What influences seniors' choice of medications for osteoarthritis? Qualitative inquiry.
Bibliographic record
Abstract
OBJECTIVE: To explore with seniors what influences their choice of medication for osteoarthritis. DESIGN: Qualitative study using semistructured in-depth interviews. SETTING: Interviews were conducted in patients' homes in two cities in Nova Scotia. PARTICIPANTS: Seniors with a physician-confirmed diagnosis of osteoarthritis. METHOD: Interviews were audiotaped and transcribed verbatim. A grounded-theory approach was used. Key words and phrases were identified independently by all members of the research team who then collectively grouped the data into conceptual categories. MAIN FINDINGS: Four themes emerged from discussions about medication choices: the role of family physicians in influencing use of cyclooxygenase-2 inhibitors, the effect of fear of making medication choices, the reasons for discontinuing cyclooxygenase-2 inhibitors, and views on other information sources. Distribution of free samples, family physicians' recommendations, and fear of side effects influenced seniors' choices of osteoarthritis medications. They claimed not to be influenced by direct-to-consumer advertising or the fact that cyclooxygenase-2 inhibitors are more expensive than other classes of drugs for osteoarthritis. CONCLUSION: Because seniors' choice of medications for osteoarthritis is often influenced by physicians' recommendations and distribution of free samples, further research into how distribution of free samples affects medication choices in family practice is needed.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".