Patient Education and Informed Consent in Head and Neck Surgery
Bibliographic record
Abstract
OBJECTIVE: To examine the effects of an educational intervention, in the form of printed material, on patient knowledge and recall of possible risks from parotidectomy or thyroidectomy. DESIGN: Prospective, randomized, controlled study conducted during a 9-month period. SETTING: Head and neck surgery clinic of an academic tertiary care hospital. PATIENTS: One hundred twenty-five consecutive patients older than 16 years who were undergoing thyroidectomy or parotidectomy at the head and neck surgery clinic were recruited. Four patients were excluded from analysis because their follow-up interview was not within the required limits. INTERVENTION: At the preoperative visit during the routine consent process, both groups received a verbally delivered checklist of risks specific for the surgery to be performed. The intervention group was also given a pamphlet with written information accompanied by illustrations. MAIN OUTCOME MEASURES: The effectiveness of the educational intervention was determined by comparing the average rate of risk recall between the intervention and control groups. The effects of age, sex, level of education, and time between the consent and recall interviews on recall rate were also assessed. RESULTS: The overall risk recall rate for both procedures was 39.1%. The recall rate of the intervention group was 50.3% compared with 29.5% for the control group (P<.001). CONCLUSIONS: The intervention consistently improved risk recall for all patients regardless of age, sex, and level of education. Patients' ability to recall potential risks was significantly increased by an educational intervention; all patients would benefit from this intervention.
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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 | 0.015 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".