Evidence map›Paper›PMID 39349864›Full record

ArticleJournal of cancer education : the official journal of the American Association for Cancer Education2025

A Survey of Perspectives and Educational Needs of Canadian Oncology Residents on Artificial Intelligence.

Fernanda M Favorito, Laura Collie, Thomas Kennedy, Jacqueline J Nabhen, Amir Safavi, Giovanni G Cerri, Wilma Hopman, Fábio Y Moraes

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In one paragraph

Article in Journal of cancer education : the official journal of the American Association for Cancer Education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Fernanda M FavoritoFaculdade de Ciências Médicas da Santa Casa de São Paulo, São Paulo, Brazil.ORCID 0009-0006-7369-5183
Laura CollieQueen's University, Kingston, ON, Canada. laura.collie@kingstonhsc.ca.
Thomas KennedyQueen's University, Kingston, ON, Canada.ORCID 0000-0002-1603-8121
Jacqueline J NabhenUniversidade Federal Do Paraná (UFPR), Curitiba, Brazil.ORCID 0000-0001-5655-6719
Amir SafaviUniversity of Toronto, Toronto, ON, Canada.ORCID 0000-0001-6106-1374
Giovanni G CerriUniversity of São Paulo (USP), São Paulo, Brazil.ORCID 0000-0002-6707-8721
Wilma HopmanQueen's University, Kingston, ON, Canada.ORCID 0000-0002-3023-0080
Fábio Y MoraesQueen's University, Kingston, ON, Canada. fabio.ynoedemoraes@kingstonhsc.ca.ORCID 0000-0003-3407-9215

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study evaluated the perspectives and educational needs of Canadian oncology residents with regard to artificial intelligence (AI) in medicine, exploring the influence of factors such as program of choice, gender, and tech literacy on their attitudes towards AI. An ethics-approved survey collected anonymous responses from Canadian oncology residents from December 2022 to July 2023. Comparisons by demographics were made using Chi-square and Mann-Whitney U tests. A total of 57 residents and fellows responded out of an expected 182, with representation from each oncology training program in Canada. Over half of the participants were male (63.2%), with radiation oncology programs being better represented than medical oncology programs (68.4% vs. 31.6%). There was balanced representation across all years of training. Most trainees (73%) were interested in learning more about AI, and many believed the topic should be formally taught during residency (63%), preferably through workshops (79%). Among evaluated factors, tech literacy showed the most impact over AI perspectives, driving a perception shift towards viewing AI as an improvement tool, rather than as a threat to professionals. In conclusion, Canadian oncology residents anticipate AI's growing influence in medicine but face educational deficiencies. Gender, oncology discipline, and self-reported tech literacy impact attitudes toward AI, highlighting the need for inclusive education.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelInternship and ResidencyMedical OncologyNeeds AssessmentAdultCanadaFemaleHumansMaleSurveys and QuestionnairesArtificial intelligenceAttitude to technologyMedical educationOncologyResidents

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.