Rate of perceived stability as a measure of balance exercise intensity in people post-stroke
Bibliographic record
Abstract
Purpose This study investigates the reproducibility and concurrent validity of the Rate of Perceived Stability (RPS) Scale in people with stroke.Methods On two separate days (2–10 days apart), participants provided their RPS ratings during clinical measures: 1)16 tasks from Community Balance and Mobility Scale (CB&M), 2)6-minute walk test (6MWT), and 3)self-paced gait speed. Intraclass correlations (ICCs) assessed between day test-retest reliability of RPS ratings. Standard error of measurement (SEM) and smallest detectable change (SDC) addressed level of between day agreement. Spearman rank correlations (rs) quantified relationships between RPS, and general rating of perceived challenge, task-performance scores.Results Thirty participants with stroke (50% female) participated. ICC ranged from 0.46 to 0.93 across tasks with 12/19 tasks showing ICCs above 0.75 (good test-retest reliability). SEM was 1-point for each task and SDC ranged from 2 to 4 across tasks. Concurrent validity between RPS and ratings of perceived challenge was good-to-excellent (rs ranged 0.78–0.94, p < 0.01). Higher RPS (indicative of feeling less stable) was associated with lower balance performance scores on CB&M tasks, negative relationships ranged in strength from fair to good-to-excellent in 10/16 tasks (rs ranged −0.46 to −0.81, p ≤ 0.01).Conclusions RPS shows promise as a measure of balance intensity in people with stroke.IMPLICATIONS FOR REHABILITATIONThe RPS is a reliable and valid measure of balance intensity in ambulatory people with stroke.The RPS scale may be a useful clinical tool to address the gap in practice of measuring balance intensity during rehabilitation of walking balance post-stroke.
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.
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 | 0.003 | 0.016 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".