Eating Disorders in Adolescent Girls and Young Adult Women With Type 1 Diabetes
Bibliographic record
Abstract
Dennis Daneman, MB, BCh, FRCPC Teens with type 1 diabetes face two clashing realities. On the one hand, the results of studies such as the Diabetes Control and Complications Trial (DCCT) provide irrefutable evidence of the link between diabetes control and the onset and progression of diabetes-related microvascular complications.1 The DCCT message was loud and clear: Control counts! On the other hand, there are numerous studies, including the DCCT, demonstrating that, during adolescence, metabolic control tends to be poorest and that the goals of intensive diabetes management are more difficult to achieve.2,3 What are the reasons for poor glycemic control in adolescents with type 1 diabetes? I believe that it results from the complex interplay between biological (e.g., insulin resistance of puberty) and psychosocial (e.g., noncompliance, family environment) factors. Our group has focused on one specific contributing factor, namely, eating disorders in teenage girls with type 1 diabetes. This From Research to Practice section offers a review of this topic by our research group at the University of Toronto. This is a departure from the usual format of Diabetes Spectrum research sections in that the entire section comprises contributions from a single research group. A number of groups around the world have made substantial contributions to this field, and we have been as diligent as possible in citing their enormous contributions. However, we do hope that our group has been able to provide a unifying view of the pathophysiology and impact of eating disturbances in girls and young women with type 1 diabetes. Our aim is to sensitize readers to the manifestations of this common co-morbidity and to highlight areas where further research is warranted. Because this monograph-style presentation represents the combined efforts of all of the authors, we have listed only the primary contributors to …
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".