Medical Students’ Career Perceptions of Radiology
Bibliographic record
Abstract
ABSTRACT Objective: Understanding and identifying the factors that influence third- and fourth-year medical students’ perceptions of radiology at Memorial University of Newfoundland and Labrador aims to inform future initiatives in medical education and workforce strategies. Methods: Third- and fourth-year medical students at Memorial University of Newfoundland and Labrador participated in a voluntary and anonymous online survey consisting of 17 questions. The survey was distributed through the Office of Learner Well-Being and Success at the Faculty of Medicine and remained open for three months. It included a mix of closed-ended and open-ended questions, with responses to closed-ended questions provided on a slider scale. The aim of the survey was to gather insights into students' perceptions of radiology within the medical school curriculum. Data analysis was conducted using the Qualtrics online survey platform and statistical analyses were performed using Microsoft Excel. Results/Discussion: Of the 160 medical students surveyed, 25 responded (15.6%). Sixteen percent of the respondents expressed an interest in pursuing radiology. The majority (56.00%) found the exposure to radiology from pre-clerkship to clerkship to be inadequate. According to the slider scale data, on average, respondents ranked "quality of family life" highest (8.52) in influencing their perception of clinical radiology as a career, followed by "amount of patient contact" (7.83) and "suitability to skills/aptitude" (7.33). Students recommended interactive radiological lectures and shadowing opportunities to enhance their learning experience. Conclusion: This survey reveals that factors influencing medical students' views on a career in radiology at Memorial University of Newfoundland and Labrador are multifactorial. The majority's perception of inadequate exposure to radiology could impact efforts to refine the medical school curriculum and develop broader workforce strategies aimed at attracting more students to the field.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".