EVALUATION OF A CANADIAN PRIMARY CARE FALL PREVENTION TRAINING AND RESOURCE PACKAGE
Bibliographic record
Abstract
Background Few physicians have the training/resources to include evidence-based fall prevention (FP) strategies as part of their standard practice. Aims/Objectives/Purpose To address this, a Primary Care Fall Prevention (PCFP) package was developed including: an instructional video; fact sheets; a fall risk checklist; and patient handouts. Materials were evaluated to determine effectiveness of the resources to increase knowledge and/or bring about change in physician practice. Methods A pre/post survey on fall-related knowledge, use of FP resources/strategies was conducted with family physicians recruited from those with substantial numbers of elderly patients. After applying the package over 4–6 weeks, 11 participated in in-depth phone interviews; 10 provided a follow-up survey. Results/Outcomes Out of a max of 17, the average ‘fall-related knowledge’ pre score=10.2 (SD=2.5) and post-survey=13.2 (SD=1.3) (t (9)=2.7, p<0.03). After reviewing resources, 60% were more likely to screen for fall risk; 30% more likely to assess mobility and/or balance; 50% more likely to give fall risk handouts; and 20% more likely to provide information on medication/fall risk. After reviewing materials on fall-prevention strategies, 30% were more likely to provide education on home safety/physical activity/balance exercises; 50% more likely to refer to PT/OT; 40% more likely to provide Vit D guidelines, 50% more likely to provide calcium intake guidelines; and 20% more likely to make referrals to FP programmes. Interviews revealed insights into barriers and facilitators to PCFP. Significance/Contributions to the Field The PCFP package increased knowledge and showed some improvements in FP practice among physicians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.000 | 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) | 0.000 | 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 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".