Testing the Webber’s Comprehensive Mobility Framework Using Self-Reported and Performance-Based Mobility Outcomes Among Community-Dwelling Older Adults in Nigeria
Bibliographic record
Abstract
Abstract Background and Objectives In 2010, Webber and colleagues conceptualized the interrelationships between mobility determinants, and researchers tested Webber’s framework using data from developed countries. No studies have tested this model using data from developing nations (e.g., Nigeria). This study aimed to simultaneously explore the cognitive, environmental, financial, personal, physical, psychological, and social influences and their interaction effects on the mobility outcomes among community-dwelling older adults in Nigeria. Research Design and Methods This cross-sectional study recruited 227 older adults (mean age [standard deviation] = 66.6 [6.8] years). Performance-based mobility outcomes included gait speed, balance, and lower extremity strength, and were assessed using the Short Physical Performance Battery, whereas the self-reported mobility outcomes included inability to walk 0.5 km, 2 km, or climb a flight of stairs, assessed using the Manty Preclinical Mobility Limitation Scale. Regression analysis was used to determine the predictors of mobility outcomes. Results The number of comorbidities (physical factor) negatively predicted all mobility outcomes, except the lower extremity strength. Age (personal factor) negatively predicted gait speed (β = −0.192), balance (β = −0.515), and lower extremity strength (β = −0.225), and a history of no exercise (physical factor) positively predicted inability to walk 0.5 km (B = 1.401), 2 km (B = 1.295). Interactions between determinants improved the model, explaining the most variations in all the mobility outcomes. Living arrangement is the only factor that consistently interacted with other variables to improve the regression model for all mobility outcomes, except balance and self-reported inability to walk 2 km. Discussion and Implications Interactions between determinants explain the most variations in all mobility outcomes, highlighting the complexity of mobility. This finding highlighted that factors predicting self-reported and performance-based mobility outcomes might differ, but this should be confirmed with a large data set.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".