Increased Risk of Falling in Older Community-Dwelling Women With Mild Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: Falls are a major health care problem for older people and are associated with cognitive dysfunction. Mild cognitive impairment (MCI) is an increasingly recognized clinical problem. No study has comprehensively compared people with and without MCI for fall risk factors in both the physiological and cognitive domains. OBJECTIVE: The purpose of this cross-sectional study was to comprehensively compare fall risk factors in community-dwelling older women with and without MCI. DESIGN: A cross-sectional design was used in the study. METHODS: Community-dwelling women (N=158) with Folstein Mini Mental State Examination scores of >or=24 participated in the study. The Montreal Cognitive Assessment (MoCA) was used to categorize participants as either having or not having MCI. Each participant's fall risk profile was assessed with the Physiological Profile Assessment (PPA). Three central executive functions were assessed: (1) set shifting was assessed with the Trail Making Test (part B), (2) updating (ie, working memory) was assessed with the Verbal Digits Backward Test, and (3) response inhibition was assessed with the Stroop Colour-Word Test. RESULTS: Both the composite PPA score and its subcomponent, postural sway performance, were significantly different between the 2 groups; participants with MCI had higher composite PPA scores and greater postural sway compared with participants without MCI. Participants with MCI performed significantly worse on all 3 central executive function tests compared with participants without MCI. LIMITATIONS: A screening tool was used to categorize participants as having MCI, and fall risk factors were compared rather than the actual incidence of falls. CONCLUSIONS: Fall risk screening may be prudent in older adults with MCI.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".