Higher Incidence of Psychiatrist-Diagnosed Depression in Taiwanese Female School-Age Children and Adolescents with Type 1 Diabetes: A Nationwide, Population-Based, Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to investigate the risk of clinical depression associated with type 1 diabetes in female Taiwanese children and adolescents. METHODS: Using Taiwan's National Health Insurance Research Database, we identified 1373 female children and adolescents, aged 5-18 years, with type 1 diabetes diagnosed between 2000 and 2007. A comparison cohort was assembled, which consisted of 20 patients without type 1 diabetes, based on frequency matching for age interval and index year for each patient with type 1 diabetes. Both groups were followed until a psychiatrist diagnosed depression or the end of the follow-up period, up to a maximum period of 5 years from the index date. A Poisson regression model was used to calculate incidence rate ratios (IRRs) for depression between the type 1 diabetes cohort and the comparison cohort. RESULTS: The incidence rate of depression in the type 1 diabetes cohort was 228.4 per 100,000 person-years and that in the comparison cohort was 73.9 per 100,000 person-years. The type 1 diabetes cohort showed a significantly higher incidence of depression compared with the comparison cohort (IRR of 3.09, p < 0.001). CONCLUSION: Findings from this nationwide, population-based, retrospective cohort study showed that the incidence of psychiatrist-diagnosed depression was significantly higher in female Taiwanese school-age children and adolescents with type 1 diabetes compared with those without the disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".