Pain assessment of elderly with neurocognitive disorders in long-term care: an occupational lens
Bibliographic record
Abstract
Abstract Background Occupational performance of older adults living in long-term care facilities is influenced by environmental possibilities and service provision. Pain among older adults with neurocognitive disorders might be a factor mitigating functional status. However, pain evaluation during daily routine through advanced stages of the disorder is scarce. Objective Identify pain-related behaviors of older adults with neurocognitive disorders during their morning routine in long-term care facilities. Methods A multiple-case study based on an embedded concurrent mixed methods design (quan-QUAL) was conducted in Quebec (Canada) in three long-term care units. Older adults with a neurocognitive disorder were observed (from 7:00 to 12:00 AM) and evaluated through the accomplishment of their morning routine. Through inter- and intra-case analyses, pain assessment scales (PACSLAC-II, Algoplus and DS-DAT) and morning routine assessment (occupational therapist's observations of the person, occupations and environment, functional autonomy measure, field notes) were integrated in mixed methods matrixes. Results Sixteen (n = 16) participants (average age: 76 years old [59, 93]) with various but advanced functional declines and pain symptoms were included. Participants' significant occupations all related to basic activities of daily living. Hygiene care and getting dressed were occupations for which an alteration of occupational performance was identified. Conclusions During their morning routine, older adults with a neurocognitive disorder living in long-term care facilities are facing pain symptoms and occupational deprivation, limiting the fulfilment of their needs and their engagement in occupations. Accordingly, older adults' occupations in relation to their environment should also be considered in future studies investigating pain. Key messages Occupational performance of older adults with a neurocognitive disorder living in long term care facilities is limited to basic activities of daily living. Assessment of pain of patients with a neurocognitive disorder in long-term care units should include the identification of environmental and occupational factors contributing to this pain.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".