Managing pain medications in long-term care: nurses' views
Bibliographic record
Abstract
The purpose of this study was to explore nurses' perceptions of their current practices related to administering pain medications to long-term care (LTC) residents. A cross-sectional survey design was used, including both quantitative and open-ended questions. Data were collected from 165 nurses (59% response rate) at nine LTC homes in southern Ontario, Canada. The majority (85%) felt that the medication administration system was adequate to help them manage residents' pain and 98% felt comfortable administering narcotics. In deciding to administer a narcotic, nurses were influenced by pain assessments, physician orders, diagnosis, past history, effectiveness of non-narcotics and fear of making dosage miscalculations or developing addictions. Finally, most nurses stated that they trusted the physicians and pharmacists to ensure orders were safe. These findings highlight nurses' perceptions of managing pain medications in LTC and related areas where continuing education initiatives for nurses are needed.
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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 | 0.001 | 0.000 |
| 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".