E45. A Qualitative Study to Explore Patients’ and Carers’ Views and Expectations about Intensive Treatment for Intermediate Rheumatoid Arthritis
Bibliographic record
Abstract
Background: There have been significant advances in the management of RA in recent decades with the introduction of intensive treatment strategies using a combination of DMARDs and in some cases the addition of biologics (e.g. anti-TNF drugs). Intensive treatment regimens require frequent hospital visits and a high number of medications, however, they have been shown to be effective for highly active RA and patients generally accept the burden of treatment. While intensive treatment is recommended for highly active RA, there is no consensus pathway for patients with less active RA and the acceptability of intensive treatment strategies with less severe disease is unknown. The purpose of this study is to understand the views and expectations of patients with RA receiving standard care who have DAS between 3.2 and 5.1, and of carers of these patients, on intensive treatment. Methods: This study has an exploratory qualitative design using focus groups and semi-structured interviews. Two focus groups took place: involving patients with RA and involving carers of patients with RA. Seven semi-structured interviews were conducted face-to-face or via the telephone (with the exception of patients whose first language is not English who were all interviewed in person with the assistance of a translator). Audio recordings of focus groups and interviews were transcribed and analysed using Framework Analysis. Five main themes were identified including the nature of RA, expectations of intensive management, acceptability of intensive management, continuity of care and patient information.
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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 | 0.022 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".