This study analyzed patient-described barriers and facilitators related to diabetes management, focusing on how these differ by glycemia and across individual characteristics. A cross-sectional telephone survey was conducted with adult patients with diabetes in Alberta, Canada, asking two open-ended questions to describe the most helpful and difficult components of their diabetes management. Responses were analyzed using directed content analysis using the Theoretical Domains Framework as a template. The most frequently cited facilitator was care context and information, and the most frequently cited barriers were cognitive challenges and structural barriers, with patient-perceived barriers and facilitators varying by individual-level factors.

Key Points

  • » The most frequently reported patient-perceived facilitator for diabetes management was care context and information (62.3%), which was more frequently cited among those who were wealthier, had higher A1C, and were older.

  • » The most frequently reported patient-perceived barriers were related to cognitive capabilities (37.4%), which was more common in the elderly, and structural barriers (16.7%), which was more common in younger and lower-income patients.

  • » Diabetes management would be improved by strengthening patient education while reducing structural barriers to care and supporting those with cognitive challenges.

  • » Age, income, and employment status were associated with particular barriers to care. Screening for these characteristics can help providers tailor diabetes management strategies to patient context.

Diabetes affects more than 463 million adults worldwide, and managing diabetes and its complications is costly (1). Patients who do not achieve glycemic targets are at higher risk of complications (2), which leads to higher health care system costs (24). Safe, efficacious, and cost-effective interventions for diabetes are available (5); however, these treatments are underused, potentially because of a combination of patient-, provider-, and system-level barriers (69). Diabetes management places a considerable burden on patients to engage with a variety of health care providers (HCPs) and also be active participants in self-management, which requires considerable effort on the part of patients (10). It is important to understand the experiences of patients to inform how health and social systems might be improved to help patients optimally manage their diabetes.

Many studies have described barriers to diabetes management experienced by specific subsets of the population (1114); these include poor health literacy, cultural and linguistic challenges, limited financial resources, and suboptimal relationships with HCPs. Much of this literature, however, has used either large surveys with pre-specified options, which forces participants to choose a predetermined option, or in-depth qualitative methods focused on a small number of participants. Few studies to date have used open-ended questions in a large heterogeneous sample to understand the prevalence of specific barriers to and facilitators of diabetes management. An exception was the second Diabetes Attitudes, Wishes and Needs study (15), in which the authors explicitly did not undertake stratified comparisons by individual characteristics. A better understanding of how barriers and facilitators vary by patient characteristics could facilitate targeted diabetes management strategies and mobilization of resources to populations for whom they are likely to be most impactful.

Our objective was to use open-ended questions to elicit patient perspectives on barriers and facilitators faced in diabetes management to identify those that are most commonly cited. Additionally, we sought to assess for differences in barriers and facilitators across a variety of individual characteristics known to affect diabetes management and outcomes (5,1619) and whether they differed in individuals with very high blood glucose levels compared with those with better glycemia.

Study Design and Sample

We conducted a cross-sectional survey, including both closed- and open-ended questions, with patients in Alberta, Canada, who have diabetes. This study was approved by the University of Calgary Conjoint Health Research Ethics Board.

Participants were eligible for inclusion in the survey if they were adults (>18 years of age) who resided in the Calgary area and had preexisting diabetes with an A1C of 7–8% (53–64 mmol/mol) or ≥10% (≥86 mmol/mol) and if the HCP who ordered the test did not indicate that they should be excluded from participating in the survey. Further exclusion criteria included having gestational diabetes and not being aware of a preexisting diagnosis of diabetes. The sample was taken from individuals who had their A1C tested in an outpatient Calgary Laboratory Services (the sole laboratory provider in the zone) facility between 1 October 2013 and 30 April 2014.

Study Setting

Calgary is a city of 1.3 million residents in the province of Alberta. The Calgary Zone of Alberta Health Services includes the city and several outlying areas, a catchment area of >1.6 million (20). The majority of diabetes care in Alberta is provided by family physicians in primary care settings, often supplemented by allied health support via primary care networks (21). Specialty services are available on a consultation basis. Physician and hospital care is publicly funded through the universal single-payer health care system. Medication costs, however, are paid by individual patients, often with supplemental health insurance through employers or government-funded programs for certain segments of the population (22).

Data Collection

Between January and May 2014, patients who met the eligibility criteria were contacted by telephone and invited to participate in the survey. This contact happened within 90 days of the index A1C test. Verbal informed consent was obtained over the telephone. The survey was administered over the telephone by professional interviewers. A standardized script was used to guide the interviewers in their conversations with participants. Justification of the sample size is described elsewhere (23).

The questionnaire was mainly composed of closed-ended questions designed to cover five broad domains from the Barriers to Diabetes Self-Care Behaviors Model (24): health status, health care experience, self-management, financial barriers, and sociodemographic factors. The results of this quantitative survey have been reported previously (23). At the conclusion of the survey, respondents were asked two open-ended questions: What do you find most helpful in the management of your diabetes? What do you find most difficult in the management of your diabetes? Participant responses to these questions were typed verbatim in open-text fields by the interviewer.

Data Analysis

The responses to these open-ended questions were deductively analyzed using manifest summative content analysis (25,26). The coding template was based on a modified version of the Theoretical Domains Framework (TDF) (27). Although the TDF was developed to explain behavior change in HCPs with regard to the implementation of recommendations, the categories within the TDF have relevance for chronic disease management (28). Because our questions were not directly related to a specific behavior, but rather to patients’ experiences with diabetes management more generally, we used a modified version of the TDF domains to ensure relevance to patients’ experiences (Table 1). We subsequently mapped the domains of the TDF to the subheadings of the Behavior Change Wheel (BCW), which is a framework linked to the COM-B (Capabilities– Opportunities–Motivation–Behavior) model to understand behavior change (27,29). The BCW subcategories include Cognitive and Physical (under Capabilities), Structural and Social (under Opportunities), and Reflective and Automatic (under Motivation). Finally, because individuals described challenges related to diabetes, we added a Diabetes-Specific category with subcategories of Nature of Behaviors and Care Context and Information.

TABLE 1

Modified TDF and Collapsed Categories for Patient Behavior Change in Diabetes

CategorySubcategorySet of DomainsExplanation
Capability Cognitive Knowledge Diabetes and health system–related knowledge 
Memory, attention, and decision processes Memory, attention, cognition, ability to make decisions 
Skills Underlying skills such as literacy and insulin titration 
Behavioral regulation Self-monitoring, habit-breaking, action-planning 
Physical Physical health General health status, burden of diabetes complications 
Motivation Reflective Beliefs about capabilities Self-confidence, self-efficacy 
Beliefs about consequences Acceptance of truth, realistic expectations 
Optimism Belief that care will have a good outcome vs. pessimism 
Intentions Plans for behavior change 
Goals Priority-setting 
Social role and identity Influence of identity as mother, employee, caregiver, and so forth 
Automatic Reinforcement Experiences: positive or negative influencing repeated behavior 
Emotion Fear, anxiety, depression 
Opportunity Structural Environmental context Specific to care services and access to care, perceived quality of care 
Financial resources Personal finance and external financial resources 
Social Social influences Family, friend, work support 
Diabetes-specific Nature of behaviors Nature of the behaviors Things that are easy or difficult about diabetes care: medication burden, burden of insulin, cost of treatment 
Care context and information Care context Likely specific to care services and access to care, perceived quality of care 
Information Available information 
CategorySubcategorySet of DomainsExplanation
Capability Cognitive Knowledge Diabetes and health system–related knowledge 
Memory, attention, and decision processes Memory, attention, cognition, ability to make decisions 
Skills Underlying skills such as literacy and insulin titration 
Behavioral regulation Self-monitoring, habit-breaking, action-planning 
Physical Physical health General health status, burden of diabetes complications 
Motivation Reflective Beliefs about capabilities Self-confidence, self-efficacy 
Beliefs about consequences Acceptance of truth, realistic expectations 
Optimism Belief that care will have a good outcome vs. pessimism 
Intentions Plans for behavior change 
Goals Priority-setting 
Social role and identity Influence of identity as mother, employee, caregiver, and so forth 
Automatic Reinforcement Experiences: positive or negative influencing repeated behavior 
Emotion Fear, anxiety, depression 
Opportunity Structural Environmental context Specific to care services and access to care, perceived quality of care 
Financial resources Personal finance and external financial resources 
Social Social influences Family, friend, work support 
Diabetes-specific Nature of behaviors Nature of the behaviors Things that are easy or difficult about diabetes care: medication burden, burden of insulin, cost of treatment 
Care context and information Care context Likely specific to care services and access to care, perceived quality of care 
Information Available information 

Because the open-ended questions asked participants to describe the most helpful or most difficult factor in diabetes management, each open-ended response could only be coded to one category (herein referred to as facilitator and barrier, respectively). In rare instances when more than one concept was expressed, the dominant theme was chosen; if all were equal (as in a list), then only the first theme mentioned was coded. Data were coded independently by two research assistants (J.S. and R.L.), and all coding was reviewed in depth by a third reviewer (A.M.). Where discrepancies were noted, these codes were also reviewed with principal investigators (D.J.T.C. and K.A.M.).

Given the number of participants, this deductive approach allowed us to quantitize the qualitative descriptive data in such a way that meaningful comparisons could be made (30). We were particularly interested in whether the facilitators and barriers patients described in managing their diabetes would vary by key characteristics, including age, annual income, sex, and glycemia (A1C). These key characteristics were selected because they have previously been shown to have a significant impact on diabetes management and complications (5,1619). In addition to these key characteristics, a summary comparison was conducted for the following individual characteristics: race (White vs. indigenous/other), immigration status (born in Canada vs. born outside of Canada), duration of diabetes (0–5 vs. >5 years), self-perceived health status (good/very good/excellent vs. poor/fair), insulin use (yes vs. no), marital status (married/common-law vs. single/divorced/ separated/widowed), location of residence (urban vs. rural), employment status (employed/full-time student vs. retired/unemployed), education (less than university vs. university degree or higher), and food insecurity (based on one-item screener asking, “In the past 12 months, how often could you [and others in your household] not afford to eat balanced meals?” and compared by always/often/sometimes vs. rarely/never). Each of these variables were dichotomized, and χ2 tests were used to determine statistically significant differences between the groups in the frequency of describing barriers and facilitators in each subcategory. P <0.05 was considered statistically significant (31).

Of 3,363 potentially eligible patients, 380 were excluded from participating by their ordering provider because of issues such as language barriers or cognitive impairment. We attempted to contact 2,822 patients, with 1,210 completing the telephone survey (response rate: 43%) (23). Those not included did not answer the telephone (n = 424), were not eligible (n = 648), refused participation or had incomplete surveys (n = 530), or were not contacted because the pre-specified sample size had been obtained (n = 161). Of the survey respondents, 1,070 (88%) responded to the open-ended question to describe facilitators, and 901 (74%) responded to the open-ended question to describe barriers.

Table 2 summarizes the characteristics of those who completed the open-ended portion of the surveys, by question answered. Most participants had an A1C ≥10% (66.8% who responded about facilitators and 68.6% who responded about barriers). Just over half of participants reported an annual income ≥$50,000 Canadian dollar (55.5%/58.4%). Most participants were men (60.8%/57.5%) and <65 years of age (63.9%/68.0%).

TABLE 2

Sociodemographic Characteristics of Study Participants

Answered Open-Ended
Question About Facilitators
(N = 1,070)
Answered Open-Ended
Question About Barriers
(N = 901)
Sex 1,070 901 
 Male 650 (60.8) 518 (57.5) 
 Female 420 (39.3) 383 (42.5) 
Age 1,070 901 
 <65 years 684 (63.9) 613 (68.0) 
 ≥65 years 386 (36.1) 288 (32.0) 
A1C 1,070 901 
 7–8% 355 (33.2) 283 (31.4) 
 ≥10% 715 (66.8) 618 (68.6) 
Duration of diabetes 1,061 898 
 1–10 years 582 (54.9) 493 (54.9) 
 >10 years 479 (45.2) 405 (45.1) 
Household income, CAD 966 815 
 <$50,000 430 (44.5) 339 (41.6) 
 ≥$50,000 536 (55.5) 476 (58.4) 
Education 1,049 886 
 Less than university 500 (47.7) 425 (48.0) 
 University/college education or higher 549 (52.3) 461 (52.0) 
Employment 1,033 874 
 Unemployed/retired 483 (46.8) 386 (44.2) 
 Employed or full-time student 550 (53.2) 488 (55.8) 
Marital status 1,055 890 
 Married/common-law 726 (68.8) 605 (68.0) 
 Widowed/separated/divorced/single 329 (31.2) 285 (32.0) 
Ethnicity 1,070 901 
 White 755 (70.6) 664 (73.7) 
 Indigenous or other 315 (29.4) 237 (26.3) 
Community size 1,060 896 
 Rural area or small population center (≤99,999) 196 (18.5) 171 (19.1) 
 Large population center (≥100,000) 864 (81.5) 725 (80.9) 
Food insecurity 1,070 901 
 Yes 309 (28.9) 275 (30.5) 
 No 761 (71.1) 626 (69.5) 
Perceived good health 1,058 893 
 Yes 754 (71.3) 619 (69.3) 
 No 304 (28.7) 274 (30.7) 
Born in Canada 1,061 895 
 Yes 698 (65.8) 627 (70.1) 
 No 363 (34.2) 268 (29.9) 
Insulin use 1,056 894 
 Yes 587 (55.6) 517 (57.8) 
 No 469 (44.4) 377 (42.2) 
 Has seen diabetes educator in the past 12 months 1,060 901 
 In the tertiary diabetes center 129 (12.1) 141 (15.6) 
 In the community 152 (14.3) 104 (11.5) 
 Both in diabetes center and community 55 (5.2) 48 (5.3) 
 No 724 (68.3) 608 (67.5) 
Answered Open-Ended
Question About Facilitators
(N = 1,070)
Answered Open-Ended
Question About Barriers
(N = 901)
Sex 1,070 901 
 Male 650 (60.8) 518 (57.5) 
 Female 420 (39.3) 383 (42.5) 
Age 1,070 901 
 <65 years 684 (63.9) 613 (68.0) 
 ≥65 years 386 (36.1) 288 (32.0) 
A1C 1,070 901 
 7–8% 355 (33.2) 283 (31.4) 
 ≥10% 715 (66.8) 618 (68.6) 
Duration of diabetes 1,061 898 
 1–10 years 582 (54.9) 493 (54.9) 
 >10 years 479 (45.2) 405 (45.1) 
Household income, CAD 966 815 
 <$50,000 430 (44.5) 339 (41.6) 
 ≥$50,000 536 (55.5) 476 (58.4) 
Education 1,049 886 
 Less than university 500 (47.7) 425 (48.0) 
 University/college education or higher 549 (52.3) 461 (52.0) 
Employment 1,033 874 
 Unemployed/retired 483 (46.8) 386 (44.2) 
 Employed or full-time student 550 (53.2) 488 (55.8) 
Marital status 1,055 890 
 Married/common-law 726 (68.8) 605 (68.0) 
 Widowed/separated/divorced/single 329 (31.2) 285 (32.0) 
Ethnicity 1,070 901 
 White 755 (70.6) 664 (73.7) 
 Indigenous or other 315 (29.4) 237 (26.3) 
Community size 1,060 896 
 Rural area or small population center (≤99,999) 196 (18.5) 171 (19.1) 
 Large population center (≥100,000) 864 (81.5) 725 (80.9) 
Food insecurity 1,070 901 
 Yes 309 (28.9) 275 (30.5) 
 No 761 (71.1) 626 (69.5) 
Perceived good health 1,058 893 
 Yes 754 (71.3) 619 (69.3) 
 No 304 (28.7) 274 (30.7) 
Born in Canada 1,061 895 
 Yes 698 (65.8) 627 (70.1) 
 No 363 (34.2) 268 (29.9) 
Insulin use 1,056 894 
 Yes 587 (55.6) 517 (57.8) 
 No 469 (44.4) 377 (42.2) 
 Has seen diabetes educator in the past 12 months 1,060 901 
 In the tertiary diabetes center 129 (12.1) 141 (15.6) 
 In the community 152 (14.3) 104 (11.5) 
 Both in diabetes center and community 55 (5.2) 48 (5.3) 
 No 724 (68.3) 608 (67.5) 

Data are n or n (%). CAD, Canadian dollars.

Overall, the most frequently cited facilitators were in the subcategories of care context and information (62.3%), cognitive capability (17.6%), and automatic motivation (6.8%) (Table 3). Exemplary quotes from each subcategory and domain are presented in Supplementary Appendix S1. Within the care context and information subcategory, participants cited that their HCPs aided them and assisted them with diabetes and self-management. For example, one participant noted the importance of “having a doctor who has really kept close tabs on me, paid attention, and anytime I need to get into the office, I can.” In addition to family physicians, participants also appreciated the help received from specialists and allied HCPs, including diabetes educators, pharmacists, dietitians, and nurses. This theme also included diabetes-related information received from other sources: “the information that is out there at the drugstores, doctor’s offices, magazines, and the internet.”

TABLE 3

Differences in Facilitators and Barriers by Individual Characteristic

TotalCapabilityOpportunityMotivationDiabetes-Specific
CognitivePhysicalStructuralSocialReflectiveAutomaticNature of
Behaviors
Care Context
and Information
FacBarFacBarFacBarFacBarFacBarFacBarFacBarFacBarFacBar
Total 1,070
(100) 
901
(100) 
188
(17.6) 
337
(37.4) 
1
(0.1) 
52
(5.8) 
16
(1.5) 
150
(16.7) 
54
(5.1) 
24
(2.7) 
15
(1.4) 
62
(6.9) 
73
(6.8) 
23
(2.6) 
56
(5.2) 
131
(14.5) 
667
(62.3) 
122
(13.5) 
A1C 1,070
(100) 
901
(100) 
 
 7–8% 355
(33.2) 
283
(31.4) 
     34
(12) 
    38
(10.7) 
   199
(56.1) 
 
 ≥10% 715
(66.8) 
618
(68.6) 
     116
(18.8) 
    35
(4.9) 
   468
(65.5) 
 
Sex 1,070
(100) 
901
(100) 
 
 Female 420
(39.3) 
383
(42.5) 
           17
(4.4) 
    
 Male 650
(60.7) 
518
(57.5) 
           6
(1.2) 
    
Income 966
(100) 
815
(100) 
 
 <$50,000 CAD 430
(44.5) 
339
(41.6) 
91
(21.2) 
  28
(8.3) 
 69
(20.4) 
        246
(57.2) 
 
 ≥$50,000 CAD 536
(55.5) 
476
(58.4) 
68
(12.7) 
  13
(2.7) 
 71
(14.9) 
        368
(68.7) 
 
Age 1,070
(100) 
901
(100) 
 
 <65 years 684
(63.9) 
613
(68.0) 
100
(14.6) 
204
(33.3) 
   117
(19.1) 
     20
(3.3) 
  458
(67) 
 
 ≥65 years 386
(36.1) 
288
(32.0) 
88
(22.8) 
133
(46.2) 
   33
(11.5) 
     3
(1) 
  209
(54) 
 
Race 1,070
(100) 
901
(100) 
 
 White 755
(70.6) 
664
(73.7) 
105
(13.9) 
         60
(8.0) 
 28
(3.7) 
 505
(66.9) 
100
(15.1) 
 Indigenous or other 315
(29.4) 
237
(26.3) 
83
(26.4) 
         13
(4.1) 
 28
(8.9) 
 162
(51.4) 
22
(9.3) 
 Born in Canada 1,061
(100) 
895
(100) 
 
 Yes 698
(65.8) 
627
(70.1) 
88
(12.6) 
         58
(8.3) 
 29
(4.2) 
 466
(66.8) 
 
 No 363
(34.2) 
268
(29.9) 
98
(27.0) 
         14
(3.9) 
 27
(7.4) 
 196
(54.0) 
 
Food insecurity 1,070
(100) 
901
(100) 
 
 Yes 309
(28.9) 
275
(30.5) 
66
(21.4) 
86
(31.3) 
   60
(21.8) 
          
 No 761
(71.1) 
626
(69.5) 
122
(16.0) 
251
(40.1) 
   90
(14.4) 
          
Duration of diabetes 1,061
(100) 
898
(100) 
 
 <10 years 582
(54.9) 
493
(54.9) 
                
 >10 years 479
(45.1) 
405
(45.1) 
                
Self-perceived health 1,058
(100) 
893
(100) 
 
 Excellent/very good/good 754
(71.3) 
619
(69.3) 
                
 Fair/poor 304
(28.7) 
274
(30.7) 
                
Insulin use 1,056
(100) 
894
(100) 
 
 Yes 587
(55.6) 
517
(57.8) 
77
(13.1) 
            90
(17.4) 
400
(68.1) 
 
 No 469
(44.4) 
377
(42.2) 
105
(22.4) 
            41
(10.9) 
263
(56.1) 
 
 Marital status 1,055
(100) 
890
(100) 
 
 Partnered 726
(68.8) 
605
(68.0) 
143
(19.7) 
             427
(58.8) 
 
 Single 329
(31.2) 
285
(32.0) 
42
(12.8) 
             232
(70.5) 
 
Community size 1,060
(100) 
896
(100) 
 
 Small city/rural 196
(18.5) 
171
(19.1) 
  1
(0.5) 
 6
(3.1) 
           
 Medium/large city 864
(81.5) 
725
(80.9) 
  0
(0.0) 
 10
(1.2) 
           
Employment 1,033
(100) 
874
(100) 
 
 Employed/full-time student 550
(53.2) 
488
(55.8) 
   16 (3.3)  94
(19.3) 
20
(3.6) 
       364
(66.2) 
 
 Unemployed/retired 483
(46.8) 
386
(44.2) 
   35
(9.1) 
 52
(13.5) 
31
(6.4) 
       278
(57.6) 
 
Education 1,049
(100) 
886
(100) 
 
 Less than university degree 500
(47.7) 
425
(48.0) 
 175
(41.2) 
              
 At least university degree 549
(52.3) 
461
(52.0) 
 156
(33.8) 
              
TotalCapabilityOpportunityMotivationDiabetes-Specific
CognitivePhysicalStructuralSocialReflectiveAutomaticNature of
Behaviors
Care Context
and Information
FacBarFacBarFacBarFacBarFacBarFacBarFacBarFacBarFacBar
Total 1,070
(100) 
901
(100) 
188
(17.6) 
337
(37.4) 
1
(0.1) 
52
(5.8) 
16
(1.5) 
150
(16.7) 
54
(5.1) 
24
(2.7) 
15
(1.4) 
62
(6.9) 
73
(6.8) 
23
(2.6) 
56
(5.2) 
131
(14.5) 
667
(62.3) 
122
(13.5) 
A1C 1,070
(100) 
901
(100) 
 
 7–8% 355
(33.2) 
283
(31.4) 
     34
(12) 
    38
(10.7) 
   199
(56.1) 
 
 ≥10% 715
(66.8) 
618
(68.6) 
     116
(18.8) 
    35
(4.9) 
   468
(65.5) 
 
Sex 1,070
(100) 
901
(100) 
 
 Female 420
(39.3) 
383
(42.5) 
           17
(4.4) 
    
 Male 650
(60.7) 
518
(57.5) 
           6
(1.2) 
    
Income 966
(100) 
815
(100) 
 
 <$50,000 CAD 430
(44.5) 
339
(41.6) 
91
(21.2) 
  28
(8.3) 
 69
(20.4) 
        246
(57.2) 
 
 ≥$50,000 CAD 536
(55.5) 
476
(58.4) 
68
(12.7) 
  13
(2.7) 
 71
(14.9) 
        368
(68.7) 
 
Age 1,070
(100) 
901
(100) 
 
 <65 years 684
(63.9) 
613
(68.0) 
100
(14.6) 
204
(33.3) 
   117
(19.1) 
     20
(3.3) 
  458
(67) 
 
 ≥65 years 386
(36.1) 
288
(32.0) 
88
(22.8) 
133
(46.2) 
   33
(11.5) 
     3
(1) 
  209
(54) 
 
Race 1,070
(100) 
901
(100) 
 
 White 755
(70.6) 
664
(73.7) 
105
(13.9) 
         60
(8.0) 
 28
(3.7) 
 505
(66.9) 
100
(15.1) 
 Indigenous or other 315
(29.4) 
237
(26.3) 
83
(26.4) 
         13
(4.1) 
 28
(8.9) 
 162
(51.4) 
22
(9.3) 
 Born in Canada 1,061
(100) 
895
(100) 
 
 Yes 698
(65.8) 
627
(70.1) 
88
(12.6) 
         58
(8.3) 
 29
(4.2) 
 466
(66.8) 
 
 No 363
(34.2) 
268
(29.9) 
98
(27.0) 
         14
(3.9) 
 27
(7.4) 
 196
(54.0) 
 
Food insecurity 1,070
(100) 
901
(100) 
 
 Yes 309
(28.9) 
275
(30.5) 
66
(21.4) 
86
(31.3) 
   60
(21.8) 
          
 No 761
(71.1) 
626
(69.5) 
122
(16.0) 
251
(40.1) 
   90
(14.4) 
          
Duration of diabetes 1,061
(100) 
898
(100) 
 
 <10 years 582
(54.9) 
493
(54.9) 
                
 >10 years 479
(45.1) 
405
(45.1) 
                
Self-perceived health 1,058
(100) 
893
(100) 
 
 Excellent/very good/good 754
(71.3) 
619
(69.3) 
                
 Fair/poor 304
(28.7) 
274
(30.7) 
                
Insulin use 1,056
(100) 
894
(100) 
 
 Yes 587
(55.6) 
517
(57.8) 
77
(13.1) 
            90
(17.4) 
400
(68.1) 
 
 No 469
(44.4) 
377
(42.2) 
105
(22.4) 
            41
(10.9) 
263
(56.1) 
 
 Marital status 1,055
(100) 
890
(100) 
 
 Partnered 726
(68.8) 
605
(68.0) 
143
(19.7) 
             427
(58.8) 
 
 Single 329
(31.2) 
285
(32.0) 
42
(12.8) 
             232
(70.5) 
 
Community size 1,060
(100) 
896
(100) 
 
 Small city/rural 196
(18.5) 
171
(19.1) 
  1
(0.5) 
 6
(3.1) 
           
 Medium/large city 864
(81.5) 
725
(80.9) 
  0
(0.0) 
 10
(1.2) 
           
Employment 1,033
(100) 
874
(100) 
 
 Employed/full-time student 550
(53.2) 
488
(55.8) 
   16 (3.3)  94
(19.3) 
20
(3.6) 
       364
(66.2) 
 
 Unemployed/retired 483
(46.8) 
386
(44.2) 
   35
(9.1) 
 52
(13.5) 
31
(6.4) 
       278
(57.6) 
 
Education 1,049
(100) 
886
(100) 
 
 Less than university degree 500
(47.7) 
425
(48.0) 
 175
(41.2) 
              
 At least university degree 549
(52.3) 
461
(52.0) 
 156
(33.8) 
              

Data are n (%). Values are only presented if the difference was statistically significant. Bar, barriers; CAD, Canadian dollars; Fac, facilitators.

In many cases, cognitive capability was the result of the care context and information a participant had received, in the form of knowledge (e.g., “when you understand what they are trying to achieve, it makes it more comfortable”), skills (e.g., “the ability to test my blood sugar level to see where it’s at”), and regulating their everyday health behaviors and lifestyles (e.g., “it is just an everyday thing for me now. I have been at it so many years, I am confident in managing my diabetes. It is second nature”).

Automatic motivation included reinforcement, and many spoke of how both self-monitoring blood glucose levels and getting regular A1C tests helped to reinforce good self-management. For example, one participant listed “reading my blood test monitor, keeping track of what I eat, then taking my blood sugar levels after.” While this theme also included emotion, this aspect was never cited as a facilitator.

Despite cognitive capabilities being one of the most commonly cited facilitators, challenges with cognitive issues were also the top-cited barriers (37.4%), followed by lack of structural opportunities (16.7%), nature of diabetes-related behaviors (14.5%), and inadequate care context and information (13.5%) (Table 3). Cognitive elements were mentioned as a barrier when participants felt they lacked the requisite knowledge (e.g., “not being aware of how devastating the disease can be”) or skills (e.g., “I do not have a good way to log all my blood sugar levels”) or were unable to remember self-management tasks such as self-monitoring and taking medications or insulin, all of which resulted in a lack of self-regulation of behaviors (e.g., “not being able to eat whatever and whenever I want”). A lack of structural opportunities included those who faced financial barriers to diabetes self-management tasks (e.g., medications, testing supplies, and healthy foods) and those whose environmental contexts did not facilitate diabetes self-management (e.g., “I don’t work regular hours, and because of that, I don’t eat [at] a regular time. I am on the road a lot, and so meals are not taken at a regular time, and, also, I am not home to cook”). The nature of diabetes-related behaviors included individuals’ frustrations with various aspects of living with diabetes (e.g., “the inconsistency of blood sugar levels” and “I hate pricking my finger and find it irritating”). Inadequate care context and information was dominated by participants who had negative health care experiences (e.g., “The last doctor did not tell me what I needed to do. He was very condescending”) or wished they had better access to HCPs (e.g., “getting into programs . . . . They weren’t available at the times I could go”).

Those with poorly controlled diabetes (A1C ≥10%/≥86 mmol/mol) reported that care context and information were facilitators more frequently than those whose A1C was 7–8%/53–64 mmol/mol (65 vs. 56%, P = 0.003). The group with higher glycemia was also more likely to report that a lack of structural opportunities (e.g., environmental context and financial resources) was a significant barrier to their diabetes management (19 vs. 12%, P = 0.012). By contrast, those with lower A1C levels were more likely to report automatic motivation (e.g., reinforcement) as a facilitator compared with those who had higher A1C (11 vs. 5%, P <0.001) (Figure 1A).

FIGURE 1

Facilitators and barriers for patients with an A1C of 7–8 versus >10% (A), those with an annual income <$50,000 versus $50,000 Canadian dollars (B), those who are <65 versus >65 years of age (C), and who are female versus male (D).

FIGURE 1

Facilitators and barriers for patients with an A1C of 7–8 versus >10% (A), those with an annual income <$50,000 versus $50,000 Canadian dollars (B), those who are <65 versus >65 years of age (C), and who are female versus male (D).

Close modal

Individuals with an annual income <$50,000 CAD were more likely to report barriers in the subcategories of structural opportunities (20 vs. 15%, P = 0.042) and physical capability (8 vs. 3%, P <0.001). Furthermore, these participants were more likely than those with higher incomes to report that their cognitive capability (e.g., knowledge, memory, attention, decision processes, skills, and behavioral regulation) was a facilitator in diabetes management (21 vs. 13%, P <0.001). However, those with higher incomes were more likely than those with lower incomes to report care context and information as a facilitator (69 vs. 57%, P <0.001) (Figure 1B).

Those >65 years of age were more likely than younger participants to cite cognitive capability as either a barrier (46 vs. 33%, P <0.001) or a facilitator (23 vs. 15%, P = 0.001). Individuals <65 years of age were more likely than the older group to report barriers related to structural opportunities (19 vs. 11%, P = 0.004) and automatic motivation (e.g., reinforcement and emotion) (3 vs. 1%, P = 0.018); they were also more likely to report that care context and information was a facilitator to diabetes management (67 vs. 54%, P <0.001) (Figure 1C).

The only statistically significant difference between sexes was that females were slightly more likely than males to describe automatic motivation as a barrier (4 vs. 1%, P = 0.001) (Figure 1D).

Statistically significant differences in barriers and facilitators by each of the other characteristics are summarized in Table 3. There were no significant differences by duration of diabetes or self-perceived health. There was only one difference noted by level of educational attainment; cognitive difficulties were more common in those with lower education (41 vs. 34%). The proportion of respondents reporting that care context and information was a facilitator in their diabetes management differed frequently by a number of characteristics.

By contrast, the structural opportunities subcategory, including environmental context and financial resources, was largely reported as a barrier to diabetes management, with differential reporting among several of the group characteristics (i.e., reported more frequently in those who were younger, had higher A1C, and had lower incomes). The reflective motivation category (beliefs about capabilities, beliefs about consequences, optimism, intentions, goals, and social role and identity) was cited rarely (1.4% as a facilitator and 6.9% as a barrier) and did not vary significantly by any of the individual characteristics.

Our study provides an overview of patient-perceived facilitators and barriers to diabetes management through a unique approach of quantitizing qualitative data collected from open-ended questions through the use of manifest summative content analysis. Overall, the most commonly cited facilitators included care context and information (i.e., access to care, perceived quality of care, and information on diabetes) and cognitive capabilities (i.e., knowledge, memory, attention, decision processes, skills, and behavioral regulation). The most frequently cited barriers were in the BCW subcategories of cognitive capabilities and structural opportunities (i.e., environmental context and financial resources). Interventions to address these barriers, such as reducing patients’ financial burdens related to diabetes management, may have the potential to significantly improve diabetes care. Given that nearly 50% of participants cited cognitive aspects as their top barrier or facilitator, interventions that help reduce the cognitive burden of diabetes and increase patients’ knowledge and decision-making abilities around diabetes may be particularly impactful.

We found that the types of barriers and facilitators cited varied by a number of individual-level characteristics. However, the pattern of barriers and facilitators experienced by patients did not vary as much as one might have expected for some of the characteristics, such as glycemia. One reason for this finding may be that participants from all groups were asked to provide both a helpful factor and a hindering factor in their diabetes management, which may explain why we did not observe a significantly larger burden of barriers in those with elevated glycemia.

Our findings are consistent with other studies that have found that perceived quality of care, access to care, and behavioral regulation are crucial (11,32). Additionally, health literacy and knowledge about diabetes are known to empower patients and have a positive influence on diabetes outcomes (33). Automatic motivation (i.e., reinforcement behaviors and emotions) was the third most cited subcategory for helpful factors and was more frequent among those with lower A1C. This same construct was described as a barrier by others. This finding supports previous literature showing that patients need to be motivated to learn and adhere to management strategies (34). Other studies have shown that emotional regulation and emotional intelligence can positively affect glycemia (35,36). We identified that these factors seem to be more impactful for some groups (i.e., women, those born in Canada, and those of White race) than others, which to our knowledge has not been described previously in the literature.

Individuals with elevated A1C were more likely to report structural barriers (i.e., environmental context and financial resources) as being important factors in their diabetes management. Diabetes is accompanied by a sizeable financial burden (37) associated with the costs of healthy food, testing supplies, and medications (38). Financial barriers are especially common among those who do not have or who cannot afford supplementary health insurance (39). We previously showed that financial barriers were associated with income (23,40), which was again demonstrated in this study. Unsurprisingly, we found that those with lower incomes were more likely to cite lack of structural opportunities as barriers in their diabetes management. Furthermore, in Alberta, public drug insurance plans are principally directed to patients ≥65 years of age (22), while most younger patients have to purchase private insurance or pay out of pocket for prescription medications and diabetes testing supplies. This likely explains why we found that a lack of structural opportunities was more common among the younger group. Younger individuals, who are usually still in the workforce, are also most likely to be financially adversely affected by illness because of absenteeism (41).

This study adds to the previous literature on factors affecting diabetes management by leveraging patient perspectives from a large, heterogeneous group, thereby permitting meaningful comparisons across individual characteristics. Our findings highlight important differences among individuals’ perspectives of barriers and facilitators to diabetes management that relate to their individual circumstances. Although there were some significant differences by individual characteristics, these differences were not large enough to support generalized recommendations. Therefore, it is important that diabetes management plans be individualized rather than based solely on demographic characteristics. Our results equip HCPs with key characteristics to screen for in their patients as a starting point when constructing these individualized plans.

This study also highlights potential areas to address with regard to patient-cited barriers to diabetes management. Given our finding that only ∼30% of participants had seen a diabetes educator in the previous year, more health care resources could be devoted to enhancing patients’ care context by providing more educational resources embedded in their medical home (i.e., the services of a diabetes educator) to provide clear and relevant information. Once internalized, this information will hopefully lead to improved knowledge and skills. Furthermore, in certain subgroups, attention should be paid to addressing the structural and financial aspects of diabetes care. A sizeable proportion of participants found dealing with the nature and burden of diabetes to be difficult, suggesting that a greater emphasis on the psychosocial elements of diabetes care may be warranted, as suggested by national guidelines (4).

Limitations

There are some limitations to this work that should be acknowledged. First, ∼40% of the potentially eligible population participated in the survey. Although survey nonresponse can lead to biased results, only 18% (540/2,282) refused participation, which is a reasonable proportion. Next, quantitization sacrifices some of the richness of patient responses and may not fully reflect individuals’ thoughts and experiences. Recognizing this limitation, the large sample size in this study provided a significant breadth that allowed us to identify a number of factors that patients perceived to be affecting their diabetes management, which we illustrated with direct quotes in text and in Supplementary Appendix S1. Second, our cohort only captured participants who spoke English well enough to complete a telephone survey. Our recruitment did not capture individuals who do not speak English but are affected by diabetes and who may experience unique facilitators and barriers. Nevertheless, our sample did capture similar proportions of participants from ethnic groups seen in the general Alberta population. Third, only 4.2% of our sample reported living in a rural community. This proportion is not reflective of Alberta, where 14% live in rural areas, but our participants reflected the urban zone from which we sampled. Those in rural communities are known to have different access to health care and social supports, which can significantly affect their experiences; therefore, our findings may not fully represent this segment of the population. We did not capture what proportion of our sample had type 1 versus type 2 diabetes or other types of diabetes. Because management of different forms of diabetes varies, there may be related differences in barriers and facilitators. We did, however, consider differences between those using insulin versus those not using insulin, which should capture most of these differences. Finally, the generalizability of our findings is not certain, given that our study was conducted only in one Canadian province. Although it is likely that people with diabetes living elsewhere face similar barriers and facilitators, these experiences are context-dependent, and there may be some variation among different locations.

Using open-ended questions, this study highlighted individual patient experiences and perspectives on barriers and facilitators to diabetes management and how these vary by several individual characteristics, including glycemia. These perspectives can inform policy and practice modifications to improve patient experience. Improving health literacy, access to care, and quality of care and incorporating psychosocial care for diabetes patients would empower them to better manage their diabetes.

Funding

This study was funded by a Canadian Diabetes Association operating grant and by an Alberta Innovates–Health Solutions team grant to the Interdisciplinary Chronic Disease Collaboration. The funders were not involved in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Duality of Interest

No potential conflicts of interest relevant to this article were reported.

Author Contributions

D.J.T.C., L.D., N.I., B.M., M.T., C.N., B.H., and K.A.M. were involved in the conceptualization of this study. The analytic approach was developed by D.J.T.C., N.I., and K.A.M. Coding of data was completed by J.S. and R.L. and reviewed by D.J.T.C., A.M., and K.A.M. D.J.T.C., H.G., and K.A.M. analyzed and summarized the data. All authors contributed to the interpretation of the data. The first draft of the manuscript was written by D.J.T.C. and H.G. All authors contributed to and reviewed the manuscript critically for content. K.A.M. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation

This study was presented at the virtual Diabetes Canada/Canadian Society of Endocrinology and Metabolism Professional Conference, 28–30 October 2020.

This article contains supplementary material online at https://doi.org/10.2337/figshare.18651869.

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