a meta-analysis of stress in teachers 1 running head: a meta-analysis of stress...

A Meta-analysis of Stress in Teachers 1

Running head: A META-ANALYSIS OF STRESS IN TEACHERS

A Meta-analysis for Exploring the Diverse Causes and Effects of Stress in Teachers

Cameron Montgomery & André A. Rupp

University of Ottawa

Address Correspondence To:

Cameron Montgomery, Assistant Professor

Faculty of Education

University of Ottawa

145 Jean-Jacques Lussier Street

Ottawa, ON, K1N 6N5

Canada

Phone: (613) 562-5800 [Ext. 4119]

E-mail: [email protected]


Abstract

This study provides a correlational meta-analysis of 78 independently written or published

studies on teacher stress between 1998 and 2003. We measured the relationships between

teacher stress and numerous other constructs including coping, burnout, emotional responses,

personality mediators, personal support, environmental structure, and background characteristics.

A theoretical-empirical model of construct relationships investigated across studies was

developed and n = 2,527 marginal effect sizes were used to estimate the empirical relationships

between the operationalized theoretical constructs. Results showed that the strongest association

of teacher stressors exist with negatively-oriented emotional responses and confirmed their

central role in teachers’ responses to stressful situations alongside active coping mechanisms,

personality mediators, and burnout.


Introduction

Over the past ten years educational research has established that high stress is associated with

psychological distress, which may be mediated through different coping mechanisms and

personality traits (Chan, 1998). Specifically, poor active coping abilities or an over-reliance of

passive coping strategies may lead to negative emotional responses and, consequently, teacher

burnout. However, although a plethora of research on the different sources of stress and their

eventual consequences in teachers and student teachers exists, researchers have generally used

varying methods in explaining the intricate relationships between psychological stress and other

intricately related constructs such as coping mechanisms, personality traits, emotional responses,

environmental effects, and burnout.

In order to tackle the problem of methodological variability in the current research

literature on teacher stress and to conceptually represent a model of teacher stress based on this

literature, this study investigates and summarizes the correlational evidence of the relationships

between stress and related constructs through a meta-analytic lens. Specifically, this study

focuses on the recent research literature on teacher and student teacher stress1 between 1998 and

2003. In doing so, this study updates recent international research data on teacher stress and

constitutes an effective way to respond to Guglielmi and Tatrow’s (1998) paramount call for a

shift toward more theory-based investigations that test causal models of teacher stress and

health-related outcomes with more sophisticated research designs and measurement strategies.

1 We will use the term teacher stress and not student teacher stress since most of the studies found concerned theformer.


Toward Developing a Theoretical-empirical Model of Stress

There are numerous constructs that have been identified as causes and effects of stress in

different populations over the years. There are numerous mediating factors that may influence

the relationships between variables in the nomological networks in which researchers place

constructs. In preparation for developing a meta-analysis framework, we began by synthesizing

existing theoretical stress models in order to map the empirical relationships and represent these

studies into the new framework. Since our meta-analysis focuses on a variety of relationships

among numerous constructs rather than on a few isolated relationships between few constructs

within a larger framework, we wanted to have a conceptual model of teacher stress that we could

augment and refine based on the empirical relationships studied in the research we surveyed.

Before presenting this model, we will define stress and some of its related inherent constructs.

Definitions and Sources of Stress.

Our understanding of stress originated in empirical research conducted by Derogatis

(1987), who, based his research on Lazarus’ (1966) social interaction theory. Globally, stress is

defined as a particular interaction between the person and the environment, appraised by the

person as being taxing or exceeding his or her personal resources, and, as a consequence,

disrupting daily routines (Lazarus & Folkman, 1984). According to this theory, stress is defined

as a state of psychological pressure influenced by three main sources, (1) personality mediators

(comprised of time pressure, driven behaviour, attitude posture, relaxation potential, and role

definition), (2) environmental factors (comprised of vocational satisfaction, domestic

satisfaction, and health posture), and (3) emotional responses (comprised of hostility, anxiety,


and depression). According to Lazarus & Folkman’s theory, these three sources must be studied

interactively to develop a comprehensive account of stress.

It is clear that teachers can be exposed to a number of sources of stress. Kyriacou (2001),

reports that the main sources of teacher stress are teaching students who lack motivation,

maintaining discipline in the classroom, confronting general time pressures and workload

demands, being exposed to a large amount of change, being evaluated by others, having

challenging relationships with colleagues, administration, and management, and being exposed

to generally poor working conditions. The author appropriately warns that the main sources of

stress experienced by a particular teacher will be unique to him or her and will depend on the

precise complex interaction between his or her personality, values, skills, and circumstances.

Moreover, coping mechanisms, personality mediators, and the environmental structure can

interactively influence the degree to which stressful situations are being perceived and influence

the teacher’s emotional and cognitive well-being.

Stress and Coping.

Our approach to investigating coping mechanisms was theoretically grounded in the well-

known transactional model of stress and coping (Lazarus, 1966, 1993; Lazarus & Folkman,

1984). This model focuses on the manner in which problematic events act as triggers for stressful

episodes. Lazarus and Folkman (1984) believe that, daily events predict changes in

psychosomatic health better than major life events (Admiraal, Korthagen & Wubbels, 2000).

When confronted by a given event, an individual engages in a process of primary appraisal

whereby, according to the individual in the situation, the event may be seen as stressful whereas,

for others, it may be seen as benign or vice versa. Next, the individual will engage in a process


of secondary appraisal. In this situation, the individual will engage in the cognitive evaluation of

his personal and environmental resources in order to deal with the loss, threat, or challenge that

is represented by the event. Both types of appraisals are cognitive processes where the first

concerns events that are, to a large extent, independent of the appraising individual. Secondary

appraisal is directly related to the perceptions that the individual has of his resources in order to

confront a stressful situation, resources that come from within himself or from his environment.

Primary appraisal allows the appraisal of the stressful character of the situation whereas

secondary appraisal permits one to evaluate one’s capacity to confront the situation. Finally, the

model predicts that the individual will use cognitive and behavioural strategies of adaptation to

deal with a given stressful event.

A number of classifications of coping strategies have been proposed in the literature. For

example, coping behaviour may be directed at managing or altering the problem that is causing

the distress or at regulating the emotional response to the problem. The former is referred to as

problem-focused coping and the latter as emotion-focused coping (Admiraal, Korthagen, &

Wubbels, 2000). Accordingly, problem-focused coping behaviour consists of confrontational

and problem-solving strategies such as defining the problem, generating alternative solutions,

weighing alternatives in terms of their cost and benefits, selecting one of them, and taking action.

Emotion-focused coping behaviour consists of positive reappraisal and positive comparison as

well as of defensive strategies such as avoidance, minimisation, and distancing. Individuals will

use emotion-focused coping behaviour when they believe that nothing can be done to modify

environmental conditions. By contrast, problem-focused coping behaviour will be utilized when

conditions may be seen as changeable. Kyriacou (2001) defines direct action techniques, on the

one hand, as things that a teacher can do that eliminate the source of stress, and mental or


physical palliative techniques, on the other hand, are aimed at lessening the feeling of stress that

occurs.

Stress and Personality Mediators.

Chan (1998) points out that evidence of stress reactions, including ill-health and

psychological distress, are not solely the result of external stressors but are also determined, by a

host of mediating variables. Many of these variables are generally collected under the umbrella

term coping (Griffith, Steptoe & Cropley, 1999; Lazarus & Folkman, 1984; Scheier & Carver,

1985). The literature also provides support that an individual’s personality characteristics

influences the degree to which he or she seeks social support (Houston & Vavak, 1991; Kobasa,

Maddi, Ouccelli, & Zola, 1985; Watson & Clark, 1984). Guglielmi and Tatrow (1998) claim

that personality traits, especially Type-A personality as well as demographic characteristics such

as gender, age, and ethnicity, further mediate the ability to establish and maintain supportive

social networks and facilitative cognitive appraisal of the stressor. Stress is not viewed as being

due exclusively to situational or personal characteristics but rather to the interaction between

them. These findings reveal that the seeking of social support and the engagement in successful

coping strategies can create a virtuous circle whereby the same objective situation can begin to

appear to be less demanding to the teacher.

Stress and Burnout.

Individuals may experience burnout as a result of: stress itself, a sudden break down of

their mediating coping mechanisms or their mediating coping mechanisms not being effective

over a long period of time (Guglielmi & Tatrow, 1998; Vandenberghe & Huberman, 1999).

Burnout has traditionally been viewed as having three components, (1) emotional exhaustion, (2)


depersonalization, and (3) lack of personal accomplishment as is most frequently measured

using Maslach’s Burnout Inventory (Maslach & Jackson, 1981). A feeling of burnout is not a

direct effect of repeated exposures to stressful situations. Burnout mediated through various

active and passive coping mechanisms, as discussed above, is a result of the accumulation of

positively and negatively oriented emotional responses that have been mediated through coping

mechanisms.

A Theoretical-empirical Model of Teacher Stress.

Based an extensive review of theoretical teacher stress models including their related

constructs and definitions found in the empirical articles for our meta-analysis, we developed a

model of the construct relationships discussed in them, which includes, as its central component,

a representation of the teachers’ intra-individual process of reacting to stressful events (see

Figure 1).


Figure 1. Theoretical-empirical model of construct relationships of teacher stress.

The first premise of the model is that the teacher is present throughout the entire model. As for

the other labels, the labelling process of the categories captures the general patterns of construct

relationships and maps onto similarly signified latent variables in structural equation models

(Chan, 1998). Specifically, the model was developed after reviewing and qualitatively

categorizing individual variables and variable relationships in the empirical literature on teacher

stress surveyed for this paper, which is why the stress sources in the diagram are semantically

tied to an instructional environment. Apart from the sources of teacher stress, however, the

remaining part of the model appears to display universally applicable relationships. The

theoretical functioning of this model will be explained in the paragraphs that follow whereas, the


coding of variables will be described in the methods’ section and the empirical relationships

between variables will be discussed in the results’ section.

According to this model, intra-individual processes consist primarily of the experience

and appraisal of stressful events that have their sources in different aspects of a teacher’s

vocational life such as students, administration, colleagues, general work demands, and

characteristics of the school environment. In addition, stressful events in the teacher’s domestic

life may also influence his or her overall emotional, cognitive, and behavioural state. Once these

events are appraised, the individual engages in active coping or passive coping strategies,

perhaps both, where the former can take the form of cognitive, behavioural, and emotional

mechanisms, and is also manifested in the physical responses or health posture of the individual.

In contrast, passive coping mechanisms such as resignation, wishful thinking, and avoidance are

characterized by a lack of direct engagement with the stressful event toward its resolution. As a

consequence of the application of these coping mechanisms or sometimes directly as a

consequence of the stressful events, the individual experiences a host of emotional responses,

which are either positively oriented such as hope, enjoyment, or passion, or are negatively

oriented such as anxiety, frustration, or depression. In addition, the individual may experience

strong feelings of satisfaction or dissatisfaction with his or her job and life situation more

generally, which may influence the individual’s commitment level to his or her work. Finally,

then, individuals may experience different levels of emotional exhaustion, depersonalization, or

personal accomplishment as facets of burnout. It is, of course, debatable whether the degree of

satisfaction is causally prior or posterior to experiences of burnout, and this will likely depend on

the individual and the situation; we chose however to place satisfaction prior to burnout, because

we viewed it predominantly as an emotional response.


The entire intra-individual situational process is further mediated by relatively stable

personality traits or personality mediators, which influence the strength of the relationships

depicted in the core. Moreover, the relationships are also mediated by the degree to which the

individual feels supported, both in his vocational and his domestic environment; these sets of

factors are depicted as outward circles around the core path diagram. Further outward in the

model one can find the relatively stable structural characteristics of the environment such as the

grade level a teacher is instructing, the average class size in his or her classes, or the type of

school in which he or she is teaching. Similarly, background variables such as sex, educational

qualifications, and years of experience are stable characteristics of the individual that may have

some influence on the intra-individual process of dealing with stressful events.

The organization of the variable sets in Figure 1 represents partially our primary focus on

the core relationships between the experience of stressful events, the engagement of coping

mechanisms, the experience of emotional responses and satisfaction, and the experience of

burnout, and partially the relative importance of each of the components. Thus, we hypothesize

that the relationship between stress and coping mechanisms as well as between coping

mechanisms, emotional responses, and burnout is stronger than the influences that background

variables have on the coping process. Similarly, considering the outer rings, we believe that

environmental structural variables would display weaker relationships with the intra-individual

variables than the support structure or the personality mediators. At the same time, we do believe

that personality mediators and support variables display strong influences on the intra-individual

relationships depicted in the core but that they are, at the same time, less situation-dependent and

more stable. This model is not able to account for the fluidity of individuals’ response to stressful

events. Moreover, because the focus of this paper is the estimation of average effect sizes for


each of the displayed paths and hypothesized relationships, we are necessarily restricted to

statements that aggregate effects over teacher groups and situations. At the same time, our study

is an important empirical step toward investigating the systemic nature of construct relationships

in a relatively comprehensive manner.

Method

The following section of the paper describes the methodological steps that were taken to

code variables and to compute average effect size measures.

Collection of Articles

Relevant recent articles on stress were located though a computer search of a variety of

international databases housed in North America such as Psyinfo, Eric, Sociofile, Canadian

Periodical Index, Index-Cpi.Q, Infotrac, Digital Dissertations, Current Contents, Ontario

Scholars Portal, Francis (international humanities and social sciences), and Merlot as well as

through searches of the internet via Google, Metacrawler and Yahoo. We also located articles in

data banks housed outside North America such as the Fis Bildung in Germany and Repère in

Canada and France.

Various permutations of keywords were employed to track down articles. Every search

included the keywords “teachers” and “stress”, while other searches included keywords such as

“student teacher”, “pre-service”, “burnout”, “coping”, “anxiety”, and “depression”. The

reference lists in all primary articles were used to perform a search of additional references

within the sampling frame of interest until no further new articles were found. We selected

studies that investigated teacher stress in some form even though, in several cases, the title did


not necessarily indicate it (e.g., we included studies on teacher burnout, teacher coping, and

teacher health if they were also investigating the relationship between these constructs and

teacher stress). Finally, we selected only articles that contained quantitative research thus

excluding conceptual overview and synthesis articles as well as qualitative research because it is

impossible to use meta-analytic procedures for these studies. In addition, we also eliminated

articles that employed complex multivariate measures such as cluster structures, because it was

impossible to unambiguously define or assign effect sizes as measuring a single variable or a

single relationship between pairs of variables.

Overall, we included research from refereed journal publications (n = 59), dissertations (n

= 17), and refereed conference proceedings (n = 2) for a total of n = 78 independently written or

published studies. Fifteen of the studies were published in a language other than English (3 were

in French, 3 were in Japanese, and 9 were in German). The Japanese studies were translated by

trained bilingual graduate students whereas the French and German studies were not translated as

both authors are multilingual. The median sample size across studies was 184 (M = 307.68, SD =

391.29) based on 75 studies that reported it, the median percentage of males in the samples was

39.90% (M = 36.73%, SD = 19.19%) based on 41 studies that reported it, the median mean age

of teachers in the samples was 41.3 years (M = 36.72 years, SD = 11.19 years) based on 30

studies that reported it, and the median mean number of years of experience was 16 years (M =

14.89 years, SD = 12.23 years) based on 27 studies that reported it.

Coding of Studies

Studies were coded according to characteristics of the sampling frame and stages, the

experimental design structure, the population(s) sampled, and the statistical methodologies


utilized. The information from the studies was entered in three different ways. First, because of

the variability in the measures employed across all studies, a data file that contained each

bivariate relationship in each study as a separate entry was created. For each relationship, the two

variables involved in it were entered as labelled in the study along with the statistical technique

used to compare them, the effect size measure that was reported, and the degrees of freedom,

sample size, and p-value for the associated test. For studies that did not report effect sizes but

provided sufficient information to compute them by hand, this was done. The resulting data file

contained k = 2,527 entries where, on the original metric, k = 2,061 effect sizes were Pearson

product-moment correlation coefficients, k = 62 were Spearman correlation coefficients, k = 6

were Pearson point-biserial correlation coefficients, k = 134 were independent-samples t-test

statistics, and k = 264 were F-test statistics largely representing independent-samples t-test

statistics since they had 1 numerator degree of freedom. Since constructs involved in the

bivariate relationships varied, it was necessary to develop more global coding categories that

would allow us to summarize the effects of different relationships that represent a single path in

the theoretical-empirical model depicted in Figure 1.

Creation of Variable Categories

After having entered all explanatory and response variables from all studies within our

sampling frame, we recoded the variables according to the theoretically-derived categories

depicted in our model (see Figure 1). Hence, the highest-order categories corresponded to

different sources of stress, different types of active and passive coping, different types of

emotional responses, different facets of burnout, and different types of support, as well as

personality mediators, environmental structure variables, and background variables. Most

variables could be unambiguously classified into one of these categories while, in other cases


where disagreement over classifications existed, a final classification was obtained by going

back to earlier studies that contained a theoretical model with these variables in them or by

consulting other empirical research articles outside of our sampling frame.2

Statistical Analysis

We analyzed the correlational data using the methods outlined in Fern and Monroe

(1996), Lipsey and Wilson (2001), Hedges & Olkin (1985), and Hunter and Schmidt (1990). For

each study, the score reliabilities of the psychometric measures were recorded, because

“interpreting the size of the observed effects requires an assessment of the reliability of the

scores” (Wilkinson & APA [American Psychological Association] Task Force on Statistical

Inference, 1999, p. 596). It was our original intention to correct the involved coefficients for

range restrictions, but too many studies did not include the necessary information to do this

meaningfully; therefore, this step was omitted. If one compares the result of correction for range

restriction in other meta-analyses, however, one can safely assume that the difference between

the uncorrected and the corrected correlation coefficients would generally be around .05 or .10

with corrected values being, of course, higher than the uncorrected ones.

The structure of effect-size statistics varies, of course, by the statistical model for which the

effect size is reported as a measure. Nevertheless, most effect sizes can be readily transformed

from one metric to another (e.g., Fern & Monroe, 1996). Since most of our effect sizes were

Pearson product-moment correlation coefficient based on two variables measured on interval

scales, we chose to transform the remaining effect sizes onto the correlation metric. This

consequently eliminated a few effect sizes such as unstandardized and standardized regression

2 At this point, it would be important to investigate the reliability of the classifications, because the current ones arebased only on the expertise of the two principal researchers.


coefficients in multiple linear regression models or structural equation models, because they

represent partial effects and are computed with other variables included in the model.

For each correlation coefficient so obtained, we also recorded the number of samples that

they were based on. Due to the variability in the measures we investigated, these samples are not,

technically, statistically independent, because multiple correlation coefficients from the same

study that index different bivariate relationships between different construct pairs were included

in the computation of the same average. However, whether the violation of the statistical

independence would lead to serious biases in the computation of the average effect size measures

and their standard errors is debatable, because it depends on the amount of dependence. In order

to ensure that sample sizes were non-inflated, we recorded only the total sample size for all

independent samples across the studies. The correlation coefficients were transformed to the

standard normal metric, which possesses superior statistical properties, and the standard errors,

weights, and 95% confidence interval limits were computed on that metric. Finally, the

confidence interval limits were transformed back to the original correlation metric.

Statistically (see, e.g., Lipsey & Wilson, 1996, p. 72), for r denoting the correlational effect

size of interest, the transformation to the standard normal scale is

˙̊˘

ÍÎ

È-

+=

r

rzr 1

1log5. , (1)

the standard error is

3

1)(

-=

nzSE r , (2)


and the corresponding weight is

3)( -= nzw r . (3)

Therefore, the average correlational effect size is computed as

Â

Â

=

=

⋅=

K

kkr

K

kkrkr

r

zw

zzwz

1

1

))((

)())(((4)

with a standard error of

Â=

=K

kkr

r

zwzSE

1

))((

1)( (5)

so that a 95% confidence interval, based on the appropriateness of distributional assumptions,

can be computed in the typical manner as

)(96.1 rr zSEz ⋅± . (6)

The confidence limits for the correlational scale were then obtained by using the simple back-

transformation

)12exp(

)12exp(

+

-=

r

r

z

zr . (7)

The following section now presents a summary of the major associations found between

indicators of the constructs included in our model.


Results

Average correlation coefficients for all pairs of variables subsumed under the higher-order

construct classification categories depicted in Figure 1 were computed; Table 1 shows the

resulting average correlational effect sizes.

[INSERT TABLE 1 HERE]

The upper off-diagonal of Table 1 shows the total sample size of all independent samples (N) and

the number of effect sizes on which the averages were based (K) whereas the lower off-diagonal

shows the average effect size statistics on a correlation metric with their respective 95%

confidence intervals. The total number of correlations between variables from the 9 categories

(i.e., stress, active coping, passive coping, emotional responses, burnout, personality mediators,

support, environmental structure, background characteristics) utilized across the 78 studies was k

= 2,023. The average absolute correlation size for the 525 utilized samples was .1913 with a

standard deviation of .0877. All average correlations are significant at an individual a = .05

level, because the corresponding 95% confidence intervals do not contain 0, with the exception

of the two average correlations associated with active coping and emotional responses ( =r .05)

as well as with background characteristics and environmental structures ( =r .14).

Results from Table 1 indicate that average correlations between external stressors and

others constructs are, generally, moderate. External stressors are most highly correlated with

burnout ( =r .26), support variables ( =r .26), personality mediators ( =r .25), and emotional

responses ( =r .25) and less strongly correlated with active coping ( =r .20), environmental

structure ( =r .19), and background variables ( =r .11); the lowest average correlation was found


for passive coping ( =r .07). In other words, external stressors may be moderately influencing

burnout directly with support from family and other colleagues playing a mediating role with

similarly moderate effects. Along the same lines, emotions such as anxiety, depression, and

disappointment are also moderately directly affected by stress or moderately affected by active

coping as a mediating variable; however, they are not strongly affected by passive coping

mechanisms.

In terms of active coping, average correlations were generally moderate, and it was found

that active coping was most strongly correlated with burnout ( =r .26). Weaker correlations were

found between active coping and environmental structure ( =r .20), personality mediators

( =r .16), support ( =r .15), and passive coping. Finally, extremely weak correlations exist

between active coping and background variables ( =r .09) as well as emotional responses

( =r .05). Thus, how one actively copes through exercise (i.e., one’s health posture), concrete

behavioral strategies, cognitive planning, and through using appropriate emotional responses in

the face of various stressors may moderately determine if one will indeed feel emotionally

exhausted, depersonalized, or not accomplished. Yet, at the same time, the degree to which one

engages in active coping strategies does not vary systematically with background characteristics

and does not systematically predict the emotional responses to stressful events, even though

these are, in themselves, moderately correlated to stressful events as a cause and burnout as a

result.

In terms of passive coping, average correlations were generally low. Interestingly, the

construct that most strongly correlated with passive coping was background characteristics

( =r .12) showing that, for example, there are differences in which people with different levels of


teaching experience cope passively even though that, in itself, does not strongly influence the

manner in which they internally mediate the stressors.

In terms of emotional responses, average correlations were moderate to high in the frame

of reference of the average correlations observed here. Specifically, a high average correlation

was observed between emotional responses and burnout ( =r .39), showing that the degree in

which teachers emotionally respond to stressful events and how satisfied they are as a

consequence, either mediated through coping mechanisms or not, has a strong influence on the

degree of burnout they experience. Moderate average correlations were observed between

emotional responses and personality mediators ( =r .30), environmental structure ( =r .27), and

support ( =r .26) indicating that these factors also influence quite strongly how people

emotionally respond to stressful events, which, in turn, influences the degree of burnout they

experience. As seen with active and passive coping, the average correlation between emotional

responses and background variables ( =r .06) was low.

In terms of personality mediators, average correlations are similarly moderate as shown

by, for example, the average correlations between personality mediators and burnout ( =r .27),

support variables ( =r .23), and environmental structure variables ( =r .22). Moreover, the

average correlation between personality mediators and background variables is low ( =r .11)

showing that personality traits do not vary systematically with stable background characteristics

such as sex.

In terms of support variables, average correlations varied by the construct they were

related to. For example, while a moderate average correlation exists between support variables

and environmental structure variables ( =r .33), there is only a low average correlation between


support and background characteristics ( =r .06) showing that the perception of available support

for individual teachers does not vary systematically with background characteristics such as sex

or educational level. Moreover, the average correlation between background characteristics and

environmental structure variables is low ( =r .14), but is, at the same time, the highest

correlation between background characteristics and other constructs.

Conclusion

To summarize some of the central average correlations discussed above, Figure 2 shows

the theoretical-empirical model described earlier with selected effect sizes indicated.

Figure 2. Theoretical-empirical model of construct relationships of teacher stress with selected

average correlations shown.


In summary, results showed that correlations between most constructs were only moderate with

some expected patterns. Specifically, stronger moderate associations exist between external

stressors and burnout, personality mediators, negatively- or positively-oriented emotional

responses including satisfaction and dissatisfaction, and support variables as well as between

emotional responses and burnout. One may gather from the above results that emotional

responses, personality mediators, support variables, and burnout play, not surprisingly, a central

role in the manner in which teachers respond to stressful situations.

Specifically, emotional responses and personality mediators are rather closely associated

suggesting that the way teachers emotionally respond to a variety of stressful situations is closely

tied to the relatively stable personality traits that mediate their responses. However, the majority

of emotional responses that have been empirically investigated in the studies that were

synthesized here are negatively orientated (e.g. distress, anxiety, depression), which implies that

the average correlations between external stressors and these responses are primarily reflective of

the fact that an exposure to stressful events leads to negative experiences for teachers, be they

mediated through coping mechanisms or not, and that these responses, in turn, may lead to

different types and magnitudes of burnout. Environmental structures and support systems also

influence teachers’ emotional responses, which shows that the subjectively perceived quality of

the environment and the support structures available to the individual teacher, both at home and

at work, is important for dealing with stressful situations. Therefore, in conclusion, there is

empirical evidence in the literature on teacher stress that primary importance should be given to

the precise examination of emotional responses within the stress cycle.


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