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Record W4318820383 · doi:10.52589/ajhnm-q0zplgvs

Time to Consider the Introduction of Mandatory Continuous Professional Development Training Programme for Registered Healthcare Workers Especially Nurses and Midwives in Sierra Leone

2023· article· en· W4318820383 on OpenAlexaboutno aff
Ibrahim Momoh, Rogers M.K.K.

Bibliographic record

VenueAfrican Journal of Health Nursing and Midwifery · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsSierra leoneStatutory lawGovernment (linguistics)Health careProfessional developmentWork (physics)NursingHealth professionalsTraining (meteorology)MedicineMedical educationPolitical scienceLawSociology

Abstract

fetched live from OpenAlex

In developed countries like Australia, Canada, UK and USA, continuous professional development (CPD) is statutory or mandatory training for all regulated healthcare staff such as doctors, midwives, nurses, pharmacists and physiotherapists. All patients facing healthcare professionals are expected to attend stipulated programs of learning some with annual recall. These trainings are compulsory to attend. Staff employers would be in breach of statutory laws or regulatory requirements if they employ or allow staff to work with expired CPD competencies. In a low- or middle-income country (LMIC) like Sierra Leone, CPD is currently selective, and voluntary and registration licences are not revalidated. This can invariably put patients at risk as clinical skills/knowledge are not regularly verified. This paper discusses the rationale for the Government of Sierra Leone (GoSL) to consider introducing mandatory CPD training programmes, especially for nurses and midwives employed in healthcare settings in the country.

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)0.005
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.612
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.116
GPT teacher head0.435
Teacher spread0.319 · 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 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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