Fear of hypoglycemia relates to glycemic levels during and after real‐world physical activity in adolescents with type 1 diabetes
Bibliographic record
Abstract
BACKGROUND: We explore the association between hypoglycaemia fear (FH) and glycaemia during and after exercise sessions in a large sample of physically active youth with type 1 diabetes (T1D). METHODS: We used data from the Type 1 Diabetes Exercise Initiative Paediatric (T1DEXIP) Study. Youth self-reported on FH using the Hypoglycaemia Fear Survey-Child (HFS-C). They used a smart phone application to self-report food intake and insulin dosing (multiple daily injection only). We collected pump and continuous glucose monitoring data directly from the device. RESULTS: Our sample included n = 251 youth (mean age: 14 ± 2 years, 55% closed loop pump; 42% women). Youth reporting higher HFS-C Total and Helplessness/Worry scores (HFS-C subscale) had slightly fewer competitive and fewer high intensity exercise events compared to youth with lower HFS-C Total and Helplessness/Worry scores. Youth reporting the highest Maintain High Blood Glucose scores (HFS-C subscale) had the lowest percent glucose time in range, higher mean glucose levels, and higher percent time above range during exercise. Youth reporting the highest Maintain High Blood Glucose scores also tended to have higher mean glucose levels post-exercise and a smaller drop in glucose during exercise. CONCLUSION: FH relates to glycaemia during and after exercise in adolescents with T1D and may signal an inclination for some youth to engage in avoidance behaviours to reduce their vulnerability to exercise-induced hypoglycaemia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".