Language-specific approaches to reduce perioperative stress and anxiety related to anaesthesia for patients with limited English proficiency: A narrative review
Bibliographic record
Abstract
Many patients experience perioperative anxiety due to a variety of different reasons. Essential processes of shared decision-making and informed consent may help to mitigate anxiety, yet language barriers may hinder this particularly in diverse patient populations. As such, language-specific approaches in anaesthesia care play a crucial role in reducing perioperative stress and anxiety among patients with limited English proficiency. This review examines which methods during anaesthetic assessments and shared decision-making processes enable anaesthetists to communicate effectively with patients who have limited English proficiency and thereby reduce perioperative stress. Findings suggest that collaborating with patients in their native language significantly reduces anxiety and improves understanding, while transcreation - culturally adapted translation - enhances the effectiveness of communication. To decrease perioperative anxiety among populations with limited English proficiency and improve surgical outcomes, it is important to enhance anaesthesia-focused training for interpreters, increase diversity in the anaesthesia field, and develop culturally relevant patient education materials.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".