Evidence map›Paper›PMID 42488878›Full record

ReviewNigerian medical journal : journal of the Nigeria Medical Association

Awareness, Perceptions, and Concerns among medical students regarding Artificial Intelligence integration in Healthcare: A Comprehensive Analysis.

Sonali Sharma, Smriti Kayat, Neha Saboo, Vaseem Naheed Baig

Abstract readReview
In one paragraph

Review in Nigerian medical journal : journal of the Nigeria Medical Association. 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.

Sonali SharmaDepartment of Biochemistry, RUHS College of Medical Sciences, Jaipur, Pratap Nagar, Jaipur, Rajasthan, India.
Smriti KayatDepartment of Biochemistry, RUHS College of Medical Sciences, Jaipur, Pratap Nagar, Jaipur, Rajasthan, India.
Neha SabooDepartment of Physiology, RUHS College of Medical Sciences, Jaipur, Rajasthan, India.
Vaseem Naheed BaigDepartment of Community Medicine, RUHS College of Medical Sciences, Jaipur, Pratap Nagar, Jaipur, Rajasthan, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) is increasingly integrated into healthcare, creating a demand for AI technology literacy among healthcare professionals. This study aimed to investigate undergraduate medical students' awareness, concerns, and perceptions of AI in healthcare. Methodology: This cross-sectional study was conducted on 356 undergraduate medical students at a constituent medical college of a health university in India. Data were collected using various sections of a structured questionnaire (Google Forms). The questionnaire was validated to ensure its authenticity and alignment with the study's aim. To assess reliability and readability, a pilot study was conducted. Before the study, ethical approval was obtained, and each participant gave their informed consent. SPSS-26 was used to analyze the data. Results: There was a 41.88% valid response rate, but the overall response rate 45.05%, and a fairly balanced distribution of sexes. Across AI domains, combined awareness ranged from 48.6% to 58.1%, whereas combined disagreement ranged from 22.8% to 32.9%. Most students did not receive formal training in AI. The major concerns noted were job security (43.8%), patient data privacy (47.2%), and errors in medical diagnosis and treatment (44.1%). However, 53.8% of the students perceived AI as a valuable tool for improving healthcare delivery and patient outcomes. Conclusion: Undergraduate medical students show moderate awareness of AI in healthcare but lack formal training and in-depth understanding. Concerns persist regarding ethics, job displacement, loss of empathy, and clinical errors, despite recognition of AI's potential to improve healthcare outcomes. These findings highlight the need for structured AI education within medical curricula and further research on its long-term impact.

Indexed as

artificial intelligenceawarenesseducationHealthcaremedicalquestionnaires

Identifiers

PMID42488878
PMCPMC13391099

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.