The quality of life in patients with multiple sclerosis – Association with depressive symptoms and physical disability: A prospective and observational study
Bibliographic record
Abstract
Background Patients with multiple sclerosis (MS) experience disabilities which significantly affect their quality of life (QOL) and mental health. Mood disorders and depressive symptoms are one of the most common psychiatric conditions in MS patients. This study aimed to evaluate the level of QOL in MS patients and to assess the influence of depressive symptoms and physical disability on QOL. Methods This prospective and observational study was conducted among 100 MS patients (mean age of 36.23 ± 11.77) recruited from the Lower Silesian Unit of the Polish Association for Multiple Sclerosis. This study used a questionnaire designed by the authors, which contained questions about sociodemographic and clinical data, as well as the following standardized questionnaires: the Activities of Daily Living questionnaire (ADL), the Instrumental Activities of Daily Living questionnaire (IADL), the Expanded Disability Status Scale (EDSS), the Beck Depression Inventory (BDI) and Multiple Sclerosis International Quality of Life Questionnaire (MusiQOL). Results The average EDSS score among patients was 3.13 ± 2.38 points. More than half of the respondents (68%) suffered from depression of varying severity. The univariate linear regression models showed that the independent ( p < 0.05) QOL predictors (total MusiQOL) were as follows: the number of complaints, IADL results, BDI results, EDSS score, higher education, and material status >2000 PLN. In addition, the multiple linear regression model showed that the BDI result was a significant predictor of QOL ( p < 0.005). Conclusion Depressive symptoms significantly affect the QOL of MS patients.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".