Barriers and facilitators to implementation of serial point-of-care hearing tests using a novel iPad-based audiometry in platinum chemotherapy-treated cancer patients (pts).
Bibliographic record
Abstract
223 Background: Platinum-based chemotherapy agents cause significant hearing loss in 40-80% of treated cancer pts. Lack of follow-up serial testing has created gaps in knowledge regarding hearing loss onset, progression, and possible recovery between treatment cycles. This study aims to determine barriers and facilitators to implementation of a tablet-based point-of-care hearing test, as a serial screening tool to address these knowledge gaps. Methods: From Jul 2019 to Mar 2020, 53 pts receiving high dose platinum agents were recruited from three clinics (Thoracic, head and neck, and testicular cancer) at a comprehensive cancer centre, to undergo serial audiometry testing. Baseline hearing tests, mid cycles (3,6, and 9 weeks), and post treatment tests (3,6,9,12, 19 and 24 months) were completed during the pts’ clinic appointments. Clinical research coordinators (CRCs) collected feedback from physicians, nurses, and pts to identify barriers and facilitators of implementing serial point-of-care hearing tests in these clinics. An inductive and iterative approach was used to identify themes. Implementation was tailored and mapped to the CIHR Knowledge to Action Framework (KTA). Results: Barriers: Logistical barriers included: locating quiet and accessible rooms to administer the test; pts being distracted or interrupted while completing the test; presence of family members adding to noise levels; concerns over the serial testing during treatment; length of each test; and clinic staff burden. Facilitators: User-friendly self-administered tests; increasing healthcare staff education and pt management. Adapting to the local context: Logistical barriers were resolved by CRCs designating quiet spaces for the study to occur, and meeting pts upon arrival to utilize their wait time. A ‘hearing test in progress’ sign put on exam room doors prevented interruptions. CRCs utilized the test’s ‘assisted mode’ feature to keep pts attentive and/or accelerate the process. Low noise level was emphasized to obtain accurate test results. Pt engagement in their test results facilitated retention in the study. Test length may be shortened in the future by omitting low frequency testing. Conclusions: Participants and stakeholders expressed support for in-clinic hearing tests and identified personal and systemic barriers to implementation. These findings suggest that implementation should focus on addressing concerns related to accessible rooms, pt time investment and overall clinic flow.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".