Hearing Care for Elders: A Personal Reflection on Participatory Action Learning With Primary Care Providers
Bibliographic record
Abstract
PURPOSE: This report is a reflective critical narrative of the authors' experience with an interdisciplinary collaboration of primary care providers (PCPs) and hearing health care providers (HHCPs) that followed the principles of participatory action research/learning. The goal for this report is to describe the 1st author's observed barriers to PCPs' willingness to learn about hearing health care and the subsequent facilitators to learning. METHOD: A team of PCPs and HHCPs created the "Communication: Hearing Loss in Elders" educational module. The module included (a) prereading developed from a combination of literature reviews and contextual factors and (b) a case study. RESULTS: The authors present the list of topics included in the module, and they reflect on why and how these topics were deemed important by the team. In particular, 2 topics were identified for motivating PCPs' behavior regarding hearing health care: (a) the overlap in symptoms and possible causation among depression, dementia, and hearing loss and (b) how hearing can affect efficiency of care regarding other health issues. CONCLUSIONS: This personal reflective narrative gives the authors' opinions about what can make for a successful collaboration and presents some hypotheses regarding information that may motivate behavior change with regard to hearing care.
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 | 0.042 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.020 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".