Denture Hygiene Awareness, Practices and Instructional Guidance among Patients in Punjab, Pakistan: a Cross-Sectional Survey
Bibliographic record
Abstract
<p><strong>Background and Objective:</strong> Dentures require regular cleaning and without proper guidance on how to clean and care for their dentures, patients may experience discomfort, bad breath, and an increased risk of oral diseases. This study explored the level of awareness, hygiene practices, and the guidance received regarding denture care among individuals wearing dentures in Punjab.<br /><strong>Methods: </strong>This survey was conducted with the agreement of the IRB, using systematic sampling, from November 2021 to August 2022 using a questionnaire developed by the authors, validated through expert review, and administered through interviews. The questions were asked in English language and in Urdu with those who did not understand English language. The survey instrument had 18 items targeting demographics, denture hygiene awareness and practices amongst private and public dental hospital patients.&nbsp;<br /><strong>Results: </strong>There was a statistically significant difference between private and public dental hospitals regarding instructions given for denture hygiene awareness. Most respondents received instructions verbally (83.3%), followed by practical demonstration (20%) and written instructions (9.3%). The majority agreed that unclean dentures have an association with oral (56%) and systemic (70.7%) health and may act as a source of infection (57.3%). A total of 56% of the respondents cleaned their dentures once daily while 16.7% reported halitosis. A significant proportion of the patients had the habit of wearing dentures overnight.&nbsp;<br /><strong>Conclusion: </strong>Approximately half of the patients were aware of the optimal denture hygiene and the implications of wearing unclean dentures. The majority received instructions from dentists verbally and were wearing dentures overnight.</p>
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".