Psychological distress in chronic craniomandibular and cervical spinal pain patients
Bibliographic record
Abstract
In chronic craniomandibular disorders, a relationship with psychological distress has often been investigated, with contradictory results. Recent studies on chronic pain patients have shown that the level of psychological distress is related to the number of painful body areas. Therefore, the aim of this study was to analyse differences in psychological distress between craniomandibular pain patients with or without cervical spinal pain, taking the number of painful body areas below the cervical spine also into account. Based on an oral history and, independently performed, dynamic/static tests, the presence or absence of a painful CMD or CSD was recognized. To assess the level of psychological distress, the Dutch version of the Symptom Checklist 90 (SCL‐90) was used. The number of painful body areas was indicated on the body drawing of the McGill Pain Questionnaire (MPQ‐DLV). From the initial 250 participants, 103 persons could unequivocally be classified as having or not having a painful CMD and/or CSD and fully completed both questionnaires. Patients with both craniomandibular and cervical spinal pain showed higher levels of psychological distress than patients with only local craniomandibular pain and persons without pain (ancova and t‐tests, P=0·026–0·000). Further, persons with more painful body areas below the cervical spine showed higher SCL‐90 scores (ancova and t‐tests, P=0·045–0·000). In conclusion, chronic craniomandibular pain patients with a coexistent cervical spinal pain show more psychological distress than patients with only local craniomandibular pain and asymptomatic persons. (Supported by the IOT)
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".