Preliminary clinical testing to inform development of the Critical Care Pain Observation Tool for Families (CPOT-Fam)
Bibliographic record
Abstract
Introduction Many patients in the intensive care unit (ICU) cannot communicate. For these patients, family caregivers (family members/ close friends) could assist in pain assessment. We previously adapted the Critical Care Pain Observation Tool (CPOT) for family caregiver use (CPOT-Fam). In this study, we conducted preliminary clinical evaluation of the CPOT-Fam to inform further tool development.Methods CPOT-Fam preliminary testing: We collected 1) pain assessments of ICU patients from family caregivers (CPOT-Fam) and nurses (CPOT) and determined the degree of agreement (kappa coefficient (κ)), and 2) collected open-ended feedback on the CPOT-Fam from family caregivers.CPOT-Fam refinement: We used preliminary testing data to refine the CPOT-Fam with a multidisciplinary working group.Results We assessed agreement between family caregiver and nurse pain scores for 29 patients. Binary agreement (κ) between CPOT-Fam and CPOT item scores (scores ≥2 considered indicative of significant pain) was fair, κ=0.43 (95% confidence interval [CI] 0.18-0.69). Agreement was highest for the CPOT-Fam items ventilator compliance/vocalization (weighted κ= 0.48, 95% CI 0.15-0.80) and lowest for muscle tension (weighted κ= 0.10, 95% [CI] -0.17-0.20). Most participants (n=19; 69.0%) reported a very positive experience using the CPOT-Fam, describing it as “good” and “easy-to-use/clear/straightforward”. We iteratively refined the CPOT-Fam over five cycles using the data collected until no further revisions were suggested.Conclusion Our preliminary clinical testing suggests that family involvement in pain assessment in the ICU is well perceived. The CPOT-Fam has been further refined and is now ready for clinical pilot testing to determine its feasibility and acceptability.
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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 | 0.075 | 0.122 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".