Evidence map›Paper›PMID 41388003›Full record

ArticleScientific reports2025

Pharm D student's Knowledge, perception, and practice of CHAT-GPT in clinical training: a web-based cross-sectional survey in India.

Vigneshwaran Easwaran, Khalid Orayj, Bhavana Reddy Bommireddy, Mohammad Jaffar Sadiq Mantargi, Mohammed Asif Mulla, Durga Prasad Thammisetty, Sri Ramachandra Magham, Vishnuvandana Bandaru, Pradeepkumar Bhupalam, Narayana Goruntla

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

10 authors.

Vigneshwaran EaswaranDepartment of Clinical Pharmacy, College of Pharmacy, King Khalid University, Abha, 61421, Kingdom of Saudi Arabia.
Khalid OrayjDepartment of Clinical Pharmacy, College of Pharmacy, King Khalid University, Abha, 61421, Kingdom of Saudi Arabia.
Bhavana Reddy BommireddyDepartment of Pharmacy Practice, Raghavendra Institute of Pharmaceutical Education and Research (RIPER) - Autonomous, Anantapur, Andhra Pradesh, India.
Mohammad Jaffar Sadiq MantargiDepartment of Pharmaceutical Sciences, Pharmacy Program, Batterjee Medical College, Jeddah, 21442, Saudi Arabia.
Mohammed Asif MullaDepartment of Pharmacy Practice, Balaji College of Pharmacy, Anantapur, Andhra Pradesh, India.
Durga Prasad ThammisettyDepartment of Pharmacy Practice, Sri Padmavathi School of Pharmacy - Autonomous, Tiruchanoor, Tirupathi, Andhra Pradesh, India.
Sri Ramachandra MaghamDepartment of Pharmacology, Dr. K.V. Subba Reddy Institute of Pharmacy, Kurnool, Andhra Pradesh, India.
Vishnuvandana BandaruDepartment of Pharmaceutical Analysis, Balaji College of Pharmacy, Anantapur, Andhra Pradesh, India.
Pradeepkumar BhupalamDepartment of Pharmacology, Balaji College of Pharmacy, Anantapur, Andhra Pradesh, India.
Narayana GoruntlaDepartment of Clinical Pharmacy and Pharmacy Practice, School of Pharmacy, Kampala International University, Western Campus, Ishaka, Uganda. drgoruntla@kiu.ac.ug.

Funding

The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Small Research Project under grant number RGP1/78/46 RGP1/78/46
6 · The paper itself

Abstract

The emergence of Large Language Models (LLMs) like ChatGPT captured significant attention in healthcare and pharmacy education, yet their real applicability and validity require extensive investigation in practice. Our study aimed to assess Pharm-D students’ knowledge, perceptions, and practices (KPP) toward ChatGPT in clinical pharmacy practice training in India. A nationwide, web-based, cross-sectional survey was conducted between June and September 2025 to assess KPP towards ChatGPT use among PharmD students. A self-administered, pre-designed, and validated questionnaire was utilized to collect demographics, educational profiles, and KPP toward ChatGPT use in clinical training. We used social media platforms and Messenger applications and approached professional groups to recruit the study participants by using the snowball sampling technique. A chi-square test was applied to elucidate factors associated with KPP of ChatGPT use in the clinical training. The two-tailed P-value less than 0.05 was considered as a statistically significant value. In our study, the majority (> 90%) of the PharmD students answered all basic knowledge questions about ChatGPT, except the source of ChatGPT’s knowledge. The majority (85.8%) perceived that they indeed benefited from the use of ChatGPT in their training; the agreement levels for benefits varies across different activities. Regarding concerns, ChatGPT use can reduce the interaction with mentors (74.4%), increase the similarity index/AI detection score (64.1%), and increase the risk of inaccurate or misleading information (66.1%), ethical issues (63.3%), and limited applicability (61.0%). The use of ChatGPT in the selection of medicine and calculation of dose was low compared with other clinical pharmacy activities. Variables such as previous experience using AI tools and prior training on AI tool use were significantly associated with greater practice of ChatGPT. Conversely, the perceived benefits of ChatGPT were significantly positively associated with students who had completed internships (P = 0.019) and had received prior training (P = 0.022) on AI tools. There was a significant positive weak correlation between knowledge and perceived concerns (r = 0.177; P < 0.001), and moderate positive correlation between perceived benefits and practices of the participants (r = 0.377; P < 0.001) towards ChatGPT use. Perceived concerns (r = -0.126; P < 0.012) were significantly negatively weakly correlated with ChatGPT use practices in clinical training. Majority of the PharmD students have good knowledge about ChatGPT, and positive perception towards ChatGPT benefits in clinical training. However, the practice was limited to certain activities due to concerns about accuracy, ethics, and reduced mentor interaction upon use of ChatGPT. Prior experience and training were significantly associated with high practice and positive attitudes. The study recommends to integrate AI tool use and application in pharmacy curriculum and train the faculty to promote competent and responsible use of ChatGPT in clinical pharmacy practice. Students must validate the information from the standard resources or interacting with mentors to deal with misleading information generated by AI tools.

Indexed as

Education, PharmacyHealth Knowledge, Attitudes, PracticeStudents, PharmacyAdultCross-Sectional StudiesFemaleGenerative Artificial IntelligenceHumansIndiaInternetLarge Language ModelsMaleSurveys and QuestionnairesYoung AdultArtificial intelligenceChatGPTClinical trainingIndiaKnowledgePerceptionPharm d studentsPractice

Identifiers

PMID41388003
PMCPMC12800338

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.