Impact of Pathway Shape and Length on the Validity of the 6-Minute Walking Test: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Although guidelines are established for performing the six-minute walking test (6MWT), it is not always possible to implement this test in any setting, due to physical and space limitations. Yet, variations in the conditions of the test could be responsible for heterogeneous outcomes. However, the impact of the condition of the 6MWT is not clearly established in literature. The objective is to determine the influence of different implementation conditions on the validity of the 6MWT. Seventeen articles were retained after a literature review, including 597 participants. Seven articles mention that performing the test on a predetermined short back-and-forth pathway led to lower performance than when the test was performed on pathways of greater distances. The walking distance covered on a rectangular path or on a 10-m eight-form path is greater than with the back and forth on a five- to ten-meter path. Seven articles suggest that the performance achieved on a treadmill is generally lower than that obtained while walking on the ground. Evidence shows that the conditions while performing the 6MWT significantly influence the score, hence the validity of the results. The use of a ground pathway, comprising the longest linear distance possible, seems critical to ensure good validity.
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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 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.023 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".