Effects of Retro-Walking Training on Kinesiophobia and Cognition in Geriatric Population: A Quasi - Experimental Study
Bibliographic record
Abstract
Introduction: Aging brings challenges such as Kinesio phobia and cognitive decline, significantly impacting quality of life and fall risk in older adults. Retro-walking, a novel exercise modality, has shown promise in improving balance and motor control. Objective: This study aimed to assess the effects of retro-walking training on kinesiophobia and cognition in geriatric subjects. Methodology: A quasi-experimental design was employed with 60 geriatric participants aged 65-75 years. Participants were divided into control and experimental groups. The experimental group underwent retro-walking training thrice weekly for 6 weeks, complemented by home exercises. Kinesio phobia was assessed using the Tampa Scale of Kinesiophobia (TSK), and cognition was evaluated using the Montreal Cognitive Assessment (MoCA) scale. Result: Significant improvements were observed in both TSK (pre: 50.6 ± 8.6, post: 27.6 ± 6.9, p < 0.001) and MoCA scores (pre: 25.0 ± 3.1, post: 27.7 ± 1.8, p < 0.001) post- intervention. The experimental group showed a marked reduction in kinesiophobia and enhanced cognitive function compared to the control group. Conclusion: Retro-walking training demonstrated beneficial effects on reducing kinesiophobia and enhancing cognition in geriatric subjects. These findings suggest that retro-walking can be an effective intervention to improve functional outcomes and mitigate fall risks in the elderly population.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".