MétaCan
Menu
Back to cohort

BHPR oral abstracts

2016· article· en· W4255956994 on OpenAlexaff
Holly Hope, Kimme L Hyrich, Suzanne Verstappen, Lis Cordingley, Rachel Ferguson, Michael Backhouse, Lindsay Bearne, Mwidimi Ndosi, Elaine Dennison, Phillip Ainsworth, Alan Roach, Lindsey Cherry

Bibliographic record

VenueLara D. Veeken · 2016
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsArthritis Research Centre of Canada
Fundersnot available
KeywordsMedicineDermatologyTraditional medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.160
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0070.003
Open science0.0020.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.8400.633

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.

Opus teacher head0.021
GPT teacher head0.290
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueLara D. VeekenSame topicRheumatoid Arthritis Research and TherapiesFrench-language works237,207