Cognitive status and sleep quality can explain the fear of falling and fall history in people with Parkinson’s disease
Bibliographic record
Abstract
Fear of falling (FOF) is highly prevalent in people with Parkinson's disease (PwPD) and contributes to high fall risk. Studies reporting on the relationship between falls, FOF, and non-motor factors such as cognitive function and sleep quality in Parkinson's disease are limited. This study aimed to investigate (1) the relationship of cognitive function and sleep quality with FOF, and history of falls in PwPD; (2) differences in cognitive function and sleep quality between Parkinson's disease fallers and non-fallers; and (3) a cut-off score for cognitive function and sleep quality to discriminate Parkinson's disease fallers from non-fallers. Fifty PwPD were assessed for FOF [Falls Efficacy Scale-International (FES-I)], cognition [Montréal Cognitive Assessment (MOCA)], sleep quality [Pittsburgh Sleep Quality Index (PSQI)], and falls history. The MOCA is significantly associated with FES-I scores ( R2 = 0.429, P < 0.0001). Both MOCA ( P = 0.012) and PSQI ( P = 0.027) were associated with falls history even after adjusting for confounding factors (age, sex, L-dopa use, Parkinson's disease severity). Both MOCA and PSQI scores were able to distinguish fallers from non-fallers with cut-off scores of 15.5 and 7.5, respectively. Although our findings revealed that both cognitive function and sleep quality are important factors influencing falls and FOF in PwPD, it remains to be determined if addressing cognitive impairments and poor sleep quality may favorably impact balance before integrating such screenings into fall prevention programs.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".