Changes in executive functions and self-efficacy are independently associated with improved usual gait speed in older women
Bibliographic record
Abstract
BACKGROUND: Improved usual gait speed predicts substantial reduction in mortality. A better understanding of the modifiable factors that are independently associated with improved gait speed would ensure that intervention strategies are developed based on a valid theoretical framework. Thus, we examined the independent association of change in executive functions and change in falls-related self-efficacy with improved gait speed among community-dwelling senior women. METHODS: A secondary analysis of the 135 senior women aged 65 to 75 years old who completed a 12-month randomized controlled trial of resistance training. Usual gait speed was assessed using a 4-meter walk. Three executive processes were assessed by standard neuropsychological tests: 1) set shifting; 2) working memory; and 3) selective attention and response inhibition. A linear regression model was constructed to determine the independent association of change in executive functions and falls-related self-efficacy with change in gait speed. RESULTS: Improved selective attention and conflict resolution, and falls-related self-efficacy, were independently associated with improved gait speed after accounting for age, global cognition, baseline gait speed, and change in quadriceps strength. The total variance explained was 24%. CONCLUSIONS: Interventions that target executive functions and falls-related self-efficacy, in addition to physical functions, to improve gait speed may be more efficacious than those that do not. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00426881.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".