Development, Implementation, and Evaluation of an Interprofessional Falls Prevention Program for Older Adults
Bibliographic record
Abstract
This article describes the development and implementation of an Interprofessional Falls Prevention Program (IFPP) designed for community-dwelling seniors. The program was a collaborative pilot research study conducted in a retirement home and an outpatient hospital setting. The pilot was successful and was positioned into a permanent falls prevention program. The IFPP aimed at improving physical function and balance and reducing the fear of falling in seniors with a history of falls. The pilot study included an interprofessional falls assessment followed by a 12-week program of once-weekly group education and exercise sessions, 3- and 6-month follow-up visits, and individual counseling. To measure program effectiveness, the Berg Balance Scale, the Timed Up and Go Test, the Falls Efficacy Scale, and the Morse Fall Risk Scale were used at baseline, upon program completion, and at 3- and 6-month follow-up. Process measures were also collected, including patient satisfaction. Persistent improvements were found in participants' balance, strength, functional mobility, and fear of falling. Patient satisfaction with the program was high. Challenges faced in program implementation are also highlighted.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".