Association between sleep bruxism and stress symptoms in adults: A systematic review and meta‐analysis
Bibliographic record
Abstract
To synthesise and critically review the association between sleep bruxism (SB) and stress symptoms in adults. A systematic review was performed. The search was completed using seven primary electronic databases in addition to a grey literature search. Two reviewers blindly selected studies based on pre-defined eligibility criteria. Risk of bias of the included articles was performed using the Joanna Briggs Institute Critical Appraisal Checklist for Analytical Cross-Sectional Studies. RevMan 5.4 was used to perform the meta-analysis. The quality of evidence was evaluated according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE). Ten studies were included for qualitative analysis, of which three were included for quantitative analysis. Three studies were evaluated to have low risk of bias, and seven were assessed with moderate risk of bias. Quality of evidence was classified as very low for all outcomes. Individuals with SB were found to have higher levels of some self-reported stress symptoms as assessed through questionnaires with a mean difference of 4.59 (95% CI 0.26-8.92). Biomarkers like epinephrine, norepinephrine, cortisol, adrenaline, dopamine, noradrenaline and prolidase enzyme levels also showed a positive association with SB. Although some associations were identified between probable SB and self-reported stress symptoms and biomarkers of stress in adults, given that the quality of evidence was found to be very low, caution should be exercised in interpreting these results. These findings suggest that additional and better designed studies are warranted in order to clarify the link between SB and stress.
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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 | 0.026 | 0.077 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.022 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".