Understanding the psychology of trust between patients and their community pharmacists
Bibliographic record
Abstract
Background: Pharmacists need patients to trust them in order to support best possible health outcomes. There has been little empirical work to test the widely stated claim that pharmacists are the “most trusted” health care professional. This study was undertaken to characterize the factors that shape public trust of individual pharmacists and the profession as a whole. Methods: An exploratory qualitative study was undertaken. Semistructured interviews with 13 patients from 5 different community pharmacies were completed. Interview data were transcribed, coded and categorized to identify trust-enhancing and trust-diminishing factors influencing patients’ perceptions of pharmacists. Results: Four trust-diminishing factors were identified, including the business context within which community pharmacy is practised, lack of transparency regarding pharmacists’ remuneration, lack of awareness of how pharmacists qualify and are regulated and inconsistent previous experiences with pharmacists. Four trust-enhancing factors were identified, including accessibility, affability, acknowledgement and respect. Discussion: This study illustrates that trust-diminishing factors appear to be somewhat outside the day-to-day control of individual community pharmacists, while trust-enhancing factors are elements that pharmacists may have greater personal control over. Further research is required to better understand these factors and to develop a more generalizable understanding of how patients develop trust in their pharmacists. Can Pharm J (Ott) 2021;154:xx-xx.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".