The effect of alpha binaural beat music on orthodontic pain after initial archwire placement: A randomized controlled trial
Bibliographic record
Abstract
OBJECTIVE: The objective of this article was to evaluate the effect of alpha binaural beat music on pain level after initial placement of a maxillary fixed appliance, compared to music without binaural beats (placebo) and no music (control). METHODS: 60 patients undergoing maxillary fixed orthodontic appliance and initial archwire placement were randomly allocated into the three aforementioned groups. The pain level experienced was monitored for the following seven days, using the short-form McGill pain questionnaire (SF-MPQ). RESULTS / DESCRIPTORS: Intensity of both sensory and psychological aspects of pain reduced significantly in the binaural beat music (BBM) group, compared to the control, after the 5th day. Statistically significant lower affective and total pain scores were also found on day 6 for the placebo group, compared to the control. Present Pain Intensity (PPI): Statistically significant lower scores were found between the BBM group and the control group from days 3 to 7. Statistically significant lower scores were also found between the placebo and the control groups on days 4, 5 and 6. Visual Analog Scale (VAS): Compared to the control group, the placebo group had a lower VAS score on day 4, and the BBM group had lower scores on days 6 and 7. CONCLUSIONS: There was a significant reduction of pain demonstrated in the BBM group, compared to the control, toward the end of the first week of treatment. There was no difference in reported pain between the BBM and placebo groups for any of the scores.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".