The development of a clinical practice guideline for the audiological management of infants and young children with permanent unilateral hearing loss using an integrated knowledge translation approach
Bibliographic record
Abstract
OBJECTIVE: To describe the development and implementation of a management pathway for infants and young children identified with permanent unilateral hearing loss within an early hearing detection and intervention program in Ontario, Canada. DESIGN: An integrated knowledge translation approach was used to synthesise knowledge and generate a product: an updated clinical practice guideline. Current unilateral hearing loss guidelines were combined with the results of a scoping literature review focusing on technology options and outcomes for children with limited usable hearing unilaterally. COLLABORATORS: Five paediatric audiologists partnered with two researchers to develop the knowledge product. A draft was provided to 75 audiologists who provide amplification services and was subsequently tailored to support clinical uptake by incorporating the audiologists' comments. RESULTS: The updated clinical practice guideline describes a care pathway for children with unilateral hearing loss. Tools and graphics were developed as part of the integrated knowledge translation approach. Following standardised, competency-based training, the co-created guideline was implemented. CONCLUSIONS: Through an integrated knowledge translation approach, an updated unilateral hearing loss clinical practice guideline was co-created and implemented. The guideline provides information for the management of infants and young children with permanent unilateral hearing loss to support the operationalisation of current evidence-informed care.
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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 | 0.060 | 0.134 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".