ArticlePDF Available

Burnout contagion: Is it due to early career teachers' social networks or organizational exposure?

Authors:
Running head: BURNOUT CONTAGION 1
Burnout Contagion: Is It Due to Early Career Teachers’
Social Networks or Organizational Exposure?
In K-12 teaching, stress and burnout are serious issues with large numbers of teachers reporting
negative work experiences (Richards, 2012; Skinner & Beers, 2014; Zhang & Sapp, 2008). These issues
have been regarded as serious not only in Western countries including the UK, the U.S.A., Israel,
Australia, Russia, and Germany (Kyriacou, 1987; Rudow, 1999), but also in many Eastern countries,
including Taiwan, Japan, and Hong Kong (see Chang, 2009 for review). Stress and burnout can reduce
teachers’ energy and commitment to their daily responsibilities and increase attrition. While a range of
personal factors can lead to teacher burnout, it is also shaped by teachers’ work experiences. In particular,
current school and policy contexts characterized by reduced budgets, pressure to increase student
achievement under accountability policies, and lack of administrative and parental support all have the
potential to increase teachers’ stress levels and cause burnout (Lambert & McCarthy, 2006; Richards,
2012).
Early career teachers (i.e., those in their first four years of teaching, hereafter ECTs) may be
particularly vulnerable to stress and burnout as they adjust to working full-time and respond to school and
district expectations. Research has documented positive impacts of formal mentoring and induction
programs on first-year teachers (Ingersoll & Strong, 2011), but most teachers in their second, third, and
fourth years are less involved in one-on-one mentoring relationships or structured induction activities.
Instead, such teachers are likely to draw on resources available to them through their relations with close
teacher colleagues (i.e., individuals in their school-based social networks). However, not all relationships
between ECTs and their mentors and/or close colleagues would be beneficial for ECTs. When an ECT’s
colleagues exhibit high levels of burnout themselves, they are less likely to provide the ECT with
sufficient resources in the form of knowledge, curricular materials, time, and emotional assistance. In
addition to social network exposure to burnout, school context can also have an important influence on
ECTs’ burnout levels in that it is representative of the level of resources available in the school. As
proxies for school context, our research focused on organizational exposure to burnout (i.e., the average
BURNOUT CONTAGION 2
burnout level of all teachers at the school who participated in the study) and students’ socio-economic
statuses (SES). The two types of burnout exposures (i.e., social network and organizational exposure to
burnout) depict different aspects of ECTs’ working conditions; the former focuses on ECTs’ direct
interactions with colleagues, while the latter focuses on the attributes of the overall school organization.
In this study, we examined factors associated with the burnout levels of 171 early career teachers
in 10 school districts in Michigan and Indiana. In particular, we drew on Conservation of Resources
(COR) theory and employed multi-level regression and social network analysis to investigate how (a) the
burnout levels of ECTs’ mentors and close colleagues (i.e., social network exposure to burnout), (b)
organizational exposure to burnout, and (c) school socio-economic status (SES) seemed to affect ECTs’
burnout levels.
In the first section of this paper, we review literature on teacher burnout, induction, and retention.
The second section introduces COR theory, social network theory, and explicates our main hypotheses. In
the third section, we describe our sample, measures, and analytical approach. The fourth section presents
our findings. In the fifth section, we discuss our findings in relation to prior research on teacher burnout,
induction, and retention, and address some limitations in our study. In the final section, we consider
implications of our results for preventing teacher burnout.
Teacher Burnout, Induction, and Retention
Teacher Burnout
The term “burnout” was first used by Freudenberger (1974) in a study of volunteers in a free
clinic. Around the same time, Maslach (1976) reported evidence of burnout among human service
workers, based on interview data. Their findings about the symptoms and causes of burnout were
analogous in that both described it as mental and physical exhaustion, and both found that more
enthusiastic and idealistic staff members tended to be more burned out (Zhang & Sapp, 2008; also see
Maslach, 1982; Farber, 1991). These early studies originated in the discipline of psychology, which
regarded burnout as resulting from one’s inability to cope with job stress (Dworkin, Saha, & Hill, 2003).
BURNOUT CONTAGION 3
Beginning in the 1980s, research on burnout became more systematic and was more often based
on empirical data from surveys; many studies featured an established measure of burnout, the Maslach
Burnout Inventory (MBI), developed by Maslach and Jackson (1981). The MBI measures three
dimensions of burnout: emotional exhaustion, depersonalization, and reduced feelings of personal
accomplishment (Maslach & Jackson, 1981). Several researchers investigated teacher burnout in the
1980s and 1990s and most of them used the MBI (Hock, 1988; Iwanicki & Schwab, 1981). In the 1990s,
though, researchers started to attend to the context in which burnout did or could occur, rather than only
focusing on individuals or their work. For example, teachers’ burnout levels were found to be associated
with their relationship with their principal or the principal’s leadership style (Dworkin, 1985; Fernet,
Guay, Senécal, & Austin, 2012; Friedman, 1991), trust levels in their school (Friedman, 1991; Van Maele
& Van Houtte, 2015), and particular types of school culture and environment (Byrne, 1994; Fernet et al.,
2012).
With regard to the definition of burnout, Farber defined burnout as “the final step in a progression
of unsuccessful attempts to cope with negative stress conditions” (1984, p.6). Thus, stress itself does not
lead to burnout; instead, having no means to deal with negative stress in the long term may lead to
burnout. In addition, Farber warned about directly attributing the burnout of teachers in schools with
scarce resources to a “simpl(e) list of its most observable and immediate precipitants . . . for example, the
prevalence of disruptive students” (1984, p.324). In other words, it may be too simplistic to argue that
ECTs in schools with many low-SES students are more likely to be burned out because they have more
exposure to stressful circumstances, without considering the types of resources available to them. As
discussed in the next section, drawing on COR theory, we examine the underlying mechanisms associated
with burnout for teachers whose resources for daily tasks are relatively limited.
In summary, research on teacher burnout was vigorous in 1980s and 1990s, but has received less
attention in the 2000s and 2010s. We argue that this may be due to the emergence of school and teacher
accountability policies over the last 15 years. Under school accountability policies, such as No Child Left
Behind, and teacher evaluation policies, teachers and schools have been expected to focus almost
BURNOUT CONTAGION 4
exclusively on improving students’ achievement scores; teacher burnout and stress have received less
attention. However, teachers’ burnout is closely related to the quality of teachers’ work lives and can have
long-term impacts on students’ learning. Further, current accountability policies are likely to increase
teachers’ burnout levels (Lambert & McCarthy, 2006; Richards, 2012). Thus, within the current policy
context, addressing teachers’ burnout becomes even more important.
Teacher Induction
Early career teachers (ECTs) often encounter significant challenges when they enter the teaching
profession. Despite their limited experience and expertise, ECTs are expected to carry out the same work
responsibilities as experienced teachers, frequently while working in isolation from other educators
(Feiman-Nemser, 2001; Hogan, Rabinowitz, & Craven, 2003; Lortie, 1975; McCormack, Gore, &
Thomas, 2006). These challenges contribute to high levels of burnout and turnover (Allensworth,
Ponisciak, & Mazzeo, 2009; Fisher, 2011) and to ECTs generally being less effective than more
experienced teachers as measured by student achievement data (Boyd, Grossman, Lankford, Loeb, &
Wyckoff, 2006).
In response to these challenges, formal teacher induction programs have attracted considerable
attention from policy makers, researchers, and practitioners. Induction programs represent a bridge
between pre-service teacher preparation and in-service professional development, and they typically
include such activities as “orientation sessions, faculty collaborative periods, meetings with supervisors,
developmental workshops, extra classroom assistance, reduced workloads, and especially mentoring”
(Ingersoll & Strong, 2011, p.203). In particular, mentoring, usually in the form of one-on-one guidance
from an expert veteran teacher, is considered the main part of induction (Feiman-Nemser, 2001; Hobson,
Ashby, Malderez, & Tomlinson, 2009; Ingersoll & Strong, 2011).
Research indicates that induction is beneficial for ECTs in many ways. Based on a review of 15
empirical studies, Ingersoll and Strong concluded that induction has a positive impact on three primary
outcomes: “teacher commitment and retention, teacher classroom instructional practices, and student
achievement” (2011, p.201). Among these studies, though, Glazerman and colleagues’ (2010)
BURNOUT CONTAGION 5
randomized experimental study of comprehensive induction programs found no effect of such programs
on instruction, retention, or student achievement during the participants’ first two years of teaching. In
addition, there has been little research on induction and teacher burnout. One exception is a study by Gold
(1989) in which stress reduction strategies were featured in an induction program. The findings from this
study suggest that such strategies could potentially reduce ECTs’ burnout levels.
Teacher Retention
Turnover, or leaving one’s job, has been considered a typical result of burnout (Goddard &
Goddard, 2006; Maslach et al., 2001). While the attrition rate of newcomers to the teaching profession is
similar to rates in other professions (Harris & Adams, 2007), “several studies have calculated that
between 40 and 50 percent of new teachers leave within the first five years of entry into teaching”
(Ingersoll & Strong, 2011, p.3). Turnover is sometimes due to individual circumstances unrelated to
teachers’ work experiences, such as other professional aspirations, the financial environment, having a
baby, or caring for an adult relative. At the same time, experiences on the job can also strongly affect
teacher retention decisions (Jones & Youngs, 2012; Jones, Youngs, & Frank, 2013; Goddard & Goddard,
2006; Johnson & Birkeland, 2003; Kapadia, Coca, & Easton, 2007).
In addition to turnover leading to teacher shortages and having detrimental effects on student
learning (Ronfeldt, Loeb, & Wyckoff, 2013), it is also costly; for example, it can cost almost $18,000 to
replace each leaver in a very large district, such as Chicago (Barnes & Crowe, 2007). However, it is also
argued that burned out teachers are more likely to remain in the profession rather than leave, given their
limited qualifications for other jobs (Dworkin, 1985); this may be even more problematic than leaving the
profession. To be sure, research on the impact on students of being taught by highly burned out teachers
has produced inconsistent results (Dworkin, 1985; Pas, Bradshaw, Hershfeldt, & Leaf, 2010; Zhang &
Sapp, 2008). But it is clear that experiencing burnout can have detrimental impacts on teachers’ lives; in
particular, burned out teachers can experience physical and mental symptoms of stress (e.g., headaches
and anxiety) that decrease their energy and their commitment to daily tasks (Leiter & Maslach, 2001).
BURNOUT CONTAGION 6
In sum, although teacher burnout, induction, and turnover have often been studied separately in
educational research, they are closely related issues. As newcomers in school organizations, ECTs are
more likely to be exposed to negative stress, due to their lack of expertise and unstable job status (i.e.,
their probationary status). Teacher induction aims to buffer the effects of stress and help ECTs learn how
to deal with negative stress by providing them with psychological and professional support in the areas of
instruction and student behavior management. When these attempts fail to help ECTs to develop their
expertise as teachers, they are likely to become burned out from their work, which might lead to teacher
turnover. That is, teacher turnover can be a result of high burnout levels, which also can be a result of lack
of proper induction. In this study, we focused on how ECTs’ interactions with formal mentors, as a part of
induction, as well as their interactions with close colleagues might affect ECTs’ burnout levels.
Conservation of Resources Theory, Social Network Theory, and Teachers’ Burnout
A prominent theory that addresses the causes of burnout is Conservation of Resources theory
(Hobfoll, 1988). There are three principles of COR theory: (a) primacy of resource loss, (b) resource
investment, and (c) loss and gain spiral. Primacy of resource loss refers to resource loss that is more
salient than the equivalent amount of resource gain while (b) refers to resources invested for protecting,
recovering, and/or gaining other resources and (c) suggests that people who lack resources become more
vulnerable because it is hard for them to obtain more resources and/or protect what they have (Hobfoll,
2001). Resources are defined as “objects, personal characteristics, conditions or energies that are valued
in their own right or that are valued because they act as conduits to the achievement or protection of
valued resources” (Hobfoll, 2001, p.339).
According to COR theory, individuals “obtain, retain, foster, and protect (their) resources”
(Gorgievski & Hobfoll, 2008, p.4), and the loss of resources, the threat of loss of resources, and/or lower
gains by investment can bring about negative stress (Hobfoll, 2001). At the same time, only if one
experiences loss, or the threat of loss, of resources continuously, and/or if their investment of resources
significantly exceeds their actual rewards, is stress likely to lead to burnout (Halbesleben & Buckley,
BURNOUT CONTAGION 7
2004; Hobfoll, 2001). COR theory has been supported by multiple empirical studies (see, e.g., Freedy &
Hobfoll, 1994; Halbesleben & Bowler, 2007; Lee & Ashforth, 1996; Wright & Cropanzano, 1998).
Halbesleben (2006) argued that resources in the workplace seem to have a stronger effect on
emotional exhaustion, whereas non-work-related resources have more impact on the other dimensions of
burnout (i.e., depersonalization and reduced feelings of personal accomplishment). In our study, our data
on ECTs’ social networks is limited to their close teacher colleagues at the same school; i.e., their work-
related resources. Thus, we decided to focus on emotional exhaustion rather than addressing all three
dimensions of burnout. Moreover, as mentioned above, emotional exhaustion has been regarded as the
first stage of the burnout sequence and, as newcomers, ECTs are more likely to experience the initial
stage of burnout rather than the other two dimensions (Maslach et al., 2001). This justified our use of
survey items that mainly focused on emotional exhaustion.
From a theoretical perspective, one might expect having access to resources to lead to reductions
in burnout levels, but results from empirical studies are mixed (Burke & Greenglass, 1996; Halbesleben,
2006; Koniarek & Dudek, 1996). This may be due to the fact that even when individuals have access to
resources through their social relations and perceive them as helpful, the available resources may not be
sufficient to reduce their burnout levels. In addition, most existing studies of resources related to stress
and/or burnout measure them by asking about teachers’ perceptions of the resources available to them.
While burnout can be affected by subjective judgment about one’s own environment, from the
perspective of COR theory, it is important for individuals to actually have access to resources that can
reduce burnout. In this sense, directly measuring the resources to which teachers have access, rather than
measuring perceptions of available resources, can help us better understand the association between
teachers’ burnout and resources in their schools.
One way to conceptualize and empirically measure the actual resources available to teachers in
their schools, such as knowledge about curricular materials, time, and emotional assistance, and how such
resources affect burnout is through social network theory and analysis. Social network theory is
concerned with using scientific methods to study patterns of social relationships within and outside of
BURNOUT CONTAGION 8
organizations (Moolenaar & Daly, 2012). According to Daly and Finnigan, “Social network analysis is a
sytematic approach used to quantify and visualize the ties and overall structure of formal and informal
networks” (2010, p.113). The data for social network analysis (SNA) usually consists of multiple nodes
(i.e., people), ties (i.e., interactions) between those nodes, and the attributes of the nodes. SNA is based on
actual interaction between individuals rather than relying on formal school organizational structures or
individuals’ overall perceptions about their social networks; this allows us to examine how social network
members’ attributes affect a person via social relations.
In our study, it is important to understand COR theory and social network theory in the context of
ECTs’ working environments. As mentioned above, ECTs are more likely to be exposed to negative
stress factors, and they often lack resources needed to meet their daily responsibilities, compared to
veteran teachers. Accordingly, as some studies indicated, teachers who have less experience are more
likely to be burned out (Fisher, 2011). In addition to lack of resources, ECTs are more likely to lack
proper strategies to secure and obtain resources. Schorn and Buchwald (2007) argued that “(a)ccording to
the COR theory, the development of burnout is a consequence of inadequate styles of coping with work-
related stressors” (p. 157). They also showed how different coping styles can shape the burnout levels of
student teachers; student teachers who had a defensive coping style were more likely to be burned out.
Building on this finding, we argue that ECTs can learn how to cope with negative stress factors and to
secure resources from other experienced teachers, and this support is also part of the resources to which
ECTs have access. This is where the social networks of ECTs can play a significant role in their burnout
levels.
For ECTs, their social networks with other teachers including formal mentors and close
colleagues have significant impacts on socialization (Jones et al.,2013 ; Pogodzinski, 2012). Based on this
socialization process, ECTs can acquire resources for fulfilling their responsibilities from other teachers,
such as knowledge of curriculum, lesson materials, and knowledge of students. Moreover, ECTs can learn
about how to secure different types of resources, which is another form of resources for ECTs. For
example, ECTs’ social network members can teach them how to be productive in a short period of time
BURNOUT CONTAGION 9
(i.e., time as a resource) and how to find a right person to answer certain questions (i.e., other teachers’
expertise as a resource). That is, one type of resource can be a springboard for obtaining another type of
resource (i.e., loss and gain spiral) via social networks. In fact, such resources available through ECTs’
school-based social networks are particularly salient for their burnout levels. This is because they
typically have limited access to other kinds of resources and because of the importance of resource loss,
one of COR theory’s main principles: “in the context of resource loss, resource gains become more
important” (Hobfoll, 2001, p.343). Thus, ECTs often need to turn to their colleagues to acquire additional
resources. If such resources are sufficient, ECTs are less likely to be burned out.
Based on our theoretical framework, we posit that mentors’ and close colleagues’ ability to
provide such resources to ECTs will be based on their own burnout levels. If a given mentor or colleague
has a low burnout level, we assume that they have enough resources to carry out their own work
responsibilities and the resources they provide to an ECT will help reduce the ECT’s burnout level. When
an ECT’s mentor and colleagues have sufficient resources to do their own work, the ECT’s attempts to
secure resources from them are likely to be successful and the ECT’s burnout levels would decrease;
otherwise, an ECT who lacks resources might not be able to acquire them and their burnout level is likely
to increase. Thus, ECTs’ burnout levels can be affected by those of their mentors and close colleagues.
In this study, we distinguish between formal mentors and close colleagues, due to their different
roles, even though technically a formal mentor can also be a close colleague. Although both can provide
ECTs with resources, such as curricular materials, instructional expertise, extra time, and emotional
support, formal mentors are usually in positions that officially connect school leaders and ECTs; for
example, they can provide formal/informal evaluations of ECTs to their principals. Moreover, ECTs are
not able to choose their mentors in most cases. On the other hand, ECTs’ close colleagues, as informal
sources of assistance, are usually chosen by ECTs based on common interests, and they would not
formally evaluate ECTs in general. ECTs tend to spend more time interacting with such colleagues and
they seem to learn more about instruction from them (Desimone et al., 2014). Accordingly, we examined
BURNOUT CONTAGION 10
the influence of (a) ECTs’ formal mentors and (b) their close colleagues in different models; it is possible
that these different types of supports influence ECTs’ burnout levels in different ways.
ECTs’ burnout levels can be affected not only by resources directly available from their social
network members, but also by resources available from the broader school context. Poor working
conditions and a lack of resources can worsen teacher burnout levels (Abel & Sewell, 1999; Loeb,
Darling-Hammond, & Luczak, 2005). In this study, we used two proxy measures for working conditions
and available resources: students’ socio-economic status (SES) and ECTs’ organizational exposure to
burnout (i.e., mean teacher burnout levels throughout their schools).
Given that burnout is related to available resources, we assume that ECTs in schools serving
mainly low-SES students are likely to suffer from higher burnout levels. These schools are more likely to
receive extra financial resources through Title 1 or other sources. Title I is a federal program in the
U.S.A. that provides “financial assistance to local educational agencies (LEAs) and schools with high
numbers or high percentages of children from low-income families to help ensure that all children meet
challenging state academic standards” (U.S. Department of Education, n.d.). At the same time, students in
such schools may place greater demands on teachers and other available resources for teachers might still
be insufficient. Also, these schools often face high levels of teacher turnover, which can reduce
opportunities for ECTs to acquire resources from mentors and colleagues, and they typically have an
inadequate physical environment (Muijs, Harris, Chapman, Stoll, & Russ, 2004). Taken together, it is
plausible that schools that serve high percentages of low-SES students may offer fewer resources to
ECTs, which might result in higher ECT burnout levels.
However, student SES does not fully capture the level of available resources for ECTs in a given
school. In particular, it does not represent potential resources such as principal leadership, teachers’
human capital, or overall school climate. In contrast, organizational exposure to burnout (i.e., the mean
burnout level of teachers in each school) captures a more authentic part of the school context that can
impact ECTs’ burnout levels. That is, if an ECT is working in a school where most teachers are burned
out, even if the ECT does not directly interact with such teachers, aspects of the school context that
BURNOUT CONTAGION 11
influenced other teachers might also affect the ECT’s burnout level. That is, organizational exposure to
burnout is less focused on ECTs’ mentors and close colleagues who have direct connections with ECTs
(i.e., social network exposure); instead, it refers to the general level of resources in a given school.
In addition to our main variables of interest, we included several control variables that might
affect ECTs’ burnout levels based on previous studies. Studies have reported significant differences in
burnout levels between females and males (Anderson & Iwanicki, 1984; Lau, Yuen, & Chan, 2005). In
terms of race/ethnicity, although there are few empirical studies about the association between
race/ethnicity and burnout, it may be that racial minorities in school organizations (i.e., non-white
teachers in our sample) might be more isolated and thus may experience higher levels of burnout (Pas et
al., 2010).
Since burnout is related to the ability to complete a task, an ECT’s expertise level can influence
their burnout level. Accordingly, we included two proxies to capture this: their number of years in
teaching, and the amount of professional development they had recently completed. Moreover, ECTs’
professional interaction with their colleagues and their burnout levels themselves can be affected by their
perceptions of their schools as organizations. Given that the constant “threat to lose resources” can lead to
burnout according to COR theory, ECTs’ perceptions about access to resources might be associated with
their burnout levels. While our main focus in this paper is the actual resources available to ECTs
manifested by social network exposure to burnout, we included a measure of ECTs’ self-reported access
to advice and information as a control variable. Similarly, ECTs’ perceptions regarding trust among
teachers in their schools and of their degree of professional fit were included. Professional fit is the
degree to which ECTs’ professional practices, such as their approach to teaching, professional goals, and
identity as a teacher align with those of other teachers at the same school (Jones et al., 2013). In this
study, we included ECTs’ perceptions about their professional fit with other teachers at the school as a
control variable, since a high level of perceived fit can enable ECTs to easily reach out to their colleagues
and it may shape ECTs’ burnout levels as well.
BURNOUT CONTAGION 12
ECTs’ commitment levels can also shape their experiences as teachers; an ECT who does not
want to remain in their teaching position much longer may be less likely to ask other colleagues for
assistance, which possibly affects their burnout levels. Following Pogodzinski, Youngs, Frank, and
Belman (2012), we conceptualized commitment as individuals’ intention to remain at their school,
district, and/or grade level. To be sure, while turnover is a potential outcome of commitment, they are
different concepts. Commitment represents a teacher’s motivation to work at their current position; low
commitment does not necessarily mean that a teacher will leave their school. We included commitment as
a control variable that represents a teacher’s characteristic that might shape both their interaction with
other teachers at the same school and their burnout level. In addition, we included school level (i.e.,
whether an ECT works at an elementary school or a middle school) as a school-level control variable,
given that the nature of school organizations and/or working environments for elementary school teachers
might differ from those of middle school teachers.
In this paper, we drew on data from a larger project, the MIECT (Michigan Indiana Early Career
Teacher) study. We used a social network influence model with multi-level regression to examine the
impact of social networks on ECTs’ burnout levels and to consider the effect of organizational exposure
to burnout on their burnout levels. This study focused on the emotional exhaustion component of burnout;
ECTs answered survey items asking about their job manageability and emotional and physical exhaustion
at time 1 and 2. As mentioned above, although emotional exhaustion is only one component of burnout,
all three aspects of burnout are closely related to each other, and emotional exhaustion is the first stage of
burnout. We conceptualized social network exposure as the mean of the burnout levels of ECTs’ formal
mentors and close colleagues at time 1, while organizational exposure was conceptualized as the mean
burnout level of all the teachers at a given school who participated in the study.
Method
Sample
The data collection for the larger MIECT study occurred in five Michigan districts and five
Indiana districts in 2007-2008 and 2008-2009. The analysis in this paper focuses on the fall 2008 and
BURNOUT CONTAGION 13
spring 2009 data for the ECTs, and on the winter 2009 data for the nominated teachers. The goal was to
recruit medium-to-large districts in both states that (a) served varying student populations with regard to
SES and race/ethnicity and (b) had at least 10 full-time teachers in core content areas (i.e., mathematics,
science, social studies, English/
language arts, and elementary general education) in grades 1-8 in their first 4 years of the profession
(Pogodzinski et al., 2012). In the 10 districts, ECTs in 99 schools were invited to participate in the study.
In fall 2008 survey, a survey item asked about their close colleagues and mentors. Based on this data, the
research team contacted experienced teachers working at the same school with ECTs. The number of
ECTs included in our analysis was 171 (about 60% were elementary school teachers and 40% were
middle school teachers), and the number of participating experienced teachers, including ECTs’ mentors
and other colleagues, was 289 in 84 schools.1 A total of 226 ECTs, including elementary and middle
school teachers, completed surveys in both fall 2008 and spring 2009, but 55 ECTs were excluded due to
missing social network data. The main reason that social network data was missing was because for some
ECTs, none of the teachers they nominated completed a survey for the study. There were no significant
differences between the 171 ECTs who were included and the 55 ECTs who were excluded from the
analysis with regard to teacher background (i.e., gender, school level, year of teaching, race/ethnicity) or
burnout level at time 1 or time 2. Since burnout may be a sensitive issue for teachers, we maintained the
confidentiality of the responses by de-identifying teachers and storing the survey data in a secure location.
This study includes elementary and middle school general education teachers in grades 1-8. Table
1 offers descriptive statistics for the schools and the ECTs’ characteristics. School characteristics were
obtained from the Common Core of Data for the 2009-2010 school year. While the data for this study
were collected a few years ago (i.e., in 2008-09), they were collected after the enactment of intensive
high-stakes testing and accountability policies (i.e., No Child Left Behind). Thus, ECTs in 2016-17 are
likely teaching in similar work environments as those who were ECTs in 2008-09.
Due to limitations in our data, the analysis excludes the ECTs’ principals from their social
networks. By including ECTs’ time 1 burnout level as a control variable, we were able to control for
BURNOUT CONTAGION 14
unobserved factors that could potentially bias our analysis, such as attributes of individual ECTs and their
schools. In addition to this pre-measure of burnout, we included four categories of control variables at the
individual ECT level: their demographic background, their level of teaching experience, their perceptions
about their school organization, and their commitment level to the profession.
(Insert Table 1 here)
Measures
Dependent variable. The dependent variable that we examined in each of the models was ECTs’
burnout level at time 2. In order to test the unidimensionality and reliability of the burnout variable that
we used for ECTs and their mentors and colleagues, we did exploratory factor analysis for the nine
burnout items in the survey, and we found only one significant factor (α=0.9114, eigenvalue= 5.01). After
conducting factor analysis, we took the mean of all nine items in the fall 2008 and spring 2009 surveys.
The survey items are same across two surveys.
Independent variable. In the fall 2008 survey, ECTs were asked to list their formal mentors (if
applicable) and up to eight of their close colleagues. They were also asked to indicate how frequently they
talked with each of these individuals about various instructional and other work-related issues (i.e., every
day, 3 to 4 times per week, 1 to 2 times per week, 1 to 3 times per month, or less than once a month).
Following Frank, Zhao, and Borman (2004), we calculated the resources that ECTs were able to access
based on their interactions with mentors and colleagues (i.e., dummy variable equal to 1 if an ECT
nominated a given teacher) multiplied by the nominated teachers’ burnout levels (as reported by mentors
and colleagues on surveys). Then, we used the average to account for differences in the number of
nominated teachers and missing values for nominated teachers across ECTs.2 This represented the term
for social network exposure to burnout. In the same way, we calculated this social network exposure for
(a) both mentors and close colleagues, (b) only formal mentors, and (c) only close colleagues.
One of the main concerns of this paper is whether different school context impact ECTs’ burnout
levels in different ways. We examined this question in a few ways. First, we used the percentage of
students eligible for free- or reduced-price lunch as a proxy for the fiscal resources available at each
BURNOUT CONTAGION 15
school. Using the percentage of racial/ethnic minority students in the school as a proxy for fiscal
resources did not produce any significant changes in our results. Second, we included ECTs’
organizational exposure to burnout. This variable was calculated by taking the mean of all participating
teachers’ burnout levels in the same school in our sample; this included the focal ECT, the focal ECT’s
mentor/colleagues, other ECTs at the school, and mentors/colleagues who were nominated by other
ECTs. Since this study featured egocentric social network data, we did not collect data on the burnout
levels of those teachers who were not nominated by the ECTs participating in our study.
While our measures of social network exposure to burnout and organizational exposure to
burnout are similar conceptually, in terms of the level of analysis, ECTs’ social network exposure to
burnout is at the individual level and organizational exposure to burnout is at the school level; we applied
this distinction in our analysis. Also, organizational exposure to burnout is a broader construct than direct
social network influence because burnout exposure through social network members is also included in
the organizational exposure construct as a measure of each ECT’s organizational exposure. While
organizational exposure to burnout assumes that ECTs are affected by direct interaction (similar to social
network exposure), it also focuses on how the broader school context affects ECTs’ burnout levels. This
paper examines the relationship between these two different types of exposure and ECT burnout.
Control variables. We included the time 1 burnout levels of ECTs in the models to control for
various confounding variables, such as individual ECTs’ attributes and school settings that ECTs had
experienced before they completed the survey (fall, 2008), which potentially affected their burnout levels
at time 2. All control variables were obtained from the fall 2008 ECT survey.
The professional development that ECTs completed was measured by taking the mean of 10
items for elementary school ECTs and 7 items for middle school ECTs in the fall 2008 survey about how
many hours they had spent on professional development in various areas. ECTs’ perceptions about their
access to resources were calculated based on the mean of 10 items for elementary school ECTs and the
mean of 7 items for middle school ECTs in the fall 2008 survey (α=0.9574, eigenvalue= 5.1053 with one
significant factor). Professional fit was calculated by taking the mean of six survey items (α= 0.8573,
BURNOUT CONTAGION 16
eigenvalue=3.0693 with one significant factor) and ECTs’ perceptions of trust among teachers were
calculated based on the mean of four items (α=0.8397, eigenvalue= 2.283 with one significant factor).
ECTs’ commitment level was calculated by taking the mean of six items about their future career plans in
the fall 2008 survey (α= 0.8749, eigenvalue= 3.3839 with one significant factor). See Table 2 for details
about how each variable was measured.
Analytic Approach
To examine the relationship between ECTs’ burnout levels and (a) their social network exposure
to burnout and (b) their broader school context, we first estimated separate models for each independent
variable (i.e., ECTs’ social network exposure to burnout, percentage of students eligible for free/reduced
lunch, and organizational exposure to burnout) and then included these variables together in the models.
Since teachers were (a) nested within schools and (b) not independent of each other, we used Hierarchical
Linear Modeling (HLM) for two-level models (Raudenbush & Bryk, 2002). Based on our analysis of the
unconditional model, about 22.95% of the variance in ECTs’ burnout levels at time 2 was at the school
level (i.e., level 2) and it was statistically significant (p=0.001); this justified the use of a two-level HLM
(Raudenbush & Bryk, 2002). Further, 19.34% of the variance in ECTs’ burnout levels at time 1 was at the
school level and it was also significant (p=0.006). While this is a small difference, it can be argued that
the variance in ECTs’ burnout levels at the school level was larger at time 2 than time 1.
The basic models for our research questions are as follows:
1) Social network exposure to burnout
Level 1: Yij = β0j + β1jLagged_Yij + β2j{(1/n
i'=1
n
wii ' Y
i’j} + β3j(Fit)ij + β4j(Access)ij + β5j(Trust) ij
+ β6j(PD) ij + β7j(Commitment) ij + Xijγ + eij
Level 2: β 0j = γ00 + γ01(School level)0j + γ02(% of FRL eligible students)0j + μ0j
Where β0j is a school specific intercept, and Yij and Lagged_Yij is a burnout level of teacher i in a
school j at spring 2009 and at fall 2008, respectively. wii’ is a vector consisting of dummies equal to 1 if
there is an interaction between early career teacher i and mentors or close colleagues i’ in school j. Yi’j is
BURNOUT CONTAGION 17
the burnout level of an ECT’s close colleague or mentor at winter 2009. Fitij is an ECT’s perceptions
about the professional fit with other teachers at the same school, and Accessij is an ECT’s perceptions
about whether they have access to their mentors and close colleagues for information and advice. Trust ij
represents an ECT’s perceptions about trust among teachers at the same school, and PDij is hours that an
ECT spent on district induction and professional development. Commitment ij is an ECT’s future career
plan, and a high value for commitment indicates that the ECT plans to stay in their current position
longer. The vector X contains ECTs’ background characteristics, such as race/ethnicity, gender, and year
of teaching. eij is a teacher specific error term. Level 2 is at the school level, and School level (i.e., an
indicator whether a school is an elementary school) and Percentage of free- and reduced-price lunch
eligible students are included as school-level control variables. μ0j is a 2nd level variance.
2) Organizational exposure to burnout
Level 1: Yij = β0j + β1j(Fit)ij + β2j(Access)ij + β3j(Trust) ij + β4j(PD) ij + β5j(Commitment) ij + Xijγ + eij
Level 2: β 0j=γ00 + γ01(School level)0j + γ02(% of FRL eligible students)0j + γ03(Organizational exposure to
burnout)0j + μ0j
This model is the same as the previous model except that Organizational exposure to burnout0j is included
at the 2nd level, instead of social network exposure at the individual teacher level.
The issue of multicollinearity was potentially significant because we used some of the same data
to calculate different variables. For instance, ECTs’ burnout levels at time 1 and social network members’
burnout levels were used to calculate organizational exposure to burnout. Based on the correlation
coefficients, organizational exposure to burnout was highly correlated with ECT time 1 burnout and
moderately correlated with social network exposure (Table 3). To avoid bias based on multicollinearity,
we employed different strategies for each variable: (a) we excluded burnout at time 1 in the model
examining organizational exposure; and (b) in terms of organizational exposure and social network
exposure, we included organizational exposure as a school-level variable and social network exposure as
a group mean-centered variable at the individual teacher level. Given the structure of the data, it is hard to
BURNOUT CONTAGION 18
completely distinguish the impact of social network exposure from that of organizational exposure, but
this approach enabled us to compare the impact of these two variables.
In addition, when accounting for missing values in the current research design, 26% of the ECTs
in our sample were the only ECTs at their schools. Thus, we excluded those cases for the models that
compared the influence of social network exposure to burnout and organizational exposure to burnout.
(Insert Tables 2 and 3 here)
Results
The main analysis for this study focuses on the associations between (a) social network exposure
to burnout and (b) aspects of school context (i.e., organizational exposure and students’ SES status) and
ECTs’ burnout levels. We first predicted ECTs’ time 2 burnout levels using those of their mentors and
close colleagues, after controlling for their burnout levels at time 1, commitment levels, demographic
backgrounds, expertise levels, school levels, and perceptions about their schools as organizations. Next,
for the research question about school context and ECTs’ burnout, we included the percentages of
students eligible for free- or reduced-price lunch at their schools. Since it is possible that ECTs in
different school settings can be affected by their social networks differently, we included a term for the
interaction between ECTs’ social networks and the percentage of students eligible for free/reduced lunch
at their schools. Although we applied different specifications for this interaction term, it was not
statistically significant in any model; therefore, we do not report the results here. As the next step, we
included organizational exposure to burnout in the model; we excluded ECTs’ burnout levels at time 1
because there was a multicollinearity issue when we included this variable. In the final model, we
included both social network exposure to burnout (group-mean centered) along with organizational
exposure to burnout. Table 4 summarizes the results from the analysis.
Based on the result from the model 1, ECTs’ burnout levels seem to have a positive and
statistically significant association with the social network exposure term, which was calculated by taking
the mean of their mentors’ and close colleagues’ burnout levels, holding other variables constant. This
means that when ECTs had mentors and colleagues with higher burnout levels, they were more likely to
BURNOUT CONTAGION 19
be more burned out at time 2, while ECTs who had mentors or colleagues who were less burned out were
less likely to be burned out at time 2. Holding other variables constant, a one-unit increase in the mean of
social network members’ burnout levels is associated with a 0.21-unit increase in ECTs’ burnout levels,
which is more than one-third of a standard deviation in ECTs’ burnout level at time 2, which is 0.58. In
terms of control variables, none of the variables had a significant association with ECTs’ burnout levels at
time 2 in any of the models. Compared with the level-1 variance in the unconditional model, 31.29% of
the level-1 variance in ECTs’ burnout at time 2 was accounted for by the teacher-level variables in model
1. In terms of level-2 variance, including a single level-2 variable, the dummy variable for elementary
school, reduced it almost to zero.
In models 2 and 3, we separated our sample into two groups to compare the potential influence of
mentors and close colleagues on ECTs’ burnout levels. We found that formal mentors’ burnout levels do
not seem to have any impact, whereas close colleagues’ burnout levels have a significant positive
association with ECTs’ burnout levels. In fact, the effect of close colleagues here is almost identical to
what we found in model 1, which includes all social network types. However, we need to be cautious in
interpreting these results because (a) model 2 has a small sample size compared to the other models, and
(b) as mentioned earlier, as ECTs acquire more experience in teaching, they are less likely to be assigned
to formal mentors. Thus, although it is hard to conclude that mentors are less influential for ECTs’
burnout based on this result, the results indicate that the influence of formal mentors and close colleagues
on ECTs’ professional lives may differ in some aspects.
In terms of school contextual factors, model 4 confirmed that the percentage of students eligible
for free/reduced lunch in the ECTs’ schools had a statistically significant and positive association with
ECTs’ burnout levels at time 2. A 10-percent increase in the ratio of students eligible for free/reduced
price lunch was associated with a 0.046-unit increase in ECTs’ burnout levels. Given that we had already
controlled for ECTs’ burnout levels at time 1 and the school context was not expected to change
throughout the school year, this finding indicates that as the school year goes by, ECTs in low-SES
schools were more likely to encounter situations that worsened their burnout levels than their counterparts
BURNOUT CONTAGION 20
in high-SES schools. Even after including the percentage of students eligible for free/reduced lunch in the
school in the model, the effect of social network exposure was still significant. However, as mentioned
above, an interaction term between social network exposure and percentage of free/reduced lunch eligible
students was not significant with any specifications. Taken together, the burnout levels of ECTs at the end
of the school year seem to be affected by their social networks, and those in schools serving higher
percentages of low-SES students were more likely to be burned out, but the impact of the ECTs’ social
networks did not vary across different schools. That is, although students’ SES might be related to ECTs’
burnout levels, it does not seem related to how social network exposure to burnout affects ECTs’ burnout
levels.
In models 5 and 6, we included a term for organizational exposure to burnout; these models
excluded ECTs who were the only ECTs in their schools who participated in the MIECT study (n=46),
since their social network exposure to burnout and their organizational exposure to burnout were
identical. We did this in order to compare social network exposure to burnout and organizational
exposure to burnout. There was an issue, however, involving multicollinearity among the multiple
burnout variables. Thus, for model 5, we did not include ECT burnout level at time 1. In model 5, one-
unit increase in the mean burnout level of other teachers at the same school was associated with a 0.9-unit
increase in ECTs’ burnout level at time 2, which is about two standard deviations of ECTs’ burnout at
time 2 (p≤0.001). In model 5, the Intraclass Correlation Coefficient (ICC) was almost zero, which means
that organizational exposure at the school level along with the ECT’s school level (i.e., elementary or
middle school) could explain most of the level-2 variance. Interestingly, when we included organizational
exposure, the ratio of students eligible for free/reduced price lunch was no longer statistically significant.
This might indicate that organizational exposure, which is a measure of other teachers’ burnout levels in
the same building, is a better measure of the working environment, with regard to ECTs’ burnout levels,
than students’ SES.
In the final model (model 6), we included both social network exposure and organizational
exposure in the same model in order to compare the impact of these two variables on ECTs’ burnout
BURNOUT CONTAGION 21
levels; in order to avoid an issue with multicollinearity, we included organizational exposure as a level-2
variable and social network exposure as a group mean-centered variable at the teacher level. While group-
mean centered social network exposure was not significant and the estimated coefficient was close to
zero, school-level organizational exposure to burnout had a significant and positive association with
ECTs’ burnout levels. The results from model 6 are almost identical to those from model 5, which means
that after controlling for school-level organizational exposure to burnout, the impact of an individual
teacher’s social network exposure is not influential. Again, we do not have data on all teachers’ burnout
levels in each school and the organizational exposure term was a less inclusive measure. At the same
time, this result indicated that the broader school context in which ECTs work might be a more powerful
predictor of their burnout levels than their direct social network exposure to burnout.
(Insert Table 4 here)
Discussion
This paper examined the burnout levels of early career teachers in light of their social networks
and school context. Drawing on longitudinal survey data, we first examined the influence the burnout
levels of formal mentors and close colleagues on ECTs’ burnout levels. We then focused on school
context: students’ SES status and organizational exposure to burnout. Finally, we compared the two types
of exposure to burnout — social network exposure and organizational exposure. Among our six models,
we found the strongest association between ECTs’ organizational exposure to burnout and their burnout
levels at time 2 (i.e., their burnout levels at the end of the school year). Although the measure of
organizational exposure to burnout was an imperfect proxy and it is hard to completely separate it from
social network exposure, this might mean that the burnout levels of ECTs are shaped by the level of
resources in each school manifested by other teachers’ burnout levels. Although ECTs who worked at
schools serving mostly low-SES students tended to be more burned out, after including organizational
exposure to burnout in the model, students’ SES levels no longer had a significant effect on ECTs’
burnout. Although the magnitude was weaker, ECTs’ social network exposure to burnout also had a
significant positive impact on their burnout levels at time 2 even after controlling for ECTs’ burnout
BURNOUT CONTAGION 22
level at time 1. In addition, our results indicate that compared to formal mentors, close colleagues that
ECTs sought out for assistance had more influence on their burnout levels.
Our results about the influence of mentors and close colleagues on ECTs are consistent with a
large body of literature on mentoring and induction for ECTs; ECTs’ relationships with their mentors and
colleagues shape their experience as teachers (Jones et al., 2013; Kapadia et al., 2007; Smith & Ingersoll,
2004). At the same time, our study builds on findings from these studies in two ways. First, we found that
not all mentors and close colleagues were capable of providing proper assistance to ECTs. Our results
show that experienced teachers who were already burned out by their own work might have been less
helpful to ECTs. Second, our findings indicate that the burnout levels of ECTs’ close colleagues may be
more consequential for ECTs than those of their mentors. This suggests the need for future studies of
ECTs to include data on other members of their social networks, not just their formal mentors.
Contagious burnout is not a new argument and our result regarding social exposure to burnout is
consistent with existing literature (Bakker & Schaufeli, 2000; Maslach et al., 2001): teachers who
communicated with burned out colleagues were more likely themselves to become burned out over time.
However, we built on prior research on contagious burnout in two ways. First, we employed a social
network influence model to measure ECTs’ colleagues’ influence on their burnout levels. We collected
survey data directly from colleagues nominated by ECTs; this contrasts with previous research (Bakker &
Schaufeli, 2000) that asked participants about their colleagues’ burnout levels, which potentially
introduces bias. Second, we drew on Conservation of Resources theory, which provides an account of
how burnout contagion occurs. Previously, it was explained in two ways: “emotional contagion” (i.e.,
unconscious mimicking of the feelings of another person) and a cognitive process that involves “tuning in
to the emotions of others” (Bakker & Schaufeli, 2000, p.2291). Although these explanations account for
burnout contagion throughout ECTs’ social networks, they are not applicable to burnout contagion that
arises without close social interaction.
On the other hand, Conservation of Resources theory provides a plausible explanation for the
results. Organizational exposure to burnout represents the resources available to teachers in each school.
BURNOUT CONTAGION 23
That is, if teachers in a school were generally burned out, this would mean that the school failed to
provide them with enough resources to fulfill their responsibilities. ECTs in such schools can be affected
by such a situation as the school year goes by. In contrast to another index for capturing school context,
students’ SES, organizational exposure to burnout may reflect a more comprehensive and authentic
measure of available resources. Our finding of a strong association between organizational exposure and
ECTs’ burnout levels implies that the burnout contagion that we observed might be a product of the level
of available resources at each school, rather than a result of ECTs mimicking others’ feelings or tuning
into the emotions of others.
Although our main focus has been ECTs’ social network exposure and school context, it is
worthwhile to note that ECTs’ perceptions about their school organization, such as organizational fit,
perceptions of access to resources, trust, and other individual factors, including their self-reported
commitment and expertise levels, did not have any significant association with ECTs’ burnout level at
time 2. Given that ECTs’ burnout levels at time 1 had a significant negative association with ECTs’
perceptions regarding trust, commitment, and fit, including the time 1 burnout level might absorb the
effects of these variables on ECTs’ burnout level at time 2. However, these variables did not have
significant effects in models 5 or 6 either, which did not include burnout level at time 1. This indicates
that organizational exposure might be more relevant to ECTs’ burnout compared to their perceptions
about the school organization, their commitment level, or their expertise level. This result accords well
with the recent literature on burnout that focuses on the environment surrounding a person, rather than the
person herself or the work itself (Fernet et al., 2012; Van Maele & Van Houtte, 2015).
There are several limitations associated with this study with regard to establishing causal
inference. First, we cannot completely rule out possible selection effects of social network exposure. That
is, if ECTs selected their colleagues based on their burnout levels, the significant association between
ECTs’ burnout levels and social exposure that we have reported here could result from their selection
process rather than social network influence. Given the nature of our data, which features egocentric
social network data at one time point, it is not possible to determine whether there were indeed selection
BURNOUT CONTAGION 24
effects on ECTs’ burnout levels. In this sense, future studies using teachers’ burnout data and sociocentric
network data at multiple time points could be fruitful as ECTs may obtain and utilize information about
other teachers’ burnout levels in selecting colleagues and their burnout levels may be associated with such
a selection process. In this study, we included ECTs’ time 1 burnout levels to control for various
unobservable attributes and it is plausible that including this pre-measure could account for some
selection effects.
Second, as noted earlier, we did not collect data from all of the teachers at every school. Only
ECTs and teachers nominated by ECTs were invited to complete surveys. Accordingly, in terms of
calculating organizational exposure to burnout, it is not clear whether teachers who participated in this
study were representative of their entire schools. To be sure, colleagues nominated by ECTs represent the
part of the school organization to which ECTs have direct access, but it is not clear whether they are
indeed representative of the entire school organization. If ECTs and their colleagues are isolated from
other members of a school organization and this isolation is related to their burnout levels, our results
regarding organizational exposure to burnout may be less convincing. However, it was not possible to
assess this with the current research design. On a related note, network autocorrelation may also be an
issue [see Appendix A].
Implications
This study builds on existing studies on the effects of mentoring and induction on early career
teachers, the impact of social networks on teachers, and burnout contagion; we found that ECTs’ burnout
can be shaped by how other teachers throughout their school feel about their professional lives as well as
with whom they interact. These findings have implications for practice.
First, various types of supports for teachers to prevent their burnout need to be considered at the
school level. As shown in this paper, burnout is not only a matter of individual attributes; the context of
each school matters for teachers’ burnout levels. Therefore, it would be more effective to provide
resources for teachers at the school level, rather than asking individual teachers to address this issue by
themselves, especially in schools that serve many low-SES students. While schools serving low-SES
BURNOUT CONTAGION 25
students often receive additional financial assistance often through Title I, our results suggest that the
current financial aid for such schools might not be sufficient to help them reduce teacher burnout. Given
the negative impact of burnout on teachers and potentially on students, this discrepancy in burnout levels
can be a factor that widens or maintains the gap between high- and low-SES students’ learning. Also,
highly burned out teachers are more likely to leave their schools (Maslach et al., 2001).
More importantly, without improved school resources, new teachers who move into open
positions would also be likely to experience increased burned out as time goes by. After becoming burned
out, these new teachers would leave their schools as well. That is, schools that lack resources might be
trapped in a vicious cycle of burnout and turnover, which is clearly harmful for students’ learning. Thus,
providing additional resources for teachers working at those schools, such as physical materials, assistant
teachers, professional development, and preparation time, is critical not only for reducing teacher burnout
itself, but also for closing gaps in students’ learning. In addition to allocating more resources, principal
leadership can be a key for teachers’ burnout levels at each school. When a principal creates an
empowering environment for teachers, they are more likely to be motivated to do their work and have
lower stress levels (Davis & Wilson, 2000). Thus, it is important for principals to be aware of teacher
burnout and make an effort to create a school climate that reduces the likelihood of burnout.
Second, given the importance of mentors and close colleagues for ECTs, principals and districts
need to pay close attention to teachers who have direct contact with ECTs (Jones et al., 2013; Kapadia et
al., 2007; Smith & Ingersoll, 2004). To be sure, it is difficult to shape teachers’ actual social networks.
However, research has found that grade-level assignment and formal organizational assignment are strong
predictors of the formation of teacher ties (Jones & Youngs, 2012). Moreover, ECTs usually have few
relationships with other teachers in their schools when they first enter, so they often depend on
relationships assigned by the formal organization. Thus, more attention needs to be paid to ECTs’
assigned mentors, teachers in their grade levels or subject areas, and teachers whose classrooms are next
door to ECTs’ classrooms, including attention to these educators’ own burnout levels and their capacity
for assisting ECTs.
BURNOUT CONTAGION 26
Various factors can be considered in choosing teachers for such a pool of ECTs’ colleagues.
However, based on our results, one important criterion should be the burnout level of those teachers. Less
burned out teachers typically have more resources (i.e., time, information, knowledge, and physical
resources) for their own work as well as for helping ECTs. Given the detrimental effects of teachers’
burnout, experienced teachers’ burnout levels should not be ignored when principals or district
administrators assign mentor teachers to ECTs or form the organizational structure for a school.
BURNOUT CONTAGION 27
References
Abel, M. H., & Sewell, J. (1999). Stress and burnout in rural and urban secondary school teachers.
Journal of Educational Research, 92(5), 287–293.
Allensworth, E., Ponisciak, S., & Mazzeo, C. (2009). The schools teachers leave: Teacher mobility in
Chicago Public Schools. Chicago: Consortium on Chicago School Research.
Allison, P. D. (1990). Change scores as dependent variables in regression analysis. Sociological
Methodology, 20(1), 93-114.
Author. (2004).
Author. (2012a).
Author. (2012b).
Author. (2013).
Bakker, A. B., & Schaufeli, W. B. (2000). Burnout contagion processes among teachers. Journal of
Applied Social Psychology, 30(11), 2289–2308.
Barnes, G., Crowe, E., & Schaefer, B. (2007). The cost of teacher turnover in five school districts: A pilot
study. Washington, DC: National Commission on Teaching and America's Future.
Boyd, D., Grossman, P., Lankford, H., Loeb, S., Wyckoff, J. (2006). How changes in entry requirements
alter the teacher workforce and affect student achievement. Education Finance and Policy,
1(2),176-216.
Burke, R. J., & Greenglass, E. (1996). Work stress, social support, psychological burnout and emotional
and physical well-being among teachers. Psychology, Health & Medicine, 1(2), 193–205.
Byrne, B. M. (1994). Burnout: Testing for the validity, replication, and invariance of causal structure
across elementary, intermediate, and secondary teachers. American Educational Research
Journal, 31(3), 645–673.
Chang, M.-L. (2009). An appraisal perspective of teacher burnout: Examining the emotional
work of teachers. Educational Psychology Review, 21(3), 193–218.
BURNOUT CONTAGION 28
Daly, A. J., & Finnigan, K. S. (2011). The ebb and flow of social network ties between district leaders
under high stakes accountability. American Educational Research Journal, 48(1), 39–79.
Davis, J., & Wilson, S. M. (2000). Principals' efforts to empower teachers: Effects on teacher motivation
and job satisfaction and stress. The Clearing House, 73(6), 349-353.
Desimone, L. M., Hochberg, E. D., Porter, A. C., Polikoff, M. S., Schwartz, R., & Johnson, L. J. (2014).
Formal and informal mentoring: Complementary, compensatory, or consistent? Journal of
Teacher Education, 65(2), 88–110.
Doreian, P. (1989). Network autocorrelation models: Problems and prospects. In D. A. Griffith (Ed.),
Spatial statistics: Past, present and future (pp. 369-389). Ann Arbor, MI: Institute of
Mathematical Geography.
Dow, M. M., Burton, M. L., & White, D. R. (1982). Network autocorrelation: A simulation study of a
foundational problem in regression and survey research. Social Networks, 4(2), 169-200.
Dworkin, A. G. (1985). When teachers give up: Teacher burnout, teacher turnover, and their impact
on children. Austin, TX: Hogg Foundation for Mental Health and Texas Press. (ERIC Document
Reproduction Service No ED 273575)
Dworkin, A. G., Saha, L. J., & Hill, A. N. (2003). Teacher burnout and perceptions of a democratic
school environment. International Education Journal, 4(2), 108-120.
Farber, B. A. (1984). Teacher burnout: Assumptions, myths, and issues. Teachers College Record, 86(2),
321–338.
Farber, B. A. (1991). Crisis in education: Stress and burnout in the American teacher. San Francisco:
Jossey-Bass.
Feiman-Nemser, S. (2001). From preparation to practice: Designing a continuum to strengthen and
sustain teaching. Teachers College Record, 103 (6), 1013-1055.
Fernet, C., Guay, F., Senécal, C., & Austin, S. (2012). Predicting intra-individual changes in teacher
burnout: The role of perceived school environment and motivational factors. Teaching and
Teacher Education, 28(4), 514–525.
BURNOUT CONTAGION 29
Fisher, M. H. (2011). Factors influencing stress, burnout, and retention of secondary teachers. Current
Issues in Education, 14(1). Retrieved from http://cie.asu.edu/
Frank, K. A., Zhao, Y., & Borman, K. (2004). Social capital and the diusion of innovations
within organizations: The case of computer technology in schools.
Sociology of Education, 77(2), 148e171.
Freedy, J. R., & Hobfoll, S. E. (1994). Stress inoculation for reduction of burnout: A conservation of
resources approach. Anxiety, Stress & Coping, 6(4), 311–325.
Friedman, I. A. (1991). High and low-burnout schools: School culture aspects of teacher burnout.
Journal of Educational Research, 84(6), 325-333.
Freudenberger, H. J. (1974). Staff burn-out. Journal of Social Issues, 30(1), 159–165.
Glazerman, S., Isenberg, E., Dolfin, S., Bleeker, M., Johnson, A., Grider, M., Jacobus, M., & Ali, M.
(2010). Impacts of comprehensive teacher induction: Final results from a randomized controlled
study. Washington, DC: U.S Department of Education, Institute of Education Sciences.
Goddard, R., & Goddard, M. (2006). Beginning teacher burnout in Queensland schools: Associations
with serious intentions to leave. Australian Educational Researcher, 33(2), 61–75.
Gold, Y. (1989). Reducing stress and burnout through induction programs. Action in Teacher Education,
11(3), 66–70.
Gorgievski, M. J., & Hobfoll, S. E. (2008). Work can burn us out or fire us up: Conservation of resources
in burnout and engagement. In J. R. B. Halbesleben (Ed.), Handbook of stress and burnout in
health care (pp. 7–22). Hauppauge, NY: Nova Science.
Halbesleben, J. R. B. (2006). Sources of social support and burnout: A meta-analytic test of the
Conservation of Resources model. Journal of Applied Psychology, 91(5), 1134–1145.
Halbesleben, J. R. B., & Bowler, W. M. (2007). Emotional exhaustion and job performance: The
mediating role of motivation. Journal of Applied Psychology, 92(1), 93–106.
Halbesleben, J. R. B., & Buckley, M. R. (2004). Burnout in organizational life. Journal of Management,
30(6), 859–879.
BURNOUT CONTAGION 30
Harris, D. N., & Adams, S. J. (2007). Understanding the level and causes of teacher turnover: A
comparison with other professions. Economics of Education Review, 26(3), 325-337.
Hobfoll, S. E. (1988). The ecology of stress. New York: Hemisphere.
Hobfoll, S. E. (2001). The influence of culture, community, and the nested self in the stress process:
Advancing Conservation of Resources theory. Applied Psychology: An International Review,
50(3), 337–370.
Hobson, A. J., Ashby, P., Malderez, A., & Tomlinson, P. D. (2009). Mentoring beginning teachers: What
we know and what we don’t. Teaching and Teacher Education, 25(1), 207–216.
Hock, R. (1988). Professional burnout among public school teachers. Public Personnel Management,
17(2), 167–167.
Hogan, T., Rabinowitz, M., & Craven, J. A. (2003). Representation in teaching: Inferences from research
of expert and novice teachers. Educational Psychologist, 38(4), 235–247.
Ingersoll, R. M., & Strong, M. (2011). The impact of induction and mentoring programs for beginning
teachers: A critical review of the research. Review of Educational Research, 81(2), 201–233.
Iwanicki, E. F., & Schwab, R. L. (1981), A cross validation study of the Maslach Burnout Inventory.
Educational and Psychological Measurement, 41(4), 1167-1174.
Johnson, S. M., & Birkeland, S. E. (2003). Pursuing a “sense of success”: New teachers explain their
career decisions. American Educational Research Journal, 40(3), 581–617.
Jones, N., Youngs, P., & Frank, K. (2013). The role of school-based colleagues in shaping the
commitment of novice special and general education teachers. Exceptional Children, 79(3),
365-383.
Jones, N., & Youngs, P. (2012). Attitudes and affect: Daily emotions and their association
with the commitment and burnout of beginning teachers. Teachers College Record, 114(2), 1-36.
Kapadia, K., Coca, V., & Easton, J. Q. (2007). Keeping new teachers: A first look at the influences of
induction in the Chicago Public Schools. Chicago: Consortium on Chicago School Research,
University of Chicago.
BURNOUT CONTAGION 31
Kalliath, T. J., O’Driscoll, M. P., & Gillespie, D. F. (1998). The relationship between burnout and
organizational commitment in two samples of health professionals. Work & Stress, 12(2),
179–185.
Koniarek, J., & Dudek, B. (1996). Social support as a buffer in the stress-burnout relationship.
International Journal of Stress Management, 3(2), 99-106.
Kyriacou, C. (1987). Teacher stress and burnout: An international review. Educational Research, 29(2),
146-152.
Lambert, R. G., & McCarthy, C. J. (Eds.). (2006). Understanding teacher stress in an era of
accountability (Volume III). Greenwich, CT: Information Age Publishing, Inc.
Lau, P. S., Yuen, M. T., & Chan, R. M. (2005). Do demographic characteristics make a difference to
burnout among Hong Kong secondary school teachers? Social Indicators Research, 71(1), 491–
516.
Lee, R. T., & Ashforth, B. E. (1996). A meta-analytic examination of the correlates of the three
dimensions of job burnout. Journal of Applied Psychology, 81(2), 123–133.
Leiter, M. P., & Maslach, C. (2001). Burnout and health. In A. Baum, T. A. Revenson, & J. E. Singer
(Eds.), Handbook of health psychology (pp.415– 426). Mahwah, NJ: Erlbaum.
Loeb, S., Darling-Hammond, L., & Luczak, J. (2005). How teaching conditions predict teacher turnover
in California Schools. Peabody Journal of Education, 80(3), 44-70.
Lortie, D. C. (1975). Schoolteacher: A sociological study. Chicago: University of Chicago Press.
Maslach, C. (1976). Burned-out. Human Behavior, 9, 16-22.
Maslach, C. (1982). Burnout: The cost of caring. Englewood Cliffs, NJ: Prentice Hall.
Maslach, C. (1993), Burnout: A multidimensional perspective, In W.B. Schaufeli, C. Maslach, & T.
Marek, (Eds.), Professional burnout: Recent developments in theory and research (pp. 19-32).
Washington, DC: Taylor & Francis.
Maslach, C., & Jackson, S.E. (1981). The measurement of experienced burnout. Journal of Occupational
Behavior, 2, 99-113.
BURNOUT CONTAGION 32
Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52(1),
397–422.
McCormack, A., Gore, J., & Thomas, K. (2006). Early career teacher professional learning. Asia
Pacific Journal of Teacher Education, 34(1), 95–113.
Moolenaar, N. M., & Daly, A. J. (2012). Social networks in education: Exploring the social side of the
reform equation. American Journal of Education, 119(1), 1–6.
Muijs, D., Harris, A., Chapman, C., Stoll, L., & Russ, J. (2004). Improving schools in socioeconomically
disadvantaged areas? A review of research evidence. School Effectiveness and School
Improvement, 15(2), 149–175.
Pas, E. T., Bradshaw, C. P., Hershfeldt, P. A., & Leaf, P. J. (2010). A multilevel exploration of the
influence of teacher efficacy and burnout on response to student problem behavior and school
based service use. School Psychology Quarterly, 25(1), 13–27.
Pogodzinski, B. (2012). Socialization of novice teachers. Journal of School Leadership, 22(5). 982-1023.
Pogodzinski, B., Youngs, P., Frank, K., & Belman, D. (2012). Administrative climate and novice
teachers’
intent to remain teaching. Elementary School Journal, 113(2), 252-275.
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis
methods (2nd ed.). Newbury Park, CA: Sage.
Richards, J. (2012). Teacher stress and coping strategies: A national snapshot. The Educational Forum,
76(3), 299–316.
Ronfeldt, M., Loeb, S., & Wyckoff, J. (2013). How teacher turnover harms student achievement.
American Educational Research Journal, 50(1), 4–36.
Rudow, B. (1999). Stress and burnout in the teaching profession: European studies, issues, and research
perspectives. In R. Vandenberghe & A. M. Huberman (Eds.), Understanding and preventing
teacher burnout: A sourcebook of international research and practice (pp. 38-58). New York:
Cambridge University Press
BURNOUT CONTAGION 33
Schorn, N. K. & Buchwald, P. (2007). Burnout in student teachers. In P. Roussi, E. Vasilaki, K.
Kaniasty, & J. D. Barker (Eds.), Electronic proceedings of the 27th conference of the STAR
Society (pp. 150 - 159). Rethymnon, Greece: University of Crete
Skinner, E., & Beers, J. (2014). Mindfulness and teachers’ coping in the classroom: A developmental
model of teacher stress, coping, and everyday resilience. In K. Schonert-Reichl & R. W. Roeser
(Eds.), Handbook on mindfulness in education: Emerging theory, research, and programs (pp.99-
118). New York: Springer-Verlag.
U.S. Department of Education (n.d.). Improving basic programs operated by local education agencies
(Title 1, Part A). Retrieved from http://www2.ed.gov/programs/titleiparta/index.html
Van Maele, D. & Van Houtte, M. (2015). Trust in school: A pathway to inhibit teacher burnout? Journal
of Educational Administration, 53(1), 93-115.
Wright, T. A., & Cropanzano, R. (1998). Emotional exhaustion as a predictor of job performance and
voluntary turnover. Journal of Applied Psychology, 83(3), 486–493.
Zhang, Q., & Sapp, D. A. (2008). A burning issue in teaching: The impact of perceived teacher
burnout and nonverbal immediacy on student motivation and affective learning. Journal
of Communication Studies, 1(2), 152–168.
BURNOUT CONTAGION 34
Appendix A
Issue Related to Network Autocorrelation
While organizational exposure to burnout was included as a level-two variable for our analysis,
without social network data and burnout data from all teachers in each school, we do not know how much
an ECT’s social network exposure overlapped with that of other ECTs at the same school. Such
interdependency between ECTs with regard to social network exposure may produce underestimated
standard errors of βs (Dow, Burton, & White, 1982). A network autocorrelation model takes into account
such interdependency among cases by including a weight matrix, W (Doreian, 1989). Although this
would be a useful way to address interdependency in our case, it was not possible for us to apply this
approach, due to the egocentric and one-time nature of the social network data used for this study.
BURNOUT CONTAGION 35
Endnotes
1. The minimum number of teachers per school was 2 and the maximum was 15; this included
ECTs, mentors, and/or colleagues.
2. The social network variable weighted by the frequency of interaction had no significance association
with the dependent variable. When we used the maximum and median levels of burnout exposure,
instead of the mean level of burnout exposure, this did not change the results.
... Recently, researchers have documented the phenomenon of burnout contagion. This phenomenon involves feelings of emotional exhaustion from exposure to other teachers' negativity and exhaustion in the same school (Kim, Youngs, & Frank, 2017;Zimmerman, 2019). Kim et al. (2017) stated that early-career teachers are particularly susceptible to this burnout contagion. ...
... This phenomenon involves feelings of emotional exhaustion from exposure to other teachers' negativity and exhaustion in the same school (Kim, Youngs, & Frank, 2017;Zimmerman, 2019). Kim et al. (2017) stated that early-career teachers are particularly susceptible to this burnout contagion. Additionally, in their review of the research in special education teacher burnout, Brunsting, Sreckovic, and Lane (2014) found that there is a negative correlation between teacher age and burnout. ...
... Researchers have underscored the importance of mentoring teacher candidates in regard to students with disabilities (Mullen, 2010) and pointed out the importance of addressing burnout during the teacher preparation process among general-education teacher candidates (Brunsting, Sreckovic, & Lane, 2014;Kim et al., 2017). This conversation has been largely missing; however, among those who prepare special-education teachers. ...
... Other research demonstrates an empirical link between lack of social support and feelings of burnout for both students and teachers, especially for early career teachers (Alsup & Moots, 2021;Bettini et al., 2018;Cooley & Yovanoff, 1996;Halbesleben, 2006;Shirrell, 2021). Environmental factors may explain why early career teachers and special education teachers have a greater propensity for burnout (Bettini et al., 2018;Fernet et al., 2014;Kim et al., 2017aKim et al., , 2017bPerrone et al., 2019). Even more troublesome is the capacity for burnout to spread among teachers interacting with other colleagues. ...
... Even more troublesome is the capacity for burnout to spread among teachers interacting with other colleagues. As Kim et al., (2017aKim et al., ( , 2017b demonstrate, early career teachers seem more likely to experience burnout if their mentors and other colleagues within their social networks themselves experience burnout. ...
... Other studies underscore the importance of transformational leadership, which can help teachers develop a sense of purpose, increase personal self-efficacy, or sustain a shared organizational vision, thereby ameliorating teacher burnout (Gong et al., 2013;Leithwood et al., 1996;Yorulmaz et al., 2017). Leaders might also make an effort to foster collegiality (Bettini et al., 2018), promote positive relationships with students and parents (Kim et al., 2017a(Kim et al., , 2017b, and secure access to counseling (Ates, 2016), all of which presumably decrease the incidence of burnout. Indeed, principals play a significant role in a teacher's decision to leave the profession entirely (Grissom, 2011). ...
Article
Full-text available
Across different faith traditions, Sabbath day observance shares a close relationship with theological conceptions of rest. Sabbath-keeping, with its promise of rest, may be a valuable spiritual practice in the context of teaching as prior research has consistently documented the adverse effects of teacher burnout. Yet no research has examined Sabbath-keeping and its connections to teaching practices and teacher burnout. We aim to fill this gap with a quantitative study of Sabbath-keeping and burnout among 1,300 teachers in Christian schools throughout the USA, Canada, Indonesia, and Paraguay. We report their conceptions of Sabbath and how those conceptions inform their teaching practice. We find an inverse and statistically significant relationship between Sabbath-keeping and burnout that is robust across several model specifications, suggesting that Sabbath-keeping may be helpful in reducing burnout among educators.
... They found individual educators' burnout levels to be uniquely related to average levels of burnout in their school and among those identified as close colleagues. This observation is consistent with a so-called "contagion effect," whereby ones' stress and burnout may be affected by those around them, and also highlights the possibility that relationships with close colleagues operate not only as a resource, but also as a burden (Kim et al., 2017). With so few studies investigating this possibility, the current study also aimed to examine stress and burnout as shared experiences in educators' networks and, further, delineated between two types of close colleagues-those sought out for stress support versus those with whom educators spent most of their time. ...
... The peer nomination process used allowed for these networks to be distinct or overlapping, based entirely on colleagues an educator chose to nominate (see Fig. 1). We expected a shared experience of wellbeing among educators to be indicated, with stress and burnout in personal networks being positively related to educator stress and burnout (Kim et al., 2017). Further, we anticipated such associations might be stronger in most-time networks, as compared to stress support networks. ...
... The study findings were consistent with the notion that educators' stress and burnout is associated with the degree of stress and burnout among close colleagues (Kim et al., 2017). We were able to consider such patterns distinctly among two types of networks of close colleagues: those providing stress support versus those with whom an educator spends the most time. ...
Article
Full-text available
School mental health practitioners and researchers are increasingly concerned about educator job-related stress and its implications for teacher burnout, teaching efficacy, turnover, and student outcomes. Educators’ collegial networks in their schools are natural resources for stress support, yet little is known about the extent to which educators seek support from their colleagues in managing their stress and whether these relationships promote their emotional wellbeing. Utilizing peer nomination and self-report data from 370 educators in 17 elementary and middle schools, we found patterns in whom educators nominated as a source of stress support. Specifically, educators more often nominated colleagues who worked in the same role, grade, and/or subject, and those similar in age and who had similar or more experience. Furthermore, men and educators of color more often nominated same-gender and same-race colleagues, respectively, whereas these trends were not observed for women or White educators. However, the prevalence of these characteristics among colleagues nominated as a source of stress support was not often significantly associated with educators’ stress and burnout. Rather, educators’ level of burnout was positively related to the burnout among those in their stress support networks. In addition, educators’ stress and burnout were positively related to the stress and burnout of their colleagues with whom they spent the most time. These findings highlight how educators’ perceptions of stress and burnout may be shared within their collegial networks and have implications for a role for colleagues in teacher stress-reduction and wellbeing-focused interventions.
... More specifically, friction in professional interactions such as leadership issues, pupil misbehavior, challenging interrelations with pupils' parents, and unsolved problems with colleagues increase the risk of teacher burnout (Dorman, 2003;Hakanen et al., 2006;Skaalvik and Skaalvik, 2007Pyhältö et al., 2011;Aloe et al., 2014;Richards et al., 2018). Teacher burnout is also suggested to cross over between teachers via professional community interactions (Bakker and Schaufeli, 2000;Kim et al., 2017;Meredith et al., 2020;Pietarinen et al., 2021). Teacher burnout can cross over in professional interactions directly via emotional contagion (Buunk and Schaufeli, 1993;Hatfield et al., 1993;Bakker and Schaufeli, 2000;Bakker et al., 2003Bakker et al., , 2006 and indirectly, through the negative influence of burned-out teachers on the working conditions of others and the quality of interaction in the school community. ...
... A reason for this might be that teachers in large schools have been shown to receive less social support than teachers in smaller schools (Skaalvik and Skaalvik, 2009). Moreover, low socio-economic status of the school neighborhood has been shown to be associated with higher levels of teacher burnout (Vercambre et al., 2009;Kim et al., 2017;Pietarinen et al., 2021). ...
... H2: Organizational factors, i.e., the school size, school's academic level, and the socioeconomic status of the school neighborhood are related to the differences between schools in the level and change of teacher burnout. More precisely, the burnout levels are expected to be higher in large schools, in schools in which higher grades are taught (i.e., lower secondary school and combined school), and in schools situated in low socioeconomic neighborhoods (see Vercambre et al., 2009;Pietarinen et al., 2013bPietarinen et al., , 2021Arvidsson et al., 2016;Kim et al., 2017;Skaalvik and Skaalvik, 2017;Saloviita and Pakarinen, 2021). ...
Article
Full-text available
Differences in teacher burnout between schools are likely to occur due to differences in the quantity and quality of interaction within the schools. Multilevel latent growth curve analyses of burnout symptoms were performed on three-wave longitudinal data collected from 2,619 teachers in 75 schools in Finland. The results showed that differences in teacher burnout between schools were pronounced in cynicism, followed by emotional exhaustion. Organizational factors were not strong predictors of differences in teacher burnout. Proactive co-regulation strategies were related to lower levels of teachers’ cynicism about the professional community, implying that they might be useful in preventing the teachers’ cynicism at the school level.
... International Journal of STEM Education (2022) 9:64 the characteristics of those providing support to novice teachers and the influence of these individuals on the experiences of novice teachers. For example, burnout levels among novice teachers at the end of the school year are related to the level of burnout among the mentors and colleagues within their social network (Kim et al., 2017). Given the association between teacher retention and teachers' perceptions of workplace support, these findings have implications for understanding the type of support that is most useful for novice teachers and the characteristics of those who provide this support, potentially impacting novice teachers' decisions to remain in the field. ...
Article
Full-text available
Background The Noyce Scholarship Program was created to attract and retain science, technology, engineering, and mathematics (STEM) teachers in high-need schools. Teacher support networks, and specifically mentorship support, have been linked to increased retention of high-quality teachers in the classroom. Using a sample of Noyce teachers, we used a multilevel model to explore how the characteristics and composition of novice teachers’ support networks are related to the likelihood that they receive mentorship support, and further, how characteristics common among Noyce programs are related to mentorship support. Results Findings suggest that the characteristics and composition of a teacher’s network, as well as certain Noyce program characteristics, contribute to the likelihood that teachers receive mentorship support from their larger support network. Implications The results of this study highlight the importance of considering how the design of teacher preparation programs may contribute to continued mentorship support for early career teachers, and ultimately, their retention in the classroom.
... To date, we know that the recent intensification of immigration enforcement has disrupted the ecologies of schools and has been detrimental to the wellbeing of entire school communities-educators, students, and families alike. While many educators express an even deeper commitment to their students in the face of what they perceive to be cruel terrorization, the adverse effects that they experience put them at great risk for burnout (Kim, Youngs & Frank, 2017). We question how much more these educators can absorb before they reach a breaking point. ...
... It is unsurprising that teacher attrition is associated with teacher working conditions (Geiger & Pivovarova, 2018). In some contexts, early career teachers have higher recorded rates of burnout (mental and physical exhaustion) and turnover (Kim et al., 2017). Early career teacher attrition may be reduced by placing greater focus upon professional wellbeing for job satisfaction (Kelly et al., 2018) ...
Research
Full-text available
The Education Achievement Service (EAS), (under the authority of the Welsh Assembly Government) commissioned a research team from Manchester Metropolitan University to evaluate the EAS model of support for Newly Qualified Teachers (NQTs) in South East Wales. It focusses on the effectiveness of the national induction programme for NQTs
Article
This study takes advantage of natural variation in alignment and accountability to analyze educator sensemaking of a complex policy environment. It describes how educators in two large, high-accountability districts in New York and Florida made sense of multiple policy changes, including new standards, curriculum, assessments, and teacher evaluation. Drawing on interviews with 68 individuals, observations of instruction and professional development, and policy documents, findings suggest that high policy alignment represents a fundamental yet insufficient condition for educators to perceive policies as coherent and coordinated. Accountability strength and policy sequence were important factors in educators’ perceptions of coherence. In both districts, the pace and complexity of change contributed to policy overwhelm.
Article
This study aimed to extend the use of a validated assessment of social-emotional development (SED) from children and adolescents to teachers. We used correlation and regression analyses to examine the factor structure of this Holistic Teacher Assessment (HTA) and the relationships between teacher SED, self-efficacy, and burnout. Results from 284 teachers identified nine interpretable and useful SED dimensions for teachers. SED was a stronger (negative) predictor of burnout than self-efficacy, but together SED and self-efficacy accounted for more variance than either one separately. Supporting every teacher using the strengths-based HTA can inform proactive approaches, tailored to teachers’ strengths and needs.
Article
Special education teachers have one of the most challenging and stressful jobs in public education, which often leads to increased burnout. High levels of burnout have, in turn, been related to lower levels of fidelity of implementation in delivery of evidence-based behavior interventions. The purpose of this position paper is to (a) propose exploration of several potential malleable factors related to burnout of special educators serving students with and at risk for emotional and behavioral disorders, (b) link those suggestions to theoretical frameworks, (c) discuss the relation between burnout and fidelity, and (d) suggest measures that may be used to pursue this research, with the ultimate goal of helping the field discover means of intervention to remediate and prevent burnout.
Article
Full-text available
Background/Context: The increasing number of districts implementing mentoring and induction programs suggests that policymakers are aware of the need to increase the support available to neiv teachers. The argument underlying many of these programs is based, at least partly, on assumptions about beginning teachers' emotional responses to their work. Yet tvhile considerable research has studied the effects of induction programs, few researchers have rigorously collected data on how beginning teachers' affective experiences seem to impact their career plans. Purpose of the Study: We tested a framework developed in the organizational behavior literature known as affective events theory (AET), which proposes that emotional responses to work, coupled ivith abstract beliefs about one's job, can influence overall judgments about job satisfaction. Specifically, we drew on research from education and organizational behavior to test whether mean levels of positive affect, negative affect, skill, and fatigue are associated with intentions to remain in teaching (i.e., commitment to one's teaching assignment), commitment to one's school, and levels of burnout. Research Design: Sources of data in this study include survey data collected at two time points (fall 2007 and spring 2008) from 42 beginning general and special education teachers in three districts in Michigan and Indiana, as well as data collected using the experience sampling method (ESM), a time sampling method for gaining information about individuals' immediate experiences. The inclusion of both data sources allowed us to capitalize on the richness of the ESM data-which accounts for variation in teachers' momentary affective states-while also supporting the data with more traditional survey measures. Conclusions/Recommendations: We found that mean levels of positive affect and skill are positively associated with commitment, even when controlling for prior commitment. Similarly, negative affect and tiredness seem to be predictive of teacher burnout. These results suggest that, by taking account of teachers1 emotional reactions to their work (in addition to features of their work environments), researchers, policymakers, and district administrators will be better positioned to support special and general educators during their early years of teaching.
Article
Full-text available
We compare beginning special and general education teachers' access to school-based colleagues. Our findings demonstrate that colleague relationships are critical for the experiences of beginning teachers, as are the school organizational norms that these beginning teachers experience. For special education teachers in particular, perception of colleague support was a strong predictor of retention plans. Similar results were seen with respect to their perception of the level of collective responsibility among the faculty. Taken together, these results suggest that schools and districts should make efforts to facilitate productive relationships between general and special education faculty, as well as to differentiate induction support for beginning special educators.
Article
Full-text available
How do democratic personnel policies of the public school principal affect teacher burnout and how does teacher burnout affect support for democratic instructional styles? Using sequential OLS models from questionnaire data of 2,961 urban public school teachers, the research finds that teachers, who perceive that their principals are non-authoritarian, are supportive and collegial, and involve them in campus decision-making, are less likely to experience burnout than those teachers who perceive the opposite. However, both burned out teachers and those who report that their principal treats them democratically do not support a similar democratic treatment of their students, as indicated by their rejection of student-centred instruction. Policy implications of the research are discussed in the context of the state 's accountability mandate.
Conference Paper
Full-text available
This meta-analysis examined how demand and resource correlates and behavioral and attitudinal correlates were related to each of the 3 dimensions of job burnout. Both the demand and resource correlates were more strongly related to emotional exhaustion than to either depersonalization or personal accomplishment. Consistent with the conservation of resources theory of stress, emotional exhaustion was more strongly related to the demand correlates than to the resource correlates, suggesting that workers might have been sensitive to the possibility of resource loss. The 3 burnout dimensions were differentially related to turnover intentions, organizational commitment, and control coping. Implications for research and the amelioration of burnout are discussed.
Chapter
Teaching is a demanding profession, with the potential to provide high levels of satisfaction. However, research shows that it can also be stressful: Teachers report multiple sources of chronic stress (including workload, students, parents, and administrators) and symptoms of burnout, such as emotional exhaustion, helplessness, and cynicism; rates of desistence often top 30 %. Studies of teachers’ everyday coping indicate that adaptive coping may provide a buffer and maladaptive coping a risk factor as teachers negotiate these stressors. In fact, developmental models suggest that constructive coping has the potential to transform previously stressful interactions into opportunities for learning and development, contributing to higher quality engagement in teaching, greater satisfaction, and well-being. This chapter explores the promise of mindfulness practices and interventions to aid teachers in developing personal resources that would help them cope more constructively, and thereby provide a pathway toward everyday resilience. First, we present a developmental model depicting the kinds of constructive coping that can promote teacher engagement and learning. Second, we identify multiple points in the process of coping where mindfulness could make an important difference, focusing especially on the mechanisms through which mindfulness could have its salutary effects. We conclude with suggestions for how mindful coping might change students’ experiences in the classroom, since better coping may improve educators’ engagement in teaching and the quality of their relationships with students and classroom management. We hope that the developmental model might provide a framework useful for guiding future studies on mindfulness and teachers’ everyday coping and resilience.
Article
In this book chapter we have outlined a comprehensive framework of burnout and job-engagement based on COR theory, for the first time placing emphasis on job-engagement. We defined burnout and job-engagement as multifaceted phenomena revolving around intrinsic energy resources, or vigor. Cognitive and behavioral inclinations, such as behavioral inhibition versus approach orientation, are considered to be close co-travelers. Burnout results from a slow, stressful process of resource bleed out that is not counterbalanced by resource gains, thus accumulating to significant losses. We proposed that job-engagement is the resultant of the inverted process of real or anticipated resource gains. Gains become significant if they feed into peoples’ primary resources, which are essential for survival or relate to basic needs, but they must also support peoples’ psychological resources of sense of efficacy, self-esteem, and sense of success. COR theory emphasizes that changes in resource levels are the principle axis by which burnout and job-engagement process are activated and sustained, or inhibited and curtailed. This means that, no matter how excellent ones’ performance, just staying the course without generating further gains is not expected to be very engaging. In such cases, people need to take investment risks in order to initiate further positive changes. Based in this idea we have proposed a new framework for boosting engagement at work based on general principles of COR theory, called striving for dynamic stability and tolerance for failure. The starting point for this framework is creativity and innovativeness as key to job-engagement. The building blocks are flexibility, balance, diversity, interdependence, loyalty, trust and tolerance for failure. We emphasize that these building blocks are important resources on both individual and environmental level, that need to fit together in order to activate and sustain engagement processes. Synergy between individuals, teams and the organization needs to be emphasized where possible, which keeps the focus on strengths and resource gain. Hopefully our framework provides an impetus for extending current job-engagement research towards original dynamic multi-level investigations.
Article
Informal mentors likely play a substantial role in novice teacher learning, yet we know little about them, especially in relation to formal mentoring, which is the cornerstone to most induction programs. This study analyzes survey and interview data from 57 first-year mathematics teachers from 11 districts to investigate differences in the characteristics of formal and informal mentoring that can inform improvements in mentoring policy. Our findings suggest that informal and formal mentors sometimes serve similar functions but often provide compensatory and complementary support. Based on these findings, we identify a set of policy recommendations to improve new teacher supports.