6c: Diabetes Quality of Life Subscale: Diabetes-Related Worry, R2=0.28
 Age −0.160 .121
 Gender −0.106 .270
 Depressive symptoms 0.175 .123
 Diabetes distress score 0.317 .007
Table 3.
Linear Regression Models Examining Associations Among Diabetes Distress and Glycemic Control, Self-Care, and Diabetes Quality of Life in Adults With Type 1 and Type 2 Diabetes Mellitus
Predictors Standardized β. P Value
Type 1 Diabetes Mellitus (n=85)
Model 1: Glycemic Control, R2=0.19
 Age −0.231 .029
 Gender −0.218 .038
 Depressive symptoms −0.092 .524
 Diabetes distress score 0.323 .025
Model 2: Diabetes Self-Care, R2=0.08
 Age 0.714 .478
 Gender −0.078 .483
 Depressive symptoms 0.053 .729
 Diabetes distress score −0.290 .056
Model 3: Diabetes Quality of Life, R2=0.65
 Age 0.023 .730
 Gender −0.045 .507
 Depressive symptoms 0.234 .013
 Diabetes distress score 0.604 <.001
Model 3a: Diabetes Quality of Life Subscale: Life Satisfaction, R2=0.50
 Age −0.013 .872
 Gender 0.004 .962
 Depressive symptoms 0.104 .353
 Diabetes distress score 0.632 <.001
Model 3b: Diabetes Quality of Life Subscale: Diabetes Impact, R2=0.48
 Age 0.083 .321
 Gender −0.103 .219
 Depressive symptoms 0.295 .012
 Diabetes distress score 0.438 <.001
Model 3c: Diabetes Quality of Life Subscale: Diabetes-Related Worry, R2=0.47
 Age −0.044 .599
 Gender −0.091 .278
 Depressive symptoms 0.258 .027
 Diabetes distress score 0.462 <.001
Type 2 Diabetes Mellitus (n=88)
Model 4: Glycemic Control, R2=0.12
 Age 0.317 .009
 Gender 0.024 .830
 Depressive symptoms 0.102 .431
 Diabetes distress score 0.249 .062
Model 5: Diabetes Self-Care, R2=0.12
 Age −0.047 .680
 Gender −0.034 .748
 Depressive symptoms −0.159 .207
 Diabetes distress score −0.248 .055
Model 6: Diabetes Quality of Life, R2=0.67
 Age −0.132 .059
 Gender 0.033 .617
 Depressive symptoms 0.443 <.001
 Diabetes distress score 0.434 <.001
Model 6a: Diabetes Quality of Life Subscale: Life Satisfaction, R2=0.67
 Age −0.060 .384
 Gender 0.004 .951
 Depressive symptoms 0.465 <.001
 Diabetes distress score 0.450 <.001
Model 6b: Diabetes Quality of Life Subscale: Diabetes Impact, R2=0.45
 Age −0.183 .043
 Gender 0.097 .247
 Depressive symptoms 0.357 <.001
 Diabetes distress score 0.312 .002
Model 6c: Diabetes Quality of Life Subscale: Diabetes-Related Worry, R2=0.28
 Age −0.160 .121
 Gender −0.106 .270
 Depressive symptoms 0.175 .123
 Diabetes distress score 0.317 .007
×
For participants with T2DM, high scores of diabetes distress (standardized β=.434, P<.001) were independently associated with lower diabetes QOL after controlling for depressive symptoms, age, and gender; this model accounted for 67% of the variation in diabetes QOL (Table 3). In addition, high diabetes distress scores were associated with the 3 QOL subscales: Lower Diabetes Life Satisfaction (standardized β=.450, P<.001, R2=0.67), Diabetes Impact (standardized β=.312, P=.002, R2=0.45), and Diabetes-Related Worry (standardized β=.317, P=.007, R2=0.28) after controlling for depressive symptoms, age, and gender. However, diabetes distress was not associated with HbA1C levels or diabetes self-care in participants with T2DM. 
Students with T1DM
Additional analyses including the students with T1DM (n=56; mean [SD] age, 21.5 [5.2] years). Forty-five of these participants were women (80.4%) and 50 were white (89.3%). Their mean (SD) HbA1C was 8.2% (1.6%); 21.4% had HbA1C less than 7.0%; their duration of illness was 10.3 (5.4) years; and their BMI was 25.3 (4.2) kg/m2. Analyses revealed that 20 participants (35.7%) reported high diabetes distress. The subscales with the highest distress scores included Powerlessness (32 [57.1%]), Management Distress (28 [50.0%]), and Eating Distress (24 [42.9%]). Nearly one-quarter (13 [23.2%]) of T1DM participants screened positive for severe depression and Fisher exact test results showed that severe depression was associated with high distress (P<.001). No gender differences were observed by high diabetes distress scores (P=.390) or severe depression (P=.206). Linear regression models found that high diabetes distress scores (standardized β=.718, P<.001) were independently associated with lower diabetes QOL after controlling for depressive symptoms, age, and gender; this model accounted for 67% of the variation in diabetes QOL. Furthermore, high diabetes distress scores were associated with the 3 QOL subscales: lower diabetes life satisfaction (standardized β=.765; R2=0.58, P<.001), diabetes impact (standardized β=.677; R2=0.49, P<.001), diabetes-related worry (standardized β=.633; R2=0.44, P<.001), after controlling for depressive symptoms, age, and gender. Using the same model, diabetes distress was not associated with HbA1C levels or self-care. 
Discussion
This cross-sectional descriptive study assessed diabetes distress in a large university population in the Midwest. Overall, students, faculty, and staff reported high levels of diabetes distress. Participants who screened positive for severe depression were more likely to have high diabetes distress levels. For participants with T1DM, high diabetes distress levels were independently associated with higher HbA1C levels and lower diabetes QOL, including the 3 subscales: life satisfaction, diabetes impact, diabetes-related worry. Among students with T1DM, high diabetes distress levels were independently associated with lower QOL, including the 3 subscales, but not HbA1C levels or diabetes self-care. Similarly, for participants with T2DM, high distress levels were independently associated with lower diabetes QOL and its 3 subscales and not HbA1C levels or diabetes self-care. These findings suggest independent associations with diabetes distress and diabetes QOL. Additional research is needed to confirm these findings. If confirmed, interventions designed to address life satisfaction, diabetes impact, and diabetes-related worry among students, faculty, and staff presenting with high diabetes distress may be necessary to reduce diabetes distress and improve QOL. 
Some of the findings in this study are consistent with prior research. First, the high diabetes distress scores found among the students, faculty, and staff at this university mirror those found in other studies.15,20 Other cross-sectional studies using the Diabetes Distress Scale found similar rates of diabetes distress, including Baek et al41 (27.7%), Burns et al42 (22.4%), Gariepy et al43 (23.0%), Fisher et al16 (51.3%), Holmes-Truscott et al44 (29.0%), Smith et al45 (22.5%), Wong et al46 (39.0%), and Zhu et al47 (33.8%). A recent systematic review and meta-analysis found that diabetes distress was significantly higher in samples with a majority of women and in samples with a higher prevalence of comorbid depression.48 No gender differences were observed in this study, though diabetes distress was associated with screening positive for severe depression. 
Second, no association was observed between diabetes distress and glycemic control among participants with T2DM despite high levels of diabetes distress. This finding counters a large body of research that has shown diabetes distress is associated with suboptimal glycemic control16,18,20,21 and lower diabetes QOL.24,25 However, this lack of significance may be explained by the university context. Seventy-four of 88 T2DM participants (84.1%) were faculty or staff employed by the university and, theoretically, were healthy enough to work and receive the university's private insurance. People with very high HbA1C levels and/or severe complications most likely would be unable to work and, consequently, would be excluded from this study. Furthermore, 69 of the 74 faculty and staff with T2DM (93.2%) had more than a high school education. The average age of the T2DM participants was younger (mean [SD], 45.4 [15.8] years) compared with samples in other studies exploring the relationship between diabetes distress and glycemic control.16,20 Thus, the T2DM participants may have been able to control their HbA1C levels as a result of better insurance coverage, which may have translated into more affordable diabetes medications, supplies, and diabetes education; higher educational attainment, which may have led to higher health literacy; and younger ages, which may have reflected less advanced disease. Other factors, such as the heavy workloads and increased expectations of the demanding academic environment, may be contributing to the high diabetes distress levels observed in this study.27 
Third, for participants with T1DM, high diabetes distress scores were independently associated with glycemic control, a finding that is supported by Hessler et al.49 However, the subanalysis with students with T1DM did not find an association with diabetes distress and glycemic control despite high levels of diabetes distress. This finding may be partially explained by the higher HbA1C levels, with one-fifth (21.4%) of the students reaching glycemic targets. Higher overall diabetes distress scores and less variability in HbA1C might explain the lack of statistical significance. This finding suggests that the university context may contribute unique factors that increase diabetes distress and lower diabetes quality of life. A large body of research documents the high rates of mental health problems (eg, depression, anxiety, self-injury, and psychological distress) in college student populations, which may play a role in the current study's observed high diabetes distress levels.50 Thus, this finding coupled with growing mental health concerns across college campuses warrant additional research. 
Fourth, this study adds to the growing literature on diabetes distress and QOL. Research has shown that higher levels of diabetes distress are associated with lower QOL in both adults with T1DM51 and T2DM.23,24,47 Diabetes QOL is the subjective evaluation of the perceived positive and negative aspects of diabetes self-management on daily life. Enhancing the QOL of people with diabetes is an important responsibility for all health care professionals as stated in the American Diabetes Association's standards of care.25 The association with glycemic control and QOL demonstrates that diabetes distress is both a physical and emotional health problem. Treating the whole person requires physicians to recognize that a person with diabetes is a combination of body, mind, and spirit. Thus, the assessment of diabetes distress reflects the first tenet of osteopathic philosophy.52 The management of diabetes necessitates an understanding of the bidirectional relationship between a person's diabetes (ie, body) and psychological well-being (ie, mind and spirit). For these reasons, diabetes management necessitates routine screening of diabetes distress. Opportunities for screening include at diagnosis, during regularly scheduled medical appointments, at the onset of complications, when complications dominate, during hospitalizations, and when problems with self-care, glycemic control, or QOL are identified.25,53 Validated measures are available for physicians to assess and monitor diabetes distress over time.30,54 
People with diabetes who screen high for diabetes distress should be referred to diabetes education to address specific areas of self-care that may be creating frustrations, worries, and concerns (eg, hypoglycemia, diet, blood glucose monitoring, complications).25 If patients’ diabetes distress levels do not improve and their self-care, glycemic control, and QOL continue to remain impaired, they should be referred to behavioral health professionals for evaluation and treatment.25 Behavioral care that focuses on the emotional side of diabetes is more likely to reduce high levels of diabetes distress.55 Effective interventions should incorporate problem-solving therapy, cognitive-behavioral techniques, motivational interviewing, and emotion regulation skills.56-59 If additional research confirms that students, faculty, and staff with diabetes experience high levels of diabetes distress, tailored interventions may be necessary. Universities are ideal settings for these behavioral interventions because they already have health and wellness facilities in place, and much of student, faculty, and staff time is spent on campus. Furthermore, university settings have an established means of communication to promote diabetes education and emotion-focused skills; students and employees can receive social support from each other, and the campus can institute policy changes to promote a healthier learning and work environment. 
Limitations
Study limitations include the homogeneity of the study sample with regard to race/ethnicity from 1 university in a Midwestern state, the unknown response rate, self-reported data, and the cross-sectional study design. The study sample was predominantly white, which is reflective of the racial and ethnic distribution in rural Appalachian Ohio where the university is located (94.6% white).60 Data from 1 university from a predominantly white sample that is not reflective of the US population limits the ability to generalize the findings to other institutions of higher education. Furthermore, the prevalence of diabetes on this college campus is not known. For this reason, we do not have a response rate for the survey and the findings are susceptible to nonresponse bias and selection bias, specifically the healthy worker effect. Thus, additional research is needed to confirm or refute these findings on other college and university campuses. 
Another limitation to the study is that the research team did not ask faculty and staff to differentiate themselves and their length of employment at the university. This information should be collected for future follow-up studies. The team did ask participants if they were current undergraduate or graduate/professional students. Furthermore, the survey did not include questions about the use of diabetes technology, which Tanenbaum et al61 found was associated with diabetes distress in younger age groups. Currently, we are conducting in-depth qualitative interviews about diabetes distress with a subset of participants and exploring the use of diabetes technology on campus. We are also conducting a community survey outside of the university to compare rates of diabetes distress between the 2 samples. Another limitation is that we did not include an option for participants who were working (eg, faculty/staff) at the university while talking classes. This option should be included in future research. 
Self-reported data was another limitation. For example, 8 participants with T1DM reported that they took a diabetes medication other than insulin; it is possible that these participants thought they could select more than 1 option to the question, which could explain those responses. Finally, the cross-sectional study design limits the ability to detect causal associations between diabetes distress, self-care, HbA1C, and QOL. Future longitudinal research should assess these variables with a larger, more racially and ethnically diverse sample among students, faculty, and staff from multiple universities in different geographic regions. 
Conclusion
Participating students, faculty, and staff with diabetes experienced high levels of diabetes distress at this university. These findings also suggest that living or working at this college campus may be associated with higher diabetes distress levels and lower diabetes QOL among students, faculty, and staff with T1DM and T2DM. Additional research with a larger, more diverse sample from multiple universities is needed to confirm these findings. If confirmed, physicians should give special attention to their patients with diabetes who attend or are employed by a university and consider screening them more frequently for diabetes distress and diabetes QOL. 
Author Contributions
All authors provided substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; all authors drafted the article or revised it critically for important intellectual content; all authors gave final approval of the version of the article to be published; and all authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. 
References
National Diabetes Statistics Report, 2017. Atlanta, GA: Centers for Disease Control and Prevention; 2017.
American Diabetes Association. Lifestyle management: Standards of Medical Care in Diabetes-2019. Diabetes Care. 2019;42(suppl 1):S46-S60.
American Diabetes Association. Diabetes technology: Standards of Medical Care in Diabetes-2019. Diabetes Care. 2019;42(suppl 1):S71-S80.
Carls G, Huynh J, Tuttle E, Yee J, Edelman SV. Achievement of glycated hemoglobin goals in the US remains unchanged through 2014. Diabetes Ther. 2017;8(4):863-873. doi: 10.1007/s13300-017-0280-5 [CrossRef] [PubMed]
Welch GW, Jacobson AM, Polonsky WH. The problem areas in diabetes scale an evaluation of its clinical utility. Diabetes Care. 1997;20(5):760-766. [CrossRef] [PubMed]
Lloyd CE, Smith J, Weinger K. Stress and diabetes: a review of the links. Diabetes Spectrum. 2005;18(2):121-127. [CrossRef]
Weinger K. Psychosocial issues and self-care [quiz 38]. Am J Nurs. 2007;107(6 suppl):34-38. [CrossRef] [PubMed]
Weinger K, Jacobson AM. Psychosocial and quality of life correlates of glycemic control during intensive treatment of type 1 diabetes. Patient Educ Couns. 2001;42(2):123-131. [CrossRef] [PubMed]
Albright TL, Parchman M, Burge SK. Predictors of self-care behavior in adults with type 2 diabetes: an RRNeST study. Fam Med. 2001;33(5):354-360. [PubMed]
Gonzalez JS, Delahanty LM, Safren SA, Meigs JB, Grant RW. Differentiating symptoms of depression from diabetes-specific distress: relationships with self-care in type 2 diabetes. Diabetologia. 2008;51(10):1822-1825. doi: 10.1007/s00125-008-1113-x [CrossRef] [PubMed]
Gonzalez JS, Safren SA, Cagliero E, et al Depression, self-care, and medication adherence in type 2 diabetes: relationships across the full range of symptom severity. Diabetes Care. 2007;30(9):2222-2227. [CrossRef] [PubMed]
Gonzalez JS, Safren SA, Delahanty LM, et al Symptoms of depression prospectively predict poorer self-care in patients with type 2 diabetes. Diabet Med. 2008;25(9):1102-1107. [CrossRef] [PubMed]
Fisher L, Mullan JT, Skaff MM, Glasgow RE, Arean P, Hessler D. Predicting diabetes distress in patients with type 2 diabetes: a longitudinal study. Diabet Med. 2009;26(6):622-627. [CrossRef] [PubMed]
Fisher L, Skaff MM, Mullan JT, et al Clinical depression versus distress among patients with type 2 diabetes: not just a question of semantics. Diabetes Care. 2007;30(3):542-548. [CrossRef] [PubMed]
Fisher L, Gonzalez JS, Polonsky WH. The confusing tale of depression and distress in patients with diabetes: a call for greater clarity and precision. Diabet Med. 2014;31(7):764-772. [CrossRef] [PubMed]
Fisher L, Glasgow RE, Strycker LA. The relationship between diabetes distress and clinical depression with glycemic control among patients with type 2 diabetes. Diabetes Care. 2010;33(5):1034-1036. [CrossRef] [PubMed]
Nicolucci A, Kovacs Burns K, Holt RI, et al Diabetes Attitudes, Wishes and Needs second study (DAWN2™): cross-national benchmarking of diabetes-related psychosocial outcomes for people with diabetes. Diabet Med. 2013;30(7):767-777. doi: 10.1111/dme.12245 [CrossRef] [PubMed]
Fisher L, Hessler DM, Polonsky WH, Mullan J. When is diabetes distress clinically meaningful?: establishing cut points for the Diabetes Distress Scale. Diabetes Care. 2012;35(2):259-264. doi: 10.2337/dc11-1572 [CrossRef] [PubMed]
Dennick K, Stuart J, Hessler D, et al High rates of elevated diabetes distress in research populations: a systematic review and meta-analysis. Int Diabetes Nurs. 2015;12(3):93-107. doi: 10.1080/20573316.2016.1202497 [CrossRef]
Fisher L, Mullan JT, Arean P, Glasgow RE, Hessler D, Masharani U. Diabetes distress but not clinical depression or depressive symptoms is associated with glycemic control in both cross-sectional and longitudinal analyses. Diabetes Care. 2010;33(1):23-28. doi: 10.2337/dc09-1238 [CrossRef] [PubMed]
Reddy J, Wilhelm K, Campbell L. Putting PAID to diabetes-related distress: the potential utility of the problem areas in diabetes (PAID) scale in patients with diabetes. Psychosomatics. 2013;54(1):44-51. [CrossRef] [PubMed]
Fisher EB, Thorpe CT, Devellis BM, Devellis RF. Healthy coping, negative emotions, and diabetes management: a systematic review and appraisal. Diabetes Educ. 2007;33(6):1080-1103; discussion 1104-1086. [CrossRef] [PubMed]
Chew BH, Mohd-Sidik S, Shariff-Ghazali S. Negative effects of diabetes-related distress on health-related quality of life: an evaluation among the adult patients with type 2 diabetes mellitus in three primary healthcare clinics in Malaysia. Health Qual Life Outcomes. 2015;13:187. doi: 10.1186/s12955-015-0384-4 [CrossRef] [PubMed]
Carper MM, Traeger L, Gonzalez JS, Wexler DJ, Psaros C, Safren SA. The differential associations of depression and diabetes distress with quality of life domains in type 2 diabetes. J Behav Med. 2014;37(3):501-510. doi: 10.1007/s10865-013-9505-x [CrossRef] [PubMed]
American Diabetes Association. Standards of Medical Care in Diabetes-2019. Diabetes Care. 2019;42(suppl 1):S1-S193.
Ginder SA, Kelly-Reid JE, Mann FB. Enrollment and Employees in Postsecondary Institutions, Fall 2016; and Financial Statistics and Academic Libraries, Fiscal Year 2016. Washington, DC: National Center for Education Statistics; 2017. https://nces.ed.gov/pubs2018/2018002.pdf
Houston D, Meyer LH, Paiwai S. Academic staff workloads and job satisfaction: expectations and values in academe. J Higher Educ Policy Manage. 2006;28(1):17-30. doi: 10.1080/13600800500283734 [CrossRef]
Ohio University Athens campus: fall 2017 enrollment by college. Ohio University website. https://www.ohio.edu/instres/student/collegeenrollment.html. Accessed November 23, 2018.
Faculty and staff data. Ohio University website. https://www.ohio.edu/instres/faculty/index.html. Accessed November 23, 2018.
Polonsky WH, Fisher L, Earles J, et al Assessing psychosocial distress in diabetes: development of the diabetes distress scale. Diabetes Care. 2005;28(3):626-631. [CrossRef] [PubMed]
Fisher L, Polonsky WH, Hessler DM, et al Understanding the sources of diabetes distress in adults with type 1 diabetes. J Diabetes Complications. 2015;29(4):572-577. [CrossRef] [PubMed]
Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606-613. [CrossRef] [PubMed]
Weinger K, Butler HA, Welch GW, La Greca AM. Measuring diabetes self-care: a psychometric analysis of the Self-Care Inventory-Revised with adults. Diabetes Care. 2005;28(6):1346-1352. [CrossRef] [PubMed]
Peyrot M, McMurry JF DFJr. A biopsychosocial model of glycemic control in diabetes: stress, coping and regimen adherence. J Health Soc Behav. 1999;40(2):141-158. [CrossRef] [PubMed]
van der Ven NC, Weinger K, Yi J, et al The confidence in diabetes self-care scale: psychometric properties of a new measure of diabetes-specific self-efficacy in Dutch and US patients with type 1 diabetes. Diabetes Care. 2003;26(3):713-718. [CrossRef] [PubMed]
Weinger K, Yi J. Psychological influences on glycemic control and self-management in type 1 diabetes [abstract]. Diabetes. 2000;48(suppl):A318.
Jacobson AM, the DCCT Research Group. The Diabetes Quality of Life Measure. In: Bradley C, ed. Handbook of Psychology and Diabetes. London, England: J Wiley; 1994.
Jacobson AM, de Groot M, Samson JA. The evaluation of two measures of quality of life in patients with type I and type II diabetes. Diabetes Care. 1994;17(4):267-274. [CrossRef] [PubMed]
Reliability and validity of a diabetes quality-of-life measure for the diabetes control and complications trial (DCCT). The DCCT Research Group. Diabetes Care. 1988;11(9):725-732.
Turst MO. How to Score the SF-36 Health Survey. Boston, MA: Medical Outcomes Trust; 1993.
Baek RN, Tanenbaum ML, Gonzalez JS. Diabetes burden and diabetes distress: the buffering effect of social support. Ann Behav Med. 2014;48(2):145-155. doi: 10.1007/s12160-013-9585-4 [CrossRef] [PubMed]
Burns RJ, Deschenes SS, Schmitz N. Associations between coping strategies and mental health in individuals with type 2 diabetes: prospective analyses. Health Psychol. 2016;35(1):78-86. [CrossRef] [PubMed]
Gariepy G, Smith KJ, Schmitz N. Diabetes distress and neighborhood characteristics in people with type 2 diabetes. J Psychosom Res. 2013;75(2):147-152. doi: 10.1016/j.jpsychores.2013.05.009 [CrossRef] [PubMed]
Holmes-Truscott E, Blackberry I, O'Neal DN, Furler JS, Speight J. Willingness to initiate insulin among adults with type 2 diabetes in Australian primary care: results from the Stepping Up Study. Diabetes Res Clin Pract. 2016;114:126-135. doi: 10.1016/j.diabres.2015.12.011 [CrossRef] [PubMed]
Smith KJ, Gariepy G, Pedneault M, Beland M, Clyde M, Schmitz N. Exploring the association of psychological status with self-rated diabetes control: results from the Montreal evaluation of diabetes treatment study. Psychosomatics. 2013;54(1):35-43. doi: 10.1016/j.psym.2012.08.002 [CrossRef] [PubMed]
Wong E, Afshar R, Zhang M, Elliott TG, Tang TS. Diabetes distress is associated with poor glycemic control among patients with type 2 diabetes presenting to a tertiary care setting in Vancouver. Can J Diabetes. 2015;39(6):539-540. doi: 10.1016/j.jcjd.2015.09.053 [CrossRef]
Zhu Y, Fish AF, Li F, Liu L, Lou Q. Psychosocial factors not metabolic control impact the quality of life among patients with type 2 diabetes in China. Acta Diabetol. 2016;53(4):535-541. [CrossRef] [PubMed]
Perrin NE, Davies MJ, Robertson N, Snoek FJ, Khunti K. The prevalence of diabetes-specific emotional distress in people with type 2 diabetes: a systematic review and meta-analysis. Diabet Med. 2017;34(11):1508-1520. doi: 10.1111/dme.13448 [CrossRef] [PubMed]
Hessler DM, Fisher L, Polonsky WH, et al Diabetes distress is linked with worsening diabetes management over time in adults with type 1 diabetes. Diabet Med. 2017;34(9):1228-1234. doi: 10.1111/dme.13381 [CrossRef] [PubMed]
Eisenberg D, Hunt J, Speer N. Mental health in American colleges and universities: variation across student subgroups and across campuses. J Nerv Ment Dis. 2013;201(1):60-67. [CrossRef] [PubMed]
Joensen LE, Almdal TP, Willaing I. Associations between patient characteristics, social relations, diabetes management, quality of life, glycaemic control and emotional burden in type 1 diabetes. Prim Care Diabetes. 2016;10(1):41-50. doi: 10.1016/j.pcd.2015.06.007 [CrossRef] [PubMed]
Tenets of osteopathic medicine. American Osteopathic Association website. https://osteopathic.org/about/leadership/aoa-governance-documents/tenets-of-osteopathic-medicine/. Accessed July 22, 2019.
Powers MA, Bardsley J, Cypress M, et al Diabetes self-management education and support in type 2 diabetes: a joint position statement of the American Diabetes Association, the American Association of Diabetes Educators, and the Academy of Nutrition and Dietetics. Diabetes Care. 2015;38(7):1372-1382. doi: 10.2337/diaclin.34.2.70 [CrossRef] [PubMed]
Polonsky WH, Anderson BJ, Lohrer PA, et al Assessment of diabetes-related distress. Diabetes Care. 1995;18(6):754-760. [CrossRef] [PubMed]
Sturt J, Dennick K, Hessler D, Hunter BM, Oliver J, Fisher L. Effective interventions for reducing diabetes distress: systematic review and meta-analysis. Int Diabetes Nurs. 2015;12:40-55. [CrossRef]
Fisher L, Hessler D, Glasgow RE, et al REDEEM: a pragmatic trial to reduce diabetes distress. Diabetes Care. 2013;36(9):2551-2558. [CrossRef] [PubMed]
Hermanns N, Schmitt A, Gahr A, et al The effect of a Diabetes-Specific Cognitive Behavioral Treatment Program (DIAMOS) for patients with diabetes and subclinical depression: results of a randomized controlled trial. Diabetes Care. 2015;38(4):551-560. [PubMed]
Heisler M, Choi H, Palmisano G, et al Comparison of community health worker-led diabetes medication decision-making support for low-income Latino and African American adults with diabetes using e-health tools versus print materials: a randomized, controlled trial. Ann Intern Med. 2014; (10 suppl):S13-S22. doi: 10.7326/M13-3012
Fisher L, Hessler D, Polonsky WH, et al T1-REDEEM: a randomized controlled trial to reduce diabetes distress among adults with type 1 diabetes. Diabetes Care. 2018;41(9):1862-1869. doi: 10.2337/dc18-0391 [CrossRef] [PubMed]
County economic status and distressed areas in Appalachia. Appalachian Regional Commission website. https://www.arc.gov/appalachian_region/CountyEconomicStatusandDistressedAreasinAppalachia.asp. Accessed July 2, 2018.
Tanenbaum ML, Hanes SJ, Miller KM, Naranjo D, Bensen R, Hood KK. Diabetes device use in adults with type 1 diabetes: barriers to uptake and potential intervention targets. Diabetes Care. 2017;40(2):181-187. doi: 10.2337/dc16-1536 [CrossRef] [PubMed]
Table 1.
Diabetes Distress in a University Population: Participant Demographic and Health Characteristicsa
Variable Total (N=173) Type 1 (n=85) Type 2 (n=88) P Value
Age, y 35.1 (16.7) 24.5 (9.3) 45.4 (15.8) <.001
Gender       .241
Female 108 (62.4) 59 (69.4) 49 (55.7)  
Male 62 (35.8) 25 (29.4) 37 (42.0)  
Other 2 (1.2) 1 (1.2) 1 (1.1)  
Prefer not to answer 1 (0.6) 0 (0) 1 (1.1)  
Race       .074
 American Indian 1 (0.6) 0 (0) 1 (1.1)  
 Asian 13 (7.5) 3 (3.5) 10 (11.4)  
 Black 10 (5.8) 3 (5.5) 6 (9.2)  
 Mixed 3 (1.7) 1 (1.1) 2 (2.3)  
 Other 3 (1.7) 2 (2.4) 1 (1.1)  
 Pacific Islander 1 (0.6) 0 (0) 1 (1.1)  
 White 142 (82.1) 77 (90.6) 65 (73.9)  
Ethnicity       .669
 Hispanic/Latino 5 (2.9) 2 (2.4) 3 (3.4)  
Education       <.001
 High school 8 (4.6) 3 (3.5) 5 (5.7)  
 Current undergraduate 62 (35.8) 52 (61.2) 10 (11.4)  
 Some college 16 (9.2) 5 (5.9) 11 (12.5)  
 2-year degree 13 (7.5) 2 (2.4) 11 (12.5)  
 4-year degree 18 (10.4) 10 (10.6) 9 (10.2)  
 Current graduate student 9 (5.2) 5 (5.9) 4 (4.5)  
 Some graduate work 4 (2.3) 1 (1.26) 3 (3.4)  
 Master's degree 18 (10.4) 6 (7.1) 12 (13.6)  
 Doctoral/professional degree 25 (14.5) 2 (2.4) 23 (26.1)  
Health Insuranceb       .816
 No coverage 3 (1.7) 1 (1.2) 2 (2.3)
 Medicaid and/or Medicare 23 (13.3) 13 (15.3) 10 (11.4)
 Private 134 (77.5) 64 (75.3) 70 (79.5)
 Other 11 (6.4) 5 (5.9) 6 (6.8)
Hemoglobin A1c, % 7.3 (1.4) 7.8 (1.6) 6.8 (1.0) <.001
Body Mass Index 30.0 (7.6) 26.6 (6.6) 33.2 (16.7) <.001
Diabetes Duration, y 10.5 (9.5) 12.8 (8.8) 8.2 (9.6) .002
Diabetes Treatment <.001
 Diet and exercise 24 (13.9) 6 (7.1) 18 (20.5)
 Oral medication 50 (28.9) 1 (1.2) 49 (55.7)
 Insulin 750 (43.4) 73 (85.9) 2 (2.3)
 Insulin and oral medication 16 (9.2) 4 (4.7) 12 (13.6)
 Other 8 (4.6) 1 (1.2) 7 (8.0)

a Data are presented as No.(%) unless otherwise indicated.

b Values were missing for health insurance for 2 participants.

Table 1.
Diabetes Distress in a University Population: Participant Demographic and Health Characteristicsa
Variable Total (N=173) Type 1 (n=85) Type 2 (n=88) P Value
Age, y 35.1 (16.7) 24.5 (9.3) 45.4 (15.8) <.001
Gender       .241
Female 108 (62.4) 59 (69.4) 49 (55.7)  
Male 62 (35.8) 25 (29.4) 37 (42.0)  
Other 2 (1.2) 1 (1.2) 1 (1.1)  
Prefer not to answer 1 (0.6) 0 (0) 1 (1.1)  
Race       .074
 American Indian 1 (0.6) 0 (0) 1 (1.1)  
 Asian 13 (7.5) 3 (3.5) 10 (11.4)  
 Black 10 (5.8) 3 (5.5) 6 (9.2)  
 Mixed 3 (1.7) 1 (1.1) 2 (2.3)  
 Other 3 (1.7) 2 (2.4) 1 (1.1)  
 Pacific Islander 1 (0.6) 0 (0) 1 (1.1)  
 White 142 (82.1) 77 (90.6) 65 (73.9)  
Ethnicity       .669
 Hispanic/Latino 5 (2.9) 2 (2.4) 3 (3.4)  
Education       <.001
 High school 8 (4.6) 3 (3.5) 5 (5.7)  
 Current undergraduate 62 (35.8) 52 (61.2) 10 (11.4)  
 Some college 16 (9.2) 5 (5.9) 11 (12.5)  
 2-year degree 13 (7.5) 2 (2.4) 11 (12.5)  
 4-year degree 18 (10.4) 10 (10.6) 9 (10.2)  
 Current graduate student 9 (5.2) 5 (5.9) 4 (4.5)  
 Some graduate work 4 (2.3) 1 (1.26) 3 (3.4)  
 Master's degree 18 (10.4) 6 (7.1) 12 (13.6)  
 Doctoral/professional degree 25 (14.5) 2 (2.4) 23 (26.1)  
Health Insuranceb       .816
 No coverage 3 (1.7) 1 (1.2) 2 (2.3)
 Medicaid and/or Medicare 23 (13.3) 13 (15.3) 10 (11.4)
 Private 134 (77.5) 64 (75.3) 70 (79.5)
 Other 11 (6.4) 5 (5.9) 6 (6.8)
Hemoglobin A1c, % 7.3 (1.4) 7.8 (1.6) 6.8 (1.0) <.001
Body Mass Index 30.0 (7.6) 26.6 (6.6) 33.2 (16.7) <.001
Diabetes Duration, y 10.5 (9.5) 12.8 (8.8) 8.2 (9.6) .002
Diabetes Treatment <.001
 Diet and exercise 24 (13.9) 6 (7.1) 18 (20.5)
 Oral medication 50 (28.9) 1 (1.2) 49 (55.7)
 Insulin 750 (43.4) 73 (85.9) 2 (2.3)
 Insulin and oral medication 16 (9.2) 4 (4.7) 12 (13.6)
 Other 8 (4.6) 1 (1.2) 7 (8.0)

a Data are presented as No.(%) unless otherwise indicated.

b Values were missing for health insurance for 2 participants.

×
Table 2.
Type 1 and Type 2 Diabetes Mellitus Participants’ Psychosocial Assessment Results (N=173)
Assessment Total Mean (SD) Type 1 Diabetes Mean (SD) Type 2 Diabetes Mean(SD) P Value
Depressive Symptoms 7.8 (6.4) 7.8 (6.5) 8.0 (6.4) .865
Diabetes Self-care 57.4 (18.9) 62.3 (17.1) 52.2 (19.2) <.001
Diabetes Self-efficacy 69.1 (23.5) 67.7 (25.9) 70.4 (20.9) .462
Coping
  Emotional 43.0 (21.3) 45.4 (19.9) 40.7 (22.5) .151
  Controlled 50.5 (16.7) 52.5 (16.5) 48.5 (16.78) .120
Diabetes Quality of Life 36.2 (16.6) 38.5 (15.8) 34.0 (17.1) .075
Table 2.
Type 1 and Type 2 Diabetes Mellitus Participants’ Psychosocial Assessment Results (N=173)
Assessment Total Mean (SD) Type 1 Diabetes Mean (SD) Type 2 Diabetes Mean(SD) P Value
Depressive Symptoms 7.8 (6.4) 7.8 (6.5) 8.0 (6.4) .865
Diabetes Self-care 57.4 (18.9) 62.3 (17.1) 52.2 (19.2) <.001
Diabetes Self-efficacy 69.1 (23.5) 67.7 (25.9) 70.4 (20.9) .462
Coping
  Emotional 43.0 (21.3) 45.4 (19.9) 40.7 (22.5) .151
  Controlled 50.5 (16.7) 52.5 (16.5) 48.5 (16.78) .120
Diabetes Quality of Life 36.2 (16.6) 38.5 (15.8) 34.0 (17.1) .075
×
Table 3.
Linear Regression Models Examining Associations Among Diabetes Distress and Glycemic Control, Self-Care, and Diabetes Quality of Life in Adults With Type 1 and Type 2 Diabetes Mellitus
Predictors Standardized β. P Value
Type 1 Diabetes Mellitus (n=85)
Model 1: Glycemic Control, R2=0.19
 Age −0.231 .029
 Gender −0.218 .038
 Depressive symptoms −0.092 .524
 Diabetes distress score 0.323 .025
Model 2: Diabetes Self-Care, R2=0.08
 Age 0.714 .478
 Gender −0.078 .483
 Depressive symptoms 0.053 .729
 Diabetes distress score −0.290 .056
Model 3: Diabetes Quality of Life, R2=0.65
 Age 0.023 .730
 Gender −0.045 .507
 Depressive symptoms 0.234 .013
 Diabetes distress score 0.604 <.001
Model 3a: Diabetes Quality of Life Subscale: Life Satisfaction, R2=0.50
 Age −0.013 .872
 Gender 0.004 .962
 Depressive symptoms 0.104 .353
 Diabetes distress score 0.632 <.001
Model 3b: Diabetes Quality of Life Subscale: Diabetes Impact, R2=0.48
 Age 0.083 .321
 Gender −0.103 .219
 Depressive symptoms 0.295 .012
 Diabetes distress score 0.438 <.001
Model 3c: Diabetes Quality of Life Subscale: Diabetes-Related Worry, R2=0.47
 Age −0.044 .599
 Gender −0.091 .278
 Depressive symptoms 0.258 .027
 Diabetes distress score 0.462 <.001
Type 2 Diabetes Mellitus (n=88)
Model 4: Glycemic Control, R2=0.12
 Age 0.317 .009
 Gender 0.024 .830
 Depressive symptoms 0.102 .431
 Diabetes distress score 0.249 .062
Model 5: Diabetes Self-Care, R2=0.12
 Age −0.047 .680
 Gender −0.034 .748
 Depressive symptoms −0.159 .207
 Diabetes distress score −0.248 .055
Model 6: Diabetes Quality of Life, R2=0.67
 Age −0.132 .059
 Gender 0.033 .617
 Depressive symptoms 0.443 <.001
 Diabetes distress score 0.434 <.001
Model 6a: Diabetes Quality of Life Subscale: Life Satisfaction, R2=0.67
 Age −0.060 .384
 Gender 0.004 .951
 Depressive symptoms 0.465 <.001
 Diabetes distress score 0.450 <.001
Model 6b: Diabetes Quality of Life Subscale: Diabetes Impact, R2=0.45
 Age −0.183 .043
 Gender 0.097 .247
 Depressive symptoms 0.357 <.001
 Diabetes distress score 0.312 .002
Model 6c: Diabetes Quality of Life Subscale: Diabetes-Related Worry, R2=0.28
 Age −0.160 .121
 Gender −0.106 .270
 Depressive symptoms 0.175 .123
 Diabetes distress score 0.317 .007
Table 3.
Linear Regression Models Examining Associations Among Diabetes Distress and Glycemic Control, Self-Care, and Diabetes Quality of Life in Adults With Type 1 and Type 2 Diabetes Mellitus
Predictors Standardized β. P Value
Type 1 Diabetes Mellitus (n=85)
Model 1: Glycemic Control, R2=0.19
 Age −0.231 .029
 Gender −0.218 .038
 Depressive symptoms −0.092 .524
 Diabetes distress score 0.323 .025
Model 2: Diabetes Self-Care, R2=0.08
 Age 0.714 .478
 Gender −0.078 .483
 Depressive symptoms 0.053 .729
 Diabetes distress score −0.290 .056
Model 3: Diabetes Quality of Life, R2=0.65
 Age 0.023 .730
 Gender −0.045 .507
 Depressive symptoms 0.234 .013
 Diabetes distress score 0.604 <.001
Model 3a: Diabetes Quality of Life Subscale: Life Satisfaction, R2=0.50
 Age −0.013 .872
 Gender 0.004 .962
 Depressive symptoms 0.104 .353
 Diabetes distress score 0.632 <.001
Model 3b: Diabetes Quality of Life Subscale: Diabetes Impact, R2=0.48
 Age 0.083 .321
 Gender −0.103 .219
 Depressive symptoms 0.295 .012
 Diabetes distress score 0.438 <.001
Model 3c: Diabetes Quality of Life Subscale: Diabetes-Related Worry, R2=0.47
 Age −0.044 .599
 Gender −0.091 .278
 Depressive symptoms 0.258 .027
 Diabetes distress score 0.462 <.001
Type 2 Diabetes Mellitus (n=88)
Model 4: Glycemic Control, R2=0.12
 Age 0.317 .009
 Gender 0.024 .830
 Depressive symptoms 0.102 .431
 Diabetes distress score 0.249 .062
Model 5: Diabetes Self-Care, R2=0.12
 Age −0.047 .680
 Gender −0.034 .748
 Depressive symptoms −0.159 .207
 Diabetes distress score −0.248 .055
Model 6: Diabetes Quality of Life, R2=0.67
 Age −0.132 .059
 Gender 0.033 .617
 Depressive symptoms 0.443 <.001
 Diabetes distress score 0.434 <.001
Model 6a: Diabetes Quality of Life Subscale: Life Satisfaction, R2=0.67
 Age −0.060 .384
 Gender 0.004 .951
 Depressive symptoms 0.465 <.001
 Diabetes distress score 0.450 <.001
Model 6b: Diabetes Quality of Life Subscale: Diabetes Impact, R2=0.45
 Age −0.183 .043
 Gender 0.097 .247
 Depressive symptoms 0.357 <.001
 Diabetes distress score 0.312 .002
Model 6c: Diabetes Quality of Life Subscale: Diabetes-Related Worry, R2=0.28
 Age −0.160 .121
 Gender −0.106 .270
 Depressive symptoms 0.175 .123
 Diabetes distress score 0.317 .007
×