BHPR oral abstracts
Bibliographic record
Abstract
Background: MTX is the recommended first-line treatment for RA.Treatment response to this drug is not universal and nonadherence may partially explain this.The extended Common-Sense Self-Regulatory Model of Illness (CS-SRM) is increasingly used in rheumatology because it helps to explain variations in outcome by highlighting relationships between people's beliefs about their condition and treatments and their coping responses, such as intentional non-adherence.The Perceptions and Practicalities Model (PPM) of adherence further recognizes that patient barriers to adherence need to be addressed in order for optimal medicine adherence to occur.Therefore the rheumatologist has a key role in shaping patients' illness and treatment beliefs and identifying possible barriers, but very little is known about how rheumatologists address these issues in routine practice.This qualitative study aimed to explore UK rheumatologists' experiences and practice when commencing MTX with new patients.Methods: In-depth one-to-one semi-structured telephone interviews were conducted with 15 rheumatologists who prescribe MTX for RA.The sampling strategy ensured collection of data from new and experienced clinicians working in university and district general hospitals.The interview topic guide included rheumatologists' perceptions of RA, MTX and their role in management of the disease; factors influencing MTX use (e.g.patient alcohol use, family planning) and the information provided to patients.Data were analyzed using principles of framework analysis in which key concepts from CS-SRM and PPM were used to identify clinicians' beliefs and strategies.Results: Rheumatologists perceived MTX as their preferred first-line treatment for RA, however, they described a range of psychological, clinical and practical barriers to effective MTX adherence.Patient focused barriers included information overload, emotional preparedness for treatment and patients' understanding of RA.Rheumatologists provided a range of strategies used to address or minimize barriers.Strategies for less-prepared patients included delaying MTX commencement, referring for nurse-led 'education' or counselling.Strategies to improve patients' understanding of the rationale for MTX included the use of disease-related metaphors.Rheumatologists' responses to diagnostic uncertainty included selection of an alternative DMARD.Conclusion: Through in-depth qualitative study of rheumatologists' experiences in prescribing MTX, a number of new issues were identified that may impact clinical practice.The results suggest the manner and timing of information delivery about MTX affect patient beliefs and adherence intentions.These findings will inform an online survey to further explore the association between rheumatologists' beliefs and strategies in the management of RA with MTX.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.840 | 0.633 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".