Bibliographic record
Abstract
Objective This aimed to assess the potential role of chronic stress in saliva secretion, xerostomia, and oral health in a population attending a saliva clinic.Materials and methods Data of 114 patients who met the inclusion criteria and completed all questionnaires were analyzed in this study.Participants completed several validated questionnaires, including the Perceived Stress Scale, the Oral Health Impact Profile (OHIP-14), Xerostomia Inventory (XI), and Bother xerostomia Index (BI).Subsequently, the unstimulated, chewingstimulated, and citric acid-stimulated saliva secretion rates were determined gravimetrically.Data were evaluated using Spearman's correlation analysis and the Mann-Whitney U test.Results A significant correlation was observed between perceived stress and XI score (r = 0.312, p = 0.001), as well as between perceived stress and BI score (r = 0.334, p = 0.001).Stress levels also were significantly associated with OHIP-14 scores (r = 0.420, p < 0.001), but an association between experienced stress and salivary flow rate could not be established.Conclusion In this population, perceived chronic stress seems to be related to several aspects of dry mouth, including the perception of dry mouth, suffering from dry mouth, and the impact on quality of life.These effects were independent of the use of psychotropic medication.No actual reduction in salivary flow was found.Further studies to explore the causal linkage of stress with xerostomia seem warranted.Clinical relevance Perceived chronic stress seems to be related with several aspects of dry mouth.This finding might be relevant in future prevention and treatment of xerostomia.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".