Caregiver knowledge of hypoglycemia and hyperglycemia management in children and adolescents with type 1 diabetes
Bibliographic record
Abstract
Objective To determine the current knowledge of the assessment and management of acute diabetes-related complications including severe hypoglycemia and diabetic ketoacidosis (DKA) among caregivers of patients with type 1 diabetes (T1D). Methods A cross-sectional survey was completed at a tertiary care pediatric hospital diabetes clinic from November 2021 to July 2022. Data was analyzed from all completed survey responses and included both Likert and evaluation-style questions. Results A total of 152 surveys were collected and 96 were included in the analysis. Caregiver knowledge on management of hypoglycemia was significantly better than their knowledge on hyperglycemia management (median score 100% vs 60%, p-value <0.001). There was no difference in caregiver knowledge around assessment of hypoglycemia or hyperglycemia (median score 88.9% vs 88.9%, p-value 0.909). There was no significant difference in overall knowledge as determined by percentage of questions correct between those on different blood glucose monitors (p-value 0.184) or whether the parent/caregiver or the patient were primarily responsible for T1D management (p-value 0.964). There was no difference in total score by management type when adjusted using the Bonferroni method. There was also no significant interaction by level of caregiver involvement. Conclusions Caregiver knowledge of management of hypoglycemia was significantly better than their knowledge of management of hyperglycemia in pediatric T1D. Blood glucose monitoring or T1D management type was not found to be associated with any differences in caregiver knowledge in the assessment or management of hypoglycemia or hyperglycemia.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".