Shedding light on pharmacists’ knowledge of kidney stones’ etiology and treatment
Bibliographic record
Abstract
Background: The recurring nature of kidney stones (KS) makes it difficult to control and treat. Patients' education plays a part in reducing disease recurrence. Pharmacists participate in the healthcare services through educating patients with kidney stones about KS preventive measures and medications that greatly reduce the disease frequency and the treatment cost. Insufficient pharmacists' knowledge may affect the services' quality and result in misuse of KS medications. Objectives: To evaluate the pharmacists' level of knowledge to provide adequate information about KS preventive measures, medications, and treatments for patients with kidney stones in Jordan. Methods: An online descriptive survey was distributed to pharmacists to assess their knowledge about KS causes, prevention, and treatment. The results were analyzed using the SPSS software. Results: There were 393 pharmacists participated in this study. Pharmacists demonstrated an overall intermediate level of knowledge about KS. They showed an excellent level of knowledge regarding KS types and etiology, an intermediate level of knowledge about KS preventive measures and treatment, and poor knowledge about home remedies and drugs that promote KS formation. Conclusion: Pharmacists knowledge about KS management through diet and medications need to be improved. This could be through focusing on pharmacists' training for the effective implementation of knowledge in the clinical practice. Adopting guidelines by pharmacists may reduce the risk of KS recurrence and provide pharmacist-led patient education about KS management in hospitals and community pharmacies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".