Complete dentures and oral health‐related quality of life – do coping styles matter?
Bibliographic record
Abstract
UNLABELLED: Oral health-related quality of life (OHRQOL) in edentulous patients with complete dentures is often impaired. This paper investigates the effect of different coping styles on OHRQOL. PURPOSE: (a) To assess OHRQOL of edentulous patients with conventional complete dentures, and (b) to investigate if individual differences in these patients' styles of coping with stress affect their OHRQOL. MATERIALS AND METHODS: Data were collected from 249 fully edentulous patients with complete dentures (mean age: 66.0 years) who responded to a mailed survey (adjusted response rate: 48.8%). OHRQOL was measured with the 14-item short form of the oral health impact profile (OHIP). Ratings of coping strategies were obtained using the 28-item Brief COPE, an instrument measuring various styles of coping with stress. Linear regression analyses were used to explore the relationships between coping styles, background variables such as age, gender, income, and age of prosthesis, and the patients' OHRQOL. RESULTS: About 35% of the respondents reported impacts from their oral conditions on their overall OHRQOL (OHIP-14 total score) occasionally, fairly often, or often. Physical pain was even more prevalent, with 53.3% of the respondents reporting pain impacts. The linear regression model (P < 0.0001) explained 31.1% of the variation in the OHIP-14 total score. The coping variables instrumental support, behavioral disengagement, substance abuse, denial, and religion were significant negative predictors of OHRQOL. Only emotional support was a significant positive predictor of OHRQOL. CONCLUSION: Wearing conventional complete dentures has a significant impact on OHRQOL. This impact is moderated by the styles a patient uses to cope with stress. Using emotional support has a positive effect on OHRQOL, while other coping styles, namely instrumental support, behavioral disengagement, substance abuse, denial, and religion are significant negative predictors of 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".