Reliability of the visual analog scale in children with acute pain in the emergency department
Bibliographic record
Abstract
In children, many psychometric properties of the visual analogue scale (VAS) are known, including the minimum clinically significant difference (10mm on a 100-mm VAS). However, its imprecision or reliability is not well known. Thus, in order to determine the reliability of this scale, a prospective cohort study was performed in patients aged 8-17 years presenting to a pediatric emergency department with acute pain. Pain was graded 4 times using a paper VAS (0-100mm): T(0), T(3), T(6), and T(≥ 36)minutes. After T(6), patients were asked if their pain had changed since T(0)minute. The primary analysis was the repeatability coefficient of the VAS, determined according to the Bland-Altman method for measuring agreement using repeated measures in patients reporting that their pain was the same for T(0), T(3), and T(6). In order to appropriately estimate the within-subject SD, 96 patients were required if we obtained 3 measurements for each patient. A total of 151 patients with a mean age of 12.2 ± 2.5 years were enrolled. Among them, 100 mentioned that their pain was the same for T(0), T(3), and T(6)minutes. The repeatability coefficient of the VAS for these children was 12 mm when the pain did not change. This implies that, for a child, all pain intensity measurements within 12 mm should be considered the same pain intensity on a paper VAS. This measure should also be evaluated on other types of VAS.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".