Why Do People Delay Accessing Health Care for Knee Osteoarthritis? Exploring Beliefs of Health Professionals and Lay People
Bibliographic record
Abstract
PURPOSE: In knee osteoarthritis (OA), opportunity for non-surgical intervention is reduced by time lost between symptom onset and diagnosis. The study's purpose was to understand, from the perspective of various stakeholders, the reasons for delay and useful strategies to enhance early awareness of knee OA. METHOD: In this qualitative study, focus groups of health professionals (n=6) and community-dwelling individuals (n=7) discussed questions relating to knowledge, attitudes, and beliefs about OA; experiences with people with OA; health care seeking behaviour; and access to services, and suggested strategies to enhance public awareness. Qualitative analyses identified dominant themes. RESULTS: Reasons for delay from the laypersons' perspective included lack of knowledge about risk factors and prevention and a belief that knee pain is expected with age. Reasons related to the health care system included long wait times and frustration getting appointments. Health professionals were unclear on which discipline should discuss prevention and risk factors. Suggested strategies included advocating a healthy lifestyle, developing prevention programs, and using celebrities to inform the public. CONCLUSIONS: Participants identified multiple reasons for delays and strategies to counter them. Knowledge about gaps in the OA care process can facilitate physiotherapists' participation in developing strategies for early intervention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".