Readiness towards artificial intelligence among medical and dental undergraduate students in Peshawar, Pakistan: a cross-sectional survey
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| Publicado en: | BMC Medical Education vol. 25 (2025), p. 1 |
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| Otros Autores: | , , , , |
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Springer Nature B.V.
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3201523402 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1472-6920 | ||
| 024 | 7 | |a 10.1186/s12909-025-06911-7 |2 doi | |
| 035 | |a 3201523402 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 58506 |2 nlm | ||
| 100 | 1 | |a Baseer, Saman | |
| 245 | 1 | |a Readiness towards artificial intelligence among medical and dental undergraduate students in Peshawar, Pakistan: a cross-sectional survey | |
| 260 | |b Springer Nature B.V. |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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 numberNot Applicable. | |
| 610 | 4 | |a Khyber Medical College | |
| 651 | 4 | |a Peshawar Pakistan | |
| 651 | 4 | |a Pakistan | |
| 653 | |a Gender | ||
| 653 | |a Questionnaires | ||
| 653 | |a Medical students | ||
| 653 | |a Colleges & universities | ||
| 653 | |a Medical schools | ||
| 653 | |a Sample size | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Knowledge | ||
| 653 | |a Response rates | ||
| 653 | |a Data collection | ||
| 653 | |a Professionals | ||
| 653 | |a Dentistry | ||
| 653 | |a Females | ||
| 653 | |a Males | ||
| 653 | |a Undergraduate Students | ||
| 653 | |a Sampling | ||
| 653 | |a Influence of Technology | ||
| 653 | |a Graduate Students | ||
| 653 | |a School Demography | ||
| 653 | |a Response Rates (Questionnaires) | ||
| 653 | |a Statistical Significance | ||
| 653 | |a Medical Education | ||
| 653 | |a Educational Technology | ||
| 653 | |a Dental Schools | ||
| 653 | |a Feedback (Response) | ||
| 653 | |a Student Surveys | ||
| 653 | |a Data Analysis | ||
| 653 | |a Student Participation | ||
| 653 | |a Dental Evaluation | ||
| 653 | |a Statistical Analysis | ||
| 653 | |a Validated Programs | ||
| 653 | |a Statistical Data | ||
| 700 | 1 | |a Brekhna Jamil | |
| 700 | 1 | |a Shehzad Akbar Khan | |
| 700 | 1 | |a Khan, Musawer | |
| 700 | 1 | |a Syed, Ambreen | |
| 700 | 1 | |a Ali, Liaqat | |
| 773 | 0 | |t BMC Medical Education |g vol. 25 (2025), p. 1 | |
| 786 | 0 | |d ProQuest |t Healthcare Administration Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3201523402/abstract/embedded/WAQKWGCDE3OCLOOD?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3201523402/fulltext/embedded/WAQKWGCDE3OCLOOD?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3201523402/fulltextPDF/embedded/WAQKWGCDE3OCLOOD?source=fedsrch |