Mediation analysis of anxiety and depression between alexithymia and frequency of headache attacks and impact on suicidal ideation in primary headache
Bibliographic record
Abstract
OBJECTIVE: Considering the constellation of psychopathological symptoms that characterize primary headaches, the present study aimed to describe the relationship between specific psychopathological symptoms (i.e., anxiety, depression, and suicidal ideation), psychological variables (i.e., alexithymia), and their impact on headache frequency. METHODS: Socio-demographic data (gender, age, occupation, marital status, and educational level) and psychological variables (alexithymia, anxiety, depression, and suicidal ideation) of 70 people with headache (the experimental group was composed of 33 with migraine, 23 with tension-type headache, and 14 with mixed tension migraine) were compared to those of 62 age-matched control subjects. First, participants underwent a neurological examination to make the diagnosis and define the frequency of headache attacks in a month. Consequently, all participants completed the Toronto Alexithymia Scale-20, the Symptom Questionnaire, and the Symptom Checklist 90-Revised. RESULTS: The Headache group reported significantly higher levels of alexithymia, anxiety, depression, and suicidal ideation compared to controls. The mediation analysis, conducted within the patient group alone, proved that anxiety and depression fully mediated the relationship between alexithymia and monthly headache frequency, even controlling for gender and age. Additionally, the frequency of headache attacks predicted suicidal ideation. DISCUSSIONS: Our results highlight the importance of conducting a psychological evaluation in headache patients because some factors can increase the clinical manifestations of the disease.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".