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Resident perspectives on global health imaging in canadian radiology training: A national survey

2025· article· en· W4413117547 on OpenAlex
Marie-Xinyi Sun, Charles-Antoine Boucher, Tharshanna Nadarajah, Ralph Nelson, Karl Muchantef, Joséphine Pressacco

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCurrent Problems in Diagnostic Radiology · 2025
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsMontreal General HospitalCentre de Santé et de Services Sociaux de la MontagneMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMedicinePreparednessDemographicsGlobal healthDeveloping countryTeleradiologyMedical educationHealth careWork (physics)Family medicinePublic healthNursingTelemedicine

Abstract

fetched live from OpenAlex

RATIONALE AND OBJECTIVES: Radiology plays a critical role in healthcare but is marked by stark global inequities. Low- and middle-income countries have far fewer imaging resources and trained personnel compared to high-income countries. As global health interest grows among trainees, understanding Canadian radiology residents' perspectives on global health imaging (GHI) is essential. This study aimed to assess their prior experiences, perceived barriers, and recommendations for integrating GHI into residency training. MATERIALS AND METHODS: A bilingual, anonymous survey was developed and distributed to residents across all 16 Canadian radiology residency programs from May 2024 to April 2025. The questionnaire included items on demographics, prior global health involvement, interest in GHI, perceived preparedness, institutional opportunities, and barriers to international engagement. Respondents were also asked to identify preferred approaches for integrating GHI into training programs. RESULTS: Fifty-one trainees responded from 14 different programs. 64.7% reported prior work in developing countries, with 54.9% perceiving an unmet need for medical imaging in those settings. Nearly half (47.1%) expressed plans to engage in GHI. On-site collaboration and education of local staff (47.1%) and residents (49%) were the most preferred methods of contribution. However, 78.4% felt unprepared or unsure to get involved in GHI. 45.1% reported no GHI opportunities in their current program. Major barriers included call coverage (94.1%), lack of funding (90.2%), and limited infrastructure (90.2%). The top proposed solutions were international electives (86.3%), teleradiology (60.8%), and case presentations focused on diseases highly prevalent in developing countries (51%). CONCLUSION: Canadian radiology trainees show strong interest in global health imaging but face systemic barriers. Curricular integration of electives, teleradiology, and global health education, along with improved access to funding, could bridge the gap between interest and participation.

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.

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)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.051
GPT teacher head0.393
Teacher spread0.343 · 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