Evidence map›Paper›PMID 40301823›Full record

ArticleBMC medical education2025

Readiness towards artificial intelligence among medical and dental undergraduate students in Peshawar, Pakistan: a cross-sectional survey.

Saman Baseer, Brekhna Jamil, Shehzad Akbar Khan, Musawer Khan, Ambreen Syed, Liaqat Ali

Abstract read
In one paragraph

Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Saman BaseerDepartment of Orthodontics, Sardar Begum Dental College Peshawar, Peshawar, Pakistan. samanbaseer@gmail.com.
Brekhna JamilInstitute of Health Professions Education & Research, KMU Peshawar, Peshawar, Pakistan.
Shehzad Akbar KhanHayatabad Medical Complex Peshawar, Peshawar, Pakistan.
Musawer KhanMardan Medical Complex/ Bacha Khan Medical College, Mardan, Pakistan.
Ambreen SyedHayatabad Medical Complex Peshawar, Peshawar, Pakistan.
Liaqat AliInstitute of Kidney Diseases HMC/KGMC Peshawar, Peshawar, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionArtificial 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.

methodsA 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.

resultsFrom 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.

conclusionThe 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.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelStudents, DentalStudents, MedicalAdultCross-Sectional StudiesEducation, Medical, UndergraduateFemaleHumansMalePakistanSurveys and QuestionnairesYoung AdultArtificial intelligenceReadinessUndergraduate dental studentsUndergraduate medical students

Identifiers

PMID40301823
PMCPMC12042488

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.