Universal newborn hearing screening: A question of evidence
Bibliographic record
Abstract
The objective of this paper is to present data on the ages of diagnosis and hearing-aid fitting of children with permanent congenital or early-onset hearing loss who were identified through neonatal hearing screening (NHS) programs or medical referral. Data were collected for 709 children born between 1980 and 2003. Children who were screened were diagnosed significantly earlier (mean 6.3 months) than referred children (mean 39.5 months). For the referred children, the ages of diagnosis and amplification improved over time but remained unacceptably high. In addition, there was an inverse relationship between degree of loss and age of diagnosis, with children with lesser degrees of hearing loss identified later than those with severe to profound hearing loss. These results contribute to the evidence that NHS programs lower the ages of diagnosis and amplification and lead to earlier improved hearing. It is argued that early access to hearing should be the desired primary outcome of NHS. The numerous studies demonstrating improved ages of diagnosis resulting from NHS programs constitute adequate evidence to support these initiatives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.122 | 0.416 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.012 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".