Resource development in otolaryngology-head and neck surgery: An analysis on patient education resource development
Bibliographic record
Abstract
BACKGROUND: There is a need for educational tools in the consenting process of otolaryngology-head and neck procedures. A development strategy for the creation of educational tools in otolaryngology-head and neck surgery, particularly pamphlets on the peri-operative period in an adenotonsillectomy, is described. METHODS: A participatory design approach, which engages key stakeholders in the development of an educational tool, is used. Pamphlets were created through a review of traditional and grey literature and then reviewed by a community expert in the field. The pamphlets were then reviewed by an interdisciplinary team including educational experts, and finally by less vulnerable members of the target population. Questionnaires evaluating the pamphlets' content, layout, style, and general qualitative features were included. RESULTS: The pamphlets yielded high ratings across all domains regardless of patient population. General feedback was provided by a non-vulnerable patient population and final pamphlets were drafted. CONCLUSIONS: By using a participatory design model, the pamphlets are written at an appropriate educational level to incorporate a broad audience. Furthermore, this methodology can be used in future resource development of educational tools.
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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 | 0.034 | 0.107 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".