The Relationship Between Adverse Childhood Experiences (ACEs) and Malocclusion
Bibliographic record
Abstract
Introduction: Adverse Childhood Experiences (ACEs) are stressful events such as abuse or neglect that may occur before age 18. The prevalence of ACEs amongst orthodontic patients and its correlation with malocclusion severity is yet to be explored. Objective: To examine the prevalence of ACEs in an orthodontic population and its link to orthodontic treatment need. Methods: A validated ACE survey was adapted for use in an orthodontic clinic. Orthodontic treatment need was assessed via pre-treatment records and the Index of Orthodontic Treatment Need (IOTN). Results: Of 334 participants, 68.0% (n=227) reported one or more ACEs and 29.4% (n=98) reported four or more ACEs. Ordinal regression revealed ACE score and IOTN grade are correlated (p=0.0488). Each 1-point increase in ACE score raised the odds of having a higher IOTN grade by 8.2% (OR=1.082, 95% CI [1.001, 1.172]). Conclusions: Most orthodontic patients (68%) in this sample have experienced one or more ACEs, highlighting the relevance of trauma-informed care in a Canadian orthodontic clinic setting. ACEs are associated with increased odds of orthodontic treatment need, helping to identify potential at-risk communities for intervention.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".