Danish dentists’ knowledge, attitudes and management of procedural dental pain in children: association with demographic characteristics, structural factors, perceived stress during the administration of local analgesia and their tolerance towards pain
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to describe Danish dentists' knowledge of, attitudes towards and management of procedural pain during paediatric dental care, and to assess the importance of demographic characteristics, structural factors, perceived stress during administration of local analgesia and the dentists' own tolerance towards procedural dental pain. DESIGN: A cross-sectional questionnaire study was conducted in Denmark in May 2001. SUBJECTS AND METHODS: The subjects were a random sample of 30% of Danish dentists treating children. Usable information was obtained from 327 (80.3%) of the dentists in the sample. RESULTS: One-quarter of the respondents answered that a 3-5-year-old child could report pain only with uncertainty. More than 80% of the dentists stated that they never compromised on painlessness. Very few agreed to the statement that children forget pain faster than adults. One-third agreed to, or were neutral to, the statement that all restorative care in primary teeth could be performed painlessly using N2O-O2 sedation alone. The majority of the respondents reported using three or more methods to assess the effect of their pain control methods. Almost 90% reported using local analgesia for restorative work 'always' or 'often'. A similar proportion reported using topical analgesia before injection 'always' or 'often'. Administering a mandibular block to preschool children was the procedure perceived as the most stressful (33.6%) pain control method. Demographic factors (gender), structural factors (always working alone and treating 3-5-year-old children daily), perceived stress during the administration of a mandibular block in preschool children and the dentists' own willingness to accept potentially painful dental treatment without local analgesia were associated with knowledge of, attitudes towards and management of procedural dental pain in children. CONCLUSIONS: Danish dentists treating children demonstrate concern about procedural dental pain in children. Factors amenable to change via training and reorganization into larger clinical units seem to determine their knowledge of, attitudes towards and management of procedural dental pain in children.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".