Alexithymia In Multiple Sclerosis: Relationship With Depression
Bibliographic record
Abstract
Introduction Alexithymia, the lack of words to express emotions, is a common problem in multiple sclerosis (MS) patients. Objectives To investigate the prevalence of alexithymia in patients with MS and to evaluate the factors related to it, including depression. Methods We conducted a cross-sectional, descriptive and analytical study, which took place in the neurology department in Sfax (Tunisia). It involved MS outpatients in remission phase. Data collection was done using a form exploring sociodemographic, clinical and radiological characteristics. We used the Expanded Disability Status Scale (EDSS) to evaluate neurological impairments, the Toronto Alexithymia Scale (TAS-20) to assess alexithymia, and the Hospital Anxiety and Depression Scale (HADS) to assess depressive symptoms. Results Our study included 93 patients. They were married in 57% of cases. The total number of relapses ranged from 1 to 30, with a median of 5. The EDSS score ranged from 0 to 8. A temporal lesion on brain imaging was found in 29% of cases. MS patients had alexithymia in 58.1% of cases and depression in 26.9% of cases. Alexithymia was more frequent in unmarried patients (p = 0.028). Among clinical and radiological factors, the number of relapses was higher (p = 0.035), and temporal lesion was more frequent in alexithymic patients (p = 0.045). In this study, alexithymic patients were more depressed (p < 10 -3 ). Conclusions According to our results, depression and alexithymia were found to be significantly inter-related in MS. Future longitudinal studies might better clarify the nature of this relationship in MS patients. Disclosure No significant relationships.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".