The relationship between fear of falling and functional ability following a multi-component fall prevention program: an analysis of clinical data
Bibliographic record
Abstract
Objectives The first objective was to evaluate clinical data from a multi-component fall prevention program. The second objective was to explore the relationship between physical function and fear of falling (FoF)Methods Adults (N = 287, mean age = 76 years) who participated in the Building Balance Program between 2011–2020 were assessed with five physical function measures and two FoF measures. Repeated measures ANOVA controlling for age and sex were performed to assess change from baseline. Linear regressions were conducted to evaluate how physical function explained variations in FoFResults There were significant improvements between pre and post-program Berg Balance Scale (BBS) scores (p < .001), Timed-Up and Go (TUG) times (p < .001), 30 second Chair-Stand (30 CST repetitions) (p < .001), Functional Reach (FR) distance (p < .001), gait speed (p < .001), single item-FoF score (p < .001), and short Falls Efficacy Scale-International (FES-I score) (p < .001). After controlling for sex on all regression analyses, age, and pre-program gait speed explained variations in pre-program short FES-I scores (Adjusted R2 = 0.19). Age, pre-program BBS and 30 CST repetitions explained variations in pre-program level of FoF (Adjusted R2 = 0.25). Variations in post-program short FES-I scores (Adjusted R2 = 0.17) were explained by age, post-program TUG times and FR distance after controlling for age and sex. Robust regressions indicated variations in post-program level of FoF explained by age, post-program TUG and FR distance with a two-way interaction between age and FRConclusion A multi-component fall prevention program improved physical function and decreased FoF. A small association between physical function and FoF similar between pre- and post-program conditions was identified.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".