Comparing the responsiveness of the Functional Autonomy Measurement System (SMAF) with that of the Functional Independence Measure (FIM) in post-stroke rehabilitation
Bibliographic record
Abstract
Background: Functional independence of persons recovering from a stroke is essential for successful re-integration into the community. The Functional Independence Measure (FIM) is a standardized assessment tool widely used to document change in functional independence of persons post-stroke, while the Functional Autonomy Measurement System (SMAF), developed for assessing the elderly, is less often used with this population. Objective: To compare the responsiveness of the SMAF and FIM in persons post-stroke admitted for inpatient rehabilitation. Methods: The FIM and SMAF were administered at admission (T1) and discharge (T2) in persons post-stroke admitted for inpatient rehabilitation in three rehabilitation centres in the province of Quebec. Internal responsiveness was assessed with the standardized response mean (SRM) and Pearsonu2019s correlation coefficient(r), between changes in SMAF and FIM total scores. Results: A total of 143 persons post-stroke (67 u00b1 15 years) were evaluated. Results show that the SMAF and FIM total scores are strongly correlated at T1 and T2 (both r=0.90; p<0.001). The change in SMAF score (T2-T1) is significantly correlated with the change in FIM score (r=0.56; 95% CI=0.44-0.66). The internal responsiveness of the two total scores is good (SRM: 1.53 versus 1.45; p=0.25) but not different (p<0.05). Conclusion: Study results indicate that the SMAF and FIM total scores are strongly correlated and detect changes equally in the functional independence of persons post-stroke admitted for inpatient rehabilitation. This study suggests that the SMAF, initially designed for older adults with declining autonomy, can successfully be used to assess functional independence in persons undergoing post-stroke 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 | 0.011 | 0.027 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".