Balance and Gait of Frail, Pre-Frail, and Robust Older Hispanics
Bibliographic record
Abstract
Older Hispanics are an understudied minority group in the US, and further understanding of the association between frailty, gait and balance impairments in disadvantaged older Hispanics is needed. The objectives of this study were to compare the balance and gait of older Hispanics by their frailty status. Sixty-three older Hispanics (21 men, 42 women, mean age 75 ± 7 years) attending senior centers in disadvantaged neighborhoods were grouped by their frailty status and completed balance and walking tests at a preferred speed and during street crossing simulations. Sixteen percent (n = 10) of the participants were frail, 71% (n = 45) were pre-frail, and 13% (n = 8) were robust. Frail participants had poorer balance than robust participants (F = 3.5, p = 0.042). The preferred walking speed of frail and pre-frail participants was lower (F = 6.3, p < 0.011) and they took shorter steps (F > 3.5, p = 0.002) than robust participants. During street crossing conditions, frail participants had wider steps (F = 3.3, p = 0.040), while pre-frail participants walked slower (F = 3.6, p = 0.032), and both took shorter steps than robust participants (F > 3.5, p < 0.043). Frailty and pre-frailty were prevalent and associated with gait and balance impairments in disadvantaged older Hispanics. The findings can inform the development of programs and interventions targeting this vulnerable underserved population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".