Table 1 Characteristics of included participants
Total (n = 466) | Students (n = 177) | Interns & Residents (n = 234) | Fellows & Beyond (n = 55) | p-value | |
|---|---|---|---|---|---|
Gender | 0.299 | ||||
Female | 228 (48.9%) | 92 (52.0%) | 114 (48.7%) | 22 (40.0%) | |
Male | 238 (51.1%) | 85 (48.0%) | 120 (51.3%) | 33 (60.0%) | |
Publication status | < 0.001 | ||||
Zero | 251 (53.9%) | 143 (80.8%) | 96 (41.0%) | 12 (21.8%) | |
≥ 1 | 215 (46.1%) | 34 (19.2%) | 138 (59.0%) | 43 (78.2%) | |
Current institution | < 0.001 | ||||
KHCC | 24 (5.2%) | 4 (2.3%) | 9 (3.8%) | 11 (20.0%) | |
Private sector | 72 (15.5%) | 0 (0.0%) | 50 (21.4%) | 22 (40.0%) | |
Public sector | 42 (9.0%) | 6 (3.4%) | 35 (15.0%) | 1 (1.8%) | |
RMS | 37 (7.9%) | 0 (0.0%) | 17 (7.3%) | 20 (36.4%) | |
University Hospitals | 291 (62.4%) | 167 (94.4%) | 123 (52.6%) | 1 (1.8%) | |
I am familiar with Big Data and AI applications in healthcare | 0.852 | ||||
Strongly disagree | 86 (18.5%) | 37 (20.9%) | 40 (17.1%) | 9 (16.4%) | |
Disagree | 100 (21.5%) | 31 (17.5%) | 57 (24.4%) | 12 (21.8%) | |
Neutral | 161 (34.5%) | 61 (34.5%) | 82 (35.0%) | 18 (32.7%) | |
Agree | 75 (16.1%) | 30 (16.9%) | 35 (15.0%) | 10 (18.2%) | |
Strongly agree | 44 (9.4%) | 18 (10.2%) | 20 (8.5%) | 6 (10.9%) |