Oral health related quality of life and its association with sociodemographic and clinical findings in 3 northern outreach clinics.
Bibliographic record
Abstract
OBJECTIVE: Aspects of oral health related quality of life (OHQOL) are attracting increased attention in dentistry. Knowledge in this field is limited, especially in terms of significant indicators and predictors of impaired OHQOL. The aim of this cross-sectional study was to examine the influence of various sociodemographic and clinical variables on OHQOL in the setting of outreach clinics in northern Alberta, Canada. METHODS: OHQOL was measured with the 49-item Oral Health Impact Profile questionnaire (OHIP-49), administered to adult patients attending 3 dental outreach clinics managed by the University of Alberta. Sociodemographic and clinical data were also collected. Data were analyzed using descriptive and multivariable methods. RESULTS: The OHIP-49 scores were comparatively low for a patient sample. After multivariable stepwise logistic regression analysis, only gender, missing anterior teeth and need for endodontic treatment remained as significant variables in the final model for impaired OHQOL. Missing anterior teeth (regardless of replacement) had the strongest effect. Subjects with this feature had an approximately 21-fold greater risk of impaired OHQOL relative to those who retained all of their anterior teeth. CONCLUSIONS: The clientele of these outreach clinics was generally young but had high treatment needs. OHQOL results can be useful in considering treatment strategies in similar rural environments, but the complexity of this indicator necessitates an individual patient-centred approach in clinical decision-making.
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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 | 0.008 | 0.001 |
| 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".