(644) Pain Experience Over 2 Years Among Older, Independently Living, Retirement Community Residents
Bibliographic record
Abstract
Authors: Jana M. Mossey, Rollin M. Gallagher, Sunil Verma, MCP Hahnemann University, Graduate Hospital Comprehensive Pain and Rehabilitation Center A 2-year study of 232 affluent, independently living residents from 25 Philadelphia retirement communities has provided a unique opportunity to investigate the longitudinal pain experience of older individuals. The study included repeated self reports of pain and pain sites. In-person interviews occurred at study enrollment and 6, 12, 18, and 24 months later. Three questions adapted from the McGill Questionnaire addressing the occurrence of pain, the number of very bad pain days, and the presence of associated activity interference allowed identification of 2-year pain experience profiles for 161 individuals with 5 completed interviews. Mean age was 80 years (SD=5.9); 18% were male. Remarkable consistency was observed in individual reported pain experiences over time. Seventeen participants (9%) reported either no or mild pain without interference at all interviews. 27 (15%) reported this pain experience at 4 interviews. At a fifth, severe pain without interference was reported. In contrast, 25 individuals (13%) reported severe, persistent pain and extensive activity interference at all 5 interviews. Nineteen (10%) reported less severe but interfering pain at each interview. Between these extremes, 35 individuals (19%) reported mild to moderate pain at most interviews but associated interference at one. Fifty-two subjects (29%) consistently reported moderate to severe pain and interference at 2 or 3 interviews. Pain profile groups were similar according to age, gender, and pain sites (Most common: back, extremities, and joints). Statistically significant differences (P<.01) were observed between pain experience profiles for depressive symptoms, physical functioning, self-reported health, and number of comorbid conditions. Expectedly, scores on these factors were poorest among the more serious, chronic pain experience profiles. The large proportion with severe, chronic or intermittent interfering pain (52%) suggests present pain treatment approaches and services are not effective. This is especially challenging since this affluent study population had excellent access to health resources.
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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 | 0.001 | 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) | 0.003 | 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".