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Record W4402463965 · doi:10.1186/s41077-024-00310-6

Reclaiming identities: exploring the influence of simulation on refugee doctors’ workforce integration

2024· article· en· W4402463965 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Simulation · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsDalhousie University
FundersScottish Government
KeywordsWorkforceHealth careRefugeeConceptual modelSociologyMedical educationPublic relationsMedicineComputer sciencePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Healthcare professionals are a precious resource, however, if they fail to integrate into the workforce, they are likely to relocate. Refugee doctors face workforce integration challenges including differences in language and culture, educational background, reduced confidence, and sense of identity. It has been proposed that simulation programmes may have the power to influence workforce integration. This study aimed to explore how an immersive simulation programme influenced workforce integration for refugee doctors joining a new healthcare system. METHODS: Doctors were referred to a six-day immersive simulation programme by a refugee doctor charity. Following the simulation programme, they were invited to participate in the study. Semi-structured interviews, based on the 'pillars' conceptual model of workforce integration, were undertaken. Data were analysed using template analysis, with the workforce integration conceptual model forming the initial coding template. Themes and sub-themes were modified according to the data, and new codes were constructed. Data were presented as an elaborated pillars model, exploring the relationship between simulation and workforce integration. RESULTS: Fourteen doctors participated. The 'learning pillar' comprised communication, culture, clinical skills and knowledge, healthcare systems and assessment, with a new sub-theme of role expectations. The 'connecting pillar' comprised bonds and bridges, which were strengthened by the simulation programme. The 'being pillar' encompassed the reclaiming of the doctor's identity and the formation of a new social identity as an international medical graduate. Simulation opportunities sometimes provided 'building blocks' for the pillars, but at other times opportunities were missed. There was also an example of the simulation programme threatening one of the integration pillars. CONCLUSIONS: Opportunities provided within simulation programmes may help refugee doctors form social connections and aid learning in a variety of domains. Learning, social connections, and skills application in simulation may help doctors to reclaim their professional identities, and forge new identities as international medical graduates. Fundamentally, simulation experiences allow newcomers to understand what is expected of them. These processes are key to successful workforce integration. The simulation community should be curious about the potential of simulation experiences to influence integration, whilst also considering the possibility of unintentional 'othering' between faculty and participants.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.100
GPT teacher head0.493
Teacher spread0.393 · 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