Depression, Automatic Thoughts, Alexithymia, and Assertiveness in Patients With Tension‐type Headache
Bibliographic record
Abstract
OBJECTIVE: The role of psychological factors related to headache has long been a focus of investigation. The aim of this study was to evaluate depression, automatic thoughts, alexithymia, and assertiveness in persons with tension-type headache and to compare the results with those from healthy controls. METHODS: One hundred five subjects with tension-type headache (according to the criteria of the International Headache Society classification) and 70 controls were studied. The Beck Depression Inventory, Automatic Thoughts Scale, Toronto Alexithymia Scale, and Rathus Assertiveness Schedule were administered to both groups. Sociodemographic variables and headache features were evaluated via a semistructured scale. RESULTS: Compared with healthy controls, the subjects with headache had significantly higher scores on measures of depression, automatic thoughts, and alexithymia and lower scores on assertiveness. Subjects with chronic tension-type headache had higher depression and automatic thoughts scores than those with episodic tension-type headache. CONCLUSIONS: These findings suggested that persons with tension-type headache have high depression scores and also may have difficulty with expression of their emotions. Headache frequency appears to influence the likelihood of coexisting depression.
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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".