Stigma and Its Association With Glycemic Control and Hypoglycemia in Adolescents and Young Adults With Type 1 Diabetes: Cross-Sectional Study
Bibliographic record
Abstract
Background: Qualitative studies in type 1 diabetes indicate that visibility of diabetes supplies, self-care, and hypoglycemia symptoms are associated with stigma and suboptimal management. This may be particularly salient in youth who face concurrent challenges such as establishing autonomy and making vocational choices. Objective: The aim of the study was to estimate stigma prevalence in youth (aged 14-24 years) with type 1 diabetes and its associations with glycemic control. Methods: Participants, recruited largely through social media, were asked to complete a Web-based survey and to send via mail capillary blood samples for glycated hemoglobin (HbA1c) measurement. The primary definition of stigma required endorsement of one or more of 3 stigma-specific items of the Barriers to Diabetes Adherence questionnaire. These addressed avoidance of diabetes management with friends present, difficulty telling others about diabetes diagnosis, and embarrassment in performing diabetes care with others present. Poor glycemic control was defined as HbA1c>9% (ie, >75 mmol/mol; measured value when available, else self-report) and/or ≥1 severe hypoglycemic episode in the previous year (reported requiring assistance from someone else during the episode). Stigma prevalence was computed (95% CI), and associations with glycemic control were evaluated (multivariate logistic regression models). Results: Among the 380 respondents, stigma prevalence was 65.5% (95% CI 60.7-70.3). Stigma was associated with a 2-fold higher odds of poor glycemic control overall (odds ratio [OR] 2.25, 95% CI 1.33-3.80; adjusted for age, sex, and type of treatment). There were specific associations with both HbA1c>9% (75 mmol/mol; OR 3.05, 95% CI 1.36-6.86) and severe hypoglycemia in the previous year (OR 1.86, 95% CI 1.05-3.31). Conclusions: There is a high prevalence of stigma in youth with type 1 diabetes that is associated with both elevated HbA1c levels and severe hypoglycemia. Targeted strategies to address stigma are needed. Trial Registration: ClinicalTrials.gov NCT02796248; http://clinicaltrials.gov/ct2/show/NCT02796248 (Archived by WebCite at http://www.webcitation.org/6yisxeV0B)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".