Evidence map›Paper›PMID 42291586›Full record

ArticlePakistan journal of medical sciences2026

Beyond Red Pen: Comparing the machine vs human grading of reflective assignments on clinical reasoning in Dermatology undergraduate students.

Lubna Rani Faysal, Shabana Ali, Mahwish Aftab Khan, Humaira Fayyaz Khan

Abstract read
In one paragraph

Article in Pakistan journal of medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Lubna Rani FaysalLubna Rani Faysal, Department of Dermatology, Faculty of Medicine and Health Sciences, Riphah International University, Islamabad, Pakistan.
Shabana AliShabana Ali, Department of Anatomy, Faculty of Medicine and Health Sciences, Riphah International University, Islamabad, Pakistan.
Mahwish Aftab KhanMahwish Aftab Khan, Department of Dermatology, Faculty of Medicine and Health Sciences, Shaheed Zulfiqar Ali Medical University, Islamabad, Pakistan.
Humaira Fayyaz KhanHumaira Fayyaz Khan, Department of Physiology, Faculty of Medicine and Health Sciences, Riphah International University, Islamabad, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: The integration of Artificial Intelligence (AI) into medical education has been a significant advancement in recent years. AI-based tools like ChatGPT offer numerous advantages for teaching and student assessment. The objective of this study was to evaluate the effectiveness of ChatGPT in assessing reflective assignments compared to human grading. Methodology: This quasi-experimental study was conducted at Islamic International Medical College from December 2024 to March 2025. In this study a total of 120 3 Results: It Conclusion: ChatGPT serves as a valuable and reliable complement to human assessment, significantly improving grading efficiency, particularly in large-scale evaluations.

Indexed as

AI in medical EducationClinical ReasoningGibbs’ Reflective CycleManual vs Automated ScoringReflective Writing

Identifiers

PMID42291586
PMCPMC13263582

What OpenQuestion holds

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LicenceCC BY
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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.