ARE YOU HURTING? FACTORS ASSOCIATED WITH PROXY REPORTED PAIN SEVERITY IN COMMUNITY-DWELLING PERSONS WITH DEMENTIA
Bibliographic record
Abstract
Under-recognized pain is associated with agitation and poor outcomes in persons with dementia (PWD). The present study examined factors related to caregiver’s proxy reported pain severity in a sample of 36 community-dwelling veterans with dementia and their caregivers, participating in a telephone-based intervention study. Caregivers were 86% female and 28% Black with a mean age of 63.06 years, and PWD were 96% male and 23% Black with a mean age of 74.08 years. Results indicated a strong concordance between caregiver/proxy and PWD self-reported pain severity (r = .718, p < .001). Additionally, caregiver/proxy reports of pain severity were significantly associated with caregivers’ own level of mindfulness (r = .380, p = .022) as well as the caregivers’ proxy reports of the PWD’s depression, quality of life, and stress level (r = .504, p = .002; r = -.434, p = .008; r = .339, p = .046, respectively). PWD’s self-reported pain was significantly related to caregivers’ proxy reported depression and quality of life (r = -.445, p = .023; r = .504, p = .009, respectively), but unrelated to perceived stress (p > .10). The PWD’s cognitive status (measured by the Montreal Cognitive Assessment) and caregiver burden were not related to pain severity in this sample (p’s > .5). Results suggest that the factors associated with caregivers’ proxy reports of pain are complex. Further research is needed to better understand the factors contributing to caregiver/proxy reports of PWD pain severity in order to support caregivers in managing pain in PWD.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".