Bridging the Gap between Research and the Community: Implementing Physical and Cognitive Interventions to Improve Spontaneous Walking Speed in Older Adults
Bibliographic record
Abstract
The application of interventions to enhance mobility in ecological settings remain understudied. This study was developed to evaluate the feasibility of training methods in a community centre and to evaluate their impact on mobility outcomes. Fifty-four participants were randomized to one of three 12-week training programs (three times/week): aerobic (AE), gross motor abilities (GMA) or cognitive (COG). Feasibility was evaluated by calculating adherence, feedback from participants and long-term participation. The impact of these interventions on mobility was assessed by comparing pre- and post-program on Timed-up-and-go (TUG) and spontaneous walking speed (SWS) performances. Results showed relatively high rates of adherence (85.1%) and long-term participation (66.7%), along with favorable feedbacks. SWS significantly improved in COG (0.10 ± 0.11 m.s−1; p = 0.004) and AE (0.06 ± 0.11 m.s−1; p = 0.017) groups, and TUG performance was maintained in all groups. Results of this feasibility study demonstrated successful implementation of physical and cognitive training programs, encouraging the development of real-world applications.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".