| Literature DB >> 27443277 |
Yeon-Yong Kim1, Un-Na Kim1, Yon Su Kim2, Jin-Seok Lee3,4.
Abstract
BACKGROUND: An imbalance of physician supply by medical specialty has been observed in most countries. In Korea, there is a greater tendency to avoid surgical specialties and specialty choices in nonclinical medicine, such as the basic science of medicine. In this study, we identified factors affecting the specialty choice of physicians in order to provide a basis for policies to address this problem.Entities:
Keywords: Health manpower; Medical education; Medical specialties; Specialty choice
Mesh:
Year: 2016 PMID: 27443277 PMCID: PMC4957410 DOI: 10.1186/s12960-016-0141-8
Source DB: PubMed Journal: Hum Resour Health ISSN: 1478-4491
General characteristics (N = 9499)
| Grade (year) | 1st | 2nd | 3rd | 4th | Total |
| ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| % | % | % | % | % | ||||||||
| Gender | Men | 1 747 | 64.8 | 1 473 | 60.7 | 1 276 | 61.0 | 1 288 | 56.3 | 5 784 | 60.9 | <0.001 |
| Women | 947 | 35.2 | 954 | 39.3 | 816 | 39.0 | 998 | 43.7 | 3 715 | 39.1 | ||
| Hometown | Metropolitan | 1 160 | 43.1 | 1 028 | 42.4 | 860 | 41.1 | 981 | 42.9 | 4 029 | 42.4 | 0.541 |
| Nonmetropolitan | 1 534 | 56.9 | 1 399 | 57.6 | 1 232 | 58.9 | 1 305 | 57.1 | 5 470 | 57.6 | ||
| Type of medical school | Medical college | 1 137 | 42.2 | 979 | 40.3 | 839 | 40.1 | 808 | 35.3 | 3 763 | 39.6 | <0.001 |
| Graduate medical school | 1 557 | 57.8 | 1 448 | 59.7 | 1 253 | 59.9 | 1 478 | 64.7 | 5 736 | 60.4 | ||
| Location of medical school | Metropolitan | 871 | 32.3 | 847 | 34.9 | 547 | 26.1 | 891 | 39.0 | 3 156 | 33.2 | <0.001 |
| Nonmetropolitan | 1 823 | 67.7 | 1 580 | 65.1 | 1 545 | 73.9 | 1 395 | 61.0 | 6 343 | 66.8 | ||
| Age (mean, SD) | 23.82 (2.94) | 25.00 (2.99) | 26.34 (3.14) | 27.37 (3.05) | 25.53 (3.32) | <0.001 | ||||||
Chi-square test was performed for gender, hometown, type of medical school, and location of medical school. Analysis of variance (ANOVA) was performed for age
Specialty preferences of medical students (N = 9499)
| Grade/gender specialty | 1st | 2nd | 3rd | 4th | Total | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Men | Women | Men | Women | Men | Women | Men | Women | ||||
| Clinical | Medical | Internal medicine | 478 (27.4)* | 283 (29.9)* | 461 (31.3)* | 326 (34.2)* | 368 (28.8)* | 282 (34.6)* | 350 (27.2)* | 287 (28.8)* | 2 835 (29.8) |
| Psychiatry | 144 (8.2)* | 98 (10.3)* | 94 (6.4) | 84 (8.8) | 82 (6.4) | 68 (8.3) | 83 (6.4) | 91 (9.1) | 744 (7.8) | ||
| Pediatrics | 51 (2.9)* | 101 (10.7)* | 45 (3.1)* | 105 (11.0)* | 58 (4.5)* | 110 (13.5)* | 50 (3.9)* | 123 (12.3)* | 643 (6.8) | ||
| Dermatology | 79 (4.5) | 59 (6.2) | 45 (3.1) | 65 (6.8) | 48 (3.8) | 35 (4.3) | 39 (3.0) | 50 (5.0) | 420 (4.4) | ||
| Neurology | 52 (3.0) | 48 (5.1) | 56 (3.8) | 50 (5.2) | 48 (3.8) | 39 (4.8) | 47 (3.6) | 38 (3.8) | 378 (4.0) | ||
| Rehabilitative medicine | 75 (4.3)* | 36 (3.8)* | 57 (3.9)* | 24 (2.5)* | 48 (3.8)* | 14 (1.7)* | 51 (4.0)* | 32 (3.2)* | 337 (3.5) | ||
| Diagnostic radiology | 57 (3.3)* | 32 (3.4)* | 37 (2.5) | 43 (4.5) | 35 (2.7) | 26 (3.2) | 33 (2.6) | 46 (4.6) | 309 (3.3) | ||
| Anesthesiology | 37 (2.1) | 30 (3.2) | 39 (2.6) | 28 (2.9) | 35 (2.7)* | 20 (2.5)* | 43 (3.3) | 42 (4.2) | 274 (2.9) | ||
| Family medicine | 22 (1.3) | 20 (2.1) | 23 (1.6) | 33 (3.5) | 23 (1.8) | 23 (2.8) | 24 (1.9) | 37 (3.7) | 205 (2.2) | ||
| Emergency medicine | 22 (1.3)* | 8 (0.8)* | 24 (1.6)* | 8 (0.8)* | 21 (1.6) | 12 (1.5) | 18 (1.4)* | 8 (0.8)* | 121 (1.3) | ||
| Clinical pathology | 6 (0.3) | 7 (0.7) | 3 (0.2) | 4 (0.4) | 6 (0.5) | 5 (0.6) | 2 (0.2)* | 13 (1.3)* | 46 (0.5) | ||
| Therapeutic radiology | 8 (0.5)* | 1 (0.1)* | 6 (0.4) | 1 (0.1) | 3 (0.2) | 5 (0.6) | 12 (0.9) | 5 (0.5) | 41 (0.4) | ||
| Occupational and environmental medicine | 5 (0.3) | 0 (0.0) | 4 (0.3) | 0 (0.0) | 8 (0.6) | 3 (0.4) | 12 (0.9) | 5 (0.5) | 37 (0.4) | ||
| Nuclear medicine | 3 (0.2) | 0 (0.0) | 3 (0.2) | 0 (0.0) | 7 (0.5) | 0 (0.0) | 3 (0.2) | 0 (0.0) | 16 (0.2) | ||
| Tuberculosis | 1 (0.1) | 0 (0.0) | 2 (0.1) | 1 (0.1) | 1 (0.1) | 0 (0.0) | 9 (0.7)* | 1 (0.1)* | 15 (0.2) | ||
| Subtotal | 1 040 (59.5)* | 723 (76.3)* | 899 (61.0)* | 772 (80.9)* | 791 (62.0)* | 642 (78.7)* | 776 (60.2)* | 778 (78.0)* | 6 421 (67.6) | ||
| Surgical | Orthopedic surgery | 257 (14.7)* | 14 (1.5)* | 222 (15.1)* | 4 (0.4)* | 169 (13.2)* | 7 (0.9)* | 174 (13.5)* | 6 (0.6)* | 853 (9.0) | |
| General surgery | 129 (7.4)* | 67 (7.1)* | 102 (6.9)* | 46 (4.8)* | 109 (8.5)* | 50 (6.1)* | 79 (6.1)* | 51 (5.1)* | 633 (6.7) | ||
| Ophthalmology | 83 (4.8)* | 50 (5.3)* | 57 (3.9)* | 27 (2.8)* | 21 (1.6) | 20 (2.5) | 52 (4.0) | 41 (4.1) | 351 (3.7) | ||
| Neurosurgery | 87 (5.0)* | 20 (2.1)* | 61 (4.1)* | 21 (2.2)* | 54 (4.2)* | 5 (0.6)* | 53 (4.1)* | 7 (0.7)* | 308 (3.2) | ||
| Otolaryngology | 50 (2.9)* | 16 (1.7)* | 37 (2.5)* | 18 (1.9)* | 35 (2.7)* | 13 (1.6)* | 41 (3.2) | 28 (2.8) | 238 (2.5) | ||
| Plastic surgery | 32 (1.8)* | 2 (0.2)* | 34 (2.3)* | 14 (1.5)* | 36 (2.8)* | 12 (1.5)* | 63 (4.9)* | 16 (1.6)* | 209 (2.2) | ||
| Obstetrics-gynecology | 8 (0.5) | 15 (1.6) | 3 (0.2)* | 31 (3.2)* | 9 (0.7)* | 38 (4.7)* | 8 (0.6)* | 45 (4.5)* | 157 (1.7) | ||
| Cardiothoracic surgery | 27 (1.5)* | 14 (1.5)* | 26 (1.8)* | 6 (0.6)* | 20 (1.6)* | 6 (0.7)* | 12 (0.9) | 10 (1.0) | 121 (1.3) | ||
| Urology | 3 (0.2) | 1 (0.1) | 4 (0.3) | 1 (0.1) | 6 (0.5) | 0 (0.0) | 5 (0.4) | 2 (0.2) | 22 (0.2) | ||
| Subtotal | 676 (38.7)* | 199 (21.0)* | 546 (37.1)* | 168 (17.6)* | 459 (36.0)* | 151 (18.5)* | 487 (37.8)* | 206 (20.6)* | 2 892 (30.4) | ||
| Nonclinical | Pathology | 10 (0.6) | 8 (0.8) | 6 (0.4) | 7 (0.7) | 12 (0.9) | 16 (2.0) | 9 (0.7) | 8 (0.8) | 76 (0.8) | |
| Basic science of medicine | 17 (1.0) | 9 (1.0) | 16 (1.1)* | 3 (0.3)* | 9 (0.7)* | 2 (0.2)* | 11 (0.9)* | 3 (0.3)* | 70 (0.7) | ||
| Preventive medicine | 4 (0.2) | 8 (0.8) | 6 (0.4) | 4 (0.4) | 5 (0.4) | 5 (0.6) | 5 (0.4) | 3 (0.3) | 40 (0.4) | ||
| Subtotal | 31 (1.8) | 25 (2.6) | 28 (1.9) | 14 (1.5) | 26 (2.0) | 23 (2.8) | 25 (1.9) | 14 (1.4) | 186 (2.0) | ||
*P < 0.05, chi-square test was performed for specialty (grouped by grade and gender)
Logistic regression for factors associated with nonclinical medicine specialty N = 9499)
| All | Subgroup analysis | |||
|---|---|---|---|---|
| aOR (95 % CI) | Men | Women | ||
| aOR (95 % CI) | aOR (95 % CI) | |||
| Men (ref: women) | 0.851 (0.628–1.152) | |||
| Age | 1.052 (0.998–1.110) | 1.038 (0.971–1.110) | 1.098 (0.999–1.207) | |
| Grade | 1st | Reference | Reference | Reference |
| 2nd | 0.780 (0.518–1.174) | 1.040 (0.617–1.753) | 0.488* (0.249–0.956) | |
| 3rd | 1.011 (0.671–1.522) | 1.047 (0.603–1.820) | 0.857 (0.459–1.597) | |
| 4th | 0.689 (0.438–1.084) | 0.964 (0.541–1.717) | 0.374* (0.176–0.793) | |
| Medical college (ref: graduate medical school) | 1.625* (1.139–2.318) | 1.768* (1.114–2.807) | 1.484 (0.823–2.677) | |
| Metropolitan hometown (ref: nonmetropolitan) | 1.161 (0.857–1.573) | 1.513* (1.023–2.240) | 0.783 (0.481–1.274) | |
| Metropolitan school (ref: nonmetropolitan) | 1.183 (0.858–1.631) | 1.198 (0.794–1.808) | 1.189 (0.709–1.993) | |
*P < 0.05
Logistic regression for factors associated with surgical specialty preference (N = 9313)
| All | Subgroup analysis | |||
|---|---|---|---|---|
| aOR (95 % CI) | Men | Women | ||
| aOR (95 % CI) | aOR (95 % CI) | |||
| Men (ref: women) | 2.537* (2.296–2.804) | |||
| Age | 0.985 (0.968–1.003) | 0.974* (0.954–0.995) | 1.024 (0.986–1.064) | |
| Grade | 1st | Reference | Reference | Reference |
| 2nd | 0.907 (0.802–1.027) | 0.967 (0.836–1.119) | 0.768* (0.608–0.970) | |
| 3rd | 0.909 (0.795–1.040) | 0.949 (0.809–1.113) | 0.805 (0.625–1.038) | |
| 4th | 1.022 (0.890–1.173) | 1.065 (0.903–1.256) | 0.876 (0.677–1.135) | |
| Medical college (ref: graduate medical school) | 0.885* (0.790–0.991) | 0.849* (0.743–0.970) | 1.009 (0.810–1.256) | |
| Metropolitan hometown (ref: nonmetropolitan) | 1.031 (0.938–1.134) | 1.055 (0.941–1.182) | 0.970 (0.815–1.154) | |
| Metropolitan school (ref: nonmetropolitan) | 0.892* (0.806–0.988) | 0.840* (0.743–0.949) | 1.032 (0.858–1.241) | |
*P < 0.05
Logistic regression for factors associated with controllable lifestyle specialty preference
| Controllable lifestyle | Self-employed specialty | ||
|---|---|---|---|
| [ | [ | ||
| aOR (95 % CI) | aOR (95 % CI) | ||
| Men (ref: women) | 0.802* (0.730–0.881) | 0.519* (0.470–0.573) | |
| Age | 0.992 (0.974–1.011) | 1.021* (1.002–1.041) | |
| Grade | 1st | Reference | Reference |
| 2nd | 0.848* (0.749–0.961) | 0.982 (0.858–1.124) | |
| 3rd | 0.779* (0.679–0.894) | 0.987 (0.853–1.142) | |
| 4th | 0.965 (0.839–1.110) | 1.229* (1.061–1.424) | |
| Medical college (ref: graduate medical school) | 1.198* (1.067–1.344) | 1.118 (0.990–1.263) | |
| Metropolitan hometown (ref: nonmetropolitan) | 0.992 (0.901–1.092) | 1.143* (1.033–1.264) | |
| Metropolitan school (ref: nonmetropolitan) | 1.030 (0.930–1.140) | 0.779* (0.698–0.870) | |
*P < 0.05