Evidence map›Paper›PMID 41938740›Full record

ArticlePerspectives on medical education2026

Whose Voice is it Anyway?

Jessica Maher, Anna Byszewski, Heather Lochnan

Abstract read
In one paragraph

Article in Perspectives on medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Jessica MaherFaculty of Medicine, University of Ottawa, Canada.ORCID 0009-0005-0761-1183
Anna ByszewskiFaculty of Medicine, University of Ottawa, Canada.ORCID 0000-0003-1339-6326
Heather LochnanFaculty of Medicine, University of Ottawa, Canada.ORCID 0000-0002-3820-7897

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Generative artificial intelligence (AI) has entered the spaces of reflection and narrative learning in medical education, spaces once defined by authenticity, introspection, and human voice. This Eye Opener examines tensions identified through a recent survey of undergraduate medical students and their ePortfolio physician coaches at the University of Ottawa regarding the use of AI in reflective writing. While the student response rate was notably lower (9.6%) than that of coaches (52.9%), this asymmetry prompted consideration of how the evaluative context of reflective writing may influence disclosure of AI use in voluntary surveys. Students who did respond described AI as a scaffold for idea generation and writing support, whereas coaches expressed unease, perceiving even limited AI use as a potential threat to authenticity. The resulting tension between pragmatism and preservation mirrors broader questions in medical education regarding reflective authorship and independent critical thinking. This moment invites reconsideration of reflection not solely as a written product but as a developmental process. Educators may need to move beyond detection toward dialogue that supports psychological safety, transparency, and shared understanding of authorship in the age of digitally assisted writing. Reflection has long been understood as a means of engaging with professional identity formation. The challenge now is determining how this process can remain meaningful as generative tools become increasingly embedded in learners' academic work.

Indexed as

Artificial IntelligenceEducation, MedicalStudents, MedicalCognitive ReflectionGenerative Artificial IntelligenceHumansSurveys and QuestionnairesWriting

Identifiers

PMID41938740
PMCPMC13045798

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.