Changes in life habits affected by mild stroke and their association with depressive symptoms
Bibliographic record
Abstract
OBJECTIVES: To examine changes in sleep, driving, employment, relationships and leisure in the first year after a mild stroke and explore the association between the presence of depressive symptoms and improvement in participation 6 months later. METHODS: Social participation (LIFE-H 3.1) and depressive symptoms (Beck Depression Inventory-II) were measured in the first month (T0), 6 months and 1 year after mild stroke. Descriptive statistics and logistic regression analysis were used. RESULTS: There were 186 participants at T0, 149 at 6 months and 138 at 1 year. Mean age at T0 was 63.3 ± 12.5 years and 81/186 (43.6%) were female. All the life habits examined showed an improvement at 6 months and 1 year, except for having a sexual relationship (p = 0.12) at 6 months, and sleep at 6 months (p = 0.15) and 1 year (p = 0.07). A significant association between the presence of depressive symptoms at T0 and reduced participation at 6 months was obtained for driving a vehicle (p = 0.02), participating in sports or recreational activities (p = 0.01) and interpersonal relationships (p = 0.003), but not for holding a paid job (p = 0.06). CONCLUSION: Systematic screening for depression should be carried out upon discharge from hospital in order to better target individuals who have had a mild stroke and are in further need of rehabilitation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".