Pilot evaluation of a protocol and a clinical tool developed to assess the audiological needs of adults with hearing loss
Bibliographic record
Abstract
Objective: To evaluate the Québec Audiological Assessment Protocol for Younger and Older Adults (QAAP-YOA) and its accompanying clinical tool efficacy to assess the needs of individuals with hearing loss in a simulated context. This study is the Phase 2 in the development of the QAAP-YOA. Design: Participants completed two needs assessments with simulated clients and wrote audiological reports, while applying the QAAP-YOA with and without the use of its clinical tool. Interviews were filmed, and reports collected. Both were scored by two independent evaluators. A qualitative analysis of reports was also conducted. Study sample: Eleven audiology students and four early-career audiologists (n = 15). Results: The clinical tool did not influence the interview process since both experimental conditions had similar compliance rates to the protocol (p = 0.114). Compliance rates for assessment reports were higher with the clinical tool (p < 0.001). Participants’ conclusions after applying the QAAP-YOA were consistent across participants. The information provided in the reports was more comprehensive and coherent with the client’s needs when participants used the clinical tool. Conclusions: The QAAP-YOA can lead to a greater standardisation of needs assessments and to more comprehensive reports, which may lead to intervention programs more closely aligned with clients’ needs.
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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 | 0.153 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".