Oral behaviors mediate the relationship between anxiety and painful temporomandibular disorders
Bibliographic record
Abstract
OBJECTIVES: Anxiety is strongly associated with chronic musculoskeletal pain, including painful temporomandibular disorders (p-TMD). Non-functional oral behaviors-such as wake-time tooth clenching or keeping the lower jaw in a tense position-are prevalent stress-related behaviors among individuals with elevated anxiety. These behaviors are thought to act as maladaptive coping strategies increasing strain on the masticatory muscles and the temporomandibular joint, thereby enhancing peripheral nociceptive input and contributing to the onset or persistence of p-TMD in individuals with high anxiety. While this behavioral pathway is theoretically supported, it has yet to be empirically verified. This study investigated whether non-functional oral behaviors mediate the relationship between anxiety and p-TMD. DESIGN: We recruited 299 adults with p-TMD (myofascial pain and/or arthralgia) and 374 pain-free controls. Anxiety levels and the frequency of non-functional oral behaviors were assessed using the Generalized Anxiety Disorder scale and the Oral Behavior Checklist, respectively. Mediation analysis was conducted to examine both the direct (anxiety → p-TMD) and indirect (anxiety → oral behaviors → p-TMD) pathways. RESULTS: Mediation analysis revealed that non-functional oral behaviors fully mediate the relationship between anxiety and p-TMD. CONCLUSION: Non-functional oral behaviors are a key behavioral mechanism linking anxiety to p-TMD. These findings highlight the importance of targeting oral behaviors in interventions for TMD pain, particularly among individuals with high anxiety, and provide a foundation for future research into behavioral and neural mechanisms underlying TMD.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".