Falls Prevention Training for Community Health Workers: Strategies and Actions for Independent Living (SAIL)
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
<h4></h4> <p>This article describes a quasi-experimental study on falls prevention for clients of home support services in British Columbia, Canada. The study tested a nurse-designed multifactorial intervention, delivered by community health workers. The intervention consisted of 1 day of falls surveillance and prevention training for 51 community health workers, followed by 6 months of evidence-based interventions with their clients (<em>n</em> = 70) using a pretested Checklist and Action Plan. Study findings showed a 43% reduction (<img alt="" width="8" height="10" src="http://www.jognonline.com/images/content/200610/chi.gif" style="border-width: 0px; border-style: solid;" /><sup>2</sup> = 8.742, <em>p</em> &lt; .01) in falls and a 44% reduction (<img alt="" width="8" height="10" src="http://www.jognonline.com/images/content/200610/chi.gif" style="border-width: 0px; border-style: solid;" /><sup>2</sup> = 5.739, <em>p</em> &lt; .05) for fallers (those who fell once or more) from the 6-month preintervention period to postintervention. The proportion of falls resulting in any injury did not decrease; however, fractures were reduced from seven in the 6-month preintervention period to one following the intervention. The results indicate this intervention is an effective and inexpensive falls prevention strategy for frail recipients of home support services.</p>
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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 | 0.003 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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