Bibliographic record
Abstract
Purpose: Medical education transformed immensely in the past decade and has more recently become increasingly digitized.These changes have been accelerated by COVID-19.However, throughout this modernisation, it is suggested that there is a continued paucity of radiological education. 1 This contrasts with the increased role of radiology in clinical medicine, wherein radiographic investigations are being increasingly utilized as diagnostic, prognostic and monitoring tools. 2 Picture archiving and communication systems (PACS) liberalized access to scans, allowing non-radiologists to interpret scans if required and thus, rely less on full interpretation of the clinical picture. 3 Altogether, increased demands have been placed on radiologists, with 44% reporting burnout in a recent survey and a projected shortage of radiologists in Australia. 3,4 The purpose of this study is to evaluate the perceptions of radiological education and the radiological specialty in medical students.It aims to assess students' views on the quantity and quality of radiological education.Additionally, it will compare whether students find radiological education more effective when delivered face-to-face or when delivered digitally.Finally, it will assess the likelihood of students considering radiology as a future specialty.Methods and Materials: A single-center qualitative cross-sectional study will be carried out at a university in Queensland, Australia.A Likert-style questionnaire will be administered that assesses several domains based on the study aims.De-identified data will be collected utilizing Microsoft Forms and stored securely on password-protected servers.Results: The survey will assess the following domains: the importance of radiological education; the quantity, quality, and preferred modes (face-to-face or digital) of radiological education; confidence in radiological anatomy and interpreting basic imaging modalities; interest in radiology as a specialty.Preliminary qualitative data suggest that medical students are not confident in radiology and feel that benefit would be garnered from further dedicated radiology education.Students find face-to-face education modalities more engaging, but digital modalities are more accessible and easily revisited.There is a moderate level of interest in radiology, with perceived positives including "lifestyle" and perceived barriers including "isolation from patients", and "competitive entry".Conclusion: This study serves as a valuable evaluation of the radiology education received by a cohort of medical students and an assessment of the extent to which students consider radiology as future career.This will be beneficial in ascertaining whether changes in radiology education may be required and highlight approaches that students find valuable, which could be subject to further studies that assess suitability for implementation into a medical curriculum.3.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".