Knowledge, attitudes, and practice patterns among healthcare providers in the prevention of recurrent kidney stones in Northern Ontario
Bibliographic record
Abstract
INTRODUCTON: Kidney stone recurrence is common. Preventive measures can lead to improved quality of life and costs savings to the individual and healthcare system. Guidelines to prevent recurrent kidney stones are published by various urological societies. Adherence to guidelines amongst healthcare professionals in general is poor, while adherence to preventive management guidelines regarding stone disease is unknown. To understand this issue, we conducted an online study to assess the knowledge, attitudes, and practice patterns of healthcare practitioners in Northern Ontario. METHODS: We used the database of healthcare providers affiliated with the Northern Ontario School of Medicine, in Sudbury (East Campus) and Thunder Bay (West Campus), Ontario. We designed the survey based on current best practice guidelines for the management of recurrent kidney stones. Questions covered 3 domains: knowledge, attitudes, and practice patterns. Demographic data were also collected. The survey was distributed electronically to all participants. RESULTS: A total of 68 healthcare providers completed the survey. Of these, most were primary care physicians (72%). To keep uniformity, we analyzed the data of this homogenous group. A total of 70% of the respondents were aware of the current guidelines; however, only 43% applied their knowledge in clinical practice. Most participants lacked confidence while answering most items in the attitude domain. CONCLUSIONS: Most primary care physician respondents were aware of the appropriate preventive measures for recurrent kidney stones; however, they do not appear to apply this knowledge effectively in clinical practice. A low response rate is a limitation of our study. Further studies involving a larger sample size may lead to information sharing and collaborative care among healthcare providers.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".