Do patients' expectations influence their use of medications? Qualitative study.
Bibliographic record
Abstract
OBJECTIVE: To investigate whether patients' expectations influence how they take their medications by looking at the expectations patients have of their medications and the factors that affect these expectations. DESIGN: Qualitative study using in-depth interviews and a grounded-theory approach. SETTING: A large city in Ontario. PARTICIPANTS: A total of 18 community-dwelling adult patients taking medication for at least 6 months. METHOD: Both purposive and convenience sampling techniques were used. The initial strategy comprised stratified, maximum variation, and typical case sampling. The research team developed a semistructured interview guide after a preliminary review of the literature. Individual, face-to-face, in-depth interviews were conducted and audiotaped. At the end of the interviews, basic demographic information was collected. Interviewers were debriefed following each interview and their comments on relevant contextual information, general impressions of the interview, and possible changes to the interview guide were audiotaped. Audiotapes of each interview, including the debriefing, were transcribed verbatim, cleaned, and given a unique identifying number. At least 2 team members participated in analyzing the data using an operational code book that was modified to accommodate emerging themes as analysis continued. MAIN FINDINGS: Patients' expectations were more realistic than idealistic. Many participants acted on their expectations by changing their medication regimens on their own or by seeking additional information on their medications. Expectations were affected by patients' beliefs, past experiences with medications, relationships with their health care providers, other people's beliefs, and the cost of medication. Patients actively engaged in strategies to confirm or modify their expectations of their medications. CONCLUSION: A range of factors (most notably past experiences with medications and relationships with health care providers) influenced patients' expectations of their medications. More comprehensive discussion between patients and their health care providers about these factors could affect whether medications are used optimally.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".