Magnification of anxiety sensitivity, alexithymia, anger and bodily sensations in patients with migraine headache
Bibliographic record
Abstract
Purpose: In this study, alexithymia, anxiety sensitivity, exaggerated physical sensations and anger expression in patients with migraine headache were compared with a healthy control group. Material and Methods: A total of 88 migraine headache patients and 91 healthy volunteers who applied to the Neurology Clinic and met the inclusion criteria were included in the study. Sociodemographic Data Form, Anxiety Sensitivity Index (ASI), Physical Sensation Exaggeration Scale (BIDS), Toronto Alexithymia Scale (TAS) and Spielberger Trait Anger Expression Scale (LASP) were administered to all subjects included in the study. Results: In our study, 59 (67%) of the patients with migraine were female and 29 (33%) were male, while 59 (64.8%) of the control group were female and 32 (35.2%) were male. The mean age of the patient group was 39.07 ± 7.5 (25-55) years, while the mean age of the control group was 37.30 ± 8.2 (25-55) years. When compared according to the mean scores of ASI, BIDS and TAS, it was determined that the scores of the patient group were significantly higher than those of the control group. Anger expression style was higher in the patient group compared to the control group. There was a significant difference between the two groups in terms of anger expression and anger control. A significant relationship was found between TAS and trait anger, anger-in and anger-out scores. Conclusion: In this study, many patients with migraine headache were associated with a psychiatric symptom. These psychiatric symptoms, which affect the current treatment of patients and the course of the disease, are often overlooked or misdiagnosed by clinicians. Our study demonstrates the need for inter-clinical consultation and liaison.
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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 | 0.001 |
| 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".