Qualitative Study Exploring the Meaning of Knee Symptoms to Adults Ages 35–65 Years
Bibliographic record
Abstract
OBJECTIVE: While osteoarthritis (OA) has mainly been viewed as a disease affecting older people, its prevalence in younger adults is substantial. However, there is limited research on how younger adults understand knee symptoms. This article explores the meaning of knee symptoms to adults ages 35-65 years. METHODS: This qualitative study comprised 6 focus groups and 10 one-on-one interviews with 51 participants (median age 49, 61% female), who self-reported knee OA or reported knee symptoms (i.e., pain, aching, or stiffness) on most days of the past month. Constructivist grounded theory guided the sampling, data collection, and analysis. Data were analyzed using a constant comparative method. RESULTS: Central to participants' understanding of knee symptoms was the perception that symptoms were preventable, meaning that there was the potential to prevent the onset of symptoms and to alter the course of symptoms. This understanding was demonstrated in participants' explanation of symptoms. Participants commented on the cause, prevention, and course of symptoms. Moreover, participants reflected on their experience with symptoms, indicating that symptoms made them feel older than their current age. However, they did not perceive their symptoms as normal or acceptable. CONCLUSION: Participants interpreted knee symptoms as potentially preventable, suggesting that they may be open to primary and secondary prevention strategies.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".