Study protocol: development and pilot testing of the Critical Care Pain Observation Tool for families (CPOT-Fam)
Bibliographic record
Abstract
BACKGROUND: Patients in the intensive care unit (ICU) often have limited ability to communicate making it more difficult to identify and effectively treat their pain. Family caregivers or close friends of critically ill patients may be able to identify signs of pain before the clinical care team and could potentially assist in routine pain assessments. This study will adapt the Critical Care Pain Observation Tool (CPOT) for use by family members to create the CPOT-Fam and compare family CPOT-Fam assessments with nurse-provided CPOT assessments for a given patient. METHODS: This study will be executed in two phases: 1) Development of the CPOT-Fam - A working group of patient partners, ICU clinicians, and researchers will adapt the CPOT for use by family caregivers (creating the CPOT-Fam) and produce an accompanying educational module to deliver information on pain and how to use the tool. The CPOT-Fam will undergo preclinical testing with participants (i.e., members of the public and family caregivers of critically ill adults), who will complete the educational module and provide CPOT-Fam scores on sample cases. Feedback on the CPOT-Fam will be collected. 2) Pilot testing the CPOT - Fam family caregivers of critically ill adults will complete the educational module and provide information on the following: (1) demographics, (2) anxiety, (3) caregiving self-efficacy, and (4) satisfaction with care in the ICU. Family caregivers will then provide a proxy assessment of their critically ill loved one's pain through the CPOT-Fam and also provide a subjective (i.e., questionnaire-based including open-ended responses) account of their loved one's pain status. A comparison (i.e., agreement) will be made between family caregiver provided CPOT-Fam scores and ICU nurse-provided CPOT scores (collected from the provincial health information system), calculated independently and blinded to one another. Feasibility and acceptability of the CPOT-Fam will be determined. DISCUSSION: The results of this work will produce a family caregiver CPOT (i.e., CPOT-Fam), determine feasibility and acceptability of the CPOT-Fam, and compare pain assessments conducted by family caregivers and ICU nurses. The results will inform whether a larger study to determine a role for family caregivers in ICU pain assessment using the CPOT-Fam is warranted.
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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 | 0.080 | 0.088 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.069 | 0.023 |
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".