Alexithymie bei Multipler Sklerose – eine narrative Übersicht
Bibliographic record
Abstract
Alexithymia is a multidimensional construct of personality implicating difficulties in identifying and describing another's feelings, and externally oriented thinking. It is broadly reported in psychiatric patients but has gained little attention regarding its occurrence and pathophysiology in multiple sclerosis (MS). This narrative review aims to address prevalence, etiology, neurobiological, and clinical findings of alexithymia. The prevalence of alexithymia in MS ranges from 10 to 53%. There seems to be an association with anxiety, depression, fatigue, and some aspects of social cognition, while the relationship with clinical and classical cognitive variables was rarely evaluated. Only a few studies referred to its pathophysiology assuming an aberrant interhemispheric transfer or regional cerebral abnormalities. The prevalence of alexithymia in MS and the potential negative impact on quality of life and interpersonal communication could severely impact clinical MS management and a screnning for these factors should be mandatory. Thus, further evaluation is needed concerning its relationship with clinical, emotional, and cognitive confounders. Large-scale studies employing neuroimaging techniques are needed for a better understanding of the neural underpinnings of this MS feature.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".