Evidence map›Paper›PMID 40761605›Full record

ArticleHealth science reports2025

Medical and Paramedical Students' Perspectives on Artificial Intelligence in a Low- and Middle-Income Country: A Cross-Sectional Study.

Seyyedeh Fatemeh Mousavi Baigi, Masoumeh Sarbaz, Ali Darroudi, Khalil Kimiafar

Abstract read
In one paragraph

Article in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  4. Observational
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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.

Seyyedeh Fatemeh Mousavi BaigiDepartment of Health Information Technology School of Paramedical and Rehabilitation Sciences Mashhad Iran.ORCID https://orcid.org/0000-0002-2214-0077
Masoumeh SarbazDepartment of Health Information Technology School of Paramedical and Rehabilitation Sciences Mashhad Iran.ORCID https://orcid.org/0000-0001-5456-8505
Ali DarroudiDepartment of Health Information Technology School of Paramedical and Rehabilitation Sciences Mashhad Iran.ORCID https://orcid.org/0000-0002-1971-8659
Khalil KimiafarDepartment of Health Information Technology School of Paramedical and Rehabilitation Sciences Mashhad Iran.ORCID https://orcid.org/0000-0003-0351-4675

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study aimed to investigate the attitude of medical and paramedical students at Mashhad (Northeast of Iran) regarding artificial intelligence (AI). Methods: This cross-sectional study was conducted from April to June 2023. A predeveloped standard questionnaire was used to collect the data. We used the proportional per-size sampling method with email distribution containing explanations and a link to a web-based survey. Results: A total of 208 students answered the survey (response rate: 98%). We did not find any significant difference between the AI attitude of students in the academic field ( Conclusion: This study explored medical and paramedical students' perceived understanding of AI and their conceptual limitations. Identifying the positive and negative attitudes of students who are the future employees of the healthcare system can help planners and policymakers in the field of AI in health design the road map of the future of AI in health in the best way.

Indexed as

AIartificial intelligenceattitudemedical studentparamedical studentsperspectives

Identifiers

PMID40761605
PMCPMC12320132

What OpenQuestion holds

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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.