Knowledge and Decision-Making among Israeli Dentists Treating Young Patients with Type 1 Diabetes Mellitus: A Cross-Sectional Survey
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To assess decision making process and knowledge level of dentists treating children with type 1 diabetes. STUDY DESIGN: Cross-sectional survey among dentistry residents and dental specialists working in clinics that provide dental care to children with type 1 diabetes. RESULTS: A total of 166 respondents were included. 42% of respondents perceived that they have sufficient knowledge to treat children with diabetes, in correlation with an average score of 1.9 out of 4 on knowledge questions. Over 80% of dentists decided to treat patients by consulting with the treating physician or by checking HbA1c and glucose blood levels independently. Greater knowledge was associated with a significantly higher tendency of the dentists to determine if the child's diabetes is controlled, and to refer less often to the hospital. Furthermore, greater knowledge was also associated with dentists' greater perception that they have enough knowledge, skills and confidence to treat children with diabetes. CONCLUSIONS: The study revealed significant gaps in the knowledge on diabetes among dentists who provide dental care to children. Dentists, pediatricians, endocrinologists, and other healthcare professionals who provide care for children should be encouraged to collaborate to create a mutual knowledgeable work environment for delivering best care to their patients.
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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 | 0.005 | 0.003 |
| 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 | 0.001 | 0.001 |
| 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 it