Patient satisfaction with pharmaceutical care delivery in community pharmacies
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to validate previously published satisfaction scales in larger and more diversified patient populations; to expand the number of community pharmacies represented; to test the robustness of satisfaction measures across a broader demographic spectrum and a variety of health conditions; to confirm the three-factor scale structure; to test the relationships between satisfaction and consultation practices involving pharmacists and pharmacy students; and to examine service gaps and establish plausible norms. METHODS: Patients completed a 15-question survey about their expectations regarding pharmaceutical care-related activities while shopping in any pharmacy and a parallel 15 questions about their experiences while shopping in this particular pharmacy. The survey also collected information regarding pharmaceutical care consultation received by the patients and brief demographic data. RESULTS: A total of 628 patients from 55 pharmacies completed the survey. The pilot study's three-factor satisfaction structure was confirmed. Overall, satisfaction measures did not differ by demographics or medical condition, but there were strong and significant store-to-store differences and consultation practice advantages when pharmacists or pharmacists-plus-students participated, but not for consultations with students alone. CONCLUSION: Patient satisfaction can be reliably measured by surveys structured around pharmaceutical care activities. The introduction of pharmaceutical care in pharmacies improves patient satisfaction. Service gap details indicated that pharmacy managers need to pay closer attention to various consultative activities involving patients and doctors.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".