Meta-analysis with systematic review to synthesize associations between oral health related quality of life and anxiety and depression
Bibliographic record
Abstract
Abstract Objectives The present systematic review aimed to investigate how oral health related quality of life (OHQOL) associates with anxiety and depression. The study protocol was registered prospectively in the PROSPERO database (CRD42023389372). Materials and methods Studies investigating associations between OHQOL and depression and/or anxiety were included. Fisher’s Z scores were used to summarize associations between OHQOL and depression/anxiety. Funnel plots and Begg’s Tests were used to assess publication bias. Meta-regression was conducted to examine potential moderator effects in the associations. Academic databases including the ISI Web of Knowledge, Scopus, ProQuest and PubMed were systematically searched. The quality of included studies was checked with the Newcastle Ottawa Scale (NOS). Results All 15 included studies were cross-sectional (14,419 participants from nine countries; mean age=43.74 years). The pooled estimates showed weak associations between OHQOL and depression (Fisher’s z-score of 0.26 [95% CI = 0.17, 0.35; I 2 = 96.2%; τ 2 = 0.03]) and anxiety (Fisher’s z-score of 0.22 [95% CI = 0.001, 0.43; I 2 = 97.9%; τ 2 = 0.06]). No severe problems in methodology quality, publication biases, or moderator effects were observed. Conclusion Both depression and anxiety were weakly associated with individuals’ OHQOL. Although the synthesized associations were not strong, they were significant, indicating that depression and anxiety are potential factors influencing individuals’ OHQOL.
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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 | 0.048 | 0.149 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.035 | 0.048 |
| Bibliometrics | 0.027 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".