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Record W4317807271 · doi:10.21203/rs.3.rs-2466798/v1

The role of medical support workers during the Covid-19 pandemic in the National Health Service in the UK: a qualitative service evaluation at the Oxford University Hospitals Foundation Trust

2023· preprint· en· W4317807271 on OpenAlexaff
Samprita Chakma, Wang Hanyu, Mesulame Namedre, Elaine Hill, Mike English, Shobhana Nagraj

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsCentre for Global Health Research
FundersNational Institute for Health and Care ResearchWellcome Trust
KeywordsThematic analysisFocus groupQualitative researchService (business)LicenseMedical educationMedicinePsychologyNursingSociologyPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Abstract Background During the COVID-19 pandemic, the National Health Service (NHS) England created a short-term position known as a Medical Support Worker (MSW), for International Medical Graduates (IMGs) and qualified doctors who had left medicine, to return to medical practice. We conducted a service evaluation of the MSW role at Oxford University Hospitals NHS Foundation Trust (OUHFT), with the aim of understanding how MSWs were perceived and contributed to the NHS, factors driving MSWs’ career choices, the short- and long-term goals of the position, analysing the perspectives of MSWs, their supervisors and recruiters. Methods A qualitative case study approach was adopted. A total of nine semi-structured interviews and two focus group discussions involving 18 participants were conducted with MSWs, their supervisors and recruiters based in OUHFT. A thematic analysis and narrative synthesis of results were conducted. Results Findings were categorised into micro, meso, and macro levels of the health system. At the micro level, MSWs were identified as a diverse group of highly qualified international medical graduates (IMGs) holding a supernumerary role, who contributed their skills during the pandemic. At the meso level, the importance of a comprehensive induction by the hospital was highlighted by all participants, to clarify the job responsibility and familiarise MSWs with the local health system. At the macro level, the role enabled familiarisation and integration of MSWs within the NHS with the aim of obtaining a license to practice as a doctor in the UK. Conclusions This service evaluation highlighted the importance of the role of MSWs during the pandemic. The MSW scheme could be a pathway for IMGs to integrate into the NHS and fill workforce shortages. This study has the potential to inform the NHS long-term policy on the role of MSWs and the integration of IMGs into the workforce.

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)0.032
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.009
Scholarly communication0.0050.003
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.310
GPT teacher head0.602
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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