Walking soccer: A systematic review of a modified sport
Bibliographic record
Abstract
BACKGROUND: Walking soccer (football) is an emerging modified sport gaining recognition globally. OBJECTIVES: To synthesize current evidence for walking soccer and provide a summary of global walking soccer organizations. DATA SOURCES: We searched for studies published across all years and all languages within multiple databases for studies focused on walking soccer (football) in adults (18 + years). Two authors independently screened citations at Level 1 and 2. We also conducted a forward citation search and reviewed the reference lists for included studies. We searched the gray literature to identify walking soccer organizations. We conducted the last database search in December 2019. STUDY APPRAISAL AND SYNTHESIS METHODS: We conducted a standard systematic review following established guidelines. We also summarized findings from a limited search for walking soccer organizations. For peer-reviewed literature, we used the Mixed Methods Appraisal Tool (MMAT) to assess methodological quality and conducted a narrative synthesis of the evidence. RESULTS: We identified nine peer-reviewed studies (with 117 participants). Most studies included small sample sizes and interventions with short duration. Walking soccer is an emerging modified sport that is popular across the United Kingdom (UK), with its reach extending to other countries. CONCLUSIONS: Limited published evidence exists for walking soccer, despite is global popularity. For the studies identified, generalizability was limited to predominately older men from the UK. Based on preliminary findings, walking soccer has the potential to confer health benefits and build social connections.
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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 | 0.019 | 0.087 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".