A unified framework for the measurement of mobility in older persons
Bibliographic record
Abstract
Mobility is often referred to as a 'sixth vital sign' because of its ability to predict critical health outcomes in later adulthood. In the World Health Organization (WHO) World Report on Aging and Health, mobility is described as movement in all its forms whether powered by the body or a vehicle. As such, mobility encompasses basic physical actions such as getting up from a chair and walking, as well as activities such as exercising, driving and using public transportation. A plethora of measurement tools have been developed to assess various aspects of mobility; however, there is wide variability in the mobility constructs being measured which limits standardisation and meaningful comparison across studies. In this paper, we propose a comprehensive framework for measuring mobility that considers three distinct facets of mobility: perceived mobility ability ('what can you do'), actual mobility ability ('what you actually do') and locomotor capacity for mobility ('what could you do'). These three facets of mobility are rooted in the three components of healthy aging endorsed by the WHO: functional ability, intrinsic capacity and environments. By proposing a unified framework for measuring mobility based on theory and empirical evidence, we can advance the science of monitoring and managing mobility to ensure functional ability in older age.
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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 | 0.023 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".