Normative and self-perceived orthodontic treatment need of a Peruvian university population
Bibliographic record
Abstract
BACKGROUND: Previous studies on orthodontic treatment need in young adults have shown that up to 50% had malocclusions that needed orthodontic treatment. The aims of this study were to assess the normative and self-perceived need for orthodontic treatment using the Index of Orthodontic Treatment Need (IOTN) and to determine if the treatment need levels were influenced by sex, age and socio-economic status (SES) in a sample of Peruvian young adults. METHODS: 281 first-year students (157 male and 124 female students) with a mean age of 18.1 +/- 1.6 years were randomly selected and evaluated through the Dental Health Component (DHC) and Aesthetic Component (AC) of the IOTN. Structured interview and clinical examination were used to assess the students. Descriptive statistics and Chi-square tests were used for data analysis with statistical significance set at P < 0.05. RESULTS: An intra-examiner reliability of 0.89 was obtained (weighted Kappa). The percentage of students according to SES was 51.2%, 40.6% and 8.2% corresponding to low, medium and high SES respectively. The percentage of students with DHC grades 4-5 was 29.9% whereas the percentage of students with AC grades 8-10 was 1.8%. There were no significant differences in the distribution of normative and self-perceived orthodontic treatment need based on sex, age and SES comparisons. CONCLUSION: Normative orthodontic treatment need was not matched by a similar level of self-perceived treatment need in these young adults. Sex, age and SES were non-significant factors associated with levels of treatment need.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".