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Record W2207311901 · doi:10.1093/occmed/kqv208

Fit for work? Evaluation of a workshop for rheumatology teams

2015· article· en· W2207311901 on OpenAlexaboutno aff
Debbie L. Cohen, Sayeed Khan, Naomi Marfell

Bibliographic record

VenueOccupational Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsRheumatoid arthritisRheumatologyMedicineWork (physics)Quarter (Canadian coin)Physical therapyInternal medicineFamily medicineEngineeringGeography

Abstract

fetched live from OpenAlex

BACKGROUND: People with rheumatoid arthritis (RA) may rapidly cease work prematurely due to ill-health. A recent survey noted that a quarter of respondents with RA experienced job loss within a year of diagnosis and 50% stopped work within 6 years. AIMS: To develop and pilot workshops to increase the knowledge, skills and confidence of rheumatology team members to support work-related issues in outpatient clinics. METHODS: A 3-h interactive workshop, informed by rheumatology experts and the Royal College of General Practitioners (RCGP) National Education Programme (NEP) about work and health, was developed to address both knowledge and skills in the management of health and work consultations in an outpatient setting. Questionnaires were developed for use pre- and immediately post-workshop, with questions that focused on the confidence of delegates in managing these discussions and the importance they placed upon them. RESULTS: Ninety-nine participants attended five workshops throughout the UK between 2013 and 2104. Seventy-three per cent (72) completed the post-workshop questionnaire. Eighty-nine per cent found the workshop useful or very useful, 88% found it relevant or very relevant and 79% responded that it had an impact or a considerable impact on their practice. Wilcoxon matched pairs signed rank tests were carried out that showed an overall increase in confidence after training. CONCLUSIONS: The results suggest that the workshop was both relevant and useful to participants and had an impact on their practice. This was true for all specialities. The workshops also highlighted participants' desire to understand how to use the 'fit note' to enhance their patient management.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.185
GPT teacher head0.437
Teacher spread0.252 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations2
Published2015
Admission routes1
Has abstractyes

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