Analysis of the Influence of Depression on the Occupational Performance of People Diagnosed with Multiple Sclerosis and Its Impact on Caregiver Burden
Bibliographic record
Abstract
Background: One of the most common symptoms in multiple sclerosis (MS) is depression, which causes disruption to daily participation. MS as a degenerative disease causes caregiver strain. The aim of this study is to analyze the influence of depression on the occupational performance of people with MS and to study whether these aspects influence caregiver strain. Materials and Methods: A descriptive cross-sectional observational study was carried out. A total of 124 people with a diagnosis of multiple sclerosis were assessed and administered the Beck Depression Inventory-II, the Canadian Occupational Performance Measure, and the Zarit Caregiver Burden Scale. Results: MS type influences performance, involvement, and caregiver burden. High levels of depression are associated with low levels of participation and performance. The types of MS with the highest caregiver burden are relapsing-remitting and secondary progressive. Conclusions: The type of MS negatively influences occupational performance. Depression and occupational performance are related to caregiver strain. The greater the depressive symptoms, the worse the performance, and the more caregiver strain.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".