Fear of Falling in People With Multiple Sclerosis: Which Clinical Characteristics Are Important?
Bibliographic record
Abstract
BACKGROUND: Fear of falling (FOF) is an important risk indicator for health-related outcomes and quality of life in patients with multiple sclerosis (MS). However, factors associated with FOF in MS are not well investigated. OBJECTIVES: This study was done to explore predictors of FOF in this population. METHODS: Seventy relapsing remitting patients with MS were evaluated. Fear of falling was assessed using the Fall Efficacy Scale-International (FES-I). Motor outcomes included: 30-second chair stand test (30s-CST), Berg Balance Scale (BBS), 10-Meter Walk Test (10MWT), and 6-Minute Walk Test (6MWT). Cognitive status was determined using the Montréal Cognitive Assessment (MOCA) and Symbol Digit Modalities Test (SDMT). Affective factors including depression, fatigue, and sleep were also assessed using the Beck Depression Inventory (BDI), Modified Fatigue Impact Scale (MFIS), and Pittsburgh Sleep Quality Index (PSQI), respectively. RESULTS: Fear of falling was significantly correlated with all motor and affective measures used. However, a stepwise regression found that only BBS from motor measures, MOCA from cognitive measures, and sleep disorders from affective factors were significantly predictive of the FOF. CONCLUSIONS: Fear of falling in patients with MS is multifactorial and includes motor and nonmotor factors. Thus, therapies that aim to reduce risk of falling in this population should address motor functions, cognitive abilities, and sleep quality.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".