Cognitive, psychological and social factors associated with older adults' mobility: a scoping review of self‐report and performance‐based measures
Bibliographic record
Abstract
Although many factors have been associated with mobility among older adults, there is paucity of research that explores the complexity of factors that influence mobility. This review aims to synthesise the available evidence for factors comprising the cognitive, psychological, and social mobility determinants and their associations with mobility self-reported and performance-based outcomes in older adults (60 years). We followed Arksey and O'Malley's five stages of a scoping review and searched PubMed, EMBASE, PsychINFO, Web of Science, AgeLine, Allied and Complementary Medicine Database, Cumulative Index to Nursing and Allied Health Literature and Sociological Abstract databases. Reviewers in pairs independently conducted title, abstract, full-text screening and data extraction. We reported associations by analyses rather than articles because articles reported multiple associations for factors and several mobility outcomes. Associations were categorised as significantly positive, negative, or not significant. We included 183 peer-reviewed articles published in 27 countries, most of which were cross-sectional studies and conducted among community-dwelling older adults. The 183 articles reported 630 analyses, of which 381 (60.5%) were significantly associated with mobility outcomes in the expected direction. For example, older adults with higher cognitive functioning such as better executive functioning had better mobility outcomes (e.g., faster gait speed), and those with poor psychological outcomes, such as depressive symptoms, or social outcomes such as reduced social network, had poorer mobility outcomes (e.g., slower gait speed) compared to their counterparts. Studies exploring the association between cognitive factors, personality (a psychological factor) and self-reported mobility outcomes (e.g., walking for transportation or driving), and social factors and performance-based mobility outcomes in older adults are limited. Understanding the additive relationships between cognitive, psychological, and social factors highlights the complexity of older adults' mobility across different forms of mobility, including independence, use of assistive devices, transportation, and driving.
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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 | 0.016 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".