Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The public is not well informed about matters relating to regional anesthesia. Previous studies concerning regional anesthesia have involved patients, surgeons, and anesthesiologists. This study is the first in-depth survey of the attitudes of the general public toward a number of commonly perceived fears about regional anesthesia. METHODS: A province-wide telephone survey was conducted in Alberta, Canada. The sample surveyed was representative of the adult population of the province and included an equal balance of urban and rural participants. General and regional anesthesia were defined, a scenario involving major knee surgery was described, and participants were asked to choose between regional and general anesthesia. Respondents were then questioned so their attitudes toward commonly perceived fears associated with regional anesthesia could be assessed. RESULTS: A total of 1,216 people were surveyed. A preference for regional or general anesthesia was not expressed in this scenario. Approximately 27% of respondents were very concerned about permanent paralysis, back injury, perioperative pain, seeing the surgical procedure, and the prospect of a needle in the back. Only 6% of individuals were concerned about headaches. CONCLUSIONS: The public's fears and conceptions about regional anesthesia are greatly distorted. The anesthesia community has not been successful in keeping the public informed about regional anesthesia. Future anesthesia-related educational programs should address the concerns of the public about anesthesia matters, particularly regional anesthesia.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".