Investigation of the Relationship of Recommended Home Exercises with Dual-Task Training for the Elderly with Physical Activity Level, Life Quality and Kinesiophobia
Bibliographic record
Abstract
Aim: To examine the effect of home exercises combined with dual-task training on physical activity level and quality of life in the elderly, and to investigate the impact of home exercises on fear of movement.Material and Methods: 60 volunteer participants over the age of 65 were included in the study. The average age of the participants was 81 years, and 70% of the participants were women. Participants were randomly divided into two equal groups called single and dual-task groups. While standard home exercise protocol was applied to both groups, additional cognitive tasks were assigned to the dual-task group. Participants were given 45 minutes of exercise under a physiotherapist monitor in a home environment three days a week for four weeks. Before the first session and after the last session, the participants were evaluated with the World Health Organization Quality of Life Scale Elderly Module, Berg Balance Scale, Fall Efficiency Scale, Tampa Kinesiophobia Scale, Physical Activity Scale for Elderly, Timed Up and Go Test, and Montreal Cognitive Assessment Scales.Results: In the analysis performed between the groups, the results of the Berg Balance Scale, the Physical Activity Scale for the Elderly, and the Montreal Cognitive Assessment Scales were found to be statistically significant (p<0.05). It was found that home exercises performed with single and dual-task training did not significantly affect movement anxiety (p> 0.05).Conclusions: Home exercises with dual-task training; It is more successful in improving balance, increasing physical activity level, and increasing cognitive performance compared to home exercises performed with single-task training.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".