Knowledge and practice of health workers to tooth avulsion in a teaching hospital in Lagos, Nigeria
Bibliographic record
Abstract
Objective: The health care workers (HCW) may be the first contact of a tooth avulsion case. This study aimed to assess their knowledge and practice of emergency management of tooth avulsion. Methods: The cross-sectional study was carried out among health care workers in a teaching hospital, using a self-administered questionnaires containing closed and open-ended questions, on their knowledge and practice of management of tooth avulsion. Data collected was analyzed using EPI info version 7 statistical software. Results: A total of 362 questionnaires were administered with a response rate of 90.4%. The health care workers were 331 between the ages of 18 years to 64years. There were 200 (60.4%) females and 131(39.6%) males (ratio 3:2). Less than half (41.7%) of the respondents rated their knowledge on avulsion as fair. About half of the respondents 156 (47.1%) reported that primary tooth should be replaced into the socket. The knowledge of how to hold avulsed tooth among 217 (65.6%) of the respondents was incorrect. More than half 185 (55.9%) answered that avulsed teeth, will be stored in a dry medium. Less than half, 146 (44.1%) knew the appropriate storage media to be used. Only a third 122 (36.9%) were confident in their knowledge to replant an avulsed tooth. About a third 114 (34.4%) of HCW had encountered an avulsion case, most were dentists and nurses. More than a quarter 92 (27.7%) referred the avulsion while (16.1%) did nothing to the avulsed tooth. Conclusion: There is a need to increase the knowledge and practice of HCW, so that immediate replantation can be practiced thereby improving the prognosis for replanted teeth.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".