Barriers to Resident Research in Radiology: A Canadian Perspective
Bibliographic record
Abstract
PURPOSE: The study sought to identify and characterise barriers to research for Canadian diagnostic radiology residents and suggest potential solutions to enhance future research success. METHODS: Institutional research board approval was obtained. Electronic surveys were solicited from all postgraduate year 2-5 diagnostic radiology residents at all 16 programs across Canada. The survey focused on key factors inhibiting research during training. RESULTS: Of all 400 Canadian diagnostic radiology residents, 88 (22%) responded. Of respondents, 86% reported research experience before residency, with 19% holding a nonphysician graduate degree. All indicated that research was a requirement for completion of their residency. The most important reported factors limiting resident research were time constraints (67%), personal disinterest (32%), and inadequate mentorship (32%). Although 44% reported dedicated residency program research training, 40% reported no such opportunities. Among the various time constraints, respondents cited studying demands (61%), on-call demands (52%), and daily clinical duties (38%) as strong or significant barriers to research. Most (63%) indicated their program provided at least some protected research time, but 21% were not aware of such protected time availability. When available, protected research time was modest, and ranged from 0.5 days/month to 3 months, with the majority of respondents citing 1 month of protected research time. CONCLUSIONS: Diagnostic radiology residents in Canada report numerous barriers to research. Programs seeking to enhance radiology research should focus on providing appropriate training, protected time, and mentorship.
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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 | 0.018 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".