Content area

Abstract

Introduction

Artificial intelligence is a transformative tool for improving healthcare delivery and diagnostic accuracy in the medical and dental fields. This study aims to assess the readiness of future healthcare workers for artificial intelligence and address this gap by examining students’ perceptions, attitudes, and knowledge related to AI in Peshawar, Pakistan.

Methods

A quantitative cross-sectional survey was conducted on 423 students from randomly chosen medical and dental colleges. The Medical AI Readiness Scale (MAIRS-MS) was used to perform a self-administered online questionnaire that was used to gather data. Using SPSS software, descriptive statistics and chi-square tests were used to evaluate the data. The level of significance was set at p ≤ 0.05.

Results

From multiple medical and dental colleges, 407 students participated in this survey. The survey showed that 29.7% of students had low, 62.2% had moderate, and only 8.1% had high readiness levels. Most medical and dental students in Peshawar, Pakistan, showed moderate readiness. There were significant gender discrepancies, showing males dominating females in readiness scores. There were only slight differences in the AI readiness scores and the academic years from the 1st to 5th year. Only a few non-Pakistani students responded, which may hinder conclusive determinations regarding national disparities.

Conclusion

The study revealed moderate AI readiness among participants, with significant gender disparities favouring males. Overall, there were no significant differences between dentistry and medical fields. In-depth analysis by domain and knowledge areas might uncover further distinctions.

Clinical trial number

Not Applicable.

Details

1009240
Company / organization
Title
Readiness towards artificial intelligence among medical and dental undergraduate students in Peshawar, Pakistan: a cross-sectional survey
Publication title
Volume
25
Pages
1-10
Publication year
2025
Publication date
2025
Section
Research
Publisher
Springer Nature B.V.
Place of publication
London
Country of publication
Netherlands
e-ISSN
14726920
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-04-29
Milestone dates
2024-11-26 (Received); 2025-02-21 (Accepted); 2025-04-29 (Published)
Publication history
 
 
   First posting date
29 Apr 2025
ProQuest document ID
3201523402
Document URL
https://www.proquest.com/scholarly-journals/readiness-towards-artificial-intelligence-among/docview/3201523402/se-2?accountid=208611
Copyright
© 2025. This work is licensed under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-05-09
Database
ProQuest One Academic