Bibliographic record
Abstract
The 21st century has seen a rapid evolution in technology designed for children with hearing loss. To maximize the potential for a child to benefit from 21st-century technology, it becomes critical to use a 21st-century fitting approach. To that end, I would like to propose the following “Pediatric Hearing Aid Fitting Bill of Rights.” In my opinion, every child with a hearing loss has a right to these fundamental aspects of a hearing instrument or FM fitting. (1) Early and accurate diagnosis and treatment The rapid decrease in the age at which hearing loss is first diagnosed is perhaps the greatest audiologic success story of the 21st century. To what extent this success leads to better outcomes is highly dependent on how quickly amplification is provided. Fortunately, today's diagnostic technology allows for frequency-specific audiometric data to be obtained early in a child's life. Audiologists can be more confident in the initial settings of instruments fitted at a very young age. (2) Appropriate, verified HA settings While Canada (DSL) and Australia (NAL) may debate which fitting rationale is better for children, the use of an empirically derived, audibility-friendly prescription is critical. Pediatric hearing aid settings are generally more aggressive since speech and language are still developing. Independent strategies such as DSL 5.0 and NAL-NL2 provide different prescriptions for infants and young children versus adults who acquire hearing loss later in life. Manufacturers' device-specific rationales are generally not developed with the needs of a child in mind and tend to be less audibility-driven. Once an appropriate fitting strategy is chosen, verification of the settings is critical. This is best achieved using a speech stimulus at multiple presentation levels. Using aided sound-field threshold data to evaluate the fitting gives an incomplete picture and can lead to inaccurate conclusions. Documenting real-ear output via in situ measures or by using a test box while incorporating child-specific real-ear-to-coupler-difference (RECD) values represents the best-case scenarios. If reliable measures cannot be made via probe microphone, use of appropriate, age-based average RECD values is critical. (3)Access to high-frequency speech cues With increases in hearing aid bandwidth, improvements in feedback-cancellation algorithms, and the advent of frequency-lowering technologies, the days of being satisfied with audibility out to 4000 Hz are numbered. For children with mild to moderately severe hearing loss, a wide bandwidth is generally indicated to maximize speech understanding. Fortunately, entry-level hearing aids with a wide bandwidth and phase-cancellation feedback algorithms are increasingly available. Bandwidth need not be sacrificed to cost considerations. In determining if a child is benefiting from aided high-frequency information, appropriate speech-testing materials are necessary. Word recognition in quiet using traditional pediatric speech measures may not be sensitive enough to capture the benefit obtained by a wider bandwidth. For children with greater degree of high-frequency loss for whom audibility cannot be provided or for those who are unable to extract information from the aided high-frequency signal, frequency-lowering technologies are a viable option. (4) Access to the teacher's voice Classrooms are often noisy and reverberant. The distance between the teacher and child varies. FM is a proven technology for overcoming these obstacles. “Right” #2 applies here as well, though. The combination of FM system with hearing instruments presents some unique challenges. Therefore, verification of the FM fitting is important. The same equipment used to verify the hearing aid fitting can be used to verify an FM fitting. The AAA has an excellent DVD on this. For rights #5-#10, see Hearing and Children in the May Hearing Journal!
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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.149 | 0.069 |
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".