Orthodontists' views on indications for and timing of orthodontic treatment in Finnish public oral health care
Bibliographic record
Abstract
The aim of this study was to analyse the variation in the views of Finnish orthodontists on the indications for orthodontic treatment, timing of orthodontic assessment, and treatment methods used. The views were elicited by a questionnaire that was sent to all 146 specialist orthodontists under 65 years of age living in Finland in 2001. The response rate was 57 per cent. The association between an orthodontist's experience and timing of treatment was tested by Fisher's exact test. Stepwise logistic regression analysis was used to estimate the association between the demographic characteristics of orthodontists and the tendency to start Class II division I treatment early. Most orthodontists recommended that the first assessment of occlusion should be carried out before 7 years of age. A crossbite was mentioned as the most frequent indication for treatment in the primary and early mixed dentition, and a severe Class II division I malocclusion with an increased overjet as the most frequent indication in the late mixed dentition. Most respondents preferred early treatment, but there was a wide variation in the choice of appliances and in the timing of treatment of malocclusions other than crossbite and Class II malocclusions. A quadhelix, headgear, and the eruption guidance appliance were the most frequently used appliances in early treatment, with fixed appliances being most frequently used during the late mixed and permanent dentition phase. Orthodontists working full time in municipal health centres tended to prefer early treatment more often than those working part-time or outside health centres. There was no statistically significant association between an orthodontist's experience and timing of Class II division I and Class III treatment (P = 0.142 and P = 0.296, respectively). The preference for an early start in Class II division I treatment might be related to differing professional decisions, but no explaining factors could be found in the regression analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".