The association between patients’ personality traits and pain perception during orthodontic treatment: a systematic review
Bibliographic record
Abstract
Background: Orthodontic treatment is frequently correlated with different levels of discomfort and pain, caused by the application of forces to move the teeth. The mechanism of orthodontic pain is based on the initially activation of sensory receptors in periodontal tissues which results in a cascade of nociceptive pain processing and transduction in both the central and peripheral nervous systems that is finally experienced by patients. The perception of pain is subjective and varies among people, as it is influenced by both general and individual elements. This systematic review aims to synthesize existing knowledge on the association between patients' personality traits and pain perception during orthodontic treatment, and its influence on the success of orthodontic therapy. Methods: The search strategy included the databases PubMed, Scopus, Embase, and Web of Science. The inclusion criteria were studies examining the correlation between personality traits and pain perception in patients undergoing orthodontic treatment. The quality of the studies was assessed using the Newcastle-Ottawa Scale (NOS). Results: The search strategy yielded 301 potential articles, with 10 papers meeting the inclusion criteria. Five studies were judged at a low risk of bias and another five studies were assessed as having a moderate risk of bias. Most of the studies reported relationship between personality traits and pain perception during orthodontic treatment, as well as treatment attitudes, and post-treatment satisfaction. Conclusion: Patients' psychological characteristics seems to affect pain perception and other factors associated with orthodontic treatment. Given that several studies were judged to have a moderate risk of bias, as well as high heterogeneity among studies, further research is needed. Systematic review registration: The systematic review was registered in PROSPERO database (CRD42024537185).
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".