Natural history and predictors of disturbed eating behaviour in girls with Type 1 diabetes
Bibliographic record
Abstract
AIM: To determine the natural history and psychosocial predictors of disturbed eating behaviour in girls with Type 1 diabetes (T1D) over a 1-year period. METHODS: One hundred and six girls with T1D, 9-13 years of age at Time 1, completed a Children's Eating Disorder Examination (cEDE) interview at Time 1 and again 1 year later (Time 2). Potential Time 1 predictors of Time 2 disturbed eating behaviour were body mass index (BMI), self-esteem, depressive symptoms, attachment to parents, and parental eating attitudes. Glycated haemoglobin (HbA(1c)) was measured. RESULTS: Disturbed eating behaviour was reported by 14% (15/106) of girls at Time 1, and 17% (18/106) at Time 2, and persisted in 8/15 girls over 1 year. Lower self-esteem, higher BMI and more disturbed maternal eating attitudes at Time 1 accounted for 35% of the variance in Time 2 cEDE score, while higher BMI and more disturbed attachment to one's mother predicted new-onset disturbed eating behaviour at Time 2. Glycaemic control was not associated with or predicted by disturbed eating behaviour. CONCLUSIONS: There was only moderate stability in disturbed eating behaviour status over a 1-year period. In this preliminary study, disturbed eating behaviour was associated with and, to a lesser degree, predicted by physical, psychological and family factors. Although the long-term clinical course of the mild disturbances identified is not known, prevention and early intervention efforts in this high-risk medical group should begin in the pre-teen years, and should probably target multiple factors in order to prevent the persistence and worsening of disturbed eating behaviour and its medical sequelae.
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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 | 0.000 | 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".