Steady As You Go (SAYGO): A Falls-Prevention Program for Seniors Living in the Community
Bibliographic record
Abstract
ABSTRACT This study was an implementation and community trial of a new falls-prevention program for seniors called Steady As You Go (SAYGO). The program, designed in the Capital Health region of Alberta, integrated the knowledge gained from successful falls-prevention research into a brief community intervention. SAYGO included a multifactorial, risk-abatement approach, as well as a cognitive-behavioural and environmental focus. The target population was relatively healthy and mobile, community-dwelling seniors. The randomized community trial was conducted in urban and rural areas in Alberta, with 660 seniors participating. Seniors who completed the program made significant reductions in eight of the nine risk factors addressed in the program. Over a 4-month follow-up period, the proportion of seniors who fell was lower in the treatment group (17%) than in the control group (23%). Among those seniors who had reported a fall in the previous year, a significantly lower proportion of those in the treatment group experienced a fall in the follow-up period (20%) as compared to those in the control group (35%).
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".