Pain Management of Elderly in Nursing Homes
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to determine pain management status of the elderly in nursing homes. METHODS: The descriptive study sample included 82 elderly who presented to two nursing homes in İzmir between February-July 2012. In this study, Elderly Identification Form, Mini-Mental Scale, McGill Pain Scale (MAS) and Pain Management Inventory were used as the data collection tool. RESULTS: It was determined that the highest rates of complaints the elderly individuals had were knee pain (64.6%) and headache (58.5%) in this study. Of the elderly people participating in the study, 96.3% took pain relievers for pain management and according to their statements, of the pain management methods they used, resting and directing attention to something else (X=5.76±0.87) and taking prescribed pain relievers (X=5.69±0.87) were very beneficial. CONCLUSION: In elderly individuals, it is important to use pharmacological and non-pharmacological methods for pain management. Therefore, it is recommended to determine the most frequently used methods for pain management by the elderly and to integrate them into the care plan.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".