Impact of Living with Stigma in Persons with Type 1 Diabetes: A Patient–Physician Perspective
Bibliographic record
Abstract
Type 1 diabetes mellitus (T1D) is an autoimmune disorder characterized by a complete deficiency in insulin due to the destruction of pancreatic beta cells. Globally, T1D accounts for nearly 5-10% of the total diabetes cases. Living with this life-long condition has a significant emotional, psychological, physical, mental, and social impact. Despite extensive research characterizing the underlying physiology of T1D, additional work is needed to address the psychosocial aspects associated with the condition and its effect on the quality of life (QoL) of people living with T1D. One area that warrants further exploration is the stigma-related stereotypes and prejudice of people living with T1D experience in real-life settings. Despite the acknowledgment of stigma for conditions such as obesity, mental illness, and epilepsy, its association with T1D and ensuing psychological distress remains relatively under-investigated. Health-related stigma is a huge barrier to seeking appropriate, timely support for enhanced healthcare management and engagement in such patients. Here, we provide the perspectives of an adult with over 33 years of living with T1D and an expert endocrinologist who details their experience of T1D-related stigma. The self-reported factors explored by the person living with T1D include (but are not limited to) blame, mockery of the condition/person, diabetes-related shame, exclusion, rejection, negative judgments, fear, stereotyping, and discrimination. The lived experience supported by the clinical insights of the endocrinologist highlights the urgent need to decipher the severity, extent, nature, determinants, and consequences of stigma faced by a person living with T1D. Raising societal awareness, increasing education for caregivers, access to counseling for people living with diabetes, and engaging in shared decision-making remain the path forward.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".