How “bad” does the pain have to be? A qualitative study examining adherence to pain medication in older adults with osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To explore the experience of adherence to pain medication in older adults with osteoarthritis (OA). METHODS: Individuals were recruited from an existing cohort (n = 1,300) of persons with disabling hip and knee OA. Twenty-seven individuals who reported previous physician visits for their arthritis, spoke English, were Toronto residents, and were receptive to in-depth interviews were approached by the cohort telephone interviewer to discuss their experiences with prescribed painkillers for OA. Semistructured face-to-face interviews were conducted by a qualitative researcher in participants' homes. RESULTS: Nineteen adults (10 women, 9 men) ages 67-92 years were interviewed for 1-3 hours. Participants varied in their socioeconomic status and education levels. Most had comorbidities, such as heart disease and diabetes, for which they were also being treated. Findings indicated that adherence to pain medication differed from that of other prescribed medications. Participants were reluctant to take painkillers, and when they did, they generally took them at a lower dose or frequency than prescribed. This behavior did not reflect their recommendations for others, who they expected to be treated appropriately for pain and to adhere to pain medication. Perceptions and attitudes to pain played an integral role in participants' adherence to painkillers. Despite obvious physical limitations, participants minimized their pain and claimed to have a high pain tolerance. CONCLUSION: These findings suggest that reevaluation of the prescription of pain medication for OA is warranted and that the effectiveness of pain management in OA needs to account for adherence behavior in older adults.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".