Alexithymia and Coping With Stress in Patients With Multiple Sclerosis: A Comparative Study
Bibliographic record
Abstract
ABSTRACT: BACKGROUND: Multiple sclerosis (MS), which is frequently seen in young adults, affects mental health because of disease symptoms and cognitive disorders. This study was conducted to evaluate the presence of alexithymia and problem- or emotion-focused coping strategies with stress in MS patients, determine the relationship between these variables, and compare the results of MS patients with those of healthy individuals. METHODS: This descriptive, cross-sectional, and comparative study was carried out with the participation of 120 MS patients presenting to a neurology clinic and outpatient clinic of a university hospital and 120 healthy individuals. Data were collected using a personal information form, the Toronto Alexithymia Scale, and the Ways of Coping Scale. RESULTS: The 40.8% rate of alexithymia in the MS patients was higher than that in the healthy individuals (21.7%). Compared with healthy individuals, MS patients use emotion-focused coping methods, such as a lack of self-confidence approach and a submissive approach, more frequently ( P < .05). A significant negative correlation was found between the alexithymia and problem-focused coping strategies of MS patients ( P < .01). CONCLUSION: Alexithymia is more common in MS patients than in healthy individuals. Alexithymia negatively affects the methods patients use to cope with stress. In the treatment and care of MS patients, nurses should plan interventions for the ability of these patients to recognize and express their emotions and develop positive coping methods.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".