Peculiarities of psychological support of patients with muscular-joint dysfunction of the temporomandibular joint
Bibliographic record
Abstract
Annotation. The pathology of the temporomandibular joint (TMJ) is one of the most difficult in the practice of the dentist, so patients go to different doctors. Often, the disease is psychosomatic, so patients have a history of stress, sleep disorders, headaches, chronic fatigue. The aim of the study is to study and comparatively analyze the nature and extent of psychological manifestations in patients with dysfunction of the temporomandibular joint according to the degree of clinical manifestations of the pathology irritability. In total, we examined 834 people with CNS dysfunction who had different etiologic causes, different complaints, and different clinical manifestations. To assess the psychological status of patients used: Gissen somatic complaints questionnaire, Toronto alexithymic scale, the method of studying the type of attitude to the disease Tobol, projective methodology “I am healthy and I am sick”, modified 10-point FPS-R (Bayers-based) subjective pain analysis scale. It was found that in the group of patients with pathology of the TMJ, the main complaint was pain (77.1%), the type of attitude to the disease is mainly alarming (59.5%), and the level of alexithymia is high (78%). Based on the received data on the general condition of the patient, they form a plan of providing comprehensive medical and psychological care, in which during the basic treatment psycho-corrective measures are combined with psychoprophylaxis of secondary disorders of the psychological health of patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".