Broad responses and attitudes to having music in surgery (the BRAHMS study) – a South African perspective
Bibliographic record
Abstract
BACKGROUND: Music is played in operating theatres (OTs) throughout the world, though controversy around its use exists. While some clinicians may find background music favourable to the theatre mood and a way to augment surgical performance, there is concern raised over its distracting and noise-creating properties. METHODS: In this prospective observational study, between August and December 2021, 110 surgeons and registrars in South Africa responded to a survey investigating the way they use music, and their perceptions and attitudes towards its effect on the OT environment. RESULTS: In this cohort, 66% were male, 29% were consultants and the most common age range was 30-39 years old. Eighty per cent of respondents reported that music was played at least "sometimes", with 74% reporting that they enjoyed it. Easy Listening was the most played and preferred genre followed by Top 40/Billboard hits. Overwhelmingly, respondents reported that background music in the OT improved temperament, focus, mood, and performance, though over a quarter felt it worsened communication. Thirty-one per cent of respondents reported that the choice of music depended on the type of operation, and 70% would turn music down or off during crises. Those who enjoyed music in their spare time were significantly more likely to enjoy music in the OT and perceive it positively. CONCLUSION: This study provides a window into the surgeons' use of and attitudes to intraoperative music in South Africa. While overall, music is viewed positively by this cohort, some concerns remain regarding communication and distractedness. Further interventional and qualitative studies would be useful.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".