694-P: Differences in Diabetes-Related Stigma by Demographic Group and Intensity of Diabetes Management
Bibliographic record
Abstract
The social stigma surrounding diabetes refers to the negative attitudes, discrimination, or prejudice someone may face due to their diabetes. For many people with diabetes (PWD), stigma is a major challenge and often results in significant negative consequences, such as poor psychological well-being and worse clinical outcomes. This study aimed to identify groups who may be at greater risk of experiencing stigma. From October-December 2022, 10,338 adults living with diabetes in the United States, Canada, France, Germany, Italy, Netherlands, Sweden, and United Kingdom took an online survey assessing stigma associated with diabetes. Stigma was measured using four items about concealing or difficulty disclosing one's diabetes as well as diabetes-related embarrassment and isolation. These four items were averaged to create a composite variable on degree of stigma experienced (α = 0.87, M = 1.82, SD = 0.89). Subsequent responses were analyzed by various demographic factors and diabetes management strategies using SPSS. Stigma levels differ by intensity of diabetes management; respondents with more demanding diabetes management regimens experience greater levels of stigma. CGM users (p<0.001) and insulin users (p<0.001) experience more stigma than non-users, and PWD taking multiple daily injections experience more stigma than pump users (p=0.027). Stigma also varies across several demographic factors. French respondents report the highest stigma score, while German respondents report the lowest. Further, people with T1D experience more stigma than those with T2D (p<0.001). This research reveals differences in diabetes-related stigma by country and diabetes type and suggests that stigma becomes more prevalent with more intensive diabetes management. Additional research is needed to further explore experiences of stigma and identify methods of support, especially for at-risk groups. Disclosure A.Zeng: Employee; dQ&A. E.Lin: Employee; dQ&A. E.Cox: Employee; dQ&A. E.Xu: Employee; dQ&A. T.Bell: Employee; dQ&A. T.L.Bristow: Employee; dQ&A.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".