The Behavior Pain Assessment Tool for critically ill adults: a validation study in 28 countries
Bibliographic record
Abstract
Many critically ill adults are unable to communicate their pain through self-report. The study purpose was to validate the use of the 8-item Behavior Pain Assessment Tool (BPAT) in patients hospitalized in 192 intensive care units from 28 countries. A total of 4812 procedures in 3851 patients were included in data analysis. Patients were assessed with the BPAT before and during procedures by 2 different raters (mostly nurses and physicians). Those who were able to self-report were asked to rate their pain intensity and pain distress on 0 to 10 numeric rating scales. Interrater reliability of behavioral observations was supported by moderate (0.43-0.60) to excellent (>0.60) kappa coefficients. Mixed effects multilevel logistic regression models showed that most behaviors were more likely to be present during the procedure than before and in less sedated patients, demonstrating discriminant validation of the tool use. Regarding criterion validation, moderate positive correlations were found during procedures between the mean BPAT scores and the mean pain intensity (r = 0.54) and pain distress (r = 0.49) scores (P < 0.001). Regression models showed that all behaviors were significant predictors of pain intensity and pain distress, accounting for 35% and 29% of their total variance, respectively. A BPAT cut-point score >3.5 could classify patients with or without severe levels (≥8) of pain intensity and distress with sensitivity and specificity findings ranging from 61.8% to 75.1%. The BPAT was found to be reliable and valid. Its feasibility for use in practice and the effect of its clinical implementation on patient pain and intensive care unit outcomes need further research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.135 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".