Evidence map›Paper›PMID 41523008›Full record

ArticleJournal of pharmacy & bioallied sciences2025

Evaluating the Effectiveness and Perception of QR Codes as Teaching-Learning Tools in the Department of Medicine for Phase 3 MBBS Students at a Medical College in Central India.

Anurag Kumar Jain, Jitendra Singh Dangi, Mohita Pandey, Maneesh Jain, Talha Saad, Satyendra Mishra

Abstract read
In one paragraph

Article in Journal of pharmacy & bioallied sciences, 2025. 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

6 authors.

Anurag Kumar JainDepartment of Medicine, Bundelkhand Medical College, Sagar, Madhya Pradesh, India.
Jitendra Singh DangiDepartment of Surgery, Government Bundelkhand Medical College, Sagar, Madhya Pradesh, India.
Mohita PandeyDepartment of Obstetrics and Gynecology, Shyam Shah Medical College, Rewa, Madhya Pradesh, India.
Maneesh JainDepartment of Medicine, Bundelkhand Medical College, Sagar, Madhya Pradesh, India.
Talha SaadDepartment of Respiratory Medicine, Bundelkhand Medical College Sagar, Madhya Pradesh, India.
Satyendra MishraDepartment of Respiratory Medicine, Bundelkhand Medical College Sagar, Madhya Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Quick response (QR) codes are emerging as practical tools to supplement clinical teaching by providing instant access to educational content. This study aimed to evaluate the effectiveness and perception of QR codes as teaching-learning (T-L) tools among Phase 3 MBBS students in the Department of Medicine. Methods: A cross-sectional, mixed-method study was conducted among 100 medical students. QR codes linking to videos, clinical guidelines, and case-based content were placed in ward areas. Effectiveness was assessed using a preintervention and postintervention MCQ test (20 items), while perception was measured using a 5-point Likert scale questionnaire and optional feedback. Statistical analysis included paired t-tests and descriptive statistics. Results: The mean pretest score was 10.63 ± 1.91, which improved significantly to 14.03 ± 2.26 in the post-test ( Conclusion: QR codes are effective, low-cost tools that enhance clinical learning and student engagement. They hold promise for scalable integration into undergraduate medical education, especially in resource-limited settings.

Indexed as

Clinical teachingdigital learning toolsmedical educationQR codesundergraduate MBBS

Identifiers

PMID41523008
PMCPMC12788464

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.