Effect of verbal encouragement on patient question-asking behaviour during medication counselling
Bibliographic record
Abstract
Abstract Context Empowering patients to take a more active role in health-related encounters is a goal of many advocates today. This stems from evidence that patients remain rather passive during interactions with doctors and pharmacists. Objective The objective of this study was to examine the effect of verbal encouragement on patient question-asking. It was hypothesised that encouragement to ask questions would elicit a freer flow of questioning. Method The study had two arms — intervention and control. The same prescription processing steps occurred for each group except that intervention subjects were presented with a short verbal message (to invite questioning) before the prescription was handed over to a pharmacist for filling. Any questions patients raised during subsequent medication counselling were recorded. Observations took place in one Canadian community pharmacy. Results A total of 127 patients were observed for study purposes (60 intervention and 67 control). A total of 141 questions were asked by 59 patients; the other 68 patients had no questions when asked. Subjects in the intervention group (one outlier removed) asked an average of 1.1 questions per encounter, while the control group asked 0.9 questions. This difference was not statistically significant. Conclusion The hypothesis of no difference in the rate of patient question-asking between groups was retained. This method of encouraging patients to become more involved in the counselling process proved unsuccessful.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".