Perception about Running and Knee Joint Health among the Public and Healthcare Practitioners
Bibliographic record
Abstract
PURPOSE: There is conflicting evidence surrounding the effect of running on knee joint health, particularly as it relates to knee osteoarthritis (KOA). The perception about running and knee joint health could affect choices of activities, but remains undocumented in the population. Given the uncertainty in the literature, the objective of this study was to evaluate the perception of the public and healthcare practitioners (HCP) with respect to running and KOA. METHODS: A total of 397 public respondents (mean age=53.1 years, 163 females; 79 non-runners [NRUN]; 318 runners [RUN]) and 176 HCP (mean age=39.2 years, 68 females) completed an online cross-sectional survey. The survey included multiple-choice questions about perceptions of running as it relates to knee joint health, and about the appropriateness of maintaining running by individuals with KOA. The HCP subgroup was also asked about clinical recommendations to runners with KOA. Proportions (agree, uncertain, disagree) were compared between subgroups using chi-squared tests. RESULTS: In general, 11% of respondents perceived running as detrimental for knee joint health (NRUN=43.0%, RUN=5.0%, HCP=6.3%; p<0.001) while 21.1% were uncertain. Frequent running was perceived as a risk factor for KOA by 6.3% of respondents (NRUN=24.1%, RUN=2.2%, HCP=5.7%; p<0.001) and 26.5% were uncertain. Running long distances (marathons, ultra-marathons) was perceived by 15.5% as a risk factor (NRUN=32.9%, RUN=9.1%, HCP=19.3%; p<0.001), but 38.7% were uncertain. As for continuation of running in the presence of KOA, 14.7% of respondents agreed that it would lead to greater cartilage damage (NRUN=40.5%, RUN=10.2%, HCP=11.1%; p<0.001). However, 31.3% were uncertain about the appropriateness of running in the absence of symptoms (NRUN=34.2%, RUN=38.7%, HCP=16.4%; p<0.001). The subgroup of HCP reported having recommended to 76.1% and 30.7% of runners with KOA to modify training parameters and to quit running, respectively. CONCLUSION: These results suggest that many non-runners perceive running as detrimental to knee joint health. High rates of uncertainty warrant further studies to guide the population and HCP about the appropriateness of running for individuals with KOA, as it may influence choices of physical activity and clinical recommendations.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".