Temporomandibular Disorder and Oral Health-Related Quality of Life in Brazilian Adults: A Population-Based Survey
Bibliographic record
Abstract
OBJECTIVE: Evaluate the association between TMD symptoms and physical and psychosocial oral health impact among adults of a small Brazilian municipality. METHODS: A population-based epidemiological study with a probabilistic sample of adults (30-49 years) was carried out. Data was collected in the participant’s residence using a structured questionnaire, and a clinical examination was conducted by calibrated examiners (Kappa >0.7). The presence of TMD symptoms was evaluated using the Fonseca’s Anamnesis Questionnaire (1994). Physical and psychosocial impact was considered if at least one oral functions item was reported as being experienced fairly often or very often, assessed by the Oral Health Impact Profile (OHIP-14), an instrument of Oral Health Related Quality of Life (OHRQoL). The association between TMD symptoms and presence of impact was adjusted for oral health condition, sociodemographic and socioeconomic profiles, and health behaviors. Associations were investigated using the crude and multivariate Poisson regression. RESULTS: Of the 197 participants, 114 (59.30%) had physical and psychosocial impact of oral health and 135 (68.19%) had at least one TMD symptom. After adjusting for covariates, individuals who reported TMD symptoms had a 1.75 times higher prevalence of impact (95%CI 1.18 - 2.57) than those who did not report symptoms, with psychological discomfort (60.46%), physical pain (40.19%), and psychological disability (35.71%) being the most affected dimensions (p <0.01). CONCLUSION: TMD is a common condition and the presence of symptoms is associated with impact in different dimensions of OHRQoL. These results demonstrate the importance of early identification of TMD symptoms to reduce the impact on OHRQoL.
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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 | 0.001 | 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) | 0.001 | 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".