Dental anxiety and empathy among undergraduate oral health students in Norway, South Africa and Namibia
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: Dental anxiety is a common type of fear that can complicate dental treatment. The dental practitioner is crucial in both treating dental fear and anxiety as well as prevent it from arising. The ability to feel empathy is important in that matter. The dental practitioner's own level of dental anxiety can possibly affect his or her ability to treat patients in an empathetic manner. The aim of this study was to assess and examine the relationship between level of empathy and dental anxiety in undergraduate oral healthcare students from Namibia, South Africa and Norway. MATERIAL AND METHODS: A cross-sectional study was performed. Questionnaires were distributed, and responses were analyzed anonymously. Dental anxiety was assessed using Modified Dental Anxiety Scale (MDAS), and empathy level was assessed using Toronto Empathy Questionnaire (TEQ). Data were presented as means or medians and analyzed using a linear regression model in STATA with a 5% level of significance. RESULTS: The response rate was 16.0%, and 298 completed questionnaires were received. MDAS was low in all groups (medians 7-10), however, significantly lower in Norway compared to Namibia and South Africa. The mean TEQ score was 46.8 in Namibia, 47.5 in South Africa and 50.4 in Norway, all above average empathy levels but significantly higher in Norway than in Namibia and South Africa. CONCLUSIONS: Oral healthcare students in Africa and Norway showed high empathy and low dental anxiety, which is reassuring for future oral health care professionals.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".