Ear health and hearing in urban Aboriginal children
Bibliographic record
Abstract
OBJECTIVE: Evaluate ear health and hearing among urban Aboriginal children and quantify relationships with child, family and social factors. METHODS: Baseline questionnaire and ear health examinations from 1430 children with diagnoses (0.5-18 years) attending Aboriginal Health Services enrolled in SEARCH. Ear health outcomes were Otitis Media (OM), and hearing loss (three-frequency average hearing loss >20dB) diagnosed using pneumatic otoscopy, tympanometry, and audiometry. RESULTS: Half the children 0.5-3 years had OM (51.5%, 136/264). One third 0.5-18 years (30.4%; 435/1430) had OM, including 1.8% (26/1430) with perforation (0.8% chronic suppurative OM, 0.6% dry perforation and 0.4% acute OM with perforation). One quarter 0.5-18 years (25.7%; 279/1087) had hearing loss; 12.4% unilateral, 13.2% bilateral (70.6% with bilateral loss had concurrent OM). OM was associated with: younger age (0.5-<3 years versus 6-18 years) age-sex-site; adjusted prevalence ratio (aPR)=2.64, 95%, 2.18-3.19); attending childcare/preschool (aPR=1.24, 95%CI, 1.04-1.49); foster care (aPR=1.40, 95%CI, 1.10-1.79); previous ear infection/s (aPR=1.68, 95%CI, 1.42-1.98); and ≥2 people/bedroom (aPR=1.66, 95%CI, 1.24-2.21). Hearing impairment was associated with younger age (0.5-<6 years vs. ≥6 years aPR=1.89, 95%CI, 1.40-2.55) and previous ear infection (aPR=1.87, 95%CI, 1.31-2.68). CONCLUSIONS: Half the urban Aboriginal children in this cohort had OM and two-thirds with hearing impairment had OM. IMPLICATIONS FOR PUBLIC HEALTH: Findings highlight importance of early detection and support for ear health, particularly in pre-school-aged children with risk factors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".