Diagnosis and prevalence of probable awake and sleep bruxism in adolescents: an exploratory analysis
Bibliographic record
Abstract
The aims of this study were to perform an exploratory analysis of probable awake (AB) and sleep bruxism (SB) prevalence using of different diagnosis criteria based on the International Consensus; evaluate the associations between self-report and clinical signs/symptoms in adolescents. Participated in this cross-sectional study 403 adolescents aged 12- to 19-years-old enrolled in public and private schools from Belo Horizonte, Brazil. Parents/caregivers answered a questionnaire about sociodemographic status and adolescents' health status. Adolescents answered a questionnaire evaluating AB (e.g., grinding and clenching) and SB (e.g., grinding, bracing, and thrusting) activities and frequent headaches. A clinical examination was performed on adolescents to evaluate bruxism clinical signs/symptoms (pain upon palpation on masseter and temporal, linea alba, indentation on the tongue and attrition wear severity). Descriptive statistics and Pearson's Qui-square test were performed (P≤0.05). Adolescents mean age was 14.3±1.5 years, and 58.1% were female. Self-report of SB was identified in 31% of participants and self-report of AB in 51.6%. Almost all adolescents (99%) presented at least one tooth with attrition wear (98.5% on enamel and 0.5% on dentin), with a mean number of 12.4±5.7 teeth. Depending on the diagnosis criteria, the prevalence of probable SB and AB varied from 0- 99% and 0.2- 99%, respectively. A high inconsistency was found for the prevalence of probable AB and SB in adolescents, which were influenced by the different clinical sings/symptoms used as diagnosis criteria. Frequent headaches and pain upon palpation on masseter and temporal muscle were associated to self-report of AB and SB among adolescents.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".