Predictors of stigma perception by people with type 1 diabetes: A cross-sectional analysis of the BETTER registry
Bibliographic record
Abstract
AIMS: This study investigates stigma predictors across ages and genders, addressing a critical gap in understanding diverse populations to reduce related suboptimal clinical and psychosocial outcomes. METHODS: Cross-sectional analysis of self-reported data from BETTER, a Canadian registry of people with type 1 diabetes. Participants (n = 709) completed the 19-item-Diabetes-Stigma Assessment-Scale (DSAS-1) categorized into treated differently, blame and judgment, and identity concerns sub-scales. Associations with diabetes distress (DDS-17-score/102), depression (PHQ-9-score/27), social-support (ESSI-score/34), fear of hypoglycemia (HFS-II-score/132), and hyperglycemia-avoidance-behaviours (HAS-score/88) were computed. RESULTS: Perceived stigma was highest in youth aged 14-24 years (46·0 ± 15·6, p < 0·001) and women (41·2 ± 15·7, p = 0·009), compared to other age groups and men. Blame and Judgment contributed to most of stigma perception. Youth perceived significantly more blame and judgment (p < 0·001) and identity concerns (p = 0·001) compared to middle-aged adults and seniors. Women perceive significantly more blame and judgment compared to men (p < 0·001). The perception of being treated differently was not reported to be an issue across ages and genders. Participants with higher scores of depression, diabetes-distress, fear of hypoglycemia, hyperglycemia-avoidance behaviours, and lesser social-support, reported increased stigma. CONCLUSIONS: Stigma varies by age and gender, underscoring the need for targeted interventions to reduce it. Challenging stereotypes and reducing stigma-related stressors are essential for better outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".