Psychological Stress Reduces the Effectiveness of Periodontal Treatment: A Systematic Review
Bibliographic record
Abstract
Background/Objectives: To systematically evaluate scientific evidence related to the influence of psychological stress on the response to periodontal treatment. Methods: PubMed/NCBI (National Center for Biotechnology Information, US National Library of Medicine), Web of Science (ClarivateTM), EBSCOHost, SCOPUS, and ProQuest databases were searched for published clinical studies in English up to May 2024. The quality of each study was assessed using the Ottawa–Newcastle scale. Results: Of 803 relevant articles identified, 8 were included in the qualitative synthesis qualitative synthesis. These studies involved 445 patients who completed the follow-up period, ranging from 6 weeks to 6 months. Stressed patients were more likely to experience higher levels of PPD and BOP compared to non-stressed patients. In total, 75% of the included studies showed a positive relationship between stress and response to NSPT, 12.5% observed a negative relationship, and the remaining 12.5% found some degree of relationship in the results of clinical periodontal parameters. The level of evidence is categorized according to the quality of the synthesis presented. Conclusions: There is a positive correlation between psychological stress and periodontal treatment response, indicating that stress may negatively influence the clinical outcomes of NSPT. Stress may reduce the inflammatory response, which is crucial for eliminating periodontal micropathogens after periodontal treatment.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".