The influence of fear of falling on gait variability: results from a large elderly population-based cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: To compare gait variability among older community-dwellers with and without fear of falling and history of falls, and 2) to examine the association between gait variability and fear of falling while taking into account the effect of potential confounders. METHODS: Based on a cross-sectional design, 1,023 French community-dwellers (mean age ± SD, 70.5 ± 5.0 years; 50.7% women) were included in this study. The primary endpoints were fear of falling, stride-to-stride variability of stride time and walking speed measured using GAITRite® system. Age, gender, history of falls, number of drugs daily taken per day, body mass index, lower-limb proprioception, visual acuity, use of psychoactive drugs and cognitive impairment were used as covariables in the statistical analysis. P-values less than 0.05 were considered as statistically significant. RESULTS: A total of 60.5% (n=619) participants were non-fallers without fear of falling, 19% (n=194) fallers without fear of falling, 9.9% (n=101) non-fallers with fear of falling, and 10.7% (n=109) fallers with fear of falling. Stride-to-stride variability of stride time was significantly higher in fallers with fear of falling compared to non-fallers without fear of falling. Full adjusted linear regression models showed that only lower walking speed value was associated to an increase in stride-to-stride variability of stride time and not fear of falling, falls or their combination. While using a walking speed ≥ 1.14 m/s (i.e., level of walking speed that did not influence stride-to-stride variability of stride time), age and combination of fear of falling with history of previous falls were significantly associated with an increased stride-to-stride variability of stride time. CONCLUSIONS: The findings show that the combination of fear of falling with falls increased stride-to-stride variability of stride time. However, the effect of this combination depended on the level of walking speed, increase in stride-to-stride variability of stride time at lower walking speed being related to a biomechanical effect overriding fear of falling-related effects.
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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 | 0.002 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".