Pain and agitation in long-term care residents with dementia: use of the Pittsburgh Agitation Scale
Bibliographic record
Abstract
AIM: to explore the relationship between total and sub-scores of the Pittsburgh Agitation Scale (PAS) and five proxy measures of pain in long-term care (LTC) residents. STUDY DESIGN: descriptive correlational design. SAMPLE AND SETTING: 58 residents in three LTC facilities in rural Western Canada with moderate to severe cognitive impairment took part in the study. Six full-time registered nurses working in the facilities and three palliative care nurse consultants provided pain and agitation assessments. MEASUREMENTS: registered nurses used PAS to assess agitation. The five proxy measures of pain were the Discomfort Scale for Dementia of the Alzheimer's Type (DS-DAT), number of pain diagnoses, use of analgesic medications, and pain ratings by both facility nurses and palliative care nurse consultants. RESULTS: there was a moderately strong relationship between total PAS agitation scores and total DS-DAT pain scores (r=0.51, P<0.01). The PAS sub-score "resisting care" was significantly correlated with total DS-DAT scores (r=0.46, P<0.01), and pain ratings by both facility nurses (r=0.48, P<0.01) and palliative care nurse consultants (r=0.51, P<0.01). CONCLUSIONS: for certain residents with dementia, PAS may allow assessment of both agitation and uncommunicated pain. It is possible that the PAS form of agitation "resistance to care" may indicate pain that individual cannot otherwise communicate. One possible response to such resistance would be to trial pain medication and reassess agitation. Nursing staff in LTC facilities may need additional training in pain assessment of residents with dementia.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".