Skip to main content
JAMA Network logoLink to JAMA Network
. 2020 Dec 9;3(12):e2028780. doi: 10.1001/jamanetworkopen.2020.28780

Association of Physician Burnout With Suicidal Ideation and Medical Errors

Nikitha K Menon 1, Tait D Shanafelt 2, Christine A Sinsky 3, Mark Linzer 4, Lindsey Carlasare 3, Keri J S Brady 5, Martin J Stillman 4, Mickey T Trockel 1,
PMCID: PMC7726631  PMID: 33295977

This cross-sectional study uses data from surveys completed by US physicians to examine associations between physician burnout, suicidal ideation, and self-reported medical errors after adjusting for depression.

Key Points

Question

Is burnout associated with increased suicidal ideation and self-reported medical errors among physicians after accounting for depression?

Findings

In this cross-sectional study of 1354 US physicians, burnout was significantly associated with increased odds of suicidal ideation before but not after adjusting for depression and with increased odds of self-reported medical errors before and after adjusting for depression. In adjusted models, depression was significantly associated with increased odds of suicidal ideation but not self-reported medical errors.

Meaning

The findings suggest that depression but not burnout is directly associated with suicidal ideation among physicians.

Abstract

Importance

Addressing physician suicide requires understanding its association with possible risk factors such as burnout and depression.

Objective

To assess the association between burnout and suicidal ideation after adjusting for depression and the association of burnout and depression with self-reported medical errors.

Design, Setting, and Participants

This cross-sectional study was conducted from November 12, 2018, to February 15, 2019. Attending and postgraduate trainee physicians randomly sampled from the American Medical Association Physician Masterfile were emailed invitations to complete an online survey in waves until a convenience sample of more than 1200 practicing physicians agreed to participate.

Main Outcomes and Measures

The primary outcome was the association of burnout with suicidal ideation after adjustment for depression. The secondary outcome was the association of burnout and depression with self-reported medical errors. Burnout, depression, suicidal ideation, and medical errors were measured using subscales of the Stanford Professional Fulfillment Index, Maslach Burnout Inventory–Human Services Survey for Medical Personnel, and Mini-Z burnout survey and the Patient-Reported Outcomes Measurement Information System depression Short Form. Associations were evaluated using multivariable regression models.

Results

Of the 1354 respondents, 893 (66.0%) were White, 1268 (93.6%) were non-Hispanic, 762 (56.3%) were men, 912 (67.4%) were non–primary care physicians, 934 (69.0%) were attending physicians, and 824 (60.9%) were younger than 45 years. Each SD-unit increase in burnout was associated with 85% increased odds of suicidal ideation (odds ratio [OR], 1.85; 95% CI, 1.47-2.31). After adjusting for depression, there was no longer an association (OR, 0.85; 95% CI, 0.63-1.17). In the adjusted model, each SD-unit increase in depression was associated with 202% increased odds of suicidal ideation (OR, 3.02; 95% CI, 2.30-3.95). In the adjusted model for self-reported medical errors, each SD-unit increase in burnout was associated with an increase in self-reported medical errors (OR, 1.48; 95% CI, 1.28-1.71), whereas depression was not associated with self-reported medical errors (OR, 1.01; 95% CI, 0.88-1.16).

Conclusions and Relevance

The results of this cross-sectional study suggest that depression but not physician burnout is directly associated with suicidal ideation. Burnout was associated with self-reported medical errors. Future investigation might examine whether burnout represents an upstream intervention target to prevent suicidal ideation by preventing depression.

Introduction

Studies have shown that a career in medicine is associated with increased risk of suicide.1,2,3,4,5,6 A recent analysis7 suggests that the increased risk for suicide among attending physicians may be declining or previously overestimated. However, reports among physicians in training indicate an association with increased risk for suicide1,2,3 despite certain risk factors associated with suicide in the general population (eg, financial constraints, job security) being uncommon in medicine. Approximately 1 in 10 medical students,1 1 in 4 interns,8 and 1 in 16 practicing physicians9 report some degree of suicidal ideation. Although medical students exhibit better mental health indexes than do age-matched peers at matriculation, these measures decline during the course of their education.2

Depression, substance abuse, impaired relationships, self-destructive tendency, and guilty self-concept10 are associated with physician suicide.7 Suicidal ideation has also been associated with occupation-specific factors, including practicing psychiatry or anesthesiology,7 increased workload volume,7 being evaluated as unfit to practice,11 perceived medical errors by surgeons,9 workplace harassment, and lack of empowering leadership among postgraduate physicians in training.12 Previous research also identifies burnout—an occupational syndrome recognized by the World Health Organization13 and experienced by physicians at epidemic levels14,15—as a factor associated with both depression and suicide in physicians and physicians in training.4,9,16 The complex nature of these associations may contribute to remaining controversy about whether burnout and depression are discrete constructs vs gradations of the same underlying disorder,17 despite results of a recent meta-analysis reporting that burnout and depression are different constructs.18 Whether burnout increases risk of suicide after accounting for symptoms of depression is unclear; studies suggesting that burnout is associated with increased risk for suicidal ideation lack control for comorbid depression,9,16,19 and the few that control for it often use the Primary Care Evaluation of Mental Disorders (PRIME-MD),4,9 a 2-item screening tool that may not be an optimal measure of symptom severity or specificity.20,21 An analogous pattern exists between physician distress and patient care outcomes; both burnout and depression are associated with occupational consequences,22,23,24,25,26 including errors,27 in studies that often do not optimally account for both.20,28,29

Addressing physician well-being and reducing suicide risk requires understanding the associations between physician distress, including burnout and depression, and personal and professional outcomes. The primary objective of this study was to investigate whether burnout is associated with increased risk of suicidal ideation after accounting for concurrent symptoms of depression. The secondary objective of this study was to investigate whether depression and burnout are independently associated with self-reported medical errors. Preparatory to these aims was to explore divergent validity between burnout and depression assessment items using instruments frequently used to assess physician burnout and a validated measure30,31,32 of symptoms specific to depression (ie, not including nonspecific vegetative symptoms). This preparatory step provided evidence supporting the assumption that burnout and depression are distinct constructs in the data analyzed for this study, a necessary assumption of the study aims. We hypothesized that physician depression, but not burnout, would be directly associated with increased risk of suicidal ideation.

Methods

Study Population

This cross-sectional study used survey data collected between November 12, 2018, and February 15, 2019, from 1354 physicians practicing throughout the US. To assemble a representative convenience sample (≥1200 individuals), populations of 70% attending and 30% postgraduate trainee physicians of all age groups, sexes, and specialties were randomly sampled from the American Medical Association Physician Masterfile and invited in waves to participate. Participants were offered a small financial incentive to complete a confidential, voluntary electronic survey (including a prerequisite survey item obtaining informed consent). The study protocol was approved by the institutional review boards at Stanford University and the University of Illinois at Chicago. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies.33

Measures

Burnout was assessed using subscales of 3 measures: the Stanford Professional Fulfillment Index (PFI),34 the Maslach Burnout Inventory–Human Services Survey for Medical Personnel (MBI),35 and the Mini-Z burnout survey.36 The PFI includes 2 subscales assessing burnout (4 work exhaustion items and 6 interpersonal disengagement items) that are scored using a 5-point Likert scale from “not at all” (0) to “extremely” (4).34 This measure has shown reliability, construct validity, and sensitivity to change among physicians.34,37,38 The MBI assesses analogous subscales (9 emotional exhaustion items and 5 depersonalization items) scored using a 7-point frequency-based Likert scale from “never”(0) to “every day” (6).39 Work exhaustion and interpersonal disengagement in the PFI are conceptually similar to emotional exhaustion and depersonalization in the MBI. The MBI is a measure of burnout with well-documented reliability and validity,39,40,41,42 including concurrent validity (correlations with occupational variables in expected directions among physicians).22,23,24,43 The Mini-Z burnout survey’s single item requests that respondents characterize their experience using their own definition of burnout; answers range in severity from “I enjoy my work. I have no symptoms of burnout” to “I feel completely burned out. I am at the point where I may need to seek help.”36 An endorsement of 1 of the 3 most severe response options including the word burnout is deemed to represent an individual experiencing burnout. Previous studies have repeatedly shown that this measure is associated with emotional exhaustion but does not assess depersonalization.44,45,46

Depression was assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) depression 4-item Short Form, which assesses symptoms specific to depression (ie, does not include items assessing vegetative symptoms) using a 5-point frequency-based Likert scale from never (1) to always (5) for scoring.30,31,32 It has demonstrated comparability to legacy measures,47,48 reliability, 31 content validity,31,49 concurrent validity,30,50 sensitivity to change,48 and capacity to assess symptom severity of clinical depression.31,32,51

Suicidal ideation was assessed using the question “During the past 12 months, have you had thoughts of taking your own life?”52 Those who responded yes were encouraged to reach out to their physician or the National Suicide Prevention Lifeline for assistance. The wording of this item and conceptual similarity with the National Comorbidity Survey item that assesses suicidal ideation facilitate comparison with nonphysician samples52,53 and suggest intuitive face validity. In addition, correlations with distress variables4,9,26,54,55 suggest concurrent validity. To our knowledge, evidence of other aspects of validity and reliability of this suicidal assessment item has not been published. Use of this item facilitates comparison of results of the present study with results of previous studies that have used the same assessment of suicidal ideation among physicians and physicians in training.4,9,15,56,57

Self-reported medical errors were assessed using a 4-item measure (eTable in the Supplement) developed in consultation with medical risk-management experts familiar with medical error.34 Used in previous research in postgraduate-trainee and attending-physician populations,25,34 this measure requests that respondents characterize their most recent experience with clinically significant errors, such as “I made a medical error that did result in patient harm” and “I ordered the wrong medication,” using a 6-point frequency-based Likert scale ranging from in the past week (5) to never (0).34 Scores are correlated with burnout and inversely correlated with professional fulfillment among physicians.34 This measure is designed to assess a broad range of errors and error rates and has intuitive face validity34 and conceptual similarity to other measures that assess this construct among physicians.23,26,58,59

Statistical Analysis

To preliminarily explore divergent validity between burnout and depression, we used principal components analysis (PCA) with direct oblimin rotation. Two separate PCAs were conducted: (1) emotional exhaustion measures (MBI–emotional exhaustion, PFI–work exhaustion, and Mini-Z) and the depression measure and (2) depersonalization measures (MBI-depersonalization and PFI–interpersonal disengagement) and the depression measure. We defined an item as demonstrating divergent validity if it had a component loading of 0.30 or greater on 1 but not both components. This minimal (rather than higher) cut point threshold is a better indicator of divergent validity and unlikely to be shown in constructs with substantial degrees of overlap. The Cronbach α internal consistency was calculated from the current study data for all scales. Statistical analyses were conducted using IBM SPSS statistical software, version 25 (IBM).

Multivariate logistic regression models were specified to assess the association of burnout with odds of suicidal ideation. Burnout scale scores from the MBI, PFI, and Mini-Z were standardized to assess the association with suicidal ideation of each SD-unit increase in scale score for each instrument. The first model was unadjusted, the second was adjusted for depression, and the third was adjusted for depression and demographic characteristics (sex, race/ethnicity, training status, and age category).

Models were also specified to assess the association of depression with odds of self-reported medical error using a dichotomous variable reflecting high vs low rates of recent error34 in which scoring in the upper half of the overall score distribution (≥4) was high, corresponding to an average response of “within the past year” across all items.34 The first model was unadjusted, the second was adjusted for overall burnout (assessed by the PFI because this measure assesses overall burnout including a combination of work exhaustion and interpersonal disengagement), and the third was adjusted for burnout and demographic characteristics.

Results

Of 1355 survey participants (11.4% of 11 884 invited), 1354 physicians completed the suicidal ideation measure and were included in this analysis; 893 (66.0%) were White, 1268 (93.6%) were non-Hispanic, 762 (56.3%) were men, 912 (67.4%) were non–primary care physicians, 934 (69.0%) were attending physicians, and 824 (60.9%) were younger than 45 years. Modal category characteristics were White race/ethnicity, male sex, and non–primary care physicians younger than 45 years. Table 1 gives demographic (sex, age category) and occupational (training status, practice type, and specialty) characteristics of participants and nonresponders (invited physicians who elected not to participate).

Table 1. Characteristics of Survey Participants and Nonresponders.

Characteristic No. (%)
Participants (n = 1354) Nonresponders (n = 10 529)a
Sex
Female 579 (42.8) 3678 (34.9)
Male 762 (56.3) 6833 (64.9)
Missing 13 (1.0) 18 (0.2)
Age, y
<35 439 (32.4) 1854 (17.6)
35-44 385 (28.4) 2245 (21.3)
45-54 243 (18.0) 2444 (23.2)
55-64 193 (14.3) 2291 (21.8)
≥65 94 (6.9) 1688 (16.0)
Training status
Attending physician 934 (69.0) 9059 (86.0)
Trainee (resident or fellow) 420 (31.0) 1470 (14.0)
Practice type
Nongovernment hospital 473 (34.9) 1882 (17.9)
Group practice 404 (29.8) 4018 (38.2)
Government hospital (city, county, state, or federal) 132 (9.8) 1166 (11.1)
Small private practiceb 114 (8.4) 1777 (16.9)
Missing or other practice typec 231 (17.1) 1686 (16.0)
Specialty
Anesthesiology 96 (7.1) 550 (5.2)
Dermatology 24 (1.8) 209 (2.0)
Emergency medicine 74 (5.5) 525 (5.0)
Family medicine 167 (12.3) 1290 (12.3)
Internal medicine 184 (13.6) 1472 (14.0)
Internal medicine subspecialty 127 (9.4) 1468 (13.9)
Neurology 28 (2.1) 207 (2.0)
Obstetrics and gynecology 96 (7.1) 623 (5.9)
Ophthalmology 30 (2.2) 256 (2.4)
Pathology 4 (0.3) 43 (0.4)
Pediatrics 91 (6.7) 610 (5.8)
Pediatrics subspecialty 63 (4.7) 318 (3.0)
Physical medicine 13 (1.0) 108 (1.0)
Psychiatry 90 (6.7) 629 (6.0)
Radiology 53 (3.9) 491 (4.7)
Surgery 62 (4.6) 390 (3.7)
General surgery subspecialty 71 (5.2) 714 (6.8)
Other 81 (6.0) 626 (5.9)
a

Nonresponder counts represent the population invited with elimination of the undeliverable and duplicate emails identified.

b

Small private practices include self-employed solo practices and full or part owners of a 2-physician practice.

c

Missing or other practice type includes no classification, medical school, other patient care, health maintenance organization, and locum tenens.

All scales had acceptable to excellent internal consistency reliability. Reliability coefficients for emotional exhaustion (α = 0.93) and depersonalization (α = 0.84) in the MBI were similar to those previously reported.60 Reliability coefficients for work exhaustion (α = 0.87), interpersonal disengagement (α = 0.92), and overall burnout (α = 0.93) in the PFI were also similar to those previously reported.34 The PROMIS depression scale and self-reported medical error scale had excellent (α = 0.91) and acceptable (α = 0.76) internal consistency reliability, respectively.

Distinguishing Burnout From Depression

Table 2 shows factor loadings for burnout and depression assessment items from PCAs with direct oblimin rotation in which values of 0.30 or above are high and values less than 0.30 are low. The PCAs showed divergent validity between and respective convergent validity within depression and all 25 items from the 3 burnout instruments, with the exception of 1 MBI–emotional exhaustion item worded “I’m at the end of my rope.” This item had approximately equal component loadings on both the emotional exhaustion and work exhaustion subscale component (0.46) and the depression component (0.40). All 13 other emotional exhaustion subscale items in the PCA (PFI–work exhaustion, MBI–emotional exhaustion, and Mini-Z) loaded high on the burnout component (range, 0.49-0.96) and low on the depression component (range, –0.20 to 0.24). In a subsequent PCA of the interpersonal disengagement and depersonalization subscale of burnout and depression, all 11 PFI–interpersonal disengagement and MBI–depersonalization assessment items showed high loadings on the burnout component (range, 0.58-0.90) and low loadings on the depression component (range, –0.09 to 0.27). In both PCAs, all PROMIS depression items loaded low on the burnout subscale components (range, –0.06 to 0.17) and high on the depression component (range, 0.74-0.93).

Table 2. Factor Loadings of Burnout and Depression Assessment Items.

Measure Item wording Pattern coefficienta
Burnout Depression
Work exhaustion (Stanford Professional Fulfillment Index) “A sense of dread when I think about work I have to do” 0.67b 0.17
“Physically exhausted at work” 0.72b 0.02
“Lacking in enthusiasm at work” 0.65b 0.15
“Emotionally exhausted at work” 0.77b 0.08
Emotional exhaustion (Maslach Burnout Inventory) “I feel emotionally drained from my work” 0.92b −0.09
“I feel used up at the end of the workday” 0.96b −0.20
“I feel fatigued when I get up in the morning and have to face another day on the job” 0.83b −0.02
“Working with people all day is really a strain for me” 0.62b 0.13
“I feel burned out from my work” 0.88b 0.02
“I feel frustrated by my job” 0.86b −0.02
“I feel I’m working too hard on my job” 0.86b −0.09
“Working with people directly puts too much stress on me” 0.49b 0.24
“I feel like I’m at the end of my rope” 0.46b 0.40c
Burnout survey (Mini-Z) “Using your own definition of ‘burnout,’ please choose one of the options below” 0.75b 0.12
Depression (NIH PROMIS Short Form) “I felt worthless” −0.06 0.90c
“I felt helpless” 0.06 0.86c
“I felt depressed” 0.17 0.74c
“I felt hopeless” 0.01 0.91c
Interpersonal disengagement (Stanford Professional Fulfillment Index) “Less empathetic with my patients” 0.89b −0.09
“Less empathetic with my colleagues” 0.67b 0.15
“Less sensitive to others’ feelings/emotions” 0.82b 0.01
“Less interested in talking with my patients” 0.87b −0.06
“Less connected with my patients” 0.90b −0.08
“Less connected with my colleagues” 0.58b 0.27
Depersonalization (Maslach Burnout Inventory) “I feel I treat some patients as if they were impersonal objects” 0.77b −0.05
“I’ve become more callous toward people since I took this job” 0.79b 0.05
“I worry that this job is hardening me emotionally” 0.72b 0.16
“I don’t really care what happens to some patients” 0.63b −0.03
“I feel patients blame me for some of their problems” 0.60b 0.00
Depression (NIH PROMIS Short Form) “I felt worthless” −0.02 0.87c
“I felt helpless” 0.00 0.90c
“I felt depressed” 0.10 0.81c
“I felt hopeless” −0.02 0.93c

Abbreviations: NIH, National Institutes of Health; PROMIS, Patient-Reported Outcomes Measurement Information System.

a

Principal component analysis with direct oblimin rotation, pattern matrix loadings. Pattern coefficients 0.30 or greater are high, and those less than 0.30 are low.

b

Item loaded moderately to highly into burnout component.

c

Item loaded moderately to highly into depression component.

Associations of Burnout and Depression With Suicidal Ideation

In aggregate, 75 of 1354 physicians (5.5%) reported having thoughts of taking their own life in the previous 12 months. The prevalence of suicidal ideation by participant characteristics, including age, race/ethnicity, sex, practice type, and specialty, is shown in Table 3.

Table 3. Prevalence of Suicidal Ideation by Participant Characteristics .

Characteristic Participants, No. (%) (N = 1354)
No suicidal ideation Suicidal ideation Total
Sex
Female 537 (39.7) 42 (3.1) 579 (42.8)
Male 730 (53.9) 32 (2.4) 762 (56.3)
Missing 12 (0.9) 1 (0.1) 13 (1.0)
Age, y
<35 418 (30.9) 21 (1.6) 439 (32.4)
35-44 360 (26.6) 25 (1.9) 385 (28.4)
45-54 227 (16.8) 16 (1.2) 243 (18.0)
55-64 183 (13.5) 10 (0.7) 193 (14.3)
≥65 91 (6.7) 3 (0.2) 94 (6.9)
Race
Asian 286 (21.1) 6 (0.4) 292 (21.6)
Black or African American 50 (3.7) 4 (0.3) 54 (4.0)
White 832 (61.5) 61 (4.5) 893 (66.0)
Other or missing 98 (7.2) 2 (0.1) 100 (7.4)
Ethnicity
Hispanic 65 (4.8) 7 (0.5) 72 (5.3)
Non-Hispanic 1200 (88.6) 68 (5.0) 1268 (93.6)
Missing 14 (1.0) 0 14 (1.0)
Training status
Attending physician 881 (65.1) 53 (3.9) 934 (69.0)
Trainee (resident or fellow) 398 (29.4) 22 (1.6) 420 (31.0)
Practice type
Nongovernment hospital 451 (33.3) 22 (1.6) 473 (34.9)
Group practice 379 (28.0) 25 (1.9) 404 (29.8)
Government hospital (city, county, state, or federal) 125 (9.2) 7 (0.5) 132 (9.8)
Small private practicea 110 (8.1) 4 (0.3) 114 (8.4)
Missing or other practice typeb 214 (15.8) 17 (1.3) 231 (17.1)
Specialty
Anesthesiology 91 (6.7) 5 (0.4) 96 (7.1)
Dermatology 22 (1.6) 2 (0.2) 24 (1.8)
Emergency medicine 71 (5.2) 3 (0.2) 74 (5.5)
Family medicine 157 (11.6) 10 (0.7) 167 (12.3)
Internal medicine 178 (13.2) 6 (0.4) 184 (13.6)
Internal medicine subspecialty 123 (9.1) 4 (0.3) 127 (9.4)
Neurology 27 (2.0) 1 (0.07) 28 (2.1)
Obstetrics and gynecology 90 (6.7) 6 (0.4) 96 (7.1)
Ophthalmology 29 (2.1) 1 (0.07) 30 (2.2)
Pathology 3 (0.2) 1 (0.07) 4 (0.3)
Pediatrics 88 (6.5) 3 (0.2) 91 (6.7)
Pediatrics subspecialty 58 (4.3) 5 (0.4) 63 (4.7)
Physical medicine 12 (0.9) 1 (0.07) 13 (1.0)
Psychiatry 82 (6.1) 8 (0.6) 90 (6.7)
Radiology 52 (3.8) 1 (0.07) 53 (3.9)
Surgery 56 (4.1) 6 (0.4) 62 (4.6)
General surgery subspecialty 67 (5.0) 4 (0.3) 71 (5.2)
Other 73 (5.4) 8 (0.6) 81 (6.0)
a

Small private practices include self-employed solo practices (n = 97) and full or part owners of a 2-physician practice (n = 17).

b

Missing or other practice type includes no classification (n = 200), medical school (n = 14), other patient care (n = 10), health maintenance organization (n = 4), and locum tenens (n = 3).

The logistic regression model revealed an association of burnout scores and burnout subscale scores with suicidal ideation before and after adjusting for depression and demographic variables (Table 4). Each increase of 1 SD in score on the PFI overall burnout scale was associated with 85% greater odds of experiencing suicidal ideation (odds ratio [OR],  1.85; 95% CI, 1.47-2.31) before adjusting for depression. After adjusting for depression, higher PFI overall burnout scores were not associated with greater risk of suicidal ideation (OR, 0.85; 95% CI, 0.63-1.17). This same pattern of results was consistent with all burnout subscale scores (PFI–work exhaustion, PFI–interpersonal disengagement, MBI–emotional exhaustion, and MBI–depersonalization); each was associated with greater risk of suicidal ideation before but not after adjusting for depression. After adjusting for overall burnout (PFI), sex, race/ethnicity, training status, and age category, each increase of 1 SD in score on the PROMIS depression scale was associated with 202% greater odds of suicidal ideation (OR, 3.02; 95% CI, 2.30-3.95).

Table 4. Logistic Regression Modeling of the Association Between Burnout and Suicidal Ideation.

Variable Odds ratio (95% CI)
Model 1a Model 2b Model 3c
Burnout (Stanford Professional Fulfillment Index) 1.85 (1.47-2.31) 0.85 (0.63-1.17) 0.88 (0.64-1.22)
Work exhaustion (Stanford Professional Fulfillment Index) 1.92 (1.52-2.41) 0.85 (0.62-1.16) 0.83 (0.60-1.15)
Interpersonal disengagement (Stanford Professional Fulfillment Index) 1.66 (1.33-2.07) 0.89 (0.67-1.18) 0.94 (0.70-1.26)
Emotional exhaustion (Maslach Burnout Inventory) 2.16 (1.69-2.75) 1.03 (0.75-1.41) 0.94 (0.68-1.31)
Depersonalization (Maslach Burnout Inventory) 1.82 (1.48-2.25) 1.08 (0.84-1.40) 1.12 (0.86-1.46)
a

Model 1 was unadjusted.

b

Model 2 was adjusted for depression.

c

Model 3 was adjusted for depression, sex, race/ethnicity, training status, and age category.

Associations of Burnout and Depression With Self-reported Medical Errors

Before adjusting for overall burnout, each SD-unit increase in depression score was associated with 27% greater odds of increased self-reported medical errors (OR, 1.27; 95% CI, 1.14-1.43). After adjusting for burnout using the PFI, higher depression scores were not associated with greater odds of self-reported medical errors (OR, 1.01; 95% CI, 0.88-1.16); this result was consistent with that of the final model, which also adjusted for sex, race/ethnicity, training status, and age category (OR, 1.06; 95% CI, 0.91-1.22). In models adjusted for the same variables, overall burnout was associated with 44% to 48% greater odds of increased self-reported medical errors (OR in the model adjusted for depression, 1.48; 95% CI, 1.28-1.71; OR in the model adjusted for depression, sex, race/ethnicity, training status, and age, 1.44; 95% CI, 1.24-1.67).

Discussion

The results of this cross-sectional study suggest that burnout was associated with suicidal ideation in physicians before but not after adjusting for depression and that depression was associated with suicidal ideation after adjustment for burnout. The results showed an opposite pattern of associations with self-reported medical errors; burnout but not depression was associated with self-reported medical errors in a fully adjusted model. In addition, PCA preparatory to analyses addressing the primary study aim provided additional evidence that burnout and depression are different constructs, with all but 1 of 25 assessment items showing associated divergent validity. The association this study showed between depression and suicidal ideation in physicians is consistent with research in the general population.61 Common factors associated with suicide or suicidal ideation in the general population include depression, hopelessness, impairment, and previous suicide attempts.62

Depression is associated with serious medical morbidity, whereas the association of burnout with suicidal ideation is either the result of confounding effects with comorbid depression or is indirect to the degree that burnout is associated with depression.4,9,61 Previously observed associations between burnout and suicidal ideation4,9,19 may have resulted from failure to adjust for depression or from adjustment for depression using a screening instrument (ie, the PRIME-MD4,9) that does not optimally capture symptom severity or specificity.20,21 The absence of a direct association of burnout with suicidal ideation is also consistent with the World Health Organization’s definitions of these constructs: burnout is an occupational distress syndrome rather than a clinical psychiatric diagnosis indicating distress in multiple life domains.13

There is also biologically plausible evidence of the distinction between occupational distress (burnout) and depression. For example, burnout and depression are differentially associated with concentrations of the microinflammation biomarkers high-sensitivity C-reactive protein and fibrinogen.63 Furthermore, the glucocorticoid receptor and brain-derived neurotrophic factor genes display different methylation patterns during depression than during occupational stress.64 Depression is a serious medical disorder, responsible for more morbidity worldwide than any other medical problem and warranting medical evaluation and evidence-based clinical treatment (eg, pharmacologic or psychotherapy).18 Burnout, in contrast, is a serious occupational distress syndrome affecting patient care25,29,65 and is directly associated with self-reported medical error. The syndrome is frequently associated with characteristics of the work environment (excessive demands and inadequate resources) and is ideally addressed through system-based occupational interventions.

Occupational burnout also has important health implications and is associated with increases in insomnia,66 mental illness symptoms,66 headaches,66 severe injury,66 type 2 diabetes,67 extended fatigue,66 coronary heart disease,63 gastrointestinal and respiratory concerns,66 myocardial infarction, atrial fibrillation,68 musculoskeletal discomfort,63,66 and all-cause mortality.66 System-level efforts should be pursued to mitigate burnout to reduce these risks. Analogous to depression, however, each of these health consequences is distinct from burnout and, once present, requires specific treatment. Burnout may be associated with cortisol dysregulation,69 hypercholesterolemia,70 decreased fibrinolytic capacity,71 and telomere function,72 although the mechanisms by which burnout may contribute to those conditions have not yet been elucidated. Similar to the association between burnout and suicidal ideation observed in this study, the association between burnout and some of these conditions may not be direct. Although burnout is not a clinical diagnosis, it may be more important than depression in terms of occupational consequences,25,28,29,59 consistent with the current study finding that burnout was directly associated with an increased risk of self-reported medical errors. Furthermore, physician burnout has been shown to be associated with unsolicited patient complaints, whereas in the same study, depression was not.25

Although some researchers continue to dispute the independence of burnout and depression, psychometric studies have predominantly shown that these 2 constructs are distinct, including a recent systematic review and meta-analysis of 67 studies that showed that burnout differed from depression.18 The results of the current study are consistent with the premise that burnout differs from depression. The single burnout assessment item that did not show divergent validity from depression assessment items was an MBI–emotional exhaustion item with wording that intuitively seems inclusive of more generalized depression symptoms than occupation-specific distress.

Limitations

This study has limitations. All of the measures were self-reported and may thus be subject to participant bias. Furthermore, although the associations between the domains assessed are unlikely to differ, it is possible that the point prevalence of burnout, depression, suicidal ideation, and self-reported medical error rate in the convenience sample, which had a low response rate (common among surveys of health care professionals73), does not generalize to US physicians at large. However, previous research using the same methods (including sensitive questions) among US physicians nationwide followed by survey of a random sample of nonrespondents showed reasonable equivalence between respondents and nonrespondents.15,57 Only 75 physicians in the sample reported suicidal ideation, which is inadequate for separate subgroup analyses of attending physicians and residents. In addition, these cross-sectional associations do not indicate causality. Future investigations are warranted to evaluate causal relationships between burnout, depression, suicidal ideation, and medical error.

Conclusions

The findings of this cross-sectional study suggest that depression but not burnout is directly associated with greater suicidal ideation in physicians. In addition, the results suggest that burnout, not depression, is directly associated with an increased risk of self-reported medical errors. The findings of this study suggest that burnout without depression does not increase suicide risk and can therefore be safely addressed outside of mental health care.

Supplement.

eTable. Self-reported medical errors

References

  • 1.Rotenstein LS, Ramos MA, Torre M, et al. . Prevalence of depression, depressive symptoms, and suicidal ideation among medical students: a systematic review and meta-analysis. JAMA. 2016;316(21):2214-2236. doi: 10.1001/jama.2016.17324 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Brazeau CMLR, Shanafelt T, Durning SJ, et al. . Distress among matriculating medical students relative to the general population. Acad Med. 2014;89(11):1520-1525. doi: 10.1097/ACM.0000000000000482 [DOI] [PubMed] [Google Scholar]
  • 3.Jiménez-López JL, Arenas-Osuna J, Angeles-Garay U. Depression, anxiety and suicide risk symptoms among medical residents over an academic year. Article in Spanish. Rev Med Inst Mex Seguro Soc. 2015;53(1):20-28. [PubMed] [Google Scholar]
  • 4.Dyrbye LN, Thomas MR, Massie FS, et al. . Burnout and suicidal ideation among U.S. medical students. Ann Intern Med. 2008;149(5):334-341. doi: 10.7326/0003-4819-149-5-200809020-00008 [DOI] [PubMed] [Google Scholar]
  • 5.Schernhammer ES, Colditz GA. Suicide rates among physicians: a quantitative and gender assessment (meta-analysis). Am J Psychiatry. 2004;161(12):2295-2302. doi: 10.1176/appi.ajp.161.12.2295 [DOI] [PubMed] [Google Scholar]
  • 6.Frank E, Biola H, Burnett CA. Mortality rates and causes among U.S. physicians. Am J Prev Med. 2000;19(3):155-159. doi: 10.1016/S0749-3797(00)00201-4 [DOI] [PubMed] [Google Scholar]
  • 7.Duarte D, El-Hagrassy MM, Couto TCE, Gurgel W, Fregni F, Correa H. Male and female physician suicidality: a systematic review and meta-analysis. JAMA Psychiatry. 2020;77(6):587-597. doi: 10.1001/jamapsychiatry.2020.0011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Guille C, Zhao Z, Krystal J, Nichols B, Brady K, Sen S. Web-based cognitive behavioral therapy intervention for the prevention of suicidal ideation in medical interns: a randomized clinical trial. JAMA Psychiatry. 2015;72(12):1192-1198. doi: 10.1001/jamapsychiatry.2015.1880 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Shanafelt TD, Balch CM, Dyrbye L, et al. . Special report: suicidal ideation among American surgeons. Arch Surg. 2011;146(1):54-62. doi: 10.1001/archsurg.2010.292 [DOI] [PubMed] [Google Scholar]
  • 10.Epstein LC, Thomas CB, Shaffer JW, Perlin S. Clinical prediction of physician suicide based on medical student data. J Nerv Ment Dis. 1973;156(1):19-29. doi: 10.1097/00005053-197301000-00002 [DOI] [PubMed] [Google Scholar]
  • 11.Iannelli RJ, Finlayson AJ, Brown KP, et al. . Suicidal behavior among physicians referred for fitness-for-duty evaluation. Gen Hosp Psychiatry. 2014;36(6):732-736. doi: 10.1016/j.genhosppsych.2014.06.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Eneroth M, Gustafsson Sendén M, Løvseth LT, Schenck-Gustafsson K, Fridner A. A comparison of risk and protective factors related to suicide ideation among residents and specialists in academic medicine. BMC Public Health. 2014;14:271. doi: 10.1186/1471-2458-14-271 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.World Health Organization International Classification of Diseases, 11th Revision (ICD-11) Accessed December 12, 2019. https://www.who.int/classifications/icd/en/
  • 14.Embriaco N, Azoulay E, Barrau K, et al. . High level of burnout in intensivists: prevalence and associated factors. Am J Respir Crit Care Med. 2007;175(7):686-692. doi: 10.1164/rccm.200608-1184OC [DOI] [PubMed] [Google Scholar]
  • 15.Shanafelt TD, West CP, Sinsky C, et al. . Changes in burnout and satisfaction with work-life integration in physicians and the general US working population between 2011 and 2017. Mayo Clin Proc. 2019;94(9):1681-1694. doi: 10.1016/j.mayocp.2018.10.023 [DOI] [PubMed] [Google Scholar]
  • 16.Lheureux F, Truchot D, Borteyrou X. Suicidal tendency, physical health problems and addictive behaviours among general practitioners: their relationship with burnout. Work & Stress. 2016;30(2):173–192. doi: 10.1080/02678373.2016.1171806 [DOI] [Google Scholar]
  • 17.Bianchi R. Do burnout and depressive symptoms form a single syndrome? confirmatory factor analysis and exploratory structural equation modeling bifactor analysis. J Psychosom Res. 2020;131:109954. doi: 10.1016/j.jpsychores.2020.109954 [DOI] [PubMed] [Google Scholar]
  • 18.Koutsimani P, Montgomery A, Georganta K. The relationship between burnout, depression, and anxiety: a systematic review and meta-analysis. Front Psychol. 2019;10:284. doi: 10.3389/fpsyg.2019.00284 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.van der Heijden F, Dillingh G, Bakker A, Prins J. Suicidal thoughts among medical residents with burnout. Arch Suicide Res. 2008;12(4):344-346. doi: 10.1080/13811110802325349 [DOI] [PubMed] [Google Scholar]
  • 20.Mata DA, Ramos MA, Bansal N, et al. . Prevalence of depression and depressive symptoms among resident physicians: a systematic review and meta-analysis. JAMA. 2015;314(22):2373-2383. doi: 10.1001/jama.2015.15845 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Williams JW Jr, Pignone M, Ramirez G, Perez Stellato C. Identifying depression in primary care: a literature synthesis of case-finding instruments. Gen Hosp Psychiatry. 2002;24(4):225-237. doi: 10.1016/S0163-8343(02)00195-0 [DOI] [PubMed] [Google Scholar]
  • 22.Shanafelt TD, Mungo M, Schmitgen J, et al. . Longitudinal study evaluating the association between physician burnout and changes in professional work effort. Mayo Clin Proc. 2016;91(4):422-431. doi: 10.1016/j.mayocp.2016.02.001 [DOI] [PubMed] [Google Scholar]
  • 23.West CP, Huschka MM, Novotny PJ, et al. . Association of perceived medical errors with resident distress and empathy: a prospective longitudinal study. JAMA. 2006;296(9):1071-1078. doi: 10.1001/jama.296.9.1071 [DOI] [PubMed] [Google Scholar]
  • 24.Shanafelt TD, Dyrbye LN, Sinsky C, et al. . Relationship between clerical burden and characteristics of the electronic environment with physician burnout and professional satisfaction. Mayo Clin Proc. 2016;91(7):836-848. doi: 10.1016/j.mayocp.2016.05.007 [DOI] [PubMed] [Google Scholar]
  • 25.Welle D, Trockel MT, Hamidi M, et al. . Occupational distress and sleep-related impairment in physicians are associated with unsolicited patient complaints. Mayo Clin Proc. 95(4):719-726. doi: 10.1016/j.mayocp.2019.09.025 [DOI] [PubMed] [Google Scholar]
  • 26.Tawfik DS, Profit J, Morgenthaler TI, et al. . Physician burnout, well-being, and work unit safety grades in relationship to reported medical errors. Mayo Clin Proc. 2018;93(11):1571-1580. doi: 10.1016/j.mayocp.2018.05.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Fahrenkopf AM, Sectish TC, Barger LK, et al. . Rates of medication errors among depressed and burnt out residents: prospective cohort study. BMJ. 2008;336(7642):488-491. doi: 10.1136/bmj.39469.763218.BE [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Salyers MP, Bonfils KA, Luther L, et al. . the relationship between professional burnout and quality and safety in healthcare: a meta-analysis. J Gen Intern Med. 2017;32(4):475-482. doi: 10.1007/s11606-016-3886-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Tawfik DS, Scheid A, Profit J, et al. . evidence relating health care provider burnout and quality of care: a systematic review and meta-analysis. Ann Intern Med. 2019;171(8):555-567. doi: 10.7326/M19-1152 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Cella D, Riley W, Stone A, et al. ; PROMIS Cooperative Group . The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005-2008. J Clin Epidemiol. 2010;63(11):1179-1194. doi: 10.1016/j.jclinepi.2010.04.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Cella D, Choi SW, Condon DM, et al. . PROMIS® adult health profiles: efficient short-form measures of seven health domains. Value Health. 2019;22(5):537-544. doi: 10.1016/j.jval.2019.02.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Schalet BD, Pilkonis PA, Yu L, et al. . Clinical validity of PROMIS depression, anxiety, and anger across diverse clinical samples. J Clin Epidemiol. 2016;73:119-127. doi: 10.1016/j.jclinepi.2015.08.036 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Int J Surg. 2014;12(12):1495-1499. doi: 10.1016/j.ijsu.2014.07.013 [DOI] [PubMed] [Google Scholar]
  • 34.Trockel M, Bohman B, Lesure E, et al. . A brief instrument to assess both burnout and professional fulfillment in physicians: reliability and validity, including correlation with self-reported medical errors, in a sample of resident and practicing physicians. Acad Psychiatry. 2018;42(1):11-24. doi: 10.1007/s40596-017-0849-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Maslach C. Maslach burnout inventory–human services survey (MBI-HSS). In: MBI Manual. Consulting Psychologists Press; 1996:192-198. [Google Scholar]
  • 36.Linzer M, Poplau S, Babbott S, et al. . Worklife and wellness in academic general internal medicine: results from a national survey. J Gen Intern Med. 2016;31(9):1004-1010. doi: 10.1007/s11606-016-3720-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Marchalik D, Shaw N, Padmore J, Lu E, Rowe S, Trockel M. The impact of sleep-related impairment on burnout in urologists: results from a national consortium study. Eur Urol Open Sci. 2019;18(1):e1114-e1115. doi: 10.1016/S1569-9056(19)30807-3 [DOI] [Google Scholar]
  • 38.Marchalik D, Brems J, Rodriguez A, et al. . The impact of institutional factors on physician burnout: a national study of urology trainees. Urology. 2019;131:27-35. doi: 10.1016/j.urology.2019.04.042 [DOI] [PubMed] [Google Scholar]
  • 39.Maslach C, Jackson SE. The measurement of experienced burnout. J Organ Behav. 1981;2(2):99-113. doi: 10.1002/job.4030020205 [DOI] [Google Scholar]
  • 40.Schaufeli WB, Bakker AB, Hoogduin K, Schaap C, Kladler A. On the clinical validity of the Maslach Burnout Inventory and the burnout measure. Psychol Health. 2001;16(5):565-582. doi: 10.1080/08870440108405527 [DOI] [PubMed] [Google Scholar]
  • 41.Maslach C, Schaufeli WB Historical and conceptual development of burnout. In: Schaufeli WB, Maslach C, Marek T, eds. Burnout: Recent developments in theory and research. Routledge; 1993:1-16. doi: 10.4324/9781315227979-1 [DOI]
  • 42.Wheeler DL, Vassar M, Worley JA, Barnes LLB. A reliability generalization meta-analysis of coefficient alpha for the Maslach burnout inventory. Educ Psychol Meas. 71(1):231-244. doi: 10.1177/0013164410391579 [DOI] [Google Scholar]
  • 43.Shanafelt TD, Gorringe G, Menaker R, et al. . Impact of organizational leadership on physician burnout and satisfaction. Mayo Clin Proc. 2015;90(4):432-440. doi: 10.1016/j.mayocp.2015.01.012 [DOI] [PubMed] [Google Scholar]
  • 44.Dolan ED, Mohr D, Lempa M, et al. . Using a single item to measure burnout in primary care staff: a psychometric evaluation. J Gen Intern Med. 2015;30(5):582-587. doi: 10.1007/s11606-014-3112-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Rohland BM, Kruse GR, Rohrer JE. Validation of a single-item measure of burnout against the Maslach Burnout Inventory among physicians. Stress Health. 2004;20(2):75-79. doi: 10.1002/smi.1002 [DOI] [Google Scholar]
  • 46.Hansen V, Girgis A. Can a single question effectively screen for burnout in Australian cancer care workers? BMC Health Serv Res. 2010;10(1):341. doi: 10.1186/1472-6963-10-341 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Clover K, Lambert SD, Oldmeadow C, et al. . PROMIS depression measures perform similarly to legacy measures relative to a structured diagnostic interview for depression in cancer patients. Qual Life Res. 2018;27(5):1357-1367. doi: 10.1007/s11136-018-1803-x [DOI] [PubMed] [Google Scholar]
  • 48.Pilkonis PA, Yu L, Dodds NE, Johnston KL, Maihoefer CC, Lawrence SM. Validation of the depression item bank from the Patient-Reported Outcomes Measurement Information System (PROMIS) in a three-month observational study. J Psychiatr Res. 2014;56:112-119. doi: 10.1016/j.jpsychires.2014.05.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Riley WT, Rothrock N, Bruce B, et al. . Patient-reported outcomes measurement information system (PROMIS) domain names and definitions revisions: further evaluation of content validity in IRT-derived item banks. Qual Life Res. 2010;19(9):1311-1321. doi: 10.1007/s11136-010-9694-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Rothrock NE, Hays RD, Spritzer K, Yount SE, Riley W, Cella D. Relative to the general US population, chronic diseases are associated with poorer health-related quality of life as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS). J Clin Epidemiol. 2010;63(11):1195-1204. doi: 10.1016/j.jclinepi.2010.04.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.American Psychiatric Association. Online assessment measures. Accessed September 27, 2020. https://www.psychiatry.org/psychiatrists/practice/dsm/educational-resources/assessment-measures
  • 52.Meehan PJ, Lamb JA, Saltzman LE, O’Carroll PW. Attempted suicide among young adults: progress toward a meaningful estimate of prevalence. Am J Psychiatry. 1992;149(1):41-44. doi: 10.1176/ajp.149.1.41 [DOI] [PubMed] [Google Scholar]
  • 53.Kessler RC, Borges G, Walters EE. Prevalence of and risk factors for lifetime suicide attempts in the National Comorbidity Survey. Arch Gen Psychiatry. 1999;56(7):617-626. doi: 10.1001/archpsyc.56.7.617 [DOI] [PubMed] [Google Scholar]
  • 54.Dyrbye LN, Harper W, Durning SJ, et al. . Patterns of distress in US medical students. Med Teach. 2011;33(10):834-839. doi: 10.3109/0142159X.2010.531158 [DOI] [PubMed] [Google Scholar]
  • 55.Jackson ER, Shanafelt TD, Hasan O, Satele DV, Dyrbye LN. Burnout and alcohol abuse/dependence among U.S. medical students. Acad Med. 2016;91(9):1251-1256. doi: 10.1097/ACM.0000000000001138 [DOI] [PubMed] [Google Scholar]
  • 56.Shanafelt TD, Boone S, Tan L, et al. Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Intern Med. 2012;172(18):1377-1385. doi: 10.1001/archinternmed.2012.3199 [DOI] [PubMed]
  • 57.Shanafelt TD, Hasan O, Dyrbye LN, et al. . Changes in burnout and satisfaction with work-life balance in physicians and the general US working population between 2011 and 2014. Mayo Clin Proc. 2015;90(12):1600-1613. doi: 10.1016/j.mayocp.2015.08.023 [DOI] [PubMed] [Google Scholar]
  • 58.West CP, Dyrbye LN, Sloan JA, Shanafelt TD. Single item measures of emotional exhaustion and depersonalization are useful for assessing burnout in medical professionals. J Gen Intern Med. 2009;24(12):1318-1321. doi: 10.1007/s11606-009-1129-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Shanafelt TD, Balch CM, Bechamps G, et al. . Burnout and medical errors among American surgeons. Ann Surg. 2010;251(6):995-1000. doi: 10.1097/SLA.0b013e3181bfdab3 [DOI] [PubMed] [Google Scholar]
  • 60.Iwanicki EF, Schwab RL. A cross validation study of the Maslach Burnout Inventory. Educ Psychol Meas. 1981;41(4):1167-1174. doi: 10.1177/001316448104100425 [DOI] [Google Scholar]
  • 61.Casey PR, Dunn G, Kelly BD, et al. ; ODIN Group . Factors associated with suicidal ideation in the general population: five-centre analysis from the ODIN study. Br J Psychiatry. 2006;189(5):410-415. doi: 10.1192/bjp.bp.105.017368 [DOI] [PubMed] [Google Scholar]
  • 62.Franklin JC, Ribeiro JD, Fox KR, et al. . Risk factors for suicidal thoughts and behaviors: a meta-analysis of 50 years of research. Psychol Bull. 2017;143(2):187-232. doi: 10.1037/bul0000084 [DOI] [PubMed] [Google Scholar]
  • 63.Toker S, Shirom A, Shapira I, Berliner S, Melamed S. The association between burnout, depression, anxiety, and inflammation biomarkers: C-reactive protein and fibrinogen in men and women. J Occup Health Psychol. 2005;10(4):344-362. doi: 10.1037/1076-8998.10.4.344 [DOI] [PubMed] [Google Scholar]
  • 64.Bakusic J, Schaufeli W, Claes S, Godderis L. Stress, burnout and depression: a systematic review on DNA methylation mechanisms. J Psychosom Res. 2017;92:34-44. doi: 10.1016/j.jpsychores.2016.11.005 [DOI] [PubMed] [Google Scholar]
  • 65.Zhang Y, Feng X. The relationship between job satisfaction, burnout, and turnover intention among physicians from urban state-owned medical institutions in Hubei, China: a cross-sectional study. BMC Health Serv Res. 2011;11:235. doi: 10.1186/1472-6963-11-235 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Salvagioni DAJ, Melanda FN, Mesas AE, González AD, Gabani FL, de Andrade SM. Physical, psychological and occupational consequences of job burnout: a systematic review of prospective studies. PLoS One. 2017;12(10):e0185781. doi: 10.1371/journal.pone.0185781 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Melamed S, Shirom A, Toker S, Shapira I. Burnout and risk of type 2 diabetes: a prospective study of apparently healthy employed persons. Psychosom Med. 2006;68(6):863-869. doi: 10.1097/01.psy.0000242860.24009.f0 [DOI] [PubMed] [Google Scholar]
  • 68.Fransson EI, Nordin M, Magnusson Hanson LL, Westerlund H. Job strain and atrial fibrillation—results from the Swedish Longitudinal Occupational Survey of Health and meta-analysis of three studies. Eur J Prev Cardiol. 2018;25(11):1142-1149. doi: 10.1177/2047487318777387 [DOI] [PubMed] [Google Scholar]
  • 69.Bellingrath S, Weigl T, Kudielka BM. Cortisol dysregulation in school teachers in relation to burnout, vital exhaustion, and effort-reward-imbalance. Biol Psychol. 2008;78(1):104-113. doi: 10.1016/j.biopsycho.2008.01.006 [DOI] [PubMed] [Google Scholar]
  • 70.Kitaoka-Higashiguchi K, Morikawa Y, Miura K, et al. . Burnout and risk factors for arteriosclerotic disease: follow-up study. J Occup Health. 2009;51(2):123-131. doi: 10.1539/joh.L8104 [DOI] [PubMed] [Google Scholar]
  • 71.Kakiashvili T, Leszek J, Rutkowski K. The medical perspective on burnout. Int J Occup Med Environ Health. 2013;26(3):401-412. doi: 10.2478/s13382-013-0093-3 [DOI] [PubMed] [Google Scholar]
  • 72.Ahola K, Sirén I, Kivimäki M, et al. . Work-related exhaustion and telomere length: a population-based study. PLoS One. 2012;7(7):e40186. doi: 10.1371/journal.pone.0040186 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73.Young IC, Johnson T, VanGeest JB. Enhancing surveys of health care professionals: a meta-analysis of techniques to improve response. Eval Health Prof. 2013;36(3):382-407. doi: 10.1177/0163278713496425 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eTable. Self-reported medical errors


Articles from JAMA Network Open are provided here courtesy of American Medical Association

RESOURCES