Less habitual knee-bent sitting and more lying time are associated with worse frailty, mobility and balance in long-term care residents
Bibliographic record
Abstract
The impact of habitual postures on frailty, and balance, mobility, and transfer ability, particularly among people in long-term care. We sought to characterize the time spent in detailed postures and the relationships they have with frailty and Hierarchical Assessment of Balance and Mobility (HABAM) among older adults living in long-term care. Forty-four moderate-to-severely frail long-term care residents were recruited (36 females; age: 83 ± 10 years; body mass index: 31.8 ± 7.6 kg/m 2 ). Participants wore an activPAL on their torso, thigh, and shin for 3.6 ± 0.5 days. Frailty was determined via a 65-item index and Clinical Frailty Scale (CFS). Functional abilities were measured using the HABAM. Linear regressions, adjusted for age and body mass index, demonstrated that higher frequency of sit-to-stand transitions (18 ± 23 transitions/day), standing time (52 ± 87 min/day) and step counts (442 ± 945 steps/day) were associated with lower frailty (frailty index: 0.438 ± 0.115) and higher HABAM scores (23.2 ± 16.3/67.0; all, p ≤ 0.034). Knee-bent sitting (142 ± 228 min/day) was associated with higher HABAM and lower frailty index scores (both, p ≤ 0.002). More non-upright time (1337 ± 133 min/day) and lying time (1138 ± 372 min/day) were associated with worse frailty index and HABAM scores (all, p ≤ 0.021). There were no associations between straight-legged sitting (56 ± 227 min/day) with frailty index or HABAM scores (both, p ≥ 0.219). Overall, participant posture was mostly characterized by a horizontal thigh (sitting or lying), with ~1 h/day upright. Intervention models promoting upright time, sit-to-stand transitions, and knee-bent sitting rather than lying are warranted for frailty and HABAM management.
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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 | 0.000 | 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 | 0.000 |
| 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".