Psychometric properties of life-space mobility measures in community-dwelling older adults: a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Mobility is one of the most important contributors to healthy aging and is traditionally measured through performance-based tests. Measuring life-space mobility is a holistic way to measure the spaces individuals visited over a period of time versus what they are physically able to do. However, before a measure of life-space mobility can be widely used in research and clinical settings, it must have robust psychometric properties. The objective of this review is to summarize the psychometric properties of existing life-space mobility measures in community-dwelling older adults. INCLUSION CRITERIA: The construct is life-space mobility and the instruments are: The Nursing Home Life Space Diameter, the Life-Space Questionnaire, and the Life-Space Assessment. The population is community-dwelling older adults (age > 65). The outcome of the review includes all psychometric properties (reliability, validity, responsiveness) as well as feasibility and interpretability data. METHODS: Following the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) and JBI guidelines, a search strategy will be piloted and then translated to multiple databases. Two independent reviewers will conduct title/abstract screening, full-text screening, data extraction, and assess the methodological quality of the studies. A narrative synthesis will be compiled for all collected data. A meta-analysis will be conducted for each psychometric property if there are enough studies with sufficiently low heterogeneity. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42019121855.
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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 | 0.081 | 0.097 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.017 | 0.016 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.049 | 0.006 |
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".