<scp>Postoperative patient‐centered</scp> multimedia education in head and neck cancer patients: A pilot study
Bibliographic record
Abstract
Objective: It is hypothesized that patients who are actively provided with more treatment-related education may report increased satisfaction and have improved overall outcomes. The aim of this study was to demonstrate the feasibility of an audiovisual education platform in patients undergoing head and neck surgery and to investigate whether patients using this module reported increased satisfaction. Methods: This was a prospective pilot study of patients undergoing major head and neck reconstructive surgery who were randomized to either (1) control group or (2) intervention (i.e., in-patient audiovisual educational module). Both study groups then completed a discharge survey. Results: = 19 Control). Patients in the intervention group reported an increased satisfaction with their overall outcome. Exactly 87.5% (14 of 16) found the intervention to be "Extremely useful," "Quite useful," or "Sometimes useful." Exactly 68.8% (11 of 16) would recommend similar patients to receive the same educational intervention. However, there was no significant difference in patients' perceived level of involvement amongst the two groups. For future improvements to the intervention, patients requested further information such as how to look after themselves, postoperative radiation, course in hospital, and nutrition. Conclusion: This pilot study demonstrated the feasibility of an audiovisual education platform in the postoperative setting for patients undergoing major head and neck reconstructive surgery. Although most patients found the module useful, future steps will incorporate patient feedback to further improve the educational platform and confirm the current preliminary impressions in prospective studies. Level of Evidence: 1b.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".