Objective To explore associations of bias frequency, sources, and types with burnout in a large, multispecialty sample of residents and fellows and to determine whether and how odds of burnout change after adjustment for bias experiences in multiple demographic subgroups. Methods Trainees in graduate medical education programs at Mayo Clinic sites were surveyed between October 12, 2020, and November 22, 2020. Survey items measured personal experiences with bias (frequency, sources, types), burnout (2 Maslach Burnout Inventory items), and demographic characteristics (age, gender, race/ethnicity, lesbian-gay-bisexual-transgender-queer-nonbinary-other identification, disability, socioeconomic background, year in school, specialty). The χ2 test and logistic regression analyses examined relationships between variables. Results Of 1825 trainees surveyed, 942 (52%) from 77 programs responded. Overall, 16% (137/881) of respondents reported 1 or more personal bias experiences. Trainees reporting bias experiences weekly or more often had markedly higher odds of burnout in adjusted analyses (odds ratio [OR], 8.00; 95% CI, 2.68 to 23.89; P<.001). Bias from education leaders/staff, fellow learners, and faculty was independently associated with burnout, whereas bias from patients/companions and other staff/employees was not. Trainees with a disability (OR, 3.16; 95% CI, 1.05 to 9.53; P=.04) and trainees from a low-income background (OR, 1.53; 95% CI, 1.03 to 2.26; P=.03) had higher odds of burnout in unadjusted analyses, but these associations were no longer statistically significant after adjustment for bias frequency. Conclusion Self-reported bias experiences relate strongly to trainee burnout. Some bias sources may be more strongly associated with burnout than others. More frequent bias experiences could account, at least in part, for higher odds of burnout in some demographic subgroups.

Despite widespread recognition of work-home interference (WHI) as a key driver of physician burnout, the day-to-day realities of how physicians navigate these challenges remain underexplored. This study examines how WHI shapes physicians’ professional and personal lives, with a particular focus on its impact on relationships and organizational resilience.Through seven focus groups with 64 physicians across specialties and career stages at Mayo Clinic in Rochester, Minnesota, we identified key sources of WHI, including inflexible work schedules and the persistent mental burden of balancing multiple roles. Physicians described resorting to unsustainable coping strategies that, over time, became entrenched. They also expressed frustration with institutional efforts to mitigate WHI, which emphasized personal resilience and time management while overlooking deeper structural issues.A critical finding from the study was the often-underappreciated role of professional relationships in buffering against WHI and sustaining both individual and organizational resilience. Physicians described how efficiency-driven interventions—such as workflow changes and increased productivity demands—unintentionally eroded collegial connections, leaving them feeling increasingly isolated and unsupported. This loss of professional community exacerbated the emotional toll of WHI and arguably weakens the adaptive capacity of most healthcare organizations.These findings suggest that WHI and burnout cannot be addressed solely through individual-level interventions or efficiency measures. Instead, healthcare institutions must acknowledge the social dimensions of physician well-being and foster work environments that prioritize connection alongside productivity. By reassessing the trade-offs between efficiency and relational cohesion, organizations can better support physicians and promote a more sustainable, resilient workforce.

OBJECTIVE:To evaluate the prevalence of burnout and satisfaction with work-life integration (WLI) among physicians and US workers in 2023 relative to 2011, 2014, 2017, and 2020, as well as physicians in 2021. PARTICIPANTS AND METHODS:Between October 19, 2023, and March 3rd, 2024, we surveyed US physicians and a probability-based sample of the US working population using methods similar to previous studies. Burnout and WLI were measured using standard tools. RESULTS:Demographic characteristics of the 7643 survey participants were similar to those of practicing US physicians (N=936,074), although participants were more likely to be women (39.6% vs 37.9%). Nonresponder analysis suggested participants were representative of US physicians with regard to burnout and satisfaction with WLI. Overall, 45.2% of physicians reported at least 1 symptom of burnout in 2023 compared with 62.8% in 2021 (P<.001), 38.2% in 2020 (P<.001), 43.9% in 2017 (P=.16), 54.4% in 2014 (P≤.001), and 45.5% in 2011 (P=.49). Overall, 42.2% of physicians (n=2732) were satisfied with WLI in 2023, compared with 30.3% in 2021 (P<.001), 46.1% in 2020 (P<.001), 42.8% in 2017 (P=.02), 40.9% in 2014 (P<.001), and 48.5% in 2011 (P <.001). On multivariable analysis of 2023 participants, physicians were at increased risk for burnout (odds ratio=1.82; 95% CI, 1.63 to 2.05) and were less likely to be satisfied with WLI (odds ratio=0.59; 95% CI, 0.53 to 0.66) than other US workers. CONCLUSION:Burnout among US physicians improved between 2021 and 2023 and is currently at levels similar to 2017. However, US physicians remain at higher risk for burnout relative to other US workers.

PURPOSE:This study compares the prevalence of occupational burnout, depression, and satisfaction with work-life integration (WLI) among U.S. residents and fellows (trainees) with that of U.S. physicians and the general U.S. workforce and examines the current point prevalence of burnout and satisfaction with WLI among trainees relative to 2012. METHOD:Between November 30, 2023, and January 2, 2024, U.S. trainees were surveyed using methods similar to a 2012 study. A sample of practicing U.S. physicians and a probability-based sample of the U.S. working population were surveyed at a similar timepoint. Burnout was assessed using the emotional exhaustion and depersonalization scales of the Maslach Burnout Inventory, depression using the Patient Reported Outcome Measurement Information System depression scale, and satisfaction with WLI with a previously used standardized item. RESULTS:Surveys were completed by 3,486 of 58,127 trainees (6.0%). Nonresponder analysis suggested participants were representative of U.S. trainees with respect to burnout and depression. A higher proportion of trainees than practicing physicians had burnout symptoms (1,376 of 3,486 [50.0%] vs 3,023 of 7,643 [45.2%]; P < .001). In pooled analysis of trainees and similarly aged U.S. workers in other fields, adjusting for age, gender, and relationship status, trainees were at higher risk for burnout (odds ratio [OR], 1.50; 95% CI, 1.27-1.77) but lower risk for moderate or severe depression (OR, 0.77; 95% CI, 0.63-0.93). In pooled multivariable analysis of trainees from the 2012 and 2023 surveys, adjusting for year in training, relationship status, and specialty, trainees in 2023 had lower odds of burnout than those who responded in 2012 (OR, 0.71; 95% CI, 0.61-0.81). CONCLUSIONS:Burnout among U.S. trainees was lower in 2023 than 2012. Despite this improvement, trainees remain at higher risk for burnout than workers in other fields. Continued efforts are needed to optimize trainee education, preparedness for practice, and well-being.

ABSTRACT Adherence in digital health studies with extended observation periods (≥ 12 months) is limited, and participant retention considerably reduces with time. The US Food and Drug Administration has issued guidelines for improving participant engagement, adherence, and diversity in digital health studies combined with decentralized procedures. A decentralized digital health study on well‐being was designed with protocolized procedures to study the feasibility of participant engagement and technology support to facilitate adherence (wearing the smartwatch ≥ 70% of time) sustained over a 12‐month period. At the end of the study, participants were asked about their ease of participation and free‐response questions about how wearing the smartwatches impacted their physical wellness. An inductive thematic analysis (ITA) was performed to assess themes of those responses and association with adherence. A total of 298 participants were recruited between 2022 and 2023 (n = 129 in Cohort A in October 22, n = 169 in Cohort B in April 23), with 23% non‐white participants accrued. Among the 298 participants accrued, 273 (92% of accrued participants) completed the 12‐month study with an average overall adherence of 77.4% (SD = 32.64) wear‐time across 12 months. Median adherence of participants whose responses exemplified an ITA theme encompassing perceived behavior changes in sleep and physical activity was higher than those who did not have a response exemplifying that theme. Conversely, those expressing perceived discomfort or intrusiveness of the smartwatch had a statistically lower adherence. These results highlight the crucial roles of technology support and robust engagement efforts to enable sustained adherence over extended follow‐up periods in decentralized digital health studies.

Importance:Burnout remains prevalent among physicians and can negatively affect quality, safety, and cost of patient care. Few randomized studies on interventions to address burnout have been conducted to date. Objective:To determine whether wearing a smartwatch and having access to its physiological data (eg, sleep, step count, and heart rate) improves physician well-being (and if so, which dimensions of well-being). Design, Setting, and Participants:This randomized clinical trial included physicians at 2 US medical centers (Mayo Clinic and the University of Colorado School of Medicine) who volunteered to wear a provided smartwatch beginning June 7, 2023. The study concluded on June 27, 2024. Intervention:Six months of wearing a smartwatch. Main Outcomes and Measures:Burnout, resilience, quality of life, depressive symptoms, stress, and sleepiness were measured using validated scales. Participants completed electronic surveys at baseline and 3, 6, 9, and 12 months. An intention-to-treat analysis was conducted. Results:This study included 184 physicians (mean [SD] age, 37.5 [9.3] years; 107 females [58.8%]). A total of 83 of 183 physicians (45.4%) were residents or fellows, 103 of 184 (56.0%) lived in Colorado, and 99 of 182 (54.4%) worked in non-primary care settings. Baseline levels of well-being across the measured dimensions were similar for the 2 study arms. At 6 months, 35 of 85 physicians (41.2%) in the intervention arm had burnout compared with 46 of 91 (50.5%) in the control arm (P = .21). Mean (SD) resilience scores at 6 months were 31.9 (5.0) and 29.5 (6.2) among physicians in the intervention and control arms, respectively (P = .01). In multivariable analysis adjusting for baseline score, demographics, specialty, and work hours, the prevalence of burnout was lower (odds ratio, 0.46 [95% CI, 0.21-0.99]; P = .046) and mean resilience score was higher (parameter estimate [scale, 0-40], 1.20 points [95% CI, 0.11-2.28 points]; P = .03; Cohen d = 0.17) among physicians in the intervention arm vs the control arm after 6 months. Conclusions and Relevance:In this randomized clinical trial to evaluate the effect of wearing a smartwatch and having access to its physiological data on physician well-being, physicians who wore a smartwatch experienced improvements in burnout and resilience. Future research should explore whether engagement with smartwatch data leads to actual behavior change (eg, adaptive coping or reflective habits) that reduces burnout risk and enhances resilience. Trial Registration:ClinicalTrials.gov Identifier: NCT05463250.

Background When job demand exceeds job resources, burnout occurs. Burnout in healthcare workers extends beyond negatively affecting their functioning and physical and mental health; it also has been associated with poor medical outcomes for patients. Data-driven technology holds promise for the prediction of occupational burnout before it occurs. Early warning signs of burnout would facilitate preemptive institutional responses for preventing individual, organizational, and public health consequences of occupational burnout. This protocol describes the design and methodology for the decentralized Burnout PRedictiOn Using Wearable aNd ArtIficial IntelligEnce (BROWNIE) Study. This study aims to develop predictive models of occupational burnout and estimate burnout-associated costs using consumer-grade wearable smartwatches and systems-level data. Methods A total of 360 registered nurses (RNs) will be recruited in 3 cohorts. These cohorts will serve as training, testing, and validation datasets for developing predictive models. Subjects will consent to one year of participation, including the daily use of a commodity smartwatch that collects heart rate, step count, and sleep data. Subjects will also complete online baseline and quarterly surveys assessing psychological, workplace, and sociodemographic factors. Routine administrative systems-level data on nursing care outcomes will be abstracted weekly. Discussion The BROWNIE study was designed to be decentralized and asynchronous to minimize any additional burden on RNs and to ensure that night shift RNs would have equal accessibility to study resources and procedures. The protocol employs novel engagement strategies with participants to maintain compliance and reduce attrition to address the historical challenges of research using wearable devices. Trial Registration NCT05481138.

Background The occupational burnout epidemic is a growing issue, and in the United States, up to 60% of medical students, residents, physicians, and registered nurses experience symptoms. Wearable technologies may provide an opportunity to predict the onset of burnout and other forms of distress using physiological markers. Objective This study aims to identify physiological biomarkers of burnout, and establish what gaps are currently present in the use of wearable technologies for burnout prediction among health care professionals (HCPs). Methods A comprehensive search of several databases was performed on June 7, 2022. No date limits were set for the search. The databases were Ovid: MEDLINE(R), Embase, Healthstar, APA PsycInfo, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Web of Science Core Collection via Clarivate Analytics, Scopus via Elsevier, EBSCOhost: Academic Search Premier, CINAHL with Full Text, and Business Source Premier. Studies observing anxiety, burnout, stress, and depression using a wearable device worn by an HCP were included, with HCP defined as medical students, residents, physicians, and nurses. Bias was assessed using the Newcastle Ottawa Quality Assessment Form for Cohort Studies. Results The initial search yielded 505 papers, from which 10 (1.95%) studies were included in this review. The majority (n=9) used wrist-worn biosensors and described observational cohort studies (n=8), with a low risk of bias. While no physiological measures were reliably associated with burnout or anxiety, step count and time in bed were associated with depressive symptoms, and heart rate and heart rate variability were associated with acute stress. Studies were limited with long-term observations (eg, ≥12 months) and large sample sizes, with limited integration of wearable data with system-level information (eg, acuity) to predict burnout. Reporting standards were also insufficient, particularly in device adherence and sampling frequency used for physiological measurements. Conclusions With wearables offering promise for digital health assessments of human functioning, it is possible to see wearables as a frontier for predicting burnout. Future digital health studies exploring the utility of wearable technologies for burnout prediction should address the limitations of data standardization and strategies to improve adherence and inclusivity in study participation.

PurposeTo examine graduating medical student reports of burnout by sex, race and ethnicity, and sexual orientation and explore trends within intersectional demographic groups from 2019-2021 in a national sample.MethodThe authors obtained medical student responses to the 2019-2021 Association of American Medical Colleges (AAMC) Graduation Questionnaires (GQs) linked to data from other AAMC sources. The dataset included year of GQ completion, responses to a modified Oldenburg Burnout Inventory (exhaustion subscale range: 0-24; disengagement subscale range: 0-15), and demographics previously shown to relate to the risk of burnout in medical students, residents, or physicians. Multivariable linear regression analysis was performed to evaluate independent associations between demographics and burnout.ResultsOverall response rate was 80.7%. After controlling for other factors, mean exhaustion scores were higher among Asian (parameter estimate [PE] 0.38, 95% confidence interval [CI] 0.21, 0.54), bisexual (PE 0.97, 95% CI 0.76, 1.17), and gay or lesbian (PE 0.55, 95% CI 0.35, 0.75) students than those who did not identify with each of those respective groups. Mean disengagement scores were lower among female (PE -0.47, 95% CI -0.52, -0.42), Hispanic (PE -0.11, 95% CI -0.22, -0.01), and White (PE -0.10, 95% CI -0.19, 0.00) students and higher among Asian (PE 0.17, 95% CI 0.07, 0.27), Black or African American (PE 0.31, 95% CI 0.18, 0.44), bisexual (PE 0.54, 95% CI 0.41, 0.66), and gay or lesbian (PE 0.23, 95% CI 0.11, 0.35) students than those who did not identify with each of those respective groups. From 2019-2021, mean exhaustion and disengagement scores were relatively stable or improved across nearly all intersectional groups.ConclusionsMale, Asian, Black or African American, and sexual minority students had a higher risk of burnout, while female, Hispanic, White, and heterosexual or straight students had a lower risk of burnout.

Goal: This research aimed to evaluate variations in perceived organizational support among physicians during the first year of the COVID-19 pandemic and the associations between perceived organizational support, physician burnout, and professional fulfillment. Methods: Between November 20, 2020, and March 23, 2021, 1,162 of 3,671 physicians (31.7%) responded to the study survey by mail, and 6,348 of 90,000 (7.1%) responded to an online version. Burnout was assessed using the Maslach Burnout Inventory, and perceived organizational support was assessed by questions developed and previously tested by the Stanford Medicine WellMD Center. Professional fulfillment was measured using the Stanford Professional Fulfillment Index. Principal Findings: Responses to organizational support questions were received from 5,933 physicians. The mean organizational support score (OSS) for male physicians was higher than the mean OSS for female physicians (5.99 vs. 5.41, respectively, on a 0–10 scale, higher score favorable; p < .001). On multivariable analysis controlling for demographic and professional factors, female physicians (odds ratio [OR] 0.66; 95% CI: 0.55–0.78) and physicians with children under 18 years of age (OR 0.72; 95% CI: 0.56–0.91) had lower odds of an OSS in the top quartile (i.e., a high OSS score). Specialty was also associated with perceived OSS in mean-variance analysis, with some specialties (e.g., pathology and dermatology) more likely to perceive significant organizational support relative to the reference specialty (i.e., internal medicine subspecialty) and others (e.g., anesthesiology and emergency medicine) less likely to perceive support. Physicians who worked more hours per week (OR for each additional hour/week 0.99; 95% CI: 0.99–1.00) were less likely to have an OSS in the top quartile. On multivariable analysis, adjusting for personal and professional factors, each one-point increase in OSS was associated with 21% lower odds of burnout (OR 0.79; 95% CI: 0.77–0.81) and 32% higher odds of professional fulfillment (OR 1.32; 95% CI: 1.28–1.36). Practical Applications: Perceived organizational support of physicians during the COVID-19 pandemic was associated with a lower risk of burnout and a higher likelihood of professional fulfillment. Women physicians, physicians with children under 18 years of age, physicians in certain specialties, and physicians working more hours reported lower perceived organizational support. These gaps must be addressed in conjunction with broad efforts to improve organizational support.

Pharmacogenomic (PGx) biomarkers integrated using machine learning can be embedded within the electronic health record (EHR) to provide clinicians with individualized predictions of drug treatment outcomes. Currently, however, drug alerts in the EHR are largely generic (not patient-specific) and contribute to increased clinician stress and burnout. Improving the usability of PGx alerts is an urgent need. Therefore, this work aimed to identify principles for optimal PGx alert design through a health-system-wide, mixed-methods study. Clinicians representing multiple practices and care settings (N = 1062) in urban, rural, and underserved regions were invited to complete an electronic survey comparing the usability of three drug alerts for citalopram, as a case study. Alert 1 contained a generic warning of pharmacogenomic effects on citalopram metabolism. Alerts 2 and 3 provided patient-specific predictions of citalopram efficacy with varying depth of information. Primary outcomes included the System's Usability Scale score (0-100 points) of each alert, the perceived impact of each alert on stress and decision-making, and clinicians' suggestions for alert improvement. Secondary outcomes included the assessment of alert preference by clinician age, practice type, and geographic setting. Qualitative information was captured to provide context to quantitative information. The final cohort comprised 305 geographically and clinically diverse clinicians. A simplified, individualized alert (Alert 2) was perceived as beneficial for decision-making and stress compared with a more detailed version (Alert 3) and the generic alert (Alert 1) regardless of age, practice type, or geographic setting. Findings emphasize the need for clinician-guided design of PGx alerts in the era of digital medicine.

Objective To assess the impact of work on personal relationships (IWPR) by specialty and demographic variables in a national sample of physicians, to assess the association between the IWPR and burnout, and to determine the effect of adjusting for IWPR on the risk of burnout associated with being a physician. Methods Analysis was conducted of data from a representative sample of US physicians surveyed between November 20, 2020, and March 23, 2021, and from a probability-based sample of other US workers. IWPR and burnout were measured with published assessments. Results Of the 7360 physicians who responded to the survey, 6271 (85.2%) completed the IWPR assessment. In multivariable analysis, moderate or higher IWPR was associated with female sex (odds ratio [OR], 1.26; 95% CI, 1.11 to 1.43), married vs single (OR, 0.59; 95% CI, 0.48 to 0.71), and emergency medicine (OR, 1.93; 95% CI, 1.43 to 2.60) or physical and rehabilitative medicine (OR, 1.67; 95% CI, 1.12 to 2.50) vs internal medicine subspecialty. Physicians were more likely than workers in other fields (OR, 2.65; 95% CI, 2.33 to 3.02) to endorse the statement “In the past year, my job contributed to me feeling more isolated or detached from the people who are important to me” as at least moderately true. After adjustment for responses to this statement, work hours, and demographic characteristics, being a physician was not associated with the risk of burnout. Conclusion IWPR is associated with burnout. Adjustment for IWPR eliminated the observed difference in burnout between physicians and workers in other fields. Interventions that identify and mitigate work practices that have a negative impact on physicians’ personal relationships and interventions that support affected individual physicians are warranted.

Purpose: This study examines sense of belonging (belongingness) in a large population of medical students, residents, and fellows and associations with learner burnout, organizational recruitment retention indicators, and potentially modifiable learning environment factors. Method: All medical students, residents, and fellows at Mayo Clinic sites were surveyed between October and November 2020 with items measuring sense of belonging in 3 contexts (school or program, organization, surrounding community), burnout (2 Maslach Burnout Inventory items), recruitment retention indicators (likelihood of recommending the organization and accepting a job offer), potentially modifiable learning environment factors, and demographics (age, gender, race and ethnicity, LGBTQ+ identification, disability, socioeconomic background). Results: Of 2,257 learners surveyed, 1,261 (56%) responded. The percentage of learners reporting a somewhat or very strong sense of belonging was highest in the school or program (994 of 1,227 [81%]) followed by the organization (957 of 1,222 [78%]) and surrounding community (728 of 1,203 [61%]). In adjusted analyses, learners with very strong organization belongingness had lower odds of burnout (odds ratio [OR], 0.05; 95% CI, 0.02-0.12) and higher odds of being likely to recommend the organization (OR, 505.23; 95% CI, 121.54-2,100.18) and accept a job offer (OR, 38.68; 95% CI, 15.72-95.15; all P < .001). School or program and community belongingness also correlated strongly with these outcomes. In multivariable analyses, social support remained associated with higher odds of belongingness in all 3 contexts; favorable ratings of faculty relationships and leadership representation remained associated with higher odds of belongingness in 2 contexts (school or program and organization); and favorable ratings of diversity, equity, and inclusion learning climate remained associated with belongingness in 1 context (community). Conclusions: Sense of belonging among medical students, residents, and fellows varies across contexts, correlates strongly with burnout and organizational recruitment retention indicators, and is associated with multiple potentially modifiable learning environment factors.

Objectives Dentists’ well-being is being challenged today by many factors. However, effective screening tools to assess their distress and well-being are yet to be validated. The present study aims to evaluate the ability of the Well-Being Index (WBI) to identify distress and stratify dentists’ well-being and their likelihood for adverse professional consequences. Method and materials A convenience sample of dentists completed a web-based 9-item WBI survey along with other instruments that measured quality of life (QOL), fatigue, burnout, and questions about suicidal ideation, recent dental error, and intent to leave their current job. Results A total of 597 dentists completed the survey. The overall mean WBI score was 2.3. The mean WBI score was significantly greater in dentists with low QOL than among dentists without low QOL (4.1 vs 1.6, p < 0.001). Dentists with extreme fatigue, burnout, and suicidal ideation had significantly higher mean WBI score than those without distress (all p < 0.001). WBI score stratified the dentists’ likelihood of reporting a recent dental error and intent to leave their current job. Conclusion The WBI may be a useful screening tool to assess well-being among dentists and identify those in distress and at risk for adverse professional consequences.

The act of taking vacation is restorative for individuals and advantageous for both employer and employee. Time away from work contributes to personal relationship satisfaction and is linked to improved physical and mental health.1, 2 Vacation time also enhances job performance and satisfaction while mitigating burnout and attrition.3, 4 Despite these benefits, fewer than half of American workers use their entire allocated paid time off.5 A recent study of U.S. physicians across all specialties demonstrated that approximately 60% of physicians reported taking 15 or fewer days (≤3 weeks) of vacation, with 20% taking 5 or fewer days, in the past 12 months.6 Vacation days varied significantly by specialty, with emergency medicine (EM) having the lowest percentage of physicians taking more than 3 weeks of vacation. This study is a secondary analysis of the aforementioned study6 and focuses on the subset of participants who were emergency physicians (EPs). The study's aim was to further characterize the EPs' vacation behaviors and to analyze the association of vacation characteristics with EP demographic and professional factors. A national work–life integration study surveyed a representative sample of physicians across all specialties in the American Medical Association Physician Professional Data between November 20, 2020, and March 23, 2021, using methods that were previously reported.6, 7 The Physician Professional Data is a nearly complete record of all U.S. physicians. Among the 3671 physicians who received the mailed survey along with a $20 incentive check, 1162 (31.7%) completed the survey. Of the 90,000 physicians who received the electronic survey, 6348 (7.1%) completed the survey. A random subset of participants received a mailed or electronic subsurvey about vacation. As previously reported,7 detailed analysis comparing the demographic characteristics of participating physicians with all 897,107 practicing U.S. physicians as well as a secondary survey of non-responders, suggested that participants were representative of U.S. physicians. The Stanford and Mayo Clinic Institutional Review Boards approved this study, which followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines. The vacation subsurvey asked physicians, "Using the definition of vacation that applies to your practice, how many days of vacation did you take in the last 12 months?" Physicians were also asked, "On a typical vacation day in the last year, how much time did you spend responding to patient-related phone calls, inbox messages in the EHR and other work-related email?" and whether they had full EHR inbox coverage while on vacation. Finally, physicians were asked how much of a barrier to taking vacation the following dimensions was for them: finding someone to cover clinical responsibilities, financial impact on professional compensation, and the volume of EHR inbox work to be faced on return. Standard demographic information, including age, gender, relationship status, specialty, hours worked per week, and primary practice setting, was collected. In addition, physicians were asked what percentage of their compensation was based on productivity. Physicians' demographic and professional characteristics and their responses to vacation barriers were summarized using standard descriptive statistics. Associations between vacation response items and demographic and professional factors were examined using Fisher's exact tests. Statistical significance was set at two-tailed p < 0.05 and analyses were conducted using R software (v4.1.2, R Core Team). A total of 3128 physicians were invited to complete the vacation subsurvey, with 3024 (96.7%) completing at least one vacation item. Among these respondents, 175 identified as EPs. Comparable to responding physicians across all specialties, most of the EP respondents were men (63.4% EPs vs. 62% all physicians), were married (86.3% EPs vs 83.7% all physicians), and had children ≤18 years old (54.1% EPs vs. 45.5% all physicians; Table 1). The median number of hours worked per week was 36 (IQR 30–43.5 h) for EPs and 50 (IQR 40–60 h) for all responding physicians. More than half of the EPs worked in a private practice setting (57.5%) and reported that their compensation was not based on productivity (53.1%). Over three-quarters of EPs (76.2%) reported taking 15 or fewer days (≤3 weeks) of vacation in the past 12 months (Table 1) versus 59.6% for all physicians. In the past year, 53 (30.8%) EPs reported ≤5 days of vacation, 78 (45.3%) 6–15 days of vacation, and 41 (23.8%) >15 days of vacation. Vacation days were not associated with EP demographics (age, gender, relationship status, age of youngest child) nor professional factors (hours worked per week, primary practice setting, percent compensation based on productivity). Compared to EPs in private practice, a greater proportion of EPs in academic medical centers reported spending more than 30 min of work on vacation per vacation day (14.1% vs. 39.6%). Most EPs replied "not at all" when asked to what degree the following were considered a barrier to taking vacation: finding someone to cover clinical responsibilities (61.8%), the financial impact of taking vacation (50.9%), and the volume of EHR inbox work to face on return to work (79.1%). EM has traditionally been viewed as one of the specialties with a "controllable lifestyle,"8 with shift-based clinical work considered one of the draws. Our targeted analysis of EPs' vacation characteristics, however, raised more questions than answers about whether expectations of EM as a specialty that is amenable to work–life balance and flexibility are accurate. The primary analysis of U.S. physicians across all specialties previously revealed that EPs were the least likely to take more than 15 vacation days per year.6 Despite EPs working fewer median hours per week compared to other physicians, more than three-quarters of EPs reported taking fewer than 16 days of vacation, with nearly one-third taking less than a week of vacation in the last year. This secondary analysis of EPs showed that vacation days taken did not differ by gender, age, relationship status, hours worked, practice setting, and compensation model. It is unclear why EPs reported taking the least amount of vacation compared to other physicians. Given that EPs work fewer median hours per week, it is possible that the greater amount of time off, along with the benefits that come with time off from work, may make additional vacation unnecessary. While this may be true for some, the fewer hours of clinical work alternatively allow more opportunities for vacation to be taken, and our results suggest that this is not the case for the majority of EPs. The barriers to taking vacation queried in the survey did not explain this discrepancy. We theorize that one of the reasons why EPs reported not taking many vacation days may be the way in which vacation is perceived among EPs. Many EM contracts—in both academic and nonacademic settings—specify an expected number of clinical hours per year and do not include paid time off. What remains unclear is how EPs treat or view the time they have outside of these required hours. For example, clinic-based specialties that operate on a Monday to Friday schedule typically have weekends off; weekends in this situation likely are considered "days off" and not "vacation." For EPs, "days off" are scattered between shifts. If an EP wishes to have a week off, they likely have to work the same number of shifts that month but fitted into the days before and after the week off. In this situation, EPs may differ in whether they consider the non–work week as "days off" versus "vacation." This arrangement also results in EPs having to "pay" for vacation by taking on more burdensome clinical responsibilities in the weeks before or after time off. And since EM shifts cover 24 h of each day, most EPs need non-clinical time to recover from frequent circadian shifts, which may carve into functional time off. We do not know how much of these factors act as barriers to EPs taking vacation. We also do not know if the benefits of "vacation" are also seen with having several consecutive "days off." Regardless of how EPs define vacation, the benefits of taking time away from work should make it a priority for physicians and their employers. There are systems-based interventions that may encourage EPs to take vacation. EM groups may proportionately decrease expected shifts during the month that vacation is taken or allow EPs to bank shifts over months to support extended time off. Compensation models that build in paid time off or that do not rely exclusively on relative value unit–related reimbursement may encourage EPs to take vacation as well. EPs themselves may also consider policing and limiting their own workload to allow vacation time. This may require a change in perspective such that time devoted to vacation is not viewed as "lost compensation" but rather an essential and expected part of the job that promotes career longevity and well-being. Finally, innovative tools that take advantage of artificial intelligence could be used to analyze physician preferences, availabilities, and vacation needs in optimizing complex schedules.9 As previously reported,6 although participants were shown to be representative of U.S. physicians, the response rate to the main survey was low and there is a possibility of response bias. This secondary analysis was also limited by the small sample size of EPs. We do not know how each responding EP defined vacation for themselves. We also do not know if EPs' estimation of work hours or EHR inbox work included nonclinical work, such as email, administrative duties, research, or education. In addition, the study occurred during the first year of the COVID-19 pandemic; travel restrictions and social distancing may have impacted physicians' answers about vacation. Shift work is the norm not just in EM but also in critical care, hospitalist, and other specialties. Future studies on this topic may reveal important physician workforce trends that need to be addressed for purposes of professional satisfaction and career longevity. Future work within EM is also needed to clarify how EPs, compared to other physicians, define vacation and what barriers prevent them from taking time off. Research into this subject, as well as potential solutions, may have important ramifications for how EM is perceived as a desirable specialty by the pipeline of future trainees.10 A better understanding of EPs' vacation use may also inform ongoing efforts to mitigate high levels of EP burnout7 and attrition.11 Dave W. Lu, D. Mark Courtney, Christine A. Sinsky, Liselotte N. Dyrbye, Lindsey E. Carlasare, Colin P. West, Tait D. Shanafelt conceived and designed the study. Liselotte N. Dyrbye, Christine A. Sinsky, and Tait D. Shanafelt supervised the conduct of the study, data collection, and data management. Tait D. Shanafelt and Hanhan Wang provided statistical advice on study design, analyzed, and interpreted the data. Dave W. Lu drafted the manuscript, and all authors contributed substantially to its revision for important intellectual content. Tait D. Shanafelt obtained research funding. Dave W. Lu takes responsibility for the paper as a whole. Funding for this study was provided by the Stanford WellMD Center, Mayo Clinic Department of Medicine Program on Physician Well-being, and the American Medical Association. Consulting for commercial interests, including advisory board work: MTT reported receiving personal fees from Marvin Behavioral Health, Inc., outside the submitted work. Grant money for commercial research: LND reported receiving grants from Med Ed Solutions outside the submitted work. Grant money for investigator-initiated research: LND reported receiving grants from the National Institute of Nursing Research and the National Science Foundation during the conduct of the study. Founder or owner of a start-up company or proprietary interest or stock or ownership in a company with an interest for or against the subject matter: LND, TDS co-invented the Well-Being Index and its derivatives; Mayo Clinic licensed the Well-Being Index and pays them royalties outside the submitted work. Employment: CAS, LEC are employed by the American Medical Association. The opinions expressed in this article are those of the authors and should not be interpreted as American Medical Association policy. The other authors declare no conflicts of interest.

GOAL:We sought to build upon previous studies that have demonstrated how healthcare workers' ratings of their immediate supervisor's leadership capabilities relate to their well-being and job satisfaction. METHODS:In 2022, we analyzed cross-sectional data from 1,780 physicians and 39,896 allied health professionals (collected in 2017) and 729 residents (collected in 2019), as well as longitudinal data from 1,632 physicians (collected from 2015 to 2017), to identify a psychometrically strong, broadly applicable, actionable, and low-burden approach to assessing supervisor leadership capability to support healthcare worker well-being. PRINCIPAL FINDINGS:The magnitude of association between our 1-, 2-, 3-, and 9-item leadership indexes and burnout, and between our 1-, 2-, 3-, and 9-item leadership indexes and satisfaction with the organization were similar to each other in the cross-sectional and longitudinal cohorts and across diverse groups of healthcare workers, including physicians, residents, and allied health professionals. The likelihood ratio for a high leadership score increased with an increasing score for each leadership measure. The area under the receiver operating characteristic curve for the 1-, 2-, and 3-item measures for a high leadership score was 0.9349, 0.9672, and 0.9819, respectively. PRACTICAL APPLICATIONS:A single item assessing perceptions of leadership capability efficiently provides useful information about leadership qualities of healthcare workers' immediate supervisors. The inclusion of this item in healthcare worker surveys may be useful for evaluating interventions and galvanizing organizational action to support healthcare worker well-being.