Evaluation of a tracheostomy education programme for speech–language therapists
Bibliographic record
Abstract
BACKGROUND: Tracheostomy management is considered an area of advanced practice for speech-language therapists (SLTs) internationally. Infrequent exposure and limited access to specialist SLTs are barriers to competency development. AIMS: To evaluate the benefits of postgraduate tracheostomy education programme for SLTs working with children and adults. METHODS & PROCEDURES: A total of 35 SLTs participated in the programme, which included a 1-day tracheostomy simulation-based workshop. Before the workshop, SLTs took an online knowledge quiz and then completed a theory package. The workshop consisted of part-task skill learning and simulated scenarios. Scenarios were video recorded for delayed independent appraisal of participant performance. Manual skills were judged as (1) completed successfully, (2) completed inadequately/needed assistance or (3) lost opportunity. Core non-medical skills required when managing a crisis situation and overall performance were scored using an adapted Ottawa Global Rating Scale (GRS). Feedback from participants was collected and self-perceived confidence rated prior, immediately post and 4 months post-workshop. OUTCOMES & RESULTS: SLTs successfully performed 94% of manual tasks. Most SLTs (29 of 35) scored > 5 of 7 on all elements of the adapted Ottawa GRS. Workshop feedback was positive with significant increases in confidence ratings post-workshop and maintained at 4 months. CONCLUSIONS & IMPLICATIONS: Postgraduate tracheostomy education, using a flipped-classroom approach and low- and high-fidelity simulation, is an effective way to increase knowledge, confidence and manual skill performance in SLTs across patient populations. Simulation is a well-received method of learning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".