Exploring unmet needs and preferences of young adult stroke patients for post-stroke care through PROMs and gender differences
Bibliographic record
Abstract
Background: Stroke incidence among young adults of working age (under 65 years of age) has significantly increased in the past decade, with major individual, social, and economic implications. There is a paucity of research exploring the needs of this patient population. This study assessed: (1) young adult stroke patients' physical, psychological, and occupational functioning and health-related quality of life (HRQoL); and (2) post-stroke care preferences using patient-reported outcome measures (PROMs), with attention to gender differences. Methods: A cross-sectional pilot study was conducted. Sociodemographic and clinical characteristics were collected through chart review and data on occupational function, physical, psychological, and social wellbeing >90 days post-stroke through a self-reported survey. Descriptive statistics, gender-based, and regression analyses were conducted. Results: = 0.02) for psychological symptoms. Conclusion: This is the first study to report impaired HRQoL, psychological and occupational functioning using PROMs, with significant gender differences and preferences for post-stroke care delivery among young adult stroke patients at >90 days after stroke. The findings highlight the importance of needs, gender, and age-specific post-stroke education and interventions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".