A cross-sectional study of alexithymia in patients with relapse remitting form of multiple sclerosis
Bibliographic record
Abstract
Background: Alexithymia is one's incapacity to identify, comprehend, and describe emotions. There is almost no literature data about the levels of alexithymia among patients with relapse remitting type of multiple sclerosis. Aim: The objective of the present study was to assess the levels of alexithymia in patients with relapse remitting type of multiple sclerosis in relation to their sociodemographic variables and clinical characteristics of the disease. Methods: This cross-sectional study included 106 consecutively assessed patients with relapse remitting type of multiple sclerosis. In addition to the data regarding disease duration, number of demyelinating relapses, and degree of neurological disability, assessed by the expanded disability scale score (EDSS), we used Toronto alexithymia scale (TAS), fatigue severity scale (FSS) and, Hamilton scale for the assessment of anxiety and depression and sociodemographic questionnaire. Results: Study included 74 female and 32 male patients, with a median age of 44 years, median disease duration 90 months, and median EDSS 4. About 29.55% of patients had alexithymia and borderline alexithymia was observed in 31.15% patients. Alexithymia correlated with anxiety and depression (P < 0.01) on all TAS subscales. Higher levels of neurological disability based on EDSS, severe fatigue based on FSS scores, and severe relapse remitting type of multiple sclerosis with more relapses and longer disease duration correlated with alexithymia (P < 0.01), depression (P < 0.01), and anxiety (P < 0.01). Higher rates of alexithymia were noticed in older, unemployed, single patients, and those having fewer children. Conclusions: Alexithymia was found in a relatively high percentage in patients with relapse remitting type of multiple sclerosis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".