Being careful: A grounded theory of emergent chronic knee problems
Bibliographic record
Abstract
OBJECTIVE: To gain insight into the prediagnostic stages of knee osteoarthritis (OA) and identify the process whereby people recognize and address emergent chronic knee problems. METHODS: Twenty-six people (15 women, mean age 53.2 +/- 7.4 years) participated in a grounded theory study. Ten participants had a recent diagnosis of knee OA, and 16 had no diagnosis. The undiagnosed participants self-reported their symptoms, which had lasted at least 6 months and were consistent with knee OA. During semistructured, one-on-one interviews, participants reflected on the development and impact of their chronic knee problems. A constant comparative approach was used for analysis. RESULTS: Participants described uncertainty in understanding the meaning of intermittent knee symptoms for several years before becoming aware of the emergence of chronic knee problems. Once aware, participants engaged in a circular process of interpreting the meaning of knee symptoms and being careful. Being careful referred to the cycle of perceptions, intentions, and behaviors aimed at avoiding knee damage during physical activity. This cycle continued until participants experienced a disruption that challenged their participation in meaningful activities, at which time they decided to access health care. CONCLUSION: As a new construct, being careful unifies the complex set of experiences and behaviors that describe how participants protected their knee during physical activity. Participants interpret the experiences associated with emerging knee problems through interactions with others. These interactions enhance the participants' self-management, despite not having the benefits associated with diagnosis, such as justification for symptoms and formal assistance.
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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 | 0.025 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".