This chapter describes the potentially modifiable contributory factors for which there is evidence supporting either a direct association or a strong indirect relationship with clinician burnout. The chapter first elaborates on the relationships between the factors that contribute to burnout and the committee’s systems model for burnout and professional well-being (see Chapter 2). The second section discusses the evidence for contributory factors, starting with work system factors related to the demands and resources of a clinician’s job, followed by the individual (clinician) factors that mediate burnout. Many of these contributory factors are under the control of the health care organization, which largely decides how work will be performed. In addition to the direct negative impact of high job demands and low job resources on burnout, the job demands–resources model suggests that job resources can offset the adverse effects of increased
1 Excerpted from the National Academy of Medicine’s Expressions of Clinician Well-Being: An Art Exhibition. To see the complete work by Zohal Ghulam-Jelani, visit https://nam.edu/expressclinicianwellbeing/#/artwork/347 (accessed January 30, 2019).
job demands (Bakker and Demerouti, 2007, 2017; Demerouti et al., 2001). Systems approaches and interventions that address the contributory factors described in this chapter are discussed in detail in Chapter 5.
RELATIONSHIP TO THE COMMITTEE’S SYSTEMS MODEL OF BURNOUT AND PROFESSIONAL WELL-BEING
Worker capacities and needs, job content, the work environment, organizational conditions and culture, and personal considerations—and the ways these components interact with each other—make up the work system (Carayon, 2009; ILO, 1986; Smith and Sainfort, 1989). In the committee’s model, decisions made at all levels—frontline care delivery, the health care organization, and the external environment—can affect clinicians’ experiences at the frontline care delivery level (i.e., “the work system”) (see Figure 4-1). This chapter focuses on the work system factors—framed as the job demands and job resources perceived by individual workers—that are under the control of health care organizations and how they affect clinicians at the frontline care delivery level. The chapter also discusses how individual factors related to the clinician may mediate the impact of the work system factors leading to burnout. Chapter 5 will build on the conclusions of this chapter to propose guidelines to address clinician burnout. Chapter 6 will examine factors related to the external environment, such as payment policies, regulatory oversight, and professional and societal expectations. And Chapter 7 will expand on some of the factors related to technology that are discussed in this chapter.
Figure 4-2 shows the work system factors, which are conceptualized as job demands and job resources that appear to contribute to clinician burnout and professional well-being. Information on clinicians’ experience of job demands and job resources may be used as feedback to change (or redesign) the system elements at each of the three levels of the system. Job demands include workload and time pressure, various intrinsic aspects of clinical work (e.g., moral distress), and work inefficiencies (e.g., administrative burden, inadequate technology usability). Job resources include tangible and intangible resources within the work environment, such as meaning in work, job control, and the availability of social support from peers and supervisors (Bakker and Demerouti, 2017; Bakker et al., 2010; Demerouti et al., 2001). The work system is influenced by the organization and includes job structure, local culture, values and expectations, leadership, and the amount of individual job control (e.g., flexibility or autonomy). Other factors, which are unique to each individual, mediate the effects of these work system factors on clinician burnout and professional well-being. Each of the work system factors and individual mediating factors are discussed in detail in the sections that follow.
When job demands require sustained physical or psychological effort or skills, individuals experience physiological or psychological costs, including burnout. Job demands can exceed an individual’s available capacity or skills when the work is inefficient (and especially when it requires numerous tasks that are considered by the clinician to be lower priority than or a distraction from direct patient care). Poorly designed work systems and chronically excessive job demands can exhaust employees and lead to burnout. Similarly, when psychological or psychosocial capacities are exceeded in response to repeated exposure to suffering, death, or social inequities without sufficient structural mechanisms to address them, emotional exhaustion can
significantly contribute to burnout. When job resources are lacking because of the structure of the job (e.g., a low level of autonomy or flexibility) and when the associated organizational culture and leadership do not support individual work goals, goal failure occurs, and burnout may develop. An imbalance between job demands and resources can also occur when there is inadequate job control or insufficient professional support, particularly during challenging and demanding work. When the overall job resources available (supply) do not fit with what is required (demand) to achieve the goal, resulting in goal failure, individuals become stressed and frustrated (Caplan, 1987; Caplan et al., 1975). In this section, the committee discusses the relationship between job demands and clinician burnout.
Job demands may contribute to work overload (Demerouti et al., 2001). Job demands are a function of work frequency and duration, work intensity, and the nature of the work itself, including the context in which the work is performed. Job demands can often be measured by objective organizational metrics such as shift duration, rotation, and frequency and patient load (e.g., panel size, patient encounters, staffing ratios) as well as with measures of patient complexity or acuity. Different clinicians’ work schedules and activities (including after-hours work) can be organized quite differently. Emergency physicians, nurses, and pharmacists are shift workers, whereas surgeons and
many specialist internists have more irregular schedules that include intermittent “call” shifts or other after-hours work. Thus, measures of job demands will vary depending on the clinician’s job. For inpatient nurses, a common metric of job demand is the number and length of shifts, while for work intensity it is nurse-to-patient ratio, adjusted for some measure of patient acuity. As a multi-dimensional concept, job demand is assessed in many different ways, with the results operationalized into different descriptive variables such as workload, time pressure, and inadequate staffing.
Excessive Workload, Unmanageable Work Schedules, and Inadequate Staffing
Workload can be conceptualized in two different ways—either as the work performed or capable of being performed within a specified time, or, more commonly in human factors engineering, as the effects of the work on the worker. In the latter case, rigorous studies use validated worker self-report tools (the most common being the National Aeronautics and Space Administration’s Task-Load Index; see Hart and Staveland, 1988), physiological measures (e.g., heart rate and heart rate variability; see Weinger et al., 2004), or quantitative metrics related to the tasks being performed or neglected (Cao et al., 2008). The concept of mental workload has been well elaborated (e.g., Rasmussen , Gopher and Donchin ) and there is extensive literature on workload assessment (Eggemeier, 1988; Hancock et al., 1985; Meshkati, 1988; Moray, 1979; Wilson and O’Donnell, 1988).
Across many industries there is ample evidence that excessive workload is associated with increased worker stress as well as with decreased job performance, including an increase in errors and accidents (Karasek and Theorell, 1990; Vidulich and Tsang, 2012; Young et al., 2015). In a direct-observation study of 124 intensive care unit (ICU) nurses, an increase in the number of medication-related events was associated with an increase in task demands and in nurses’ subjective workload (Xu et al., 2017). In a survey of pediatric nurses, both mental workload (related to interruptions, divided attention, being rushed) and the perception of staffing adequacy were predictors of burnout (Holden et al., 2011).
For more than a century, the norm for health care professionals has been to work long intense hours and to selflessly put patients’ needs ahead of one’s own. Yet, despite compelling positive associations between job demands and burnout, as discussed in the remainder of this chapter, the “demand side” of the equation is not the entire story; the nature of modern clinical work is as important as, if not more important than, the actual work hours. For example, a number of studies across professions show that other factors, such as job control (Pisanti et al., 2016a; Portoghese et al.,
The scientific literature does not provide enough evidence to determine the precise relationships between job demands and clinicians’ resulting perceptions of their workload and associated stress. However, a number of factors that have been shown to be associated with less burnout likely act, at least in part, on these relationships; such as for a given level of job demands, the workload will be perceived as lower when a clinician finds greater meaning in work; experiences greater job control, rewards, or sense of community; or works in a supportive organizational culture. Globally considered, the evidence for an association between job demands and clinician burnout is arguably the strongest for any independent variable.
In a 2002 study of 1,740 U.S. oncologists, the most common self-reported contributors to burnout were excessive workload and insufficient time away from the office (Allegra et al., 2005). With regard to hours at work, a review of 47 multinational studies of physicians published between 2008 and 2013 (Amoafo et al., 2015) found that longer work hours was a strong predictor of burnout. A subsequent systematic review of studies published between 2010 and 2016 (Azam et al., 2017) reported that 21 of 31 studies found at least one measure of job demands to be significantly associated with burnout. In a systematic review of 71 studies of burnout in surgeons (Oskrochi et al., 2016), total work hours, frequency of call, and patient load were all associated with high emotional exhaustion. When Embriaco and colleagues (2007a) surveyed 978 critical care physicians from 189 French ICUs, they found that almost 50 percent of respondents met their criteria for burnout. Workload (number of night shifts per month and time since most recent non-working week) was a strong independent predictor of burnout. With regard to workload, “perception of the work as stressful” was strongly associated with increased emotional exhaustion in orthopedic surgeons (Arora et al., 2013).
According to a multi-variate analysis of the results of a survey of 7,288 U.S. physicians, for every extra hour worked (above 51.8 hours) per week, the odds of burnout symptoms increase by about 2 percent (Dyrbye et al., 2013). Night call is extremely taxing, and several large studies found that for each additional night on call per week, the odds of burnout increased by from 3 to 9 percent (varying in part because of differences in the baseline incidence of night call among study populations) (Dyrbye et al., 2011a, 2013; Shanafelt et al., 2009a, 2012b). In a study of 1,490 U.S. oncologists, for each extra hour spent at home working (e.g., on electronic documentation), there was a 2 percent increase in the odds of burnout (Shanafelt et al.,
2014). These three measures of job demands are probably at least additive so that a physician who is working 60 hours per week, taking more than two calls per week, and taking appreciable work home could be 30 percent or more likely to be at risk of burnout than one in the same specialty who works 50 hours per week, takes one call per week, and does little work once at home.
One of the arguments for extended work schedules is care continuity—if the same clinician cares for the same patient for extended periods of time, there will be fewer care transitions (i.e., handovers) and thus a lower likelihood of errors and care gaps (Arora and Farnan, 2008; Riesenberg et al., 2009). However, even in the absence of sleep deprivation or circadian cycle disturbances, extended day shifts (longer than 12 hours) or repeated continuous work shifts for many days in a row without days off could have adverse effects on clinician performance and degrade clinician well-being. Furthermore, when shift schedules are actively managed, including using structured handovers, there do not appear to be differences in quality of care between extended schedules and those with reasonable work breaks. For example, in a study of 45 intensivists in 5 ICUs taking care of 1,900 patients, the clinicians were cluster-randomized in half-month rotations to either a continuous schedule (14 consecutive all-day shifts) or weekday coverage with weekend cross-coverage by colleagues (interrupted schedule) (Ali et al., 2011). The patient length of stay (LOS) and mortality were non-significantly higher in the continuous schedule condition (ICU LOS 0.36 day, P = 0.20; hospital LOS 0.34 day, P = 0.71; ICU mortality, odds ratio [OR] = 1.43, P = 0.12; hospital mortality, OR = 1.17, P = 0.41). On the other hand, according to survey measures derived from the National Study of the Changing Workforce (Fenwick and Tausig, 2001), the intensivists working under the continuous schedule experienced significantly greater burnout, work–home life imbalance, and job distress.
There are numerous studies that relate measures of (especially inpatient) nurses’ job demands to burnout. Led by pioneering work by Linda Aiken and her colleagues, there is an extensive literature relating higher nurse-to-patient ratios to nurse burnout as well as to other clinician, patient, and organizational outcomes. In a study of more than 10,000 hospital nurses showed that nurses are 23 percent more likely to experience emotional exhaustion for each additional patient they cover after exceeding a 4:1 patient-to-nurse ratio (Aiken et al., 2002). In a 2012 study, increasing the overall workload of the nurses in a hospital by just one patient per nurse was associated with significant increases in both urinary tract and surgical site infections in the patients, and this was mediated by job-related burnout
(Cimiotti et al., 2012). Similarly, Liu et al. (2018) in a study of 1,523 nurses in 23 hospitals in China, found that lower day shift patient–nurse ratios and better work environments correlated with fewer nursing care tasks left undone, less nurse burnout (using the emotional exhaustion sub-scale of the Maslach Burnout Inventory [MBI]), and with better nurse perceptions of patient safety. A meta-analysis by Shin and colleagues (Shin et al., 2018) showed that a greater patient-to-nurse ratio was consistently associated with slightly higher degree of burnout among nurses (OR = 1.07; 95% confidence interval [CI] = 1.04–1.11), increased job dissatisfaction (OR = 1.08; 95% CI = 1.04–1.11), and higher intent to leave (OR = 1.05; 95% CI = 1.02–1.07). The relationship between staffing ratios and burnout persists even after adjusting for wages and other covariates (McHugh and Ma, 2014).
Increased nurse burnout has been associated with “inadequate,” “inappropriate,” or “short” staffing—primarily as measured by nurses’ self-report (Edwards et al., 2018; Garrett, 2008; Simpson et al., 2016)—as well as with perceptions of more “unfinished tasks” (Sochalski, 2001) and missed care (Simpson et al., 2016). In a time-lagged study of 406 Canadian new graduate nurses, short-staffing at the first sample time resulted in more nurse burnout, lower job satisfaction, and lower patient care quality 1 year later (Boamah and Laschinger, 2016). A cross-sectional survey of 821 nurses in 20 urban U.S. hospitals found that perceptions of adequate staffing were associated with lower burnout (Vahey et al., 2004). Consistent with this, a review of seven studies suggested a positive bidirectional relationship between a shortage of oncology nurses’ and their job dissatisfaction, stress, and burnout (Gi et al., 2011).
Independent of total work hours, longer shift length is associated with greater burnout. In a cross-sectional study of 31,627 nurses in 488 hospitals in 12 European countries, nurses who worked shifts greater than 12 hours were much more likely than those who worked shifts of 8 hours or less to experience burnout, be dissatisfied with their job, and report an intention to leave their jobs (Dall’Ora et al., 2015). This study reinforced similar findings in two studies of U.S. nurses by Stimpfel and colleagues (Stimpfel et al., 2012, 2013)—that nurses working shifts of 10 hours or longer were more than twice as likely to experience burnout than nurses working shorter shifts. It is important to note that nurses commonly work longer than their specified shift length (27 percent of the nurses in the Dall’Ora study reported working overtime on their most recent shift). Feeling pressured or expected to work overtime could be an important mediator of the relationship between shift length and burnout (Patrick and Lavery, 2007).
Other measures of job demands that have been associated with nurse burnout include overall job demands, physical demands, and time pressure (Gelsema et al., 2006). In a series of studies involving hospital-based European nurses, higher job demands (Pisanti, 2012; Pisanti et al., 2011)
and increased workload (Portoghese et al., 2014) were associated with higher emotional exhaustion and depersonalization. In a sample of 263 Polish nurses, the strongest correlation with emotional exhaustion was “excessive demands” (Basińska and Wilczek-Ruzyczka, 2013).
The data are more limited for other clinical professionals. Work hours, workload, or time pressure were associated with measures of job stress or burnout in community pharmacists in studies in France (Balayssac et al., 2017), Turkey (Calgan et al., 2011), and the United Kingdom (Lea et al., 2012). There are fewer data for inpatient pharmacists. Among pharmacy practice faculty, greater emotional exhaustion scores were associated with longer working hours (El-Ibiary et al., 2017), but another study of inpatient pharmacists failed to find a significant relationship between work hours and burnout (Jones et al., 2017). Greater external demands experienced during medication dispensing (interruptions, divided attention, and rushing) were positively associated with a risk of burnout among inpatient pharmacists (Holden et al., 2010). In a study among critical care pharmacists, no single factor predicted burnout, but 73 percent of the reporting pharmacists were found to work more than 50 hours per week (Ball et al., 2018).
Among practicing dentists, time pressure and long working hours may be associated with burnout (Singh et al., 2016). In a national survey of 700 New Zealand dentists, 48 percent reported “constant time pressure” as a major stressor (Ayers et al., 2008). In a study of 300 dentists practicing in Northern Ireland, time pressure was associated with the risk of burnout (Gorter and Freeman, 2011). Studies of both Pakistani (Jugale et al., 2016) and Lithuanian (Puriene et al., 2008) dentists found associations between longer working hours and measures of burnout.
Perhaps the most prominent current complaint by clinicians about their workplaces is the excessive amount of time they must spend on administrative tasks. These tasks can be divided into patient care–related (i.e., such clinical administrative tasks as looking up laboratory values or documenting a history and physical examination) and non–patient care–related (e.g., billing activities). Because clinicians view administrative tasks as less meaningful work and finding meaning in one’s work is an important mediator of burnout (see section below), the addition of administrative tasks can be predicted to increase the risk of burnout. In fact, in a study of 1,774 physicians a higher percentage of time spent on administrative duties was associated with decreased career satisfaction and more burnout after adjusting
for gender, race, specialty, and years of experience (Rao et al., 2017). The respondents felt that administrative tasks adversely affected their ability to deliver high-quality care and to focus during patient encounters. Note, however, that while shifting clerical tasks from physicians to nurses may reduce physician burnout, it runs the risk of increasing the burnout of the nurses on whom they are relying (Edwards et al., 2018).
Nurses spend appreciable time doing indirect patient care tasks including clinical documentation, care coordination, patient flow management, reporting of quality indicators, ordering of supplies, and communication tasks. The degree to which such administrative tasks impede direct patient care and engender frustration varies by the nurse’s role and by the administrative resources provided by the organization (Michel et al., 2017). Survey responses from nearly 11,000 nurses in a large Southeastern state suggested that many nurses had inadequate resources or lacked the administrative support necessary to provide quality care (Neff et al., 2011). Similarly, in 974 inpatient clinical pharmacists, administrative burden (“too many non-clinical duties” and “inadequate administrative time”) independently increased the odds of burnout (Jones et al., 2017).
Workflow, Interruptions, and Distractions
Workflow issues are related to work inefficiency and greater difficulty achieving everyday tasks and goals. Workflow that is poorly designed to meet clinicians’ needs leads to frustration and creates time pressure. In a study of 422 family practitioners and general internists, adverse workflow, defined in terms of time pressure and chaotic environments, was associated with symptoms of emotional exhaustion (Linzer et al., 2009). Interruptions and distractions are known to disrupt clinicians’ workflow and are associated with lower-quality and less safe care (Chrouser et al., 2018; Flynn et al., 1999; Morrison and Rudolph, 2011). Interruptions are known to add to cognitive burden, delay task completion, and increase the risk of forgetting tasks (Grundgeiger et al., 2010). Pharmacists have also reported that phone-call interruptions are one of the most stressful parts of their jobs (Munger et al., 2013).
While many interruptions in daily clinical work are clinically relevant and likely inevitable, the introduction of the modern electronic health record (EHR) has created many additional and often unnecessary interruptions. As but one example, excessive and often irrelevant or poorly timed electronically generated alerts or “decision support” prompts lead to interruptions and alert fatigue and are likely associated with burnout (Gregory et al., 2017). This topic is discussed further in Chapter 7.
Inadequate Technology Usability
Technology is a tool that is intended to meet users’ needs. Technology can be designed to be a job resource that will enhance job performance; however, the use of technology can also create new job demands, particularly if that technology is not well designed. Human-centered design evaluates the outcomes of health care technology use in terms of effectiveness, efficiency, safety, and clinician and patient satisfaction (Weinger et al., 2004). An incomplete or ineffective human-centered design or implementation of a technology can lead to products that do not attain optimal outcomes. For example, the poor usability of many types of medical technology, such as infusion pumps, can lead to clinician inefficiency, frustration, and error (Weinger et al., 2011).
The technology that plays the biggest role in creating work frustration and contributing to clinician burnout is the EHR (see Chapter 7 for an expanded discussion of this topic). Greater use of the EHR and other information technology during clinical care is associated with more clinician burnout (Babbott et al., 2014; Shanafelt et al., 2016a).
In an observational study of 57 physicians in four specialties, 47.2 percent of clinic time was spent on the EHR and desk work, nearly double the amount of time spent doing direct patient care tasks (Sinsky et al., 2016). Clinicians also spent 1–2 hours of work, primarily with the EHR, each night after work. A different study using different methods found similar results. In a retrospective cohort audit log and direct observational study of EHR use by 142 family medicine physicians in Wisconsin, full-time physicians spent an average of 4.5 hours during and 1.4 hours after clinic hours per weekday working on the EHR (61 percent of an 11.4-hour workday) (Arndt et al., 2017). The predominant tasks were chart review and documentation (47.9 percent of total use). Nearly 1.5 hours each day were spent managing the inbox. Almost 1 hour of EHR time was spent each weekend day. Shanafelt and colleagues (Shanafelt et al., 2016a) found that physicians who used EHRs or computerized physician order entry (CPOE) were significantly less likely to be satisfied with the amount of time they spent on clerical tasks after adjusting for work hours, specialty, practice setting, and demographic variables. Furthermore, the use of CPOE was associated with a higher risk of burnout (OR = 1.29) after similar statistical adjustments.
Eighty-five percent of 585 physician residents and faculty in 19 primary care programs indicated that the use of the EHR affected their work–life balance. Respondents who spent more than 6 hours per week after hours using the EHR were almost three times (OR = 1.9–4.4) more likely to report burnout and almost four times (OR = 1.9–8.2) more likely to attribute burnout to the EHR (Robertson et al., 2017).
Many nurses and nursing leaders are frustrated with the current EHR (Staggers et al., 2018). In a 2016 online survey, 469 participants from 45 countries expressed low levels of satisfaction (4.5 mean out of 10) with the current state of nursing functionality in EHRs. Two-thirds of the participants provided disconcerting comments associated with their low rankings. More than half of the comments identified technology design issues (e.g., poor usability and interoperability, lack of integration or standards, and limited functionality), while 28 percent noted user–task issues (e.g., failure to meet nurses’ clinical needs) (Topaz et al., 2016). In a single state survey, among 333 advanced practice nurse participants with an EHR, half agreed or strongly agreed that the EHR added to their daily frustration, and one-third reported an insufficient amount of time for documentation. Both insufficient time for documentation (adjusted odds ratio [AOR] = 3.2 [1.8–7.8]) and EHR use adding to daily frustration were predictors of burnout (Harris et al., 2018).
EHR use cannot be disentangled from increasingly granular billing, compliance, and documentation requirements (Downing et al., 2018). And greater clinician involvement in EHR deployment decisions clearly improves the success of deployments (Boonstra et al., 2014). However, human factors evaluations have demonstrated that the poor usability of many EHRs increases task times and contributes to work frustration (Ratwani et al., 2018a,b). Only in the past few years has a groundswell of clinician complaints, supported by increasing evidence of poor usability (Sittig et al., 2018), led to improved efforts by stakeholders in the health information technology (IT) system, including The Office of the National Coordinator for Health Information Technology (ONC) to address the poor usability of EHR products.
In summary, to ensure that the technology used by clinicians and patients enhances rather than degrades well-being, all stakeholders must appreciate that clinicians’ and patients’ experience with the technology will depend on the details of its design, configuration, implementation, and ultimate context of use. Furthermore, the successful use of any technology, including its effects on clinician burnout, is a shared responsibility and requires the productive collaboration of all stakeholders as well as the use of a human-centered design approach to design and implementation (Sinsky and Privitera, 2018). The topic of technology, and specifically health information technology, as both a potential source and solution of the problem of burnout is covered in some detail in Chapter 7.
Time Pressure and Encroachment on Personal Time
Although it has always been the case that many health care professionals work long hours, a number of changes to the practice environment
have increased job demands in many disciplines. Organizational budget structures drive nurse assignment and nurse-to-patient staffing ratios. For physicians and advanced practice providers, increasing expectations concerning productivity and the number of patients seen each day have resulted in shorter office visits, and there is often not enough time for clinicians to complete clinical documentation or other tasks (e.g., order entry) during the workday (Arndt et al., 2017). The introduction of electronic patient portals has led to increased electronic messages and patient queries (see Chapter 7 for an expanded discussion on patient portals). The evidence is mixed on whether patient portals are linked to improved patient outcomes (Goldzweig et al., 2013), but there is evidence that the use of these patient portals may increase patient phone calls and overall workload (Dexter et al., 2016) and create additional work for health care professionals (Palen et al., 2012). This often results in professionals having to perform many professional tasks outside of regular work hours by remotely accessing the EHR to complete professional work on personal time. Although such work is compensated for hourly employees, it is typically not compensated for physicians, advance practice providers (APPs), and other clinicians. This can often lead administrators to erroneously conclude that they have “increased productivity” without increasing costs when, in reality, they have simply extended the work week of health care professionals and stolen time from their families and personal activities. Based on EHR time-stamp data, the average family physician now spends approximately 28 hours per month completing clinical documentation on nights and weekends when he or she is not on duty (Arndt et al., 2017; Sinsky et al., 2016).
Clinical documentation and online patient messages are not the only professional tasks clinicians must perform on personal time. Continuing medical education (CME) and the maintenance of certification (see Chapter 6) are frequently performed on nights, weekends, and even vacation time since most organizations do not provide dedicated time for their completion. Clinicians also must complete a number of required training modules each year, typically mandated by regulators, covering topics such as patient safety, infection control, the Health Insurance Portability and Accountability Act (HIPAA), and human subjects protections. Once again, although the time to complete these tasks may be provided to hourly employees, physicians, APPs, and other salaried or non-hourly health care professionals must typically complete them on personal time. Independent of CME and maintenance of certification, health care professionals must keep abreast of advancing knowledge in their field by reading the literature. Because the pace at which medical knowledge is expanding has accelerated significantly, the time required to stay current has also increased, which is another demand on personal time.
While these time pressures affect health care professionals in all practice settings, several additional dimensions specific to academic practice settings merit attention. For example, academic physicians historically have had a portion of their time dedicated to clinical work and a portion of their time dedicated to scholarly pursuits, including providing education for health care professionals in training and carrying out clinical or translational research (which are core components of their professional duties and necessary to sustain and improve the nation’s health care delivery system). Indeed, the performance of these health care professionals is typically measured using an academic yardstick that requires them to engage in substantial educational activities (lectures and presentations) and produce a specified number of manuscripts and grants in defined timeframes as a requirement for retaining their positions. To increase revenue generation, nearly all academic centers have steadily reduced the proportion of time allocated to scholarly pursuits and increased the time devoted to clinical care without adjusting any of the academic performance expectations. Most academic centers still have a similar set of criteria for the publications, presentations, grants, and educational responsibilities that are required to retain a position. Accordingly, the requirements for scholarly activity necessary to preserve job security have been increasingly shifted to personal time on nights and weekends.
Collectively, all of these variables have led to the encroachment of professional tasks into personal time for health care professionals to a much greater degree than for most other fields (Shanafelt et al., 2012a, 2015, 2019a,b). In most settings, this work is not clearly compensated. These professional activities steal time from family, relationships, self-care, and personal pursuits, creating problems with work–life integration (see section below) as well as with getting adequate sleep, all of which fuel burnout.
An honest accounting of the collective amount of work being done by health care professionals both on and off the clock, along with a recalibration of a sustainable cumulative work week, is long overdue. For academic institutions, this must also include a reassessment of the criteria and timelines required of their faculty for academic promotion and for retaining a position, in light of the reduced scholarly time institutions are now providing.
Moral distress is a factor that contributes to burnout, particularly among critical care clinicians (Johnson-Coyle et al., 2016a; Moss et al., 2016b). It occurs when a clinicians’ professional ethical values or commitments are in-congruent with those of their patients and families, colleagues, supervisors, or the health care organization (HCO) in which they work. In clinicians, moral distress is commonly described as the anguish experienced when clinicians
perceive that they have participated in a morally undesirable situation or been unable to act in accord with their professional ethical values under conditions of constraint or duress (Campbell et al., 2016; Thomas and McCullough, 2015). Pressure to act contrary to ethical standards can arise from patients or their surrogates, the clinical team, the HCO, or the external environment (Burston and Tuckett, 2013; Dodek et al., 2016). For example, providing potentially harmful or futile treatment, providing care that prolongs dying, or witnessing clinicians who give false hope to patients or family members can create moral distress (Campbell et al., 2016; Epstein et al., 2019; Johnson-Coyle et al., 2016b; Thomas and McCullough, 2015). Among nurses poor communication, insufficient input to clinical decisions, clinical disagreements with physicians, unsafe staffing, and unnecessary tests and procedures also contribute to moral distress (Burston and Tuckett, 2013; Pauly et al., 2009; Piers et al., 2012; Sauerland et al., 2015). Witnessing patient care suffer as a result of a lack of provider continuity was identified by a sample of interprofessional clinicians as a key driver of moral distress (Whitehead et al., 2015). Data from a revised instrument to measure moral distress among health care professionals indicated that the most common sources of moral distress among physicians were related to excessive documentation, a lack of resources that compromised patient care, and lack of administrative action (Epstein et al., 2019). Negative perceptions of staffing, support by managers, and resources are influential factors associated with moral distress among nurses (Browning, 2013; Burston and Tuckett, 2013).
These experiences are associated with an organization’s overall ethical climate (Atabay et al., 2015; Epstein et al., 2019; Lamiani et al., 2017; Pauly et al., 2009), perceived practice environment (Hiler et al., 2018), and quality of care (Browning, 2013), which in turn appears associated with nurse outcomes (e.g., retention, job satisfaction) (Hart, 2005; Hiler et al., 2018; Hwang and Park, 2014; Piers et al., 2011). Studies of moral distress among interprofessional clinicians showed that nearly 20 percent of respondents were considering leaving their jobs because of moral distress (Dodek et al., 2016; Epstein et al., 2019; Whitehead et al., 2015), which has implications for workforce sustainability. Ethical climate and practice setting are postulated to be predictors of moral distress along with the frequency of exposure to morally distressing situations, particularly for nurses (Rathert et al., 2016).
Although moral distress appears to be common among nurses in various settings (Rushton et al., 2016), the prevalence of moral distress among other clinicians is less well understood (Dzeng and Curtis, 2018). Several studies have documented moral distress among physicians and other clinicians (Houston et al., 2013; Ulrich et al., 2007; Whitehead et al., 2015), particularly in high-intensity settings such as critical care (Dodek et al., 2016; Epstein et al., 2019; Moss et al., 2016a). The data suggest that moral
distress may be less prevalent in physicians than in nurses (Johnson-Coyle et al., 2016a; Moss et al., 2016a), although this gap may be closing (Epstein et al., 2019). Whether these trends can be generalized requires further investigation.
Repeated episodes of moral distress can have a cumulative effect over time, causing feelings of depletion, disillusionment, despair, and moral residue2 (Carse and Rushton, 2018; Epstein and Hamric, 2009). Practice settings in which the frequency of morally distressing events is higher are priorities for intervention, especially when they are associated with poor ethical climate (Epstein et al., 2019). Several studies have described a relationship between moral distress and burnout among nurses (Delfrate et al., 2018; Johnson-Coyle et al., 2016a; Meltzer and Huckabay, 2004; Piers et al., 2012), as well as among critical care clinicians, with those having higher moral distress scores being more likely to experience burnout (Fumis et al., 2017). Additional research is needed to more fully understand the relationship between moral distress and burnout among nurses and other clinicians and to determine the direction of the relationship (Moss et al., 2016b), as well as whether the development of protective psychological factors or the cultivation of moral resilience, along with interventions that address team and systemic factors that contribute to moral distress and the development of burnout, may mitigate the negative impact of moral distress on burnout (Epstein et al., 2019; Lamiani et al., 2017; Rushton, 2018).
Degraded Patient–Provider Relationships
The opportunity to attend to and ease individual suffering is the reason why many clinicians enter the healing professions. As noted earlier in this chapter, the job demands that erode the time spent with patients or spent on direct clinical care can be contributing factors to burnout. Caring for the sick is not without consequences. When patients die or experience serious preventable adverse events, this can be a major stressor for clinicians. In particular, studies in nurses have reported that dealing with patient death and dying played a role in their distress and burnout (Borteyrou et al., 2014; Payne, 2001; Tawfik et al., 2017). Similarly, in a study of 1,156 physicians from various specialties, caring for dying patients was found to be associated with an increased likelihood of symptoms of burnout (Yoon et al., 2017). Several studies in primary care physicians suggest that interactions with patients who ignore medical advice, insist on unnecessary tests or treatments, or exhibit disrespectful behavior is associated with greater
In dentistry, working in a practice with more anxious patients may predispose a dentist to burnout. In a survey of more than 1,800 Swiss dentists of whom 638 responded, the more anxious that patients in the practice were perceived to be, the higher the risk of burnout (Goetz et al., 2018). A study of 300 dental practices in Northern Ireland found that dealing with difficult patients was associated with higher emotional exhaustion and depersonalization (Gorter and Freeman, 2011). Similarly, pharmacists have reported that managing difficult patients is one of the attributes that is the most stressful in their job (Munger et al., 2013).
Threats of psychological and physical harm from the work environment can negatively affect how clinicians can find joy and meaning in their work (Sikka et al., 2015). Nurses commonly experience incivility from patients and their families (Ulrich et al., 2019), and interpersonal challenges or conflicts with patients also correlate with clinician burnout (Borteyrou et al., 2014; Campana and Hammoud, 2015).
Patient and family physical violence against clinicians is the extreme side of interpersonal conflict (Ulrich et al., 2019), and several studies have found an association between patient/family violence and clinician burnout. In one study, 53 percent of 2,397 nurses and midwives working in Queensland reported having experienced occupational violence (Rees et al., 2018). Those who experienced such violence had higher rates of burnout than those who had not experienced violence. In a study of patient-initiated violence in 1,656 physicians from 123 public hospitals in 3 Chinese provinces, reports of verbal abuse (92.8 percent), physical threats (88.1 percent), and physical assault (81.0 percent) by patients were common (Shi et al., 2015). Exposure to violence was also significantly associated with increased emotional exhaustion and decreased job satisfaction. While physical violence against clinicians in the United States is commonplace, particularly in hospital settings (Phillips, 2016), the committee is not aware of any U.S.-based research that links violence to clinician burnout.
Meaning and Purpose in Work
Purpose, in life and work, gives direction, guides decisions, influences behavior, and propels individuals toward goals or specific outcomes (Steger, 2009). Meaning and purpose are synergistic and can be the fuel for sustained engagement and creativity, particularly under adversity (Rushton, 2018). Both meaning and purpose are critical to clinicians’ professional identity (Tak et al., 2017). In a sample of 1,289 U.S. physicians, “sense of
calling” was strongly associated with elevated levels of meaning in life. In this study, physicians with burnout were less likely to report life satisfaction, commitment to direct patient care, and high life meaning (Tak et al., 2017). In a national study of more than 2,200 U.S. physicians, physicians with burnout were less likely to identify medicine as a calling (Jager et al., 2017). For nurses, the concept of “calling to nursing” is associated with improved meaningfulness in work, career commitment, personal well-being and satisfaction, and work engagement (Ziedelis, 2018).
Finding meaning in work can protect clinicians from burnout (Ben-Itzhak et al., 2015; Rasmussen et al., 2016). For example, in a sample of nurses working in high-intensity settings, meaning in patient care and hope were independent predictors of a lower risk of burnout (Rushton et al., 2015). A study of 300 Israeli physicians found that the existential meaning derived from work served as a significant protective factor against burnout (Ben-Itzhak et al., 2015). In contrast, when dissonance arises between what clinicians find meaningful and the reality of their daily work tasks, they may experience increased work stress and burnout. Physicians who report spending less than 20 percent of their time (approximately 1 day per week) on the professional activity they find most meaningful have higher rates of burnout (Shanafelt, 2009; Shanafelt et al., 2009b). In a related study, the amount of personally rewarding hours spent each day was found to be positively associated with more career and life satisfaction and commitment to clinical practice (Tak et al., 2017).
Alignment between work activities and what an individual finds meaningful has also been shown to be related to burnout in samples of nurses. For example, a better person–job match in six areas of work–life (manageable workload, control, reward, community, fairness, and values) had a direct negative effect on burnout (emotional exhaustion and cynicism in a cross-sectional survey of 215 registered nurses) (Boamah and Laschinger, 2016). Similarly, personal goal facilitation (career fit) was associated with lower burnout in another study of nurses (Pisanti et al., 2016a).
Organizational culture is defined by the fundamental artifacts, values, beliefs, and assumptions held by employees of an organization (Schein, 1992). An organization’s culture is manifested in its actions (e.g., decisions, resource allocation) and relayed through organizational structure, focus, mission and value alignment, and leadership behaviors (see also Chapter 5). Perceptions of low organizational support, organizational politics, or insufficient resources offered for professional development may increase the risk of burnout among clinicians (Lorenz and Guirardello Ede, 2014; McAbee et al., 2015). For example, having inadequate time for professional development was an independent predictor of burnout in a multi-variate analysis performed on a national sample of 783 neurosurgeons (McAbee et al., 2015). Similarly, inadequate time allocated for teaching independently increased the odds of burnout in a sample of 974 inpatient clinical pharmacists (Jones et al., 2017). Management and policy decisions and
change-management processes influence the daily work lives of health care professionals and set the tone for decision latitude and interprofessional collaboration (Van Bogaert et al., 2013). Another important component of an organization’s culture is the ethical climate, which influences the way clinicians appraise their relationships, leadership, and workplace (see previous section on Moral Distress and Chapter 5).
Overall organizational culture can be reflected in a clinician’s satisfaction with the overall work environment. Physicians and nurses who are less satisfied with their work environment are more likely to experience burnout (Aiken et al., 2012; Casalicchio et al., 2017; Hanrahan et al., 2010; Hayes et al., 2015; Kutney-Lee et al., 2013; McHugh and Ma, 2014; Meeusen et al., 2011; O’Mahony, 2011; Pantenburg et al., 2016; Patrician et al., 2010; Poghosyan et al., 2010). Similar findings have been reported in mental health providers (Green et al., 2014).
In contrast, healthy work environments have been positively associated in nuses with job satisfaction, retention, and better patient outcomes and negatively correlated with emotional strain (emotional exhaustion, burnout, compassion fatigue, and stress) (Aiken et al., 2011, 2012; Cho et al., 2015; Lake et al., 2019; McHugh and Ma, 2014; Olds et al., 2017; Pantenburg et al., 2016; Ulrich et al., 2019; Van Bogaert et al., 2013; Wei et al., 2018). For example, in a sample of more than 2,300 physicians in Germany, higher satisfaction with the work environment was associated with lower emotional exhaustion and depersonalization (Pantenburg et al., 2016). Similarly, in a study of more than 26,000 nurses, better work environment quality was associated with less burnout and job dissatisfaction after controlling for wages and other covariates (McHugh and Ma, 2014). In a retrospective, two-stage study of nurses employed in hospitals between 1999 and 2006, improvements in perceptions of the work environment were associated with lower adjusted rates of emotional exhaustion, job dissatisfaction, and intent to leave (Kutney-Lee et al., 2013). One potential approach to improving the work environment would be to implement the American Association of Critical-Care Nurses’ Healthy Work Environment standards (AACN, 2016) (see Chapter 5). The 2018 National Survey of Critical Care Nurse Work Environments, which involved more than 8,000 acute and critical care nurses (Ulrich et al., 2019), found that nurses working in clinical units actively addressing work environment issues rated the work environment more positively than nurses who were not working in such units.
Alignment of Values and Expectations
Studies indicate that when individual clinicians perceive that their values are aligned with the values of the organization, engagement and job
satisfaction increase (Linzer et al., 2017; Rothenberger, 2017). Conversely, when values or expectations are not congruent, the resulting dissonance intensifies stress, and burnout can result (Leiter et al., 2009). For example, a longitudinal survey in a sample of practicing primary care physicians working in a large integrated delivery system found that values dissonance along with workload and job control were the largest drivers of burnout (Gregory and Menser, 2015). In a study of 88,605 U.S. Department of Veterans Affairs employees, alignment between stated values and the organization’s behaviors and decisions was associated with more favorable perceptions of organizational culture, which in turn was related to employee satisfaction and worker engagement (Foglia et al., 2013). The issue of what constitutes important aspects of an ethical climate with respect to creating a positive work environment is discussed in Chapter 5.
Job Control, Flexibility, and Autonomy
Job control (also referred to as job decision latitude), flexibility, and autonomy are associated with clinician burnout. For this discussion, autonomy can be defined as the amount of freedom an individual has to control and plan his or her work activities and the input that an individual has in decisions that affects the work (Maslach and Leiter, 2008).
Several cross-sectional studies of physicians have reported a low sense of control over the practice environment, little autonomy, and lack of involvement in decision making correlate with burnout (Campbell et al., 2001; Gabbe et al., 2002; Gregory and Menser, 2015; Linzer et al., 2009; Oskrochi et al., 2016). For example, in a study of chairs of obstetrics and gynecology, low perceived control over professional life was independently associated with burnout after controlling for work–life integration, partner support, and current work-related stressors (Gabbe et al., 2002). A small longitudinal study of primary care physicians indicated that job control played a central role in physicians’ experience of burnout and emphasized the need for physicians to be involved in practice-related decisions as a key strategy for reducing burnout (Gregory and Menser, 2015).
Similarly, a lack of input in decision making, particularly in the context of the reorganization of work, is a source of stress for nurses (Billeter-Koponen and Freden, 2005). In a study of more than 20,000 nurses working in 425 hospitals, higher perceived engagement in shared governance
(i.e., frontline workers being active and empowered to influence institutional decision making) was associated with lower emotional exhaustion, better job satisfaction, less turnover intention, higher nurse-reported quality of care, and better patient-reported care experience scores (Kutney-Lee et al., 2016). Several cross-sectional studies of nurses working outside the United States have reported associations between limited autonomy, input in decision making, and job control and burnout (Lorenz and Guirardello Ede, 2014; Mudallal et al., 2017; Pisanti et al., 2016b). For example, in a national sample of more than 2,400 ICU nurses in France, the inability to schedule days off according to personal wishes was associated with symptoms of burnout (Poncet et al., 2007), and in a study of more than 1,300 Italian hospital-based nurses, lower job control was independently associated with higher emotional exhaustion and depersonalization (Pisanti, 2012). Longitudinal studies exploring the relationship between job control and burnout are limited. In one small longitudinal study of 217 nurses working in Italy, decreases in perceived job control predicted increased emotional exhaustion scores 14 months later, after controlling for baseline job characteristics (Pisanti et al., 2016b). In contrast, a longitudinal study of 170 nurses working in 15 emergency rooms in Belgium found that changes in perceived job control did not predict changes in emotional exhaustion scores 18 months later after controlling for other factors (Adriaenssens et al., 2015a). These differences may be due to differences in workload, as one study of 352 hospital workers (nurses and others) from 5 Italian public hospitals reported that job control mediated the relationship between workload and emotional exhaustion (measured by the MBI–General Survey [MBI–GS]) (Portoghese et al., 2014).
Research by Leiter and Maslach suggests that personal resources are expended to meet job demands and that when this effort does not result in reward, work stress occurs and burnout ensues (Leiter and Maslach, 2004). Individuals experience intrinsic rewards when they perceive work as meaningful, have job control, feel mastery over their work (especially when challenged), are respected, and connect with others at work (Deci and Ryan, 1985). In a study of more than 800 physicians in the United Kingdom, deriving intellectual stimulation from work was found to contribute to job satisfaction, which in turn had a protective effect against job stress on emotional exhaustion and depersonalization (Ramirez, 1996). On the other hand, threats to mastery—such as feeling inadequately trained—may increase the risk of burnout (Ramirez, 1996). Intrinsic rewards derived from meaning in work are discussed further in the earlier Meaning and Purpose in Work section. Extrinsic rewards include money, prestige, and praise. The
last factor, explicit feedback on a “job well done” from supervisors, peers, and patients, is an important reward for clinicians.
For external rewards, one typically thinks of financial compensation, but in a national sample of more than 900 general and subspecialty physicians, no relationship was found between gross income and burnout (Keeton et al., 2007). Similarly, a small longitudinal study of primary care physicians found that workload and job control—but not rewards—predicted burnout (Gregory and Menser, 2015). However, relationships have been found between physician burnout and compensation models. A 2008 study of 7,900 surgeons reported that incentive pay based entirely on an individual’s billings was associated with a 37 percent increased odds of burnout, after controlling for demographics, years in practice, subspecialty, hours worked per week, number of nights on call, practice setting, and other professional factors (Shanafelt et al., 2009a). Another study, in 1,490 U.S. oncologists, similarly found that the risk of burnout increased with greater reliance on productivity-based compensation (Shanafelt et al., 2014). On the other hand, some (Porter et al., 2018; Sargent et al., 2004) but not all (Bertges Yost et al., 2005) studies using a univariate analysis have found financial stress or concerns to be related to domains of burnout, although in a study involving more than 700 neurosurgeons, a multi-variate analysis found that concerns about future earnings was an independent predictor of burnout (McAbee et al., 2015).
Differences in nurses’ overall compensation may not be a contributory factor in burnout. In a study of more than 26,000 registered inpatient nurses working in non-federal acute hospitals in four states, wages did not explain differences in nurses’ emotional exhaustion after adjusting for nurse-to-patient ratio (McHugh et al., 2013). However, in a study of 602 Canadian nurses, a perceived imbalance between effort expended and the rewards provided was associated with burnout (Pratt et al., 2009). Similarly, in a cohort of 974 inpatient clinical pharmacists, while payment structure (salaried versus hourly with overtime pay) was not an independent predictor of burnout, feeling that one’s contributions were underappreciated by others doubled the odds of burnout (Jones et al., 2017).
Professional Relationships and Social Support
It could be said of every clinician “that strong relationships with patients also benefit the health of physicians” (Dugdale, 2017, p. 1075). In line with this, interpersonal relationships between colleagues can be a source of support that buffers against detrimental stress or, alternatively, can be a source of tension and conflict and contribute to work-related stress (Borteyrou et al., 2014; Leiter and Maslach, 1988).
Several studies have suggested that poor professional relationships increase the risk of burnout (Embriaco et al., 2007a; Leiter and Maslach, 1988; Oskrochi et al., 2016; Pereira et al., 2016; Petitta et al., 2017). For example, in a study of more than 900 critical care physicians working in France, impaired relationships with physician colleagues were independently associated with higher burnout (Embriaco et al., 2007a).
Poor relationships with colleagues has also been demonstrated to correlate with burnout among nurses in both cross-sectional (Adriaenssens et al., 2015b; Embriaco et al., 2007a; Li et al., 2013; Oyeleye et al., 2013; Payne, 2001; Read and Laschinger, 2013) and longitudinal studies (Nicholson et al., 2014). Supervisor incivility and co-worker bullying were associated with emotional exhaustion among a group of 342 new graduate nurses in Ontario (Read and Laschinger, 2013). Co-worker incivility at baseline predicted depersonalization 1 year later in 300 nurses in Canada (Nicholson et al., 2014).
Comparable findings have been reported in pharmacists (Gaither and Nadkarni, 2012; Jones et al., 2017). For example, in a study of 974 inpatient clinical pharmacists, a multi-variate analysis found that difficult relationships with pharmacist colleagues doubled the odds of burnout (Jones et al., 2017).
Poor interpersonal relationships across disciplines have been shown to be associated with burnout (Embriaco et al., 2007b; Gunnarsdóttir et al., 2009; Hanrahan et al., 2010; Li et al., 2013; Sargent et al., 2004) in some but not all studies (Lorenz and Guirardello Ede, 2014). In one study of more than 900 physicians working in ICUs in France, conflicts with nurses were independently associated with a higher risk of burnout, while better relationships with nurses and with the head nurse were independently associated with a lower risk of burnout (Embriaco et al., 2007a). In a sample of orthopedic surgeons, perceived stress with other faculty and with nursing staff correlated with burnout (Sargent et al., 2004).
According to an analysis of survey data from 23,446 nurses in 352 hospitals in 11 countries, nurse-perceived doctor–nurse collegial relations affected all burnout dimensions at the unit level (Li et al., 2013). Similar findings were reported in a study of 353 psychiatric nurses in 67 hospitals (Hanrahan et al., 2010) and in 695 Icelandic nurses (Gunnarsdóttir et al., 2009). Another study in five acute care community hospitals measured perceptions of relational coordination (i.e., communicating and relating for the purpose of completing tasks) between 382 direct care nurses and other on-unit and out-of-unit nurses, physicians, and support staff (Havens et al., 2018). Higher perceived relational coordination—and particularly mutual respect—correlated with lower emotional exhaustion. Interestingly, in a longitudinal study of 2,100 critical care nurses and physicians, measures of teamwork did not predict subsequent emotional exhaustion, although
emotional exhaustion predicted subsequent deterioration in the clinicians’ perception of interpersonal teamwork between nurses and physicians (Welp et al., 2016).
Petitta and colleagues (2017) studied “emotional contagion,” defined as perception of how one’s own emotions are influenced by the emotions of colleagues. In this study, “feeling better after interacting with happy individuals” was associated with a lower risk of emotional exhaustion and depersonalization in physicians and a lower risk of depersonalization in nurses. Conversely, feeling irritated after interacting with angry individuals was associated with the opposite effects on burnout measures.
Interpersonal relationships may serve a buffering role against stress by providing social support. Multiple studies have found that positive support from colleagues lowers the risk of burnout among clinicians (Adriaenssens et al., 2015b; Hyman et al., 2017; Pisanti, 2012; Pisanti et al., 2016b; Proost et al., 2004). In a study of 2,075 nurses in Belgium (Proost et al., 2004) and of 1,383 hospital-based nurses in Italy (Pisanti, 2012), higher perceived social support was associated with lower burnout. In two longitudinal studies of nurses in Western Europe, emotional exhaustion was negatively correlated with improvements in social support over more than 1 year (Adriaenssens et al., 2015a; Pisanti et al., 2016b). Unfortunately, maintaining patient confidentiality may be a considerable obstacle for clinicians seeking social support in some cultures (Løvseth et al., 2010, 2013).
Work–life integration is the combination of personal and professional responsibilities and activities; in contrast, work–life balance refers to the segmentation of one’s life, an approach that may be more cognitively draining (Burkus, 2016; Smit et al., 2016). In comparison to other U.S. workers, physicians are less likely to be satisfied with their work–life integration. This finding persists even after controlling for work hours and other factors (Shanafelt et al., 2015, 2019b). Within the house of medicine, satisfaction with work–life integration among physicians varies substantially by specialty, age, sex, work hours, and practice setting (Shanafelt et al., 2015, 2019b). The burden of personal responsibilities is also influenced by home dynamics, such as the age of one’s children and having a partner who is employed (Dyrbye et al., 2010). Lower satisfaction with work–life integration is associated with a higher risk of burnout (Anandarajah et al., 2018; McAbee et al., 2015; Oskrochi et al., 2016).
When struggles with work–life integration occur, work–home conflicts can occur, and such events also increase the risk of burnout (Dyrbye et al., 2011b, 2012; Oskrochi et al., 2016; Sargent et al., 2004). Work–home conflicts are commonly experienced by physicians, especially among women,
those in dual-physician relationships, and early career physicians (Dyrbye et al., 2010, 2011a,b). Both having a recent work–home conflict and solving a work–home conflict in favor of work (rather than being able to solve in a manner that enables one to meet both work and home responsibilities) have been shown to be independent predictors of burnout for both sexes in a national sample of more than 7,800 U.S. surgeons and a smaller sample of 465 academic general and subspecialist internists (Dyrbye et al., 2011b, 2012). A longitudinal study of physicians working in Norway found that a failure to experience a reduction in work–home interference over a 5-year time span after medical school graduation was an independent predictor of emotional exhaustion 15 years after medical school graduation (Hertzberg et al., 2016).
Several nursing studies also have reported a relationship between lower satisfaction with work–life integration and burnout (Boamah et al., 2017; Flynn and Ironside, 2018; Naruse et al., 2012; Proost et al., 2004). For example, in a large longitudinal study of recently graduated Canadian nurses, reported work–life imbalance predicted burnout (MBI–GS), lower job satisfaction, and lower perceived patient care quality 1 year later (Boamah et al., 2017). In a cross-sectional study of more than 2,000 nurses in Belgium, work–home conflicts increased the risk of burnout when controlling for dimensions of Karasek’s (Karasek and Theorell, 1990) job demand–control–support model (Proost et al., 2004). Work–home conflicts may be reduced when there is better alignment between work schedules and personal life needs. For example, in a longitudinal study of 247 nurses in the Netherlands, when the nurses’ work schedules fit better with their personal lives, they had less emotional exhaustion and were less likely to report declines in work engagement 1 year later (Peters et al., 2016).
INDIVIDUAL FACTORS MEDIATING BURNOUT AND PROFESSIONAL WELL-BEING
Available personal resources are strongly influenced by individual traits (e.g., personality), current individual states (e.g., sleep deprivation, mood), the complex intersection of one’s personal and professional responsibilities (e.g., relationships, health issues, age of children, status of personal relationships, and other demands), and the prior history of goal achievement across all aspects of life.
Individuals vary in their capacity, their approaches, and their response to work-related stressors. These differences may be related to traits intrinsic to the individual (e.g., demographic variables such as gender, cultural background, and age as well as personality and general disposition), individual states (e.g., degree of sleep deprivation, mood, mindfulness), and other contextual factors (e.g., the varying nature of personal relationships).
While many individual traits are not modifiable, states and context can vary over time and have stronger or weaker effects depending on the work context. Individual factors, such as personality traits, cognitive abilities, and decision styles play a crucial role in workers’ performance and in their subjective responses to perceived task difficulty and workload (Borg, 1978; Borg et al., 1971; Damos, 1988; Meshkati and Loewenthal, 1988; Moray, 1982). The role of demographic variables in the predisposition to burnout is discussed in Chapter 3; this section discusses other individual mediators. Figure 4-3 highlights the indvidual factors that mediate burnout in the committee’s systems model of burnout and professional well-being.
Personality and Temperament
Although personality is multifaceted, the “big 5” personality traits (openness, conscientiousness, extraversion, agreeableness, and neuroticism) are widely considered to be the basic dimensions of personality (DeYoung et al., 2016). Perfectionism is another commonly explored dimension that correlates with conscientiousness and neuroticism. There are some data on the mediating role of personality on burnout in clinicians. Several studies have reported small associations between high neuroticism and burnout among physicians and nurses (McManus et al., 2004; Shimizutani et al., 2008; van der Wal et al., 2016; Yao et al., 2018; Zellars et al., 2004). For example, a prospective study of more than 2,000 physicians in the United Kingdom reported a weak, but statistically significant association between higher levels of neuroticism and subsequent symptoms of burnout among physicians. In this study of UK physicians, as well as in another study of
680 nurses in China, being an introvert was also associated with a higher likelihood of burnout (McManus et al., 2004; Yao et al., 2018). Other aspects of personality, such as having an easygoing and receptive personality (Meeusen et al., 2011) and having an internal locus of control, have also been reported to have some small mediating impact on the relationship between work stress and burnout (Partlak Günüşen et al., 2014).
Self-efficacy, an individual’s belief in his or her own ability, and comfort with decision making may also relate to how individuals deal with stressors (Fida et al., 2018; Moreno-Jiménez et al., 2008; Spence Laschinger and Fida, 2014). For example, in a 1-year longitudinal study of 596 Canadian nurses, a higher level of self-efficacy in an individual’s ability to cope with interpersonal conflict in the workplace was correlated with lower levels of burnout 1 year later (Fida et al., 2018). In a small study of 130 physicians working in Madrid, physicians’ anxiety about decision-making processes was associated with burnout after controlling for age, gender, and patient characteristics. Attitudes about death (acceptance versus avoidance) moderated the relationship between decision making and burnout. When physicians took more responsibility for decision making, greater acceptance of death was correlated with the physician experiencing less emotional exhaustion (Moreno-Jiménez et al., 2008).
Personality, in particular locus of control, may influence the selection and use of coping behaviors (Haybatollahi and Gyekye, 2014), which in turn appears to mediate the impact of stress on well-being. Active or task-focused coping is associated with lower levels of psychological distress. Emotion-focused coping, such as wishful thinking, can moderate stress, but extensive reliance on it can lead to problems. The data regarding coping strategies and the risk of burnout among clinicians are conflicting. Some studies have reported that escape avoidance coping increased the risk of burnout (Pejuskovic et al., 2011; Pisanti, 2012) and task-focused coping reduced the risk for burnout (Bertges Yost et al., 2005), while other studies have reported no independent relationships among avoidance coping, task-focused coping, and burnout (Howlett et al., 2015). Still other studies have reported a significant but small relationship between emotion-oriented coping and burnout (Buttigieg et al., 2015; Howlett et al., 2015; Pisanti, 2012). In a study of 616 emergency room personnel, emotion-oriented coping was found to have a small to moderate (r = 0.18 to 0.22) relationship with a higher risk of burnout (Howlett et al., 2015). Similarly, in a study of 1,383 hospital-based nurses in Italy, a multi-variate analysis found emotion-oriented coping to be associated with a higher risk of burnout (Pisanti, 2012). On the other hand,
planful problem solving (coping though analysis and planning to resolve the situation) was correlated with a decreased risk of depersonalization in a small study of hospice nurses (Payne, 2001). In aggregate, these studies suggest that coping strategies likely explain approximately 10 percent of variance in burnout (Payne, 2001; Pejuskovic et al., 2011).
Other active coping strategies, such as getting regular sleep, exercise, spending time with family and friends and engaging in recreation or hobbies, have been associated with a lower risk of burnout (Balayssac et al., 2017; Bertges Yost et al., 2005; Oskrochi et al., 2016; Sargent et al., 2004; Shanafelt et al., 2005, 2012b). For example, a systemic review of burnout among surgeons concluded that surgeons who exercised were at lower risk for burnout (Oskrochi et al., 2016). Protecting time away from work to be with spouses or partners, family, and friends and talking about feeling with them as a way to manage stress is another active coping strategy associated with a lower risk of burnout in physicians (Shanafelt et al., 2012b).
As indicated in Chapter 2, resilience has a variety of definitions, including the ability to persevere and remain positive and a mindset and skill set that enables individuals to maintain their performance and well-being under adversity (Szanton and Gill, 2010). Resilience is considered a continuous, dynamic state that can be nurtured into a stronger and more effective attribute, at least up to a point (Howe et al., 2012). Resilience includes self-regulation and mindfulness and also the capacity for self-monitoring, limit setting, and attitudes that promote engagement with difficult issues at work (Epstein and Krasner, 2013; Luthar et al., 2000).
Studies suggest that higher levels of resilience may decrease the risk of burnout among nurses (Guo et al., 2018; Mealer et al., 2012; Rushton et al., 2015). In a survey by Rushton et al. (2015), greater resilience was associated with lower emotional exhaustion and a higher sense of personal accomplishment in a sample of nurses practicing in high-intensity settings. Mealer and colleagues (2012), in a national survey of 744 critical care nurses, found that high resilience was also associated with a lower likelihood of burnout as well as a lower likelhood of posttraumatic stress disorder, anxiety, and depression. Higher levels of resilience in nurses have also been associated with improved work relationships (McDonald et al., 2013), increased job satisfaction (Matos et al., 2010), improved professional quality of life (Hegney et al., 2015), and increased overall well-being (Ablett and Jones, 2007). It is worthwhile to note, however, that no published study to date has reported lower levels of resilience among physicians, nurses, or other health care professionals than among the general population.
Personal Relationships and Support Systems
Relationships can be a source of support as well as of stress. In a 2010 study, having a spouse or partner who worked outside the home was independently associated in physicians with high emotional exhaustion after controlling for a variety of personal and professional factors (Dyrbye et al., 2010). Other studies have reported that low spousal support and spousal occupation was associated with high emotional exhaustion (Gabbe et al., 2002; Golub et al., 2008; Johns and Ossoff, 2005; Oskrochi et al., 2016). Of course, being a partner of a clinician creates challenges since work-related stressors can affect home life and relationships with partners and children (Shanafelt et al., 2013, 2016b).
The literature on the work system and individual factors associated with clinician burnout and professional well-being is vast. Much of the evidence has been derived from physician studies and, to a lesser degree, nursing studies. More investigations are needed to confirm the relevance of particular contributing factors in other professions. One conclusion that may be drawn is that systemic contributory factors that can cause burnout or adversely affect professional well-being are numerous and varied but are quite context-dependent—factors in one setting may not be present in another. These contributory factors are further mediated by individual traits, many of which are intrinsic and not modifiable. Nevertheless, system factors are impacted by the way work is organized and managed and are influenced by multiple system levels. These system factors need to be addressed to decrease, prevent, and mitigate burnout.
AACN (American Association of Critical-Care Nurses). 2016. AACN standards for establishing and sustaining healthy work environments: A journey to excellence. Aliso Viejo, CA: American Association of Critical-Care Nurses.
Ablett, J. R., and R. S. Jones. 2007. Resilience and well-being in palliative care staff: A qualitative study of hospice nurses’ experience of work. Psycho-Oncology 16(8):733–740.
Adriaenssens, J., V. De Gucht, and S. Maes. 2015a. Causes and consequences of occupational stress in emergency nurses: A longitudinal study. Journal of Nursing Management 23(3):346–358.
Adriaenssens, J., V. De Gucht, and S. Maes. 2015b. Determinants and prevalence of burnout in emergency nurses: A systematic review of 25 years of research. International Journal of Nursing Studies 52(2):649–661.
Aiken, L. H., S. P. Clarke, and D. M. Sloane. 2002. Hospital staffing, organization, and quality of care: Cross-national findings. International Journal for Quality in Health Care 14(1):5–13.
Aiken, L. H., J. P. Cimiotti, D. M. Sloane, H. L. Smith, L. Flynn, and D. F. Neff. 2011. Effects of nurse staffing and nurse education on patient deaths in hospitals with different nurse work environments. Medical Care 49(12):1047–1053.
Aiken, L. H., W. Sermeus, K. Van Den Heede, D. M. Sloane, R. Busse, M. McKee, L. Bruyneel, A. M. Rafferty, P. Griffiths, M. T. Moreno-Casbas, C. Tishelman, A. Scott, T. Brzostek, J. Kinnunen, R. Schwendimann, M. Heinen, D. Zikos, I. S. Sjetne, H. L. Smith, and A. Kutney-Lee. 2012. Patient safety, satisfaction, and quality of hospital care: Cross sectional surveys of nurses and patients in 12 countries in Europe and the United States. BMJ (Online) 344(7851).
Ali, N. A., K. M. Wolf, J. Hammersley, S. P. Hoffmann, J. M. O’Brien, Jr., G. S. Phillips, M. Rashkin, E. Warren, and A. Garland. 2011. Continuity of care in intensive care units: A cluster-randomized trial of intensivist staffing. American Journal of Respiratory and Critical Care Medicine 184(7):803–808.
Allegra, C. J., R. Hall, and G. Yothers. 2005. Prevalence of burnout in the U.S. oncology community: Results of a 2003 survey. Journal of Oncology Practice 1(4):140–147.
Amoafo, E., N. Hanbali, A. Patel, and P. Singh. 2015. What are the significant factors associated with burnout in doctors? Occupational Medicine (London) 65(2):117–121.
An, P. G., J. S. Rabatin, L. B. Manwell, M. Linzer, R. L. Brown, and M. D. Schwartz. 2009. Burden of difficult encounters in primary care: Data from the Minimizing Error, Maximizing Outcomes study. Archives of Internal Medicine 169(4):410–414.
An, P. G., L. B. Manwell, E. S. Williams, N. Laiteerapong, R. L. Brown, J. S. Rabatin, M. D. Schwartz, P. J. Lally, and M. Linzer. 2013. Does a higher frequency of difficult patient encounters lead to lower-quality care? Journal of Family Practice 62(1):24–29.
Anandarajah, A. P., T. E. Quill, and M. R. Privitera. 2018. Adopting the quadruple aim: The University of Rochester Medical Center experience: Moving from physician burnout to physician resilience. American Journal of Medicine 131(8):979–986.
Arndt, B. G., J. W. Beasley, M. D. Watkinson, J. L. Temte, W. J. Tuan, C. A. Sinsky, and V. J. Gilchrist. 2017. Tethered to the EHR: Primary care physician workload assessment using EHR event log data and time–motion observations. Annals of Family Medicine 15(5):419–426.
Arora, V. M., and J. M. Farnan. 2008. Care transitions for hospitalized patients. Medical Clinics of North America 92(2):viii, 315–324.
Arora, M., A. D. Diwan, and I. A. Harris. 2013. Burnout in orthopaedic surgeons: A review. ANZ Journal of Surgery 83(7–8):512–515.
Atabay, G., B. G. Cangarli, and S. Penbek. 2015. Impact of ethical climate on moral distress revisited: Multidimensional view. Nursing Ethics 22(1):103–116.
Ayers, K. M., W. M. Thomson, J. T. Newton, and A. M. Rich. 2008. Job stressors of New Zealand dentists and their coping strategies. Occupational Medicine (London) 58(4):275–281.
Azam, K., A. Khan, and M. T. Alam. 2017. Causes and adverse impact of physician burnout: A systematic review. Journal of the College of Physicians and Surgeons Pakistan 27(8):495–501.
Babbott, S., L. B. Manwell, R. Brown, E. Montague, E. Williams, M. Schwartz, E. Hess, and M. Linzer. 2014. Electronic medical records and physician stress in primary care: Results from the MEMO study. Journal of the American Medical Informatics Association 21(E2):e100–e106.
Bakker, A. B., and E. Demerouti. 2007. The job demands–resources model: State of the art. Journal of Managerial Psychology 22(3):309–328.
Bakker, A. B., and E. Demerouti. 2017. Job demands–resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology 22(3):273–285.
Bakker, A. B., M. van Veldhoven, and D. Xanthopoulou. 2010. Beyond the demand–control model: Thriving on high job demands and resources. Journal of Personnel Psychology 9(1):3–16.
Balayssac, D., B. Pereira, J. Virot, A. Collin, D. Alapini, D. Cuny, J. M. Gagnaire, N. Authier, and B. Vennat. 2017. Burnout, associated comorbidities, and coping strategies in French community pharmacies–BOP study: A nationwide cross-sectional study. PLOS ONE 12(8):e0182956.
Ball, A., J. Schultheis, H. Lee, and P. Bush. 2018. Incidence of burnout among critical care pharmacists. Abstracts of the 2018 ASHP Midyear Clinical Meeting. Session 4-001. December 2–6, 2018.
Basińska, B. A., and E. Wilczek-Ruzyczka. 2013. The role of rewards and demands in burnout among surgical nurses. International Journal of Occupational Medicine and Environmental Health 26(4):593–604.
Ben-Itzhak, S., J. Dvash, M. Maor, N. Rosenberg, and P. Halpern. 2015. Sense of meaning as a predictor of burnout in emergency physicians in Israel: A national survey. Clinical and Experimental Emergency Medicine 2(4):217–225.
Bertges Yost, W., A. Eshelman, M. Raoufi, and M. S. Abouljoud. 2005. A national study of burnout among American transplant surgeons. Transplantation Proceedings 37(2):1399–1401.
Billeter-Koponen, S., and L. Freden. 2005. Long-term stress, burnout, and patient-nurse relations: Qualitative interview study about nurses’ experiences. Scandinavian Journal of Caring Sciences 19:20–27.
Boamah, S. A., and H. Laschinger. 2016. The influence of areas of worklife fit and work–life interference on burnout and turnover intentions among new graduate nurses. Journal of Nursing Management 24(2):E164–E174.
Boamah, S. A., E. A. Read, and H. K. Spence Laschinger. 2017. Factors influencing new graduate nurse burnout development, job satisfaction and patient care quality: A time-lagged study. Journal of Advanced Nursing 73(5):1182–1195.
Boonstra, A., A. Versluis, and J. F. Vos. 2014. Implementing electronic health records in hospitals: A systematic literature review. BMC Health Services Research 14:370.
Borg, G. 1978. Subjective aspects of physical and mental load. Ergonomics 21(3):215–220.
Borg, G., O. Bratfisch, and S. Dornic. 1971. On the problems of perceived difficulty. Scandinavian Journal of Psychology 12(1):249–260.
Borteyrou, X., D. Truchot, and N. Rascle. 2014. Development and validation of the Work Stressor Inventory for Nurses in Oncology: Preliminary findings. Journal of Advanced Nursing 70(2):443–453.
Browning, A. M. 2013. CNE article: Moral distress and psychological empowerment in critical care nurses caring for adults at end of life. American Journal of Critical Care 22(2):143–151.
Burkus, D. 2016. Research: Keeping work and life separate is more trouble than it’s worth. Harvard Business Review. https://hbr.org/2016/08/research-keeping-work-and-life-separate-is-more-trouble-than-its-worth (accessed July 14, 2019).
Burston, A. S., and A. G. Tuckett. 2013. Moral distress in nursing: Contributing factors, outcomes and interventions. Nursing Ethics 20(3):312–324.
Buttigieg, S., D. Cachia, and D. Gauci. 2015. Stress, burnout and coping strategies in the emergency and intensive care hospital departments. In C. R. Hopkins (ed.), Job stress: Risk factors, health effects, and coping strategies. New York: Nova Publishers. Pp. 49–82.
Calgan, Z., D. Aslan, and S. Yegenoglu. 2011. Community pharmacists’ burnout levels and related factors: An example from Turkey. International Journal of Clinical Pharmacy 33(1):92–100.
Campana, K. L., and S. Hammoud. 2015. Incivility from patients and their families: Can organisational justice protect nurses from burnout? Journal of Nursing Management 23(6):716–725.
Campbell, D. A., Jr., S. Sonnad, F. E. Eckhauser, K. Campbell, and L. J. Greenfield. 2001. Burnout among American surgeons. Surgery 130:696–705.
Campbell, S. M., C. M. Ulrich, and C. Grady. 2016. A broader understanding of moral distress. American Journal of Bioethics 16(12):2–9.
Cao, C. G., M. B. Weinger, J. Slagle, C. Zhou, J. Ou, S. Gillin, B. Sheh, and W. Mazzei. 2008. Differences in day and night shift clinical performance in anesthesiology. Human Factors 50(2):276–290.
Caplan, R. D. 1987. Person–environment fit theory and organizations: Commensurate dimensions, time perspectives, and mechanisms. Journal of Vocational Behavior 31(3):248–267.
Caplan, R. D., S. Cobb, J. R. P. French, R. V. Harrison, and S. R. Pinneau. 1975. Job demands and worker health. Washington, DC: U.S. Government Printing Office.
Carayon, P. 2009. The balance theory and the work system model. Twenty years later. International Journal of Human–Computer Interaction 25(5):313–327.
Carse, A., and C. H. Rushton. 2018. Moral distress: Context, sources, and consequences. In C. H. Rushton (ed.), Moral resilience: Transforming moral suffering in healthcare. Oxford, England: Oxford University Press. Pp. 24–51.
Casalicchio, G., E. Lesaffre, H. Küchenhoff, and L. Bruyneel. 2017. Nonlinear analysis to detect if excellent nursing work environments have highest well-being. Journal of Nursing Scholarship 49(5):537–547.
Cho, E., D. M. Sloane, E. Y. Kim, S. Kim, M. Choi, I. Y. Yoo, H. S. Lee, and L. H. Aiken. 2015. Effects of nurse staffing, work environments, and education on patient mortality: An observational study. International Journal of Nursing Studies 52(2):535–542.
Chrouser, K. L., J. Xu, S. Hallbeck, M. B. Weinger, and M. R. Partin. 2018. The influence of stress responses on surgical performance and outcomes: Literature review and the development of the surgical stress effects (SSE) framework. American Journal of Surgery 216(3):573–584.
Cimiotti, J. P., L. H. Aiken, D. M. Sloane, and E. S. Wu. 2012. Nurse staffing, burnout, and health care–associated infection. American Journal of Infection Control 40(6):486–490.
Dall’Ora, C., P. Griffiths, J. Ball, M. Simon, and L. H. Aiken. 2015. Association of 12 h shifts and nurses’ job satisfaction, burnout, and intention to leave: Findings from a cross-sectional study of 12 European countries. BMJ Open 5(9).
Damos, D. 1988. Individual differences in subjective estimates of workload. Advances in Psychology 52C:231–238.
Deci, E. L., and R. M. Ryan. 1985. Intrinsic motivation and self-determination in human behavior. New York: Plenum Press.
Delfrate, F., P. Ferrara, D. Spotti, S. Terzoni, G. Lamiani, E. Canciani, and L. Bonetti. 2018. Moral distress (MD) and burnout in mental health nurses: A multicenter survey. La Medicina de Lavoro 109(2):97–109.
Demerouti, E., A. B. Bakker, F. Nachreiner, and W. B. Schaufeli. 2001. The job demands–resources model of burnout. Journal of Applied Psychology 86(3):499–512.
Dexter, E. N., S. Fields, R. E. Rdesinski, B. Sachdeva, D. Yamashita, and M. Marino. 2016. Patient–provider communication: Does electronic messaging reduce incoming telephone calls? Journal of the American Board of Family Medicine 29(5):613–619.
DeYoung, C. G., B. E. Carey, R. F. Krueger, and S. R. Ross. 2016. Ten aspects of the big five in the personality inventory for dsm-5. Personality Disorders 7(2):113–123.
Dodek, P. M., H. Wong, M. Norena, N. Ayas, S. C. Reynolds, S. P. Keenan, A. Hamric, P. Rodney, M. Stewart, and L. Alden. 2016. Moral distress in intensive care unit professionals is associated with profession, age, and years of experience. Journal of Critical Care 31(1):178–182.
Downing, N. L., D. W. Bates, and C. A. Longhurst. 2018. Physician burnout in the electronic health record era: Are we ignoring the real cause? Annals of Internal Medicine 169(1):50–51.
Dugdale, L. S. 2017. Physician work environment and well-being: Re-enchanting medicine. JAMA Internal Medicine 177(8):1075–1076.
Dyrbye, L. N., T. D. Shanafelt, C. M. Balch, D. Satele, and J. Freischlag. 2010. Physicians married or partnered to physicians: A comparative study in the American College of Surgeons. Journal of the American College of Surgeons 211(5):663–671.
Dyrbye, L. N., T. D. Shanafelt, C. M. Balch, D. Satele, J. Sloan, and J. Freischlag. 2011a. Relationship between work–home conflicts and burnout among American surgeons: A comparison by sex. Archives of Surgery 146(2):211–217.
Dyrbye, L. N., C. P. West, D. Satele, J. A. Sloan, and T. D. Shanafelt. 2011b. Work/home conflict and burnout among academic internal medicine physicians. Archives of Internal Medicine 171(13):1207–1209.
Dyrbye, L. N., J. Freischlag, K. L. Kaups, M. R. Oreskovich, D. V. Satele, J. B. Hanks, J. A. Sloan, C. M. Balch, and T. D. Shanafelt. 2012. Work–home conflicts have a substantial impact on career decisions that affect the adequacy of the surgical workforce. Archives of Surgery 147(10):933–939.
Dyrbye, L. N., P. Varkey, S. L. Boone, D. V. Satele, J. A. Sloan, and T. D. Shanafelt. 2013. Physician satisfaction and burnout at different career stages. Mayo Clinic Proceedings 88(12):1358–1367.
Dzeng, E., and J. R. Curtis. 2018. Understanding ethical climate, moral distress, and burnout: A novel tool and a conceptual framework. BMJ Quality & Safety 27(10):766.
Edwards, S. T., C. D. Helfrich, D. Grembowski, E. Hulen, W. L. Clinton, G. B. Wood, L. Kim, D. E. Rose, and G. Stewart. 2018. Task delegation and burnout trade-offs among primary care providers and nurses in Veterans Affairs patient-aligned care teams (VA PACTs). Journal of the American Board of Family Medicine 31(1):83–93.
Eggemeier, F. 1988. Properties of workload assessment techniques. Advances in Psychology 52C:41–62.
El-Ibiary, S. Y., L. Yam, and K. C. Lee. 2017. Assessment of burnout and associated risk factors among pharmacy practice faculty in the United States. American Journal of Pharmaceutical Education 81(4):75.
Embriaco, N., E. Azoulay, K. Barrau, N. Kentish, F. Pochard, A. Loundou, and L. Papazian. 2007a. High level of burnout in intensivists: Prevalence and associated factors. American Journal of Respiratory and Critical Care Medicine 175(7):686–692.
Embriaco, N., L. Papazian, N. Kentish-Barnes, F. Pochard, and E. Azoulay. 2007b. Burnout syndrome among critical care healthcare workers. Current Opinions in Critical Care 13(5):482–488.
Epstein, E. G., and A. B. Hamric. 2009. Moral distress, moral residue, and the crescendo effect. Journal of Clinical Ethics 20(4):330–342.
Epstein, E. G., P. B. Whitehead, C. Prompahakul, L. R. Thacker, and A. B. Hamric. 2019. Enhancing understanding of moral distress: The measure of moral distress for health care professionals. AJOB Empirical Bioethics 10(2):113–124.
Epstein, R. M., and M. S. Krasner. 2013. Physician resilience: What it means, why it matters, and how to promote it. Academic Medicine 88(3):301–303.
Fenwick, R., and M. Tausig. 2001. Scheduling stress: Family and health outcomes of shift work and schedule control. American Behavioral Scientist 44(7):1179–1198.
Fida, R., H. K. S. Laschinger, and M. P. Leiter. 2018. The protective role of self-efficacy against workplace incivility and burnout in nursing: A time-lagged study. Health Care Management Review 43(1):21–29.
Flynn, E. A., K. N. Barker, J. T. Gibson, R. E. Pearson, B. A. Berger, and L. A. Smith. 1999. Impact of interruptions and distractions on dispensing errors in an ambulatory care pharmacy. American Journal of Health-System Pharmacy 56(13):1319–1325.
Flynn, L., and P. M. Ironside. 2018. Burnout and its contributing factors among midlevel academic nurse leaders. Journal of Nursing Education 57(1):28–34.
Foglia, M. B., J. H. Cohen, R. A. Pearlman, M. M. Bottrell, and E. Fox. 2013. Perceptions of ethical leadership and the ethical environment and culture: IntegratedEthicsTM staff survey data from the VA health care system. AJOB Primary Research 4(1):44–58.
Fumis, R. R. L., G. A. Junqueira Amarante, A. de Fatima Nascimento, and J. M. Vieira Junior. 2017. Moral distress and its contribution to the development of burnout syndrome among critical care providers. Annals of Intensive Care 7(1):71.
Gabbe, S. G., J. Melville, L. Mandel, and E. Walker. 2002. Burnout in chairs of obstetrics and gynecology: Diagnosis, treatment, and prevention. American Journal of Obstetrics and Gynecology 186(4):601–612.
Gaither, C. A., and A. Nadkarni. 2012. Interpersonal interactions, job demands and work-related outcomes in pharmacy. International Journal of Pharmacy Practice 20(2):80–89.
Garrett, C. 2008. The effect of nurse staffing patterns on medical errors and nurse burnout. AORN Journal 87(6):1191–1192, 1194, 1196–1200, 1202–1204.
Gelsema, T. I., M. van der Doef, S. Maes, M. Janssen, S. Akerboom, and C. Verhoeven. 2006. A longitudinal study of job stress in the nursing profession: Causes and consequences. Journal of Nursing Management 14(4):289–299.
Gi, T. S., K. M. Devi, and E. A. Neo Kim. 2011. A systematic review on the relationship between the nursing shortage and nurses’ job satisfaction, stress, and burnout levels in oncology/haematology settings. JBI Library of Systematic Reviews 9(39):1603–1649.
Goetz, K., R. Schuldei, and J. Steinhauser. 2018. Working conditions, job satisfaction and challenging encounters in dentistry: A cross-sectional study. International Dental Journal 69(1):44–49.
Goldzweig, C. L., G. Orshansky, N. M. Paige, A. A. Towfigh, D. A. Haggstrom, I. Miake-Lye, J. M. Beroes, and P. G. Shekelle. 2013. Electronic patient portals: Evidence on health outcomes, satisfaction, efficiency, and attitudes: A systematic review. Annals of Internal Medicine 159(10):677–687.
Golub, J. S., M. M. Johns, 3rd, P. S. Weiss, A. K. Ramesh, and R. H. Ossoff. 2008. Burnout in academic faculty of otolaryngology–head and neck surgery. Laryngoscope 118(11):1951–1956.
Gopher, D., and E. Donchin. 1986. Workload: An examination of the concept. In Handbook of perception and human performance, vol. 2: Cognitive processes and performance. Oxford, England: John Wiley & Sons. Pp. 1–49.
Gorter, R. C., and R. Freeman. 2011. Burnout and engagement in relation with job demands and resources among dental staff in Northern Ireland. Community Dentistry and Oral Epidemiology 39(1):87–95.
Green, A. E., B. J. Albanese, N. M. Shapiro, and G. A. Aarons. 2014. The roles of individual and organizational factors in burnout among community-based mental health service providers. Psychological Services 11(1):41–49.
Gregory, S. T., and T. Menser. 2015. Burnout among primary care physicians: A test of the areas of worklife model. Journal of Healthcare Management 60(2):133–148.
Gregory, M. E., E. Russo, and H. Singh. 2017. Electronic health record alert-related workload as a predictor of burnout in primary care providers. Applied Clinical Informatics 8(3):686–697.
Grundgeiger, T., P. Sanderson, H. G. MacDougall, and B. Venkatesh. 2010. Interruption management in the intensive care unit: Predicting resumption times and assessing distributed support. Journal of Experimental Psychology: Applied 16(4):317–334.
Gunnarsdóttir, S., S. P. Clarke, A. M. Rafferty, and D. Nutbeam. 2009. Front-line management, staffing and nurse–doctor relationships as predictors of nurse and patient outcomes. A survey of Icelandic hospital nurses. International Journal of Nursing Studies 46(7):920–927.
Guo, Y. F., Y. H. Luo, L. Lam, W. Cross, V. Plummer, and J. P. Zhang. 2018. Burnout and its association with resilience in nurses: A cross-sectional study. Journal of Clinical Nursing 27(1–2):441–449.
Hancock, P. A., N. Meshkati, and M. M. Robertson. 1985. Physiological reflections of mental workload. Aviation, Space, and Environmental Medicine 56(11):1110–1114.
Hanrahan, N. P., L. H. Aiken, L. McClaine, and A. L. Hanlon. 2010. Relationship between psychiatric nurse work environments and nurse burnout in acute care general hospitals. Issues in Mental Health Nursing 31(3):198–207.
Harris, D. A., J. Haskell, E. Cooper, N. Crouse, and R. Gardner. 2018. Estimating the association between burnout and electronic health record–related stress among advanced practice registered nurses. Applied Nursing Research 43:36–41.
Hart, S. E. 2005. Hospital ethical climates and registered nurses’ turnover intentions. Journal of Nursing Scholarship 37(2):173–177.
Hart, S. G., and L. E. Staveland. 1988. Development of NASA-TLX (task load index): Results of empirical and theoretical research. In P. A. Hancock and N. Meshkati (eds.), Advances in psychology, vol. 52. Amsterdam: North-Holland. Pp. 139–183.
Havens, D. S., J. H. Gittell, and J. Vasey. 2018. Impact of relational coordination on nurse job satisfaction, work engagement and burnout: Achieving the quadruple aim. Journal of Nursing Administration 48(3):132–140.
Haybatollahi, M., and S. A. Gyekye. 2014. The moderating effects of locus of control and job level on the relationship between workload and coping behaviour among Finnish nurses. Journal of Nursing Management 22(6):811–821.
Hayes, B., C. Douglas, and A. Bonner. 2015. Work environment, job satisfaction, stress and burnout among haemodialysis nurses. Journal of Nursing Management 23(5):588–598.
Hegney, D. G., C. S. Rees, R. Eley, R. Osseiran-Moisson, and K. Francis. 2015. The contribution of individual psychological resilience in determining the professional quality of life of Australian nurses. Frontiers in Psychology 6:1613.
Hertzberg, T. K., K. I. Rø, P. J. W. Vaglum, T. Moum, J. O. Røvik, T. Gude, Ø. Ekeberg, and R. Tyssen. 2016. Work–home interface stress: An important predictor of emotional exhaustion 15 years into a medical career. Industrial Health 54(2):139–148.
Hiler, C. A., R. L. Hickman, Jr., A. P. Reimer, and K. Wilson. 2018. Predictors of moral distress in a U.S. sample of critical care nurses. American Journal of Critical Care 27(1):59–66.
Holden, R. J., N. R. Patel, M. C. Scanlon, T. M. Shalaby, J. M. Arnold, and B. T. Karsh. 2010. Effects of mental demands during dispensing on perceived medication safety and employee well-being: A study of workload in pediatric hospital pharmacies. Research in Social and Administrative Pharmacy 6(4):293–306.
Holden, R. J., M. C. Scanlon, N. R. Patel, R. Kaushal, K. H. Escoto, R. L. Brown, S. J. Alper, J. M. Arnold, T. M. Shalaby, K. Murkowski, and B. T. Karsh. 2011. A human factors framework and study of the effect of nursing workload on patient safety and employee quality of working life. BMJ Quality & Safety 20(1):15–24.
Houston, S., M. A. Casanova, M. Leveille, K. L. Schmidt, S. A. Barnes, K. R. Trungale, and R. L. Fine. 2013. The intensity and frequency of moral distress among different healthcare disciplines. Journal of Clinical Ethics 24(2):98–112.
Howe, A., A. Smajdor, and A. Stockl. 2012. Towards an understanding of resilience and its relevance to medical training. Medical Education 46(4):349–356.
Howlett, M., K. Doody, J. Murray, D. LeBlanc-Duchin, J. Fraser, and P. R. Atkinson. 2015. Burnout in emergency department healthcare professionals is associated with coping style: A cross-sectional survey. Emergency Medicine Journal 32(9):722–727.
Hwang, J. I., and H. A. Park. 2014. Nurses’ perception of ethical climate, medical error experience and intent-to-leave. Nursing Ethics 21(1):28–42.
Hyman, S. A., M. S. Shotwell, D. R. Michaels, X. Han, E. B. Card, J. L. Morse, and M. B. Weinger. 2017. A survey evaluating burnout, health status, depression, reported alcohol and substance use, and social support of anesthesiologists. Anesthesia & Analgesia 125(6):2009–2018.
ILO (International Labour Organization). 1986. Psychosocial factors at work: Recognition and control. Geneva, Switzerland: International Labour Office.
Jager, A. J., M. A. Tutty, and A. C. Kao. 2017. Association between physician burnout and identification with medicine as a calling. Mayo Clinic Proceedings 92(3):415–422.
Johns, M. M., 3rd, and R. H. Ossoff. 2005. Burnout in academic chairs of otolaryngology: Head and neck surgery. Laryngoscope 115(11):2056–2061.
Johnson-Coyle, L., D. Opgenorth, M. Bellows, J. Dhaliwal, S. Richardson-Carr, and S. M. Bagshaw. 2016a. Moral distress and burnout among cardiovascular surgery intensive care unit healthcare professionals: A prospective cross-sectional survey. Canadian Journal of Critical Care Nursing 27(4):27–36.
Johnson-Coyle, L., D. Opgenorth, M. Bellows, J. Dhaliwal, S. Richardson-Carr, and S. M. Bagshaw. 2016b. Moral distress and burnout among cardiovascular surgery intensive care unit healthcare professionals: A prospective cross-sectional survey. Canadian Journal of Critical Care Nursing 27(4):27–36.
Jugale, P. V., P. Mallaiah, A. Krishnamurthy, and R. Sangha. 2016. Burnout and work engagement among dental practitioners in Bangalore City: A cross-sectional study. Journal of Clinical and Diagnostic Research 10(2):ZC63–ZC67.
Karasek, R. A., and T. Theorell. 1990. Healthy work: Stress, productivity and the reconstruction of working life. New York: Basic Books.
Keeton, K., D. E. Fenner, T. R. Johnson, and R. A. Hayward. 2007. Predictors of physician career satisfaction, work–life balance, and burnout. Obstetrics & Gynecology 109(4):949–955.
Kutney-Lee, A., E. S. Wu, D. M. Sloane, and L. H. Aiken. 2013. Changes in hospital nurse work environments and nurse job outcomes: An analysis of panel data. International Journal of Nursing Studies 50(2):195–201.
Kutney-Lee, A., H. Germack, L. Hatfield, S. Kelly, P. Maguire, A. Dierkes, M. Del Guidice, and L. H. Aiken. 2016. Nurse engagement in shared governance and patient and nurse outcomes. Journal of Nursing Administration 46(11):605–612.
Lake, E. T., J. Sanders, R. Duan, K. A. Riman, K. M. Schoenauer, and Y. Chen. 2019. A meta-analysis of the associations between the nurse work environment in hospitals and 4 sets of outcomes. Medical Care 57(5):353–361.
Lamiani, G., L. Borghi, and P. Argentero. 2017. When healthcare professionals cannot do the right thing: A systematic review of moral distress and its correlates. Journal of Health Psychology 22(1):51–67.
Lea, V. M., S. A. Corlett, and R. M. Rodgers. 2012. Workload and its impact on community pharmacists’ job satisfaction and stress: A review of the literature. International Journal of Pharmacy Practice 20(4):259–271.
Leiter, M. P., and C. Maslach. 1988. The impact of interpersonal environment on burnout and organizational commitment. Journal of Organizational Behavior 9(4):297–308.
Leiter, M. P., and C. Maslach. 2004. Areas of worklife: A structured approach to organizational predictors of job burnout. In P. L. Perrewé and D. C. Ganster (eds.), Research in occupational stress and well being, vol. 3: Emotional and physiological processes and positive intervention strategies. Greenwich, CT: Elsevier Science/JAI Press. Pp. 91–134.
Leiter, M. P., E. Frank, and T. J. Matheson. 2009. Demands, values, and burnout: Relevance for physicians. Canadian Family Physician 55(12):1224–1225.
Li, B., L. Bruyneel, W. Sermeus, K. Van den Heede, K. Matawie, L. Aiken, and E. Lesaffre. 2013. Group-level impact of work environment dimensions on burnout experiences among nurses: A multivariate multilevel probit model. International Journal of Nursing Studies 50(2):281–291.
Linzer, M., L. B. Manwell, E. S. Williams, J. A. Bobula, R. L. Brown, A. B. Varkey, B. Man, J. E. McMurray, A. Maguire, B. Horner-Ibler, and M. D. Schwartz. 2009. Working conditions in primary care: Physician reactions and care quality. Annals of Internal Medicine 151(1):28–36.
Linzer, M., C. A. Sinsky, S. Poplau, R. Brown, and E. Williams. 2017. Joy in medical practice: Clinician satisfaction in the healthy work place trial. Health Affairs (Millwood) 36(10):1808–1814.
Liu, X., J. Zheng, K. Liu, J. G. Baggs, J. Liu, Y. Wu, and L. You. 2018. Hospital nursing organizational factors, nursing care left undone, and nurse burnout as predictors of patient safety: A structural equation modeling analysis. International Journal of Nursing Studies 86:82–89.
Lorenz, V. R., and B. Guirardello Ede. 2014. The environment of professional practice and burnout in nurses in primary healthcare. Revista Latino-Americana de Enfermagem 22(6):926–933.
Løvseth, L. T., O. G. Aasland, A. Fridner, L. S. Jónsdottir, M. Marini, and O. M. Linaker. 2010. Confidentiality and physicians’ health. A cross-sectional study of university hospital physicians in four European cities (the HOUPE study). Journal of Occupational Health 52(5):263–271.
Løvseth, L. T., A. Fridner, L. S. Jõnsdõttir, M. Marini, and O. M. Linaker. 2013. Associations between confidentiality requirements, support seeking and burnout among university hospital physicians in Norway, Sweden, Iceland, and Italy (the HOUPE study). Stress and Health 29(5):432–437.
Luthar, S. S., D. Cicchetti, and B. Becker. 2000. The construct of resilience: A critical evaluation and guidelines for future work. Child Development 71(3):543–562.
Maslach, C., and M. P. Leiter. 2008. Early predictors of job burnout and engagement. Journal of Applied Psychology 93(3):498–512.
Matos, P. S., L. A. Neushotz, M. T. Griffin, and J. J. Fitzpatrick. 2010. An exploratory study of resilience and job satisfaction among psychiatric nurses working in inpatient units. International Journal of Mental Health Nursing 19(5):307–312.
McAbee, J. H., B. T. Ragel, S. McCartney, G. M. Jones, L. M. Michael, II, M. DeCuypere, J. S. Cheng, F. A. Boop, and P. Klimo, Jr. 2015. Factors associated with career satisfaction and burnout among U.S. neurosurgeons: Results of a nationwide survey. Journal of Neurosurgery 123(1):161–173.
McDonald, G., D. Jackson, L. Wilkes, and M. H. Vickers. 2013. Personal resilience in nurses and midwives: Effects of a work-based educational intervention. Contemporary Nurse 45(1):134–143.
McHugh, M. D., and C. Ma. 2014. Wage, work environment, and staffing: Effects on nurse outcomes. Policy, Politics, and Nursing Practice 15:72–80.
McHugh, M. D., L. A. Kelly, H. L. Smith, E. S. Wu, J. M. Vanak, and L. H. Aiken. 2013. Lower mortality in Magnet hospitals. Medical Care 51(5):382–388.
McManus, I. C., A. Keeling, and E. Paice. 2004. Stress, burnout and doctors’ attitudes to work are determined by personality and learning style: A twelve-year longitudinal study of UK medical graduates. BMC Medicine 2:29.
Mealer, M., J. Jones, J. Newman, K. K. McFann, B. Rothbaum, and M. Moss. 2012. The presence of resilience is associated with a healthier psychological profile in intensive care unit (ICU) nurses: Results of a national survey. International Journal of Nursing Studies 49(3):292–299.
Meeusen, V. C. H., K. Van Dam, C. Brown-Mahoney, A. A. J. Van Zundert, and H. T. A. Knape. 2011. Understanding nurse anesthetists’ intention to leave their job: How burnout and job satisfaction mediate the impact of personality and workplace characteristics. Health Care Management Review 36(2):155–163.
Meltzer, L. S., and L. M. Huckabay. 2004. Critical care nurses’ perceptions of futile care and its effect on burnout. American Journal of Critical Care 13(3):202–208.
Meshkati, N. 1988. Heart rate variability and mental workload assessment. Advances in Psychology 52C:101–115.
Meshkati, N., and A. Loewenthal. 1988. The effects of individual differences in information processing behavior on experiencing mental workload and perceived task difficulty: A preliminary experimental investigation. In Advances in psychology. Vol. 52, edited by P. A. Hancock and N. Meshkati. Amsterdam: North-Holland. Pp. 269–288.
Michel, L., M. Waelli, D. Allen, and E. Minvielle. 2017. The content and meaning of administrative work: A qualitative study of nursing practices. Journal of Advanced Nursing 73(9):2179–2190.
Moray, N. 1979. Mental workload: Its theory and measurement. Edited by N. Moray. New York: Plenum Press.
Moray, N. 1982. Subjective mental workload. Human Factors 24(1):25–40.
Moreno-Jiménez, B., R. Rodríguez-Carvajal, E. G. Hernández, and M. E. M. Benadero. 2008. Terminal versus non-terminal care in physician burnout: The role of decision-making processes and attitudes to death. Salud Mental 31(2):93–101.
Morgan Jones, G., N. A. Roe, L. Louden, and C. R. Tubbs. 2017. Factors associated with burnout among U.S. hospital clinical pharmacy practitioners: Results of a nationwide pilot survey. Hospital Pharmacy 52(11):742–751.
Morrison, J. B., and J. Rudolph. 2011. Learning from accident and error: Avoiding the hazards of workload, stress, and routine interruptions in the emergency department. Academic Emergency Medicine 18:1246–1254.
Moss, M., V. S. Good, D. Gozal, R. Kleinpell, and C. N. Sessler. 2016a. An official Critical Care Societies Collaborative statement—Burnout syndrome in critical care health-care professionals: A call for action. Chest 150(1):17–26.
Moss, M., V. S. Good, D. Gozal, R. Kleinpell, and C. N. Sessler. 2016b. An official Critical Care Societies Collaborative statement: Burnout syndrome in critical care healthcare professionals: A call for action. Critical Care Medicine 44(7):1414–1421.
Mudallal, R. H., M. Y. N. Saleh, H. M. Al-Modallal, and R. Y. Abdel-Rahman. 2017. Quality of nursing care: The influence of work conditions, nurse characteristics and burnout. International Journal of Africa Nursing Sciences 7:24–30.
Munger, M. A., E. Gordon, J. Hartman, K. Vincent, and M. Feehan. 2013. Community pharmacists’ occupational satisfaction and stress: A profession in jeopardy? Journal of the American Pharmaceutical Association (2003) 53(3):282–296.
Naruse, T., A. Taguchi, Y. Kuwahara, S. Nagata, I. Watai, and S. Murashima. 2012. Relationship between perceived time pressure during visits and burnout among home visiting nurses in Japan. Japan Journal of Nursing Science 9(2):185–194.
Neff, D. F., J. P. Cimiotti, A. S. Heusinger, and L. H. Aiken. 2011. Nurse reports from the frontlines: Analysis of a statewide nurse survey. Nursing Forum 46(1):4–10.
Nesje, K. 2017. Professional commitment: Does it buffer or intensify job demands? Scandinavian Journal of Psychology 58(2):185–191.
Nicholson, R. M., M. P. Leiter, and H. K. Laschinger. 2014. Predicting cynicism as a function of trust and civility: A longitudinal analysis. Journal of Nursing Management 22(8):974–983.
Olds, D. M., L. H. Aiken, J. P. Cimiotti, and E. T. Lake. 2017. Association of nurse work environment and safety climate on patient mortality: A cross-sectional study. International Journal of Nursing Studies 74:155–161.
O’Mahony, N. 2011. Nurse burnout and the working environment. Emergency Nurse 19(5): 30–37.
Oskrochi, Y., M. Maruthappu, M. Henriksson, A. H. Davies, and J. Shalhoub. 2016. Beyond the body: A systematic review of the nonphysical effects of a surgical career. Surgery 159(2):650–664.
Oyeleye, O., P. Hanson, N. O’Connor, and D. Dunn. 2013. Relationship of workplace incivility, stress, and burnout on nurses’ turnover intentions and psychological empowerment. Journal of Nursing Administration 43(10):536–542.
Palen, T. E., C. Ross, J. D. Powers, and S. Xu. 2012. Association of online patient access to clinicians and medical records with use of clinical services. JAMA 308(19):2012–2019.
Pantenburg, B., M. Luppa, H. H. König, and S. G. Riedel-Heller. 2016. Burnout among young physicians and its association with physicians’ wishes to leave: Results of a survey in Saxony, Germany. Journal of Occupational Medicine and Toxicology 11(1):2.
Partlak Günü en, N., B. Ustün, and S. Erdem. 2014. Work stress and emotional exhaustion in nurses: The mediating role of internal locus of control. Research and Theory for Nursing Practice 28(3):260–268.
Patrician, P. A., J. Shang, and E. T. Lake. 2010. Organizational determinants of work outcomes and quality care ratings among Army medical department registered nurses. Research in Nursing & Health 33(2):99–110.
Patrick, K., and J. F. Lavery. 2007. Burnout in nursing. Australian Journal of Advanced Nursing 24(3):43–48.
Pauly, B., C. Varcoe, J. Storch, and L. Newton. 2009. Registered nurses’ perceptions of moral distress and ethical climate. Nursing Ethics 16(5):561–573.
Payne, N. 2001. Occupational stressors and coping as determinants of burnout in female hospice nurses. Journal of Advanced Nursing 33(3):396–405.
Pejuskovic, B., D. Lecic-Tosevski, S. Priebe, and O. Toskovic. 2011. Burnout syndrome among physicians—The role of personality dimensions and coping strategies. Psychiatria Danubina 23(4):389–395.
Pereira, S. M., C. M. Teixeira, A. S. Carvalho, and P. Hernández-Marrero. 2016. Compared to palliative care, working in intensive care more than doubles the chances of burnout: Results from a nationwide comparative study. PLOS ONE 11(9):e0162340.
Peters, V., A. De Rijk, J. Engels, Y. Heerkens, and F. Nijhuis. 2016. A new typology of work schedules: Evidence from a cross-sectional study among nurses working in residential elder care. Work 54(1):21–33.
Petitta, L., L. Jiang, and C. E. J. Härtel. 2017. Emotional contagion and burnout among nurses and doctors: Do joy and anger from different sources of stakeholders matter? Stress and Health 33(4):358–369.
Phillips, J. P. 2016. Workplace violence against health care workers in the United States. New England Journal of Medicine 374(17):1661–1669.
Piers, R. D., E. Azoulay, B. Ricou, F. DeKeyser Ganz, J. Decruyenaere, A. Max, A. Michalsen, P. Azevedo Maia, R. Owczuk, F. Rubulotta, P. Depuydt, A. P. Meert, A. K. Reyners, A. Aquilina, M. Bekaert, N. J. Van Den Noortgate, W. J. Schrauwen, and D. D. Benoit. 2011. Perceptions of appropriateness of care among European and Israeli intensive care unit nurses and physicians. JAMA 306(24):2694–2703.
Piers, R. D., M. Van den Eynde, E. Steeman, P. Vlerick, D. D. Benoit, and N. J. Van Den Noortgate. 2012. End-of-life care of the geriatric patient and nurses’ moral distress. Journal of the American Medical Directors Association 13(1):80.e7–80.e13.
Pisanti, R. 2012. Job demands–control–social support model and coping strategies: Predicting burnout and wellbeing in a group of Italian nurses. Medicina del Lavoro 103(6):466–481.
Pisanti, R., M. van der Doef, S. Maes, D. Lazzari, and M. Bertini. 2011. Job characteristics, organizational conditions, and distress/well-being among Italian and Dutch nurses: A cross-national comparison. International Journal of Nursing Studies 48(7):829–837.
Pisanti, R., M. van der Doef, S. Maes, C. Violani, and D. Lazzari. 2016a. Psychosocial job characteristics and psychological distress/well-being: The mediating role of personal goal facilitation. Journal of Occupational Health 58(1):36–46.
Pisanti, R., M. v. van der Doef, S. Maes, L. L. Meier, D. Lazzari, and C. Violani. 2016b. How changes in psychosocial job characteristics impact burnout in nurses: A longitudinal analysis. Frontiers in Psychology 7:1082.
Poghosyan, L., S. P. Clarke, M. Finlayson, and L. H. Aiken. 2010. Nurse burnout and quality of care: Cross-national investigation in six countries. Research in Nursing & Health 33(4):288–298.
Poncet, M. C., P. Toullic, L. Papazian, N. Kentish-Barnes, J. F. Timsit, F. Pochard, S. Chevret, B. Schlemmer, and E. Azoulay. 2007. Burnout syndrome in critical care nursing staff. American Journal of Respiratory and Critical Care Medicine 175(7):698–704.
Porter, M., H. Hagan, R. Klassen, Y. Yang, D. A. Seehusen, and P. J. Carek. 2018. Burnout and resiliency among family medicine program directors. Family Medicine 50(2):106–112.
Portoghese, I., M. Galletta, R. C. Coppola, G. Finco, and M. Campagna. 2014. Burnout and workload among health care workers: The moderating role of job control. Safety and Health at Work 5(3):152–157.
Pratt, M., M. Kerr, and C. Wong. 2009. The impact of ERI, burnout, and caring for SARS patients on hospital nurses’ self-reported compliance with infection control. The Canadian Journal of Infection 24(3):167–172, 174.
Proost, K., H. De Witte, K. De Witte, and G. Evers. 2004. Burnout among nurses: Extending the job demand–control–support model with work–home interference. Psychologica Belgica 44(4):269–288.
Puriene, A., J. Aleksejuniene, J. Petrauskiene, I. Balciuniene, and V. Janulyte. 2008. Self-perceived mental health and job satisfaction among Lithuanian dentists. Industrial Health 46(3):247–252.
Ramirez. 1996. Mental health of hospital consultants: The effects of stres and satisfaction at work. The Lancet 347:724–728.
Rao, S. K., A. B. Kimball, S. R. Lehrhoff, M. K. Hidrue, D. G. Colton, T. G. Ferris, and D. F. Torchiana. 2017. The impact of administrative burden on academic physicians: Results of a hospital-wide physician survey. Academic Medicine 92(2):237–243.
Rasmussen, J. 1979. Reflection on the concept of operator workload. In Mental workload, edited by N. Moray. Boston, MA: Springer.
Rasmussen, V., A. Turnell, P. Butow, I. Juraskova, L. Kirsten, L. Wiener, A. Patenaude, J. Hoekstra-Weebers, L. Grassi, and C. Ipos Research. 2016. Burnout among psychosocial oncologists: An application and extension of the effort–reward imbalance model. Psycho-Oncology 25(2):194–202.
Rathert, C., D. R. May, and H. S. Chung. 2016. Nurse moral distress: A survey identifying predictors and potential interventions. International Journal of Nursing Studies 53:39–49.
Ratwani, R. M., E. Savage, A. Will, R. Arnold, S. Khairat, K. Miller, R. J. Fairbanks, M. Hodgkins, and A. Z. Hettinger. 2018a. A usability and safety analysis of electronic health records: A multi-center study. Journal of the American Medical Informatics Association 25(9):1197–1201.
Ratwani, R. M., E. Savage, A. Will, A. Fong, D. Karavite, N. Muthu, A. J. Rivera, C. Gibson, D. Asmonga, B. Moscovitch, R. Grundmeier, and J. Rising. 2018b. Identifying electronic health record usability and safety challenges in pediatric settings. Health Affairs (Millwood) 37(11):1752–1759.
Read, E., and H. K. Laschinger. 2013. Correlates of new graduate nurses’ experiences of workplace mistreatment. Journal of Nursing Administration 43(4):221–228.
Rees, C., L. Wirihana, R. Eley, R. Ossieran-Moisson, and D. Hegney. 2018. The effects of occupational violence on the well-being and resilience of nurses. Journal of Nursing Administration 48(9):452–458.
Riesenberg, L. A., J. Leitzsch, J. L. Massucci, J. Jaeger, J. C. Rosenfeld, C. Patow, J. S. Padmore, and K. P. Karpovich. 2009. Residents’ and attending physicians’ handoffs: A systematic review of the literature. Academic Medicine 84(12):1775–1787.
Robertson, S. L., M. D. Robinson, and A. Reid. 2017. Electronic health record effects on work–life balance and burnout within the I3 population collaborative. Journal of Graduate Medical Education 9(4):479–484.
Rothenberger, D. A. 2017. Physician burnout and well-being: A systematic review and framework for action. Diseases of the Colon and Rectum 60(6):567–576.
Rushton, C. H. 2018. Moral resilience: Transforming moral suffering in healthcare. New York: Oxford University Press.
Rushton, C. H., J. Batcheller, K. Schroeder, and P. Donohue. 2015. Burnout and resilience among nurses practicing in high-intensity settings. American Journal of Critical Care 24(5):412–420.
Rushton, C. H., M. Caldwell, and M. Kurtz. 2016. Moral distress: A catalyst in building moral resilience. American Journal of Nursing 116(7):40–49.
Sargent, M. C., W. Sotile, M. O. Sotile, H. Rubash, and R. L. Barrack. 2004. Stress and coping among orthopaedic surgery residents and faculty. Journal of Bone and Joint Surgery, American Volume 86A(7):1579–1586.
Sauerland, J., K. Marotta, M. A. Peinemann, A. Berndt, and C. Robichaux. 2015. Assessing and addressing moral distress and ethical climate, part II: Neonatal and pediatric perspectives. Dimensions in Critical Care Nursing 34(1):33–46.
Schein, E. H. 1992. Organizational culture and leadership, 2nd ed. San Francisco, CA: Jossey-Bass.
Shanafelt, T. D. 2009. Enhancing meaning in work: A prescription for preventing physician burnout and promoting patient-centered care. JAMA 302(12):1338–1340.
Shanafelt, T. D., P. Novotny, M. E. Johnson, X. Zhao, D. P. Steensma, M. Q. Lacy, J. Rubin, and J. Sloan. 2005. The well-being and personal wellness promotion strategies of medical oncologists in the North Central Cancer Treatment Group. Oncology 68(1):23–32.
Shanafelt, T. D., C. M. Balch, G. J. Bechamps, T. Russell, L. Dyrbye, D. Satele, P. Collicott, P. J. Novotny, J. Sloan, and J. A. Freischlag. 2009a. Burnout and career satisfaction among American surgeons. Annals of Surgery 250(3):463–470.
Shanafelt, T. D., C. P. West, J. A. Sloan, P. J. Novotny, G. A. Poland, R. Menaker, T. A. Rummans, and L. N. Dyrbye. 2009b. Career fit and burnout among academic faculty. Archives of Internal Medicine 169(10):990–995.
Shanafelt, T. D., S. Boone, L. Tan, L. N. Dyrbye, W. Sotile, D. Satele, C. P. West, J. Sloan, and M. R. Oreskovich. 2012a. Burnout and satisfaction with work–life balance among U.S. physicians relative to the general U.S. population. Archives of Internal Medicine 172(18):1377–1385.
Shanafelt, T. D., M. R. Oreskovich, L. N. Dyrbye, D. V. Satele, J. B. Hanks, J. A. Sloan, and C. M. Balch. 2012b. Avoiding burnout: The personal health habits and wellness practices of U.S. surgeons. Annals of Surgery 255(4):625–633.
Shanafelt, T. D., S. L. Boone, L. N. Dyrbye, M. R. Oreskovich, L. Tan, C. P. West, D. V. Satele, J. A. Sloan, and W. M. Sotile. 2013. The medical marriage: A national survey of the spouses/partners of U.S. physicians. Mayo Clinic Proceedings 88(3):216–225.
Shanafelt, T. D., W. J. Gradishar, M. Kosty, D. Satele, H. Chew, L. Horn, B. Clark, A. E. Hanley, Q. Chu, J. Pippen, J. Sloan, and M. Raymond. 2014. Burnout and career satisfaction among U.S. oncologists. Journal of Clinical Oncology 32(7):678–686.
Shanafelt, T. D., O. Hasan, L. N. Dyrbye, C. Sinsky, D. Satele, J. Sloan, and C. P. West. 2015. Changes in burnout and satisfaction with work–life balance in physicians and the general U.S. working population between 2011 and 2014. Mayo Clinic Proceedings 90(12):1600–1613.
Shanafelt, T. D., L. N. Dyrbye, C. Sinsky, O. Hasan, D. Satele, J. Sloan, and C. P. West. 2016a. Relationship between clerical burden and characteristics of the electronic environment with physician burnout and professional satisfaction. Mayo Clinic Proceedings 91(7):836–848.
Shanafelt, T. D., O. Hasan, S. Hayes, C. A. Sinsky, D. Satele, J. Sloan, C. P. West, and L. N. Dyrbye. 2016b. Parental satisfaction of U.S. physicians: Associated factors and comparison with the general U.S. working population. BMC Medical Education 16(1):228.
Shanafelt, T. D., C. Sinsky, L. N. Dyrbye, M. Trockel, and C. P. West. 2019a. Burnout among physicians compared with individuals with a professional or doctoral degree in a field outside of medicine. Mayo Clinic Proceedings 94(3):549–551.
Shanafelt, T. D., C. P. West, C. Sinsky, M. Trockel, M. Tutty, D. V. Satele, L. E. Carlasare, and L. N. Dyrbye. 2019b. Changes in burnout and satisfaction with work–life integration in physicians and the general U.S. working population between 2011 and 2017. Mayo Clinic Proceedings.
Shi, J., S. Wang, P. Zhou, L. Shi, Y. Zhang, F. Bai, D. Xue, and X. Zhang. 2015. The frequency of patient-initiated violence and its psychological impact on physicians in China: A cross-sectional study. PLOS ONE 10(6):PMC4450867.
Shimizutani, M., Y. Odagiri, Y. Ohya, T. Shimomitsu, T. S. Kristensen, T. Maruta, and M. Iimori. 2008. Relationship of nurse burnout with personality characteristics and coping behaviors. Industrial Health 46(4):326–335.
Shin, S., J. H. Park, and S. H. Bae. 2018. Nurse staffing and nurse outcomes: A systematic review and meta-analysis. Nursing Outlook 66(3):273–282.
Sikka, R., J. M. Morath, and L. Leape. 2015. The quadruple aim: Care, health, cost and meaning in work. BMJ Quality and Safety 24(10):608–610.
Simpson, K. R., A. Lyndon, and C. Ruhl. 2016. Consequences of inadequate staffing include missed care, potential failure to rescue, and job stress and dissatisfaction. Journal of Obstetric, Gynecologic, and Neonatal Nursing 45(4):481–490.
Singh, P., D. S. Aulak, S. S. Mangat, and M. S. Aulak. 2016. Systematic review: Factors contributing to burnout in dentistry. Occupational Medicine 66(1):27–31.
Sinsky, C. A., and M. R. Privitera. 2018. Creating a “manageable cockpit” for clinicians: A shared responsibility. JAMA Internal Medicine 178(6):741–742.
Sinsky, C., L. Colligan, L. Li, M. Prgomet, S. Reynolds, L. Goeders, J. Westbrook, M. Tutty, and G. Blike. 2016. Allocation of physician time in ambulatory practice: A time and motion study in 4 specialties. Annals of Internal Medicine 165(11):753–760.
Sittig, D. F., A. Wright, E. Coiera, F. Magrabi, R. Ratwani, D. W. Bates, and H. Singh. 2018. Current challenges in health information technology–related patient safety. Health Informatics Journal Dec 11:1460458218814893 [Epub ahead of print].
Smit, B. W., P. W. Maloney, C. P. Maertz, and T. Montag-Smit. 2016. Out of sight, out of mind? How and when cognitive role transition episodes influence employee performance. Human Relations 69(11):2141–2168.
Smith, M. J., and P. C. Sainfort. 1989. A balance theory of job design for stress reduction. International Journal of Industrial Ergonomics 4(1):67–79.
Sochalski, J. 2001. Quality of care, nurse staffing, and patient outcomes. Policy, Politics, & Nursing Practice 2(1):9–18.
Spence Laschinger, H. K., and R. Fida. 2014. New nurses burnout and workplace wellbeing: The influence of authentic leadership and psychological capital. Burnout Research 1(1):19–28.
Staggers, N., B. L. Elias, E. Makar, and G. L. Alexander. 2018. The imperative of solving nurses’ usability problems with health information technology. Journal of Nursing Administration 48(4):191–196.
Steger, M. F. 2009. Meaning in life. In S. J. Lopez and C. R. Snyder (eds.), The Oxford handbook of positive psychology, 2nd ed. New York: Oxford University Press. Pp. 679–687.
Stimpfel, A. W., D. M. Sloane, and L. H. Aiken. 2012. The longer the shifts for hospital nurses, the higher the levels of burnout and patient dissatisfaction. Health Affairs 31(11):2501–2509.
Stimpfel, A. W., E. T. Lake, S. Barton, K. C. Gorman, and L. H. Aiken. 2013. How differing shift lengths relate to quality outcomes in pediatrics. Journal of Nursing Administration 43(2):95–100.
Szanton, S. L., and J. M. Gill. 2010. Facilitating resilience using a society-to-cells framework: A theory of nursing essentials applied to research and practice. Advances in Nursing Science 33(4):329–343.
Tak, H. J., F. A. Curlin, and J. D. Yoon. 2017. Association of intrinsic motivating factors and markers of physician well-being: A national physician survey. Journal of General Internal Medicine 32(7):739–746.
Tawfik, D. S., C. S. Phibbs, J. B. Sexton, P. Kan, P. J. Sharek, C. C. Nisbet, J. Rigdon, M. Trockel, and J. Profit. 2017. Factors associated with provider burnout in the NICU. Pediatrics 139(5). pii: e20164134 [Epub ahead of print].
Thomas, T. A., and L. B. McCullough. 2015. A philosophical taxonomy of ethically significant moral distress. Journal of Medical Philosophy 40(1):102–120.
Topaz, M., C. Ronquillo, L. M. Peltonen, L. Pruinelli, R. F. Sarmiento, M. K. Badger, S. Ali, A. Lewis, M. Georgsson, E. Jeon, J. L. Tayaben, C. H. Kuo, T. Islam, J. Sommer, H. Jung, G. J. Eler, D. Alhuwail, and Y. L. Lee. 2016. Nurse informaticians report low satisfaction and multi-level concerns with electronic health records: Results from an international survey. AMIA Annual Symposium Proceedings 2016–2025.
Ulrich, C., P. O’Donnell, C. Taylor, A. Farrar, M. Danis, and C. Grady. 2007. Ethical climate, ethics stress, and the job satisfaction of nurses and social workers in the United States. Social Science & Medicine 65(8):1708–1719.
Ulrich, B., C. Barden, L. Cassidy, and N. Varn-Davis. 2019. Critical care nurse work environments 2018: Findings and implications. Critical Care Nurse 39(2):67–84.
Vahey, D. C., L. H. Aiken, D. M. Sloane, S. P. Clarke, and D. Vargas. 2004. Nurse burnout and patient satisfaction. Medical Care 42(2 Suppl):II57–II66.
Van Bogaert, P., C. Kowalski, S. M. Weeks, D. Van heusden, and S. P. Clarke. 2013. The relationship between nurse practice environment, nurse work characteristics, burnout and job outcome and quality of nursing care: A cross-sectional survey. International Journal of Nursing Studies 50(12):1667–1677.
van der Wal, R. A., M. J. Bucx, J. C. Hendriks, G. J. Scheffer, and J. B. Prins. 2016. Psychological distress, burnout and personality traits in Dutch anaesthesiologists: A survey. European Journal of Anaesthesiology 33(3):179–186.
Vidulich, M. A., and P. Tsang. 2012. Handbook of human factors and ergonomics. Hoboken, NJ: John Wiley & Sons.
Webster, G. C., and F. E. Baylis. 2000. Moral residue. In Margin of error: The ethics of mistakes in the practice of medicine, edited by S. B. Rubin and L. Zoloth. Hagerstown, MD: University Publishing Group. Pp. 217–230.
Wei, H., K. Sewell, G. Wood, and M. Rose. 2018. The state of the science of nurse work environments in the United States: A systematic review. International Journal of Nursing Sciences 5:287–300.
Weinger, M. B., S. B. Reddy, and J. M. Slagle. 2004. Multiple measures of anesthesia workload during teaching and nonteaching cases. Anesthesia & Analgesia 98(5):1419–1425.
Weinger, M., M. Wiklund, and D. Gardner-Bonneau. 2011. Handbook of human factors in medical device design. Boca Raton, FL: CRC Press/Taylor Francis.
Welp, A., L. L. Meier, and T. Manser. 2016. The interplay between teamwork, clinicians’ emotional exhaustion, and clinician-rated patient safety: A longitudinal study. Critical Care 20(1):110.
Whitehead, P. B., R. K. Herbertson, A. B. Hamric, E. G. Epstein, and J. M. Fisher. 2015. Moral distress among healthcare professionals: Report of an institution-wide survey. Journal of Nursing Scholarship 47(2):117–125.
Wilson, G. F., and R. D. O’Donnell. 1988. Measurement of operator workload with the neuropsychological workload test battery. In Advances in psychology. Vol. 52, edited by P. A. Hancock and N. Meshkati. North-Holland. Pp. 63–100.
Xu, J., C. Reale, J. M. Slagle, S. Anders, M. S. Shotwell, T. Dresselhaus, and M. B. Weinger. 2017. Facilitated nurse medication-related event reporting to improve medication management quality and safety in intensive care units. Nursing Research 66(5):337–349.
Yao, Y., S. Zhao, X. Gao, Z. An, S. Wang, H. Li, Y. Li, L. Gao, L. Lu, and Z. Dong. 2018. General self-efficacy modifies the effect of stress on burnout in nurses with different personality types. BMC Health Services Research 18(1):667.
Yoon, J. D., N. B. Hunt, K. C. Ravella, C. S. Jun, and F. A. Curlin. 2017. Physician burnout and the calling to care for the dying: A national survey. American Journal of Hospice and Palliative Medicine 34(10):931–937.
Young, M. S., K. A. Brookhuis, C. D. Wickens, and P. A. Hancock. 2015. State of science: Mental workload in ergonomics. Ergonomics 58(1):1–17.
Zellars, K. L., W. A. Hochwarter, P. L. Perrewé, N. Hoffman, and E. W. Ford. 2004. Experiencing job burnout: The roles of positive and negative traits and states. Journal of Applied Social Psychology 34(5):887–911.
Ziedelis, A. 2018. Perceived calling and work engagement among nurses. Western Journal of Nursing Research 41(6):816–833.
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