Qualitative Research in Rheumatology: An Overview of Methods and Contributions to Practice and Policy
Bibliographic record
Abstract
Patient-centered care is widely advocated in rheumatology. This involves collaboration among patients, caregivers, and health professionals and is particularly important in chronic rheumatic conditions because the disease and treatment can impair patients' health and well-being. Qualitative research can systematically generate insights about people's experiences, beliefs, and attitudes, which patients may not always express in clinical settings. These insights can address complex and challenging areas in rheumatology, such as treatment adherence and transition to adult healthcare services. Despite this, qualitative research comprises 1% of studies published in top-tier rheumatology journals. A better understanding about the effect and role, methods, and rigor of qualitative research is needed. This overview highlights the recent contributions of qualitative research in rheumatology, summarizes the common approaches and methods used, and outlines the key principles to guide appraisal of qualitative studies.
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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 | 0.188 | 0.130 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.016 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".