A Square Peg in a Round Hole: Social Experiences of Living With Diabetes in Canada in 2024
Bibliographic record
Abstract
OBJECTIVES: Diabetes self-management often occurs in social contexts, around others without diabetes. International consensus identifies the pervasive presence of social stigma toward those with diabetes, negatively impacting health, well-being, and social and professional lives. In this study, we aimed to identify the social experiences of Canadian adults living with type 1 diabetes (T1D) or type 2 diabetes (T2D). METHODS: An online survey was completed by 1,799 adults with diabetes (T1D: n=786; T2D: n=1,013). The survey assessed diabetes stigma, emotional well-being, diabetes distress, quality of life, and health-care experiences. Analyses involved descriptives of stigma experiences and associations with other measures. RESULTS: Experiencing blame and judgment for having diabetes was common. For T1D, 73% of respondents reported people making unfair assumptions about their capabilities, and 69% reported being judged for what they eat. For T2D, 41% reported being stigmatized as having a "lifestyle disease," and 31% reported being judged for their food choices. Being treated differently due to diabetes was common: 54% with T1D reported being rejected, and 22% with T2D reported being treated as sick. Many respondents with T1D were concerned about managing diabetes in public (44.2%) and many with T2D were embarrassed about having diabetes (27.4%). Greater stigmatization was associated with lower general emotional well-being, greater diabetes distress, and greater negative impact on quality of life. CONCLUSIONS: Adults with T1D or T2D commonly experience stigmatization, negatively impacting well-being and quality of life. These data support changing the conversation about diabetes in ways that will lead to greater respect, empathy, and support for all people living with diabetes in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.043 | 0.009 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".