Compensatory beliefs about glucose testing are associated with low adherence to treatment and poor metabolic control in adolescents with type 1 diabetes
Bibliographic record
Abstract
The goal of this research was to investigate whether compensatory beliefs (CBs) regarding glucose testing predict blood glucose levels and adherence to treatment in adolescents with type 1 diabetes. CBs are convictions that the negative effects of one behavior (e.g. not testing one's glucose level) can be compensated for by engaging in another behavior (e.g. not eating any sweets). Adolescent patients from the Diabetes Clinic at the Montreal Children's Hospital and their parents filled out scales while coming for a regular visit. Results from their HbA(1c) blood test from that visit and prior visits were obtained from their medical records. Results showed that holding glucose testing CBs was associated with poorer HbA(1c) and poorer adherence to self-care behaviors. Hierarchical regression analyses showed that glucose testing CBs predicted blood glucose control and adherence to treatment above and beyond a number of other constructs including diabetes knowledge. Addressing CBs in diabetes education, in particular targeting those concerning glucose testing, could improve the adherence to treatment and thereby the long-term health of people with diabetes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".