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Record W4389520415 · doi:10.1186/s12909-023-04883-0

Undergraduate oncology education in Sudanese public medical schools; a national cross-sectional study

2023· article· en· W4389520415 on OpenAlexaff
Salma S. Alrawa, Ammar Elgadi, Esraa S. A. Alfadul, Shahd Alshikh, Nazik Hammad, Abdelhafeez H. Abdelhafeez

Bibliographic record

VenueBMC Medical Education · 2023
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineCurriculumCross-sectional studyRadiation oncologyClinical OncologyStratified samplingOncologyInternal medicineFamily medicineMedical educationCancerRadiation therapyPsychologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer was the fifth leading cause of death in Sudan general hospitals in 2020, and its incidence is increasing. Medical students' cancer education is key in cancer control. Evaluating the current education is the first step in optimizing it. The aim of this study was to assess undergraduate oncology education in Sudan public medical schools as reflected by the graduates of the year 2021-2022. METHOD: This was a cross-sectional institution-based study. A validated online questionnaire was sent between 8 September and 11 November 2022 to graduates who were selected using a stratified random sampling technique from 17 Sudan public medical schools. The data were collected using Google Forms and analyzed using R software version 4.2.2 and Microsoft Excel 2022. RESULTS: A total of 707 graduates completed the questionnaire. They reported generally poor exposure to oncology. Palliative and radiation oncology in addition to chemotherapy daycare units were never attended by 76.0%, 72.0%, and 72.0% of graduates, respectively. The massed oncology curriculum was associated with increased hours of lectures dictated to medical (p = 0.005), radiation (p < 0.001), and palliative oncology (0.035). It was associated with an increased likelihood of assessment in breaking bad news (p < 0.001), counseling cancer patients (p = 0.015), and oncology-related knowledge (p < 0.001). The massed curriculum was associated with a decrease in interest in pursuing an oncology career (p = 0.037). Students were generally confident in their oncology competencies, and no difference was observed in relation to the curriculum approach (p > 0.05). CONCLUSION: This study reflected poor exposure to oncology at the undergraduate level in Sudanese public medical schools. The massed oncology curriculum was associated with formal assessment of oncology-related competencies and better exposure to some disciplines, such as radiation and palliative oncology. Nonetheless, it was associated with decreased interest in an oncology career. In spite of the poor exposure, graduates were confident in their skills in oncology-related competencies. Further objective analysis of competence is needed.

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)0.003
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient 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: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.051
GPT teacher head0.511
Teacher spread0.460 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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