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Record W3149474227 · doi:10.1093/occmed/kqab037

Creating a return to work Medical Readers’ Theatre

2021· article· en· W3149474227 on OpenAlexaffabout
Boon Kek, W. A. C. Stewart, Anil Adisesh

Bibliographic record

VenueOccupational Medicine · 2021
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversity of TorontoSt. Michael's HospitalUniversity of New BrunswickSaint John Regional Hospital
FundersWorkSafe Victoria
KeywordsWork (physics)NegotiationPerceptionMedical educationPsychologyPublic relationsMedicineSociologyPolitical scienceEngineeringSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Previous work on sickness absence has shown that conversations about return to work can be challenging. The perception of competing interests and multiple stakeholders in the return to work process may also complicate and erode trust, further impacting health and well-being. AIMS: This study aims to explore the themes arising from the experiences of physicians and patients on the impact of health and return to work. The goal was to use these results to develop a Medical Readers' Theatre workshop focusing on negotiating challenging return to work scenarios to serve as an educational support for stakeholders. METHODS: Semi-structured interviews were conducted with 19 physicians and 15 patients from the Canadian Maritime Provinces on their experiences in return to work following an injury or illness. Interviews were recorded, transcribed and thematically analysed. Using the emergent themes, an educational workshop in the modality of Readers' Theatre was developed. RESULTS: The findings confirm there are multiple stakeholders involved in the return to work process and the factors influencing successful return are not always medically related. Six recurring themes were identified for the patient group and five for the physicians', allowing the development of storylines and four return to work scenarios. The scenarios have been used in teaching sessions. CONCLUSIONS: The themes reinforced that challenges in return to work are not always medical in nature. This Readers' Theatre adopts perspectives of patients, physicians and other stakeholders whilst focusing on return to work with the goal of providing engagement in reflective and purposeful discussion.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.632
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.001

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.

Opus teacher head0.056
GPT teacher head0.432
Teacher spread0.377 · 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.

Study designObservational
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

Citations3
Published2021
Admission routes2
Has abstractyes

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