Feasibility and results of a pilot study of group occupational therapy for fall risk management after stroke
Bibliographic record
Abstract
Introduction This article examines the feasibility and outcomes of a pilot study of Group Occupational Therapy for Falls, a fall risk management program designed for individuals with chronic stroke. Method This was a single-arm pilot study. All 10 participants had chronic stroke (>6 months), self-reported falling or fear of falling, and used a mobility device. Group Occupational Therapy for Falls included six sessions and focused on individual fall risk factor management. Assessments were completed before and after the intervention and assessed management of fall risk factors (five assessments, including the Falls Control Scale and Falls Prevention Strategy Survey), fear of falling (yes/no) question, falls self-efficacy, and activity and participation with the IMPACT (ICF Measure of Participation and ACTivity). Alpha was set at .10 owing to the small sample size and feasibility/pilot-study design. Results Group Occupational Therapy for Falls was feasible and management of fall risk factors improved overall, with significant improvements noted in the Falls Control Scale ( p = .046) and Falls Prevention Strategy Survey (.064). The number of people with FoF significantly decreased ( p = .076). Conclusion Group Occupational Therapy for Falls for fall prevention after stroke should be further developed and assessed in people with stroke as a promising intervention that may manage fall risks and possibly fall rates in the future.
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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 | 0.018 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".