Critical Care Nurses' Pain Assessment and Management Practices: A Survey in Canada
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Regular pain assessment can lead to decreased incidence of pain and shorter durations of mechanical ventilation and stays in the intensive care unit. OBJECTIVES: To document knowledge and perceptions of pain assessment and management practices among Canadian intensive care unit nurses. METHODS: A self-administered questionnaire was mailed to 3753 intensive care unit nurses identified through the 12 Canadian provincial/territorial nursing associations responsible for professional regulation. RESULTS: A total of 842 nurses (24%) responded, and 802 surveys could be evaluated. Nurses were significantly less likely (P < .001) to use a pain assessment tool for patients unable to communicate (267 nurses, 33%) than for patients able to self-report (712 nurses, 89%). Significantly fewer respondents (P < .001) rated behavioral pain assessment tools as moderately to extremely important (595 nurses, 74%) compared with self-report tools (703 nurses, 88%). Routine (>50% of the time) discussion of pain scores during nursing handover was reported by 492 nurses (61%), and targeting of analgesia to a pain score or other assessment parameters by physicians by 333 nurses (42%). Few nurses (n = 235; 29%) were aware of professional society guidelines for pain assessment and management. Routine use of a behavioral pain tool was associated with awareness of published guidelines (odds ratio, 2.5; 95% CI, 1.7-3.7) and clinical availability of the tool (odds ratio, 2.6; 95% CI, 1.6-4.3). CONCLUSIONS: A substantial proportion of intensive care unit nurses did not use pain assessment tools for patients unable to communicate and were unaware of pain management guidelines published by professional societies.
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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 | 0.001 | 0.003 |
| 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 it