Table 2 Baseline characteristics of included studies
Author (year) [ref] | Country | Study design | Follow Up Duration | Number of Participants | Mean age | Sex (female) | outcomes |
|---|---|---|---|---|---|---|---|
Liu et al. (2022) [52] | The United States | Mixed Methods | - | 390 medical students | 26 ± 3 | Assessment the sight of medical student about involving AI in education | |
McLennan et al. (2022) [53] | Germany | Cross – sectional | - | 844 medical students | 19 (median) | 545 (66.8%) | Assessment the knowledge and sight of medical student about AI and its usefulness, advantages and disadvantages, role in clinical-decision-making, and issues |
Mehta et al. (2021) [23] | Canada | Cross – sectional | - | 321 medical students | - | 201 (63%) | Assessment the knowledge and perception of medical student about AI and its application in education |
Moldt et al. (2023) [19] | Germany | Mixed methods | - | 12 medical students | 24.8 ± 2.0 | 6 (50%) | Assessment the knowledge and attitude of medical student about involving AI technology in education |
Yüzbaşıoğlu et al. (2020) [27] | Turkey | cross-sectional | 1 month | 1103 dental students | 21.36 ± 1.93 | 650 (58.9%) | Assessment the attitude and perception of dental student about Ai and its application in dentistry |
Hassan Mekawy et al. (2020) [34] | Egypt | cross-sectional | 2 months | 128 nursing students | 21.9 ± 1.7 | 77 (60.2%) | Assessment the digital health literacy level of nursing student and its relationship with their perception, attitude toward AI utilization |
Hamd et al. (2023) [25] | United Arab Emirates | cross-sectional | eight-week | 134 including academic staff, clinical dentists, and undergraduate dental students (72) | - | 87 (64.9%) | Assessment the knowledge, attitude, and willingness of dentist/dentistry student and their organization to integrate AI |
Thulasi et al. (2022) [33] | India | cross-sectional | - | 200 dental students and dental practitioners | 26.08 ± 4.13 | 101 (50.5%) | Assessment the knowledge, attitude, and practice of dental student/practitioners toward AI |
Swed et al. (2022) [38] | Syria | cross-sectional | 36 days | 1494 Including 1252 medical students and 255 doctors | 25.5 | 718 (48%) | Predict the knowledge, attitude, and practice of AI taking account baseline characteristic |
Ejaz et al. (2022) [39] | 48 different countries | Original (mixed-methods) | - | 128 medical students | - | 72 (56%) | Assessment the perception of medical student about the role of AI in education |
Buabbas et al. (2023) [37] | Kuwait | Cross-sectional | - | 352 medical students | 22.1 ± 1.8 years | 313 (88.9%) | Assessment the perception of medical student about role of AI in education |
Khanagar et al. (2021) [30] | Saudi Arabia | Cross-sectional | 1 month | 423 dental students | - | 208 (49.2%) | Assessment the knowledge, attitude, and perception of dentistry student toward AI application |
Doumat et al. (2022) [21] | Lebanon | Cross-sectional | - | 206 medical students | 22.7 | 87 (42.2%) | Assessment the knowledge and attitude of medical student about using AI in education |
Ahmed et al. (2022) [22] | Pakistan | cross-sectional | 1 month | 470 individuals including 223 doctors and 247 medical students | 21–30 Median age | 231 (49.1%) | Assessment the knowledge, attitude and practice of medical students/doctors about AI |
Asmatahasin et al. (2021) [32] | India | cross-sectional | - | 270 dental students | 24.6 ± 3.03 | 221 (81.85%) | Assessment the attitude and perception of dental student toward AI utilization in dentistry |
Gaye Keser (2021) [28] | Turkey | cross-sectional | - | 140 (including 75, 4th and 65, 5th grades dental students) | 22.91 ± 1.48 | 85 (60.7%) | Assessment the knowledge, attitude, and perception of dental student toward AI usage in radiological diagnoses |
Nisha Jha (2021) [36] | Nepal | cross-sectional | 24 days | 216 Medical Students | - | 125 (57.9%) | Assessment the knowledge and perception of medical students toward AI and their preference of including AI teaching in study programm |
Rohin Kansal (2022) [31] | India | Cross-Sectional | one week | 212 Medical Students | - | 86 (40.6%) | Assessment the knowledge of medical students/doctors about basic principle, limitation, and application of AI |
Milan Karan-Romero (2023) [35] | Peru | cross-sectional | About one year | 200 dental students | 22 ± 2.87 | 98 (49%) | Assessment the attitudes and perceptions of dentistry student toward AI usage |
Andrés Barreiro-Ares (2323) [29] | Spain | cross-sectional | from 3 January to 31 March 2022 | 283 Medical Students | (22.2 ± 3.5) | 200 (71.17%) | Assessment the perception of undergraduate medical student about current AI situation in medicine and radiology |
Sit (2020) et al | The U.K | Cross-sectional | 484 medical students | - | - | Assessment the attitude of medical student about AI and its role in radiology | |
Dere et.al (2023) | Nigeria | Cross-sectional | 6 weeks | 481 medical students and doctors | - | - | Assessment the knowledge and attitude of the medical students / doctors about AI |