‘The right advice’: a qualitative study examining enablers and barriers to recreational running and beliefs about knee health following knee surgery
Bibliographic record
Abstract
OBJECTIVES: To examine the experiences, knowledge and beliefs of recreational runners with a history of knee surgery regarding (i) enablers and barriers to running participation, (ii) the association of running and knee joint health, and (iii) perceived benefits and motivations for running. METHODS: 17 runners (≥3 times/week, ≥10 km/week) with a history of knee surgery (7±7 years post-surgery, 9 women, age 36±8 years) participated in one-on-one semi-structured interviews. Interviews were recorded, transcribed verbatim and analysed using reflexive thematic analysis. Trustworthiness was built by following established qualitative research guidelines and by participant validation of findings in the final analysis stages. RESULTS: We identified 9 themes (5 subthemes) for aim (i); 3 themes (10 subthemes) for aim (ii); and 2 themes (4 subthemes) for aim (iii). Positive health professional support including education, exercise rehabilitation and a tailored return-to-run plan enabled participants to return to running following surgery. Effective load management either independently or with coach assistance, and consistent strength training were considered key to maintaining participation. Barriers to running following surgery included unhelpful health professional encounters, persistent knee symptoms and muscle weakness, new running-related injuries, anxiety and fear about reinjury, and difficulty finding time. Participants had varying beliefs about running and knee joint health, although most believed that running benefited long-term knee health. Improved mental health and social connection were the most common motivators to run. CONCLUSION: Our qualitative findings may inform strategies to support adults to commence, or return to, and maintain running participation following knee surgery.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".