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School Poverty Status, Time of Year, and ElementaryTeachers' Perceptions of StressMegan O'Donnell a , Richard G. Lambert b & Christopher J. McCarthy ca Arizona State Universityb University of North Carolina, Charlottec University of Texas at AustinPublished online: 07 Aug 2010.

To cite this article: Megan O'Donnell , Richard G. Lambert & Christopher J. McCarthy (2008) School Poverty Status, Time of Year, andElementary Teachers' Perceptions of Stress, The Journal of Educational Research, 102:2, 152-160, DOI: 10.3200/JOER.102.2.152-160

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eaching has been recognized as an emotionally taxing and potentially frustrating occupation for many years. For decades, researchers in the social

sciences have identified teaching as an occupation with a high risk of stress (Dunham & Varma, 1998; Kyriacou, 2000, 2001; Kyriacou & Sutcliffe, 1977; Travers & Cooper, 1996), and teachers are the largest homogenous occupa-tional group investigated in burnout research (Schaufeli & Enzmann, 1998). In a National Education Association poll, one third of the participants stated they would not choose to become teachers if they had to do it all over again (National Education Association, 1979). In addi-tion, 40% of the teachers reported that they would leave the profession before retirement (McGuire, 1979). This high risk of stress and burnout in the teaching profession can potentially compromise the quality and consistency of educational practices in today’s schools (Farber, 1984).

Ingersoll (2001) reported that shortages of qualified teachers are not caused by a lack of entrants to the field but rather larger numbers of teachers leaving before retire-ment. Ingersoll noted inadequate support from adminis-trators, student discipline problems, limited faculty input into school decision making, and—to a lesser extent—low salaries as being responsible for teacher turnover after controlling for the characteristics of both teachers (e.g.,

specialty field, age) and schools (e.g., private vs. public, higher income vs. lower income).

Occupational demands are not the only causal factors associated with stress. Stress theorists view stress as result-ing from an increase in these environmental demands. Teachers’ own perceptions of those environmental con-ditions, as well as personality traits and locus of control, can play a role in the onset of teacher stress (Friedman, 1992). In addition, some studies have examined the role that professional self-concept can play in the development of teacher stress and burnout (Farber, 1991). Self-con-cept is defined as a person’s own perceptions of his or her sense of worth and abilities in relation to others and the environment (Rogers, 1951; Rosenberg, 1965; Rosenberg & Simmons, 1971). Hughes (1987) found that teachers with highly positive self-concepts who feel confident in their professional roles are likely to cope better with stress, perceive themselves as less burnt out, and be happier with the relationships they have with their colleagues. Further exploration of the internal processes that manifest stress or burnout may contribute to a better understanding of the sources, symptoms, and treatment strategies of stress and burnout (Friedman).

The previously described phenomena can be explained by the transactional model of stress, which suggests that when life demands are encountered, perceived demands of the event are weighed against one’s perceived capabilities for dealing with it (Lazarus & Folkman, 1984). The stress response is triggered when demands are perceived as out-weighing one’s resources for coping (Sapolsky, 1998). Once triggered, the stress response leads to a range of physiologi-cal changes designed to prepare the body for fight or flight. McCarthy, Lambert, and Brack (1997) noted that one of the potential benefits of possessing adequate levels of cop-ing resources is that fewer events may be interpreted as threats to well-being, thereby reducing the occurrence of

Address correspondence to Megan O’Donnell, Arizona State Uni-versity, School of Social and Family Dynamics, Box 873701, Tempe, AZ 85287-3701, USA. (E-mail: maodonn1@asu.edu)

Copyright © 2008 Heldref Publications

School Poverty Status, Time of Year, and Elementary Teachers’

Perceptions of Stress

MEGAN O’DONNELL CHRISTOPHER J. MCCARTHYArizona State University University of Texas at Austin

RICHARD G. LAMBERTUniversity of North Carolina, Charlotte

ABSTRACT. The authors explored stress among 521 teach-ers in 16 elementary schools. They used hierarchical linear modeling to examine the relation of school and teacher char-acteristics to reported demands and resources in the class-room. School-level predictor variables included spring vs. fall data collection, Title I status, minority percentage, the inter-action between spring data collection and Title I status, and the composite achievement score. There were no statistically significant associations between Title I status or time of year for data collection and the Classroom Appraisal of Resources and Demands subscale scores. However, there were rela-tions among minority percentage, the student achievement composite, and perceptions of the availability of instructional resources.

Keywords: coping, elementary teachers, stress

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the stress response. This is particularly important because chronic elicitation of the stress response can lead to a vari-ety of physiological, behavioral, and psychological stress symptoms.

Theoretical developments suggest that coping and the subjective experience of stress can be situationally spe-cific (Sapolsky, 1998). Individuals may report perceived control in one situation and make a different appraisal of resources and demands under other circumstances. Such a distinction seems especially important to examine in an educational context, in which resources and demands can vary considerably depending on classroom characteristics, teacher background, and school environment (McCarthy, Lambert, Beard, & Dematatis, 2002). Furthermore, experts in the field of teacher-stress research have called for mea-sures that consider each teacher’s unique occupational circumstances, particularly their perceptions of excessive administrative demands, teacher–child interactions, and classroom climate (Kyriacou, 2001).

The Classroom Appraisal of Resources and Demands (CARD) was developed to examine stress using teachers’ perceptions of the demands specific to their classrooms and the resources their schools provide to address these demands. Stress theorists define resources broadly as mate-rial (e.g., money, materials, technical support from others) and personal (e.g., coping strategies, interpersonal skills; Lazarus & Folkman, 1984). The CARD places emphasis on the material resources available to teachers in their school and, more specifically, is rooted in the transactional mod-els of stress and coping, which focus on cognitive apprais-als of an event and its meaning in relation to one’s well-being (Lazarus & Folkman). Folkman and Lazarus (1988a, 1988b) describe the following types of cognitive appraisals: (a) primary appraisal of an event and its potential threat to one’s well-being and (b) secondary appraisal of an individ-ual’s perceived ability to deal with the potential stressor. Those events that one perceives as threatening can lead to the stress response, which results in a variety of phys- iological and psychological changes that occur when one’s coping resources are challenged. Experiencing these stress responses consistently over an extended period of time can lead to a variety of psychological and physical disorders (Matheny, Aycock, Pugh, Curlette, & Canella, 1986).

Previous literature on elementary teacher stress has focused more on the demands side of the stress equations. Three groups of work-related demands have been reported through this literature: children with problem behaviors in the classroom, class size, and external demands from outside the classroom, such as administrative and policy-related issues. Pratt (1978) found that teachers who serve young children view those children with behavior prob-lems as the most demanding aspect of their jobs. Teachers have the difficult task of responding to the specific needs of individual children as well as the class as a whole. In addition, they have the responsibility of completing certain requirements so that students are considered competent

at the end of the school year. French (1993) also found that larger class sizes tend to increase teacher stress and decrease perceived teaching efficacy. Research has revealed that teachers are concerned about excessive paperwork requirements, workload and time constraints, and pressure from administrators, specifically those related to mandated curricula and instructional strategies (Moriarty, Edmonds, Blatchford, & Martin, 2001). This accentuates the fact that teacher demands and pressures can potentially come from a combination of students’ parents, school and state administration, and society in general.

Although there have been many studies on teacher stress that examined factors associated with school envi-ronmental conditions, minimal focus has been placed on the influence of the community’s SES on teacher’s perceptions of stress (Kenyeri, 2002). The few studies that have examined the association between SES and teacher stress have found that low-income schools tend to possess specific factors that lead to higher stress levels (i.e., fewer resources, absenteeism, behavior problems, and teach-ers with lower education levels; Pierce & Molloy, 1990; Pratt 1978). Pratt reported significantly higher levels of stress and lower levels of psychological well-being among elementary teachers in lower SES areas. Pierce and Molloy also found that teachers in low-SES schools experienced higher levels of emotional exhaustion. In a more recent study, elementary and middle school teachers were given the Maslach Burnout Inventory (MBI), and no major dif-ferences were found between the stress levels of teachers in high- and low-SES school districts (Kenyeri). Kenyeri also indicated that higher stress levels were reported in the spring, as opposed to the fall, which could be attributed to the increase in testing that occurs at the end of the school year. However, there was no previous research to support this notion.

The purpose of the present study was to compare teach-er stress in both Title I and non-Title I elementary school settings, examining whether lower family and commu-nity resources led to higher stress levels. In addition, data were compared between fall and spring to assess whether closer proximity in time to end-of-grade testing led to an increase in teacher stress. We were also interested in comparing various aspects of classroom demands and resources to determine which components of the work-place elementary teachers perceived as most demanding and which resources they saw as most helpful in meet-ing those demands. Last, the study proposed to examine whether stress was reported as a function of the level of student achievement in the school.

Method

Participants

The data for this study was collected from teachers (n = 521) working in 16 elementary schools in a county

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that is part of the metropolitan statistical area for a large urban area in the southeastern United States. The county represents a wide range of geographic, socioeconomic, and cultural diversity. Table 1 includes a summary of the school-level characteristics, which indicates that eight of the schools (50.0%) were designated as Title I schools and six of them received targeted assistance (37.5%). Minority students in each school ranged from 11% to as high as 52% (M = 30.75, SD = 12.60). Title I schools are considered to have higher numbers of children below the poverty level and receive extra funding to support an overall initiative toward school improvement. Some schools are not eligible for or choose not to operate a Title I schoolwide program and may receive targeted assistance, which provides fund-ing to assist a select group of children who are at risk of not meeting the state’s performance standards. The state accountability testing system provides a composite score for elementary schools that represents the percentage of students who are performing at or above grade level. The mean composite score was 87.56 (SD = 4.16) for the academic year preceding this study, and the scores ranged from 79.6 to 93.0. Five of the schools (31.25%) made their adequate yearly progress (AYP) goals for compliance with the No Child Left Behind (2001) federal guidelines.

The teachers had an average of 11.94 years of experience in the profession (SD = 8.85; see Table 2). Their experi-ence levels ranged from less than 1 year to a maximum of 38 years, and 5.57% of the sample was in their first year of teaching. The teachers had worked at their current school

for an average of 6.24 years (SD = 6.31). Their years of experience at their current school ranged from less than 1 year to 34 years, and 18.04% of the sample was in their first year at their current school. The gender and ethnicities of the teachers are included in Table 3 and are represented as the following: male teachers (4.3%), female teachers (95.7%), European American (90.4%), African American (1.4%), Hispanic (0.8%), Asian (0.2%), and other (7.3%). In addition to these characteristics, the education levels of the teachers are also included in Table 3.

Procedures

Two waves of data collection took place over 2 academic years. Schools were randomly assigned to fall or spring data collection after being blocked using the following conditions: Title I designation, targeted assistance status, minority percentages, and student achievement levels. A data collection coordinator hand delivered the CARD to each of the schools and provided an introduction and explanation of the research project to the teachers during an already scheduled staff meeting. The teachers filled out the surveys on site and returned them to the data collec-tion coordinator on completion. In the instance that some teachers were not able to complete the survey in the allot-ted time, a business reply envelope was provided so that the surveys could be mailed to us once completed. Blank copies of the surveys, along with business reply envelopes, were placed in the mailboxes of those teachers who were not able to attend the staff meeting. The response rate was almost 100%. However, we obtained neither the exact information about the number of teachers at each school nor the attendance rates of the meetings. For this reason, the exact response rates could not be determined, and this

TABLE 1. School-Level Characteristics in Percentages

Variable M SD Min Max

Minority percentage 30.75 12.60 11.00 52.00Free and reduced lunch 36.74 16.82 10.37 73.96Achievement composition 87.56 4.02 79.60 93.00New teacher 5.80 3.79 0.00 14.00New to school 20.90 18.45 0.00 83.00

Note. n = 16 schools; min = minimum; max = maximum; school poverty status = 50.00% (Title I and non-Title I); time of year = 50.00% (fall and spring); data collected in Title I and spring = 25.00%; schools receiving targeted assistance = 37.50%; schools that met adequate yearly progress goals = 31.30%.

TABLE 2. Teacher-Level Characteristics: Years of Experience (n = 516)

Variable M SD Min Max

Years of experience as a teacher 11.94 8.85 0.00 38.00Years of experience at school 6.24 6.31 0.00 38.00

TABLE 3. Teacher-Level Characteristics: Demographics (n = 521)

Variable %

Gender Male 4.3 Female 95.7Ethnicity European American 90.4 African American 1.4 Hispanic 0.8 Asian 0.2 Other 7.3Highest education level reached High school 0.2 Technical school 0.2 Associate of Science 8.8 Bachelor of Science 59.7 Master of Science or Master of Education 29.0New teacher 5.6New to school 18.0

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sample can only be considered one of convenience. To ensure confidentiality, we chose not to ask participants to reveal the grade level they taught. The reason for this is that this information, in combination with ethnicity, could reveal the identity of participants in many of the schools.

Measures

The CARD (elementary version; Lambert, Abbott-Shim, & McCarthy, 2002) was used because of its ability to measure teacher stress by examining their perceptions of classroom demands and resources provided by the school. The item content of the CARD was constructed on the basis of a review of literature on stress in teachers of young children, as well as teacher and administrator interviews. Several pilot studies were administered during the develop-ment of the instrument so that feedback could be given on the basis of both the content of items and the ability of the instrument as a whole to measure the construct of elemen-tary teacher stress (Lambert et al., 2002).

The CARD consists of two scales: Classroom Demands and Classrooms Resources. The Demands scale consists of 35 items that ask teachers to rate the severity of demands on the basis of various aspects of the classroom using a 5-point Likert-type scale ranging from 1 (not demanding) to 5 (extremely demanding). The resources section includes 30 items addressing the helpfulness of various school resources using the same Likert-type scale. It was important to con-struct the items distinctively for each scale so that that the Demands items could not be construed as potential resources and vice versa. A relatively low degree of correlation was found (r = –.208), indicating that both scales were distinct.

A previous study (Lambert, McCarthy, O’Donnell, & Melendres, 2007) found sample-specific reliabilities for both the Demands scale score (α = .92) as well as the Resources scale score (α = .95). This study also yielded factor analysis results that assisted in defining the con-struct validity of the CARD. Criterion validity was found by associations in the predicted direction between the measure’s scale scores and the classroom level number of children with problem behaviors and learning disabili-ties. Specifically, teachers who rated classroom demands as higher than resources also reported two times as many children with behavior problems compared with teachers who reported that classroom resources were at least equal to demands. Another study (Lambert, O’Donnell, Kusher-man, & McCarthy, 2006) found similar reliability and validity evidence in the preschool version of the CARD, which demonstrated the following sample-specific reliabili-ties: Demands scale score (α = .94) and Resources scale score (α = .95). Factor analysis results were also presented in this study, which helped to define the construct validity of the measure. In addition, criterion validity was shown by associations in the expected direct between CARD scale scores and the classroom number of children with prob-lem behaviors. Specifically, teachers who rated classroom

demands as higher than classroom resources also reported, on average, 1.5 more children with problem behaviors than those who reported that classroom resources were at least equal to classroom demands.

The current study also demonstrates sample-specific reli-ability, which is demonstrated through the following sub-scales: (a) Other student-related demands (α = .85), (b) children with problem behaviors (α = .93), (c) administra-tive demands (α = .89), (d) availability of instructional materials (α = .89), and (e) overall demands (α = .93). The Classroom Resources scale includes the following subscale reliabilities: (a) Additional adults in the classroom (α = .84), (b) support personnel (α = .89), (c) instructional resources (α = .84), (d) specialized resources (α = .94), and (e) overall resources (α = .94). The general form of the reliability of a difference score formula that allows for different variances for each of the component scale scores (Crocker & Algina, 1986) was used to examine the reliability of the stress score. A difference score was calculated by subtracting the stan-dardized versions of the scale scores (Demands − Resources) and yielded a reliability estimate of .94. Each teacher was classified into one of three groups: Demands greater than resources (D > R; 24.2%), resources equal to demands (R = D; 37.8%), or resources greater than demands (R > D; 38.0%). The D > R group was considered to be at risk for a more stressful experience in the classroom.

Analyses

Data were analyzed using a two-level hierarchical linear model (HLM). The dependent variable for the level-one models consisted of the scale and subscale scores from the CARD. Four variables were entered into these models as predictor variables: (a) the teacher’s years of experience in education, (b) years of experience at their current school, (c) whether the teacher was new to the education field, and (d) whether the teacher was new to the school. The preliminary analyses also included free and reduced lunch percentages as a predictor variable. However, this was not included in the final analyses because it was never a statistically significant predictor in any of the models and was thus highly correlated with Title I status and minority percentage. These percentages were included for descrip-tive purposes in Table 1 (school-level characteristics). The dependent variable for the level-two models was the model-estimated school mean for each CARD scale or sub-scale and the predictor variables were: (a) spring versus fall data collection, (b) Title I school designation, (c) interac-tion between spring data collection and Title I status, (d) minority percentage, and (e) composite achievement score from the state accountability program.

Results

The first step in conducting these analyses was fitting uncon-ditional HLM models. These models contain no predictor

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variables and are used to examine the variance partition-ing of the dependent variables. Specifically, we examined the percentage of the variance in each dependent variable related to teacher differences within schools and between-school variance percentages. The variance partitioning for all scales is reported in Table 4. Approximately 96.06% of the variance occurred within schools, ranging from 89.95% to 98.01%. This indicates that the teachers’ own appraisals of resources and demands were a stronger indicator of stress than the difference in environmental demands and resources among schools. The reliability of the estimates of the school means were low (.385 to .763) because there were very small amounts of between-school variance.

There were no statistically significant associations between Title I status or time of the year for data col-

lection and the CARD scores. Although not statistically significant, it was found that more of the teachers found the demands to be greater than resources in non-Title I (27.0%) compared with Title I schools (20.7%). In addition, teachers more often perceived the demands to be greater than resources in fall (27.0%) than in spring (21.0%). Again, teachers are considered to be at risk for stress when they perceive their demands to outweigh their available resources.

There were some statistically significant associations among some of the remaining school-level predictor vari-ables and the subscale scores of the CARD (see Table 5). The school-level variable that represents the percentage of the minority students was positively associated with the other student-related demands subscale score (regression

TABLE 4. Characteristics of Each Model

Variance within Variance between School MOutcome schools (%) schools (%) reliability

Classroom resources Additional adults in classroom 97.99 2.01 .387 Support personnel 89.95 10.05 .763 Instructional resources 98.01 1.99 .385 Specialized resources 95.01 4.99 .609 Overall resources 93.89 6.11 .657Classroom demands Other student-related demands 93.93 6.07 .655 Behavior problems 95.67 4.33 .575 Administrative demands 94.96 5.04 .612 Availability of instructional materials 91.32 8.68 .734 Overall demands 95.65 4.35 .576Stress 96.06 3.94 .657

TABLE 5. School Mean Models

Achievement Title I Minority composition New New toOutcome measure Spring Title I in spring percentage (%) AYP teacher school

Classroom demands Other student-related γ –0.072 –0.136 –0.160 2.1* 1.6 0.086 0.098 –0.200 demands SE 0.011 0.131 0.140 0.5 1.3 0.091 1.504 0.265 Behavior problems γ 0.098 –0.087 –0.472 1.9 2.5 0.042 3.070 –0.724 SE 0.268 0.319 0.327 1.3 3.2 0.217 3.493 0.538 Administrative demands γ –0.206 –0.150 –0.062 0.7 2.2 0.029 0.485 –0.289 SE 0.189 0.225 0.231 0.9 2.2 0.153 2.464 0.381 Availability of instructional γ –0.380 0.020 0.101 –24.0* –5.7* –0.203 –2.817 0.584 materials SE 0.205 0.245 0.254 1.0 2.4 0.168 2.715 0.435 Overall demands γ –2.295 –1.734 –2.156 13.5 15.7 0.262 2.944 –1.931 SE 2.160 2.588 2.674 10.3 25.5 1.766 28.692 4.801Stress γ –2.733 –3.574 –0.384 5.5 4.0 –0.941 –9.866 5.064 SE 3.579 4.272 4.381 17.0 42.5 2.902 46.900 7.550

Note. AYP = adequate yearly progress goals; n = 16 schools.*p < .05.

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coefficient = .021, p = .005). This subscale focused on the teacher’s perceptions of the demands related to cultural and linguistic diversity in the classroom. This same school-level characteristic—minority percentage—was negatively asso-ciated with the teacher’s perceptions of demands related to the availability of instructional resources subscale (regres-sion coefficient = –.024, p = .045). The student achieve-ment composite score, which can be interpreted as the percentage of students scoring at or above grade level on the state accountability measures, was also negatively asso-ciated with the teacher’s perceptions of demands related to the availability of instructional resources (regression coef-ficient = –.057, p = .049). Table 6 represents the teacher-level perceptions of demands in their environment. Teach-ers who were new to their current school reported fewer demands on the behavior problems subscale than other teachers (regression coefficient = –.318, p =.035).

Discussion

One of the strongest findings from the present study indi-cates that approximately 96.06% of the variance occurred within schools (see Table 4), supporting the transactional model of stress and coping. Individual teacher appraisals of their resources and demands seem to play a larger role in the stress response than do the environmental demands and resources that differ between schools. To help elemen-tary teachers prevent excessive work-related stress, it seems important to further explore these personalized differ-ences in experiencing the stress response (Cocco, Gatti, de Mendonça Lima, & Camus, 2003). According to Sapolsky (1998), when perceived demands outweigh resources for coping, the stress response is triggered, eliciting physi-ological changes designed to prepare the body for fight or flight. Experiencing this stress response on a constant basis can lead to a variety of physiological, behavioral, and psy-

chological stress symptoms, including burnout. To prevent this burnout process from taking place, it is essential that teachers possess adequate levels of coping resources. It has been shown that coping mechanisms can help decrease the number of events that may be interpreted as threats to well-being, therefore reducing the occurrence of the stress response (McCarthy et al., 1997). Reducing the stress response can in turn minimize the occurrences of burnout (Sapolsky, 1998), which could play a key role in increasing teacher retention in today’s schools.

Although the findings show the majority of variance occurring within schools, it should be noted that the lack of variance among schools could be related to the homo-geneous nature of the sample. A more culturally and geo-graphically diverse sample of schools could have resulted in higher levels of variance among schools. That said, the county represented in this study does include a reason-able amount of diversity among income levels, minority percentages, and rural versus suburban settings. However, it still fails to include other demographic settings, such as inner-city schools and other areas of the country. In addi-tion, there is a lack of diversity among the teachers in the study, as the majority were White women.

The current findings indicate that the relation between perceived resources and demands appears to be less stress-ful in this particular sample when compared with previous studies using the CARD, in which approximately one in three teachers were at risk for stress (Lambert et al., 2007; Lambert et al., 2006). The teachers in the present study perceived the resources as being greater than demands 38.0% of the time, whereas they perceived demands as being greater than resources only 24% of the time. The latter condition is the group considered to be most at risk for stress. However, the present study included teachers from one suburban county composed of schools consisting of similar demographic variables. Although the findings

TABLE 6. Teacher-Level Models (n = 521)

Years of Years of experience in experience in New New toOutcome measure education school teacher the school

Classroom demands Other student-related demands β 0.000 0.004 0.088 –0.171 SE 0.005 0.007 0.159 0.104 Behavior problems β –0.123 0.006 0.027 –0.318*

SE 0.007 0.010 0.230 0.150 Administrative demands β 0.003 0.012 –0.136 –0.059 SE 0.005 0.007 0.165 0.108 Availability of instructional materials β 0.004 –0.002 –0.146 0.253 SE 0.006 0.009 0.213 0.140 Overall demands β 0.006 –0.102 –0.727 –1.176 SE 0.064 0.097 2.223 1.456

*p < .05.

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describe the stress as a product of individual perceptions of environment, it would still be interesting to compare these perceptions among different types of school districts (i.e. rural, urban, and suburban).

In addition to examining the role that teachers’ own perceptions play in the generalized stress response, we also assessed how poverty status and time of year can spe-cifically affect the way in which teachers perceive stress. Little research has examined either of these factors in the elementary teacher stress literature. This study found no statistically significant differences in school poverty sta-tus or time of year. However, the results did indicate that 27% of the teachers perceived demands to be greater than resources in non-Title I schools, whereas only 20.7% of the teachers reported demands being greater than resources in Title I schools. In addition, 27% of the teachers found demands to be greater than resources in fall, compared with 27% of teachers who found demands to be greater than resources in spring.

These findings contradict the predictions made prior to beginning the research. We hypothesized that teachers would be more at risk for stress (D > R) in low-SES schools because they tend to possess fewer community and familial resources as well as higher levels of absenteeism and behav-ior problems when compared with schools in higher SES communities (Pierce & Molloy, 1990; Pratt, 1978). It was also predicted that teachers would be more at risk for stress in spring (D > R), which was found by Kenyeri (2002) in previous research examining teacher burnout in elemen-tary and middle school teachers. This predication was made on the basis that most of the statewide standardized testing occurs in spring, which we assumed would cause higher perceived stress levels among the teachers during that time of the year. However, the results indicated the oppo-site, which may be attributed to the fact that the CARD includes only two questions on the demands of testing. If the teachers were given more of an opportunity to rate their perceptions of demands related to testing, then their perceived demands might appear to be higher in spring.

Although there were no statistically significant relations between school poverty or time-of-year teacher stress, there were significant findings among three of the school-level (see Table 5) and one of the teacher-level (see Table 6) variables. At the school level, the building-level minority percentage was positively associated with the teachers’ per-ceptions of the demands associated with the other student-related demands subscale, which focused on teachers’ per-ceptions of language and cultural diversity in the classroom. In addition, as the minority percentage increased, teachers’ perceptions of the demands associated with the availability of instructional resources decreased. In other words, teach-ers felt as though they had sufficient resources to meet the needs of students from different cultural backgrounds, supporting the notion that more resources are provided for Title I schools, often containing higher numbers of minor-ity children. The school-level findings also indicated that

as the student achievement composite score went up, the teachers’ perceptions of the demands related to availability of instructional resources decreased. This indicates that a higher school-achievement level led teachers to feel more confident that they had sufficient instructional resources to meet students’ needs. The last statistical finding was at the teacher level, which indicated that teachers who were newer to the school perceived less behavior problems in the classroom. Thus, teachers who are new to a school may feel a sense of invigoration by surrounding themselves with new administrators and teachers, and from overall environ-mental surroundings. Changing schools perhaps could be a wise option for those teachers experiencing career-related stress on a consistent basis.

All of the various findings from this study indicate that further research is needed to clarify the impact of individual appraisals on teacher stress, and specific predictor variables such as teacher experience, poverty status and time of year. Because the strongest findings in this study indicate that the majority of variance occurs within schools, it is impera-tive that more research is done to examine why some teachers excel in specific school environments, whereas other teachers struggle in that same setting. How are the successful teachers flourishing despite the same environ-mental conditions? It is important that effective coping mechanisms are identified at the teacher level, but at the same time, administrators must be on board with monitor-ing the environmental conditions that could be contribut-ing to teach stress and burnout.

Limitations

There were several limitations in our study. All of the data were collected in one school district, which inhib-ited us from generalizing our findings to other school environments, such as inner-city school districts. This particular school district’s mean achievement composite for elementary schools was 87.6, which is considered high in comparison with the state-level composite for math (63.4) and reading (84.9). Schools with lower composite scores can present teachers with more pressure to meet state standards, which can be perceived as stressful. The sample was also rather homogenous at the teacher level, making it difficult to generalize our findings to individuals of other social or cultural backgrounds. Also, the CARD does not require teachers to provide their teaching grade level, making it difficult to decipher the differences in stressors at the varying grade levels. For example, teachers of grades 3 through 5 may experience more stress with the end-of-grade testing that occurs at those levels compared with grades K-2.

Future Research

Future research on this subject matter should include a more diverse sample composed of varying types of school

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November/December 2008 [Vol. 102(No. 2)] 159

districts, and teachers from different social and cultural backgrounds. It would be useful to examine the differences in individual experiences of teacher stress among men and women and across varying ethnic backgrounds. In addition, it would be helpful to examine how teacher perceptions of stress differ across grade levels. To identify these dif-ferences in stress across grade levels, the CARD could be further developed by producing two different instruments: one for Grades K–2, and one for Grades 3–6. This would help separate specific stressors that occur at the different grade levels, which could help us establish effective coping mechanisms for teachers at all levels. Identifying all of the various ways in which different types of teachers from vary-ing backgrounds and experiences perceive stress could also help us develop and teach effective coping mechanisms dependent on an individual’s specific needs.

ACKNOWLEDGMENTS

A version of this paper was presented at the annual meetings of the North Carolina Association for Research in Education, on March 23, 2007 in Hickory, North Carolina, and the American Educational Research Association, on April 12, 2007 in Chicago, Illinois. Funding for this research was provided by the U.S. Department of Education as well as Utrecht University.

REFERENCES

Cocco, E., Gatti, M., de Mendonça Lima, C. A., & Camus, V. (2003). A comparative study of stress and burnout among staff caregivers in nurs-ing homes and acute geriatric wards. International Journal of Geriatric Psychiatry, 18, 78–85.

Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. Orlando, FL: Holt, Rinehart and Winston.

Dunham, J., & Varma, V. (Eds.). (1998). Stress in teachers: Past, present, and future. London: Whurr.

Farber, B. A. (1984). Stress and burnout in suburban teachers. The Journal of Educational Research, 77, 325–331.

Farber, B. A. (1991). Crisis in education: Stress and burnout in the American teacher. San Francisco: Jossey-Bass.

Folkman, S., & Lazarus, R. S. (1988a). Coping as a mediator of emotion. Journal of Personality and Social Psychology, 54, 466–475.

Folkman, S., & Lazarus, R. S. (1988b). The relationship between cop-ing and emotion: Implications for theory and research. Social Science Medicine, 26, 309–317.

French, N. (1993). Elementary teacher stress and class size. Journal of Research and Development in Education, 26, 66–73.

Friedman, I. A. (1992). Professional self-concept as a predictor of teacher burnout. The Journal of Educational Research, 86, 28–35.

Hughes, T. M. (1987, November). The prediction of teacher burnout through personality type, critical thinking and self-concept. Paper presented at the annual meeting of the Mid-South Educational Research Association, Mobile, AL.

Ingersoll, R. M. (2001). Teacher turnover and teacher shortages: An organizational analysis. American Educational Research Journal, 38, 499–534.

Kenyeri, N. T. (2002). Teacher attrition: A comparison study between teacher burnout and low and high socio-economic status schools. Dis-sertation Abstracts International, 63, 2131.

Kyriacou, C. (2000). Stress busting for teachers. Cheltenham, England: Nelson Thornes.

Kyriacou, C. (2001). Teacher stress: Directions for future research. Educa-tional Review, 53, 27–35.

Kyriacou, C., & Sutcliffe, J. (1977). Teacher stress: A review. Educational Review, 29, 299–306.

Lambert, R. G., Abbott-Shim, M., & McCarthy, C. J. (2002). Classroom appraisal of resources and demands, school-age version. Atlanta, GA: Head Start Quality Research Center.

Lambert, R., McCarthy, C., O’Donnell, M., & Melendres, L. (2007). Teacher stress and classroom structural characteristics in elementary settings. In Gates, G. (Ed.), Stress and coping in education (pp. 109–130). Greenwich, CT: Information Age.

Lambert, R., O’Donnell, M., Kusherman, J., & McCarthy, C. (2006). Teacher stress and classroom structural characteristics in preschool set-tings. In R. Lambert & C. McCarthy (Eds.), Understanding teacher stress in an age of accountability (pp. 105–120). Greenwich, CT: Information Age.

Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. New York: Springer.

Matheny, K. B., Aycock, D. W., Pugh, J. L., Curlette, W. L., & Canella, K. A. (1986). Stress coping: A qualitative and quantitative synthesis with implications for treatment. Counseling Psychologist, 14, 499–549.

McCarthy, C., Lambert, R., Beard, M., & Dematatis, A. (2002). Factor structure of the Preventive Resources Inventory and its relationship to existing measures of stress and coping. In G. S. Gates & M. Wolverton (Eds.), Toward wellness: Prevention, coping, and stress (pp. 3–37). Green-wich, CT: Information Age.

McCarthy, C., Lambert, R., & Brack, G. (1997). Structural model of coping, appraisals, and emotions after relationship breakup. Journal of Counseling and Development, 76, 53–64.

McGuire, W. H. (1979). Teacher burnout. Today’s Education, 68(4), 5.Moriarty, V., Edmonds, S., Blatchford, P., & Martin, C. (2001). Teaching

young children: Perceived satisfaction and stress. Educational Research, 43, 33–46.

National Education Association. (1979). Nationwide teacher opinion poll. Washington, DC: Author.

No Child Left Behind Act of 2001, Pub. L. No. 107-110, 2204 (2002).Pierce, C. B., & Molloy, G. N. (1990). Psychological and biographical dif-

ferences between secondary school teachers experiencing high and low levels of burnout. British Journal of Educational Psychology, 60, 37–51.

Pratt, J. (1978). Perceived stress among teachers: The effects of age and background of the children taught. Educational Review, 30, 3–14.

Rogers, C. R. (1951). Child-centered therapy. Boston: Houghton Mifflin.Rosenberg, M. (1965). Society and the adolescent self-image. Princeton, NJ:

Princeton University Press.Rosenberg, M., & Simmons, R. G. (1971). Black and white self-esteem: The

urban school child. Washington, DC: American Sociological Association.Sapolsky, R. M. (1998). Why zebras don’t get ulcers: An updated guide to

stress, stress-related diseases, and coping. New York: W. H. Freeman.Schaufeli, W. B., & Enzmann, D. (1998). The burnout component to study

and practice. London: Taylor & Francis.Travers, C. J., & Cooper, C. L. (1996). Teachers under pressure: Stress in the

teaching profession. London: Routledge.

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JER Among Those PresentMIDO CHANG (mchang@vt.edu) is an assistant professor in the educational research and evaluation program at Virginia Polytechnic and State University. Her current research focuses on longitudinal growth and multilevel models exploring educational policy issues related to the academic achievement of educa-tionally disadvantaged students.

SONJA DEKKER (sonjalh@clear.net.nz) is a statis-tical analyst for Statistics New Zealand as part of the education team. Her current research involves inves-tigating student loan and allowance data. RONALD FISCHER (ronald.fischer@vuw.ac.nz) is a senior lecturer at Victoria University of Wellington. He is currently the principal investigator on a 15-country project investigating the interaction between cultural values and organizational practices on helping and creativity behavior.

ANNE C. BLACK (anne.black@yale.edu) is an asso-ciate research scientist in the Department of Psychia-try at Yale University. Her current research interests include statistical modeling of variables related to stu-dent achievement and the effects of missing data on the accuracy of statistical inferences. CATHERINE A. LITTLE (catherine.little@uconn.edu) is an assistant professor of educational psychology at the University of Connecticut. Her current research interests involve professional development, teacher talent development, and curriculum differentiation. D. BETSY MCCOACH (betsy.mccoach@uconn.edu) is an assistant professor of educational psychology at the University of Connecti-cut. Her research interests include hierarchical linear modeling, instrument design, factor analysis, structural equation modeling, longitudinal analysis, and quantita-tive research methodology. JEANNE H. PURCELL (jeanne.purcell@ct.gov) is a consultant to the Con-necticut State Department of Education for gifted and talented education and the director of UConn Mentor Connection. DEL SIEGLE (del.siegle@uconn.edu) is an associate professor of Educational Psychology at the University of Connecticut. His research interests involve web-based instruction, motivation of gifted stu-dents, and teacher bias in the identification of students for gifted programs.

DONNA CHIU (dchiu77@aol.com) is an English teacher in Rockville, MD. YODIT BERU (yodit.

beru@gmail.com) is a graduate student at the Uni-versity of Michigan School of Public Health. ERIN WATLEY (ewatley@umd.edu) is a graduate of the University of Maryland. SELAM WUBU (selam.wubu@gmail.com) is a graduate student in biol-ogy at the Pennsylvania State University. EMMA SIMSON (emma.simson@gmail.com) teaches social studies in Upper Marlboro, MD. ROBIN KESS-INGER (robin.a.kessinger@gmail.com) is a structural engineer for Bechtel Corporation in Frederick, MD. ANAHI RIVERA (anahir@umd.edu) and PAT-RICK SCHMIDLEIN (pschmidl@umd.edu) are graduates of the University of Maryland. ALLAN WIGFIELD (awigfiel@umd.edu) is professor and chair of the Department of Human Development at the University of Maryland. His current research interests include students’ motivation and achieve-ment and the development of reading motivation and reading comprehension.

BRACHA KRAMARSKI (kramab@mail.biu.ac.il) is a senior lecturer in the School of Education and the current head of mathematical teacher education at Bar-Ilan University in Israel. Her interests focus on mathematics education, metacognition, innovative learning methods, and teachers’ professional develop-ment. SARIT ZOLDAN (zoltan@mail.biu.ac.il) is a graduate of Bar-Ilan University in Israel.

MEGAN O’DONNELL (maodonn1@asu.edu) is pursuing a doctorate in family and human devel-opment at Arizona State University. Her research interests include the effects of hypothalamic- pituitary-adrenal axis function on health outcomes and coping abilities in adolescence. RICHARD G. LAMBERT (rglamber@uncc.edu) is a profes-sor in the Department of Educational Leadership at the University of North Carolina at Charlotte. His research interests include the evaluation of programs for young children, stress coping with an emphasis on teacher stress, and applied statis-tics. CHRISTOPHER J. MCCARTHY (chris.mccarthy@mail.utexas.edu) is a professor in the Department of Educational Psychology at the Uni-versity of Texas at Austin. He is the training director of the counseling psychology program and researches stress and coping in educational and health settings.

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