Malocclusion Impact Scale for Early Childhood (MIS-EC): development and validation
Bibliographic record
Abstract
This study aimed to develop and validate the Malocclusion Impact Scale for Early Childhood (MIS-EC), a malocclusion-specific measure of oral health-related quality of life (OHRQoL) of children aged 3-5 years and their parents/caregivers. A pool of items was analysed to identify those relevant to the assessment of the impact of malocclusion on OHRQoL. Dental professionals and mothers of children with and without malocclusion rated the importance of these items. The final version of the MIS-EC was evaluated in a cross-sectional study comprising 381 parents of children aged 3-5 years to assess construct validity, internal consistency and test-retest reliability. Twenty-two items were identified from item pooling. After item reduction, eight items were chosen to constitute the MIS-EC, in addition to two general questions. The MIS-EC demonstrated good internal consistency (Cronbach's alpha = 0.79 for the Child Impact section and 0.53 for the Family Impact section), and excellent test-retest reliability (ICC = 0.94), floor effect was 55.7% and ceiling effect 0%. MIS-EC scores indicating worse OHRQoL were significantly associated with the presence of malocclusion (p < 0.05). The MIS-EC is reliable and valid for assessing the impact of malocclusion on the OHRQoL of preschool children and their parents/caregivers.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".