Demographics
There were 4433 respondents (27% response rate). Demographic characteristics (gender, training stage, race/ethnicity, marital status, parental status, financial support, and parental career background) of respondents are summarized in Table 1.
Table 1
Demographics of Female and Male Respondents
Demographic | Female, n (%) | Male, n (%) | P-value |
Gender Distribution | 2328 (56.31%) | 1795 (43.42%) | |
Training program | | | < 0.001 |
MD-RI | 366 (15.72%) | 284 (15.82%) | |
MD/PhD | 394 (16.92%) | 459 (25.57%) | |
MD Only | 1568 (67.35%) | 1052 (58.61%) | |
TOTAL | 2328 (100 %) | 1795 (100 %) | |
Training stagea | | | 0.20 |
Medical School Year 1 | 657 (28.42 %) | 502 (28.22 %) | |
Medical School Year 2 | 576 (24.91%) | 462 (25.97 %) | |
Medical School Year 3 | 392 (16.96%) | 281 (15.80 %) | |
Medical School Year 4 | 407 (17.60 %) | 271 (15.23 %) | |
Graduate School Year | 5 (0.22 %) | 5 (0.28 %) | |
Year Out for Research | 61 (2.63 %) | 39 (2.19 %) | |
Graduate School Year 1 | 64 (2.76 %) | 69 (3.88 %) | |
Graduate School Year 2 | 49 (2.12 %) | 54 (3.04 %) | |
Graduate School Year 3 | 44 (1.90 %) | 40 (2.25 %) | |
Graduate School Year 4 | 46 (1.99 %) | 42 (2.36%) | |
Graduate School Year 5 or more | 11 (0.48 %) | 14 (0.79 %) | |
TOTAL | 2312 (100 %) | 1779 (100 %) | |
Race | | | 0.002 |
White | 1587 (69.94 %) | 1263 (72.75 %) | |
Black or African American | 114 (5.02 %) | 52 (3.00 %) | |
American Indian or Alaska Native | 6 (0.26 %) | 4 (0.23 %) | |
Asian or Pacific Islander | 259 (11.41 %) | 159 (9.16 %) | |
Multi-racial or Other | 303 (13.35 %) | 258 (14.86 %) | |
TOTAL | 2269 (100 %) | 1736 (100 %) | |
Marital status | | | 0.07 |
Married/Partnered | 569 (25.10 %) | 481 (27.61 %) | |
Not Married/Partnered | 1698 (74.90 %) | 1261 (72.39 %) | |
TOTAL | 2267 (100 %) | 1742 (100%) | |
Parental status | | | < 0.0001 |
Has a child/children (of 4,041) | 97 (4.28 %) | 132 (7.57 %) | |
Does NOT have a child/children | 2168 (95.72 %) | 1611 (92.43 %) | |
TOTAL | 2265 (100 %) | 1743 (100 %) | |
Primary source of medical school funding | | | < 0.0001 |
MD-PhD or DO-PhD sponsored only | 345 (15.14 %) | 403 (22.90 %) | |
Scholarships | 210 (9.21 %) | 171 (9.72 %) | |
Grants | 37 (1.62 %) | 36 (2.05 %) | |
Loans | 1238 (54.32 %) | 874 (49.66 %) | |
National Service | 19 (0.83 %) | 31 (1.76 %) | |
Personal Savings | 27 (1.18 %) | 18 (1.02 %) | |
Family/Partner Support | 398 (17.46 %) | 223 (12.67 %) | |
Work | 2 (0.09 %) | 4 (0.23 %) | |
Other | 3 (0.13 %) | 0 (0.00 %) | |
TOTAL | 2279 (100 %) | 1760 (100 %) | |
a Excluding Other/NA |
Gender
Among all respondents, there were more females (2328, 56.3%) than males (1795, 43.4%). Female respondents were more likely to be enrolled MD-only programs (1568, 67.4% versus 1052, 58.6%) while male respondents were more likely to be enrolled in MD/PhD programs (459, 25.6% versus 394, 16.9%). In contrast, an equal proportion of female (366, 15.7%) and male respondents (284, 15.8%) self-identified to be MD-RI as defined by intending a > 50% research/clinical ratio. P-value < 0.001 unless otherwise stated (Table 1).
Training stage
Survey responses came from trainees in all stages of MD and MD/PhD programs, including all medical school years, five different graduate school years, and students in a research year program. No significant difference in distribution between males and females within each specific stage of training was observed (p = 0.20). More responses came from those in their medical school phases (3548, 86.7%) than graduate or research years (543, 13.3%) (Table 1).
Race/ethnicity
The majority of respondents were white (2850, 71.3%) compared to American Indian or Alaskan Native (10, 0.25%), Asian or Pacific Islander (418, 10.3%), and multiracial or other (561, 14.1%). Among male students, significantly more white (1263, 72.8% versus 1587, 70.0%) and multiracial students (258, 14.9% versus 303, 13.4%) responded compared to females. In contrast, among female respondents, more identified as black (114, 5.0% versus 52, 3.0%) or Asian (259, 11.4% versus 159, 9.2%) compared to their male counterparts (p = 0.002) (Table 1).
Marital status
Most survey respondents were not married/partnered (2959, 73.8%) versus married/partnered students (1050, 26.2%). There were no gender differences between partnered and not partnered students (p = 0.07) (Table 1).
Parental status
A majority of respondents did not have children (3779, 94.3%) compared to those who had children (229, 5.7%). 132 (7.6%) of male respondents reported having children compared to 97 (4.3%) of female respondents (p < 0.0001) (Table 1).
Financial support
Significant differences were seen between sources of financial support. More males than females paid for their medical training exclusively through program (i.e. MD/PhD or DO/PhD) sponsorships (403, 22.9% versus 345, 15.1%), scholarships (171, 9.7% versus 210, 9.2%), grants (36, 2.1% versus 37, 1.6%), national services (31, 1.8% versus 19, 0.8%), and work (4, 0.2% versus 2, 0.1%). In contrast, more female than male respondents depended upon loans (1238, 54.3% versus 874, 49.7%), personal savings (27, 1.2% versus 18, 1.0%), and family/partner support (398, 17.5% versus 223, 12.7%) (p < 0.0001) (Table 1).
Career intentions
Career sector
Most trainees responded with academia as their first-choice sector (1841, 47.9%) compared to all other careers. More male trainees selected academia (833, 49.7% versus 1008, 46.7%) as their first-choice career compared to females. In contrast, more female respondents chose hospitalist (432, 20.0% versus 254, 15.2%) careers as their top selection relative to males (p = 0.0004) (Fig. 1a).
Career content
Clinical duty was the top career intention for most students, (2539, 66.2%) relative to all others. More females desired clinical duties (1526, 70.1% versus 1013, 61.1%) and advocacy work (73, 3.4% versus 16, 1.0%) as their first career intention compared to male trainees. Male students, in contrast, chose translational research (242, 14.6% versus 200, 9.2%), basic research (130, 7.8% versus 75, 3.4%), and therapeutics/diagnostics work (44, 2.7% versus 27, 1.2%) as their top career intention compared to females (p < 0.0001) (Fig. 1b).
Residency specialties: 1st specialty of interest: Both male and female students selected medical specialties most frequently as the top intended specialty (782, 47.0% and 1245, 58.0% respectively). Significantly more male trainees preferred surgical specialties (471, 28.3% versus 499, 23.3%), emergency medicine (168, 10.1% versus 153, 7.1%), and radiology (90, 5.4% versus 75, 3.5%) relative to females, while more female respondents chose medical specialties (1245, 58.0% versus 782, 47.0%) as their top intended specialty (p < 0.0001) (Fig. 1c).
Career selection factors
1394 (36.3%) respondents and 1319 (34.4%) respondents identified work life balance and patient care as the most critical career selection factors, respectively. In gender comparisons, there were significant differences between top career selection factors. More male respondents identified research (255, 15.4% versus 169, 7.7%), teaching (60, 3.6% versus 41, 1.9%), financial security (110, 6.6% versus 52, 2.4%) and autonomy (61, 3.7% versus 33, 1.5%) as the top career selection factors. In comparison, more female respondents identified patient care (809, 37.1% versus 510, 30.8%), community service (93, 4.3% versus 29, 1.8%) and work life balance (855, 39.2% versus 539, 32.6%) as the top career selection factors (p < 0.0001) (Table 2).
Table 2
Top Career Selection Factors by Female and Male Respondents
Factora | Female, n (%) | Male, n (%) | P < 0.0001 |
Opportunities to do research | 169 (7.74 %) | 255 (15.42 %) | |
Opportunities for patient care | 809 (37.06 %) | 510 (30.83 %) | |
Opportunities to teach | 41 (1.88 %) | 60 (3.63 %) | |
Opportunities for community service | 93 (4.26 %) | 29 (1.75 %) | |
Opportunities for interaction with students | 20 (0.92 %) | 16 (0.97 %) | |
Opportunities for travel | 14 (0.64 %) | 10 (0.60 %) | |
Opportunities for international work | 70 (3.21 %) | 42 (2.54 %) | |
Opportunities for national work | 8 (0.37 %) | 8 (0.48 %) | |
Opportunities for local work | 12 (0.55 %) | 7 (0.42 %) | |
Ability to balance work and personal life | 855 (39.17 %) | 539 (32.59 %) | |
Financial security | 52 (2.38 %) | 110 (6.65 %) | |
Autonomy | 33 (1.51 %) | 61 (3.69 %) | |
Prestige | 7 (0.32 %) | 7 (0.42 %) | |
TOTAL | 2183 (100 %) | 1654 (100 %) | |
a Excluding Other/NA |
Obstacles: Foreseeable work-related obstacles: There is a significant difference between the top foreseeable obstacles identified by male and female respondents (p < 0.0001). Though balancing family and work responsibilities was most commonly selected by both males and females as the first foreseeable obstacle, a greater percentage of female respondents (1219, 55.9% versus 709, 42.6%) selected this obstacle. In contrast, a greater percentage of male respondents (202, 12.2% versus 128, 5.9%) identified lack of opportunity/research funding as the top foreseeable obstacle (Table 3).
Table 3
Obstacles by Female and Male Respondents
Obstaclea | Female, n (%) | Male, n (%) | P < 0.0001 |
Lack of opportunity/funding | 128 (5.87 %) | 202 (12.15 %) | |
Not finding position in desired location | 179 (8.21 %) | 181 (10.88 %) | |
Loan repayment | 319 (14.63 %) | 210 (12.63 %) | |
Malpractice/lawsuit | 19 (0.87 %) | 42 (2.53 %) | |
Under-compensation | 65 (2.98 %) | 74 (4.45 %) | |
Discrimination/biases against your gender, ethnicity, sexual orientation | 34 (1.56 %) | 12 (0.72 %) | |
Sexual harassment | 2 (0.09 %) | 0 (0.00 %) | |
Balancing family and work responsibilities | 1219 (55.89 %) | 709 (42.63 %) | |
Balancing clinical, research, and education responsibilities | 162 (7.43 %) | 186 (11.18 %) | |
Satisfactory professional advancement | 54 (2.48 %) | 47 (2.83 %) | |
TOTAL | 2181 (100 %) | 1663 (100 %) | |
Foreseeable non-work-related responsibilities after residency | | | P < 0.0001 |
Raising children | 2048 (87.97%) | 1579 (87.97%) | > 0.99 |
Taking care of elderly parents | 1513 (64.99%) | 1150 (64.07%) | 0.54 |
Being a caretaker to others | 657 (28.2%) | 595 (33.2%) | 0.0007 |
Financial support of others | 1184 (50.9%) | 1017 (56.7%) | 0.0002 |
a Excluding Other/NA |
Foreseeable non-work-related responsibilities
Both male and female respondents expected to raise children (1579, 88.0% versus 2048, 88.0%, p > 0.99) and take care of elderly parents (1150, 64.1% versus 1513, 65.0%, p = 0.54), respectively. More male than female respondents expected to be a caretaker to others (595, 33.2% versus 657, 28.2%, p = 0.0007) and financially support others (1017, 56.7% versus 1184, 50.9%, p = 0.0002), respectively (Table 3).
Perceptions
Intended research/clinical work ratio
Significant gender differences were seen in intended research/clinical work ratios. Female students preferred to have no research component (558, 24.3% versus 348, 19.8%) or 25%-time commitment (1047, 44.6% versus 747, 42.4%), while male trainees preferred 50% research commitment (309, 17.6% versus 370, 16.1%), 75% research commitment (319, 18.1% versus 291, 12.7%) or full-time research (38, 2.2% versus 29, 1.3%) (p = 0.03) (Table 4).
Table 4
Perceptions of Research/Clinical Work Ratio, Feasibility, and Mentoring
RI Ratio (Research/Clinical Work)a | Female, n (%) | Male, n (%) | P = 0.03 |
0% | 558 (24.31 %) | 348 (19.76 %) | |
25% | 1047 (44.62 %) | 747 (42.42 %) | |
50% | 370 (16.12 %) | 309 (17.55 %) | |
75% | 291 (12.68 %) | 319 (18.11 %) | |
100% | 29 (1.26 %) | 38 (2.16 %) | |
TOTAL | 2295 (100 %) | 1761 (100 %) | |
How feasible is a research intense career in acute care medicine specialties? | P < 0.0001 |
Highly feasible | 130 (5.87 %) | 118 (6.92 %) | |
Feasible | 750 (33.88 %) | 494 (28.99 %) | |
Difficult | 945 (42.68 %) | 700 (41.08 %) | |
Highly difficult | 359 (16.21 %) | 359 (21.07 %) | |
Impossible | 30 (1.36 %) | 33 (1.94 %) | |
TOTAL | 2214 (100 %) | 1704 (100 %) | |
How feasible is a research intense career in surgical specialties? | P < 0.0001 |
Highly feasible | 156 (7.05 %) | 98 (5.74 %) | |
Feasible | 707 (31.96 %) | 466 (27.32 %) | |
Difficult | 799 (36.12 %) | 588 (34.47 %) | |
Highly difficult | 494 (22.33%) | 471 (27.61 %) | |
Impossible | 56 (2.53 %) | 83 (4.87 %) | |
TOTAL | 2212 (100 %) | 1706 (100 %) | |
How much importance is given to talents/accomplishments when recruiting applicants for jobs and/or positions in science and medicine? | P = 0.30 |
A great deal of importance | 669 (30.72 %) | 519 (31.06 %) | |
A lot of importance | 1070 (49.13 %) | 789 (47.22 %) | |
Moderate amount of importance | 410 (18.82 %) | 327 (19.57 %) | |
Little importance | 28 (1.29 %) | 35 (2.09 %) | |
None at all | 1 (0.05 %) | 1 (0.06 %) | |
TOTAL | 2178 (100 %) | 1671 (100 %) | |
How much importance is given to connections/networking when recruiting applicants for jobs and/or positions in science and medicine? | P = 0.01 |
A great deal of importance | 721 (33.04 %) | 527 (31.52 %) | |
A lot of importance | 946 (43.35 %) | 675 (40.37 %) | |
Moderate amount of importance | 456 (20.90 %) | 406 (24.28 %) | |
Little importance | 59 (2.70 %) | 62 (3.71 %) | |
None at all | 0 (0.00 %) | 2 (0.12 %) | |
TOTAL | 2182 (100%) | 1672 (100%) | |
a Excluding Other/NA |
Figure 1a) 1st Sector Choice by Gendera, P = 0.0004 |
Figure 1b) 1st Career Intention by Genderb, P < 0.0001 |
Figure 1c) 1st Specialty of Interest by Genderc, P < 0.0001 |
a Top sector choice for participants separated by gender. The following sectors were included in the category “Other” for better visualization: nonprofit, government, industry, and consulting. |
b Top career intention for participants separated by gender. The category “Other/NA” was excluded for better visualization. |
c Top choice specialty of interest for participants separated by gender. The following specialties were included in the category “Medicine” for better visualization: allergy and immunology, dermatology, family medicine, internal medicine, internal medicine subspecialties, medical genetics, pathology, pediatrics, physical medicine and rehabilitation, preventive medicine, and psychiatry. The following specialties were included in the category “Surgery” for better visualization: surgical subspecialties, obstetrics and gynecology, ophthalmology, otolaryngology, and urology. The following specialties were included in the category “Radiology” for better visualization: nuclear medicine and radiation oncology. The category “Other/NA” was excluded for better visualization. |
Feasibility of research in acute care and surgical specialties
More female than male respondents (750, 33.9% versus 494, 29.0%) believe that research intensive careers in acute care specialties are feasible, while more male than female respondents (359, 21.1% versus 359, 16.2%) believe that research intensive careers in acute care are highly difficult (p < 0.0001). As for surgical specialties, more females than males perceive research intensive careers as highly feasible (156, 7.1% versus 98, 5.7%) or feasible (707, 32.0% versus 466, 27.3%), while more males than females believe research intensive careers in surgical specialties are highly difficult (471, 27.6% versus 494, 22.3%), or impossible (83, 4.9% versus 56, 2.5%) (p < 0.0001) (Table 4).
Perceived important factors in job recruitment
During recruitment of applicants for jobs and/or positions in science and medicine, female and male respondents similarly perceived talent and accomplishments to be “a great deal of importance” (669, 30.7% versus 519, 31.1%) and “a lot of importance” (1070, 49.1% versus 789, 47.2%) (p = 0.30). Interestingly, more female than male respondents perceived connections/networking to be “a great deal of importance” (721, 33.0% versus 527, 31.5%), whereas more males than females perceived connections/networking to be of “moderate amount of importance” (406, 24.3% versus 456, 20.9%) (p = 0.01) (Table 4).