Predictors of long-term participation after stroke
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: (1) To explore factors that predict long-term participation after stroke (2-4 years after discharge from rehabilitation), and (2) to determine factors that predict both short- and long-term participation. METHODS: Biopsychosocial data of people who had had a stroke were measured at discharge from an intensive rehabilitation unit using valid instruments. Six months later (n=102) as well as 2-4 years later (n=66), social participation of the survivors was measured in their living environments. Participation was estimated with the Assessment of Life Habits (LIFE-H), which includes 12 categories of daily activities and social roles. RESULTS: From multivariate regression analyses, the best predictors of long-term participation after stroke appear to be age, comorbidity, motor coordination, upper extremity ability and affect. Age, comorbidity, affect and lower extremity coordination are the best predictors of participation after stroke at both measurement times. CONCLUSIONS: With the exception of age, these factors may be positively modified and thus warrant special attention in rehabilitation interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it