Chronic orofacial pain and psychological distress: findings from a multidisciplinary university clinic
Bibliographic record
Abstract
Background: Chronic orofacial pain (COFP) is a complex condition that requires multidisciplinary management grounded in the biopsychosocial model. This study examined the associations between temporomandibular disorders (TMD) and headache symptoms and psychological factors within a university-based multidisciplinary care setting, providing insight into the integration of mental health in COFP management. Methods: A retrospective review of 162 patient records from the University of Alberta Multidisciplinary Orofacial Pain Clinic (2020–2023) was conducted. Psychological assessments included the Adverse Childhood Experiences (ACE) scale, Pain Catastrophizing Scale (PCS) and Injustice Experience Questionnaire (IEQ). Logistic regression was used to evaluate associations between psychological factors and pain severity. Results: The cohort (aged 13–93) was predominantly female (84.0%). Fifteen percent declined psychological measures. Significant associations were observed between PCS (p = 0.036) and IEQ (p = 0.005) scores and reported pain severity. Moderate-to-high PCS scores were associated with a 3.67-fold increase in the odds of moderate to severe TMD symptoms (Odds Ratio (OR): 3.67, 95% Confidence Interval (CI): 1.09–12.35), while high PCS scores predicted severe headaches (OR: 3.91, 95% CI: 1.50–10.17, p = 0.005). Elevated IEQ scores were similarly associated with increased odds of severe headaches (OR: 2.76, 95% CI: 1.08–7.05, p = 0.034). Conclusions: Psychological factors such as pain catastrophizing and perceived injustice are strongly associated with symptom severity of TMD and headache symptoms in COFP. These findings underscore the importance of integrating targeted psychological assessments into multidisciplinary care. Further research should explore barriers to implementation and advance biopsychosocial approaches to improve outcomes for patients with COFP.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".