FIT for FUNCTION: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: The current state of evidence suggests that community-based exercise programs are beneficial in improving impairment, function, and health status, and are greatly needed for persons with stroke. However, limitations of these studies include risk of bias, feasibility, and cost issues. METHODS/DESIGN: This single-blinded, randomized controlled trial (RCT) of 216 participants with stroke will compare the effectiveness of a 12-week YMCA community-based wellness program (FIT for FUNCTION) specifically designed for community-dwelling persons with stroke to persons who receive a standard YMCA membership. The primary outcome will be community reintegration using the Reintegration to Normal Living Index at 12 and 24 weeks. Secondary outcomes include measurement of physical activity level using the Rapid Assessment of Physical Activity and accelerometry; balance using the Berg Balance Scale; lower extremity function using the Short Physical Performance Battery; exercise capacity using the 6-min walk test; grip strength and isometric knee extension strength using hand held dynamometry; and health-related quality of life using the European Quality of Life 5-Dimension Questionnaire. We are also assessing cardiovascular health and lipids; glucose and inflammatory markers will be collected following 12-h fast for total cholesterol, insulin, glucose, and glycated hemoglobin. Self-efficacy for physical activity will be assessed with a single question and self-efficacy for managing chronic disease will be assessed using the Stanford 6-item Scale. The Patient Activation Measure will be used to assess the patient's level of knowledge, skill, and confidence for self-management. Healthcare utilization and costs will be evaluated. Group, time, and group × time interaction effects will be estimated using generalized linear models for continuous variables, including relevant baseline variables as covariates in the analysis that differ appreciably between groups at baseline. Cost data will be treated as non-parametric and analyzed using a Mann-Whitney U test. DISCUSSION: This is a RCT with broad study eligibility criteria intended to recruit a wide spectrum of individuals living in the community with stroke. If positive benefits are demonstrated, results will provide strong research evidence to support the implementation of structured, community-based exercise and education/self-management programs for a broad range of people living in the community with stroke. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02703805 . Registered on 14 October 2014.
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How this classification was reachedexpand
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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 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 teacher head, 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".