Abstract
Objectives:
To define the prevalence of poor faculty well-being and workplace mistreatment and investigate factors impacting surgical faculty well-being.
Summary Background Data:
Recent qualitative data suggests that faculty well-being has been largely unaddressed. Rates of poor faculty well-being are undefined and workplace factors influencing well-being are poorly characterized.
Methods:
A national cross-sectional survey was sent to all general surgery faculty through the ACGME in 2024. Multivariable logistic regression models evaluated associations of faculty and departmental characteristics with measures of well-being.
Results:
Responses from 3,253 (30.0% response rate) surgical faculty from all 350 general surgery programs were analyzed. Weekly burnout symptoms were reported by 34.9% of faculty, thoughts of attrition were reported by 30.2%, and suicidal thoughts were reported by 4.4%. Mistreatment was reported by 66.2% of faculty (n= 2,132), including bullying (54.4%), discrimination (46.3%), or sexual harassment (13.2%). Women reported significantly higher mistreatment (88.6% vs 55.7%, P<0.001). Faculty were more likely to report burnout if they were women (OR 1.30, 95%CI 1.06–1.60) or working >70 hours/week (aOR 2.09, 95%CI 1.63–2.68) or >7 nights on call/month on average (aOR 1.58, 95%CI 1.30–1.93). Faculty were more likely to consider leaving their job if they were Non-White (aOR 1.25, 95%CI 1.04–1.51), childless (aOR 1.32, 95%CI 1.05–1.67), or making < $350K (aOR 2.00, 95%CI 1.34–2.97). After adjusting for mistreatment, the association between gender and burnout was no longer observed (aOR 0.95, 95%CI 0.77–1.18).
Conclusions:
Burnout and mistreatment are common especially among female surgeons, which may be driven by differential workplace mistreatment. These results provide actionable targets for interventions within institutions to improve surgeon well-being.
INTRODUCTION
Physician burnout has been reported to impact between 30%–60% of the workforce in recent years.[1–4] When physicians experience burnout, they are more susceptible to job dissatisfaction and poor patient outcomes.[5, 6] Burnout may be driven by poor workplace conditions, a lack of appreciation, and high work/call burden.[7] Mistreatment (i.e., bullying, identity-based discrimination, and sexual harassment) in the workplace may also contribute to burnout, poor psychological safety, thoughts of attrition and suicide for physicians.[8, 9] Presently, the groups most vulnerable to higher exposure rates of mistreatment are trainees, surgeons, and female physicians.[10, 11] Despite recent efforts to address poor well-being among trainees, there has been less work in the space of the well-being and workplace environment of surgical faculty. This may be of particular importance in light of ongoing changes to the training environment, which qualitative work has indicated may shift additional workplace burdens onto faculty.[12]
Addressing modifiable workplace factors contributing to poor surgeon well-being also has implications for the surgical workforce overall. Given the projected physician shortage of more than 30,000 within the next 10 years, of which up to 74% are predicted to be surgeons, maximizing retention of trained surgeons is of great importance.[13] Augmenting well-being and curtailing mistreatment in the workplace should decrease attrition and may improve patient outcomes.[14]
Despite the urgent need to improve the well-being of practicing surgeons, the prevalence of poor well-being amongst surgical faculty and the workplace factors associated with it is poorly understood. To address this, a new anonymous, national survey was distributed by the Accreditation Council for Graduate Medical Education (ACGME) to general surgery faculty within the U.S. to assess overall well-being and the workplace environment. The survey could not be used by the ACGME for program accreditation or assessment. Our objectives were to (1) assess the prevalence of poor faculty well-being (e.g., burnout, thoughts of attrition, and suicidality), (2) examine the prevalence and sources of faculty mistreatment (e.g., bullying, identity-based discrimination, and sexual harassment), and (3) investigate faculty and institutional characteristics associated with surgeon well-being.
METHODS
Study Setting and Participants
An anonymous, cross-sectional survey was distributed by the Surgical Education Numbered Trials (SENT) Team in collaboration with the ACGME to general surgery faculty at all ACGME-accredited general surgery residency programs from November 4, 2024 to January 5, 2025. Prior to completing the survey, an introductory statement defined the purpose of the survey, specifying that the survey would be used to contribute to future research, policy decisions, and improvements within departments of surgery. This introductory statement also confirmed that responses would be confidential, de-identified, aggregated and withheld in the event of a low response if a survey item risked identification. No incentives were provided for faculty participation.[15–17] Importantly, it was made clear that the survey could not be used by the ACGME to assess or accredit programs, thus encouraging forthright reporting for well-being issues.
Survey responses were collected by the ACGME and de-identified prior to data transfer to Indiana University for analysis. Data were not retained by the ACGME, and the ACGME was contractually forbidden from reviewing or using these data for program accreditation to allow more candid reporting. The Indiana University Institutional Review Board (IRB) office reviewed this study and deemed that it did not meet the criteria for human-subjects research. Thus, this study did not require full review and approval by the IRB.
Survey Development
The 2024 survey items were adapted from previously published and validated instruments.[9, 15, 16, 18, 19] Pretest cognitive interviews were conducted with general surgery faculty from multiple institutions to assess overall survey coherence, balance, and clarity. Following feedback from pretest cognitive interviews, the survey was then iteratively revised and retested.
Faculty and Institutional Characteristics
Respondents were asked to self-report the following demographics: gender, race and/or ethnicity, sexual orientation, relationship status, parental status, and primary specialty. Respondents could select one or more options for primary specialty, gender, and race and/or ethnicity (American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, White, Middle Eastern or North African, Hispanic or Latinx, Other or Prefer not to say). Faculty were identified by primary specialty by a hierarchical placement in which they were classified as Acute Care Surgery if they selected Acute Care Surgery, Trauma Surgery, Critical Care or Burn.[20] Faculty who selected more than one specialty were assigned upon manual review. The ACGME provided faculty-level institution size quartiles (< 19, 19–26, 27–39, >39 faculty). The American Board of Surgery (ABS) provided resident-level institution type (University-Affiliated, Independent, Military) and geographic region (Northeast, Southeast, Midwest, Southwest, or West).
Primary Outcomes
The primary outcomes in our analysis were: burnout, thoughts of attrition, and thoughts of suicide. Burnout was measured using a modified, abbreviated Maslach Burnout Inventory-Human Services Survey for Medical Personnel (aMBI), which assesses the experience of 3 emotional exhaustion and 3 depersonalization symptoms.[15–17] In our analyses, and consistent with prior literature, burnout was defined as experiencing any emotional exhaustion or depersonalization symptom at least once weekly.[21]
Thoughts of attrition were assessed with the item, “How likely are you to leave your current practice/institution within two years?”[22] Faculty were stratified into having 1) no thoughts of attrition if they responded “none” or “slight” or 2) any thoughts of attrition if they responded “moderate”, “likely,” or “definite.” Additional information regarding attrition plans was assessed by the following item, “What do you intend to do if you leave your current practice?”[23, 24] Faculty selected from the following options: join another surgical practice, seek a leadership position and/or promotion at another institution, move for life reasons (e.g., to be closer to family), work as a locum tenens, administrative nonclinical job, leave medicine/surgery altogether, retire, or other (Supplementary Table 1, Supplemental Digital Content 1, http://links.lww.com/SLA/F849). We performed a sensitivity analysis using a modified threshold measuring thoughts of attrition (Supplementary Table 2, Supplemental Digital Content 2, http://links.lww.com/SLA/F850). We performed additional sensitivity analyses to analyze nonretirement attrition excluding all senior (> 30 years in practice) faculty with intent to retire (Supplementary Table 3, Supplemental Digital Content 3, http://links.lww.com/SLA/F851).
Thoughts of suicide were measured with a validated single yes/no item, “During the past 12 months, have you had thoughts of taking your own life?”[19] Contact information for the National Suicide Prevention Lifeline was provided to respondents who reported suicidal thoughts.
Mistreatment and Workplace Exposures
Faculty were asked to report mistreatment experiences during the current academic year of specific identity-based (e.g., gender, race) discrimination, bullying, or sexual harassment behaviors (5 items, 7 items, and 6 items, respectively). Faculty reported they had either “never” experienced a particular mistreatment behavior, or they had experienced the behavior from one or more sources (patients/families, other faculty members, trainees, administrators, or nurses/support staff [e.g., radiology technicians, IT personnel, etc.]). Faculty were asked to report on the frequency of average nights on call per month, average hours worked per week, and the number of weeks of vacation taken in the past year.[20] Faculty were also asked to report their annual compensation.
Statistical Analysis
Multivariable logistic regression models were constructed including all available faculty demographic characteristics (gender, race/ethnicity, years in practice, surgical specialty, relationship status, parental status), measures of work/life balance (personal compensation, average monthly nights on call, vacation time, and average weekly work hours), and institution characteristics (size, type, and geographic region) as predictors of burnout or thoughts of attrition. Separate models were fit both omitting and adjusting for mistreatment. All models were estimated with clustered robust standard errors to account for clustering of faculty within institutions. A Firth-type bias-reduced multivariable logistic regression model was used for suicidal thoughts due to the low event rate (Supplementary Table 4, Supplemental Digital Content 4, http://links.lww.com/SLA/F852). Statistical analyses were performed using RStudio, version 4.5.2 (RStudio, Boston, MA) and State 19 SE (StataCorp, College Station, TX).
RESULTS
Survey Responses and Key Demographics
Overall, 3,253 faculty at all 350 institutions responded to the survey (30.0% response rate). In total, 3,248 faculty were included in unadjusted analyses, excluding 5 faculty who identified as transgender, nonbinary, or other to maintain confidentiality. Of all respondents who self-reported gender, 1,956 were male, and 873 were female. The majority of faculty self-identified as non-Hispanic White (n=2,094, 64.5%), were married or in a relationship (n=2,855, 87.9%), had children (n=2,592, 79.8%), and worked at university-affiliated institutions (n=2,088, 64.3%). Male faculty were more likely to be married or in a relationship than female faculty (93.4% vs. 77.3%) and more frequently had children compared to female faculty (89.1% vs. 62.4%). Respondents represented a wide range of surgical specialties. A complete table of demographics is listed in Table 1.
Table 1.
Demographic Characteristics of Faculty from 350 U.S. Surgical Residency Programs
| Characteristic | Overall N = 3,248a | Male N = 1,965 | Female N = 873 | Unknown N = 410b |
|---|---|---|---|---|
| Race and Ethnicity | ||||
| NH White1 | 2,094 (64.5%) | 1,348 (68.6%) | 583 (66.8%) | 163 (39.8%) |
| Non-White2 | 941 (29.0%) | 498 (25.3%) | 234 (26.8%) | 209 (51.0%) |
| Years in Practice | ||||
| <5 yrs | 596 (18.3%) | 286 (14.6%) | 230 (26.3%) | 80 (19.5%) |
| 5 – 10 yrs | 688 (21.2%) | 334 (17.0%) | 260 (29.8%) | 94 (22.9%) |
| 11 – 20 yrs | 881 (27.1%) | 521 (26.5%) | 233 (26.7%) | 127 (31.0%) |
| 21 – 30 yrs | 656 (20.2%) | 478 (24.3%) | 103 (11.8%) | 75 (18.3%) |
| >30 yrs | 417 (12.8%) | 343 (17.5%) | 47 (5.4%) | 27 (6.6%) |
| Specialty 3 | ||||
| Acute Care Surgery | 966 (29.7%) | 574 (29.2%) | 264 (30.2%) | 128 (31.2%) |
| Bariatric Surgery | 152 (4.7%) | 103 (5.2%) | 33 (3.8%) | 16 (3.9%) |
| Breast Surgery | 165 (5.1%) | 32 (1.6%) | 116 (13.3%) | 17 (4.1%) |
| Cardiothoracic | 165 (5.1%) | 120 (6.1%) | 26 (3.0%) | 19 (4.6%) |
| Colorectal Surgery | 275 (8.5%) | 164 (8.3%) | 79 (9.0%) | 32 (7.8%) |
| Endocrine Surgery | 77 (2.4%) | 39 (2.0%) | 29 (3.3%) | 9 (2.2%) |
| General Surgery | 388 (11.9%) | 270 (13.7%) | 79 (9.0%) | 39 (9.5%) |
| Other | 74 (2.3%) | 45 (2.3%) | 16 (1.8%) | 13 (3.2%) |
| Pediatric Surgery | 203 (6.3%) | 115 (5.9%) | 58 (6.6%) | 30 (7.3%) |
| Plastic Surgery | 82 (2.5%) | 52 (2.6%) | 18 (2.1%) | 12 (2.9%) |
| Surgical Oncology | 257 (7.9%) | 179 (9.1%) | 45 (5.2%) | 33 (8.0%) |
| Transplant | 129 (4.0%) | 78 (4.0%) | 33 (3.8%) | 18 (4.4%) |
| Unknown | 13 (0.4%) | 1 (0.1%) | 4 (0.5%) | 8 (2.0%) |
| Vascular | 302 (9.3%) | 193 (9.8%) | 73 (8.4%) | 36 (8.8%) |
| Personal Compensation 4 | ||||
| < $350K | 566 (17.4%) | 279 (14.2%) | 225 (25.8%) | 62 (15.1%) |
| $350–499K | 1,107 (34.1%) | 598 (30.4%) | 371 (42.5%) | 138 (33.7%) |
| $500–749K | 992 (30.5%) | 680 (34.6%) | 208 (23.8%) | 104 (25.4%) |
| >= $750K | 335 (10.3%) | 268 (13.6%) | 33 (3.8%) | 34 (8.3%) |
| Prefer not to answer | 193 (5.9%) | 108 (5.5%) | 29 (3.3%) | 56 (13.7%) |
| Average Nights on Call 5 | ||||
| <5 nights | 1,098 (33.8%) | 671 (34.1%) | 307 (35.2%) | 120 (29.3%) |
| 5–7 nights | 1,112 (34.2%) | 671 (34.1%) | 308 (35.3%) | 133 (32.4%) |
| >7 nights | 931 (28.7%) | 576 (29.3%) | 232 (26.6%) | 123 (30.0%) |
| Vacation Time 6 | ||||
| <4 weeks | 1,525 (47.0%) | 912 (46.4%) | 436 (49.9%) | 177 (43.2%) |
| 4–5 weeks | 1,281 (39.4%) | 770 (39.2%) | 354 (40.5%) | 157 (38.3%) |
| >5 weeks | 336 (10.3%) | 232 (11.8%) | 63 (7.2%) | 41 (10.0%) |
| Average Work Hours 7 | ||||
| <55 hrs/week | 784 (24.1%) | 448 (22.8%) | 237 (27.1%) | 99 (24.1%) |
| 55–61 hrs/week | 1,168 (36.0%) | 731 (37.2%) | 303 (34.7%) | 134 (32.7%) |
| 62–70 hrs/week | 599 (18.4%) | 364 (18.5%) | 159 (18.2%) | 76 (18.5%) |
| >70 hrs/week | 581 (17.9%) | 362 (18.4%) | 150 (17.2%) | 69 (16.8%) |
| Relationship Status | ||||
| Single/Divorced/Widowed | 343 (10.6%) | 120 (6.1%) | 193 (22.1%) | 30 (7.3%) |
| Married/Relationship | 2,855 (87.9%) | 1,835 (93.4%) | 675 (77.3%) | 345 (84.1%) |
| Parental Status | ||||
| No Children | 610 (18.8%) | 208 (10.6%) | 325 (37.2%) | 77 (18.8%) |
| Yes Children | 2,592 (79.8%) | 1,751 (89.1%) | 545 (62.4%) | 296 (72.2%) |
| Program Size | ||||
| <19 Faculty | 369 (11.4%) | 237 (12.1%) | 95 (10.9%) | 37 (9.0%) |
| 19–26 Faculty | 535 (16.5%) | 350 (17.8%) | 120 (13.7%) | 65 (15.9%) |
| 27–39 Faculty | 884 (27.2%) | 547 (27.8%) | 224 (25.7%) | 113 (27.6%) |
| >39 Faculty | 1,460 (45.0%) | 831 (42.3%) | 434 (49.7%) | 195 (47.6%) |
| Program Type | ||||
| University Affiliated | 2,088 (64.3%) | 1,196 (60.9%) | 607 (69.5%) | 285 (69.5%) |
| Independent | 940 (28.9%) | 619 (31.5%) | 220 (25.2%) | 101 (24.6%) |
| Military | 60 (1.8%) | 37 (1.9%) | 17 (1.9%) | 6 (1.5%) |
| Unknown | 160 (4.9%) | 113 (5.8%) | 29 (3.3%) | 18 (4.4%) |
| Program Location | ||||
| Northeast | 959 (29.5%) | 580 (29.5%) | 263 (30.1%) | 116 (28.3%) |
| Southeast | 718 (22.1%) | 459 (23.4%) | 171 (19.6%) | 88 (21.5%) |
| Midwest | 686 (21.1%) | 423 (21.5%) | 185 (21.2%) | 78 (19.0%) |
| Southwest | 390 (12.0%) | 237 (12.1%) | 101 (11.6%) | 52 (12.7%) |
| West | 478 (14.7%) | 256 (13.0%) | 149 (17.1%) | 73 (17.8%) |
| Unknown | 17 (0.5%) | 10 (0.5%) | 4 (0.5%) | 3 (0.7%) |
5 faculty members who identified as transgender, nonbinary, or other were excluded for confidentiality.
Faculty members with either missing data regarding gender or selected “prefer not to say” were included in an “unknown” gender group
Non-Hispanic White
Any race or ethnicity except Non-Hispanic White
Plastic Surgery includes Maxillofacial Surgery
Personal 2023 Compensation
Average monthly nights on call
Vacation time taken last year
Average weekly work hours
Missing data rows are not displayed in the table for the following variables: Race/Ethnicity: Overall (N=213, 6.6%) Male (N=119; 6.1%), Female (N=56; 6.4%), Unknown (N=38; 9.3%)
Years in Practice: Overall (N=10; 0.3%) Male (N=1; 0.1%), Unknown (N=7; 1.7%)
Specialty: Overall (N= 13, 0.4%) Male (N=1; 0.1), Female (N=4; 0.5%), Unknown (N=8; 2.0%)
Personal 2023 Compensation: Overall (N=55; 1.7%), Male (N=32; 1.6%), Female (N=7; 0.8%), Unknown (N=16; 3.9%)
Average monthly nights on call: Overall (N= 128; 3.9%) Male (N=60; 3.1%), Female (N=32; 3.7%), Unknown (N=36; 8.8%)
Weeks of vacation: Overall (N=108; 3.3%) Male (N=51; 2.6%), Female (N=21; 2.4%), Unknown (N=36; 8.8%)
Average weekly work hours: Overall (N=116; 3.3%) Male (N=60; 3.1%), Female (N=24; 2.7%), Unknown (N=32; 7.8%)
Relationship status: Overall (N= 50; 1.5%) Male (N=10 ; 0.5%), Female (N=5; 0.6%), Unknown (N=35; 8.5%)
Parental status: Overall (N= 46; 1.4%) Male (N=6; 0.3%), Female (N=3; 0.3%), Unknown (N=37; 9.0%)
Program type: Overall (N= 160; 4.9%) Male (N=113; 5.8%), Female (N=29; 3.3%), Unknown (N=18, 4.4%)
Program location: Overall (N= 17; 0.5%) Male (N=10; 0.5%), Female (N=4, 0.5%), Unknown (N=3; 0.7%)
Prevalence of Burnout, Thoughts of Attrition, and Suicidality
Faculty were excluded if data were missing on burnout (n=18), thoughts of attrition (n=20), or suicidal thoughts (n=18) for a total cohort of 3,221. More than one third of all faculty (34.9%) reported experiencing burnout at least weekly (42.0% female vs 31.2% male; p<0.001). Thoughts of attrition were reported by 30.2% of all faculty respondents. Thoughts of suicide during the past 12 months were reported by 4.4% of all faculty, more frequently by female faculty (5.4%) compared to male faculty (3.6%; p=0.014). Complete descriptions of measures of burnout, thoughts of attrition, and suicidality are shown in Table 2.
Table 2.
Frequency of Mistreatment, Burnout, Attrition and Suicidal Thoughts among U.S. Surgical Faculty
| Characteristic | Overall N = 3,2211 | Male N = 1,958 | Female N = 870 | Unknown N = 393 | p-value2 |
|---|---|---|---|---|---|
| Discrimination | <0.001 | ||||
| No Discrimination | 1,643 (51.0%) | 1,350 (68.9%) | 112 (12.9%) | 181 (46.1%) | |
| Any Discrimination |
1,492 (46.3%) | 557 (28.4%) | 742 (85.3%) | 193 (49.1%) | |
| Bullying | <0.001 | ||||
| No Bullying | 1,392 (43.2%) | 949 (48.5%) | 287 (33.0%) | 156 (39.7%) | |
| Any Bullying | 1,753 (54.4%) | 968 (49.4%) | 568 (65.3%) | 217 (55.2%) | |
| Sexual Harassment | <0.001 | ||||
| No Sexual Harassment | 2,710 (84.1%) | 1,739 (88.8%) | 642 (73.8%) | 329 (83.7%) | |
| Any Sexual Harassment | 424 (13.2%) | 172 (8.8%) | 207 (23.8%) | 45 (11.5%) | |
| Mistreatment | <0.001 | ||||
| No Mistreatment | 1,029 (31.9%) | 835 (42.6%) | 87 (10.0%) | 107 (27.2%) | |
| Any Mistreatment | 2,132 (66.2%) | 1,091 (55.7%) | 771 (88.6%) | 270 (68.7%) | |
| Weekly Burnout Symptoms | <0.001 | ||||
| No weekly burnout symptoms | 2,098 (65.1%) | 1,347 (68.8%) | 505 (58.0%) | 246 (62.6%) | |
| Any weekly burnout symptoms | 1,123 (34.9%) | 611 (31.2%) | 365 (42.0%) | 147 (37.4%) | |
| Thoughts of Attrition | 0.531 | ||||
| No Thoughts of Attrition | 2,248 (69.8%) | 1,379 (70.4%) | 603 (69.3%) | 266 (67.7%) | |
| Any Thoughts of Attrition | 973 (30.2%) | 579 (29.6%) | 267 (30.7%) | 127 (32.3%) | |
| Suicidal Thoughts | 0.014 | ||||
| No | 3,078 (95.6%) | 1,887 (96.4%) | 823 (94.6%) | 368 (93.6%) | |
| Yes | 143 (4.4%) | 71 (3.6%) | 47 (5.4%) | 25 (6.4%) |
A total of 3,221 were included in the final cohort. Faculty with missing data regarding outcomes of weekly burnout symptoms (N = 18), thoughts of attrition (N = 20), and suicidal thoughts (N = 18) were excluded.
Pearson’s X^2: Rao & Scott adjustment
Missing data rows are not displayed in the table for the following variables:
Discrimination: Overall (N=86; 2.7%); Male (N=51, 2.6%), Female (N=16, 1.8%), Unknown (N=19, 4.8%)
Bullying: Overall (N=76, 2.4%), Male (N=41, 2.1%), Female (N=15, 1.7%), Unknown (N=20, 5.1%)
Sexual Harassment: Overall (N=87, 2.7%), Male (N=47, 2.4%), Female (N=21, 2.4%), Unknown (N=19, 4.8%)
Mistreatment: Overall (N=60, 1.9%), Male (21, 1.6%), Female (12, 1.4$), Unknown (N-16, 4.1%)
Mistreatment and Workplace Exposures
Among all faculty, 66.2% reported exposure to any mistreatment type (88.6% of female faculty and 55.7% of male faculty). Bullying was reported by 54.4% of faculty (65.3% of female faculty and 49.4% of male faculty). Faculty identified colleagues (55.8%) and administration (54.4%) as the most common sources of bullying with similar frequencies among male and female faculty. Identity-based discrimination was reported by 46.3% of faculty (85.3% of female faculty and 28.4% of male faculty). Among female faculty who reported exposure to discrimination, nearly all (90.5%) identified patients as the most common source. Among male faculty who reported exposure to discrimination, more than half (58.2%) identified administration as the most common source. A higher percentage of female faculty reported nurses/support staff as a source of discrimination (58.0% vs 23.1% in men). Sexual harassment was reported by 13.2% of faculty (23.8% of female faculty and 8.8% of male faculty). Patients and colleagues were the most common sources of sexual harassment in both male and female respondents. Comprehensive details of mistreatment exposures and the sources from which faculty experienced those individual mistreatment types are outlined in Table 2 and Table 3.
Table 3.
Sources of Bullying, Discrimination, and Sexual Harassment among U.S. Surgical Faculty
| Bullying 1 | Sources of Bullying | Overall N = 1,760 | Male N = 970 | Female N = 570 | Unknown N = 220 |
| Administration | 958 (54.4%) | 567 (58.5%) | 268 (47.0%) | 123 (55.9%) | |
| Colleagues | 982 (55.8%) | 494 (50.9%) | 369 (64.7%) | 119 (54.1%) | |
| Nurses/Support Staff | 481 (27.3%) | 260 (26.8%) | 156 (27.4%) | 65 (29.5%) | |
| Patients | 697 (39.6%) | 369 (38.0%) | 246 (43.2%) | 82 (37.3%) | |
| Trainees | 379 (21.5%) | 199 (20.5%) | 137 (24.0%) | 43 (19.5%) | |
| Discrimination 1 | Sources of Discrimination | Overall N = 1,499 | Male N= 558 | Female N = 745 | Unknown N = 196 |
| Administration | 784 (52.3%) | 325 (58.2%) | 348 (46.7%) | 111 (56.6%) | |
| Colleagues | 818 (54.6%) | 263 (47.1%) | 450 (60.4%) | 105 (53.6%) | |
| Nurses/Support Staff | 647 (43.2%) | 129 (23.1%) | 432 (58.0%) | 86 (43.9%) | |
| Patients | 1,028 (68.6%) | 230 (41.2%) | 674 (90.5%) | 124 (63.3%) | |
| Trainees | 268 (17.9%) | 58 (10.4%) | 171 (23.0%) | 39 (19.9%) | |
| Sexual Harassment 1 | Sources of Sexual Harassment | Overall N = 425 | Male N = 172 | Female N = 207 | Unknown N = 46 |
| Administration | 33 (7.8%) | 14 (8.1%) | 13 (6.3%) | 6 (13.0%) | |
| Colleagues | 190 (44.7%) | 73 (42.4%) | 96 (46.4%) | 21 (45.7%) | |
| Nurses/Support Staff | 112 (26.4%) | 64 (37.2%) | 39 (18.8%) | 9 (19.6%) | |
| Patients | 234 (55.1%) | 77 (44.8%) | 132 (63.8%) | 25 (54.3%) | |
| Trainees | 45 (10.6%) | 21 (12.2%) | 16 (7.7%) | 8 (17.4%) |
Faculty were asked to either select that they “never” experienced at least one of 5 items for discrimination, 6 items for sexual harassment, and 7 items for bullying or they selected one or more sources listed above that they experienced the specific mistreatment type item from.
Faculty were able to select more than one source of mistreatment; thus, column totals may not equal 100%.
Over 70% of the faculty reported working 55 or more hours per week with about 18% reporting working greater than 70 hours per week on average. Faculty self-reported average nights on call per month with about one third working <5 nights while 28.7% reported working >7 nights. Just under half of respondents (47.0%) took <4 weeks of vacation the previous year (Table 1).
Factors Associated with Burnout
In multivariable models, faculty were more likely to report burnout if they were later in their career, took more call shifts, worked longer hours, worked in military institutions, or worked in the largest departments (Table 4). Compared to junior faculty less than 5 years into practice, more experienced faculty (i.e., 5–30 years into practice) were more likely to report burnout with a stepwise decrease over time in practice: faculty 5–10 years (aOR 1.93; 95% confidence interval [CI] 1.52–2.46), 11–20 years (aOR 1.67; 95%CI 1.29–2.16), and 21–30 years in practice (aOR 1.46, 95%CI 1.10–1.92). Stepwise increases in reported weekly burnout symptoms were reported by faculty who worked 5 or more nights on call per month on average (aOR 1.37, 95%CI 1.13–1.66 for 5–7 nights; aOR 1.58, 95%CI 1.30–1.93 for >7 nights) and those who worked 55 or more hours on average per week (aOR 1.27, 95%CI 1.03–1.55 for 55–61 hrs/week, aOR 1.91, 95%CI 1.49–2.43 for 62–70 hrs/week, and aOR 2.09, 95%CI 1.63–2.68 for >70 hours per week). Faculty were more likely to report burnout if working in military institutions compared to independent institutions (aOR 1.87, 95%CI 1.06–3.30) or in large (>39 surgical faculty) institutions (aOR 1.50, 95%CI 1.13–1.99). Overall, faculty who reported exposure to any mistreatment were nearly three times more likely to report burnout (aOR 2.90, 95% 2.38–3.53).
Table 4.
Characteristics Associated with Burnout among U.S. Surgical Faculty
| Excluding Mistreatment | Including Mistreatment | |||||
|---|---|---|---|---|---|---|
|
| ||||||
| Predictor | OR | 95% CI | p | OR | 95% CI | p |
|
| ||||||
| Gender | ||||||
| Male | Ref | Ref | Ref | Ref | Ref | Ref |
| Female | 1.30 | 1.06 – 1.60 | 0.014 | 0.95 | 0.77 – 1.18 | 0.66 |
| Unknown | 1.20 | 0.92 – 1.56 | 0.18 | 1.05 | 0.81 – 1.37 | 0.70 |
| Race/Ethnicity | ||||||
| NH White1 | Ref | Ref | Ref | Ref | Ref | Ref |
| Non-White2 | 0.90 | 0.76 – 1.08 | 0.26 | 0.87 | 0.73 – 1.03 | 0.11 |
| Unknown | 0.71 | 0.51 – 0.97 | 0.034 | 0.70 | 0.50 – 0.97 | 0.030 |
| Years in Practice | ||||||
| <5 yrs | Ref | Ref | Ref | Ref | Ref | Ref |
| 5 – 10 yrs | 2.01 | 1.59 – 2.54 | <0.001 | 1.93 | 1.52 – 2.46 | <0.001 |
| 11 – 20 yrs | 1.76 | 1.37 – 2.27 | <0.001 | 1.67 | 1.29 – 2.16 | <0.001 |
| 21 – 30 yrs | 1.49 | 1.14 – 1.95 | 0.004 | 1.46 | 1.10 – 1.92 | 0.008 |
| >30 yrs | 0.95 | 0.68 – 1.32 | 0.74 | 0.96 | 0.69 – 1.35 | 0.83 |
| Unknown | 6.48 | 0.67 – 62.8 | 0.11 | 6.69 | 1.07 – 42.0 | 0.043 |
| Surgical Specialty 3 | ||||||
| Other | Ref | Ref | Ref | Ref | Ref | Ref |
| ACS | 1.15 | 0.68 – 1.96 | 0.60 | 1.07 | 0.63 – 1.82 | 0.80 |
| Bariatric Surgery | 0.68 | 0.36 – 1.29 | 0.24 | 0.71 | 0.37 – 1.36 | 0.30 |
| Breast Surgery | 1.14 | 0.63 – 2.07 | 0.65 | 1.28 | 0.71 – 2.31 | 0.42 |
| Cardiothoracic | 0.78 | 0.42 – 1.44 | 0.42 | 0.78 | 0.42 – 1.44 | 0.42 |
| Colorectal Surgery | 1.24 | 0.69 – 2.23 | 0.48 | 1.24 | 0.69 – 2.24 | 0.47 |
| Endocrine Surgery | 0.71 | 0.31 – 1.61 | 0.42 | 0.73 | 0.32 – 1.64 | 0.44 |
| General Surgery | 1.10 | 0.63 – 1.92 | 0.73 | 1.05 | 0.60 – 1.85 | 0.85 |
| Pediatric Surgery | 1.02 | 0.57 – 1.81 | 0.95 | 0.99 | 0.56 – 1.75 | 0.96 |
| Plastic Surgery | 0.46 | 0.21 – 0.99 | 0.048 | 0.51 | 0.23 – 1.13 | 0.10 |
| Surgical Oncology | 0.85 | 0.48 – 1.52 | 0.59 | 0.82 | 0.46 – 1.47 | 0.51 |
| Transplant | 0.67 | 0.35 – 1.25 | 0.21 | 0.72 | 0.38 – 1.36 | 0.32 |
| Unknown | 5.07 | 0.59 – 43.4 | 0.14 | 4.49 | 0.45 – 44.4 | 0.20 |
| Vascular | 0.95 | 0.55 – 1.67 | 0.87 | 0.98 | 0.56 – 1.71 | 0.94 |
| Personal Compensation 4 | ||||||
| >= $750K | Ref | Ref | Ref | Ref | Ref | Ref |
| < $350K | 1.30 | 0.93 – 1.81 | 0.13 | 1.22 | 0.86 – 1.72 | 0.27 |
| $350–499K | 1.36 | 1.00 – 1.86 | 0.053 | 1.36 | 0.99 – 1.86 | 0.060 |
| $500–749K | 1.21 | 0.92 – 1.60 | 0.17 | 1.17 | 0.88 – 1.55 | 0.28 |
| Prefer not to answer | 0.70 | 0.44 – 1.11 | 0.13 | 0.73 | 0.45 – 1.19 | 0.21 |
| Unknown | 0.47 | 0.20 – 1.12 | 0.089 | 0.54 | 0.23 – 1.31 | 0.18 |
| Average Nights on Call 5 | ||||||
| <5 nights | Ref | Ref | Ref | Ref | Ref | Ref |
| 5–7 nights | 1.42 | 1.18 – 1.71 | <0.001 | 1.37 | 1.13 – 1.66 | 0.001 |
| >7 nights | 1.64 | 1.35 – 1.99 | <0.001 | 1.58 | 1.30 – 1.93 | <0.001 |
| Unknown | 1.05 | 0.56 – 1.99 | 0.87 | 1.03 | 0.54 – 1.97 | 0.93 |
| Vacation Time 6 | ||||||
| <4 weeks | Ref | Ref | Ref | Ref | Ref | Ref |
| 4–5 weeks | 0.96 | 0.81 – 1.14 | 0.64 | 1.04 | 0.87 – 1.23 | 0.69 |
| >5 weeks | 0.83 | 0.59 – 1.17 | 0.29 | 0.90 | 0.64 – 1.27 | 0.56 |
| Unknown | 1.15 | 0.61 – 2.17 | 0.67 | 1.30 | 0.68 – 2.50 | 0.43 |
| Average Work Hours 7 | ||||||
| Q1: <55 hrs/week | Ref | Ref | Ref | Ref | Ref | Ref |
| Q2: 55–61 hrs/week | 1.29 | 1.05 – 1.58 | 0.014 | 1.27 | 1.03 – 1.55 | 0.022 |
| Q3: 62–70 hrs/week | 2.07 | 1.63 – 2.62 | <0.001 | 1.91 | 1.49 – 2.43 | <0.001 |
| Q4: >70 hrs/week | 2.16 | 1.70 – 2.75 | <0.001 | 2.09 | 1.63 – 2.68 | <0.001 |
| Unknown | 1.24 | 0.69 – 2.23 | 0.47 | 1.40 | 0.81 – 2.42 | 0.23 |
| Relationship Status | ||||||
| Married/Relationship | Ref | Ref | Ref | Ref | Ref | Ref |
| Single/Divorced/Widowed | 1.22 | 0.93 – 1.60 | 0.16 | 1.24 | 0.94 – 1.64 | 0.13 |
| Unknown | 2.42 | 1.07 – 5.47 | 0.034 | 2.60 | 1.19 – 5.67 | 0.016 |
| Children | ||||||
| Yes Children | Ref | Ref | Ref | Ref | Ref | Ref |
| No Children | 1.27 | 1.02 – 1.59 | 0.037 | 1.25 | 1.00 – 1.56 | 0.052 |
| Unknown | 1.04 | 0.41 – 2.66 | 0.93 | 0.98 | 0.41 – 2.37 | 0.97 |
| Program Type | ||||||
| Independent | Ref | Ref | Ref | Ref | Ref | Ref |
| University Affiliated | 1.03 | 0.85 – 1.26 | 0.75 | 1.02 | 0.83 – 1.24 | 0.87 |
| Military | 1.74 | 0.97 – 3.13 | 0.063 | 1.87 | 1.06 – 3.30 | 0.031 |
| Unknown | 0.80 | 0.49 – 1.29 | 0.36 | 0.78 | 0.47 – 1.29 | 0.33 |
| Program Size | ||||||
| <19 Faculty | Ref | Ref | Ref | Ref | Ref | Ref |
| 19–26 Faculty | 1.06 | 0.78 – 1.43 | 0.72 | 1.03 | 0.76 – 1.40 | 0.84 |
| 27–39 Faculty | 1.30 | 0.98 – 1.72 | 0.069 | 1.30 | 0.98 – 1.73 | 0.067 |
| >39 Faculty | 1.49 | 1.12 – 1.98 | 0.006 | 1.50 | 1.12 – 1.99 | 0.006 |
| Program Location | ||||||
| Northeast | Ref | Ref | Ref | Ref | Ref | Ref |
| Southeast | 1.08 | 0.85 – 1.39 | 0.52 | 1.05 | 0.82 – 1.35 | 0.69 |
| Midwest | 1.16 | 0.89 – 1.50 | 0.27 | 1.16 | 0.89 – 1.51 | 0.27 |
| Southwest | 1.09 | 0.81 – 1.46 | 0.58 | 1.09 | 0.81 – 1.48 | 0.57 |
| West | 1.10 | 0.83 – 1.45 | 0.52 | 1.13 | 0.85 – 1.50 | 0.40 |
| Unknown | 0.87 | 0.51 – 1.50 | 0.63 | 1.18 | 0.67 – 2.09 | 0.56 |
| Mistreatment | ||||||
| No Mistreatment | Ref | Ref | Ref | |||
| Any Mistreatment | 2.90 | 2.38 – 3.53 | <0.001 | |||
| Unknown | 1.86 | 0.98 – 3.51 | 0.057 | |||
A total of 3,221 were included in the final cohort. Faculty with missing data regarding outcomes of weekly burnout symptoms (N = 18), thoughts of attrition (N = 20), and suicidal thoughts (N = 18) were excluded from the model.
Non-Hispanic White
Any race or ethnicity except Non-Hispanic White
Plastic Surgery includes Maxillofacial Surgery
Personal 2023 Compensation
Average monthly nights on call
Vacation time taken last year
Average weekly work hours
In models that did not adjust for mistreatment exposures, female faculty were more likely to report burnout (OR 1.30, 95%CI 1.06 to 1.60). However, after adjusting for mistreatment, no significant association was observed between faculty gender and burnout (aOR 0.95, 95%CI 0.77 to 1.18). Burnout was not significantly associated with faculty-reported surgical specialty, personal compensation, relationship status, parental status, vacation time, or geographic region (Table 4).
Factors Associated with Thoughts of Attrition
In multivariable models, faculty were more likely to have thoughts of attrition if they were mid-career, did not have children, had a lower salary, identified as non-White, or worked in university-affiliated programs. Compared to junior faculty with less than 5 years in practice, more experienced faculty (i.e., >20 years in practice) were more likely to report thoughts of attrition (Table 5). Faculty without children were more likely to report thoughts of attrition (aOR 1.32, 95%CI 1.05–1.67). Compared to faculty making more than $750K annually, faculty were more likely to report thoughts of attrition if reporting an annual salary <$350K (aOR 2.00, 95%CI 1.34–2.97) or $350–499K (aOR 1.81, 95%CI 1.29–2.53). Overall, faculty who reported exposure to any mistreatment were nearly three times more likely to have thoughts of attrition compared to faculty who did not report mistreatment (aOR 2.78, 95%CI 2.29–3.38).
Table 5.
Characteristics Associated with Thoughts of Attrition among U.S. Surgical Faculty
| Excluding Mistreatment | Including Mistreatment | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
| |||||||||||||
| Predictor | OR | 95% CI | p | OR | 95% CI | p | |||||||
|
| |||||||||||||
| Gender | |||||||||||||
| Male | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| Female | 0.93 | 0.75 – 1.16 | 0.522 | 0.69 | 0.55 – 0.87 | 0.001 | |||||||
| Unknown | 1.12 | 0.86 – 1.46 | 0.402 | 0.98 | 0.74 – 1.29 | 0.876 | |||||||
| Race/Ethnicity | |||||||||||||
| NH White1 | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| Non-White2 | 1.29 | 1.07 – 1.55 | 0.008 | 1.25 | 1.04 – 1.51 | 0.018 | |||||||
| Unknown | 1.01 | 0.71 – 1.44 | 0.969 | 1.01 | 0.71 – 1.42 | 0.977 | |||||||
| Years in Practice | |||||||||||||
| <5 yrs | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| 5 – 10 yrs | 1.45 | 1.10 – 1.91 | 0.008 | 1.37 | 1.04 – 1.82 | 0.026 | |||||||
| 11 – 20 yrs | 1.31 | 1.00 – 1.72 | 0.050 | 1.23 | 0.93 – 1.62 | 0.143 | |||||||
| 21 – 30 yrs | 1.65 | 1.24 – 2.19 | <0.001 | 1.61 | 1.21 – 2.14 | 0.001 | |||||||
| >30 yrs | 3.49 | 2.57 – 4.72 | <0.001 | 3.79 | 2.74 – 5.24 | <0.001 | |||||||
| Unknown | 1.45 | 0.14 – 15.4 | 0.755 | 1.33 | 0.15 – 11.6 | 0.793 | |||||||
| Surgical Specialty 3 | |||||||||||||
| Other | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| ACS | 1.10 | 0.64 – 1.90 | 0.726 | 1.01 | 0.57 – 1.81 | 0.962 | |||||||
| Bariatric Surgery | 0.56 | 0.28 – 1.12 | 0.099 | 0.57 | 0.27 – 1.18 | 0.132 | |||||||
| Breast Surgery | 1.10 | 0.58 – 2.08 | 0.781 | 1.19 | 0.61 – 2.33 | 0.617 | |||||||
| Cardiothoracic | 0.95 | 0.49 – 1.84 | 0.883 | 0.94 | 0.47 – 1.89 | 0.869 | |||||||
| Colorectal Surgery | 0.79 | 0.43 – 1.46 | 0.447 | 0.77 | 0.41 – 1.47 | 0.433 | |||||||
| Endocrine Surgery | 0.65 | 0.32 – 1.34 | 0.246 | 0.65 | 0.31 – 1.37 | 0.262 | |||||||
| General Surgery | 1.16 | 0.67 – 2.00 | 0.603 | 1.11 | 0.62 – 2.00 | 0.727 | |||||||
| Pediatric Surgery | 1.15 | 0.59 – 2.26 | 0.681 | 1.11 | 0.55 – 2.24 | 0.774 | |||||||
| Plastic Surgery | 0.94 | 0.45 – 1.99 | 0.874 | 1.03 | 0.47 – 2.26 | 0.940 | |||||||
| Surgical Oncology | 0.88 | 0.47 – 1.64 | 0.678 | 0.85 | 0.44 – 1.66 | 0.636 | |||||||
| Transplant | 0.85 | 0.44 – 1.63 | 0.618 | 0.92 | 0.47 – 1.81 | 0.806 | |||||||
| Unknown | 0.99 | 0.19 – 5.22 | 0.991 | 0.85 | 0.16 – 4.61 | 0.854 | |||||||
| Vascular | 1.33 | 0.73 – 2.43 | 0.348 | 1.36 | 0.74 – 2.53 | 0.324 | |||||||
| Personal Compensation 4 | |||||||||||||
| >= $750K | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| < $350K | 2.04 | 1.40 – 2.99 | <0.001 | 2.00 | 1.34 – 2.97 | <0.001 | |||||||
| $350–499K | 1.77 | 1.28 – 2.46 | <0.001 | 1.81 | 1.29 – 2.53 | <0.001 | |||||||
| $500–749K | 1.23 | 0.90 – 1.68 | 0.194 | 1.21 | 0.88 – 1.66 | 0.246 | |||||||
| Prefer not to answer | 0.99 | 0.65 – 1.51 | 0.948 | 1.06 | 0.68 – 1.65 | 0.803 | |||||||
| Unknown | 0.14 | 0.03 – 0.60 | 0.008 | 0.15 | 0.03 – 0.67 | 0.013 | |||||||
| Average Nights on Call 5 | |||||||||||||
| <5 nights | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| 5–7 nights | 1.15 | 0.94 – 1.41 | 0.161 | 1.10 | 0.90 – 1.35 | 0.335 | |||||||
| >7 nights | 1.12 | 0.90 – 1.39 | 0.295 | 1.06 | 0.85 – 1.33 | 0.581 | |||||||
| Unknown | 1.59 | 0.75 – 3.38 | 0.225 | 1.52 | 0.68 – 3.40 | 0.305 | |||||||
| Vacation Time 6 | |||||||||||||
| <4 weeks | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| 4–5 weeks | 0.92 | 0.77 – 1.10 | 0.370 | 0.99 | 0.83 – 1.19 | 0.920 | |||||||
| >5 weeks | 0.93 | 0.70 – 1.22 | 0.578 | 1.02 | 0.77 – 1.33 | 0.908 | |||||||
| Unknown | 0.93 | 0.45 – 1.93 | 0.852 | 1.02 | 0.47 – 2.24 | 0.958 | |||||||
| Average Work Hours 6 | |||||||||||||
| <55 hrs/week | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| 55–61 hrs/week | 0.93 | 0.75 – 1.16 | 0.518 | 0.90 | 0.73 – 1.12 | 0.352 | |||||||
| 62–70 hrs/week | 0.99 | 0.76 – 1.28 | 0.928 | 0.89 | 0.69 – 1.15 | 0.373 | |||||||
| >70 hrs/week | 1.24 | 0.96 – 1.60 | 0.096 | 1.18 | 0.90 – 1.53 | 0.226 | |||||||
| Unknown | 0.37 | 0.18 – 0.76 | 0.007 | 0.38 | 0.18 – 0.79 | 0.009 | |||||||
| Relationship Status | |||||||||||||
| Married/Relationship | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| Single/Divorced/Widowed | 1.19 | 0.90 – 1.58 | 0.213 | 1.21 | 0.91 – 1.61 | 0.199 | |||||||
| Unknown | 2.00 | 0.69 – 5.83 | 0.202 | 2.11 | 0.74 – 6.01 | 0.164 | |||||||
| Parental Status | |||||||||||||
| Yes Children | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| No Children | 1.34 | 1.07 – 1.69 | 0.011 | 1.32 | 1.05 – 1.67 | 0.018 | |||||||
| Unknown | 0.87 | 0.26 – 2.87 | 0.816 | 0.82 | 0.26 – 2.58 | 0.734 | |||||||
| Program Type | |||||||||||||
| Independent | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| University Affiliated | 1.26 | 1.03 – 1.53 | 0.023 | 1.25 | 1.02 – 1.52 | 0.029 | |||||||
| Military | 1.56 | 0.85 – 2.86 | 0.147 | 1.67 | 0.95 – 2.93 | 0.076 | |||||||
| Unknown | 0.83 | 0.57 – 1.20 | 0.325 | 0.81 | 0.54 – 1.21 | 0.299 | |||||||
| Program Size | |||||||||||||
| <19 Faculty | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| 19–26 Faculty | 0.77 | 0.58 – 1.04 | 0.093 | 0.76 | 0.56, 1.03 | 0.074 | |||||||
| 27–39 Faculty | 0.88 | 0.65 – 1.18 | 0.393 | 0.89 | 0.65, 1.20 | 0.439 | |||||||
| >39 Faculty | 0.96 | 0.73 – 1.26 | 0.752 | 0.95 | 0.72, 1.25 | 0.715 | |||||||
| Program Location | |||||||||||||
| Northeast | Ref | Ref | Ref | Ref | Ref | Ref | |||||||
| Southeast | 0.93 | 0.75 – 1.16 | 0.532 | 0.90 | 0.73 – 1.12 | 0.351 | |||||||
| Midwest | 1.16 | 0.91 – 1.47 | 0.224 | 1.16 | 0.90 – 1.48 | 0.254 | |||||||
| Southwest | 0.81 | 0.63 – 1.03 | 0.089 | 0.81 | 0.63 – 1.03 | 0.089 | |||||||
| West | 1.05 | 0.82 – 1.33 | 0.709 | 1.08 | 0.85 – 1.37 | 0.529 | |||||||
| Unknown | 0.19 | 0.13 – 0.29 | <0.001 | 0.26 | 0.17 – 0.39 | <0.001 | |||||||
| Mistreatment | |||||||||||||
| No Mistreatment | Ref | Ref | Ref | ||||||||||
| Any Mistreatment | 2.78 | 2.29 – 3.38 | <0.001 | ||||||||||
| Unknown | 2.47 | 1.38 – 4.40 | 0.002 | ||||||||||
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
A total of 3,221 were included in the final cohort. Faculty with missing data regarding outcomes of weekly burnout symptoms (N = 18), thoughts of attrition (N = 20), and suicidal thoughts (N = 18) were excluded from the model.
Non-Hispanic White
Any race or ethnicity except Non-Hispanic White
Plastic Surgery includes Maxillofacial Surgery
Personal 2023 Compensation
Average monthly nights on call
Vacation time taken last year
Average weekly work hours
In models that did not adjust for mistreatment exposures, there was no significant difference between thoughts of attrition and gender identity. However, after adjusting for mistreatment, female faculty were less likely to report thoughts of attrition compared to male faculty (aOR 0.69, 95%CI 0.55–0.87). The association between thoughts of attrition and non-White race/ethnicity persisted in models adjusted for mistreatment (aOR 1.25, 95%CI 1.04–1.51).
DISCUSSION
We report a national study of surgical faculty from all ACGME-accredited U.S. general surgery residency programs to evaluate surgeon well-being, prevalence of mistreatment, and factors associated with well-being. In our analysis, approximately one-third of faculty experienced burnout or reported thoughts of attrition. Two thirds of faculty reported experiencing some form of mistreatment. Female faculty reported high prevalence of each mistreatment type, particularly discrimination. Overall, male and female faculty identified their colleagues as common sources of bullying and discrimination, whereas patients were identified as common sources of sexual harassment. Adjusted models demonstrated higher rates of burnout among surgical faculty reporting mistreatment, high call and work burden. Female faculty were more likely to report burnout in models not adjusted for mistreatment. However, when adjusting for the higher rates of mistreatment experienced by female faculty, they were no more likely to have symptoms of burnout. These results offer a national assessment of well-being and mistreatment among surgical faculty that may be considered for use in local well-being improvement efforts.
The rates of weekly burnout symptoms reported in this study align with prior estimates, which have ranged from 30 to 60%.[6, 25] In a large, national survey evaluating the well-being of surgical trainees, 38.5% of surgical trainees reported experiencing burnout.[9] The observed rate of thoughts of attrition in this study is also similar to previously reported studies estimating that 32% of faculty have reported at least a moderate likelihood of leaving their current practice.[23] This study provides a contemporary assessment of these well-being measures, demonstrating no substantial improvement over the last 18 years despite increasing general focus on well-being in the workplace. Notably, surgical trainees cited a substantially lower prevalence of thoughts of attrition (12.6%).[26] While attrition of surgical trainees is not directly comparable to attrition of surgical faculty due to increased flexibility in faculty positions, these stark numbers and lack of apparent improvement after “promotion” to faculty from training further highlight the urgent need to address well-being in the entirety of the surgical workforce.
Previous literature has shown that mistreatment is a factor in the work environment that contributes to poor surgeon well-being, but this study provides the most comprehensive assessment of surgical faculty mistreatment to date.[9, 27] Our results demonstrate both significantly higher rates of mistreatment among female faculty and variation in the sources of mistreatment, with female faculty highlighting relatively higher rates of mistreatment due to patients and nurses/support staff. This finding suggests that female surgeons may be exposed to discrimination by groups with less authority more often than male surgeons, despite an inherent power imbalance in those groups. These reported mistreatment rates are slightly higher than rates reported in a national survey of general surgery residents with a robust response rate, which may be due to nonresponse bias in our current study.[9] There were also similar findings among faculty as in trainees regarding the intersection of gender, mistreatment and burnout, with the addition of mistreatment to models of burnout abrogating associations between gender and burnout. These findings suggest that measures to mitigate mistreatment in the work environment may serve to improve poor well-being, particularly for female surgical faculty and trainees.
There are clearly workplace exposures outside of mistreatment that may contribute to poor well-being. This study found higher likelihood of burnout in faculty who took more call shifts, worked more hours, or worked in larger programs. Faculty also had higher likelihood of considering leaving their current job if they were childless, had a lower salary, identified as non-White, or worked at university-affiliated program. Other studies have described an association between workplace factors and job dissatisfaction among academic physicians, including personal-organization values alignment, control over schedule, reimbursement and paperwork.[1, 28, 29] Some of these structural workplace factors may be more easily intervened upon than workplace mistreatment and provide actionable targets for interventions to improve surgical faculty well-being.
Taken together, these data are a call to action for the surgical community to continue to address well-being, particularly among surgical faculty. Efforts to address well-being over the last decade have been substantial and often focused on surgical trainees, including the Surgical Education Culture Optimization through Targeted Interventions Based on National Comparative Data (SECOND) Trial which was successful in improving burnout amongst trainees through targeted interventions.(Hu, Eng, Amortegui, et al). Early qualitative data have indicated significant concern among faculty that interventions to improve trainee well-being may shift work toward the faculty and negatively impact faculty well-being, especially at academic institutions heavily reliant on the resident workforce. We believe that the results of this study, paired with ongoing concerns about shifting workload, reimbursement, and loss of faculty physician autonomy, make organized and concentrated efforts to improve the faculty workplace environment of paramount importance. The ACS recently published specialty-specific workplace standards for surgeons to address distinctive workplace demands such as sleep deprivation, inadvertent exploitation, and excessive workload that can lead to the outcomes of attrition and burnout that we explored in our study.[30] In their article, they identify that physicians are held to a moral commitment to professionalism, duty and patient accountability; however, based on the prevalence of burnout, attrition, and suicidality, safeguards must be in place to support the surgeon workforce. A national, longitudinal analysis evaluating sex differences in physician attrition from clinical practice found that female physicians are more likely to leave clinical practice than their male counterparts at every age and across specialties.[31] These results are striking especially in the setting of the predicted physician shortage within the next decade; however, work from our group seeks to identify workplace factors that may explain gender differences in well-being. As in our current analysis, when mistreatment is controlled for, female surgeons are actually less likely to consider leaving. Prevalence rates of well-being among surgeons are important to highlight, but there is a need to identify modifiable factors for targeted interventions to improve the workplace environment.
Such will be the focus of the Trial to Harness and Improve Well-being and Resilience in Departments of Surgery (THIRD). It must be acknowledged that such efforts may be more complex than its predecessor, the SECOND trial, but we believe that these results indicate actionable targets for local interventions to improve faculty well-being. Globally reported rates of faculty well-being have been published, but interventions at the institutional level are needed. Additionally, these granular data regarding workplace exposure rates according to specific institution characteristics, mistreatment types and sources of mistreatment will help future studies to more precisely target areas in need of improvement. The General Surgery Research Collaborative on Resident Wellbeing recently published a study examining the importance of workplace elements which differed by gender and race.[32] Such work can guide targeted interventions at the institution-level taking into consideration distinct needs. Ultimately, the goal of improving surgeon well-being lies in an effort to prevent surgeon attrition, improve patient outcomes, patch the leaky pipeline, and support meaning at work. Dr. Rosenbaum has previously described that the framing of physician distress as burnout and “moral injury” highlights the relationship between well-being and meaningful work.[33] Recently, research teams are dedicating time and resources into well-being research for faculty and trainees. For our team, and as described by others, the overarching goal is to foster a safe workplace environment to allow us to finally reclaim meaning and joy in Medicine.
This study has several important limitations. First, the survey was cross-sectional in nature and thus can only define point prevalence. Longitudinal data would provide a more robust and comprehensive assessment of the faculty workplace environment and well-being over time. Second, survey items corresponding to the mistreatment exposures of discrimination, bullying, and sexual harassment were intentionally undefined in the survey. Literature suggests that the use of “labeled measures,” may lead to respondent underreporting of mistreatment; however, we used unlabeled measures to capture the nuances of mistreatment as perceived by the individual.[34] Third, our survey response rate of 30% introduces non-response bias, which may lead to over- or underestimation of exposures and outcomes. Despite this, we publish these results given they should be generalizable to the surgeon workforce of today. Within our missing data, 12.6% of respondents did not self-identify gender and 6.6% of respondents did not self-identify race and/or ethnicity. Although the survey was preempted by introductory statements indicating that all data would be de-identified, understandably some respondents could still fear identification. Multiple iterations of the post-ABSITE survey has been shared, but this is the first iteration of the survey distributed to all general surgery faculty so we anticipated less engagement. We are hopeful that response rates will increase with subsequent iterations. According to recent Association of American Medical Colleges U.S. Physician Workforce Data Dashboard, there are between 61–65% White and about 26% female general surgeons in various specialties. This demographic data is comparable to our survey respondents.[35] It is possible, however, that respondents who did not disclose their gender and race may lead to underestimation of gender and race-related mistreatment survey items.[36] Overall, our response rate is in line with other national surveys of academic faculty.[37] Fourth, there are undoubtedly unmeasured institutional factors (e.g., recent mergers, faculty turnover, overall financial stability of the institution) that may influence overall well-being that our survey did not capture. Finally, given the cross-sectional nature of our study we are unable to conclude any causality between the association of mistreatment and likelihood of burnout or thoughts of attrition.
Conclusion
Burnout, thoughts of attrition, and mistreatment are common among surgical faculty, especially female surgeons. Exposure to any type of mistreatment and multiple workplace factors (e.g., call burden) was associated with burnout or thoughts of attrition among surgery faculty. Gendered disparities in mistreatment may influence poorer overall well-being among female faculty. These results provide potential modifiable targets to improve the well-being of surgeons.
Supplementary Material
DISCUSSANT.
DR. JULIE ANN SOSA (San Francisco, CA): This paper addresses the critically important question of faculty well-being in academic surgery, which is an area that has been less studied than trainee well-being.
The authors conducted a national cross-sectional survey via the ACGME in 2024, with over 3,200 respondents across all U.S. general surgery programs. Even with a 30% response rate, this is definitely a large and important dataset.
Three findings stand out. First, the prevalence of distress remains extremely high - unacceptably high. About 35% of the faculty report weekly burnout, 30% are considering leaving, and 4.4% report suicidal ideation. These rates suggest that despite increased attention to well-being, there has been little meaningful improvement for faculty. Second, mistreatment is common and disproportionately affects women. About two-thirds reported mistreatment, with nearly 90% of women affected. Notably, women most often cite patients as the source of discrimination, while men more often cite administration. This broadens the scope of where interventions need to focus. Third, mistreatment appears to mediate burnout. Women initially showed higher burnout rates, but the difference disappeared after adjusting for mistreatment. This suggests that disparities in burnout may be driven by exposure to mistreatment rather than gender itself. At the same time, traditional factors like long hours, call burden, and large departments remain strongly associated with burnout, while lower compensation, non-White race, and lack of children are linked to attrition. Overall, this study really reframes faculty well-being as a structural issue, not just an institutional one. It also raises concern that improvements in trainee wellbeing may be shifting burden onto faculty.
It highlights the persistence of burnout and identifies mistreatment and workplace structure as key, potentially modifiable factors.
There are three areas where it would be good to extend your discussion:
Regarding causality vs association, can we conclude mistreatment drives burnout, or might burnout influence how mistreatment is perceived and reported?
With a 30% response rate, are the estimates you provided likely inflated or potentially understated? Can you tell us a little bit about who is missing from the dataset you presented? And finally, regarding actionability: If patients are a major source of discrimination, what are realistic institutional interventions that could be adopted to address that?
DR. AMY HOLMSTROM (Indianapolis, IN): I'll start with your first question about mistreatment perception.
We use unlabeled measures, so we don't ask, have you been mistreated? Have you been bullied? Have you been sexually harassed? We ask specific behavior questions and then ask if they experienced it and who their source was.
So I think that to be very specific and granular helps to avoid -- in fact, I think it makes the responses higher. It might make it look like people are experiencing these behaviors more frequently, but I would argue that most surveys are likely not capturing the true nature of mistreatment experience.
I do agree that if people are experiencing more burnout, perhaps they're more likely to answer that they're experiencing those behaviors, and I can't say for sure.
Your next question was about who is missing, because our response rate is 30%, and I certainly wish I knew. But I can tell you that based on our demographic data, it looks like we have a good representation based on gender and race/ethnicity, based on what AAMC surgeon workforce looks like. So my hope is that it's a relatively broad sampling and we can never tell who actually is missing.
Regarding actionability, I think that the granularity of the data, as far as the sources of various mistreatment behaviors, do make this actionable. Every department will look a little different. An example of something that I saw while working in a VA was a public service campaign. In their main lobbies, they had these large person-height posters and it was a female physician or staff member that said, “my name is Doctor, not Sweetheart” or something to that effect. I really felt as though even if that didn't change patient perceptions, it made me feel that the VA was taking this seriously and they were trying to make the staff and faculty who work there feel supported.
DR. DOUGLAS WOOD (Seattle, WA): Dr. Holmstrom, I look forward to seeing the manuscript because there is work that we are doing in the American College of Surgeons that is responsive to this problem of surgeon lack of autonomy and burnout. While it does not address the mistreatment part of what you're bringing up, the College Board of Regents approved a document of Workplace Standards for Surgeons in October that was published in the Journal of the American College of Surgeons in March. I encourage people to look at this paper because it is trying to address this issue of burnout among surgeons, and a lot of it is related to lack of autonomy in our workplace and ability to control work hours and call schedule like you have described. What I'm recognizing, from listening to your talk, is we have not addressed mistreatment or the gender disparities and their impact. Do you have suggestions for us of how we could try to incorporate that as well into this guidance that is now being developed by 13 specialty organizations to create their own workplace standards?
DR. AMY HOLMSTROM (Indianapolis, IN): I would say certainly we would be happy to partner, and I think using national data to guide interventions is wonderfully helpful. However, I don't think there's going to be one rollout intervention that everyone can do because it depends locally what the sources are and what the main problem for mistreatment is. But I think you could certainly develop, like what we're doing is developing a toolkit.
So if you know locally, your problem is sexual harassment, these are some toolkit items that address that, versus if your problem is discrimination from patients, here's some suggested items for that.
So that's the route I would take.
DR. JUSTIN SACKS (St. Louis, MO): Incredible work, timely and impactful.
As a certain scientist, I always try to think about first principles. So not trying to assign what the cause of this is, where in this study did you discuss sleep deprivation with the respondees? Because I really think that when you get down to it, sleep deprivation, with all the things you mentioned, can lead to cognitive dissonance and issues with burnout. So where in that was that discussed or asked?
DR. AMY HOLMSTROM (Indianapolis, IN): We did not ask about sleep deprivation. I don't necessarily think work hours or call burden are a complete surrogate for that, but certainly if you're working in the greater than 70 hours per week, I suspect there's some sleep deprivation, but that's an excellent idea for future iterations of the survey.
DR. TERRENCE FULLUM (Washington, DC): Looking at well-being and burnout, I saw that the more call you took, the greater the incidence of well-being and burnout.
So I thought about my own faculty. And my trauma surgeons, acute care surgeons and neurosurgeons who take call, they seem to be the happiest. They make the most money. They generate the most revenue.
So did you look at specialties or subspecialties? Were there any independent risk factors for being in any specialty and the incidence of burnout in your study?
DR. AMY HOLMSTROM (Indianapolis, IN): There were no significant associations by specialty with burnout or with thoughts of attrition. I think professional fulfillment is a big part of the work and the job. And those people, you know, they're happy taking call. And I think that that's fine.
DR. JULIE FREISCHLAG (Winston Salem, NC): I think it is very important that we continue to look into factors that will make people have joy in their job and make them enjoy others around them.
The issues with patients is a bigger deal that needs to be addresses.
We have actually taken a stand that if you have a patient that is misbehaving, mainly inpatient where you can see it more than outpatient, we have the right to fire that patient. There's many institutions that have done that.
Then we also have done a lot of bystander training mainly for our students and faculty to help deal with that. So when something is said or done that is not ok, you as a leader need to say something at the time, i so people don't think you condone that to make that happen.
The last thing I want to ask about is peer mentoring.
We've started peer mentoring courses where we put six people together that are not in the same department. They don't report to each other, and we have a leader that meets with them every month in person if possible and discusses things such as having about tough conversations and making hard decisions. Following the 6 month course, they continue to go on and meet with each other. The in-person piece is really important to do that.
My question to you was, what do you think this has to do with lack of in-person ability to talk to somebody else, to hear what you're seeing and doing?
DR. AMY HOLMSTROM (Indianapolis, IN): I completely agree. I think peer mentoring and coaching is something that has become really popular for good reason. There's good evidence that coaching helps.
So I think professional development, leadership development by way of peer mentoring, figuring out how to resolve conflict, being able to vent, I think that's incredibly important and I think valuable to certainly consider including in our toolkits.
DR. BRENESSA LINDEMAN (Birmingham, AL): Congratulations to you and your colleagues on this well-presented, broad and what is sure to be impactful work.
If you could theorize, and I recognize you can't have a concrete answer to this question, but having the survey come from the ACGME, do you think that having it administered by such an authoritative body had an impact on the response rate, either positively or negatively?
The second question is somewhat related to Dr. Sosa's comment in that thinking to the future, I'm curious whether you may have plans to examine faculty well-being data in concert with resident well-being data.
I could certainly never argue that many of these challenges are structural. However, I might also think that there are institutional hotspots where the problem is worse than in others, and that while improved resident well-being might contribute to worsened faculty well-being, my own opinion is that the learning and working environment is a milieu shared by everyone and that negative things tend to roll downhill.
So, worsened well-being for one group likely impacts well-being for the other. I'm hopeful that your group may take on such work, and interested in your thoughts, with thanks.
DR. AMY HOLMSTROM (Indianapolis, IN): To your first question regarding the ACGME. I think it probably depended on who was reading the email. Some people said, I don't want to take this. And other people thought, well, this is important. I should take it.
So I think the response rate was going to be about this, regardless. So I wish we could have done better, and I hope that everyone in the room will consider taking the survey and encouraging your colleagues to take it as well.
Regarding faculty and resident well-being, yes, we intend to look at them together. We've had the same thought of, does well-being improving in one group worsen in the other? Or is it more of a cultural thing and everyone's unwell versus everyone's doing well? And we are looking at that.
DR. CHERISSE BERRY (Newark, NJ): Excellent presentation. Very well done and an important study.
I wanted to ask whether you have begun to disaggregate the data to examine outcomes across more granular subgroups. When analyses are limited to binary gender categories, there is a risk of obscuring important differences across intersecting identities. Have you explored this further, and if so, are there any emerging findings you can share?
DR. AMY HOLMSTROM (Indianapolis, IN): We are looking at all forms of the data, and we even have missing data, which is a whole separate thing that we'll have to do something with. But I don't have any alternative analyses to share with you today. We're certainly looking at other analyses to understand this data better.
DR. CHERISSE BERRY (Newark, NJ): Thank you. Just to clarify, are your current analyses examining outcomes across intersecting demographic factors, such as gender in combination with race and ethnicity?
DR. AMY HOLMSTROM (Carmel, IN): Yes, gender versus race and ethnicity, yes, we've been looking into that.
Funding Sources:
This body of work was supported by a grant from the ACGME and ACS. The sponsoring organizations had no role in the design, conduct, or reporting of the study.
Footnotes
Conflict of Interest Disclosure: Conflict of Interest Disclosure: Dr. Bilimoria reported receiving grants from the American College of Surgeons (ACS) and the Accreditation Council of Graduate Medical Education (ACGME). Dr. Brue is supported by training grant T32CA282070 (PI: Bilimoria) from the National Cancer Institute. Dr. Huber is supported in part by Grant T32 TR004389 (Thomas D. Hurley, PI, Mary Ann McDowell, co-PI) from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award. No other disclosures were reported.
Meeting Information: This work was presented at the American Surgical Association 146th meeting in Seattle, Washington on April 23, 2025.
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