Pain behaviors observed during six common procedures: Results from Thunder Project II*
Bibliographic record
Abstract
OBJECTIVE: Patients frequently display behaviors during procedures that may be pain related. Clinicians often rely on the patient's demonstration of behaviors as a cue to presence of pain. The purpose of this study was to identify specific pain-related behaviors and factors that predict the degree of behavioral responses during the following procedures: turning, central venous catheter insertion, wound drain removal, wound care, tracheal suctioning, and femoral sheath removal. DESIGN: Prospective, descriptive study. SETTING: Multiple units in 169 hospitals in United States, Canada, England, and Australia. PATIENTS: A total of 5,957 adult patients who underwent one of the six procedures. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A 30-item behavior observation tool was used to note patients' behaviors before and during a procedure. By comparing behaviors exhibited before and during the procedure as well as behaviors in those with and without procedural pain (as noted on a 0-10 numeric rating scale), we identified specific procedural pain behaviors: grimacing, rigidity, wincing, shutting of eyes, verbalization, moaning, and clenching of fists. On average, there were significantly more behaviors exhibited by patients with vs. without procedural pain (3.5 vs. 1.8 behaviors; t = 38.3, df = 5072.5; 95% confidence interval, 1.6-1.8). Patients with procedural pain were at least three times more likely to have increased behavioral responses than patients without procedural pain. A simultaneous regression model determined that 33% of the variance in amount of pain behaviors exhibited during a procedure was explained by three factors: degree of procedural pain intensity, degree of procedural distress, and undergoing the turning procedure. CONCLUSIONS: Because of the strong relationship between procedural pain and behavioral responses, clinicians can use behavioral responses of verbal and nonverbal patients to plan for, implement, and evaluate analgesic interventions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".