research articles 2016

Understanding the burnout experience: recent research and its implications for psychiatry

Christina maslach.

1 Psychology Department, University of California at Berkeley, Berkeley, CA, 94720, USA

Michael P. Leiter

2 Centre for Organizational Research & Development, Acadia University, Wolfville, NS, B4P 2R6, Canada

The experience of burnout has been the focus of much research during the past few decades. Measures have been developed, as have various theoretical models, and research studies from many countries have contributed to a better understanding of the causes and consequences of this occupationally‐specific dysphoria. The majority of this work has focused on human service occupations, and particularly health care. Research on the burnout experience for psychiatrists mirrors much of the broader literature, in terms of both sources and outcomes of burnout. But it has also identified some of the unique stressors that mental health professionals face when they are dealing with especially difficult or violent clients. Current issues of particular relevance for psychiatry include the links between burnout and mental illness, the attempts to redefine burnout as simply exhaustion, and the relative dearth of evaluative research on potential interventions to treat and/or prevent burnout. Given that the treatment goal for burnout is usually to enable people to return to their job, and to be successful in their work, psychiatry could make an important contribution by identifying the treatment strategies that would be most effective in achieving that goal.

For many years, burnout has been recognized as an occupational hazard for various people‐oriented professions, such as human services, education, and health care. The therapeutic or service relationships that such providers develop with recipients require an ongoing and intense level of personal, emotional contact. Although such relationships can be rewarding and engaging, they can also be quite stressful.

Within such occupations, the prevailing norms are to be selfless and put others' needs first; to work long hours and do whatever it takes to help a client or patient or student; to go the extra mile and to give one's all. Moreover, the organizational environments for these jobs are shaped by various social, political, and economic factors (such as funding cutbacks or policy restrictions) that result in work settings that are high in demands and low in resources. Recently, as other occupations have become more oriented to “high‐touch” customer service, the phenomenon of burnout has become relevant for these jobs as well 1 .

DEFINING BURNOUT

Burnout is a psychological syndrome emerging as a prolonged response to chronic interpersonal stressors on the job. The three key dimensions of this response are an overwhelming exhaustion, feelings of cynicism and detachment from the job, and a sense of ineffectiveness and lack of accomplishment. The significance of this three‐dimensional model is that it clearly places the individual stress experience within a social context and involves the person's conception of both self and others.

The initial research on burnout was exploratory and relied primarily on qualitative techniques. Because the earliest researchers came from social and clinical psychology, they gravitated toward relevant ideas from these fields. The social perspective utilized concepts involving interpersonal relations, i.e. how people perceive and respond to others; these included detached concern, dehumanization in self‐defense, and attribution processes. It also brought in concepts of motivation and emotion (and especially coping with emotional arousal). The clinical perspective also dealt with motivation and emotion, but framed these more in terms of psychological disorders, such as depression. Subsequent researchers came from industrial‐organizational psychology, and this perspective emphasized work attitudes and behaviors. It was also at this point that burnout was conceptualized as a form of job stress, but the primary focus was on the organizational context and less on the physical characteristics of the experienced stress.

What emerged from this descriptive work were the three dimensions of the burnout experience. The exhaustion dimension was also described as wearing out, loss of energy, depletion, debilitation, and fatigue. The cynicism dimension was originally called depersonalization (given the nature of human services occupations), but was also described as negative or inappropriate attitudes towards clients, irritability, loss of idealism, and withdrawal. The inefficacy dimension was originally called reduced personal accomplishment, and was also described as reduced productivity or capability, low morale, and an inability to cope.

Assessment of burnout

As the characteristics of burnout became more clearly identified, the next step was to develop measures that could assess them. Various measures were proposed, based on different assumptions about burnout, and many of them relied on the face validity of the measurement items or statements. The first burnout measure that was based on a comprehensive program of psychometric research was the Maslach Burnout Inventory (MBI) 2 , 3 . The MBI was specifically designed to assess the three dimensions of the burnout experience which had emerged from the earlier qualitative research. It has been considered the standard tool for research in this field, and has been translated and validated in many languages 4 . In contrast, other initial measures of burnout focused only on the dimension of exhaustion 5 , 6 .

This distinction between measures that assess several dimensions of burnout, and those that assess the sole dimension of exhaustion, continues to the present day, and reflects different conceptualizations of burnout. For example, the Bergen Burnout Inventory (BBI) 7 assesses three dimensions of burnout: exhaustion at work, cynicism toward the meaning of work, and sense of inadequacy at work. The Oldenburg Burnout Inventory (OLBI) 8 assesses the two dimensions of exhaustion and disengagement from work. Other burnout measures focus on exhaustion alone, although they differentiate between various aspects of exhaustion. For example, the Shirom‐Melamed Burnout Measure (SMBM) 9 distinguishes between physical fatigue, emotional exhaustion, and cognitive weariness; and the Copenhagen Burnout Inventory (CBI) 10 makes a distinction between physical and psychological exhaustion.

There have been other changes and modifications of burnout measures over the years. Because the initial concern about burnout emerged from caregiving occupations, such as health care and human services, the measures developed in the 1980s tended to reflect the experience of those professions. Later, however, other occupational groups became interested in the occurrence of burnout, but had some difficulties in adapting the existing measures to their work situation. For the MBI, the solution was the development of a General Survey that could be used within any occupation (MBI‐GS) 11 . Not only were various items revised to be more “occupation‐neutral”, but the dimension of depersonalization (which was more specific to human services) was broadened to refer to a negative detachment from work and was renamed cynicism , and the dimension of personal accomplishment was broadened and renamed professional efficacy . More recent burnout measures utilized more occupation‐neutral wording from the outset.

However, some measures also added some new dimensions to the concept of burnout. For example, the Spanish Burnout Inventory consists of four dimensions: enthusiasm towards the job, psychological exhaustion, indolence, and guilt 12 . Meanwhile, some researchers were concerned that the more neutral wording meant a loss of the specific interpersonal issues for human service workers, so they developed a new measure of interpersonal strain 13 . It remains an open question whether these additional elements are essential components of burnout per se , or whether they assess experiences or conditions that often accompany the experience of burnout.

An important development, at the beginning of the 21st century, has been that researchers have tried to broaden their understanding of burnout by extending their attention to its positive antithesis. This positive state has been identified as “engagement”. Although there is general agreement that engagement with work represents a productive and fulfilling state within the occupational domain, there are differences in its definition.

For some burnout researchers, engagement is considered to be the opposite of burnout and is defined in terms of the same three dimensions as burnout, but the positive end of those dimensions rather than the negative. From this perspective, engagement consists of a state of high energy, strong involvement, and a sense of efficacy 14 . By implication, engagement is assessed by the opposite pattern of scores on the three MBI dimensions.

However, a different approach has defined work engagement as a persistent, positive affective‐motivational state of fulfillment that is characterized by the three components of vigor, dedication, and absorption. In this view, work engagement is an independent and distinct concept, which is not the opposite of burnout (although it is negatively related to it). A new measure, the Utrecht Work Engagement Scale (UWES) 15 , was developed to assess this positive state, and extensive research has been carried out in the last decade 16 .

The relationship between burnout and engagement continues to be debated, however, and a recent approach has been to use dialectical theory to synthesize conflicting views on the two constructs, and to develop an alternate model 17 .

Conceptual models

There have been various conceptual models about the development of burnout and its subsequent impact. At first, the focus was on the relationship between the three dimensions of burnout, which was often described in sequential stages. Exhaustion was assumed to develop first, in response to high demands and overload, and then this would precipitate detachment and negative reactions to people and the job (depersonalization or cynicism). If this continued, then the next stage would be feelings of inadequacy and failure (reduced personal accomplishment or professional inefficacy).

More recently, burnout models have been based on theories about job stress, and the notion of imbalances leading to strain. The first such model was the transactional one, which served as the conceptual bridge between sequential stages and imbalances 18 . Its three stages are: a) job stressors (an imbalance between work demands and individual resources), b) individual strain (an emotional response of exhaustion and anxiety), and c) defensive coping (changes in attitudes and behavior, such as greater cynicism).

Subsequently, two developmental models of the demands‐resources imbalance have emerged: the Job Demands‐Resources (JD‐R) model and the Conservation of Resources (COR) model. The JD‐R model focuses on the notion that burnout arises when individuals experience incessant job demands and have inadequate resources available to address and to reduce those demands 19 . The COR model follows a basic motivational theory assuming that burnout arises as a result of persistent threats to available resources 20 . When individuals perceive that the resources they value are threatened, they strive to maintain those resources. The loss of resources or even the impending loss of resources may aggravate burnout. Both the JD‐R and the COR theory of burnout development have received confirmation in research studies.

A different variation of an imbalance model of burnout is the Areas of Worklife (AW) model, which frames job stressors in terms of person‐job imbalances, or mismatches, but identifies six key areas in which these imbalances take place: workload, control, reward, community, fairness, and values. Mismatches in these areas affect an individual's level of experienced burnout, which in turn determines various outcomes, such as job performance, social behaviors, and personal wellbeing. The greater is the mismatch between the person and the job, the greater the likelihood of burnout; conversely, the greater the match, the greater the likelihood of engagement. Initial empirical support for the AW model has been provided by both cross‐sectional and longitudinal studies 21 .

CAUSES AND OUTCOMES

Most models of burnout make explicit the causal theorizing that has always been implicit in burnout research: certain factors (both situational and individual) cause people to experience burnout, and once burnout occurs, it causes certain outcomes (both situational and individual). However, these causal assumptions have rarely been tested directly. Most research on burnout has involved cross‐sectional designs or studies using statistical causal models. This correlational database has provided support for many of the hypothesized links between burnout and its sources and effects, but it is unable to address the presumed causality of those linkages. The recent increase in longitudinal studies is beginning to provide a better opportunity to test sequential hypotheses, but stronger causal inferences will also require appropriate methodological designs (and these are often difficult to implement in applied settings). One other critical constraint is that many of the variables have been assessed by self‐report measures (rather than other indices of behavior or health).

Over two decades of research on burnout have identified a plethora of organizational risk factors across many occupations in various countries 22 , 23 . Six key domains have been identified, as mentioned earlier: workload, control, reward, community, fairness, and values. The first two areas are reflected in the Demand‐Control model of job stress 24 .

Work overload contributes to burnout by depleting the capacity of people to meet the demands of the job. When this kind of overload is a chronic job condition, there is little opportunity to rest, recover, and restore balance. A sustainable and manageable workload, in contrast, provides opportunities to use and refine existing skills as well as to become effective in new areas of activity.

A clear link has been found between a lack of control and burnout. On the contrary, when employees have the perceived capacity to influence decisions that affect their work, to exercise professional autonomy, and to gain access to the resources necessary to do an effective job, they are more likely to experience job engagement.

The area of reward refers to the power of reinforcements to shape behavior. Insufficient recognition and reward (whether financial, institutional, or social) increases people's vulnerability to burnout, because it devalues both the work and the workers, and is closely associated with feelings of inefficacy. In contrast, consistency in the reward dimension between the person and the job means that there are both material rewards and opportunities for intrinsic satisfaction.

The area of community has to do with the ongoing relationships that employees have with other people on the job. When these relationships are characterized by a lack of support and trust, and by unresolved conflict, then there is a greater risk of burnout. On the contrary, when these job‐related relationships are working well, there is a great deal of social support, employees have effective means of working out disagreements, and they are more likely to experience job engagement.

The area of fairness emerges from the literature on equity and social justice. Fairness is the extent to which decisions at work are perceived as being fair and equitable. People use the quality of the procedures, and their own treatment during the decision‐making process, as an index of their place in the community. Cynicism, anger and hostility are likely to arise when people feel they are not being treated with the appropriate respect.

Finally, the area of values picks up the cognitive‐emotional power of job goals and expectations. Values are the ideals and motivations that originally attracted people to their job, and thus they are the motivating connection between the worker and the workplace, which goes beyond the utilitarian exchange of time for money or advancement. When there is a values conflict on the job, and thus a gap between individual and organizational values, employees will find themselves making a trade‐off between work they want to do and work they have to do, and this can lead to greater burnout.

In terms of outcomes, burnout has been frequently associated with various forms of negative reactions and job withdrawal, including job dissatisfaction, low organizational commitment, absenteeism, intention to leave the job, and turnover 23 . For example, cynicism has been found to be the pivotal aspect of burnout to predict turnover 25 , and burnout mediates the relationship between being bullied in the workplace and the intention to quit the job 26 . On the other hand, for people who stay on the job, burnout leads to lower productivity and impaired quality of work. As burnout diminishes opportunities for positive experiences at work, it is associated with decreased job satisfaction and a reduced commitment to the job or the organization.

People who are experiencing burnout can have a negative impact on their colleagues, both by causing greater personal conflict and by disrupting job tasks. Thus, burnout can be “contagious” and perpetuate itself through social interactions on the job 27 , 28 . The critical importance of social relationships for burnout is underscored by studies that show that burnout increases in work environments characterized by interpersonal aggression 29 , 30 . Such findings suggest that burnout should be considered as a characteristic of workgroups rather than simply an individual syndrome.

Burnout has a complex pattern of relationships with health, in that poor health contributes to burnout and burnout contributes to poor health 31 . Of the three burnout dimensions, exhaustion is the closest to an orthodox stress variable, and therefore is more predictive of stress‐related health outcomes than the other two dimensions. Exhaustion is typically correlated with such stress symptoms as headaches, chronic fatigue, gastrointestinal disorders, muscle tension, hypertension, cold/flu episodes, and sleep disturbances. These physiological correlates mirror those found with other indices of prolonged stress. Parallel findings have been found for the link between burnout and substance abuse 32 .

A ten‐year longitudinal study of industrial workers found burnout to predict subsequent hospital admissions for cardiovascular problems 33 . Other research found that a one‐unit increase in burnout score was related to a 1.4 unit increase in risk for hospital admission for mental health problems, as well as a one‐unit increase in risk for hospital admissions for cardiovascular problems 31 . Other studies have provided a more detailed examination of the link between burnout and cardiovascular disease, noting the role of high‐sensitivity C‐reactive protein and fibrinogen concentrations in the link 34 .

BURNOUT IN PSYCHIATRY

To a large extent, the research literature on burnout in psychiatry echoes those previous themes. Workplace variables have been found to be more stressful for psychiatrists than other factors, and thus may be more likely to perpetuate burnout 35 . These variables include too much work, long working hours, chronic staff shortages, an aggressive administrative environment, and lack of support from management. Poor relationships with management and supervisors have also been identified as related to burnout among psychiatry residents 36 . However, research has found mixed results with regard to the role of job satisfaction in burnout, with some studies reporting no relationship 37 , 38 , and other studies reporting that job satisfaction did play a role 39 , 40 .

The rate of burnout among those employed in the health care field tends to be reported in the moderate to high levels, and it is generally believed that the burnout risk in health care is higher than in the general working population. Reported burnout rates for psychiatrists are quite similar to this overall trend 41 , 42 , 43 . Some studies have raised the possibility that psychiatrists show an even more negative risk profile for burnout than do other health care employees 36 , 43 , 44 . For example, one study found that 89% of psychiatrists had either thought about or experienced a clear threat of severe burnout 45 .

There are other critical risk factors that may be more unique to the field of psychiatry. Chief among these is the working relationship that psychiatrists, and other mental health professionals, have with clients who are experiencing psychological trauma. The challenging demands posed by these and other difficult clients can lead to greater stress and frustration among psychiatrists, which in turn can fuel the exhaustion, cynicism, and inefficacy of burnout. This process has also been described in terms such as compassion fatigue, secondary traumatic stress, and vicarious traumatization 46 , 47 , 48 . The burnout experience can become especially overwhelming when the psychiatrist becomes the target of anger, hatred, and even violence, as a result of negative transference 49 . Violent incidents with patients can be emotionally draining and difficult to manage, and can lead health providers to psychologically distance themselves from their work. The occurrence of violence can also make providers feel that they lack control over their job, and thus challenge their sense of professional efficacy.

Higher levels of burnout are correlated with more negative feelings about patients 50 and a poorer quality of patient care 51 . This link between burnout and poor care is supported by research on how burnout is manifested in psychiatrists, by changes in appearance (e.g., look of fatigue), behavior (e.g., becoming avoidant, making less eye contact), and mood (e.g., becoming more irritable and agitated, communicating poorly). In addition, perfectionist and obsessive traits may perpetuate burnout, particularly when the workload is heavy or stressful 52 .

Working with demanding patients and working with patients’ families have been found to be closely associated with psychiatrists’ levels of exhaustion and depersonalization 35 . These relationships reflect psychiatrists’ frustrations with the limits of their craft. Contact with patients’ families intensified these feelings, especially when family members expressed unrealistic expectations for treatment. Psychiatrists are emotionally drained by their inability to meet the strenuous demands they put upon themselves, and the demands inherent in their interactions with patients and patients’ families. In contrast, diminished personal accomplishment reflects problematic relationships with superiors and colleagues, rather than demands from patients. Colleagues provide the most relevant source of information regarding one's sense of efficacy in professional life. When those relationships are strained, it is difficult to find meaningful confirmation of one's job performance.

Research on burnout has always recognized a central role for social relationships in the development and resolution of the syndrome. Initially, the research focus was primarily on the therapeutic relationship between the provider and the service recipient. Over time, studies have confirmed that relationships with colleagues and supervisors are equally, if not more, relevant to the potential for providers to experience burnout. For example, recent research on attachment styles found that attachment anxiety was accompanied by more frequent incivility from colleagues, and was associated with more exhaustion and cynicism. Attachment avoidance was linked to fewer instances of positive social encounters at work, and was associated with a greater sense of inefficacy 53 . In sum, negative social interactions seem to drain energy and distance people from their job, and the absence of positive social encounters is discouraging.

CURRENT ISSUES

There are many interesting questions about burnout and engagement which are being studied in many countries around the world. A few inter‐related themes should be of particular significance for the profession of psychiatry. First is the question of the relationship between burnout and mental illness. Second is the question of the value of simplifying the multi‐dimensional construct of burnout to the single dimension of exhaustion. And third is the question of how best to ameliorate burnout in terms of treatment and prevention.

Burnout and mental illness

When the construct of burnout was first proposed in the 1970s, there were arguments that it was not a distinctly different phenomenon, but rather a new label for an already known state – i.e., “old wine in a new bottle”. However, there were a lot of differing opinions about what the “already known state” actually was. These included job dissatisfaction, anomie, job stress, anxiety, anger, depression, or some combination of them 54 , 55 , 56 . For example, one psychoanalytic perspective argued that burnout was not distinguishable from either job stress or depression, but represented a failure to achieve narcissistic satisfaction in the pursuit of ideals 57 . As a result of these critiques, subsequent research often focused on testing the discriminant validity of burnout by assessing whether it could be distinguished from these other phenomena. The results of many studies have established that burnout is indeed a distinct construct 23 .

Much of this prior discussion has focused on depression, thus raising the question of whether burnout is a precipitating factor for depression, and thus is a predictor for it, or whether burnout is the same thing as depression, and thus is itself a mental illness. Research has demonstrated that the two constructs are indeed distinct: burnout is job‐related and situation‐specific, as opposed to depression, which is more general and context‐free.

However, a recent article has renewed debate on the distinction between burnout and depression by claiming that at high levels the two states are indistinguishable 58 . This position is in contrast to the view that burnout is an occupationally‐specific dysphoria that is distinct from depression as a broadly based mental illness 22 . But close examination of the new research article reveals problems with its argument.

A necessary condition to examine the distinction between burnout and depression is a set of measures that provide a complete and accurate operationalization of each construct, and the new study fell short of this criterion. Specifically, the nine‐item depression measure (Patient Health Questionnaire, PHQ‐9 59 ) used in this study includes five items that refer explicitly to fatigue (lack of interest, trouble sleeping, trouble concentrating, moving slowly, and feeling tired). The other four items include one referring to loss of appetite and three referring to negative thoughts (suicidal thoughts, feeling depressed, negative self‐evaluation). The measure produces a single factor score; clearly that factor is heavily weighted towards fatigue (Cronbach alpha of .88). It may be argued that these nine items fail to capture the full complexity of clinical depression. In any case, the depression construct operationalized in this measure is one dominated by fatigue, accompanied by negative thoughts. To measure burnout, the study used the SMBM 9 , which is a one‐factor fatigue scale with items referring explicitly to trouble concentrating, feeling tired, and thinking in a slow, unfocused, and unclear manner. Although conceptualized as representing three distinct factors of cognitive, physical, and emotional fatigue, the measure consistently reduces to a single factor of fatigue (Cronbach alpha of .96). Given the overlap in the explicit reference of the two measures to fatigue in the majority of their items, it is not surprising that the two scales are correlated highly (r=.77) 58 .

The high correspondence of burnout and depression in this new study reflects a large level of concept redundancy between the SMBM and PHQ‐9. The two instruments primarily measure exhaustion, leading to a strong correspondence between them, especially at high levels of exhaustion. The correlation was especially high in this study; earlier research that used these identical measures reported correlations at three different times as .51, .53, and .54 60 . These results are consistent with other research that finds that burnout and depression are inter‐related conditions.

Research using the MBI departs further from depression measures in its three‐component definition of the syndrome as exhaustion, cynicism, and inefficacy. Some studies that have used the MBI and different measures of depression have found the following range of correlations. The Profile of Mood States (POMS) depression scale correlated with the MBI ‐ Human Services Survey (MBI‐HSS) exhaustion (r=.33), depersonalization (r=.30), and personal accomplishment (r=−.14) 61 . The Depression Anxiety Stress Scale (DASS‐21) depression subscale correlated with the MBI‐GS exhaustion (r=.37), cynicism (r=.47), and efficacy (r=−.21) 62 . The Beck negative emotions and attitudes subscale correlated with the MBI‐GS exhaustion (r=.46) and cynicism (r=.28), and the Beck performance difficulties and somatic complaints subscale correlated with MBI‐GS exhaustion (r=.61) and cynicism (r=.36) 63 .

The wide range of correlations between burnout and depression argues for a complex relationship between the two constructs. Clearly, they are linked to each other. For example, one study found that 90% of the respondents with severe burnout (i.e., daily occurrence of burnout symptoms) reported a physical or mental disease, with musculoskeletal pain and depression as the most common problems 64 . A longitudinal study found that increases in burnout predicted increases in subsequent prescriptions of antidepressant medication 65 .

A new understanding of this linkage comes from a recent longitudinal study in Finland, which found a reciprocal relationship between burnout and depression, with each predicting subsequent developments in the other. It was noteworthy that burnout fully mediated the relationship of workplace strains with depression: when problems at work contribute to depression, experiencing burnout is a step in the process 66 .

These studies confirm that burnout and depression are not independent. Each state has implications for the other. However, that relationship is far from saying that burnout and depression are the same mental illness.

Single or multiple dimensions

Although the original construct acknowledged exhaustion as a key aspect of burnout, it argued that exhaustion is not the whole story. Indeed, if burnout were solely exhaustion, then the word “burnout” would be unnecessary, as it would not be providing any added value. “Exhaustion” would suffice. To rename “exhaustion” as “burnout” would definitely be inviting the criticism of “putting old wine in new bottles”.

And yet, that simplification of burnout to exhaustion has been taking place not only among researchers, but also among practitioners. The driving force seems to be the goal of establishing a clinical diagnosis for burnout, so that health professionals can then receive reimbursement for treating individuals suffering from that condition.

This shift to defining and diagnosing burnout as an individual disorder or disability has been taking place in Northern Europe, primarily in Sweden and the Netherlands. There, burnout has been likened to neurasthenia or other syndromes with a quality of chronic fatigue. Sweden began using work‐related neurasthenia as a burnout diagnosis in 1997; soon, that was within the five most frequent diagnoses 67 . Researchers developed a similar diagnosis in the Netherlands, using clinically validated cut‐off scores on the MBI 68 .

To provide more precise diagnostic direction, Sweden in 2005 revised the ICD‐10 burnout diagnosis (Z73.0) as a difficulty in life management characterized by “vital exhaustion”. The signs of vital exhaustion include two weeks of daily experiences of low energy, with difficulties in concentration, irritability, emotional instability, dizziness, and sleep difficulties. Additionally, these symptoms must interfere with the patients’ capacity to perform their work responsibilities.

In the Netherlands, the term overspannenheid or “overstrain” is used to indicate burnout. This diagnostic approach estimates burnout prevalence at 3‐7% across various occupations, with psychotherapists at 4% 69 . In terms of MBI scores, Dutch researchers recommended that a burnout diagnosis should be connected with very negative scores on exhaustion accompanied by negative scores on one of the other two subscales (cynicism and inefficacy) 70 , 71 .

The use of burnout as a medical diagnosis implies one‐dimensionality, and it is clear that exhaustion has emerged as that single dimension. Moreover, since 1997, the Dutch census bureau has been assessing “burnout” among the working population by using an index of work‐related exhaustion (that is based on the MBI) in its annual national survey. As a consequence, public discourse about burnout in the Netherlands is increasingly limited to exhaustion alone. The risk is that a focus on just exhaustion (and its connection to work overload) will miss the distinct quality of burnout as reflecting a crisis of meaning or values. The exhaustion dimension captures the problem of lacking sufficient energy to make a useful and enduring contribution at work. But it is the cynicism dimension that captures the difficulty in dealing with other people and activities in the work world. Furthermore, efficacy captures the core self‐evaluation people make regarding the value of their work and the quality of their contribution. To ignore these core aspects of the burnout experience would truly be a “mis‐diagnosis” that could have important ramifications for both policy and practice.

It is interesting that North American jurisdictions have been reluctant to recognize burnout as a clinical diagnosis, partially due to concerns about a flood of requests for disability coverage. The lack of an official diagnosis of burnout limits access to treatment, disability coverage, and workplace accommodations. Alternatively, disability applications have referred to depression, neurasthenia, or chronic fatigue. An unfortunate consequence is that inaccurate diagnoses may reduce possibilities for successful recovery and return to work.

New research has begun to focus on an innovative use of the three burnout dimensions, which allows for multiple distinct patterns along the burnout‐engagement continuum. In addition to the two standard endpoint patterns of Burnout (high on all three dimensions) and Engagement (low on all three dimensions), this approach can identify people who are only experiencing one of the dimensions, rather than all of them 72 . A particularly relevant comparison is between people with the complete Burnout profile and those with only high exhaustion (the Overextended profile). The research findings show that these two patterns are decidedly different in terms of their workplace experience, so it is clear that exhaustion alone is not a proxy for burnout. Instead, the profile that comes closer to the negative endpoint of Burnout is the cynicism‐only one (Disengaged profile), which suggests that the experience of cynicism may be more of a core part of burnout than exhaustion. Cynicism is more clearly linked to the job environment, in terms of the poor quality of social relationships at work and the lack of critical resources, and that will lead to reduced job satisfaction and poor job performance 73 .

Treatment and prevention

The personal and organizational costs of burnout have led to proposals for various intervention strategies. Some try to treat burnout after it has occurred, while others focus on how to prevent burnout by promoting engagement. Intervention may occur on the level of the individual, workgroup, or an entire organization. In general, the primary emphasis has been on individual strategies, rather than social or organizational ones, despite the research evidence for the primary role of situational factors.

Many of these individual strategies have been adapted from other work done on stress, coping, and health. The most common recommendations have included: a) changing work patterns (e.g., working less, taking more breaks, avoiding overtime work, balancing work with the rest of one's life); b) developing coping skills (e.g., cognitive restructuring, conflict resolution, time management); c) obtaining social support (both from colleagues and family); d) utilizing relaxation strategies; e) promoting good health and fitness; and f) developing a better self‐understanding (via various self‐analytic techniques, counseling, or therapy) 74 .

Initiatives to moderate workload demands complemented by improvements in recovery strategies through better sleep, exercise, and nutrition have direct relevance to the exhaustion component of burnout. Cynicism, in contrast, pertains more directly to a sense of community or to the congruence of personal and workplace values. For example, an intervention that improved workplace civility among health care providers showed that cynicism declined as a function of improved civility 75 , and that this change was sustained at a one‐year follow‐up assessment 76 . A sense of efficacy, in contrast, could be more responsive to improvements in the forms of recognition from colleagues and leaders within an organization or the profession. An alternative proposal has been that people can make various changes in how they do their job (a process known as “job crafting”), and that such job alterations could lead to less burnout 77 .

Unfortunately, there is very little research that has evaluated the efficacy of any of these approaches in reducing the risk of burnout. Especially rare are studies modeled even loosely on randomized control trials. More common are studies with a single intervention group of volunteer participants for whom there are rarely follow‐up assessments after treatment has ended 78 . It is not yet clear whether burnout is generally susceptible to a range of strategies or whether it is crucial to fit the strategy to the specific context of a workplace to be effective.

The same basic points can be made about studies examining interventions specific to psychiatrists. There have been several recommendations about possible interventions, but no thorough research on whether these ideas are viable solutions. One fairly common recommendation emphasizes the importance of various forms of support, such as peer support groups, formal support via regular feedback and performance evaluation, or the use of a community‐based approach in the work environment. Interestingly, medical students and residents have also identified support as a critical factor, including support from faculty, peers, outside personal relationships, and counseling services 79 .

Another suggestion involves having psychiatrists evaluate their workload frequently, to ensure they are not putting themselves at additional risk for burnout. A related recommendation is that psychiatrists should develop a more versatile lifestyle, in which they diversify their work (e.g., take on a part‐time teaching job, do some writing, or extend one's practice to other types of clients) and/or engage in activities outside of work (such as hobbies and other personal interests).

Mental health professionals who have worked in the areas of trauma and palliative care have made additional recommendations on how to deal with burnout 80 , 81 . Notably, one approach emphasizes the need to take care of oneself – and not only in terms of personal health and physical fitness, but also in terms of psychological wellbeing. Professionals who deal with trauma survivors are encouraged to work through their own personal traumatic experiences in order to prevent becoming “wounded healers” or secondarily traumatized therapists. Professionals working in hospice and palliative medicine are encouraged to focus on spirituality and human nature, via prayer, meditation, or religious services. Other methods for self‐care include taking regular breaks from work, advocating for better social recognition of the difficult work that is being accomplished, and focusing on the positive aspects of life, both at work and home, so that one is not overwhelmed by adversity and misery.

Although various studies have provided excellent ideas to explore as interventions, the logistics of funding, designing, implementing, and evaluating these ideas remain the primary obstacles to better knowledge about the best solutions for burnout. For example, a Swedish group contrasted two therapeutic modalities for people who had been on long‐term leave from work with a diagnosis of “work‐related depression”. They found that both cognitive group therapy and focused psychodynamic group therapy were effective in facilitating their return to work, but found no difference in effectiveness between the two approaches 82 . This study raises two important issues for further research. First, to what extent does “work‐related depression” map upon clinical depression, in contrast to mapping upon burnout? Second, what are the common qualities of the two therapeutic modalities that could serve as mechanisms in treatment efficacy?

CONCLUSIONS

Research to date indicates that the three aspects of burnout do present challenges for psychiatrists. Many of the issues for psychiatrists are similar to those facing other professionals providing human services to people in need of help. But additionally, psychiatric work entails close contact with people in emotional distress, and in some cases the potential for threats from some of these patients. Both of these stressors make demands on psychiatrists’ energy, their capacity for involvement with others, and their sense of professional efficacy.

An issue of special significance to psychiatry is the alignment and differentiation of burnout and depression. The concept of workplace depression as a basis for workers’ disability coverage in some European countries raises important issues for practitioners, which have extensive implications for employees, employers, and insurance providers. Research and conceptual development that includes multidisciplinary participation is needed for definitive progress.

Psychiatry is in a strong position to contribute to the growth of knowledge regarding burnout. The question of burnout's status as a basis for disability claims requires precise and objective assessment. Further, psychiatric‐based treatments may be relevant to burnout, especially regarding return to work for people experiencing severe burnout. Finally, effective research on preventing and alleviating aspects of burnout among psychiatrists requires giving the issue a high priority within the profession.

Research Design Review

A discussion of qualitative & quantitative research design, qualitative research: a collection of articles from 2016.

Qualitative Research: A Collection of Articles from Research Design Review Published in 2016 is a compilation of the 17 RDR articles that were published in 2016 devoted to qualitative research. These 17 articles include articles on:

the Total Quality Framework , such as Applying a Quality Framework to the In-depth Interview Method .
Qualitative data & analysis, such as Qualitative Data: Achieving Accuracy in the Absence of “Truth” and Words Versus Meanings .
Specific methods, such as Reporting Ethnography: Storytelling & the Roles Participants Play .
Researcher bias, such as Mitigating Researcher-as-instrument Effects .
Misplaced quantitative concepts , such as the use of “respondents” to refer to qualitative participants.

The Performance Management Revolution

Peter Cappelli

Hated by bosses and subordinates alike, traditional performance appraisals have been abandoned by more than a third of U.S. companies. The annual review’s biggest limitation, the authors argue, is its emphasis on holding employees accountable for what they did last year, at the expense of improving performance now and in the future. That’s why many organizations are moving to more-frequent, development-focused conversations between managers and employees.

The authors explain how performance management has evolved over the decades and why current thinking has shifted: (1) Today’s tight labor market creates pressure to keep employees happy and groom them for advancement. (2) The rapidly changing business environment requires agility, which argues for regular check-ins with employees. (3) Prioritizing improvement over accountability promotes teamwork.

Some companies worry that going numberless may make it harder to align individual and organizational goals, award merit raises, identify poor performers, and counter claims of discrimination—though traditional appraisals haven’t solved those problems, either. Other firms are trying hybrid approaches—for example, giving employees performance ratings on multiple dimensions, coupled with regular development feedback.

The focus is shifting from accountability to learning.

Idea in Brief

The problem.

By emphasizing individual accountability for past results, traditional appraisals give short shrift to improving current performance and developing talent for the future. That can hinder long-term competitiveness.

The Solution

To better support employee development, many organizations are dropping or radically changing their annual review systems in favor of giving people less formal, more frequent feedback that follows the natural cycle of work.

The Outlook

This shift isn’t just a fad—real business needs are driving it. Support at the top is critical, though. Some firms that have struggled to go entirely without ratings are trying a “third way”: assigning multiple ratings several times a year to encourage employees’ growth.

When Brian Jensen told his audience of HR executives that Colorcon wasn’t bothering with annual reviews anymore, they were appalled. This was in 2002, during his tenure as the drugmaker’s head of global human resources. In his presentation at the Wharton School, Jensen explained that Colorcon had found a more effective way of reinforcing desired behaviors and managing performance: Supervisors were giving people instant feedback, tying it to individuals’ own goals, and handing out small weekly bonuses to employees they saw doing good things.

Peter Cappelli is the George W. Taylor Professor of Management at the Wharton School and the director of its Center for Human Resources. He is the author of several books, including Our Least Important Asset: Why the Relentless Focus on Finance and Accounting Is Bad for Business and Employees (Oxford University Press, 2023).
AT Anna Tavis is a clinical associate professor of human capital management at New York University and the Perspectives editor at People + Strategy, a journal for HR executives.

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Research Article

When the tables are turned: The effects of the 2016 U.S. Presidential election on in-group favoritism and out-group hostility

Contributed equally to this work with: Burak Oc, Celia Moore

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Management and Organisations, University of Western Australia Business School, Crawley, Western Australia, Australia

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Validation, Writing – original draft, Writing – review & editing

Affiliation Department of Management and Technology, Bocconi University, Milan, Lombardy, Italy

Roles Conceptualization, Investigation, Methodology, Writing – original draft, Writing – review & editing

Affiliation Lee Kong Chian School of Business, Singapore Management University, Singapore, Singapore

Burak Oc,
Celia Moore,
Michael R. Bashshur

Published: May 24, 2018
https://doi.org/10.1371/journal.pone.0197848
Reader Comments

The outcome of the 2016 U.S. Presidential election was a big surprise to many, as the majority of polls had predicted the opposite outcome. In this two-stage cross-sectional study, we focus on how Democrats and Republicans reacted to this electoral surprise and how these reactions might have influenced the way they allocated resources to each other in small groups. We find that, before the election, Republicans showed greater in-group favoritism than Democrats, who treated others equally, regardless of their political affiliation. We then show that Democrats experienced the election outcome as an ego shock and, in the week following the election, reported significantly higher levels of negative emotions and lower levels of self-esteem than Republicans. These reactions then predicted how individuals’ decided to allocate resources to others: after the election, Republicans no longer showed in-group favoritism, while Democrats showed out-group derogation. We find these decisions when the tables were turned can be partially explained by differences in participants’ state self-esteem.

Citation: Oc B, Moore C, Bashshur MR (2018) When the tables are turned: The effects of the 2016 U.S. Presidential election on in-group favoritism and out-group hostility. PLoS ONE 13(5): e0197848. https://doi.org/10.1371/journal.pone.0197848

Editor: Jonathan Jong, Coventry University, UNITED KINGDOM

Received: May 17, 2017; Accepted: May 9, 2018; Published: May 24, 2018

Copyright: © 2018 Oc et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: We pre-registered the second part of the study design (see https://osf.io/mujyg/ ). Experimental materials, data, and analysis code for both parts of the study reported in this article can be downloaded from the Open Science Framework at https://osf.io/vqy27/ .

Funding: This research was supported by the London Business School (CM) and Bocconi University (BO). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

On November 9, 2016, the New York Times announced, “Donald Trump’s Victory Is Met With Shock Across a Wide Political Divide” [ 1 ]. This headline captures two critical features of the 2016 U.S. presidential election. The first is how shocking the outcome was. Pollsters had estimated a 75% to 99% chance that Hillary Clinton would win [ 1 , 2 ], so Trump’s victory came as a surprise to most. The second is the degree of political polarization the 2016 election cycle highlighted. The divide between Democrats and Republicans in the U.S., in both voting trends [ 3 ] and political ideology [ 4 ], has increased dramatically in the last two decades, reaching fever pitch during this most recent presidential election. As a result, Democrats’ experienced Trump’s victory as a negative shock, while for Republicans the victory came as a positive surprise.

In this paper we explore how the shock of the unexpected outcome of this highly contested and important election, coupled with increasing political polarization nationally, affected how people in the U.S treat members of their political in-group and out-group. Specifically, we focus on how individuals who feel strong ties to either the Democratic or Republican Party treat each other when they control how resources are allocated, and how these patterns differed before and after the 2016 U.S. Presidential election. We observe that, prior to the election, Democrats treat others equally, regardless of their political affiliation, while Republicans show significant in-group favoritism (higher levels of generosity towards other Republicans). After the election, we demonstrate that these allocation patterns no longer held. Specifically, we argue that Democrats experienced the election as an ego shock (manifested in terms of low levels of state self-esteem), and this negative shock led to less generosity towards Republicans (out-group derogation). On the other hand, Republicans, experiencing the election as a positive shock, had less need to show in-group favoritism, and could be more generous to everyone.

Before the election: Secure Democrats, threatened Republicans

A large body of research confirms that simply being a member of a group is sufficient to elicit more positive evaluations of fellow group members, as well as to like and favor them more than others [ 5 ]. This is because group membership provides individuals with a lens through which they construe their own reality and shapes their conscious and unconscious reactions toward in- and out-group members [ 6 , 7 ].

Political party affiliation is an important group membership for individuals [ 8 ], and represents a social identity that is highly salient during elections [ 9 ]. As part of increasing political polarization in the U.S., individuals tend to classify co-partisans as members of their in-group and opposing partisans as members of their out-group [ 4 , 10 , 11 ]. The resulting in-group bias means that individuals treat co-partisans better than opposing partisans, regardless of their political affiliation: Democrats favor Democrats, and Republicans favor Republicans (4).

This bias is especially evident when groups compete for scarce resources (e.g., money or political power). One of the earliest theories of intergroup threat, realistic group conflict theory (RGCT) [ 12 , 13 ] suggests that in-group favoritism and out-group hostility are more likely to emerge when groups have conflicting goals. This is because the prospect of the out-group’s success threatens the in-group’s access to tangible resources, undermines their power over the out-group and thus the in-group’s potential to achieve its goals. As Sherif and Sherif [ 13 ] argued, such threats will impair inter-group relations by enhancing in-group friendship, exacerbating out-group hostility, and reinforcing in- and out-group distinctions. Although earlier studies of RGCT demonstrated that this in-group bias exists when the individuals involved are threatened directly, more recent work suggests that individuals also exhibit this bias when the interests of their group as a whole are threatened (even if they are threatened directly themselves) [ 14 ].

An election is an important type of resource competition, as its outcome creates a single winner, who then has greater control over resource distribution. Both RGCT and social identity explanations rooted in political partisanship predict in-group favoritism or out-group hostility, broadly, for members of both parties. However, drawing on theory about individuals’ fundamental desire to maintain a positive social identity under threat [ 15 ] helps us make more specific predictions about how an election outcome might affect resource allocations to political in-group and out-group members. On one hand, the prospect of losing a resource competition against an out-group represents a threat, which motivates individuals to protect this aspect of their social identity against the source of the threat. This motivation is driven largely by the desire to develop and maintain good relationships with other in-group members, and thus tends to manifest as in-group favoritism rather than as out-group derogation [ 16 , 17 ]. As Brewer [ 16 ] points out, that “it is easy to fear control by outsiders; perceived common threat from out-group increases in-group cohesion and loyalty” (p. 438).

On the other hand, individuals who are confident that their in-group will prevail in a resource competition do not have the same need to protect their social identity, and thus do not have the same motivation to demonstrate in-group favoritism. In fact, in the absence of threat, individuals may be indifferent towards out-group members or even show them sympathy, providing that in-group boundaries and intergroup distinctions are clearly defined (akin to “we have our ways, they have theirs”) [ 16 ]. Indeed, those who are confident of winning a resource competition may exhibit even more generosity towards out-groups. As Nadler [ 18 ] states, “members of higher status groups may give help to members of lower status groups not only out of caring and concern but also to maintain their social advantage” (p. 490). In other words, members of groups with confidence that they will maintain their power may implicitly assert their dominance to those in relatively less powerful groups by behaving more generously towards them.

These arguments underpin our primary prediction about how Republicans and Democrats treated co-partisans and opposing partisans before the election. Specifically, before the election, we expect Republicans to show in-group favoritism, as the polls heralding the impeding defeat of Trump in the election would be threatening and trigger the desire to reassert a positive social identity. In contrast, the polls prior to the election heightened Democrats’ confidence that they would continue to maintain control over the executive branch. As a result, they would have felt less threatened than Republicans, and thus have less need to assert a positive social identity, which would manifest in terms of less in-group favoritism. Their confidence that Clinton would win may have encouraged them to be more generous towards Republicans, as an assertion of their perceived political or power advantage. Taken together, we predict that, prior to the election, Republicans will favor other Republicans and thus allocate more resources to groups they believe to be more representative of their in-group, while Democrats will show less of this in-group favoritism (if any), and allocate resources more equally to others.

After the election: Threatened Democrats, secure Republicans

Elections can be extremely distressing for those who supported losing candidates [ 19 ]. Specifically, supporters of losing candidates may not only feel rejected [ 20 ], anxious, angry [ 21 ], and extremely unhappy [ 8 ] but also threatened [ 22 ]. This was certainly the case for some of those who supported Clinton [ 23 ], who responded to the election using catastrophic language (e.g., This is a really tragic, unfortunate, terrible disaster”; “At a very base level, it’s terrifying to me”, cf. [ 24 ]).

One way to think about the extremely negative surprise this election outcome represented for Democrats is as an ego-shock . An ego-shock is caused by a major rejection, failure or traumatic event that ultimately shakes one’s self-esteem [ 25 ]. Indeed, people consistently report lower self-evaluations in losing situations than in winning situations [ 26 ]. Hence, as the supporters of the unexpected losing party, we hypothesize that Democrats will report more negative emotions, a larger ego-shock, and lower levels of self-esteem after the election, compared to Republicans.

One of the primary predictions of social identity theory is that threatened self-esteem promotes inter-group discrimination [ 27 ]. This is particularly likely when individuals identify strongly with the threatened social group [ 28 ], and the threat affects those individuals’ state self-esteem [ 17 , 29 ]. Both Branscombe and Wann [ 28 ] and Fein and Spencer [ 30 ] found that one of the outcomes of threat is out-group derogation. As Branscombe and Wann [ 28 ] explain, “when individuals with an important stake in a particular social identity were exposed to a social comparison that threatens the value of that identity, then the more their self-esteem is lowered [and] the more they would derogate the source of threat” (p. 642). Extrapolating from these findings, we hypothesize that Democrats, as the partisan losers of the election, will show more out-group derogation than Republicans, and allocate fewer resources to groups that contain more out-group members. In addition, we expect this effect to be amplified for those who identify strongly with the Democratic Party.

In contrast, individuals who do not experience a direct threat to a valued social identity will be less likely to show in-group favoritism or out-group derogation [ 31 ]. Hence, we expect Republicans, as the partisan winners of the election, will show neither in-group favoritism nor out-group derogation, and allocate resources equally to others irrespective of whether those individuals are members of their in-group or out-group. Furthermore, given that Republicans were not threatened by the election results, we do not expect group identification to moderate these effects for them [ 32 ].

Finally, we propose that Democrats’ and Republicans’ allocations following the election will be partly explained by their state self-esteem. Specifically, individuals with low state self-esteem tend to exhibit greater out-group derogation to enhance their self-image [ 17 ], while those with high state self-esteem are less likely to engage in out-group derogation [ 30 ]. Thus, we predict that lower levels of state self-esteem in the election’s aftermath will explain individuals’ lack of generosity towards out-groups after the election. As the more detrimentally affected party, we predict this effect to be particularly evident among Democrats.

Materials and methods

In a two-stage cross-sectional study, we tested whether the allocations of self-identified Democrats and Republicans to members of their own and opposing political parties differed before and after the 2016 U.S. Presidential election. We conducted the first part of the study before the final primaries and national conventions of both parties (May 3–8, 2016), and the second part, using a new sample, in the week after the election (November 15–20, 2016). We pre-registered the second part of the study design (see https://osf.io/mujyg/ ). Experimental materials, data, and analysis code for both parts of the study reported in this article can be downloaded from the Open Science Framework at https://osf.io/vqy27/ .

Time 1: Before the election

Participants..

We recruited 280 full-time working adults residing in the United States via Amazon Mechanical Turk. We determined this sample size a priori using a power analysis and considering possible exclusions. Specifically, an a priori analysis (calculating the sample size needed for a test of the main effects and the interaction of political party and group composition with a two-factorial design, numerator df = 2, number of groups = 6) using the G*Power software [ 33 ] indicated that a total sample size of 206 would be sufficient in order to reach a power of 90% to detect a medium effect size ( f = 0.25) consistent with polarization effects reported in previous research [ 11 ]. Of these 280 participants, 38 did not feel strong ties to either the Democratic or Republican Party and 33 failed to correctly reply to questions designed to check whether they understood the game. These participants were not allowed to continue in the study. Furthermore, we excluded five participants who reported suspicion that other participants were fake.

We were left with 204 participants who felt meaningful ties to either the Democratic ( n = 109) or Republican Party ( n = 95) (48% female, average age 33.60 years, SD = 11.58). Of those, 174 self-identified as Caucasian, 12 as African American, 10 as Asian, and 8 as Hispanic. Thirty-six participants had post-graduate or graduate degrees, 83 had four-year college degrees and the remaining 85 had two-year college degrees or lower. With respect to annual income, 63.73% of participants reported their earnings as greater than $40,000 a year. Finally, participants earned $0.50 for their participation and had the opportunity to collect up to an additional $1.00 depending on the allocations they made in the study. Participants spent on average 12.56 minutes ( SD = 3.41) completing the study.

Procedure and measures.

Before providing participants with information about the design and procedure of the study, we asked them whether they identified more as a Democrat , a Republican or felt no meaningful tie to either party , and told them that this information would be shared with the other members of their group (we excluded participants who selected the “I feel no meaningful tie to either party” option).

We employed a multi-party dictator game [ 34 ], and informed participants that they would be part of a 4-person group (including themselves), and randomly assigned to be either a dictator, who would decide how much of a common resource ($1.00) they would keep for themselves and how much they would allocate to the other group members (to be divided equally amongst the three recipients). In reality, all participants were assigned to the dictator role, and the recipients were not real people. We formed groups differently for Republican and Democrat dictators in order to test whether they allocated a portion of the $1.00 common resource to others differently as a function of the group members’ political affiliations.

Specifically, we randomly assigned Republican participants to groups of either 1) three Republicans (i.e., all in-group members) ( n = 31), 2) two Republicans and one Democrat (i.e., majority in-group members) ( n = 32), or 3) one Republican and two Democrats (i.e., majority out-group members) ( n = 32). In parallel, we randomly assigned Democrat participants to groups of either 1) three Democrats (i.e., all in-group members) ( n = 38), 2) two Democrats and one Republican (i.e., majority in-group members) ( n = 36), or 3) one Democrat and two Republicans (i.e., majority out-group members) ( n = 35). Once provided with this information about the political party affiliation of their group members, we then asked participants to decide what proportion of the $1.00 they wanted to keep for themselves.

Time 2: After the election

We recruited 280 full-time working adults residing in the United States via Amazon Mechanical Turk. In an effort to replicate the sample size and power of the first wave of data collection we used the same power analysis to determine the required sample size. Of these 280 participants, 31 did not feel strong ties to either the Democratic or Republican party and 40 failed to correctly reply to questions designed to check whether they understood the game. As in Time 1, these participants again were not allowed to continue in the study. Furthermore, we excluded three participants who reported suspicion that other participants were fake and six participants who failed the attention checks.

As in Time 1 (before the election), we report results for the 200 participants who understood the dynamics of the experimental game, did not report suspicion, provided complete responses and felt meaningful ties to either the Democratic ( n = 107) or the Republican Party ( n = 93) (49% female, average age 35.91 years, SD = 11.71). Of those, 148 self-identified as Caucasian, 18 as African American, 22 as Asian, and 12 as Hispanic. 41 participants had post-graduate and graduate degrees, 86 had four-year college degrees and the remaining 73 had two-year college degrees or lower. With respect to annual income, 62% of participants reported their earnings being greater than $40,000 a year. As in Time 1, we paid participants a $0.50 base rate and they had the opportunity to earn up to an additional $1.00 depending on the decisions they made in the study. The average time to complete the study was 12.40 minutes ( SD = 4.87).

As in Time 1, we again randomly assigned Republican participants to groups of either 1) three Republicans ( n = 29), 2) two Republicans and one Democrat ( n = 32), or 3) one Republican and two Democrats ( n = 32) and Democrat participants to groups of either 1) three Democrats ( n = 36), 2) two Democrats and one Republican ( n = 35), or 3) one Democrat and two Republicans ( n = 36). The procedure was the same as Time 1, with several important exceptions. First, before receiving information about the dictator game, we asked participants several questions about their emotional and cognitive reactions to the result of United States presidential election. Second, in line with previous research on intergroup emotions [ 35 ], we asked participants to indicate on a 7-point scale (1 = not at all , 7 = very much ) the extent to which they felt the following six positive emotions ( hope , pride , happiness , pleasantness , enthusiasm , gladness ) and six negative emotions ( hatred , hostility , anger , fear , paranoia , suspicion ) since the election results had been confirmed. Third, using four items of Campbell et al.’s [ 25 ] measure of ego shock (α = .94), we asked participants to rate on a 7-point scale (1 = not at all , 7 = very much) their endorsement of items such as, “Did you feel yourself “freeze up” or find yourself unable to act at any time immediately after the election results were announced?”. Fourth, in order to better capture the effect of the election results on participants’ self-esteem after the election results were announced, we asked participants to respond to Heatherton and Polivy’s [ 36 ] 20-item state self-esteem scale (SSES) (α = .94). This measure modified the Janis-Field Feelings of Inadequacy Scale [ 37 ] and was developed to capture state-dependent, momentary changes in one’s self-esteem or feelings about one’s abilities (as opposed to trait self-esteem, or general levels of self-esteem beyond the effects of situational factors). Previous studies have already provided empirical support for its factor structure as well as construct, content and discriminant validity [ 38 ]. Finally, we measured our participants’ level of identification with their political party on a 7-point scale (1 = strongly disagree , 7 = strongly agree ) using Smith, Seger and Mackie’s [ 39 ] four-item identification measure (e.g., “I identify with other Republicans/Democrats”) (α = .93).

Ethics statement

In both rounds of data collection, participants gave written informed consent before the study began and were paid for their participation. Full ethical approval for the study was received from Singapore Management University (Approval number: IRB-13-0028-A0034) and London Business School (Approval Number: REC91).

Results and discussion

Descriptive analyses.

Table 1 provides descriptive statistics of the sample characteristics both in Time 1 (before the election) and in Time 2 (after the election). Our pre-registered hypotheses were that (1) there would be a difference in how self-identified Republicans and Democrats would allocate resources to others before and after the election, and that (2) their affective and cognitive reactions to the election outcome would help explain this difference. Building on this, we argued that Republicans would show more in-group favoritism before the election, but that after the election they would be less likely to allocate resources in a way that favors their in-group. On the other hand, we expected Democrats to allocate resources more equally to groups, regardless of the group’s composition, before the election, but that the negative shock of the election results would lead them to exhibit out-group derogation after the election, penalizing Republicans by allocating less to them. Moreover, we predicted this allocation pattern would be partly explained by low state self-esteem among Democrats after the election.

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https://doi.org/10.1371/journal.pone.0197848.t001

In order to make the inference using this two-wave cross sectional design that different allocation patterns before and after the election are a function of the election and not other causes, it is first necessary to demonstrate that the two samples are the same on all observable characteristics that might represent alternative explanations of our effects. The more similar the samples, the better the case is that differences in allocation patterns can be attributed to the election and not other causes. The composition of both samples did not differ in terms of gender ( X 2 (1) = .01, p = .93), age ( t = -1.35, p = .18), race ( X 2 (3) = 9.56, p = .15), education ( X 2 (2) = 5.59, p = .59), income ( X 2 (8) = 12.08, p = .15), or political party affiliation ( X 2 (1) = .00, p = .99). In addition, we examined whether there were differences between our pre- and post-election samples of Democrats and Republicans. In fact, the composition of Democrats did not differ in terms of gender ( X 2 (1) = .01, p = .91), age ( t = -1.56, p = .12), race ( X 2 (3) = 6.45, p = .10), education ( X 2 (2) = 8.59, p = .20), or income ( X 2 (8) = 4.82, p = .78). Similarly, Republicans did not differ in terms of gender ( X 2 (1) = .07, p = .79), age ( t = -.36, p = .72), race ( X 2 (3) = 2.72, p = .44), education ( X 2 (2) = 7.20, p = .41), or income ( X 2 (8) = 10.11, p = .26).

We further examined the interaction between political party affiliation and time (pre- and post-election) to test whether Democrats were wealthier than Republicans (or vice versa) before versus after the election, information that is potentially important in interpreting our findings. Their interaction was non-significant ( F (1, 399) = 0.14, p = .713, η p 2 = .013) (suggesting the difference in our participants’ income as a function of political party affiliation across samples did not differ before and after election). Republicans reported higher incomes than Democrats, both before ( F (1, 202) = 5.49, p = .020, η p 2 = .083) and after the election ( F (1, 197) = 3.33, p = .069, η p 2 = .067). Different allocation patterns before and after the election can therefore not be explained by income changes within either political party affiliation before and after the election.

Table 2 presents means, standard deviations, and zero-order Pearson correlations for the main study variables. Fig 1 displays the relative frequency distribution of allocations Republicans and Democrats made (A) before and (B) after the election. The allocations appear to be bipolar (the histogram is overlaid with an appropriately scaled normal density curve which is characterized by the mean and standard deviation of the allocations).

The relative distribution of resource allocations to others (A) before and (B) after the election .

https://doi.org/10.1371/journal.pone.0197848.g001

https://doi.org/10.1371/journal.pone.0197848.t002

An analysis of variance using for the entire sample revealed a main effect for the political party affiliation of the participant, F (1, 392) = 4.81, p = .029, η p 2 = .012, such that, on average, across both time periods and all group compositions, Republicans allocated less money to recipients ( M = 42.55, SD = 31.26) than Democrats ( M = 49.25, SD = 29.18). Additionally, group composition also had a main effect on the amount of money participants allocated to recipients, F (2, 392) = 5.47, p = .005, η p 2 = .027, such that individuals allocated the most to others if their group was comprised of all in-group members ( M = 52.91, SD = 31.26), less if their group included one out-group member ( M = 44.55, SD = 30.80), and even less if their group included two out-group members ( M = 40.99, SD = 30.61). The main effect for tine period was not significant, F (1, 392) = .14, p = .71, indicating that, overall, there was no change in the total amount allocated to group members across the time periods ( M Pre-election = 46.74, SD = 31.04 and M Post-election = 45.52, SD = 29.62).

Resource allocations before the election

Our pre-registered hypotheses were that the (1) allocations of self-identified Republicans and Democrats would change in the aftermath of the election, and that (2) these changes would be explained by participants’ affective and cognitive reactions to the election outcome. Building on this, we argued that, before the election, Republicans would show in-group favoritism, while Democrats would distribute allocations more equally. After the election, we expected Democrats to show out-group derogation, while Republicans would distribute allocations more equally. We additionally predicted that the negative shock of the election results and resulting drop in state self-esteem would partly explain why Democrats would penalize Republicans by allocating less to them after the election.

To test whether, before the election, Republicans would show in-group favoritism while Democrats would distribute allocations more equally involves two specific contrasts. We find that Republicans showed significant in-group favoritism before the election, allocating significantly more to groups of all Republicans ( M = 55.16, SD = 30.01) than to groups of 2 Republicans and 1 Democrat ( M = 36.66, SD = 32.98), or groups of 2 Democrats and 1 Republican ( M = 36.47, SD = 28.06), F (2, 392) = 4.04, p = .018, η p 2 = .020 (see Republicans, pre-election in Fig 2 ). We also find that, before the election, Democrats make equal allocations to their groups, whatever the group composition. The allocations Democrats made to groups of all Democrats ( M = 53.15, SD = 29.21) were not statistically different from the allocations they made to groups of 2 Democrats and 1 Republican ( M = 48.83, SD = 30.23), or groups of 2 Republicans and 1 Democrat ( M = 48.74, SD = 32.62), F (2, 392) = .26, p = .77, η p 2 = .001 (see Democrats, pre-election in Fig 2 ).

Amount allocated by (A) Republicans and (B) Democrats before and after the election .

https://doi.org/10.1371/journal.pone.0197848.g002

Resource allocations after the election

In contrast, after the election, Democrats penalized Republicans, allocating significantly less to groups of 2 Republicans and 1 Democrat ( M = 37.56, SD = 27.52) than to groups of 2 Democrats and 1 Republican ( M = 51.20, SD = 27.64), or groups of all Democrats ( M = 55.83, SD = 25.98), F (2, 392) = 3.63, p = .027, η p 2 = .018 (see Democrats, post-election in Fig 2 ). In contrast, Republicans’ in-group favoritism softened, and Republican allocators made equal allocations to groups, regardless of whether they were comprised of all Republicans ( M = 46.55, SD = 29.15), 2 Republicans and 1 Democrat ( M = 40.34, SD = 31.43), or 2 Democrats and 1 Republican ( M = 40.87, SD = 33.71), F (2, 392) = .40, p = .67, η p 2 = .002 (see Republicans, post-election in Fig 2 ).

Emotional and cognitive reactions to the election

We argued that this difference in how Republicans and Democrats allocate resources to members of their in- and out-group before and after the election would be partially explained by participants’ emotional and cognitive reactions to the election results. Using the Time 2 data, we find an expected significant main effect of political party affiliation on each positive and negative emotion we asked participants to report: Democrats felt less hope , pride , happiness , pleasantness , enthusiasm , and gladness and felt more hatred , hostility , anger , fear , paranoia , and suspicion than Republicans after the election. Each of these differences were significant at p s < .001 (see Fig 3 ). Additionally, a two-tailed t-test confirmed that Democrats experienced the election as a greater ego shock than did Republicans ( M Democrats = 4.37, SD Democrats = 1.84 vs. M Republicans = 2.07, SD Republicans = 1.40, t (198) = 9.79, p < .001, d = 1.41), and, relatedly ( r = -.29, p < .001), reported lower levels of state self-esteem than Republicans ( M Democrats = 3.62, SD Democrats = .84 vs. M Republicans = 3.94, SD Republicans = .65, t (198) = 2.91, p = .004, d = .43) after the election.

Error bars indicate standard errors.

https://doi.org/10.1371/journal.pone.0197848.g003

Mediation by state self-esteem

We predicted that the effect of political party affiliation on resource allocations after the election would be partially mediated by state self-esteem. In other words, we predicted that being a Democrat would be associated with lower levels of state self-esteem after the election, which would motivate smaller allocations to others depending on whether they were co-partisans or opposing partisans. This is a moderated mediation hypothesis, which we tested using PROCESS Model 14 [ 40 ]. Specifically, we included political party affiliation as the independent variable, state self-esteem as the mediating variable, the amount allocated to others as the dependent variable, and the group composition as a variable moderating the relationship between state self-esteem and the allocation amount. For the sake of analytic parsimony, we created one dummy variable for the conditions where the majority of recipients are out-group members (i.e., two out-group members with one in-group member), so that conditions where the majority of recipients are in-group members (i.e., groups of all in-group members or one out-group member with two in-group members) represent the reference category. Results of the analysis are presented in Table 3 .

https://doi.org/10.1371/journal.pone.0197848.t003

The mediator model showed that Democrats had significantly lower levels of self-esteem than Republicans ( b = -.31, p = .004) after the election. The complete model shows the main effects for political party affiliation (Democrats, on average, allocating marginally more than Republicans, b = 7.42, p = .077), and majority out-group (smaller allocations to groups where the majority are members of the out-group, b = -70.50, p = .001). These effects were qualified by an interaction between state self-esteem and majority out-group ( b = 16.52, p = .003). The results also confirmed a significant conditional indirect effect of political party affiliation on the amount of money allocated to others through state self-esteem when the majority of recipients were out-group members ( b = -3.87, 95% confidence interval -8.41 to -.94), but not when the majority of recipients were in-group members ( b = 1.31, 95% confidence interval -.62 to 4.46). When the majority of recipients were in-group members, state self-esteem did not mediate the effect of political party on allocations; however, when the majority of the recipients were out-group members, participants decreased their allocations as their self-esteem dropped, t (199) = 10.89, p = .009 (see Fig 4 ).

https://doi.org/10.1371/journal.pone.0197848.g004

An additional analysis, using PROCESS Model 3 [ 40 ] to decompose the conditional effect of state self-esteem on allocations for different combinations of political party affiliation and group membership was only significant for Democrats making allocations to groups of majority Republicans ( b = 11.05, SE = 5.10, 95% CI [.98, 21.10]). The conditional effect was not significant for Republicans making allocations to groups of majority Democrats ( b = 12.73, SE = 8.69, 95% CI [-4.41, 29.88]).

Moderation by strength of identification with one’s political party

We further predicted that this moderated mediated effect of political affiliation on the amount allocated after the election would be stronger for Democrats who identify strongly with their political party. In other words, we expected the indirect effect of political party affiliation on the amount allocated to others (through participants’ state self-esteem) would be moderated by not only the composition of the group, but also by the strength of the participant’s identification with his or her political party. Model 18 of Hayes’ PROCESS macro [ 40 ] tests the significance of this indirect effect as a function of dual moderators. It calculates confidence intervals for the conditional indirect effects of group composition and political party identification for each possible combination of these moderators’ values. The results of this model are presented in Table 4 . Although the three-way interaction between state self-esteem, group composition and party identification was not significant ( b = -2.04, p = .63), the conditional indirect effect for political party affiliation was present for groups with a majority of out-group members, when the strength of one’s party identification was 4.5 or higher.

https://doi.org/10.1371/journal.pone.0197848.t004

Finally, we wanted to explore whether the conditional effects of state self-esteem on the amount allocated as a function of strength of party identification differed as a function of individuals’ political party affiliations. We had predicted that the strength of identification would matter more for Democrats after the election than for Republicans.

For ease of interpretation, we ran two separate PROCESS Model 3 analyses, one for Democrats and one for Republicans, to determine if the conditional effect of state self-esteem on allocations as a function of group composition and party identification differed for Democrats and Republicans. For Republicans, allocations did not vary as a function of the strength of their identification with their political party and state self-esteem. However, for Democrats, the conditional effect of state self-esteem on allocations to groups with majority Republicans only held for those at the high end (5.25 and higher) of party identification. These findings confirm that Democrats’ social identities played an important role in how the negative shock of the election ultimately lessened their generosity towards Republicans.

Conclusions

In this research, we provide empirical evidence that how Democrats and Republicans treat others was different before and after the 2016 United States presidential election as a function of political party affiliation. Before the election, Democrats, confident Clinton would be elected, allocated resources equally to others across groups, regardless of whether group members were Democrats or Republicans. In contrast, Republicans, who had reasonable concerns that Trump would lose, showed significant in-group favoritism and allocated more resources to groups where the majority of recipients were in-group members (i.e., Republicans).

After the election, the tables were turned. Democrats reported experiencing significantly higher levels of negative emotions and significantly lower levels of positive emotions than Republicans, as well as significantly higher levels of ego shock and lower levels of state self-esteem. What’s more, after the election, Democrats allocated resources to others differently than they did before the election, demonstrating significant out-group derogation and allocating fewer resources to groups where the majority of recipients were Republicans. Conversely, after the election Republicans behaved more like Democrats had behaved prior to the election, giving equally to others, regardless of their political party affiliation.

We explored the role of state self-esteem as a potential underlying mechanism explaining these findings, in particular focusing on resource allocations after the election. Indeed, individuals (and Democrats in particular) allocated fewer resources to others in groups where the majority of recipients were out-group members as a function of their state self-esteem, suggesting avarice towards the out-group was a reaction to the negative shock of the election. Overall, we believe our findings provide evidence that unexpected outcomes, or shocks, can influence how individuals treat members of their in-group and out-group. Self-esteem interacted with in-group identification and the presence or absence of out-group members to help explain the level of generosity or avarice expressed.

That being said, our results indicate that state self-esteem only partially mediated the effects of election results (or political party affiliation) on allocation to others. Although the direct effect of political party affiliation remained significant, state self-esteem accounted for approximately 18 percent of the direct effect on allocations to others when recipients are majority in-group and 52 percent when recipients are majority out-group, suggesting there are alternative mechanisms that also drive the effects of election results on allocations to others. One additional mechanism that seems likely is the negative affective reaction Democrats experienced in response to the result. Indeed, some Clinton supporters report being afraid or traumatized as a result of the election outcome [ 24 ]. These negative emotions (fear, anger, etc.) could have (along with state self-esteem) contributed to increased hostility towards out-groups on the part of Democrats [ 41 ].

We also acknowledge that employing a two-stage cross-sectional, between-person design rather than a longitudinal, within-person design with the same participants before and after the election, somewhat compromises our ability to make strong inferences about the extent to which the election outcome actually changed how Democrats and Republicans allocated resources to others. Nevertheless, given that participant demographics remained constant across both time periods, we are fairly confident about using our findings to argue that the election outcome contributed to the extent to which Democrats and Republicans showed in-group favoritism and out-group hostility before and after the election.

Finally, by necessity, we focused on one particular type of shock in this paper, and used a somewhat artificial setting in which individuals made decisions about resources independent of context other than political party affiliation. Future research might fruitfully examine the influence of other type of shocks (e.g., peer rejection, failure) in broader contexts requiring more interaction (e.g., social dilemmas, [ 42 ]) to determine if the effect of ego shocks on self-esteem persists in these types of settings. However, the negative affect Democrats feel towards Republicans does not seem to be waning [ 43 ], suggesting that these effects might be longer lasting than anyone might have expected.

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News Use Across Social Media Platforms 2016

Acknowledgments
Methodology
Appendix A: 2013 and 2016 trends

About 6-in-10 Americans get news from social media

A majority of U.S. adults – 62% – get news on social media, and 18% do so often, according to a new survey by Pew Research Center, conducted in association with the John S. and James L. Knight Foundation. In 2012, based on a slightly different question, 49% of U.S. adults reported seeing news on social media. 1

But which social media sites have the largest portion of users getting news there? How many get news on multiple social media sites? And to what degree are these news consumers seeking online news out versus happening upon it while doing other things?

As part of an ongoing examination of social media and news , Pew Research Center analyzed the scope and characteristics of social media news consumers across nine social networking sites. This study is based on a survey conducted Jan. 12-Feb. 8, 2016, with 4,654 members of Pew Research Center’s American Trends Panel.

Reddit, Facebook and Twitter users most likely to get news on each site

News plays a varying role across the social networking sites studied. 2 Two-thirds of Facebook users (66%) get news on the site, nearly six-in-ten Twitter users (59%) get news on Twitter, and seven-in-ten Reddit users get news on that platform. On Tumblr, the figure sits at 31%, while for the other five social networking sites it is true of only about one-fifth or less of their user bases.

It is also useful to see how, when combined with the sites’ total reach, the proportion of users who gets news on each site translates to U.S. adults overall. Facebook is by far the largest social networking site, reaching 67% of U.S. adults. The two-thirds of Facebook users who get news there, then, amount to 44% of the general population. YouTube has the next greatest reach in terms of general usage, at 48% of U.S. adults. But only about a fifth of its users get news there, which amounts to 10% of the adult population. That puts it on par with Twitter, which has a smaller user base (16% of U.S. adults) but a larger portion getting news there.

Social media news use: Facebook leads the pack

The audience overlap

To what extent do the various news audiences on social media overlap? Of those who get news on at least one of the sites, a majority (64%) get news on just one – most commonly Facebook. About a quarter (26%) get news on two of those sites. Just one-in-ten get news on three or more.

Most social media news consumers only get news on one site

Seeking out news online

Differences also emerge in how active or passive each group of news users is in their online news habits more generally. YouTube, Facebook and Instagram news users are more likely to get their news online mostly by chance, when they are online doing other things. Alternatively, the portion of Reddit, Twitter and LinkedIn news users who seek out news online is roughly similar to the portion that happen upon it. 3

Instagram, Facebook and YouTube news users most likely to happen upon news online, but LinkedIn, Twitter and Reddit news users are more evenly divided between news seekers and non-seekers

The demographics of social media news consumers

A look at the demographic characteristics of news consumers on the five social networking sites with the biggest news audiences shows that, while there is some crossover, each site appeals to a somewhat different group. Instagram news consumers stand out from other groups as more likely to be non-white, young and, for all but Facebook, female. LinkedIn news consumers are more likely to have a college degree than news users of the other four platforms; Twitter news users are the second most likely. The demographics of other sites can be found in the Appendix .

Social news consumers and other news platforms

Social media news consumers still get news from a variety of other sources and to a fairly consistent degree across sites. For example, across the five sites with the biggest news audiences, roughly two-in-ten news users of each also get news from nightly network television news; about three-in-ten turn to local TV. One area that saw greater variation was news websites and apps. Roughly half of Twitter and LinkedIn news consumers also get news from news websites and apps, while that is true of one-third of Facebook and YouTube news users.

Social media news consumers access news on a number of other platforms

Changes over time

This report is an update to a 2013 report, with the addition of Snapchat and the removal of three sites: Pinterest, which has been shown to have a small portion of users who use it for news ; Myspace, which has largely transitioned to a music site ; and Google+, which through its recent transformations is being phased out as a social networking site . For the sites analyzed in both 2013 and 2016, a few significant differences emerge.

Of the sites we tracked since 2013, three of eight show an increase in the portion of users who get news there: Facebook, Instagram and LinkedIn. 4

The full 2013-2016 trends for usage and demographics can be found in the Appendix .

In 2012, this was asked over the phone and asked about “seeing” news rather than “getting” news. Additionally, this figure combines items about news on social media generally and news specifically on Twitter. ↩
News consumers for each social networking website are defined as those who answered that they “ever get news or news headlines” on each site. News is defined as “information about events and issues that involve more than just your friends or family.” ↩
While the portion of Reddit news users who get news online because they are looking for it is 13 percentage points higher than the portion of those users that get news while doing other things online, these numbers are not statistically different due to the small number of Reddit news users in the sample. ↩
Twitter’s difference between 2013 and 2016 approaches statistical significance, but does not reach significance with traditional standards. ↩

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Articles in 2016

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Article 19 Dec 2016 Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes The hypothalamus is a brain region rich in functionally segregated neurons.
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PEW RESEARCH CENTER FOR RELEASE JUNE 15, 2016 FOR MEDIA OR OTHER INQUIRIES: Amy Mitchell, Director of Journalism Research Jesse Holcomb, Associate Director of Research Rachel Weisel, Communications Associate 202.419.4372 www.pewresearch.org RECOMMENDED CITATION: Pew Research Center, June, 2016, "State of the News Media 2016"
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Articles in 2016. Filter By: Article Type. All. All; Addendum (1) Article (17) ... Any delays to mitigation or cuts to renewable energy research by the US will likely render the 2 °C target ...