How does it feel to run in minimalist and advanced footwear technology shoes: A qualitative study involving male recreational runners
Bibliographic record
Abstract
We examined the perceptions and experiences of male recreational runners when using minimalist racing flats (FLAT, Saucony Endorphin Racer 2) and advanced footwear technology (AFT, Nike Vaporfly 4%) shoes, compared with their habitual shoes (OWN). Eighteen runners completed three 1.5 km outdoor trials, running in OWN first, followed by FLAT and AFT in a randomised counter-balanced order. Semi-structured interviews conducted before and after each trial provided qualitative data, analysed using a six-phase reflexive thematic approach. Five interconnected themes emerged: 'novelty and familiarity', 'feel', 'performance', 'biomechanics', and 'injury'. Runners' perceptions were shaped by iterative feedback loops combining experiential, educated, and instinctual assessments. OWN shoes were generally ranked highest for comfort and lowest for perceived injury risk due to familiarity and balanced design. Novel shoes elicited mixed reactions. FLAT shoes were valued for their lightweight and natural feel, but raised concerns about discomfort and potential injury from minimal cushioning and support. AFT shoes were appreciated for their bounciness and performance potential, but raised concerns about instability and excessive cushioning. Findings indicate that footwear comfort is multifaceted, context-dependent, and not always aligned with performance or injury reduction. Runners often prioritised performance over comfort in competitive scenarios, highlighting the inherent trade-offs in footwear selection and the importance of personalised approaches. Concerns about injury and biomechanics changes underscore the need for gradual transitions to novel footwear. By adopting a real-world approach, this study advances understanding of footwear perceptions, emphasises the dynamic and subjective nature of runners' experiences, and offers practical implications for runners, clinicians, and shoe manufacturers.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".