A cross-sectional survey to determine Turkish dental patients’ probiotic knowledge, attitude, and consumption status
Bibliographic record
Abstract
Introduction: Probiotics play a significant role in improving oral and dental health.Objectives: This study aimed to determine the probiotic knowledge, attitude, and consumption status of Turkish adult patients, who underwent dental treatment at a dentistry faculty.Material and methods: This cross-sectional study included 509 participants, 281 females, and 228 males, who were 18 years of age or older.A printed face-to-face survey consisting of 18 questions was administered to patients.For statistical analyses, Kolmogorov-Smirnov, Shapiro-Wilk, Mann-Whitney U, and Kruskal-Wallis tests were used.P-values < 0.05 were considered statistically significant at a 95% confidence interval.Results: 78.4% of the participants were familiar with probiotics, but only 45.6% of them correctly knew its definition.Females had more probiotic awareness than males.The most common source of information about probiotics was the Internet.23.8% of all participants were probiotic consumers, and 47.1% of participants who consumed probiotics were university graduates.43.8% of female participants and 29.8% of males stated to use probiotics for gastrointestinal diseases, but only 11.4% of females and 8.3% of males claimed to use probiotics to support oral flora.Most of the participants consumed homemade yogurt/ ayran as a naturally fermented food.According to the participants, the most beneficial form of probiotics for oral and dental health was using it in the form of sachets or drops and natural foods, such as yogurt.Conclusions: More public education is required concerning the awareness and benefits for oral and dental health as well as consumption of probiotics to improve the general health of individuals, especially oral and dental health.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".