Microsoft Word - v23n43 fnl.doc Journal website: http://epaa.asu.edu/ojs/ Manuscript received: 7/21/2014 Facebook: /EPAAA Revisions received: 12/22/2014 Twitter: @epaa_aape Accepted: 2/24/2015 education policy analysis archives A peer-reviewed, independent, open access, multilingual journal Arizona State University Volume 23 Number 43 April 13th, 2015 ISSN 1068-2341 Identification of Elementary Teachers’ Risk for Stress and Vocational Concerns Using the National Schools and Staffing Survey Richard G. Lambert University of North Carolina at Charlotte Christopher J. McCarthy University of Texas at Austin Paul G. Fitchett University of North Carolina at Charlotte & Sally Lineback Jenson Reiser University of Texas at Austin Citation: Lambert, R. G., McCarthy, C., Fitchett, P. G., Lineback, S., & Reiser, J. (2015). Identification of elementary teachers’ risk for stress and vocational concerns using the national schools and staffing survey. Education Policy Analysis Archives, 23(43). http://dx.doi.org/10.14507/epaa.v23.1792 Abstract: Transactional models of stress suggest that elementary teachers who appraise classroom demands as higher than classroom resources are more vulnerable to stress and likely to experience vocational concerns. Previous research using the Classroom Appraisal of Resources and Demands (CARD), a measure designed to assess teacher perceptions of classroom demands and resources, has epaa aape Educational Policy Analysis Archives Vol. 23 No. 43 2 supported transactional models with local samples. The current study replicated this previous research with two waves of large nationally representative data from the Schools and Staffing Survey (1999-2000 and 2007-2008). Theoretically-predicted differences were found, suggesting that an understanding of individual elementary teachers’ perceptions of demands and resources in the classroom could have important implications for policy and research aimed at addressing teachers’ vocational concerns. Keywords: teacher; stress; appraisals; vocational concerns; job satisfaction; retention El Uso de las N a t i o n a l S c h o o l s a n d S t a f f i n g S u r v e y para Identificar el Riesgo de Estrés y Preocupaciones Profesional de Maestros de Primaria Resumen: Los modelos transaccionales de estrés sugieren que los maestros de primaria que consideran que las demandas de aula son mayores que los recursos que reciben se enfrentan a un mayor riesgo de estrés y son más propensos a tener inquietudes vocacionales. La investigación anterior utilizando la Evaluación de los Recursos y la Demanda en el Aula (CARD por sus siglas en Inglés), un sistema diseñado para evaluar la opinión de los profesores sobre las demandas y recursos, es compatible con los modelos transaccionales con muestras locales. Esta investigación replico la investigación anterior utilizando dos grupos de datos representativos a nivel nacional de las Schools and Staffing Survey (1999-2000 y 2007-2008). Se encontraron diferencias previstas en teoría, lo que sugiere que entender las opiniones individuales de los maestros de primaria sobre las demandas y recursos en el aula puede tener implicaciones importantes para la política educativa y de investigación que tiene como objetivo hacer frente a las preocupaciones de formación profesional de los docentes. Palabras-clave: los maestros; el estrés; opiniones; inquietudes vocacionales; satisfacción laboral; retención Usando o N a t i o n a l S c h o o l s a n d S t a f f i n g S u r v e y para Identificar o Risco de Estresse e Preocupações Vocacionais em Professores de Ensino Primário Resumo: Modelos transacionais de estresse sugerem que professores de ensino primário que consideram que as demandas da sala de aula são maiores do que os recursos que eles recebem enfrentam um risco maior de estresse e são mais prováveis de terem preocupações vocacionais. Pesquisas anteriores usando a Avaliação de Recursos e Demandas da Sala de Aula (CARD por sua sigla em inglês), um sistema criado para avaliar a opinião dos professores sobre demandas e recursos, apoia modelos transacionais com amostras locais. Esta pesquisa reproduziu a pesquisa anterior usando dois grupos de dados representativos nacionais da Schools and Staffing Survey (1999-2000 e 2007-2008). Diferenças teoricamente que tinham sido previstas foram encontradas, sugerindo que compreender as opiniões individuais de professores de ensino primário sobre demandas e recursos na sala de aula pode ter consequências importantes para políticas e pesquisas educativas que tem como objetivo lidar com preocupações vocacionais de professores. Palavras-chave: professores; estresse; avaliações; preocupações vocacionais; satisfação profissional; retenção Kyriacou and Sutcliffe (1977) defined teacher stress as “a response by a teacher of negative affect …as a result of the demands made upon the teacher in his role as a teacher” which is determined by “the degree to which the teacher perceives that he is unable to meet the demands made upon him” (p. 299). While this definition emphasizes teachers’ perceptions of the classroom, in subsequent years research has taken an education production function approach (Hanushek, 2008; Monk, 1988) by focusing on external workforce factors (Zellars, Hochwarter, & Perrewe´, 2004) such as having larger classes (French, 1993) and excessive administrative burdens (Lambert & Identification of Elementary Teachers’ Risk for Stress 3 Ullrich, 2012; Moriarty, Edmonds, Blatchford, & Martin, 2001). This approach is followed in research on teacher job satisfaction and retention research as well (cf. Ingersoll, 2001; Liu, 2007; Liu & Ramsey, 2008). The resulting line of inquiry follows the historical trend of educational policy analysis and research by examining “inputs” (class size, administrative climate) that are presumed to lead to certain teacher “outputs,” such as level of satisfaction and occupational commitment. This approach, while valuable, neglects consideration of the psychological factors associated with teachers’ everyday experience of their classrooms. Incorporating the predominant model of stress, transactional theory (Lazarus & Folkman, 1984), we conceptualize teacher stress as caused by a perceived imbalance of teachers’ classroom demands and resources. Meyer (2003) noted that early stress researchers such as Wheaton (1999) used an engineering analogy for stress, “explaining that stress can be assessed as a load relative to a supportive surface” (p. 675). How people appraise their “load” relative to support is a key determinant of vulnerability to stress and recent research has examined the role of appraisals that teachers make of their classroom (Chang, 2009; Chang & Davis, 2009; Kokkinos, Panayiotou, & Davazoglou, 2005). However, much of this research fails to capture the central proposition of transactional models: teacher perceptions of classroom demands vis-à-vis perceived classroom resources are what puts them at risk for stress (Moore, 2006). In other words, it is not appraisals of high demands alone that are hypothesized to lead to stress, but rather a teacher’s perceptions that the level of demands exceeds their perceived classroom resources. Accounting for such factors could lead to a better understanding of why some teachers are more vulnerable to stress than others when experiencing the same workforce realities. Lambert, McCarthy, O’Donnell, and Wang (2009) developed the Classroom Appraisal of Resources and Demands (CARD) to measure both classroom demands and resources with the goal of identifying which elementary teachers view demands as outstripping their classroom resources. The CARD was originally developed for elementary teachers because they are more likely than teachers at other levels to spend most of their workday in the same classroom with the same students, allowing for a more stable context in which demands and resources can be assessed (McCarthy, Lambert, O'Donnell, & Melendres, 2009). A recent meta-analysis of 18 CARD studies using a range of local samples of teachers (many of them elementary level) across various districts and states provided evidence that the CARD measures teachers’ appraisals of their classroom demands and resources reliably (McCarthy, Lineback, Lambert, Allender, Reiser, & Murphy, 2014). Further, the validity of the transactional approach for assessing elementary teachers’ risk for stress was supported with consistent findings in these studies that elementary teachers perceiving the highest levels of demands with respect to classroom resources were also likely to experience concerns related to student behaviors, report more job dissatisfaction, and less occupational commitment (McCarthy, Lambert, & Reiser, 2014). In other words, such teachers are more likely to report the symptoms associated with stress. This study examined whether transactional stress research with local samples of elementary teachers using the CARD can be replicated nationally. Fortunately, the Schools and Staffing Survey (SASS) dataset contains many items similar to the CARD Demands and Resources scale. Administered by the National Center for Education Statistics, SASS is the largest and most comprehensive data source available on teachers and schools (Ingersoll & Smith, 2003). Items from the SASS survey addressing similar classroom demands and resources to those measured in the CARD were identified, and this information was used to classify teachers according to stress vulnerability. In addition to surveying teachers about classroom demands and resources, which allows for a replication of the CARD classification strategy, the SASS also includes questions about teachers’ vocational concerns (specifically, questions about intentions to remain in teaching, job Educational Policy Analysis Archives Vol. 23 No. 43 4 security and job satisfaction), classroom characteristics (specifically, questions about class size and composition), and professional autonomy. Examination of whether teachers classified according to level of risk (i.e., vulnerability) for stress was associated with scores on these constructs was considered evidence of stress symptoms and therefore formed the basis for three main research questions investigated. Background Examining Teacher Perceptions Using the Transactional Model The CARD was developed to measure teachers’ appraisals of both classroom demands and resources in order to operationalize transactional models of stress (Lambert et al., 2009). Teachers are classified into three groups based on their responses to the CARD: (1) those perceiving classroom resources as greater than demands (labeled the Resourced group), (2) those perceiving classroom demands as equal to resources (labeled the Balanced group), and (3) those perceiving classroom demands as greater than resources (labeled the Demands group). According to transactional models of stress, this last group is theorized to most likely to experience stress symptoms (McCarthy, Lambert et al., 2014; McCarthy, Lineback et al., 2014). This process is represented in Figure 1. Figure 1. Hypothesized model of teacher risk for stress As can be seen in the Figure, elementary teachers appraising overall classroom resources as equal to, or exceeding classroom demands, are hypothesized as less vulnerable to stress symptoms. Such teachers are predicted to report higher levels of satisfaction and occupational commitment. As will be described further, a similar pattern for professional autonomy is hypothesized in this study. Identification of Elementary Teachers’ Risk for Stress 5 Conversely, teachers appraising overall classroom resources as insufficient for classroom demands are hypothesized to be most vulnerable to stress symptoms (McCarthy et al., 2009). As was noted above, a unique feature of the CARD is that it operationalizes transactional models by accounting for perceived imbalances in teachers’ classroom demands. This is accomplished by creating a score for each teacher based on the difference between the Demands and Resources scale scores. This is labeled an Appraisal Index, as it represents the teachers’ overall appraisal of whether their classroom resources are sufficient for the magnitude of classroom demands (McCarthy, Lambert et al., 2014). The Appraisal Index therefore serves as a measure of the extent to which teachers experience demand imbalances in their classroom at the level of specific demands and resources, allowing for a more granular understanding of their everyday classroom experience. In this approach to understanding teacher stress, appraisals are seen as central to understanding why some elementary teachers become dissatisfied with teaching and consider leaving the profession (Folkman & Moskowitz, 2004; McCarthy, Lineback et al., 2014). In the context of this study, it is expected that teachers classified in the Demands group will be more likely to report (a) being dissatisfied with their jobs, (b) more vocational concerns, and (c) lower levels of professional autonomy. Given that research with the CARD has only been conducted with local samples of elementary and secondary teachers (McCarthy, Lineback et al., 2014), an important question is whether support for transactional models using this methodology can be found in a national sample. The similarity of the SASS to variables investigated in CARD research allowed us to replicate of the classification strategy used to place teachers in the three Appraisal groups: Demands, Balanced, and Resourced. Both the 1999-2000 and 2007-2008 SASS surveys1 were used in this study because there is some evidence that increased high-stakes testing and accountability brought on by No Child Left Behind (NCLB) has led to increased stressors and demands on many teachers (Berryhill, Linney, & Fromewick, 2009; Grissom, Nicholson-Crotty, & Harrington, 2014). Utilizing the 2000 and 2008 surveys provided information about teachers’ perceptions of classrooms, both before and after implementation of the No Child Left Behind Act. The 2007-2008 timeframe was also important to include as it is contemporaneous with recent CARD studies (c.f. McCarthy et al., 2009; McCarthy, Lambert, Crowe, & McCarthy, 2010). The rationale for examining Appraisal group differences in risk for stress with SASS questions about teachers’ vocational concerns, classroom characteristics, and autonomy, which formed the three main research questions in this study, will be provided next. Teacher Vocational Concerns Ingersoll (2012) noted the United States currently has a significant teacher turnover problem, and labeled the phenomenon of early career teachers exiting as the “greening” of the field. Ingersoll also posited that this greening is mostly due to teacher dissatisfaction and the pursuit of other employment, despite new teachers being hired at an accelerated pace. This attrition rate is considerably higher than other professional occupations (Ingersoll, 2003) and has a detrimental impact on students, teachers, and the overall school climate (Béteille & Loeb, 2009; Guin, 2004; Hong, 2012; Johnson, Craft & Papay, 2012; Ronfeldt, Loeb, & Wyckoff, 2013). The greening problem may be explained, at least partially, by falling levels of teacher satisfaction. According to the Metlife Survey of the American Teacher (2012), teacher satisfaction has fallen to a 25-year low: only 39% of respondents report that they are very satisfied. In general, job satisfaction research conceptualizes the construct as either overall satisfaction (usually only one question on a survey), or as a construct involving multiple components, including satisfaction with 1We will hereafter refer to these datasets as the 2000 SASS and the 2008 SASS. Educational Policy Analysis Archives Vol. 23 No. 43 6 salary, promotion, working conditions, benefits, and organizational climate (Koeske, Kirk, Koeske, & Rauktis, 1994; Liu & Ramsey, 2008). Not surprisingly, research using the SASS has consistently demonstrated that satisfaction is related to both intentions to leave and attrition itself. Ingersoll (2001) used the 1990-1991 SASS and the 1991-1992 Teacher Follow-Up Survey to show that job dissatisfaction, or the desire to pursue other employment, accounted for most of the variance in why teachers left their teaching positions. Another more recent study using SASS data found that a teacher’s job satisfaction was the most significant predictor of a teacher’s intentions to stay in teaching (Tickle, Chang, & Kim, 2011). Surprisingly, however, we found scant research using the SASS to evaluate the role of stress in teacher dissatisfaction or intention to leave the field. Grissom et al. (2014) used the SASS data to investigate teacher work environments across several administrations of the SASS and defined teacher demands as the number of hours in the week teachers spend working and support from the school, but did examine teacher resources. Interestingly, they found that while teachers’ reported weekly work increased 2 hours between 2000 and 2004 (just before No Child Left Behind was enacted), work hours leveled off between 2004 and 2008. This suggests teacher work hours have not necessarily increased since the Act was implemented. Transactional theorists would suggest that teachers’ appraisals of the classroom environment could explain why some teachers become dissatisfied and make plans to leave the profession (McCarthy, Lineback, et al., 2014). A primary question in this study, therefore, is whether teachers classified in the Demands group report more vocational concerns, which are defined as teachers’ dissatisfaction with, and intention to leave, the teaching profession (McCarthy, Lambert et al., 2014). Research using the CARD (McCarthy, Lineback, et al., 2014) with local samples has consistently demonstrated that teachers classified in the Demands group report more job dissatisfaction and lowered occupational commitment (Lambert, McCarthy, McCarthy, Crowe, & Fisher, 2012; McCarthy et al., 2009; McCarthy, Lambert, O’Donnell, Villarreal, & Melendres, 2012; McCarthy, Lambert et al., 2014). Further, although based on correlational analyses, one study found that teachers classified in the Demands group reported lowered satisfaction, which in turn was associated with more plans to leave the profession (McCarthy, Lambert, Crowe, & McCarthy, 2010). In other words, teachers’ appraisals of high demand vis-à-vis their resources could be antecedent to, and possibly be the reason for, higher levels of dissatisfaction. Therefore a primary goal of this study was replication of our findings connecting teacher’s risk for stress and vocational concerns with the SASS. Classroom Structural Characteristics and Student Behavioral Tendencies Though salary is frequently referenced as a substantial predictor of where and how long one remains in the classroom (Guarino, Santibãnez, & Daley, 2006; Hanushek & Rivikin, 2007), Béteille and Loeb (2009) note in their review of educational policy literature that “non-wage characteristics” are important to consider in determining professional trajectory of teachers. Research has specifically connected classroom working conditions and climate to teacher satisfaction, mobility, and attrition (Ingersoll, 2001; Johnson, Berg, & Donaldson, 2005; Simon & Johnson, 2013). Classroom management issues, particularly with respect to student behavior, is a common source of teacher stress (Chang, 2009; Eskridge & Coker, 1985; Lewis, Roache, & Romi, 2011; Sutton, Mudrey-Camino, & Knight, 2009). Here again, it is important to understand which teachers are most vulnerable to stress caused by classroom factors: as Chang asked with respect to stress caused by disruptive behaviors, “how does one teacher manage to survive while another is depleted by it?” (Chang, 2009, p. 202). Research using the CARD has demonstrated that teachers in the Demands group experience their classrooms differently (McCarthy, Lineback et al., 2014): they perceive more challenges due to Identification of Elementary Teachers’ Risk for Stress 7 student behavior and tend to report larger classroom sizes. In this replication study, we asked if appraisal group differences (Demands, Balanced, and Resourced) could be found in teachers’ self- reports about classroom characteristics and student behavioral characteristics contained in the 2000 and 2008 SASS. Both the 2000 and 2008 SASS datasets included numerous questions about teachers’ classroom characteristics and the behavioral tendencies of their students (class size, students with learning issues, students with attendance issues, students with problem behaviors, having been attacked or threatened, satisfied with class size, and wasting time as a teacher) and previous studies have examined whether classroom characteristics are linked to teacher turnover. For example, Feng (2010) utilized the 2000 SASS dataset along with a state data set from Florida to show that higher levels of teacher-specific disciplinary incidents were associated with greater levels of teacher turnover. Likewise, Ingersoll and May (2012) found that for both math and science teachers, the incidence of student discipline problems was positively associated with teacher turnover. Examining class size, Schcrff and Hahs-Vaughn (2008) indicated that a minority (40%) of SASS-surveyed English teachers were satisfied with their class size. In a study of teachers in Florida using a statewide data set, teachers who were less experienced (defined as 1-5 years of teaching) had higher percentages of students with Individualized Education Plans and Language Education Plans (Feng, 2010). Once again, however, stress has not been examined as a possible factor in SASS research establishing connections between classroom variables and vocational concerns. As was noted, studies using the CARD have explored the link between stress and classroom factors by examining whether Demands teachers’ classroom characteristics differ in significant ways from Resourced and Balanced teachers. CARD research on this topic has provided mixed findings: Lambert, McCarthy et al. (2012) found that teachers classified as Resourced reported smaller classrooms and teachers in the Demands group reported greater percentages of students with learning disabilities, problem behaviors, and poor attendance. However, while Lambert, McCarthy, O’Donnell, and Melendes (2007) also found that teachers classified in the Demands group reported more students with problem behaviors and learning disabilities, they found no differences in class size or reported percentages of students who were English language learners or had poor attendance. Given such equivocal findings using the CARD, and the lack of research on teacher stress with the SASS, the current study sought to examine whether differences in classroom characteristics and student behavioral tendencies exist between teachers classified in each of the Appraisal groups using SASS data. Teacher Autonomy SASS items related to teacher autonomy allowed for an extension of teacher stress research with an important construct not addressed in prior transactional stress CARD studies. A teacher’s sense of autonomy at work, which entails pedagogical, organizational, principle, and routine decision-making (Friedman, 1999), correlates highly with job satisfaction and other teacher attitudes (Pearson, 1998). Lam and Yan (2011) found that professional autonomy significantly influenced job satisfaction and teaching motivation. Research by Pearson and Moomaw (2005) examined the relationship between teacher autonomy and job stress, work satisfaction, empowerment, and professionalism, and found that as teachers’ autonomy over curriculum increased, job stress decreased. Additionally, Jiang (2005) found that involving teachers in curriculum reform facilitated teachers’ autonomy and reduced levels of burnout. Research using the SASS has examined two types of autonomy variables: school influence and classroom control. Though they have varying names in the literature, researchers have typically used the same or similar questions from the SASS in order to develop scales around these constructs (e.g. Ingersoll & May, 2012; Jackson, 2012; Liu, 2007). Educational Policy Analysis Archives Vol. 23 No. 43 8 School influence. Research on school influence using SASS data defines school influence as the perception that teachers have over school policy decisions and involves items relating to teachers’ perceived influence over school-wide issues such as hiring, policies, and non-teaching related duties (Jackson, 2012). Higher levels of school influence have been associated with a greater likelihood of teachers staying in their current positions than either to move schools or leave teaching (Jackson, 2012), with higher retention of specifically math and science teachers (Ingersoll & May, 2012), and with greater intentions of remaining in the teaching profession (Sedivy-Benton, Boden, & McGill, 2012). Liu (2007) also found that having school influence rapidly decreases the attrition rate for first year teachers. Lastly, Price and Collett (2012) conducted a structural equation modeling study using data from elementary teachers in the 2004 SASS dataset. They uncovered a construct operationalized as interdependence (which uses the same questions on the SASS that others have termed “school influence”) was positively related to commitment to stay in the profession directly and also through the additional variables of increased interaction with colleagues, positive affect, enthusiasm, and satisfaction. Classroom control. Classroom control, also called instructional autonomy, is commonly defined as a teacher’s sense of authority and control over her or his own classroom decision-making, including both teaching and testing (Pearson & Hall, 1993; Pearson & Moomaw, 2005). Ingersoll and May (2012) found that for math teachers, classroom control was the single greatest predictor of a teacher remaining in the same teaching position, higher than school influence. Sedivy-Benton et al. (2012) found that for teachers responding in the 2008 SASS dataset, classroom control was positively associated with intentions of remaining in the teaching profession. Grissom et al. (2014) found that feelings of classroom control have increased overall from 1994-2008, but classroom control has fallen between 2004 and 2008. They also found evidence that NCLB positively affected perceptions of classroom control between 2000 and 2004. Given that teacher autonomy has not been explored in previous CARD research, the current study examined possible differences in school influence, classroom control, and an overall composite of teacher autonomy (school influence plus classroom control) among the three Appraisal groups. For teachers in the 2000 SASS dataset, both school influence and classroom control were examined. Given that the 2008 SASS did not include the questions comprising the school influence scale, we examined only classroom control for that data set. Goals of the Current Study The current study was designed to replicate the three-group classification system used in previous CARD research (Demanded, Balanced, and Resourced) with elementary teachers in the SASS data set. Three questions guided the research: 1. Are Appraisal group differences (Demands, Balanced, and Resourced) observed in questions regarding teachers’ perceived vocational concerns contained in the 2000 and 2008 SASS (specifically, questions relating intentions to remain in teaching, job security and job satisfaction)? 2. Are Appraisal group differences (Demands, Balanced, and Resourced) observed in questions regarding teachers’ classroom characteristics and student behavioral characteristics contained in the 2000 and 2008 SASS? 3. Are Appraisal group differences (Demands, Balanced, and Resourced) observed in questions reporting teachers’ perceived autonomy contained in the 2000 and 2008 SASS? Identification of Elementary Teachers’ Risk for Stress 9 Methods Participants and Materials The participants in this study were elementary teacher respondents to the 2000 and 2008 Schools and Staffing Survey (SASS). As was noted previously, the CARD was originally developed with elementary teachers given their relatively intact classrooms. CARD surveys also include questions about teacher demographic and professional background, certification and training, and professional development activities, and this type of information is summarized for the elementary teacher respondents from the SASS in this study in Table 1. Extensive sets of questions also address classroom organization, available resources, assessment activities, working conditions, school policy and decision-making, and general employment information. Both waves of the SASS used a complex multi-stage sampling procedure in which buildings were sampled and then samples of teachers were selected from within each sampled school. The SASS was designed to create a nationally representative sample of teachers and to collect data regarding their perceptions of school climate, overall employment and working conditions, and descriptive data about school contexts throughout the nation (NCES, 2007). Low incidence groups of teachers were oversampled. Since many, though not all, previous CARD studies included full-time elementary school regular classroom teachers, the full SASS teacher data file was reduced to a sample of full-time public school elementary teachers (n=9,300).2 Weighted percentages are reported using the normalized version of the final teacher weight to adjust the sample to be nationally representative of the teacher population at the time the survey responses were collected. Procedures First, our research team reviewed items from the Classroom Appraisal of Resources and Demands (CARD) along with items from the SASS Public School Teacher Questionnaire in order to identify items with theoretical, conceptual, and thematic similarity of content. A total of 21 SASS items were identified by overall thematic content as possible matches to the Demands items from the CARD in the 2000 SASS, and 13 items in 2008 SASS (see Appendix B for a list of all items from the SASS selected to match the Demands and Resources scales from the CARD). A total of 15 SASS items were identified as possible matches to the content of items from the Resources section of the CARD in 2000 SASS and 11 items in 2008 SASS and were used to form the Resources scale (see Appendix B). 2 2All sample sizes were rounded to the nearest 10 in keeping with NCES policies of data disclosure. Educational Policy Analysis Archives Vol. 23 No. 43 10 Table 1 Demographic Characteristics of the Samples 1999-2000 2007-2008 Weighted Weighted Demographic variable Category % % Urbanity of school Central city 29.3 27.2 Urban fringe 50.2 49.1 Small town or rural 20.5 23.6 Census region Northeast 18.4 18.9 Midwest 22.0 21.4 South 38.1 40.8 West 21.5 19.0 Ever taught in a private school Yes 12.8 11.0 No 87.2 89.0 Years of teaching experience Less than two 7.0 11.4 Two or more 93.0 88.6 Highest educational degree Bachelor's only 58.4 49.6 Graduate degree 41.6 50.4 Union member Yes 80.7 76.8 No 19.3 23.2 Gender Male 9.7 15.6 Female 90.3 84.4 Race Native American 0.8 1.1 Asian or Pacific Islander 2.4 1.9 African American 8.7 7.9 European American 88.0 90.1 Hispanic Yes 6.6 7.9 No 93.4 92.1 Next, we conducted a content validity study in which we surveyed a panel consisting of educational research experts (n=5), elementary teachers (n=3), and school administrators (n=4). The 12 member panel was provided with the elementary version of the CARD and the proposed items from the SASS. The panel members were asked to indicate the extent to which they agreed that CARD items measured classroom Demands and Resources respectively. They were also asked the extent to which they agreed that the proposed SASS items focused on similar themes to those addressed by the CARD. The panelists were also asked a series of open-ended questions focusing on their general opinions about classroom resources and demands for elementary teachers. Almost all of the panelists (91.67%) answered “Agree” or “Strongly Agree” to the question about whether CARD Demands items address classroom demands. Similarly, 91.67% of the panelists answered “Agree” or “Strongly Agree” to the question about whether CARD Resources items address classroom resources. A majority of panelists (72.73%) answered “Agree” or “Strongly Agree” to the Identification of Elementary Teachers’ Risk for Stress 11 question about SASS demands items being thematically consistent with CARD Demands items. Similarly, a majority of panelists (83.33%) answered “Agree” or “Strongly Agree” to the question about SASS resource items being thematically consistent with CARD Demands items. Based on these results, we proceeded with the development of SASS Demands and Resources scales. A specific case of the one parameter item response theory (IRT) model, the Rasch rating scale model, was used through the WINSTEPS software package to combine the SASS responses to the identified items for each data set into scale scores and estimate ability parameters for each teacher. The scores were scaled to have a mean of 500 and a standard deviation of 100. The resulting Demands and Resources scale scores were moderately correlated in both waves (r2000=-.404; r2008=- .479). The two waves of data provided scores on the SASS Demands scales that were adequately reliable (α2000=.898, α2008=.870). The two waves of data provided scores on the SASS Resources scales that were adequately reliable (α2000=.837, α2008=.832). In order to match the previous protocol for classifying teachers using the CARD, an Appraisal index score was created based on the difference between the Demands and Resources scale scores in both waves (reliability2000=.906; reliability2008=.900). This reliability coefficient is based on the reliability of a difference score. Also following the CARD scoring protocol, a 95% confidence interval was formed around no difference between the Demands and Resources scale scores (McCarthy, Lambert et al., 2014). Teachers who provided difference scores greater than the upper limit of this interval were classified in the Demands group, those who provided difference scores below the lower limit of the confidence interval were classified in the Resourced group, and those with difference scores within the interval were classified in the Balanced group. The third goal of this study also necessitated scale creation, and SASS items that address teacher perceptions about their autonomy in the school and classroom were formed. For 2000 survey, items reporting teachers’ perceptions on their influence over school-wide issues such as staffing, budgeting, and instructional policy were used to form the School Influence (Cronbach’s alpha=.807) scale score using Rasch IRT modeling. Both surveys include items that address teachers’ perception of control over instructional materials, teaching strategies, and student discipline issues within the classroom. Through the Rasch model, these items were used to form the Classroom Control scale scores (Cronbach’s α2000 =.759; Cronbach’s α2008 =.726) scale score. The Rasch model was also used to form the Total Autonomy scale score (Cronbach’s alpha=.830), a total score for the 2000 SASS dataset only. Given the complex, multi-stage sampling procedures, the purposeful oversampling, and the varying non-response rates across subgroups of teachers, specialized statistical procedures were necessary in order to both weight the results to be nationally representative and to calculate the appropriate standard errors and significance tests. The AM software was used for these purposes. Throughout the results section whenever robust percentages, means, or standard errors are referred to, these values were obtained from AM by using the final teacher sampling weights and the replicate weights with the Balanced Repeated Replication estimation method. Results Teachers were classified into groups based on their Appraisal index score according to the CARD scoring protocol, as described in the previous section, resulting in the following sample sizes in the three groups the 2000 data: Resourced n=2,860 (30.7%), Balanced n=4,020 (43.2%), and Demands n=2,420 (26.1%). Classification frequencies were similar in the 2008 data: Resourced n=2,900 (24.2%), Balanced n=5,930 (49.5%), and Demands n=3,150 (26.3%). These national data suggest approximately a quarter of elementary teachers can be considered as at risk for occupational Educational Policy Analysis Archives Vol. 23 No. 43 12 stress. These values reflect the results of the CARD classification strategy when applied to the total sample of teachers across each of the waves. The reported sample sizes may vary from these values in subsequent analyses due to missing data. Appraisal Group Differences Across Teachers’ Perceived Vocational Concerns Prior to examining our research questions, we investigated whether there were differences between the three teacher stress groups according to location of the teacher’s school. Using the 2000 SASS data, the weighted results indicate that there were statistically significant associations between membership in the three stress groups and both census region (χ2(6)=108.59, p<.000) and urbanicity (χ2(4)=217.55, p<.000) of school location. Of teachers working in urban schools, 34.3% of them were in the Demands group and 20.9% were in the Resourced group. In contrast, only 20.4% of teachers in suburban schools were in the Demands and 34.3% were in the Resourced group. Similarly, in rural schools 23.3% of teachers were in the Demands group and 27.9% were in the Resourced group. For teachers working in the Northeast, 35.9% were in the Resourced group and 22.3% were in the Demands group. A similar pattern was found in the Midwest where 32.5% were in the Resourced group and 19.9% were in the Demands group. However, in the South and West, the pattern was quite different. In the South, 27.4% were in the Resourced group and 27.7% were in the Demands group. In the West, 22.8% were in the Resourced group and 27.7% were in the Demands group. Similar patterns were found when using the 2008 SASS data. The weighted results indicate that there were statistically significant associations between membership in the three stress groups and both census region (χ2(6)=96.60, p<.000) and urbanicity (χ 2 (4)=424.03, p<.000) of school location. Of teachers working in urban schools, 38.3% of them were in the Demands group and 16.9% were in the Resourced group. In contrast, only 21.7% of teachers in suburban schools were in the Demands and 31.1% were in the Resourced group. Similarly, in rural schools 25.6% of teachers were in the Demands group and 23.0% were in the Resourced group. For teachers working in the Northeast, 32.1% were in the Resourced group and 24.0% were in the Demands group. In the Midwest where 25.7% were in the Resourced group and 24.0% were in the Demands group. In the South, 24.5% were in the Resourced group and 27.6% were in the Demands group. In the West, 22.2% were in the Resourced group and 31.9% were in the Demands group. We addressed the first research question by investigating Appraisal group differences in vocational concerns (see Table 2 for SASS items utilized in these analyses). Each of these SASS items was used as an outcome measure to test for differences between the three CARD Appraisal groups. Given previous findings with the CARD, we hypothesized that teachers in the Demands group would rate their occupational conditions more negatively than their colleagues in the other Appraisal groups. As can be seen in Table 2, there were statistically significant and large differences in the expected directions between the Demands and the two other Appraisal groups on outcomes for vocational concerns for both the 2000 and the 2008 data sets. Several of the SASS questions show in Table 2 focused specifically on retention issues, and teachers in the Demands group were much less likely to report they would become a teacher again (75.3% for 2000 SASS and 76.6% for 2008 SASS) than those classified in the Resourced group (94.3% for 2000 SASS and 94.5% for 2008 SASS) and much less likely to report they would return to teaching the next year (65.1% for 2000 SASS and 67.2% for 2008 SASS) than Resourced teachers (86.0% for 2000 SASS and 85.2% for 2008 SASS). Teachers in the Demands group were also more likely to agree or strongly agree that they were worried about their job security than their peers in the Balanced or Resourced group (see Table 2). Identification of Elementary Teachers’ Risk for Stress 13 SASS questions asking about satisfaction and wasting time as a teacher also revealed large differences between the Appraisal groups. While overall most teachers in both the 2000 and 2008 SASS reported they were at least somewhat satisfied with their jobs, an inspection of Table 2 reveals that the modal response of teachers in the Resourced and Balanced groups was “Strongly agree” while for Demand teachers it was “Somewhat agree.” While only the 2000 SASS included questions about satisfaction with class size and perceptions of wasting time as a teacher, once again the modal response of teachers in the Resourced and Balanced groups was “Strongly agree” while the Demands group was evenly split between “Strongly” and “Somewhat” agree for satisfaction with class size. Teachers in the Demands group were also much more likely to report feeling like they were wasting time as a teacher. Educational Policy Analysis Archives Vol. 23 No. 43 14 Table 2. Teacher Vocational Satisfaction by Appraisal Group 2000 SASS 2008 SASS Resourced Balanced Demands Resourced Balanced Demands Group Group Group Group Group Group Item Response n =2,310 n =3,880 n =2,090 n =3,090 n =5,660 n =3,230 Would become a teacher again Yes Weighted % 94.3 85.9 75.3 94.5 87.2 76.6 Robust se 0.67 0.62 1.29 0.66 0.67 1.35 No Weighted % 5.7 14.1 24.7 5.5 12.8 23.4 Robust se 0.67 0.62 1.29 0.66 0.67 1.35 Will return to teaching next year Yes Weighted % 86.0 77.1 65.1 85.2 78.3 67.2 Robust se 0.95 0.93 1.18 1.22 1.02 1.76 No Weighted % 14.0 22.9 34.9 14.8 21.7 32.8 Robust se 0.95 0.93 1.18 1.22 1.02 1.76 Worried about job Strongly Weighted % 5.0 7.7 15.3 3.0 6.6 14.8 security agree Robust se 0.63 0.70 1.06 0.57 0.68 1.38 Somewhat Weighted % 18.9 25.4 32.1 18.2 25.8 31.6 agree Robust se 1.06 0.96 1.24 1.23 1.02 1.56 Somewhat Weighted % 22.9 32.4 26.6 25.2 33.1 29.3 disagree Robust se 1.08 0.92 1.23 1.35 1.03 1.50 Strongly Weighted % 53.3 34.5 26.0 53.6 34.5 24.4 disagree Robust se 1.34 1.03 1.21 1.59 1.25 1.55 Identification of Elementary Teachers’ Risk for Stress 15 Table 2. (Cont’d) Teacher Vocational Satisfaction by Appraisal Group 2000 SASS 2008 SASS Resourced Balanced Demands Resourced Balanced Demands Group Group Group Group Group Group Item Response n =2,310 n =3,880 n =2,090 n =3,090 n =5,660 n =3,230 Satisfaction with being a teacher Strongly Weighted % 88.3 59.3 21.4 93.0 64.5 24.3 agree Robust se 0.88 1.22 1.11 0.88 1.18 1.34 Somewhat Weighted % 10.9 36.4 49.9 6.5 32.9 54.1 agree Robust se 0.85 1.13 1.44 0.86 1.13 1.36 Somewhat Weighted % 0.2 3.3 20.7 0.3 2.2 15.8 disagree Robust se 0.11 0.40 1.32 0.23 0.33 1.27 Strongly Weighted % 0.6 0.9 8.0 0.1 0.5 5.8 disagree Robust se 0.17 0.17 0.83 0.08 0.14 0.91 Satisfaction with class size* Strongly Weighted % 53.0 38.6 28.8 agree Robust se 1.40 0.92 1.38 Somewhat Weighted % 27.1 29.7 27.4 agree Robust se 1.00 0.84 1.35 Somewhat Weighted % 11.4 15.3 16.7 disagree Robust se 0.80 0.75 1.06 Strongly Weighted % 8.4 16.4 27.1 disagree Robust se 0.71 0.65 1.32 Educational Policy Analysis Archives Vol. 23 No. 43 16 Table 2. (Cont’d) Teacher Vocational Satisfaction by Appraisal Group 2000 SASS 2008 SASS Resourced Balanced Demands Resourced Balanced Demands Group Group Group Group Group Group Item Response n =2,310 n =3,880 n =2,090 n =3,090 n =5,660 n =3,230 Wasting time as a teacher* Strongly Weighted % 1.5 1.9 7.7 agree Robust se 0.28 0.28 0.82 Somewhat Weighted % 3.6 13.0 27.6 agree Robust se 0.52 0.71 1.42 Somewhat Weighted % 6.8 16.7 18.6 disagree Robust se 0.63 0.83 1.15 Strongly Weighted % 88.2 68.4 46.0 disagree Robust se 0.88 1.01 1.63 Note.* Denotes items that appeared on the 2000 SASS only Identification of Elementary Teachers’ Risk for Stress 17 Appraisal Group Differences among Classroom and Student Behavioral Characteristics Table 3 provides results for questions about whether teachers were ever threatened or attacked from the 2000 and the 2008 SASS data sets, and it is clear from these results that teachers classified in the Demands group were much more likely to report both. The 2000 SASS included questions about attendance problems (tardiness) and behavior problems (interruptions) (see Table 4). The following differences between the Demands and Resourced groups, reported as effect sizes, were found: tardy students (d = .711), and interruptions due to problem behaviors (d = .550). The 2008 SASS did not include these questions. Both the 2000 and the 2008 SASS data sets also included questions about classroom size, number of students with an Individualized Education Plan (IEP), and number of Limited English Proficiency (LEP) students. In Table 4, statistically significant differences between the three Appraisal groups are shown across each classroom variable for the 2000 SASS. All the differences indicated higher concentrations of demanding student behaviors and students with an IEP or LEP in the classrooms of Demands teachers. The following differences between the Demands and Resourced groups, reported as effect sizes, were found: class size (d = .142), children with an IEP (d = .182), children with an LEP (d = .396). The 2008 SASS also included these questions, but differences were only found for children designated LEP (d = .467). Educational Policy Analysis Archives Vol. 23 No. 43 18 Table 3. Teacher Experience with Threatening Behavior by Appraisal Group 2000 SASS 2008 SASS Resourced Balanced Demands Resourced Balanced Demands Group Group Group Group Group Group Item Response n =2,310 n =3,880 n =2,090 n =3,090 n =5,660 n =3,230 Ever threatened Yes Weighted % 7.1 14.2 28.3 6.7 15.2 32.3 Robust se 0.62 0.71 1.28 0.85 0.96 1.38 No Weighted % 92.9 85.8 71.7 93.3 84.8 67.7 Robust se 0.62 0.71 1.28 0.85 0.96 1.38 Ever attacked Yes Weighted % 7.6 11.1 19.7 5.9 11.1 18.4 Robust se 0.68 0.60 1.20 0.71 0.69 1.16 No Weighted % 92.4 88.9 80.3 94.1 88.9 81.6 Robust se 0.68 0.60 1.20 0.71 0.69 1.16 Identification of Elementary Teachers’ Risk for Stress 19 Table 4. Classroom Structural Characteristics and Behavioral Tendencies Resourced Balanced Demands Demands Group Group Group vs. (R) (B) (D) Resourced 2000 SASS n =1,810 n =3,060 n =1,660 Contrasts F Effect Size Class size Unweighted mean 20.247 20.626 20.844 Weighted mean 20.843 21.084 21.737 D > R,B 3.789* 0.142 Robust sd 5.602 14.307 6.944 Robust se 0.158 0.509 0.279 Students with an IEP Unweighted mean 2.649 2.896 3.367 Weighted mean 2.687 2.929 3.353 D > B > R 8.807*** 0.182 Robust sd 3.293 3.502 4.034 Robust se 0.093 0.078 0.119 LEP students Unweighted mean 1.592 2.426 3.636 Weighted mean 1.453 2.153 3.547 D > B > R 27.624*** 0.396 Robust sd 3.793 4.86 6.547 Robust se 0.107 0.118 0.278 Tardy students Unweighted mean 1.867 2.639 3.7 Weighted mean 1.869 2.706 3.885 D > B > R 121.411*** 0.711 Robust sd 1.957 3.107 3.565 Robust se 0.06 0.07 0.133 Interruptions due to problem behaviors Unweighted mean 10.598 14.539 19.159 Weighted mean 11.017 15.055 20.428 D > B > R 58.724*** 0.55 Robust sd 14.307 16.231 19.767 Robust se 0.509 0.37 0.676 Educational Policy Analysis Archives Vol. 23 No. 43 20 Table 4. (Cont’d) Classroom Structural Characteristics and Behavioral Tendencies Resourced Balanced Demands Demands Group Group Group vs. (R) (B) (D) Resourced 2008 SASS n =1,652 n =3,060 n =1,465 Contrasts F Effect Size Class size Unweighted mean 20.194 20.308 20.237 Weighted mean 20.489 20.425 20.32 0.248 -0.027 Robust sd 6.371 6.656 6.01 Robust se 0.282 0.208 0.334 Students with an IEP Unweighted mean 2.534 2.737 2.876 Weighted mean 2.58 2.78 2.68 0.935 0.047 Robust sd 3.116 3.141 3.096 Robust se 0.143 0.093 0.137 LEP students Unweighted mean 1.213 1.939 2.912 Weighted mean 1.673 2.942 3.928 D > B > R 21.978*** 0.467 Robust sd 3.682 5.242 5.864 Robust se 0.186 0.215 0.323 Note. * - p<.05, ** - p<.01, *** - p<.001. Identification of Elementary Teachers’ Risk for Stress 21 Table 5. Autonomy Scale Scores by Appraisal Group Resourced Balanced Demands Demands Group Group Group vs. (R) (B) (D) Resourced 2000 SASS n =2,310 n =3,880 n =2,090 Contrasts F Effect Size School Influence Unweighted mean 542.429 502.808 447.432 Weighted mean 537.573 495.981 440.510 D > B > R 341.578*** -1.073 Robust sd 86.309 87.818 94.769 Robust se 2.029 1.491 3.023 Classroom Control Unweighted mean 538.813 499.862 465.124 Weighted mean 532.975 494.005 454.618 D > B > R 215.505*** -0.825 Robust sd 101.561 92.679 86.990 Robust se 2.723 1.877 2.296 Total Autonomy Unweighted mean 544.076 502.058 450.300 Weighted mean 539.164 495.763 441.069 D > B > R 415.143*** -1.148 Robust sd 87.207 78.082 83.393 Robust se 2.177 1.623 2.495 (R) (B) (D) 2008 SASS n=3,150 n=5,930 n=2,900 Contrasts F Effect Size Classroom Control Unweighted mean 533.377 500.476 469.020 Weighted mean 527.209 493.016 459.627 D > B > R 114.875*** -0.762 Robust sd 98.740 94.590 94.705 Robust se 3.517 2.510 3.774 Note. * - p<.05, ** - p<.01, *** - p<.001. Educational Policy Analysis Archives Vol. 23 No. 43 22 Appraisal Group Differences and Teachers’ Perceived Autonomy As was noted above, items examining Classroom Control were available for both the 2000 and 2008 SASS (see Appendix A). Noted in Table 5, Demands group teachers reported statistically significantly lower scores in the 2000 SASS on all three measures as compared to Resourced teachers: School Influence (d = -1.073), Classroom Control (d = -.825), and Total Autonomy (d = -1.148); further, the same pattern of difference was found for Classroom Control for the 2008 SASS (d = -.762). Discussion Two important patterns to the results of this study are worthy of note. First, the results were not appreciably different across the 2000 SASS and the 2008 SASS, suggesting that the pattern of results in this study have not changed appreciably during the intervening years. Grissom et al. (2014) also found no differences in job satisfaction reported by teachers in SASS surveys before and after NCLB. Second, this pattern of findings replicates previous research with the CARD using local samples of teachers; specifically teachers classified in the Demands group had lower levels of job satisfaction and were more likely to be planning to leave the profession (AUHTOR, 2012b, 2014a). The findings were more equivocal with respect to Appraisal group classifications and classroom characteristics. While previous CARD research using local samples of teachers has indicated that teachers classified in the Demands group report students with problem behaviors and learning disabilities in greater frequency (AUHTOR, 2007a), in this study a consistent pattern of theoretically-predicted group differences was found only in the 2000 SASS. However, the 2008 SASS only contained items on class size and percentage of students with an IEP or LEP. Statistical significance across groups was only found for the LEP percentage. It is important to note that such associations, statistically significant or not, do not imply that students with special needs are the cause of teacher stress. Rather, these patterns, especially for the 2000 SASS, suggest that classroom characteristics are an important factor in teachers’ everyday experience of their work environment. As noted in previous studies (Béteille & Loeb, 2009; Boyd, Lankford, Loeb, & Wyckoff, 2005; Hanushek & Rivkin, 2007), school context can have a significant effect on teachers’ professional trajectory and vocational concerns. Specifically, more recent research suggests that working conditions, rather than the student demographics, are better predictors of teacher attrition and mobility (Johnson, et al., 2012; Simon & Johnson, 2013). While not the primary focus of this study, findings from our analyses suggest that particularly challenging school environments frequently associated with high minority, high poverty schools might place teachers at risk for stress—thus potentially exacerbating teacher mobility and attrition. Research question three extended previous research by examining classroom variables not investigated in previous research with the CARD. Again, we found that the Demands group differed in important ways from the other groups. The results provided in Table 5 support previous research examining teacher autonomy and its association with teacher welfare and stress (Jiang, 2005; Pearson & Moomaw, 2005). Hargreaves (1994) suggested that taking measures to increase the professionalism of teaching, particularly in teachers’ control over instructional decision-making, may reduce teacher pressure, stress, and the perception of the inadequacy of time, a suggestion supported in this study. Providing opportunities for teachers to take on leadership roles within the school is associated with improved commitment to the profession, perceived autonomy, and efficacy (Smylie & Denny, 2001; York-Barr & Duke, 2004). Specifically, fostering environments of distributed leadership that give teachers greater professional responsibilities and control over their workplace Identification of Elementary Teachers’ Risk for Stress 23 environments has the potential to improve workplace climate and alleviate teacher stress (Hulpia, Devos, & Rosseel, 2010; Spillane, 2012). These results support evidence than has been found in previous research with the CARD – teachers classified in the Demands group have different perceptions of their professional environment and work under conditions substantially different from other teachers. The results suggest that if administrators, and society at large, is interested in retaining a higher proportion of their teachers, it can be important to address perceived imbalances in workloads for teachers. In other words, considering how teachers perceive their workplace climate can be a valuable asset for school- and district-level leaders interested in retention and curtailing mobility. Instead of pursuing unilaterally “top-down” educational mandates that do not take into account how the aims align with the capabilities of teachers, policymakers should consider pursuing “bottom-up” approaches toward policy implementation (Cohen & Moffitt, 2010; Cohen, Moffitt, & Goldin, 2007). The importance of administrators and other support professionals developing strategies to professionally enfranchise teachers so that they may take part in decision-making processes is implied from our findings. For example, involving teachers in the process of assigning children to classrooms, giving them the freedom to make their own decisions regarding curriculum and instruction (Jiang, 2005) and including them in hiring decisions can offer teachers an enhanced sense of professionalism and autonomy; thus potentially reducing occupational stress. Furthermore, the framework of understanding teachers’ perceptions suggested by transactional models of stress can guide administrators through a process of carefully evaluating the areas in which their teachers feel the need for more resources, do not feel that existing resources are helpful enough, and areas where teachers may not recognize or be fully utilizing existing resources. Similarly, these findings suggest that administrators make efforts to identify classroom characteristics that teachers are likely to perceive as most demanding and to those individual teachers who perceive an imbalance between resources and demands. Acknowledging which teachers are more at-risk for occupational stress can inform leadership on best to distribute resources among and within schools. Such bottom-up resourced-based incentives can contribute toward a stable professional climate and are potentially much more economical than wage-based policies, which have a mixed record in retaining teachers (Béteille & Loeb, 2009; Fowler, 2003). The results of this study also suggest that a more granular understanding of elementary teachers’ perceptions of demands and resources in their classroom could help explain why some teachers are more vulnerable to stress even when working under similar occupational conditions. The education production function approach (Hanushek, 2008; Monk, 1988) has been valuable in identifying external workforce factors such as school and administrative climate that are linked to trends such as teacher dissatisfaction, burnout, and turnover (Ingersoll, 2012; Tickle et al., 2011; Zellars, Hocwarter, & Perrewe´, 2004). External realities such as being in a lower performing school, lacking administrative support, and increased pressure related to student performance on standardized exams are clearly important to elementary teachers’ occupational well-being. However, our findings suggest that by looking at factors rooted in the perceived classroom experience of elementary teachers, we may be better able to understand the mismatch that some teachers experience and perhaps develop policies that address this imbalance. The identification of elementary teachers experiencing high demand levels vis-à-vis their resources could be critical in an era in which turnover is high and demands are unlikely to abate. The overall pattern of results in this study suggested that teachers classified as at risk for stress were also those most likely to be experiencing vocational concerns. Rather than measuring teacher stress in terms of its global sequalea such as lowered student achievement, job satisfaction, burnout, or intention to leave the profession, the CARD provides actionable feedback to teachers, administrators, and policy makers regarding the specific classroom demands and resources that are Educational Policy Analysis Archives Vol. 23 No. 43 24 at the root of the subjective perception and experience of stress for individual teachers and groups of teachers within schools. Moreover, it can help account for why some teachers persevere in the face of high demands, a burgeoning issue in the research of early-career educators (cf. Robertson- Kraft & Duckworth, 2014). Limitations and Future Directions A number of cautions should be observed in interpreting the results of this study. First, the results are based on responses to survey self-reported data. Therefore, considerations regarding the potential for measurement error should be considered in the interpretation of our research findings. Second, this exploratory study aimed to replicate previous CARD research using similar analyses and variable. It was therefore beyond the scope of this research to include multi-level, multivariate models that contained teacher and school control variables. Future research could examine the interaction of variables such as vocational concerns, autonomy, and particularly classroom characteristics, since the latter were not clearly linked to teacher stress in the 2008 SASS. Additional research is also warranted to examine building-level variance in teacher stress to determine if teachers nested within schools’ with similar characteristics vary in their stress levels compared to teachers in other schools. Multi-level models that include building, district, and even state policy and climate variables that were not included in the present study may offer additional evidences for the antecedents to and possible supports to prevent teacher stress. This is particularly important given recent findings, which emphasize the importance of building-level conditions in predicting turnover and mobility. Furthermore, causality among the patterns in the data should not be inferred given the absence of experimental designs. This caution is particularly important with respect to the pattern of findings using the 2000 and 2008 SASS – while examination of teacher responses at these two time intervals reveals important information, causality about effects of policies such as No Child Left Behind should not be inferred. These limitations suggest a number of avenues for future research. In addition to the Schools and Staffing Survey, the Teacher Follow-Up Survey and Beginning Teacher Longitudinal Study were conducted the following years with a subsample of respondents who both left and remained in the profession. Future research could utilize the classification system from this study to analyze whether teachers in the Demands group actually left the profession the following year or transferred schools. References Berryhill, J., Linney, J. A., & Fromewick, J. (2009). The effects of educational accountability on teachers: Are policies too stress provoking for their own good? International Journal of Education Policy and Leadership, 4(5), 1-14. Béteille, T., & Loeb, S. (2009). Teacher quality and labor markets. In G. Sykes, B. Schneider & D. N. Plank (Eds.), Handbook of educational policy research (pp. 598-612). New York, NY: Routledge. Boyd, D., Lankford, H., Loeb, S., & Wyckoff, J. (2005). Explaining the short careers of of high achieving teachers in schools with low performing students. American Economic Review, 95(2), 166-171. http://dx.doi.org/10.1257/000282805774669628 Cohen, D. K., & Moffitt, S. L. (2010). The ordeal of equality: Did federal regulation fix the schools?. Cambridge, MA: Harvard University Press. Cohen, David K., Susan L. Moffitt, and Simona Goldin. (2007) Policy and practice: The dilemma. American Journal of Education, 113(4), 515-548. http://dx.doi.org/10.1086/518487 Chang, M. L. (2009). An appraisal perspective of teacher burnout: Examining the emotional work of Identification of Elementary Teachers’ Risk for Stress 25 teachers. Educational Psychology Review, 21(3), 193-218. http://dx.doi.org/10.1007/s10648- 009-9106-y Chang, M. L., & Davis, H. A. (2009). Understanding the role of teacher appraisals in shaping the dynamics of their relationships with students: Deconstructing teachers’ judgments of disruptive behavior/students. In P. A. Schutz & M. Zembylas (Eds.), Advances in teacher emotion research: The impact on teachers’ lives (pp. 95-127). New York, NY: Springer. http://dx.doi.org/10.1007/978-1-4419-0564-2_6 Eskridge, D. H., & Coker, D. R. (1985). Teacher stress: symptoms, causes, and management techniques. Clearing House, 58, 387–390. Feng, L. (2010). Hire today, gone tomorrow: New teacher classroom assignments and teacher mobility. Education, 5(3), 278-316. http://dx.doi.org/10.1162/EDFP_a_00002 Folkman, S., & Moskowitz, J. T. (2004). Coping: Pitfalls and promise. Annual Review of Psychology, 55, 745-774. http://dx.doi.org/10.1146/annurev.psych.55.090902.141456 Fowler, R. C. (2003). The Massachusetts signing bonus program for new teachers: A model of teacher preparation worth copying? Education Policy Analysis Archives, 11(13), 1-24. http://dx.doi.org/10.14507/epaa.v11n13.2003 French, N. (1993). Elementary teacher stress and class size. Journal of Research and Development in Education, 26, 66-73. Friedman, I. A. (1999). Teacher-perceived work autonomy: The concept and its measurement. Educational and Psychological Measurement, 59(1), 58-76. http://dx.doi.org/10.1177/0013164499591005 Grissom, J. A., Nicholson-Crotty, S., & Harrington, J. R. (2014) Estimating the effects of no child left behind on teachers’ work environments and job attitudes. Educational Evaluation and Policy Analysis, 20(10), 1-20. http://dx.doi.org/10.3102/0162373714533817 Guarino, C. M., Santibãnez, L., & Daley, G. A. (2006). Teacher recruitment and retention: A review of the recent empirical literature. Review of educational research, 76(2), 173-208. http://dx.doi.org/10.3102/00346543076002173 Guin, K. (2004). Chronic teacher turnover in urban elementary schools. Educational Policy Analysis Archives, 42(12), 1-30. http://dx.doi.org/10.14507/epaa.v12n42.2004 Hanushek, E. A., & Rivkin, S. G. (2007). Pay, working conditions, and teacher quality. The Future of our Children, 17(1), 69-86. http://dx.doi.org/10.1353/foc.2007.0002 Hanushek, E. A. (2008). Education production functions. In S. N. Durlauf & L. E. Blume (Eds.), The new Palgrave dictionary of economics (pp.1-9). Basingstoke: U.K.: Palgrave Mcmillan. http://dx.doi.org/10.1057/9780230226203.0448 Hargreaves, A. (1994). Changing teachers, changing times: Teachers' work and culture in the postmodern age. New York, NY: Teachers College Press. Hong, J. Y. (2012). Why do some beginning teachers leave the school, and others stay? Understanding teacher resilience through psychological lenses. Teachers and Teaching: Theory and practice, 18(4), 417-440. http://dx.doi.org/10.1080/13540602.2012.696044 Hulpia, H., Devos, G., & Rosseel, Y. (2009). The relationship between the perception of distributed leadership in secondary schools and teachers' and teacher leaders' job satisfaction and organizational commitment. School Effectiveness and School Improvement, 20(3), 291-317. http://dx.doi.org/10.1080/09243450902909840 Ingersoll, R. (2001). Teacher turnover and teacher shortages: An organizational analysis. American Educational Research Journal, 38(3), 499-534. http://dx.doi.org/10.3102/00028312038003499 Ingersoll, R. M. (2012). Beginning Teacher Induction: What the data tell us. Phi Delta Kappan, 93, 47- 51. http://dx.doi.org/10.1177/003172171209300811 Educational Policy Analysis Archives Vol. 23 No. 43 26 Ingersoll, R. M., & May, H. (2012). The magnitude, destinations, and determinants of mathematics and science teacher turnover. Educational Evaluation and Policy Analysis, 34(4), 435-464. http://dx.doi.org/10.3102/0162373712454326 Ingersoll, R. M., & Smith, T. M. (2003). The wrong solution to the teacher shortage. Educational Leadership, 60(8), 30-33. Jackson, K. M. (2012). Influence matters: The link between principal and teacher influence over school policy and teacher turnover. Journal of School Leadership, 22(5), 875-901. Jiang, Y. (2005). The influencing and effective model of early childhood: Teachers' job satisfaction in China. US-China Education Review, 2(11), 65-74. Johnson, S. M., Berg, J. H., & Donaldson, M. L. (2005). Who stays in teaching and why?: A review of the literature on teacher retention. Project on the Next Generation of Teachers, Harvard Graduate School of Education. Johnson, S., Kraft, M. A., & Papay, J. P. (2012). How context matters in high-need schools: The effects of teachers' working conditions on their professional satisfaction and their students' achievement. Teachers College Record, 114(10), 1-39. Koeske, G. F., Kirk, S. A., Koeske, R. D., & Rauktis, M. B. (1994). Measuring the Monday blues: Validation of a job satisfaction scale for the human services. Social Work Research, 18(1), 27-35. Kokkinos, C. M., Panayiotou, G., & Davazoglou, A. M. (2005). Correlates of teacher appraisals of student behaviors. Psychology in the Schools, 42(1), 79-89. http://dx.doi.org/10.1002/pits.20031 Kyriacou, C., & Sutcliffe, J. (1977). Teacher stress: A review. Educational Review, 29, 299-306. http://dx.doi.org/10.1080/0013191770290407 Lam, B., & Yan, H. (2011). Beginning teachers' job satisfaction: The impact of school-based factors. Teacher Development, 15(3), 333-348. http://dx.doi.org/10.1080/13664530.2011.608516 Lambert, R., McCarthy, C., McCarthy, C., Crowe, E., & Fisher, M. (2012). Assessment of teacher demands and resources: Relationship to stress, classroom structural characteristics, job satisfaction, and turnover. In McCarthy C., Lambert, R., & Ullrich, A. (Eds.) International Perspectives on Teacher Stress (pp. 155-174). Charlotte, NC: Information Age Publishing. Lambert, R., McCarthy, C., O’Donnell, M., & Melendes, L. (2007). Teacher stress and Classroom structural characteristics in elementary settings. In G. Gates, Wolverton, M., and Gmelch, W. (Eds.), Emerging thought and research on student, teacher, and administrator stress and coping (pp. 109-131). Charlotte, NC: Information Age Publishing. Lambert, R., McCarthy, C., O’Donnell, M., & Wang, C. (2009). Measuring elementary teacher stress and coping in the classroom: Validity evidence for the Classroom Appraisal of Resources and Demands, Psychology in the Schools, 46(10), 973-988. http://dx.doi.org/10.1002/pits.20438 Lambert, R. & Ullrich, A. (2012). Understanding teacher stress in an age of globalization. In McCarthy C., Lambert, R., & Ullrich, A. (Eds.) International Perspectives on Teacher Stress (pp. 243-248). Charlotte, NC: Information Age Publishing. Lambert, R., Ullrich, A., & McCarthy, C. (2012). Mixed methods study of stress, coping, and burnout among kindergarten and elementary in Germany. In McCarthy C., Lambert, R., & Ullrich, A. (Eds.) International Perspectives on Teacher Stress (pp. 95-120). Charlotte, NC: Information Age Publishing. Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. New York, NY: Springer. Lewis, R., Roache, J., & Romi, S. (2011). Coping styles as mediators of teachers’ classroom management techniques. Research in Education, 85, 53–68. http://dx.doi.org/10.7227/RIE.85.5 Identification of Elementary Teachers’ Risk for Stress 27 Liu, X. S. (2007). The effect of teacher influence at school on first-year teacher attrition: A multilevel analysis of the Schools and Staffing Survey for 1999–2000. Educational Research and Evaluation, 13(1), 1-16. http://dx.doi.org/10.1080/13803610600797615 Liu, X. S., & Ramsey, J. (2008). Teachers’ job satisfaction: Analyses of the teacher follow-up survey in the United States for 2000–2001. Teaching and Teacher Education, 24(5), 1173-1184. http://dx.doi.org/10.1016/j.tate.2006.11.010 McCarthy, C. J., Lambert, R.G., Crowe, R. W., & McCarthy, C. J. (2010) Coping, Stress, and Job Satisfaction as Predictors of Advanced Placement Statistics Teachers’ Intention to Leave the Field. NASSP Bulletin, 94, 306-326. http://dx.doi.org/10.1177/0192636511403262 McCarthy, C. J., Lambert, R. G., O'Donnell, M., & Melendres, L. T. (2009). The relation of elementary teachers' experience, stress, and coping resources to burnout symptoms. The Elementary School Journal, 109(3), 282-300. http://dx.doi.org/10.1086/592308 McCarthy, C., Lambert, C., O’Donnell, M., Villarreal, S., & Melendres, L. (2012). Predictors of elementary teachers’ burnout symptoms: The role of teacher’s personal resources, perceptions of classroom stress, and disruption of teaching. In McCarthy C., Lambert, R., & Ullrich, A. (Eds.) International Perspectives on Teacher Stress (pp. 333-356). Charlotte, NC: Information Age Publishing. McCarthy, C. J., Lambert, R. G., & Reiser, J. (2014). Vocational concerns of elementary teachers: Stress, job satisfaction, and occupational commitment. Journal of Employment Counseling.51(2), 59-74. http://dx.doi.org/10.1002/j.2161-1920.2014.00042.x McCarthy, C. J., Lineback, S., & Lambert, R.G., Allender, M., Reiser, J., & Murphy, S. (2014, April). Elementary Teacher Stress: Associations with Perceptions of Classroom and Professional Variables. In Carson, R. (Chair). Noncognitive Correlates of Stress and Resilience Among Students and Teachers. Symposium conducted at the Annual Meeting of the American Educational Research Association, Philadelphia, PA, April 3 – 7, 2014. Metropolitan Life Insurance, C. (2012). The Metlife survey of the American teacher: Teachers, parents and the economy. Metlife, Inc. Retrieved from https://www.metlife.com/assets/cao/foundation/MetLife-Teacher-Survey-2012.pdf Meyer, I H. (2003). Prejudice, social stress, and mental health in gesbian, Gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129, 674-697. http://dx.doi.org/10.1037/0033-2909.129.5.674 Monk, D. H. (1988). The education production function: Its evolving role in policy analysis. Educational Evaluation and Policy Analysis, 11(1), 31-45. http://dx.doi.org/10.3102/01623737011001031 Moore, K. (2006). Foreword. In G. Gates, M. Wolverton, & W. Gmelch, (Eds.), Emerging thought and research on student, teacher, and administrator stress and coping (pp. 7-10). Charlotte, NC: Information Age Publishing. Moriarty, V., Edmonds, S., Blatchford, P., & Martin, C. (2001). Teaching young children: Perceived satisfaction and stress. Educational Research, 43, 33-46. http://dx.doi.org/10.1080/00131880010021276 Pearson, L. (1998). The prediction of teacher autonomy. Educational Research Quarterly, 22(1), 33-46. Pearson, L., & Hall, B. W. (1993). Initial construct validation of the teaching autonomy scale. Journal Of Educational Research, 86, 172-178. doi:10.1080/00220671.1993.9941155 Pearson, L., & Moomaw, W. (2005). The relationship between teacher autonomy and stress, work satisfaction, empowerment, and professionalism. Educational Research Quarterly, 29(1), 37-53. http://dx.doi.org/10.1080/00220671.1993.9941155 Petty, T., Fitchett, P. G., & O'Connor, K. (2012). Teachers in high-need schools: How do we attract them and keep them? The American Secondary Education Journal, 40(2), 67-88. Educational Policy Analysis Archives Vol. 23 No. 43 28 Price, H. E., & Collett, J. L. (2012). The role of exchange and emotion on commitment: A study of teachers. Social science research, 41(6), 1469-1479. http://dx.doi.org/10.1016/j.ssresearch.2012.05.016 Robertson-Kraft, C., & Duckworth, A. L. (2014). True grit: Trait-leve perserverance and passion for long-term goal predicts effectiveness and retention among novice teachers. Teachers College Record, 116, 1-27. Ronfeldt, M., Loeb, S., & Wyckoff, J. (2013). How teacher turnover harms student achievement. American Educational Research Journal, 50(1), 4-36. http://dx.doi.org/10.3102/0002831212463813 Scherff, L., & Hahs-Vaughn, D.L. (2008). What we know about English language arts teachers: An analysis of the 1999-2000 SASS and 2000-2001 TFS databases. English Education, 40, 174- 200. Sedivy-Benton, A. L., & Boden McGill, C. J. (2012). Significant factors for teachers' intentions to stay or leave the profession: Teacher influence on school, perception of control, and perceived support. National Teacher Education Journal, 5(2), 99-114. Simon, N.S. & Johnson, S.M. (2013). Teacher turnover in high-poverty schools: What we know and can do. Harvard Graduate School of Education: Project on the Next Generation of Teachers. Smylie, M. A., & Denny, J. W. (1990). Teacher leadership: Tensions and ambiguities in organizational perspective. Educational Administration Quarterly, 26(3), 235-259. http://dx.doi.org/10.1177/0013161X90026003003 Spillane, J. P. (2012). Distributed leadership (Vol. 4). San Francisco, CA: John Wiley & Sons. Sutton, R. E., Mudrey-Camino, R., & Knight, C. C. (2009). Teachers’ emotion regulation and classroom management. Theory into Practice, 48(2), 130–137. http://dx.doi.org/10.1080/00405840902776418 Tickle, B. R., Chang, M., & Kim, S. (2011). Administrative support and its mediating effect on US public school teachers. Teaching and Teacher Education: An International Journal Of Research And Studies, 27(2), 342-349. http://dx.doi.org/10.1016/j.tate.2010.09.002 Wheaton, B. (1999). The nature of stressors. In A. F. Horwitz & T. L. Scheid (Eds.), A handbook for the study of mental health: Social contexts, theories, and systems (pp. 176–197). Cambridge, England: Cambridge University Press. York-Barr, J., & Duke, K. (2004). What do we know about teacher leadership? Findings from two decades of scholarship. Review of educational research, 74(3), 255-316. http://dx.doi.org/10.3102/00346543074003255 Zellars, K, Hochwarter, W., & Perrewé, P. (2004). Experiencing job burnout: The roles of positive and negative traits and states. Journal of Applied and Social Psychology, 34, 887-911. http://dx.doi.org/10.1111/j.1559-1816.2004.tb02576.x Identification of Elementary Teachers’ Risk for Stress 29 Appendix A 2kDenotes 1999-2000 only Autonomy Scale Items from SASS Surveys SASS Items Comprising School Influence (no influence = 1; a great deal of influence = 5) Setting performance standards for students in this school2k Establishing curriculum2k Determining the content of in-service professional development programs* Evaluating teachers2k Hiring new full-time teachers2k Setting discipline policy2k Deciding how the school budget will be spent2k SASS Items Comprising Classroom Control (no control = 1, complete control = 5) Selecting textbooks and other instructional materials Selecting content, topics, and skills to be taught Selecting teaching techniques Evaluating and grading students Disciplining students Determining the amount of homework to be assigned Autonomy= Classroom control +School influence (Note: only 2000 SASS) Educational Policy Analysis Archives Vol. 23 No 43 30 Appendix B Demands and Resources Scale from the SASS and the CARD SASS Demands Scale Demands (recoded strongly disagree 1 to strongly agree 4) The level of student misbehavior in this school interferes with my teaching Routine duties and paperwork interfere with my job of teaching The amount of student tardiness and class cutting in this school interferes with my teaching Demands (serious problem 1 to not a problem 4) Student tardiness Student absenteeism Teacher absenteeism Students cutting class Physical conflicts among students2k Robbery or theft2k Vandalism of school property2k Student pregnancy2k Student use of alcohol2k Student drug abuse2k Student possession of weapons2k Student disrespect for teachers2k Students dropping out Student apathy Lack of parental involvement Poverty Students come to school unprepared to learn Poor student health 2k denotes 1999/2000 only CARD Demands Scale How Demanding Are the Following? (rated not demanding 1 to extremely demanding 5) Number of children in the classroom Children with limited English skills Children from diverse cultural backgrounds Range of developmental levels Number of children performing below grade level Children with learning disabilities Children with physical disabilities Gifted and talented children Homeless or transient children Children who do not follow directions Children with problem behaviors Children who require more time and energy than most children Number of program/administrative disruptions to the daily schedule Identification of Elementary Teachers’ Risk for Stress 31 CARD Demands Scale (Cont’d) Amount of physical classroom space Classroom environment conditions Availability of instructional resources Availability of instructional materials Availability of instructional supplies Availability of instructional technology Instructional resources and materials that are outdated Time and effort working with protégé teachers Meetings you are required to attend Time spent performing non-teaching related duties Parent conferences and contacts Formal testing and objective assessments Portfolios, performance assessments, or teacher ratings of children's achievement Grading student work Preparing lessons Setting up classroom for instructional activities Preparing classroom materials Externally imposed changes to the expectations for your job performance Overall, how demanding is your classroom Disruptive children & children with problem behaviors Paperwork requirements Children with poor attendance SASS Resources Scale Resources (recoded strongly disagree 1 to strongly agree 4) The principal lets staff members know what is expected of them2k The school administration's behavior toward the staff is supportive and encouraging I am satisfied with my teaching salary I receive a greater deal of support from parents for the work I do Necessary materials such as textbooks, supplies, and copy machines are available as needed by the staff My principal enforces school rules for student conduct and backs me up when I need it The principal talks with me frequently about my instructional practices2k Rules for student behavior are consistently enforced by teachers in this school, even for students who are not in their classes Most of my colleagues share my beliefs and values about what the central mission of the school should be The principal knows what kind of school he/she wants and has communicated it to the staff There is a great deal of cooperative effort among the staff members In this school, staff members are recognized for a job well done I am given the support I need to teach students with special needs I make a conscious effort to coordinate the content of my courses with that of other teachers2k I plan with the library media specialist/librarian for the integration of library media services into my teaching2k 2k denotes 1999/2000 only Educational Policy Analysis Archives Vol. 23 No 43 32 CARD Resources Scale How helpful are the following resources? (rated very unhelpful 1 to very helpful 5) Aides/Assistants Parent volunteers in the classroom Parent support of school learning activities Parent support of learning activities at home adult mentors from the community Support personnel for children with physical disabilities Support personnel for gift or talented children Support personnel for children with limited English skills Support personnel for children from diverse cultural backgrounds Support personnel for children with problem behaviors Support personnel for children performing below grade level Support personnel for computers and instructional technology Counselors or family services workers Special area teachers Mentor teachers Staff development opportunities Materials for children with learning disabilities Materials for gift or talented children Materials for children with limited English skills Materials for children from diverse cultural backgrounds Materials for children with problem behaviors Materials for children performing below grade level Instructional materials Instructional supplies provided by your school or program Overall, how would you rate the resources available to help you with the demands of your classroom? Administrators at your school Instructional resources provided by your school or program Support personnel for children with learning disabilities Identification of Elementary Teachers’ Risk for Stress 33 About the Authors Richard G. Lambert University of North Carolina at Charlotte rglamber@uncc.edu Dr. Richard Lambert is a Professor of Educational Research at the University of North Carolina at Charlotte. He specializes in applied statistics, teacher stress and coping, and assessment for young children. Christopher McCarthy University of Texas at Austin cjmccarthy@austin.utexas.edu Christopher J. McCarthy is a Professor in the Department of Educational Psychology at the University of Texas at Austin. He studies stress and coping, particularly in educational contexts. Paul G. Fitchett University of North Carolina at Charlotte Paul.Fitchett@uncc.edu Paul G. Fitchett is an Associate Professor in the Department of Middle, Secondary, and K12 Education at the University of North Carolina at Charlotte. He studies the intersections between teacher working conditions, student learning outcomes, and educational policy. Sally Lineback University of Texas at Austin sallylineback@gmail.com Sally Lineback is a doctoral student in Counseling Psychology at the University of Texas at Austin. She is a former teacher and currently studies teacher stress and coping, with a particular interest in gay and lesbian teachers’ experiences with stress. Jenson Reiser University of Texas at Austin jenson.reiser@gmail.com Jenson Reiser is a doctoral candidate in Counseling Psychology at the University of Texas at Austin. Her research interests include stress and coping in educational settings; specifically, the research and development of in-school interventions to help teachers reduce and manage stress. education policy analysis archives Volume 23 Number 43 April 13th, 2015 ISSN 1068-2341 Readers are free to copy, display, and distribute this article, as long as the work is attributed to the author(s) and Education Policy Analysis Archives, it is distributed for non- commercial purposes only, and no alteration or transformation is made in the work. More Educational Policy Analysis Archives Vol. 23 No 43 34 details of this Creative Commons license are available at http://creativecommons.org/licenses/by-nc-sa/3.0/. All other uses must be approved by the author(s) or EPAA. EPAA is published by the Mary Lou Fulton Institute and Graduate School of Education at Arizona State University Articles are indexed in CIRC (Clasificación Integrada de Revistas Científicas, Spain), DIALNET (Spain), Directory of Open Access Journals, EBSCO Education Research Complete, ERIC, Education Full Text (H.W. Wilson), QUALIS A2 (Brazil), SCImago Journal Rank; SCOPUS, SOCOLAR (China). Please contribute commentaries at http://epaa.info/wordpress/ and send errata notes to Gustavo E. Fischman fischman@asu.edu Join EPAA’s Facebook community at https://www.facebook.com/EPAAAAPE and Twitter feed @epaa_aape. Identification of Elementary Teachers’ Risk for Stress 35 education policy analysis archives editorial board Editor Gustavo E. Fischman (Arizona State University) Associate Editors: Audrey Amrein-Beardsley (Arizona State University), Kevin Kinser (University of Albany) Jeanne M. 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Wiley Center for Applied Linguistics Craig Howley Ohio University John Willinsky Stanford University Steve Klees University of Maryland Kyo Yamashiro Los Angeles Education Research Institute Educational Policy Analysis Archives Vol. 23 No 43 36 archivos analíticos de políticas educativas consejo editorial Editores: Gustavo E. Fischman (Arizona State University), Jason Beech (Universidad de San Andrés), Alejandro Canales (UNAM) y Jesús Romero Morante (Universidad de Cantabria) Armando Alcántara Santuario IISUE, UNAM México Fanni Muñoz Pontificia Universidad Católica de Perú, Claudio Almonacid University of Santiago, Chile Imanol Ordorika Instituto de Investigaciones Economicas – UNAM, México Pilar Arnaiz Sánchez Universidad de Murcia, España Maria Cristina Parra Sandoval Universidad de Zulia, Venezuela Xavier Besalú Costa Universitat de Girona, España Miguel A. 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Gandin (Universidade Federal do Rio Grande do Sul) Dalila Andrade de Oliveira Universidade Federal de Minas Gerais, Brasil Jefferson Mainardes Universidade Estadual de Ponta Grossa, Brasil Paulo Carrano Universidade Federal Fluminense, Brasil Luciano Mendes de Faria Filho Universidade Federal de Minas Gerais, Brasil Alicia Maria Catalano de Bonamino Pontificia Universidade Católica-Rio, Brasil Lia Raquel Moreira Oliveira Universidade do Minho, Portugal Fabiana de Amorim Marcello Universidade Luterana do Brasil, Canoas, Brasil Belmira Oliveira Bueno Universidade de São Paulo, Brasil Alexandre Fernandez Vaz Universidade Federal de Santa Catarina, Brasil António Teodoro Universidade Lusófona, Portugal Gaudêncio Frigotto Universidade do Estado do Rio de Janeiro, Brasil Pia L. Wong California State University Sacramento, U.S.A Alfredo M Gomes Universidade Federal de Pernambuco, Brasil Sandra Regina Sales Universidade Federal Rural do Rio de Janeiro, Brasil Petronilha Beatriz Gonçalves e Silva Universidade Federal de São Carlos, Brasil Elba Siqueira Sá Barreto Fundação Carlos Chagas, Brasil Nadja Herman Pontificia Universidade Católica – Rio Grande do Sul, Brasil Manuela Terrasêca Universidade do Porto, Portugal José Machado Pais Instituto de Ciências Sociais da Universidade de Lisboa, Portugal Robert Verhine Universidade Federal da Bahia, Brasil Wenceslao Machado de Oliveira Jr. Universidade Estadual de Campinas, Brasil Antônio A. S. Zuin University of York