Physical Function and Health Status among Seniors with and without a Fear of Falling
Bibliographic record
Abstract
BACKGROUND: Fear of falling (FF) is pervasive among older people and is an independent risk factor for decreased mobility and loss of quality of life. Although it is a serious health concern, little is known about the severity of the physical and health-related deficits in high-functioning fearful seniors. OBJECTIVE: This study examined the physical correlates of FF in community-dwelling seniors in relation to their non-fearful counterparts and also explored the relevance of recent fall history. SUBJECTS: Twenty-five volunteers who stated that they had curtailed their activities due to a FF and who reported themselves to be healthy participated. Non-fearful, age- and gender-matched subjects were also recruited and served as a comparison group. METHODS: This cross-sectional study had participants come to the laboratory on one occasion for about 1.5 h. Limits of balance stability, walking speed, and lower limb muscle strength were measured in random order. In addition, the SF-36, the Activities-specific Balance Confidence (ABC) scale and the Human Activity Profile questionnaires were completed to provide measures of heath status, FF and activity levels, respectively. RESULTS: Subjects with a FF had lower ABC scores (69.8 +/- 10.2) than controls (90.2 +/- 7.9; p < 0.001), and although they reported activity curtailment, the groups presented similar activity profiles (p > 0.05). Balance ability was not compromised in seniors with a FF, although their walking speed was slower than that of control subjects (p < 0.004). Lower limb weakness was significant in the FF group, which also reported low physical health. Perceived physical health, activity and hip flexor torque in combination accounted for almost 62% of the variance in ABC scores. Secondary analysis of the data from the FF group revealed a tendency for those who had fallen in the past year to restrict their limits of stability compared to those who had not fallen; though generally the effect sizes were small to moderate. CONCLUSIONS: The marked deficits in strength and health status found among seniors living independently in the community, who are in good health, but report being fearful of falling underscores the seriousness of FF as a potential health risk factor in the well elderly.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".