Walking football as sustainable exercise for older adults – A pilot investigation
Bibliographic record
Abstract
The health benefits of playing football and the importance of exercise and social contact for healthy ageing are well established, but few older adults in the UK take enough exercise. Football is popular, flexible in format and draws players into engrossing, effortful and social exercise, but the physical demands of play at full speed may make it unsustainable for some older adults. Restricted to walking pace, will play still be engaging? Will health benefits be retained? Will physical demands remain manageable? This pilot study aims to investigate: (1) the experience of older adults playing walking football every week, is it sustainable and rewarding, (2) the intensity and locomotor pattern of walking football, (3) the scale and nature of walking football health benefits and (4) possible cognitive benefits of playing walking football through measures of processing speed, selective and divided attention and updating and inhibition components of executive function. 'Walking football' and 'waiting list' groups were compared before and after 12 weeks of one-hour per week football. Walking football was found to be engaging, sustainable for older adults and moderately intensive; however, selective health and cognitive benefits were not found from this brief intervention. Highlights Walking football is a lower impact but authentic form of football that enables older players to extend their active participation. Walking football is enjoyable and moderately demanding and may be a sustainable form of exercise for older adults. Health and cognitive benefits to playing walking football were not found.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".