A randomized, single-blind, placebo-controlled trial to evaluate the effectiveness of verbal behavior modification and acetaminophen on orthodontic pain
Bibliographic record
Abstract
ABSTRACT Objectives: To evaluate the effectiveness of verbal behavior modification, acetaminophen, and the combined effectiveness of verbal behavior modification along with acetaminophen on orthodontic pain. Materials and Methods: One hundred and forty orthodontic fixed appliance patients were randomly assigned to four groups. Group A was administered acetaminophen, group B was given verbal behavior modification, group C was administered acetaminophen as well as verbal behavior modification, and group D was placebo-controlled. A visual analog scale was used to assess pain intensity after 1 week of separator placement. Results: Group A had less mean pain intensity when compared to group B at 6 hours ( P < .001) and at 1 ( P < .001) and 2 ( P = .002) days. Group C patients encountered less mean pain intensity when compared to group B patients at 6 hours ( P < .001) and at 1 ( P < .001), 2 ( P < .001), and 4 ( P = .001) days. There was a statistically significant difference between groups A and C (group C experienced less pain intensity) after 6 hours ( P = .004) and at day 4 ( P = .009) after separator placement. Conclusions: Acetaminophen is the main agent of orthodontic pain reduction after separator placement, with verbal behavior serving as an adjunct to it.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".