Dental Students in Egypt: To What Extent Do They Perceive and Comply with Infection Control Measures?
Bibliographic record
Abstract
This study was carried out in the dental school of Ahram Canadian University in Egypt to investigate the knowledge and compliance of senior students and interns toward infection control practices. A self‑administered questionnaire was employed with questions pertinent to the participants’ knowledge of risks in the dental settings, the practice of hand hygiene, the use of protective equipment, and the management of sharp injuries, among others. Although the knowledge and practice of the 240 surveyed participants were good; they were not up to the coveted standards. Despite being an integral part of their curriculum, an alarming percentage (19.6%) of the participants denied receiving knowledge about infection control instructions. Meanwhile, only 72.5% were aware of being at risk in the dental settings, and 78.3% confirmed their practice of hand hygiene. On the other hand, 84.6% of the surveyed participants confirmed the availability of protective equipment and 94.2% of them expressed their willingness to apply infection control measures in the future. The defects in the knowledge and practice mandate corrective actions to promote and upgrade the students’ compliance. Meanwhile, other gaps can be rectified via developing state-of-the-art communicative strategies. Efforts are warranted to enhance the attitude and motivate the students to conform to the protective safety measures. With all the infection control procedures already established in dental schools, the challenge lies in improving the students’ compliance with these recommendations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".